Chapter 1 Understanding the Assign Function

The assign function in Pandas serves as a powerful method for adding new columns to a DataFrame, utilizing existing columns or other forms of data. This function yields a new DataFrame that includes the additional columns, leaving the original DataFrame unchanged.

To begin using the assign function, first, ensure you have the pandas library imported:

import pandas as pd

Once imported, you can apply the assign function to a DataFrame to generate one or more new columns. Below is an illustration of how to use the assign function to add a new column to a DataFrame:

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

df = df.assign(C=df['A'] + df['B'])

print(df)

This snippet creates a DataFrame with columns A and B, and subsequently employs the assign function to introduce a new column C, which is the result of summing columns A and B. The output DataFrame appears as follows:

A B C

0 1 4 5

1 2 5 7

2 3 6 9

Moreover, the assign function can also generate new columns based on a scalar value or by applying a function to existing columns. For instance:

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

df = df.assign(C=lambda x: x['A'] * x['B'])

print(df)

In this example, a DataFrame is created with columns A and B, and the assign function is used to create a new column C, which represents the product of columns A and B. The resulting DataFrame is:

A B C

0 1 4 4

1 2 5 10

2 3 6 18

You can also utilize the assign function to add multiple columns simultaneously. Consider the following example:

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

df = df.assign(C=lambda x: x['A'] * x['B'], D=lambda x: x['A'] - x['B'])

print(df)

In this scenario, the DataFrame is established with columns A and B, and the assign function is employed to create two new columns: C, which is the product of A and B, and D, which represents the difference between A and B. The resulting DataFrame appears as follows:

A B C D

0 1 4 4 -3

1 2 5 10 -3

2 3 6

Explore how to use the assign method in a Pandas DataFrame effectively in the video above.

Chapter 2 Advanced Usage of Assign Function

In this video, learn how to add a column to a Pandas DataFrame in Python with two examples, demonstrating the append list as a variable and the assign() function.