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Pandas can be used to create a date range by using the date_range() function. This function takes start date, end date, and frequency parameters, which allows you to specify the starting date, end date, and size of the date range. Additionally, you can also specify the time zone that should be used when creating the date range. This function returns a DatetimeIndex object that can be used for data analysis and manipulation.
You can use the pandas.date_range() function to create a date range in pandas.
This function uses the following basic syntax:
pandas.date_range(start, end, periods, freq, …)
where:
- start: The start date
- end: The end date
- periods: The number of periods to generate
- freq: The frequency to use (refer to for frequency aliases)
The following examples show how to use this function in practice.
Example 1: Create Date Range with Individual Days
The following code shows how to create a date range composed of individual days with a specific start and end date:
import pandas as pd #create 10-day date range pd.date_range(start='1/1/2020', end='1/10/2020') DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04', '2020-01-05', '2020-01-06', '2020-01-07', '2020-01-08', '2020-01-09', '2020-01-10'], dtype='datetime64[ns]', freq='D')
The result is a list of 10 days that range from the specified start date to the specified end date.
Example 2: Create Date Range with Specific Number of Periods
The following code shows how to create a date range that has a specific number of equally-spaced periods between a certain start and end date:
import pandas as pd #create 10-day date range with 3 equally-spaced periods pd.date_range(start='1/1/2020', end='1/10/2020', periods=3) DatetimeIndex(['2020-01-01 00:00:00', '2020-01-05 12:00:00', '2020-01-10 00:00:00'], dtype='datetime64[ns]', freq=None)
The result is a list of 3 equally-spaced days that range from the specified start date to the specified end date.
Example 3: Create Date Range with Specific Frequency
The following code shows how to create a date range that starts on a specific date and has a frequency of six month start dates:
import pandas as pd #create date range with six month start dates pd.date_range(start='1/1/2020', freq='MS', periods=6) DatetimeIndex(['2020-01-01', '2020-02-01', '2020-03-01', '2020-04-01', '2020-05-01', '2020-06-01'], dtype='datetime64[ns]', freq='MS')
The following code shows how to create a date range that starts on a specific date and has a yearly frequency:
import pandas as pd #create date range with six consecutive years pd.date_range(start='1/1/2020', freq='YS', periods=6) DatetimeIndex(['2020-01-01', '2021-01-01', '2022-01-01', '2023-01-01', '2024-01-01', '2025-01-01'], dtype='datetime64[ns]', freq='AS-JAN')
The result is a list of six dates that are each one year apart.
Note: You can find the complete online documentation for the pd.date_range() function .
The following tutorials explain how to perform other common operations with dates in pandas: