Pandas Dataframe Index

Last Updated : 24 Mar, 2026

The index in a Pandas DataFrame represents the labels assigned to each row. It helps in identifying and accessing data efficiently and can be either default numeric values or custom-defined labels.

Accessing and Modifying the Index

Accessing and modifying the index allows to understand how rows are labeled and customize them as needed. One can view the existing index using the .index attribute and later update it based on your requirements.

Python 
import pandas as pd

data = {'Name': ['Jake', 'Eve', 'Charlie'],
        'Age': [ 22, 35, 28],
        'Gender': [ 'Male', 'Female', 'Male'],
        'Salary': [40000, 70000, 48000]}
df = pd.DataFrame(data)
print(df.index)

Output
RangeIndex(start=0, stop=3, step=1)

Setting a Custom Index

The set_index() method is used to change the index of a DataFrame by setting one or more columns as the new index.

Python 
import pandas as pd

data = {'Name': ['Jake', 'Mike'],
        'Age': [25, 30],
        'Salary': [50000, 55000]}
df = pd.DataFrame(data)
res = df.set_index('Name')
print(res)

Output
      Age  Salary
Name             
Jake   25   50000
Mike   30   55000

Resetting the Index

If one need to reset the index back to default integer index, use reset_index() method. This will convert the current index into a regular column and create a new default index.

Python 
import pandas as pd

data = {'Name': ['Jake', 'Maria', 'Sam'],
        'Age': [25, 30, 22] }
df = pd.DataFrame(data)
res = df.reset_index(drop=True)
print(res)

Output
    Name  Age
0   Jake   25
1  Maria   30
2    Sam   22

Indexing with loc

The loc[] method in pandas allows to access rows and columns of a dataFrame using their labels, making it easy to retrieve specific data points.

Python 
import pandas as pd
data = {'age': [25, 30], 'city': ['NY', 'LA']}
df = pd.DataFrame(data, index=['Alice', 'Bob'])
row = df.loc['Alice']
print(row)

Output
age     25
city    NY
Name: Alice, dtype: object

Changing the Index

The set_index() method is used to change the index of a DataFrame by setting one or more columns as the new index.

Python 
import pandas as pd

data = { 'Name': ['Jake', 'Mike', 'Sam'],
         'Age': [25, 30, 22],
         'Salary': [50000, 55000, 40000] }
df = pd.DataFrame(data)
res = df.set_index('Age')
print(res)

Output
     Name  Salary
Age              
25   Jake   50000
30   Mike   55000
22    Sam   40000
Comment

Explore