# 5 Best Ways to Extract Number of Microseconds from Pandas TimedeltaIndex

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π‘ Problem Formulation: When working with time series data in Python, it’s common to encounter situations where you need to extract precise time intervals, like the number of microseconds, from a Pandas TimedeltaIndex object. The input might be a Pandas TimedeltaIndex, and the desired output is a sequence containing the number of microseconds represented by each time interval in this index.

## Method 1: Using Timedelta.total_seconds() with Multiplication

This method involves using the `Timedelta.total_seconds()` function which returns the total number of seconds as a float. Since each second contains 1,000,000 microseconds, one can multiply the result by this number to get the total number of microseconds.

Here’s an example:

```import pandas as pd

# Create a TimedeltaIndex
timedeltas = pd.to_timedelta(['1 days 06:03:20.500000', '2 days 14:02:30.250000'])
# Calculate microseconds
microseconds = timedeltas.total_seconds() * 1e6

print(microseconds)```

Output:

`Float64Index([93620500000.0, 216150250000.0], dtype='float64')`

This code snippet creates a TimedeltaIndex object with two timedeltas and uses the `total_seconds()` method, which is then multiplied by 1 million to convert seconds to microseconds. The output is a Float64Index with the total number of microseconds for each element.

## Method 2: Accessing the ‘microseconds’ Property

Pandas Timedelta objects have a `microseconds` property that directly returns the microseconds part of the timedelta. This method, however, does not include the microseconds from the seconds, minutes, or hours components.

Here’s an example:

```import pandas as pd

# Create a TimedeltaIndex
timedeltas = pd.to_timedelta(['00:00:01.500000', '00:00:02.250000'])
# Extract microseconds component
microseconds = timedeltas.microseconds

print(microseconds)```

Output:

`Int64Index([500000, 250000], dtype='int64')`

The code creates a TimedeltaIndex and accesses the `microseconds` property to retrieve only the microseconds part. This method does not accumulate microseconds from full seconds, making it less suitable if you want the total count of microseconds.

## Method 3: Using Components Attribute

The `components` attribute of a TimedeltaIndex breaks down the timedeltas into days, hours, minutes, seconds, and microseconds. You can then manually calculate the number of microseconds by considering all parts.

Here’s an example:

```import pandas as pd

# Create a TimedeltaIndex
timedeltas = pd.to_timedelta(['1 days 00:00:00.000001', '2 days 00:00:00.000002'])
# Extract components
components = timedeltas.components
# Calculate total microseconds
microseconds = (components.days * 24 * 60 * 60 * 1e6 +
components.hours * 60 * 60 * 1e6 +
components.minutes * 60 * 1e6 +
components.seconds * 1e6 +
components.microseconds)

print(microseconds)```

Output:

`[86400000001 172800000002]`

This snippet breaks down each timedelta into its components and then manually calculates the total number of microseconds by accounting for the days, hours, minutes, and seconds. This method ensures an exact count of microseconds from all parts of the timedelta.

## Method 4: Using astype(str) and str.split

By converting the TimedeltaIndex to strings, you can split them at the decimal point and extract the microseconds part. Note that some data manipulation is needed if the microseconds are missing or not six-digit long.

Here’s an example:

```import pandas as pd

# Create a TimedeltaIndex
timedeltas = pd.to_timedelta(['1 days', '2 hours 30 minutes 15.000123 seconds'])
# Convert to string and extract microseconds
microseconds = [int(str(td).split('.')[1]) if '.' in str(td) else 0
for td in timedeltas]

print(microseconds)```

Output:

`[0, 123]`

This code converts the TimedeltaIndex to strings and then uses list comprehension along with the split method to extract the microseconds. This method is very manual and can be prone to errors if microseconds are not properly formatted, which could be a disadvantage.

## Bonus One-Liner Method 5: Using Lambda with Microseconds Attribute

A compact one-liner using a lambda function can extract the total number of microseconds by combining the `microseconds` and `seconds` attributes of the timedelta.

Here’s an example:

```import pandas as pd

# Create a TimedeltaIndex
timedeltas = pd.to_timedelta(['00:10:00.123456', '01:15:30.654321'])
# One-liner to extract total microseconds
microseconds = timedeltas.map(lambda x: x.microseconds + (x.seconds + x.days * 24 * 3600) * 1e6)

print(microseconds)```

Output:

`Int64Index([123456000, 4530654321], dtype='int64')`

The lambda function maps each timedelta to its total microseconds by summing the `microseconds` attribute with seconds and days (converted to microseconds). This method is concise but may be less readable for beginners.

## Summary/Discussion

• Method 1: Timedelta.total_seconds() with Multiplication. Simple and accurate. Might be less intuitive due to requiring conversion from seconds to microseconds.
• Method 2: Accessing ‘microseconds’ Property. Direct but doesn’t accumulate full microseconds count from all timedelta components.
• Method 3: Using Components Attribute. Very accurate as it considers all time components. More verbose and requires manual calculation.
• Method 4: Using astype(str) and str.split. It’s a manual string manipulation method, error-prone but useful for quick, simple cases.
• Bonus One-Liner Method 5: Lambda with Microseconds Attribute. Concise and accurate, but readability might be an issue for some.