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 Index.repeat() function repeat elements of an Index. The function returns a new index where each element of the current index is repeated consecutively a given number of times.
Syntax: Index.repeat(repeats, *args, **kwargs)
Parameters :
repeats : The number of repetitions for each element.
**kwargs : Additional keywords have no effect but might be accepted for compatibility with numpy.Returns : Newly created Index with repeated elements.
Example #1: Use Index.repeat()() function to repeat the elements of the index 2 times.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index(['Beagle', 'Pug', 'Labrador', 'Pug', 'Mastiff', None, 'Beagle']) # Print the Index idx |
Output :
Let’s repeat the index elements 2 times.
# to repeat the values idx.repeat(2) |
Output :
As we can see in the output, the function has returned a new index with all the values repeated 2 times. One important thing to notice is that the function has also repeated the NaN value.
Example #2: Use Index.repeat() function to repeat the value of index 3 times.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index([22, 14, 8, 56, None, 21, None, 23]) # Print the Index idx |
Output :
Let’s repeat the index elements 3 times.
# to repeat the values idx.repeat(3) |
Output :
As we can see in the output, the function has returned a new index with all the values repeated 3 times. One important thing to notice is that the function has also repeated the NaN value.
