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_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
Code #1:
# importing pandas as pd import pandas as pd # period_range with freq = day per1 = pd.period_range(start ='2018-12-20', end ='2019-01-01', freq ='D') # period_range with freq = month per2 = pd.period_range(start ='2018-12-20', end ='2019-12-01', freq ='M') print(per1, "\n\n", per2) |
Output:
Code #2:
# importing pandas as pd import pandas as pd # period_range with freq = day per1 = pd.period_range(start ='2018-12-20', end ='2019-01-01', freq ='D') for val in per1: print(val) |
Output:
Code #3:
# importing pandas as pd import pandas as pd # Calling with pd.Period per = pd.period_range(start = pd.Period('2017Q1', freq ='Q'), end = pd.Period('2018Q2', freq ='Q'), freq ='M') for val in per: print(val) |
Output:
