**π‘ Problem Formulation:** When working with time series data in pandas, sometimes data indexed by time deltas need to be rounded to the nearest microsecond for uniformity or aggregation purposes. Below, we detail five methods of achieving this, starting with a TimeDeltaIndex like `TimedeltaIndex(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789'], dtype='timedelta64[ns]')`

with a desired output resembling `TimedeltaIndex(['00:00:00.000000', '00:00:00.000000', '00:00:00.001000'], dtype='timedelta64[ns]')`

.

## Method 1: Using `TimedeltaIndex.round()`

This method involves using the `round()`

function provided by the pandas `TimedeltaIndex`

class to round to the nearest specified frequency. Itβs directly supported and easy to use, making it an ideal starting point for most rounding operations involving pandas timedeltas.

Here’s an example:

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

This one-liner utilizes a lambda function to apply `round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.map(lambda t: t.round('us')) print(rounded_td_index)

Output:

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

This one-liner utilizes a lambda function to apply `round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

TimedeltaIndex(['0 days 00:00:01', '0 days 00:00:01', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

Using pandas `ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

A flexible and concise way to round timedeltas is to use a lambda function alongside the `round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.map(lambda t: t.round('us')) print(rounded_td_index)

Output:

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

This one-liner utilizes a lambda function to apply `round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) ceiling_td_index = td_index.ceil('us') print(ceiling_td_index)

Output:

TimedeltaIndex(['0 days 00:00:01', '0 days 00:00:01', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

Using pandas `ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

A flexible and concise way to round timedeltas is to use a lambda function alongside the `round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.map(lambda t: t.round('us')) print(rounded_td_index)

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:00'], dtype='timedelta64[ns]', freq=None)

The `floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

In contrast to flooring, sometimes an operation that always rounds up is needed. The `ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) ceiling_td_index = td_index.ceil('us') print(ceiling_td_index)

Output:

TimedeltaIndex(['0 days 00:00:01', '0 days 00:00:01', '0 days 00:00:01'], dtype='timedelta64[ns]', freq=None)

Using pandas `ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

A flexible and concise way to round timedeltas is to use a lambda function alongside the `round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) floored_td_index = td_index.floor('us') print(floored_td_index)

Output:

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:00'], dtype='timedelta64[ns]', freq=None)

The `floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

In contrast to flooring, sometimes an operation that always rounds up is needed. The `ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) ceiling_td_index = td_index.ceil('us') print(ceiling_td_index)

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:00', '0 days 00:00:00'], dtype='timedelta64[ns]', freq=None)

After initiating a `TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

Similar to rounding, sometimes a consistent floor operation is required. Pandas offers the `floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) floored_td_index = td_index.floor('us') print(floored_td_index)

Output:

The `floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

In contrast to flooring, sometimes an operation that always rounds up is needed. The `ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd import numpy as np td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = pd.to_timedelta(np.around(td_index.microseconds, decimals=0)) print(rounded_td_index)

Output:

After initiating a `TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

Similar to rounding, sometimes a consistent floor operation is required. Pandas offers the `floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) floored_td_index = td_index.floor('us') print(floored_td_index)

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

This code snippet demonstrates how to round a `TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

The numpy library offers a generic rounding method `around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

import pandas as pd import numpy as np td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = pd.to_timedelta(np.around(td_index.microseconds, decimals=0)) print(rounded_td_index)

Output:

After initiating a `TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

Similar to rounding, sometimes a consistent floor operation is required. Pandas offers the `floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.round('us') print(rounded_td_index)

Output:

This code snippet demonstrates how to round a `TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

The numpy library offers a generic rounding method `around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

import pandas as pd import numpy as np td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = pd.to_timedelta(np.around(td_index.microseconds, decimals=0)) print(rounded_td_index)

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.round('us') print(rounded_td_index)

Output:

This code snippet demonstrates how to round a `TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

The numpy library offers a generic rounding method `around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

import pandas as pd td_index = pd.to_timedelta(['00:00:00.000123', '00:00:00.000456', '00:00:00.000789']) rounded_td_index = td_index.round('us') print(rounded_td_index)

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Output:

`TimedeltaIndex`

to the nearest microsecond using `round()`

. After converting a list of string representations to a `TimedeltaIndex`

, the `round()`

function is called with ‘us’ as the frequency to indicate the microsecond level.

## Method 2: Using `numpy.around()`

`around()`

which allows rounding of arrays to a given number of decimals. This can be applied to the total number of microseconds in our `TimedeltaIndex`

.

Here’s an example:

Output:

`TimedeltaIndex`

, this code uses `numpy.around()`

to round the microseconds to the nearest whole number. The result is passed to `pd.to_timedelta()`

to recreate the `TimedeltaIndex`

.

## Method 3: Flooring with `TimedeltaIndex.floor()`

`floor()`

method to always round down to the nearest specified frequency.

Here’s an example:

Output:

`floor()`

method works like `round()`

but ensures that the result is the largest previous duration mark in microseconds, effectively rounding down.

## Method 4: Ceiling with `TimedeltaIndex.ceil()`

`ceil()`

method provided by pandas rounds a timedelta up to the nearest given frequency.

Here’s an example:

Output:

`ceil()`

function rounds each timedelta in the index up to the nearest microsecond frequency.

## Bonus One-Liner Method 5: Lambda Function with `round()`

`round()`

method. This can be handy for customized rounding behavior in more complex scenarios.

Here’s an example:

Output:

`round()`

directly to each element of the `TimedeltaIndex`

. Here, each timedelta is individually rounded to the microseconds frequency.

## Summary/Discussion

**Method 1:**Using`TimedeltaIndex.round()`

. Straightforward and concise. Preferred for standard rounding.**Method 2:**Using`numpy.around()`

. Offers flexibility and useful for handling complex rounding operations across multiple array elements.**Method 3:**Flooring with`TimedeltaIndex.floor()`

. Reliable for always rounding down. May not be suitable if upward rounding is sometimes required.**Method 4:**Ceiling with`TimedeltaIndex.ceil()`

. Good for always rounding up. The opposite of floor β may not be suitable for always rounding down scenarios.**Method 5:**Lambda Function with`round()`

. Offers maximum customization. Requires a bit more code than the built-in functions.

Emily Rosemary Collins is a tech enthusiast with a strong background in computer science, always staying up-to-date with the latest trends and innovations. Apart from her love for technology, Emily enjoys exploring the great outdoors, participating in local community events, and dedicating her free time to painting and photography. Her interests and passion for personal growth make her an engaging conversationalist and a reliable source of knowledge in the ever-evolving world of technology.