Pandas
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Adding new column containing the difference between two date columnsCombining columns containing date and timeCombining columns of years, months and daysConverting a column of strings to datetimeConverting dates to stringsConverting datetime column to date and time columnsConverting DatetimeIndex to Series of datetimeConverting index to datetimeConverting UNIX timestamp to datetimeCreating a column of datesCreating a range of datesExtracting month and year from Datetime columnGetting all weekdays between two datesGetting all weekends between two datesGetting day unit from date columnGetting month unit from date columnGetting name of months in date columnGetting week numbers from a date columnGetting day of week of date columnsGetting year unit from date columnModifying datesOffsetting datetimeRemoving time unit from datesSetting date to beginning of monthSorting DataFrame by datesUsing dates as the index of a DataFrame
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Modifying dates in Pandas
schedule Aug 12, 2023
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Tags Python●Pandas
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Replacing dates of Timestamp
To modify dates (Timestamp) in Pandas, use the dt.replace(~) helper method:
ts = pd.to_datetime("2020/12/25") # returns a Timestampts.replace(year=2025)
Timestamp('2025-12-25 00:00:00')
Note that since Timestamp is immutable, a new Timestamp is returned and the original is kept intact.
Replacing dates in Series of datetime
Consider the following Series:
dates = pd.Series(pd.to_datetime(["2019/11/25","2020/12/26"]))dates
0 2019-11-251 2020-12-26dtype: datetime64[ns]
To iteratively modify each date (datetime64) in dates:
dates.map(lambda val: val.replace(year=2025))
0 2025-11-251 2025-12-26dtype: datetime64[ns]
Again, map(~) returns a new Series and so the original dates is kept intact.
Published by Isshin Inada
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