Python | Pandas TimedeltaIndex.fillna
Last Updated :
06 Jan, 2019
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.fillna()
function fill all the missing values in the given TimedeltaIndex object with the specified value.
Syntax : TimedeltaIndex.fillna(value=None, downcast=None)
Parameters :
value : Scalar value to use to fill holes (e.g. 0). This value cannot be a list-likes.
downcast : a dict of item->dtype of what to downcast if possible, or the string ‘infer’ which will try to downcast to an appropriate equal type (e.g. float64 to int64 if possible)
Return : filled : %(klass)s
Example #1: Use TimedeltaIndex.fillna()
function to fill all the missing values n the given TimedeltaIndex objects.
import pandas as pd
tidx = pd.TimedeltaIndex(data = [ None , '1 days 06:05:01.000030' , None ,
'1 days 02:00:00' , '21 days 06:15:01.000030' ])
print (tidx)
|
Output :
Now we will use the TimedeltaIndex.fillna()
function to fill all the missing values in tidx object.
Output :
As we can see in the output, the TimedeltaIndex.fillna()
function has filled all the missing values with the specified value in the tidx object.
Example #2: Use TimedeltaIndex.fillna()
function to fill all the missing values n the given TimedeltaIndex objects.
import pandas as pd
tidx = pd.TimedeltaIndex(data = [ '06:05:01.000030' , None , '22 day 2 min 3us 10ns' ,
'+23:59:59.999999' , None , '+12:19:59.999999' ])
print (tidx)
|
Output :
Now we will use the TimedeltaIndex.fillna()
function to fill all the missing values in tidx object.
tidx.fillna( '2 days 10:50' )
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Output :
As we can see in the output, the TimedeltaIndex.fillna()
function has filled all the missing values with the specified value in the tidx object.
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