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How to Change Index in Pandas?

Published in Data Manipulation 3 mins read

You can change the index in a Pandas DataFrame using the set_index() method. This method allows you to specify a column or a list of columns to use as the new index.

Here's a breakdown of how to change the index:

1. Setting a New Index

  • Using a single column:

      import pandas as pd

  data = {'Name': ['Alice', 'Bob', 'Charlie'],
          'Age': [25, 30, 28],
          'City': ['New York', 'London', 'Paris']}

  df = pd.DataFrame(data)
  df = df.set_index('Name')
  print(df)

    This code sets the 'Name' column as the new index.

  • Using multiple columns:

      import pandas as pd

  data = {'Name': ['Alice', 'Bob', 'Charlie'],
          'Age': [25, 30, 28],
          'City': ['New York', 'London', 'Paris']}

  df = pd.DataFrame(data)
  df = df.set_index(['Name', 'City'])
  print(df)

    This code sets both 'Name' and 'City' columns as the new index, creating a hierarchical index.

2. Resetting the Index

If you want to revert to a default numerical index, use the reset_index() method:

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'],
        'Age': [25, 30, 28],
        'City': ['New York', 'London', 'Paris']}

df = pd.DataFrame(data)
df = df.set_index('Name')
df = df.reset_index()
print(df)

This will create a new numerical index, starting from 0, and move the previous index to a new column named 'Name'.

3. Renaming the Index

You can rename the index using the rename() method:

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'],
        'Age': [25, 30, 28],
        'City': ['New York', 'London', 'Paris']}

df = pd.DataFrame(data)
df = df.set_index('Name')
df = df.rename(index={'Alice': 'A', 'Bob': 'B', 'Charlie': 'C'})
print(df)

This code renames the index values 'Alice', 'Bob', and 'Charlie' to 'A', 'B', and 'C', respectively.

4. Setting a Custom Index

You can create a custom index using a list or a range:

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'],
        'Age': [25, 30, 28],
        'City': ['New York', 'London', 'Paris']}

df = pd.DataFrame(data)
df = df.set_index(pd.Index(['A', 'B', 'C']))
print(df)

This code sets a custom index with values 'A', 'B', and 'C'.

Remember that changing the index can affect how you access and manipulate data in your DataFrame.

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