How to Rename Column by Index in Pandas

How to rename column by index in pandas? You can rename pandas DataFrame column name by index (position) using rename() method or by assigning column name to df.columns.values[index]. In this article, I will explain renaming column names by index on pandas DataFrame with examples.

Key Points –

• Columns can be renamed by directly modifying the DataFrame.columns attribute, which is a list-like structure.
• Use the column’s index position to target the specific column for renaming.
• Assign a new name to the desired index position within DataFrame.columns to rename it.
• The rename() method can be used in combination with the columns parameter to rename columns, though it primarily focuses on renaming by label rather than index.
• Modifications to DataFrame.columns directly affect the DataFrame, so if temporary renaming is needed, consider creating a copy of the DataFrame.
• If multiple columns need renaming, assign a list with the new names to DataFrame.columns.

Quick Examples of Rename Column by Index

If you are in a hurry, below are some quick examples of how to change column names by index on Pandas DataFrame.

# Quick examples of rename column by index

# Example 1: Assign column name by index
df.columns.values[1] = 'Courses_Fee'
print(df.columns)

# Example 2: Rename column name by index
df.rename(columns={df.columns[2]: 'Courses_Duration'},inplace=True)
print(df.columns)

# Example 3: Rename multiple columns
df.rename(columns={df.columns[1]: 'Fee', df.columns[2]: 'Duration'},inplace=True)
print(df.columns)

Now, let’s create a DataFrame with a few rows and columns, execute these examples, and validate the results. Our DataFrame contains column names Courses, Fee, Duration, and Discount.

# Create DataFrame
import pandas as pd
technologies = [ ["Spark",20000,"30days"], 
                 ["Pandas",25000,"40days"], 
               ]
column_names=["Courses","Fee",'Duration']
df=pd.DataFrame(technologies, columns=column_names)
print("Create DataFrame:\n",df.columns)

Yields below column names.

Rename Column Name by Index

If you want to rename a single column by Index on pandas DataFrame then you can just assign a new value to the df.columns.values[idx], replace idx with the right index where you wanted to rename.

This program first assigns the value ‘Courses_Fee’ to the element at index 1 of the df.columns.values array, effectively renaming the column at index 1 in the DataFrame. The print(df.columns) line then outputs the updated column names.

# Assign column name for Index
df.columns.values[1] = 'Courses_Fee'
print(df.columns)

Yields below output. df.columns get the column names as a list from pandas DataFrame.

# Output:
Index(['Courses', 'Courses_Fee', 'Duration'], dtype='object')

This changes the column name from Fee to Courses_Fee.

Using rename() to Change Column Name at Index

You can also use pandas DataFrame.rename() method to change column name at a specific index. This method takes the columns param with value as dict (key-value pair). The key is an existing column name and the value would be a new column name. Though this method doesn’t support by index, we can get the column name of the index by using df.columns[index].

This program renames the column at index 2 (column ‘Duration’) to ‘Courses_Duration’ using the rename method with the columns parameter. The inplace=True argument modifies the original DataFrame in place. The print(df.columns) line then outputs the updated column names.

# Rename single column by index
df.rename(columns={df.columns[2]: 'Courses_Duration'},inplace=True)
print(df.columns)

Yields below output. Use inplace=True to replace on existing DataFrame object. not using this it returns a new DF without changing on an existing one.

# Output:
Index(['Courses', 'Courses_Fee', 'Courses_Duration'], dtype='object')

This changes the column name from Duration to Courses_Duration.

Rename Multiple Columns by Index

Now let’s see how to rename multiple column names by index/position in pandas DataFrame. For this, I will be using the same method explained above. To rename multiple, you have to pass multiple mappings in key-value pair to the columns param.

# Rename multiple columns by Index
df.rename(columns={df.columns[1]: 'Fee', df.columns[2]: 'Duration'},inplace=True)
print(df.columns)

Yields below output.

# Output:
Index(['Courses', 'Fee', 'Duration'], dtype='object')

The above example renames the multiple columns to the original values.

Complete Example

# Import pandas library
import pandas as pd
technologies = [ ["Spark",20000, "30days"], 
                 ["Pandas",25000, "40days"], 
               ]]

# Create DataFrame
column_names=["Courses","Fee",'Duration']
df=pd.DataFrame(technologies, columns=column_names)
print(df.columns)

# Assign column name by index
df.columns.values[1] = 'Courses_Fee'
print(df.columns)

# Rename column name by index
df.rename(columns={df.columns[2]: 'Courses_Duration'},inplace=True)
print(df.columns)

# Rename multiple columns
df.rename(columns={df.columns[1]: 'Fee', df.columns[2]: 'Duration'},inplace=True)
print(df.columns)

Frequently Asked Questions on Rename Column by Index in Pandas?

Conclusion

In this article, you have learned to rename column names by index using the rename() method and df.columns.values[idx]. By using the rename() method you can also change single and multiple columns, for multiples you need to create a map with a key-value pair for all columns you want to change.

Related Articles

• Pandas Rename Column with Examples
• How to Rename Multiple Columns in Pandas
• How to Rename Columns With List in Pandas
• How to Rename Specific Columns in Pandas
• Pandas Select Rows Based on Column Values
• Pandas GroupBy Multiple Columns Explained
• Pandas Aggregate Functions with Examples
• pandas.DataFrame.where() Examples
• Pandas Filter by Index 
• Pandas DataFrame insert() Function 
• Pandas Add Column with Default Value 
• Apply Multiple Filters to Pandas DataFrame or Series

References

• https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.rename.html