Python | Pandas TimedeltaIndex.duplicated
Last Updated :
28 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 TimedeltaIndex.duplicated()
function detects duplicate values in the given TimedeltaIndex object. It return a boolean np.ndarray denoting duplicate values. All duplicate occurrence of the values are marked True
except the first occurrence.
Syntax : TimedeltaIndex.duplicated(keep=’first’)
Parameters :
keep : {‘first’, ‘last’, False}, default ‘first’
-> first : Mark duplicates as True except for the first occurrence.
-> last : Mark duplicates as True except for the last occurrence.
-> False : Mark all duplicates as True.
Return : duplicated : np.ndarray
Example #1: Use TimedeltaIndex.duplicated()
function to check for all the duplicate occurrence of the elements in the given TimedeltaIndex object.
import pandas as pd
tidx = pd.TimedeltaIndex(data = [ '06:05:01.000030' , '+23:59:59.999999' ,
'22 day 2 min 3us 10ns' , '+23:59:59.999999' ,
'+23:29:59.999999' , '+12:19:59.999999' ])
print (tidx)
|
Output :
Now we will use the TimedeltaIndex.duplicated()
function to check for all duplicate occurrence.
Output :
As we can see in the output, the TimedeltaIndex.duplicated()
function has returned an ndarray containing boolean values for each element of tidx. Elements are marked True
if they are not duplicated else they are marked False
.
Example #2: Use TimedeltaIndex.duplicated()
function to check for all the duplicate occurrence of the elements in the given TimedeltaIndex object.
import pandas as pd
tidx = pd.TimedeltaIndex(data = [ '1 days 02:00:00' , '1 days 06:05:01.000030' ,
'1 days 02:00:00' , '1 days 02:00:00' ,
'21 days 06:15:01.000030' ])
print (tidx)
|
Output :
Now we will use the TimedeltaIndex.duplicated()
function to check for all duplicate occurrence.
Output :
As we can see in the output, the TimedeltaIndex.duplicated()
function has returned an ndarray containing boolean values for each element of tidx. Elements are marked True
if they are not duplicated else they are marked False
.
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