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 TimedeltaIndex.shift()
function performs specialized shift on the given TimedeltaIndex object, which produces a DatetimeIndex object.
Syntax : TimedeltaIndex.shift(n, freq=None)
Parameters :
n : Periods to shift by
freq : DateOffset or timedelta-like, optionalReturn : shifted : DatetimeIndex
Example #1: Use TimedeltaIndex.shift()
function to shift the given TimedeltaIndex object by 2 periods.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(start = '11 days 22:14:12.001124' , periods = 5 , freq = 'T' ) # Print the TimedeltaIndex object print (tidx) |
Output :
Now we will use the TimedeltaIndex.shift()
function to shift each element of the given TimedeltaIndex object by 2 periods.
# shift by 2 periods tidx.shift(n = 2 ) |
Output :
As we can see in the output, the TimedeltaIndex.shift()
function has returned a new object and it has shifted each element by 2 minutes.
Example #2: Use TimedeltaIndex.shift()
function to shift the given TimedeltaIndex object by 2 periods.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(start = '03 days 09:22:56' , periods = 5 , freq = 'H' ) # Print the TimedeltaIndex object print (tidx) |
Output :
Now we will use the TimedeltaIndex.shift()
function to shift each element of the given TimedeltaIndex object by 5 periods.
# shift by 5 periods tidx.shift(n = 5 ) |
Output :
As we can see in the output, the TimedeltaIndex.shift()
function has returned a new object and it has shifted each element by 5 hours.