DataFrame.period_range() to generate fixed frequency periodindex in Pandas

Pandas date & time Pandas

Generate Periodindex of fixed frequency.

Options
start Start of the generating period.
end End of the generating period.
periods number of periods to generate.

Note that two of the above ( start, end , periods ) options has to be used.

freq Frequency is 'D' by default. We can specify to others.

Examples

import pandas as pd 
pd.period_range(start='4/1/2020', end='12/31/2020',freq='M')

Output , Here frequency is Months

PeriodIndex(['2020-04', '2020-05', '2020-06', '2020-07', '2020-08', '2020-09',
             '2020-10', '2020-11', '2020-12'],
            dtype='period[M]', freq='M')

Q : Quarter end frequency

pd.period_range(start='4/1/2020', end='12/31/2020',freq='Q')

Output

PeriodIndex(['2020Q2', '2020Q3', '2020Q4'], dtype='period[Q-DEC]', freq='Q-DEC')

Weekly frequency

pd.period_range(start='4/1/2020', end='4/30/2020',freq='W')

Output

PeriodIndex(['2020-03-30/2020-04-05', '2020-04-06/2020-04-12',
             '2020-04-13/2020-04-19', '2020-04-20/2020-04-26',
             '2020-04-27/2020-05-03'],
            dtype='period[W-SUN]', freq='W-SUN')

We used start and end options in above code. Similarly we can use other options.

Business Day

pd.period_range(start='4/1/2020', end='4/30/2020',freq='B')

Output

PeriodIndex(['2020-04-01', '2020-04-02', '2020-04-03', '2020-04-06',
             '2020-04-07', '2020-04-08', '2020-04-09', '2020-04-10',
             '2020-04-13', '2020-04-14', '2020-04-15', '2020-04-16',
             '2020-04-17', '2020-04-20', '2020-04-21', '2020-04-22',
             '2020-04-23', '2020-04-24', '2020-04-27', '2020-04-28',
             '2020-04-29', '2020-04-30'],
            dtype='period[B]', freq='B')

periods

We can specify integer values like periods=3, this is optional.

import pandas as pd 
pd.period_range(start='4/20/2020',periods=3,freq='M')

Output

PeriodIndex(['2020-04', '2020-05', '2020-06'], dtype='period[M]', freq='M')

name

We can give name of to the resulting DataFrame.

Practice this exercise to understand how to use date and time in Pandas DataFrame.
Exercise3 on Date and time

Pandas date & time to_datetime() date_range() strftime()

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