How to get column index from column name in Python Pandas?

To get column index from column name in Python Pandas, we can use the get_loc() method on the DataFrame's columns Index object.

Syntax

df.columns.get_loc(column_name)

Parameters

• column_name − The name of the column whose index you want to find

Return Value

Returns an integer representing the positional index of the specified column.

Example

Let's create a DataFrame and find the index of different columns ?

import pandas as pd

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

print("Input DataFrame:")
print(df)
print("\nColumns in the DataFrame:", list(df.columns))

# Get index for different columns
column_name = "z"
column_index = df.columns.get_loc(column_name)
print(f"\nIndex of column '{column_name}': {column_index}")

column_name = "x"
column_index = df.columns.get_loc(column_name)
print(f"Index of column '{column_name}': {column_index}")

column_name = "y"
column_index = df.columns.get_loc(column_name)
print(f"Index of column '{column_name}': {column_index}")

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

Columns in the DataFrame: ['x', 'y', 'z']

Index of column 'z': 2
Index of column 'x': 0
Index of column 'y': 1

Alternative Method Using List Index

You can also convert columns to a list and use the index() method ?

import pandas as pd

df = pd.DataFrame({
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "city": ["NYC", "LA", "Chicago"]
})

# Using list index method
column_index = list(df.columns).index("age")
print(f"Index of 'age' column: {column_index}")

# Using get_loc method
column_index = df.columns.get_loc("city")
print(f"Index of 'city' column: {column_index}")

Index of 'age' column: 1
Index of 'city' column: 2

Comparison

Conclusion

Use df.columns.get_loc(column_name) to get the positional index of a column by name. This method is efficient and specifically designed for pandas Index objects.