Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas DatetimeIndex.date attribute outputs an Index object containing the date values present in each of the entries of the DatetimeIndex object.
Syntax: DatetimeIndex.date
Return: numpy array of python datetime.date
Example #1: Use DatetimeIndex.date attribute to find the date part of the DatetimeIndex object.
# importing pandas as pdimport pandas as pd # Create the DatetimeIndex# Here 'W' represents Weekly frequencydidx = pd.DatetimeIndex(start ='2000-01-10 06:30', freq ='W', periods = 3, tz ='Asia/Calcutta') # Print the DatetimeIndexprint(didx) |
Output :
Now we want to find all the date values present in the DatetimeIndex object.
# find all the date values present in the objectdidx.date |
Output :
As we can see in the output, the function has returned an Index object containing the date values present in each entry of the DatetimeIndex object.
Example #2: Use DatetimeIndex.date attribute to find the date part of the DatetimeIndex object.
# importing pandas as pdimport pandas as pd # Create the DatetimeIndex# Here 'D' represents Daily frequencydidx = pd.DatetimeIndex(start ='2014-08-01 10:05:45', freq ='D', periods = 5, tz ='Asia/Calcutta') # Print the DatetimeIndexprint(didx) |
Output :
Now we want to find all the date values present in the DatetimeIndex object.
# find all the date values present in the objectdidx.date |
Output :
As we can see in the output, the function has returned an Index object containing the date values present in each entry of the DatetimeIndex object.
