Pandas index column title or name

Question

How do I get the index column name in python pandas? Here's an example dataframe:

             Column 1 Index Title           Apples              1 Oranges             2 Puppies             3 Ducks               4   

What I'm trying to do is get/set the dataframe index title. Here is what i tried:

import pandas as pd data = {'Column 1'     : [1., 2., 3., 4.],         'Index Title'  : ["Apples", "Oranges", "Puppies", "Ducks"]} df = pd.DataFrame(data) df.index = df["Index Title"] del df["Index Title"] print df 

Anyone know how to do this?

Answer 1

You can just get/set the index via its name property

In [7]: df.index.name Out[7]: 'Index Title'  In [8]: df.index.name = 'foo'  In [9]: df.index.name Out[9]: 'foo'  In [10]: df Out[10]:           Column 1 foo               Apples          1 Oranges         2 Puppies         3 Ducks           4 

Answer 2

You can use rename_axis, for removing set to None:

d = {'Index Title': ['Apples', 'Oranges', 'Puppies', 'Ducks'],'Column 1': [1.0, 2.0, 3.0, 4.0]} df = pd.DataFrame(d).set_index('Index Title') print (df)              Column 1 Index Title           Apples            1.0 Oranges           2.0 Puppies           3.0 Ducks             4.0  print (df.index.name) Index Title  print (df.columns.name) None 

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The new functionality works well in method chains.

df = df.rename_axis('foo') print (df)          Column 1 foo               Apples        1.0 Oranges       2.0 Puppies       3.0 Ducks         4.0 

You can also rename column names with parameter axis:

d = {'Index Title': ['Apples', 'Oranges', 'Puppies', 'Ducks'],'Column 1': [1.0, 2.0, 3.0, 4.0]} df = pd.DataFrame(d).set_index('Index Title').rename_axis('Col Name', axis=1) print (df) Col Name     Column 1 Index Title           Apples            1.0 Oranges           2.0 Puppies           3.0 Ducks             4.0  print (df.index.name) Index Title  print (df.columns.name) Col Name 

print df.rename_axis('foo').rename_axis("bar", axis="columns") bar      Column 1 foo               Apples        1.0 Oranges       2.0 Puppies       3.0 Ducks         4.0  print df.rename_axis('foo').rename_axis("bar", axis=1) bar      Column 1 foo               Apples        1.0 Oranges       2.0 Puppies       3.0 Ducks         4.0 

From version pandas 0.24.0+ is possible use parameter index and columns:

df = df.rename_axis(index='foo', columns="bar") print (df) bar      Column 1 foo               Apples        1.0 Oranges       2.0 Puppies       3.0 Ducks         4.0 

Removing index and columns names means set it to None:

df = df.rename_axis(index=None, columns=None) print (df)          Column 1 Apples        1.0 Oranges       2.0 Puppies       3.0 Ducks         4.0 

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If MultiIndex in index only:

mux = pd.MultiIndex.from_arrays([['Apples', 'Oranges', 'Puppies', 'Ducks'],                                   list('abcd')],                                    names=['index name 1','index name 1'])   df = pd.DataFrame(np.random.randint(10, size=(4,6)),                    index=mux,                    columns=list('ABCDEF')).rename_axis('col name', axis=1) print (df) col name                   A  B  C  D  E  F index name 1 index name 1                   Apples       a             5  4  0  5  2  2 Oranges      b             5  8  2  5  9  9 Puppies      c             7  6  0  7  8  3 Ducks        d             6  5  0  1  6  0 

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print (df.index.name) None  print (df.columns.name) col name  print (df.index.names) ['index name 1', 'index name 1']  print (df.columns.names) ['col name'] 

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df1 = df.rename_axis(('foo','bar')) print (df1) col name     A  B  C  D  E  F foo     bar                   Apples  a    5  4  0  5  2  2 Oranges b    5  8  2  5  9  9 Puppies c    7  6  0  7  8  3 Ducks   d    6  5  0  1  6  0  df2 = df.rename_axis('baz', axis=1) print (df2) baz                        A  B  C  D  E  F index name 1 index name 1                   Apples       a             5  4  0  5  2  2 Oranges      b             5  8  2  5  9  9 Puppies      c             7  6  0  7  8  3 Ducks        d             6  5  0  1  6  0  df2 = df.rename_axis(index=('foo','bar'), columns='baz') print (df2) baz          A  B  C  D  E  F foo     bar                   Apples  a    5  4  0  5  2  2 Oranges b    5  8  2  5  9  9 Puppies c    7  6  0  7  8  3 Ducks   d    6  5  0  1  6  0 

Removing index and columns names means set it to None:

df2 = df.rename_axis(index=(None,None), columns=None) print (df2)             A  B  C  D  E  F Apples  a  6  9  9  5  4  6 Oranges b  2  6  7  4  3  5 Puppies c  6  3  6  3  5  1 Ducks   d  4  9  1  3  0  5 

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For MultiIndex in index and columns is necessary working with .names instead .name and set by list or tuples:

mux1 = pd.MultiIndex.from_arrays([['Apples', 'Oranges', 'Puppies', 'Ducks'],                                   list('abcd')],                                    names=['index name 1','index name 1'])   mux2 = pd.MultiIndex.from_product([list('ABC'),                                   list('XY')],                                    names=['col name 1','col name 2'])  df = pd.DataFrame(np.random.randint(10, size=(4,6)), index=mux1, columns=mux2) print (df) col name 1                 A     B     C    col name 2                 X  Y  X  Y  X  Y index name 1 index name 1                   Apples       a             2  9  4  7  0  3 Oranges      b             9  0  6  0  9  4 Puppies      c             2  4  6  1  4  4 Ducks        d             6  6  7  1  2  8 

Plural is necessary for check/set values:

print (df.index.name) None  print (df.columns.name) None  print (df.index.names) ['index name 1', 'index name 1']  print (df.columns.names) ['col name 1', 'col name 2'] 

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df1 = df.rename_axis(('foo','bar')) print (df1) col name 1   A     B     C    col name 2   X  Y  X  Y  X  Y foo     bar                   Apples  a    2  9  4  7  0  3 Oranges b    9  0  6  0  9  4 Puppies c    2  4  6  1  4  4 Ducks   d    6  6  7  1  2  8  df2 = df.rename_axis(('baz','bak'), axis=1) print (df2) baz                        A     B     C    bak                        X  Y  X  Y  X  Y index name 1 index name 1                   Apples       a             2  9  4  7  0  3 Oranges      b             9  0  6  0  9  4 Puppies      c             2  4  6  1  4  4 Ducks        d             6  6  7  1  2  8  df2 = df.rename_axis(index=('foo','bar'), columns=('baz','bak')) print (df2) baz          A     B     C    bak          X  Y  X  Y  X  Y foo     bar                   Apples  a    2  9  4  7  0  3 Oranges b    9  0  6  0  9  4 Puppies c    2  4  6  1  4  4 Ducks   d    6  6  7  1  2  8 

Removing index and columns names means set it to None:

df2 = df.rename_axis(index=(None,None), columns=(None,None)) print (df2)             A     B     C               X  Y  X  Y  X  Y Apples  a  2  0  2  5  2  0 Oranges b  1  7  5  5  4  8 Puppies c  2  4  6  3  6  5 Ducks   d  9  6  3  9  7  0 

And @Jeff solution:

df.index.names = ['foo','bar'] df.columns.names = ['baz','bak'] print (df)  baz          A     B     C    bak          X  Y  X  Y  X  Y foo     bar                   Apples  a    3  4  7  3  3  3 Oranges b    1  2  5  8  1  0 Puppies c    9  6  3  9  6  3 Ducks   d    3  2  1  0  1  0