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.quarter attribute return an integer value which represents the quarter in which the date of the given Timestamp object lies.
Syntax : Timestamp.quarter
Parameters : None
Return : quarter
Example #1: Use Timestamp.quarter attribute to find in which quarter the date of the given Timestamp object lies.
# importing pandas as pd import pandas as pd # Create the Timestamp object ts = pd.Timestamp(2016, 1, 1, 12, 25, 16, 28, 32) # Print the Timestamp object print(ts) |
Output :
Now we will use the Timestamp.quarter attribute to print the quarter in which the date in the ts object falls.
# find the value of quarter ts.quarter |
Output :
As we can see in the output, the Timestamp.quarter attribute has returned 1 indicating that the date in the ts object falls in the first quarter of the year.
Example #2: Use Timestamp.quarter attribute to find in which quarter the date of the given Timestamp object lies.
# importing pandas as pd import pandas as pd # Create the Timestamp object ts = pd.Timestamp(year = 2009, month = 5, day = 31, hour = 4, nanosecond = 15, tz = 'Europe/Berlin') # Print the Timestamp object print(ts) |
Output :
Now we will use the Timestamp.quarter attribute to print the quarter in which the date in the ts object falls.
# find the value of quarter ts.quarter |
Output :
As we can see in the output, the Timestamp.quarter attribute has returned 2 indicating that the date in the ts object falls in the second quarter of the year.