How to get Unique Values from Index Column of Pandas Dataframe?

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You can use the following methods to get the unique values from the index column of a pandas DataFrame:

Method 1: Get Unique Values from Index Column

df.index.unique()

Method 2: Get Unique Values from Specific Column in MultiIndex

df.index.unique('some_column')

The following examples show how to use this syntax in practice.

Example 1: Get Unique Values from Index Column

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'points': [18, 22, 19, 14, 14, 11, 20, 28],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4]},
                   index = [0, 1, 1, 1, 2, 2, 3, 4])

#view DataFrame
print(df)

  team  points  assists
0    A      18        5
1    B      22        7
1    C      19        7
1    D      14        9
2    E      14       12
2    F      11        9
3    G      20        9
4    H      28        4

We can use the following syntax to get the unique values from the index column of the DataFrame:

#get unique values from index column 
df.index.unique()

Int64Index([0, 1, 2, 3, 4], dtype='int64')

The output displays each of the unique values from the index column.

We can also use the len() function to count the number of unique values in the index column:

#count number of unique values in index column 
len(df.index.unique())

5

We can see that there are 5 unique values in the index column of the DataFrame.

Example 2: Get Unique Values from Specific Column in MultiIndex

Suppose we have the following pandas DataFrame:

import pandas as pd
#define index values
index_names = pd.MultiIndex.from_tuples([('West', 'A'),
                                         ('West', 'A'),
                                         ('West', 'B'),
                                         ('East', 'C'),
                                         ('East', 'C'),
                                         ('East', 'D')],
                                       names=['Division', 'Team'])

#define data values
data = {'Sales': [12, 44, 29, 35, 44, 19]}

#create DataFrame
df = pd.DataFrame(data, index=index_names)

#view DataFrame
print(df)

               Sales
Division Team       
West     A        12
         A        44
         B        29
East     C        35
         C        44
         D        19

Notice that this DataFrame has a multiIndex.

We can use the following syntax to get the unique values from just the Team column from the multiIndex:

#get unique values from Team column in multiIndex
df.index.unique('Team')

Index(['A', 'B', 'C', 'D'], dtype='object', name='Team')

The output displays the four unique values from the Team column of the multiIndex: A, B, C, and D.

We can use similar syntax to extract the unique values from the Division column of the multiIndex:

#get unique values from Division column in multiIndex
df.index.unique('Division')

Index(['West', 'East'], dtype='object', name='Division')

The output displays the two unique values from the Division column of the multiIndex: West and East.

The following tutorials explain how to perform other common functions in pandas: