Python | Pandas tseries.offsets.DateOffset.normalize

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. 

Python3

# 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)

Output : Now we will add the dateoffset to the given timestamp object to increment it. We will also check if the DateOffset has been normalized or not. 

Python3

# 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)

Output : As we can see in the output, the attribute has successfully returned the a boolean value indicating whether the given DateOffset has been normalized or not. Example #2: Use pandas.tseries.offsets.DateOffset.normalize attribute to check if the given DateOffset value has been normalized or not. 

Python3

# 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)

Output : Now we will add the dateoffset to the given timestamp object to increment it. We will also check if the DateOffset has been normalized or not. 

Python3

# 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)

Output : As we can see in the output, the attribute has successfully returned the a boolean value indicating whether the given DateOffset has been normalized or not.