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:
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