chevron_left Time Series Cookbook

Adding new column containing the difference between two date columns Combining columns containing date and time Combining columns of years, months and days Converting a column of strings to datetime Converting dates to strings Converting datetime column to date and time columns Converting DatetimeIndex to Series of datetime Converting index to datetime Converting UNIX timestamp to datetime Creating a column of dates Creating a range of dates Extracting month and year from Datetime column Getting all weekdays between two dates Getting all weekends between two dates Getting day unit from date column Getting month unit from date column Getting name of months in date column Getting week numbers from a date column Getting day of week of date columns Getting year unit from date column Modifying dates Offsetting datetime Removing time unit from dates Setting date to beginning of month Sorting DataFrame by dates Using dates as the index of a DataFrame

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Offsetting datetime in Pandas

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Time Series Cookbook

schedule Jul 1, 2022

Last updated

local_offer Python●Pandas

Example

Consider the following DataFrame:


        
        
            
                
                
                    date_index = pd.to_datetime(["24/12/2020", "26/12/2020"])
df = pd.DataFrame({"A":[3,4]}, index=date_index)
df
                
            
                        A
2020-12-24  3
2020-12-26  4

Here, the index is of type DatetimeIndex.

To offset the index by a day:


        
        
            
                
                
                    df.index + pd.Timedelta("1D")
                
            
            DatetimeIndex(['2020-12-25', '2020-12-27'], dtype='datetime64[ns]', freq=None)

Note that date arithmetics with Timedelta works other datetime-related objects such as datetime64 and Timestamp.

Pandas | Timedelta constructor

Creates a new Timedelta object, which represents a time difference in units that you specify. It is typically used to perform date arithmetics.

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