To create a PeriodIndex, use the pandas.PeriodIndex() method. Get the days of the month using the PeriodIndex.daysinmonth property
At first, import the required libraries −
import pandas as pd
Create a PeriodIndex object. PeriodIndex is an immutable ndarray holding ordinal values indicating regular periods in time. We have set the frequency using the "freq" parameter −
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 object −
print("PeriodIndex...\n", periodIndex)
Display days in the specific month from the PeriodIndex object −
print("\nDays of the specific month from the PeriodIndex...\n", periodIndex.daysinmonth)
Example
Following is the code −
import pandas as pd # Create a PeriodIndex object # PeriodIndex is an immutable ndarray holding ordinal values indicating regular periods in time # We have set the frequency using the "freq" parameter 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 object print("PeriodIndex...\n", periodIndex) # Display PeriodIndex frequency print("\nPeriodIndex frequency...\n", periodIndex.freq) # Display the month number i.e. 1 = January, 2 = February ... 12 = December print("\nMonth number...\n", periodIndex.month) # Display days in the specific month from the PeriodIndex object print("\nDays of the specific month from the PeriodIndex...\n", periodIndex.daysinmonth)
Output
This will produce the following code −
PeriodIndex... PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20', '2021-09-15', '2022-03-12', '2023-06-18'], dtype='period[D]') PeriodIndex frequency... <Day> Month number... Int64Index([7, 10, 11, 9, 3, 6], dtype='int64') Days of the specific month from the PeriodIndex... Int64Index([31, 31, 30, 30, 31, 30], dtype='int64')