Dateoffsets are a standard kind of date increment used for a date range in Pandas. It works exactly like relativedelta in terms of the keyword args we pass in. DateOffsets work as follows, each offset specify a set of dates that conform to the DateOffset. For example, Bday defines this set to be the set of dates that are weekdays (M-F). DateOffsets can be created to move dates forward a given number of valid dates. For example, Bday(2) can be added to date to move it two business days forward. If the date does not start on a valid date, first it is moved to a valid date and then offset is created. Pandas tseries.offsets.DateOffset.normalize attribute returns boolean value. It returns True when the DateOffset value has been normalized else it returns False. Note : Normalizing means to round the result of a DateOffset addition down to the previous midnight.
Syntax: pandas.tseries.offsets.DateOffset.normalize Parameter : None Returns : boolean
Example #1: Use pandas.tseries.offsets.DateOffset.normalize attribute to check if the given DateOffset value has been normalized or not.
# importing pandas as pd import pandas as pd
# Creating Timestamp ts = pd.Timestamp( '2019-10-10 07:15:11' )
# Create the DateOffset do = pd.tseries.offsets.DateOffset(n = 2 )
# Print the Timestamp print (ts)
# Print the DateOffset print (do)
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Output :
# Adding the dateoffset to the given timestamp new_timestamp = ts + do
# Print the updated timestamp print (new_timestamp)
# check if the DateOffset has been normalized or not print (do.normalize)
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Output :
# importing pandas as pd import pandas as pd
# Creating Timestamp ts = pd.Timestamp( '2019-10-10 07:15:11' )
# Create the DateOffset # Also normalize it do = pd.tseries.offsets.DateOffset(days = 10 , hours = 2 , normalize = True )
# Print the Timestamp print (ts)
# Print the DateOffset print (do)
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Output :
# Adding the dateoffset to the given timestamp new_timestamp = ts + do
# Print the updated timestamp print (new_timestamp)
# check if the DateOffset has been normalized or not print (do.normalize)
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Output :