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 Timestamp.year attribute return the year in which the date in the given Timestamp object lies.
Syntax : Timestamp.year Parameters : None Return : year
Example #1: Use Timestamp.year attribute to find the year in which the date present in the given Timestamp object lies.
Python3
# importing pandas as pdimport pandas as pd# Create the Timestamp objectts = pd.Timestamp(year = 2011, month = 11, day = 21, hour = 10, second = 49, tz = 'US/Central')# Print the Timestamp objectprint(ts) |
Output : 
Now we will use the Timestamp.year attribute to find the year value of the date.
Python3
# return the yearts.year |
Output : 
As we can see in the output, the Timestamp.year attribute has returned 2011 indicating that the year value of the date in the given Timestamp object is 2011. Example #2: Use Timestamp.year attribute to find the year in which the date present in the given Timestamp object lies.
Python3
# importing pandas as pdimport pandas as pd# Create the Timestamp objectts = pd.Timestamp(year = 2009, month = 5, day = 31, hour = 4, second = 49, tz = 'Europe/Berlin')# Print the Timestamp objectprint(ts) |
Output : 
Now we will use the Timestamp.year attribute to find the year value of the date.
Python3
# return the yearts.year |
Output : 
As we can see in the output, the Timestamp.year attribute has returned 2009 indicating that the year value of the date in the given Timestamp object is 2009.
