Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.normalize() function convert times to midnight. The time component of the date-time is converted to midnight i.e. 00:00:00. This is useful in cases, when the time does not matter. Length is unaltered. The timezones are unaffected.
Syntax: Series.dt.normalize(*args, **kwargs)
Parameter : None
Returns : DatetimeArray, DatetimeIndex or Series
Example #1: Use Series.dt.normalize() function to convert the times in the given series object to midnight.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range('2012-12-31 09:45', periods = 5, freq = 'M', tz = 'Europe / Berlin')) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Print the series print(sr) |
Output :
Now we will use Series.dt.normalize() function to convert the times to midnight.
# convert to midnight result = sr.dt.normalize() # print the result print(result) |
Output :
As we can see in the output, the Series.dt.normalize() function has successfully converted the times in the given series object to midnight.
Example #1: Use Series.dt.normalize() function to convert the times in the given series object to midnight.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range('2019-1-1 12:30', periods = 5, freq = 'H', tz = 'Asia / Calcutta')) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Print the series print(sr) |
Output :
Now we will use Series.dt.normalize() function to convert the times to midnight.
# convert to midnight result = sr.dt.normalize() # print the result print(result) |
Output :
As we can see in the output, the Series.dt.normalize() function has successfully converted the times in the given series object to midnight.
