Python Pandas - Create a PeriodIndex and get the days of the period

To create a PeriodIndex, use the pandas.PeriodIndex() method. Get the days of the period using the PeriodIndex.day property.

What is PeriodIndex?

A PeriodIndex is an immutable ndarray holding ordinal values indicating regular periods in time. It's useful for representing time periods with specific frequencies like days, months, or years.

Creating a PeriodIndex

First, import pandas and create a PeriodIndex object with daily frequency ?

import pandas as pd

# Create a PeriodIndex object with daily frequency
periodIndex = pd.PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20',
                             '2021-09-15', '2022-03-12', '2023-06-18'], freq="D")

print("PeriodIndex...")
print(periodIndex)

PeriodIndex...
PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20', '2021-09-15', '2022-03-12', '2023-06-18'], dtype='period[D]')

Getting Days from PeriodIndex

Use the .day property to extract the day component from each period ?

import pandas as pd

periodIndex = pd.PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20',
                             '2021-09-15', '2022-03-12', '2023-06-18'], freq="D")

# Display PeriodIndex frequency
print("PeriodIndex frequency:")
print(periodIndex.freq)

# Extract day component from each period
print("\nThe day numbers from the PeriodIndex:")
print(periodIndex.day)

PeriodIndex frequency:
<Day>

The day numbers from the PeriodIndex:
Index([25, 30, 20, 15, 12, 18], dtype='int64')

Understanding the Results

The day property returns an Index containing the day component of each period. For example, '2018-07-25' returns 25, '2019-10-30' returns 30, and so on.

Conclusion

Use pd.PeriodIndex() to create time period objects and the .day property to extract day components. This is useful for time-based data analysis and filtering operations.