How to apply a function to multiple columns in Pandas

How to apply a function to multiple columns in Pandas

To apply a function to multiple columns in Pandas, you can use the apply method. This method allows you to apply a function to a DataFrame or a specific column or set of columns.

For example, consider the following DataFrame:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3, 4, 5],
    'B': [10, 20, 30, 40, 50],
    'C': [100, 200, 300, 400, 500]
})

This DataFrame has three columns A, B, and C, with five rows of data.

To apply a function to all the columns in this DataFrame, you could do the following:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3, 4, 5],
    'B': [10, 20, 30, 40, 50],
    'C': [100, 200, 300, 400, 500]
})

# Define the function to apply
def square(x):
    return x ** 2

# Apply the function to the DataFrame
df_squared = df.apply(square)

# Print the resulting DataFrame
print(df_squared)

In the code above, the apply method is applied to the DataFrame, and the square function is passed as an argument.

This tells the apply method to apply the square function to each column in the DataFrame. The result is a new DataFrame object containing the squared values for each column.

You can also use the apply method to apply a function to a specific column or set of columns in a DataFrame. For example, if you wanted to apply the square function to only column B, you could do the following:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3, 4, 5],
    'B': [10, 20, 30, 40, 50],
    'C': [100, 200, 300, 400, 500]
})

# Define the function to apply
def square(x):
    return x ** 2

# Apply the function to column B
df_squared = df['B'].apply(square)

# Print the resulting Series
print(df_squared)

In the code above, the apply method is applied to the B column of the DataFrame, and the square function is passed as an argument.

This tells the apply method to apply the square function to the B column.

The result is a new Series object containing the squared values for the B column.