Pandas index column title or name

StackOverflow

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 rating: 471

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 rating: 95

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

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

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

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"]

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

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"]

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




Get Solution for free from DataCamp guru