Adding New Columns to Pandas DataFrames

Pandas is a powerful library in Python for data manipulation and analysis. One common operation when working with DataFrames is adding new columns. In this tutorial, we will explore different ways to add new columns to a DataFrame.

Introduction to DataFrames

Before diving into the topic of adding new columns, let’s briefly introduce what a DataFrame is. A DataFrame in pandas is a two-dimensional table of data with rows and columns. It’s similar to an Excel spreadsheet or a table in a relational database. You can create a DataFrame from various sources such as dictionaries, lists, or even CSV files.

Adding New Columns

There are several ways to add new columns to a DataFrame:

1. Direct Assignment

The most straightforward way to add a new column is by directly assigning it using the square bracket [] notation.

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['John', 'Anna', 'Peter', 'Linda'],
        'Age': [28, 24, 35, 32]}
df = pd.DataFrame(data)

# Add a new column
df['Country'] = ['USA', 'UK', 'Australia', 'Germany']

print(df)

Output:

    Name  Age    Country
0   John   28        USA
1   Anna   24         UK
2  Peter   35  Australia
3  Linda   32     Germany

2. Using the assign Method

Another way to add new columns is by using the assign method, which returns a new DataFrame with the added column.

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['John', 'Anna', 'Peter', 'Linda'],
        'Age': [28, 24, 35, 32]}
df = pd.DataFrame(data)

# Add a new column using assign
df = df.assign(Country=['USA', 'UK', 'Australia', 'Germany'])

print(df)

Output:

    Name  Age    Country
0   John   28        USA
1   Anna   24         UK
2  Peter   35  Australia
3  Linda   32     Germany

3. Using the insert Method

You can also add a new column at a specific position using the insert method.

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['John', 'Anna', 'Peter', 'Linda'],
        'Age': [28, 24, 35, 32]}
df = pd.DataFrame(data)

# Add a new column at the first position
df.insert(0, 'Country', ['USA', 'UK', 'Australia', 'Germany'])

print(df)

Output:

    Country   Name  Age
0        USA   John   28
1         UK   Anna   24
2  Australia  Peter   35
3     Germany  Linda   32

Best Practices

When adding new columns to a DataFrame, keep the following best practices in mind:

• Use meaningful column names that describe the data.
• Avoid using reserved keywords as column names.
• Use the assign method when working with method chains to avoid creating intermediate DataFrames.

By following these guidelines and understanding the different ways to add new columns, you can efficiently manipulate your DataFrames and perform complex data analysis tasks.