Python | Pandas Period.hour

Python | pandas.period_range() method

Last Updated : 17 Dec, 2018

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 PeriodIndex Returns: PeriodIndex

Code #1:

Python3 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:

Python3 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')

for val in per1:
    print(val)

Output:

Code #3:

Python3 1==

# 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:

Python | Pandas Period.hour

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