pd.date_range()
date_range creates a regular sequence of dates for building indexes and test data.
In this page:
Syntax
pd.date_range(start="start_date", periods=n, freq="D")
pd.date_range(start="start_date", end="end_date", freq="W")pd.date_range()
pd.date_range(start, end or periods, freq) generates timestamps at a chosen frequency such as "D" for days or "W" for weeks. Use either end or periods, not both. bdate_range skips weekends.
Note:
pd.bdate_range gives business days only.
Example: pd.date_range()
import pandas as pd
print(pd.date_range("2024-01-01", "2024-01-05"))
print(pd.date_range("2024-01-01", periods=3, freq="W"))
print(pd.bdate_range("2024-01-05", periods=3))
# Output:
# DatetimeIndex(['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04',
# '2024-01-05'],
# dtype='datetime64[ns]', freq='D')
# DatetimeIndex(['2024-01-07', '2024-01-14', '2024-01-21'], dtype='datetime64[ns]', freq='W-SUN')
# DatetimeIndex(['2024-01-05', '2024-01-08', '2024-01-09'], dtype='datetime64[ns]', freq='B')Related Topics
Common Mistakes
- Giving both end and periods
- Misjudging inclusive ends
- Using an unknown frequency alias
Chapter Summary
- date_range builds regular timestamps
- freq sets the step
- Use end or periods
- bdate_range skips weekends
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