Determine Period Index and Column for DataFrame in Pandas
In Pandas to determine Period Index and Column for Data Frame, we will use the pandas.period_range() method. It is one of the general functions in Pandas that 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 pdcourse = ["DBMS", "DSA", "OOPS", "System Design", "CN", ]# pass the period and starting indexwebinar_date = pd.period_range('2020-08-15', periods=5)# Determine Period Index and Column# for DataFramedf = pd.DataFrame(course, index=webinar_date, columns=['Course'])df |
Output:
Example 2:
Python3
import pandas as pdday = ["Sun", "Mon", "Tue", "Wed", "Thurs", "Fri", "Sat"]# pass the period and starting indexdaycode = pd.period_range('2020-08-15', periods=7)# Determine Period Index and Column for DataFramedf = pd.DataFrame(day, index=daycode, columns=['day'])df |
Output:
Example 3:
Python3
import pandas as pdTeam = ["Ind", "Pak", "Aus"]# pass the period and starting indexmatch_date = pd.period_range('2020-08-01', periods=3)# Determine Period Index and Column for DataFramedf = pd.DataFrame(Team, index=match_date, columns=['Team'])df |
Output:
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