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 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 course = ["DBMS", "DSA", "OOPS", "System Design", "CN", ] # pass the period and staring index webinar_date = pd.period_range('2020-08-15', periods=5) # Determine Period Index and Column # for DataFrame df = pd.DataFrame(course, index=webinar_date, columns=['Course']) df |
Output:
Example 2:
Python3
import pandas as pd day = ["Sun", "Mon", "Tue", "Wed", "Thurs", "Fri", "Sat"] # pass the period and staring index daycode = pd.period_range('2020-08-15', periods=7) # Determine Period Index and Column for DataFrame df = pd.DataFrame(day, index=daycode, columns=['day']) df |
Output:
Example 3:
Python3
import pandas as pd Team = ["Ind", "Pak", "Aus"] # pass the period and staring index match_date = pd.period_range('2020-08-01', periods=3) # Determine Period Index and Column for DataFrame df = pd.DataFrame(Team, index=match_date, columns=['Team']) df |
Output:
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