Python | Pandas DatetimeIndex.to_period()
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 DatetimeIndex.to_period()
function is used to cast the given DatetimeIndex to PeriodIndex at a particular frequency. The function basically converts DatetimeIndex to PeriodIndex.
Syntax: DatetimeIndex.to_period(freq=None)
Parameters :
freq : One of pandas offset strings or an Offset object. Will be inferred by defaultReturn : PeriodIndex
Example #1: Use DatetimeIndex.to_period()
function to cast the data of the DatetimeIndex object to PeriodIndex.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'S' represents secondly frequency didx = pd.DatetimeIndex(start = '2018-11-15 09:45:10' , freq = 'S' , periods = 5 ) # Print the DatetimeIndex print (didx) |
Output :
Now we want to cast the DatetimeIndex object to PeriodIndex object.
# cast to PeriodIndex # 'T' represents minute based frequency didx.to_period( 'T' ) |
Output :
As we can see in the output, the function has casted the DatetimeIndex object to PeriodIndex object.
Example #2: Use DatetimeIndex.to_period()
function to cast the data of the DatetimeIndex object to PeriodIndex.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'T' represents minutely frequency didx = pd.DatetimeIndex(start = '2015-03-02 01:15:12' , freq = 'T' , periods = 5 ) # Print the DatetimeIndex print (didx) |
Output :
Now we want to cast the DatetimeIndex object to PeriodIndex object.
# cast to PeriodIndex # 'H' represents hourly frequency didx.to_period( 'H' ) |
Output :
As we can see in the output, the function has casted the DatetimeIndex object to PeriodIndex object.
Contact Us