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Pandas | period_range method

Pandas
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General Functions
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
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Pandas period_range(~) method returns a PeriodIndex with fixed frequency. A Period represents a specific time span or a duration. PeriodIndex is most often used as the index of a DataFrame.

Parameters

1. startlink | string or period-like | optional

The lower bound (inclusive) of the range. By default, start=None.

2. endlink | string or period-like | optional

The upper bound (inclusive) of the range. By default, end=None.

3. periodslink | int | optional

The desired number of periods. By default, periods=None.

WARNING

Out of the above three parameters, exactly two must be specified - no less, no more.

4. freqlink | string or DateOffset | optional

The step-size (interval size) between a pair of consecutive dates. By default, freq="D" (step-size of a day).

5. namelink | string | optional

The name to assign to the resulting PeriodIndex. By default, name=None.

Return Value

A PeriodIndex.

Examples

Basic usage

To create a sequence of dates from 2020-12-25 to 2020-12-27 (both inclusive):

pd.period_range(start="2020-12-25", end="2020-12-27")
PeriodIndex(['2020-12-25', '2020-12-26', '2020-12-27'], dtype='period[D]', freq='D')

The default step-size (the frequency) is a day, so this is why we see freq="D" in the output.

Specifying the period

To create a sequence of dates of length 3 from 2020-12-25 (inclusive):

pd.period_range(start="2020-12-25", periods=3)
PeriodIndex(['2020-12-25', '2020-12-26', '2020-12-27'], dtype='period[D]', freq='D')

Specifying the frequency

In Pandas, frequency can be thought of as the length of a period. The default frequency is 1 day.

Let's try a 2-day interval:

pd.period_range(start="2020-12-25", periods=3, freq="2D")
PeriodIndex(['2020-12-25', '2020-12-27', '2020-12-29'], dtype='period[2D]', freq='2D')

Notice how we have our specified freq="2D" encoded into the resulting PeriodIndex.

Let's now try a 1-month interval:

pd.period_range(start="2020-12-25", periods=3, freq="M")
PeriodIndex(['2020-12', '2021-01', '2021-02'], dtype='period[M]', freq='M')

Note that we could have also used freq="1M" for the same effect.

Specifying a name

To give a name to the resulting PeriodIndex:

pd.period_range(start="2020-12-25", periods=3, name="My Dates")
PeriodIndex(['2020-12-25', '2020-12-26', '2020-12-27'], dtype='period[D]', name='My Dates', freq='D')

Notice how we have name="My Dates" encoded into the PeriodIndex.

Using PeriodIndex as the index of a DataFrame

To initialise a DataFrame with PeriodIndex:

idx = pd.period_range(start="2020-12-25", periods=3)
pd.DataFrame({"A":["a","b","c"]}, index=idx)
A
2020-12-25 a
2020-12-26 b
2020-12-27 c
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Published by Isshin Inada
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