How to determine Period Range with Frequency in Pandas?

Last Updated : 25 May, 2021

In pandas, we can determine Period Range with Frequency with the help of period_range(). pandas.period_range() is one of the general functions in Pandas which is used to return a fixed frequency PeriodIndex, with day (calendar) as the default frequency.

Syntax: pandas.to_numeric(arg, errors=’raise’, downcast=None)

Parameters:
start : Left bound for generating periods
end : Right bound for generating periods
periods : Number of periods to generate
freq : Frequency alias
name : Name of the resulting PeriodIndex

Returns: PeriodIndex

Example 1:

Python3

import pandas as pd
 
 
# initialize country
country = ["India", "Australia", "Pak", "Sri Lanka", 
           "England", "Bangladesh"]
 
# perform period_range() function
match_date = pd.period_range('8/1/2020', '8/6/2020', freq='D')
 
# generates dataframes
df = pd.DataFrame(country, index=match_date, columns=['Country'])
 
df

Output:

Example

Python3

import pandas as pd
 
# initialize country
Course = ["DSA", "OOPS", "DBMS", "Computer Network", 
          "System design", ]
 
# perform period_range() function
webinar_month = pd.period_range('8/1/2020', '12/1/2020', freq='M')
 
# generates dataframes
df = pd.DataFrame(Course, index=webinar_month, columns=['Course'])
 
df

Output:

Example 3:

Python3

import pandas as pd
 
 
# initialize gold price
gold_price = ["32k", "34k", "37k", "33k", "38k", "39k", "35k",
              "32k", "42k", "52k", "62k", "52k", "38k", "39k",
              "35k", "33k"]
 
# perform period_range() function
price_month = pd.period_range(start=pd.Period('2019Q1', freq='Q'),
                              end=pd.Period('2020Q2', freq='Q'),
                              freq='M')
 
# generates dataframes
df = pd.DataFrame(gold_price, index=price_month, columns=['Price'])
 
df