Python | Pandas Index.set_names()
Last Updated :
18 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 Index.set_names()
function set new names on index. For the given Index it resets the name attribute for that Index. It defaults to returning new index. The functions can also be used to reset the name attribute of the multi-index.
Syntax: Index.set_names(names, level=None, inplace=False)
Parameters :
names : [str or sequence] name(s) to set
level : If the index is a MultiIndex (hierarchical), level(s) to set (None for all levels). Otherwise level must be None
inplace : [bool] if True, mutates in place
Returns : new index (of same type and class…etc) [if inplace, returns None]
Example #1: Use Index.set_names()
function create an anonymous Index and set its name using the name parameter.
import pandas as pd
pd.Index([ 'Beagle' , 'Pug' , 'Labrador' , 'Pug' ,
'Mastiff' , None , 'Beagle' ]).set_names( 'Dog_breeds' )
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Output :
As we can see in the output, the function has reset the name attribute of the anonymous Index.
Example #2: Use Index.set_names()
function to reset the name attribute of the multi-index.
import pandas as pd
midx = pd.MultiIndex.from_tuples([( 'Sam' , 21 ), ( 'Norah' , 25 ), ( 'Jessica' , 32 ),
( 'Irwin' , 24 )], names = [ 'Name' , 'Age' ])
midx
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Output :
As we can see in the output, the name attribute of midx multi-index is set to ‘Name’ and ‘Age’. Let’s reset these names to be ‘Student_Name’ and ‘Student_Age’
midx.set_names([ 'Student_Name' , 'Student_Age' ])
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Output :
As we can see in the output, the function has reset the name attribute of midx multi-index.
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