When working with data in Python, it is common to have multiple columns in a dataset. Sometimes, you may need to add the same header to multiple columns. In this article, we will explore three different ways to achieve this task.

Method 1: Using a Loop

One way to add the same header to multiple columns is by using a loop. We can iterate over the columns and assign the same header to each column.

import pandas as pd

# Create a sample dataframe
data = {'Column1': [1, 2, 3],
        'Column2': [4, 5, 6],
        'Column3': [7, 8, 9]}

df = pd.DataFrame(data)

# Add the same header to multiple columns
header = 'Header'
for column in df.columns:
    df.rename(columns={column: f'{header}_{column}'}, inplace=True)

print(df)

This method uses the rename() function from the pandas library to assign the new header to each column. The loop iterates over each column in the dataframe and renames it by appending the header to the original column name.

Method 2: Using List Comprehension

Another way to add the same header to multiple columns is by using list comprehension. We can create a new list of column names by appending the header to each original column name.

import pandas as pd

# Create a sample dataframe
data = {'Column1': [1, 2, 3],
        'Column2': [4, 5, 6],
        'Column3': [7, 8, 9]}

df = pd.DataFrame(data)

# Add the same header to multiple columns
header = 'Header'
df.columns = [f'{header}_{column}' for column in df.columns]

print(df)

In this method, we use list comprehension to create a new list of column names. Each column name is modified by appending the header to the original column name. Finally, we assign the new list of column names to the dataframe’s columns attribute.

Method 3: Using the add_prefix() Function

The pandas library provides a built-in function called add_prefix() that can be used to add a prefix to each column name in a dataframe.

import pandas as pd

# Create a sample dataframe
data = {'Column1': [1, 2, 3],
        'Column2': [4, 5, 6],
        'Column3': [7, 8, 9]}

df = pd.DataFrame(data)

# Add the same header to multiple columns
header = 'Header'
df = df.add_prefix(f'{header}_')

print(df)

In this method, we use the add_prefix() function to add the header as a prefix to each column name in the dataframe. The function returns a new dataframe with the modified column names.

After exploring these three methods, it is clear that the third method using the add_prefix() function is the most concise and efficient way to add the same header to multiple columns in Python. It provides a built-in solution that requires fewer lines of code and is easier to read and understand.