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.BusinessHour.name attribute return the frequency applied on the given offset as a string.
Syntax: pandas.tseries.offsets.BusinessHour.name Parameter : None Returns : frequency applied as string
Example #1: Use pandas.tseries.offsets.BusinessHour.name attribute to return the name of the frequency applied on the given offset as string.
# importing pandas as pd import pandas as pd
# Creating Timestamp ts = pd.Timestamp( '2019-10-10 11:15:00' )
# Create an offset bh = pd.tseries.offsets.BusinessHour(n = 5 )
# Print the Timestamp print (ts)
# Print the Offset print (bh)
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Output :
# Adding the Business hour offset to the given timestamp new_timestamp = ts + bh
# Print the updated timestamp print (new_timestamp)
# print the name of the frequency # applied as string print (bh.name)
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Output :
# importing pandas as pd import pandas as pd
# Creating Timestamp ts = pd.Timestamp( '2019-10-10 11:15:00' )
# Create an offset bh = pd.tseries.offsets.BusinessHour(offset = datetime.timedelta(hours = 1 ))
# Print the Timestamp print (ts)
# Print the Offset print (bh)
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Output :
# Adding the Business hour offset to the given timestamp new_timestamp = ts + bh
# Print the updated timestamp print (new_timestamp)
# print the name of the frequency # applied as string print (bh.name)
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Output :