# Converting Frequency from Seconds to Minutes in Python Pandas Period Objects

Rate this post

π‘ Problem Formulation: When working with time series data in Pandas, it is often necessary to change the frequency of period objects. For instance, if you have a Period object representing a time span in seconds, you might want to convert it to a minutely frequency for better alignment with your data analysis goals. Let’s say you start with a Period object of ‘2023-01-01 00:00:05’ (YYYY-MM-DD HH:MM:SS) in seconds and you need it to be ‘2023-01-01 00:01’ in minutes.

## Method 1: Using the `asfreq()` Method

This method leverages the `asfreq()` function of a Pandas Period object to resample the frequency from seconds to minutes. The function is straightforward and explicitly designed for frequency conversion, making it an ideal choice when you need precise manipulation over the Period object’s frequency specification.

Here’s an example:

```import pandas as pd

# Create a period at second frequency
second_freq = pd.Period('2023-01-01 00:00:05', freq='S')

# Convert to minute frequency
minute_freq = second_freq.asfreq('T')

print(minute_freq)```

Output:

`2023-01-01 00:01`

In this snippet, `asfreq('T')` is used to convert a period from second (‘S’) to minute (‘T’) frequency. This method is simple and clear, and it is particularly useful when dealing with individual Period objects.

## Method 2: Using the `Period` Constructor with Rounding

Another approach involves reconstructing the Period object with a new frequency. The constructor method allows specifying the frequency directly, and when used in conjunction with date/time rounding, it can effectively switch the frequency from seconds to minutes.

Here’s an example:

```import pandas as pd
from pandas.tseries.frequencies import to_offset

# Original period in seconds
original_period = pd.Period('2023-01-01 00:00:05', freq='S')

# Round the time downwards and create a new period with minute frequency
rounded_time = original_period.to_timestamp().floor('T')
new_period = pd.Period(rounded_time, freq='T')

print(new_period)```

Output:

`2023-01-01 00:00`

This code starts by converting the Period object to a Timestamp, then rounding it down to the nearest minute using `floor('T')`. A new Period object is created with the rounded time and minute frequency. Note that this approach rounds down to the start of the minute.

## Method 3: Converting to `Timestamp`, then Back to `Period`

Occasionally, it may be advantageous to work with a Timestamp rather than a Period object for certain operations. This method allows for such flexibility. Upon converting a Period to a Timestamp, the frequency can be changed straightforwardly, then converted back to a Period.

Here’s an example:

```import pandas as pd

# Period object in seconds
period_sec = pd.Period('2023-01-01 00:00:05', freq='S')

# Convert to timestamp and then to a period with minute frequency
timestamp = period_sec.to_timestamp()
period_min = pd.Period(timestamp, freq='T')

print(period_min)```

Output:

`2023-01-01 00:00`

The conversion to `Timestamp` is seamless, and once in this form, frequency conversion is implicitly handled when creating a new Period object. This method gives a rounded-down result, similar to the previous method.

## Method 4: Using Time Offsets

Time offsets in Pandas are powerful for adjusting time periods. With them, you can create a new Period object by specifying an offset, such as a minute, to the current Period object’s start or end time.

Here’s an example:

```import pandas as pd

# Original period
orig_period = pd.Period('2023-01-01 00:00:05', freq='S')

# Convert to the start of the period's minute
start_of_minute = orig_period - pd.tseries.offsets.Second(orig_period.second)

print(start_of_minute)```

Output:

`2023-01-01 00:00`

By subtracting a Second offset equal to the number of seconds in the original period, we align the period with the start of the minute. This method offers a manual approach for finer-grained time manipulation.

## Bonus One-Liner Method 5: Using `replace()` on Timestamp

If you’re looking for the shortest possible solution, the `replace()` method on a Timestamp can swiftly zero out the seconds, effectively converting the frequency to minutely without having to explicitly create a new Period object.

Here’s an example:

```import pandas as pd

# Create the timestamp from the period
timestamp = pd.Period('2023-01-01 00:00:05', freq='S').to_timestamp()

# Zero out the seconds
minute_timestamp = timestamp.replace(second=0)

print(minute_timestamp)```

Output:

`2023-01-01 00:00:00`

This code uses the `replace()` function to reset the seconds to zero. The resulting timestamp represents the start of the minute the original period belonged to. Keep in mind that this produces a Timestamp, not a Period.

## Summary/Discussion

• Method 1: `asfreq()`. Straightforward frequency conversion. No rounding needed. Best for simple use cases.
• Method 2: Constructor with Rounding. Flexible with rounding options. Rounds down to the nearest minute, which might not be desirable in all cases.
• Method 3: Convert to `Timestamp`. Offers intermediate conversion to Timestamp, which could be useful in complex time manipulations. Implicit rounding.
• Method 4: Time Offsets. Allows for manual adjustments and can be tailored for different rounding behaviors. Slightly more complex.
• Bonus Method 5: `replace()` on Timestamp. Quick and easy, but does not return a Period object. It’s a compact one-liner solution.