Skip to content
Related Articles

Related Articles

Improve Article
Save Article
Like Article

Python | Pandas Period.freq

  • Last Updated : 06 Jan, 2019

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 Period.freq attribute returns the frequency applied on the given Period object.

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course

Syntax : Period.freq



Parameters : None

Return : frequency

Example #1: Use Period.freq attribute to find the time series frequency applied on the given Period object.




# importing pandas as pd
import pandas as pd
  
# Create the Period object
prd = pd.Period(freq ='D', year = 2001, month = 2, day = 21)
  
# Print the Period object
print(prd)

Output :

Now we will use the Period.freq attribute to find the frequency applied on prd object.




# return the frequency
prd.freq

Output :

As we can see in the output, the Period.freq attribute has returned ‘Day’ indicating that the time series frequency applied on the given object was day.

Example #2: Use Period.freq attribute to find the time series frequency applied on the given Period object.




# importing pandas as pd
import pandas as pd
  
# Create the Period object
prd = pd.Period(freq ='Q', year = 2006, quarter = 1)
  
# Print the object
print(prd)

Output :

Now we will use the Period.freq attribute to find the frequency applied on prd object.




# return the frequency
prd.freq

Output :


As we can see in the output, the Period.freq attribute has returned ‘QuarterEnd’ indicating that the time series frequency applied on the given object was ‘Quarter’.




My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!