Python | Pandas TimedeltaIndex.take()
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.take()
function return a new Index of the values selected by the indices. We generally pass a list of indices to be taken. It is used for internal compatibility with numpy arrays.
Syntax : TimedeltaIndex.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs)
Parameters :
indices : list Indices to be taken
axis : The axis over which to select values, always 0.
allow_fill : bool, default True
fill_value : bool, default None ,If allow_fill=True and fill_value is not None, indices specified by -1 is regarded as NA. If Index doesn’t hold NA, raise ValueError
Return : Object of same type
Example #1: Use TimedeltaIndex.take()
function to return a new TimedeltaIndex object containing only selected values in it.
import pandas as pd
tidx = pd.TimedeltaIndex(data = [ '06:05:01.000030' , '+23:59:59.999999' ,
'22 day 2 min 3us 10ns' , '+23:29:59.999999' ,
'+12:19:59.999999' ])
print (tidx)
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Output :
Now we will use the TimedeltaIndex.take()
function to select some specific values from tidx.
Output :
As we can see in the output, the TimedeltaIndex.take()
function has returned a new TimedeltaIndex object which contains only those elements whose locations has been passed to the function.
Example #2: Use TimedeltaIndex.take()
function to return a new TimedeltaIndex object containing only selected values in it.
import pandas as pd
tidx = pd.TimedeltaIndex(start = '1 days 02:00:12.001124' ,
periods = 5 , freq = 'D' , name = 'Koala' )
tidx
|
Output :
Now we will use the TimedeltaIndex.take()
function to select some specific values from tidx.
Output :
As we can see in the output, the TimedeltaIndex.take()
function has returned a new TimedeltaIndex object which contains only those elements whose locations has been passed to the function.
Last Updated :
06 Jan, 2019
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