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 PeriodIndexReturns: PeriodIndex
Example 1:
Python3
import pandas as pd# initialize countrycountry = ["India", "Australia", "Pak", "Sri Lanka", "England", "Bangladesh"]# perform period_range() functionmatch_date = pd.period_range('8/1/2020', '8/6/2020', freq='D')# generates dataframesdf = pd.DataFrame(country, index=match_date, columns=['Country'])df |
Output:
Example
Python3
import pandas as pd# initialize countryCourse = ["DSA", "OOPS", "DBMS", "Computer Network", "System design", ]# perform period_range() functionwebinar_month = pd.period_range('8/1/2020', '12/1/2020', freq='M')# generates dataframesdf = pd.DataFrame(Course, index=webinar_month, columns=['Course'])df |
Output:
Example 3:
Python3
import pandas as pd# initialize gold pricegold_price = ["32k", "34k", "37k", "33k", "38k", "39k", "35k", "32k", "42k", "52k", "62k", "52k", "38k", "39k", "35k", "33k"]# perform period_range() functionprice_month = pd.period_range(start=pd.Period('2019Q1', freq='Q'), end=pd.Period('2020Q2', freq='Q'), freq='M')# generates dataframesdf = pd.DataFrame(gold_price, index=price_month, columns=['Price'])df |
Output:
