Python – Pandas Dataframe.rename()

The rename() method in Pandas allows you to change column names in a DataFrame efficiently. You can rename single or multiple columns using dictionary mapping or functions.

Basic Syntax

The basic syntax for renaming columns is ?

DataFrame.rename(columns={old_name: new_name}, inplace=False)

Renaming a Single Column

Here's how to rename one column using the rename() method ?

import pandas as pd

df = pd.DataFrame(
    {
        "x": [5, 2, 7, 0],
        "y": [4, 7, 5, 1],
        "z": [9, 3, 5, 1]
    }
)

print("Input DataFrame:")
print(df)

df_renamed = df.rename(columns={"x": "new_x"})
print("\nAfter renaming column 'x' to 'new_x':")
print(df_renamed)

Input DataFrame:
   x  y  z
0  5  4  9
1  2  7  3
2  7  5  5
3  0  1  1

After renaming column 'x' to 'new_x':
   new_x  y  z
0      5  4  9
1      2  7  3
2      7  5  5
3      0  1  1

Renaming Multiple Columns

You can rename multiple columns at once by passing multiple key-value pairs ?

import pandas as pd

df = pd.DataFrame(
    {
        "x": [5, 2, 7, 0],
        "y": [4, 7, 5, 1],
        "z": [9, 3, 5, 1]
    }
)

df_renamed = df.rename(columns={"x": "col_A", "y": "col_B", "z": "col_C"})
print("After renaming multiple columns:")
print(df_renamed)

After renaming multiple columns:
   col_A  col_B  col_C
0      5      4      9
1      2      7      3
2      7      5      5
3      0      1      1

Using inplace Parameter

Set inplace=True to modify the original DataFrame directly ?

import pandas as pd

df = pd.DataFrame(
    {
        "x": [5, 2, 7, 0],
        "y": [4, 7, 5, 1]
    }
)

print("Original DataFrame:")
print(df)

df.rename(columns={"x": "Value_X", "y": "Value_Y"}, inplace=True)
print("\nAfter inplace renaming:")
print(df)

Original DataFrame:
   x  y
0  5  4
1  2  7
2  7  5
3  0  1

After inplace renaming:
   Value_X  Value_Y
0        5        4
1        2        7
2        7        5
3        0        1

Key Parameters

Conclusion

The rename() method provides a flexible way to rename DataFrame columns. Use dictionary mapping for specific columns and set inplace=True to modify the original DataFrame directly.