Pandas DataFrame.pop

Pandas DataFrame.pop

The DataFrame.pop method in pandas is used to remove a specific column from a DataFrame and return it as a Series. This is particularly useful when you want to extract and remove a column from a DataFrame in one step.

Syntax

The syntax for DataFrame.pop is:

DataFrame.pop(item)

Here, DataFrame refers to the pandas DataFrame, and item specifies the column label to be removed and returned.

Parameters

Returns

A pandas Series representing the removed column.

Examples

Removing a Column

Use the pop method to remove a column from a DataFrame and return it as a Series.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Remove the 'Age' column using pop
print("Removing 'Age' column:")
age_series = df.pop('Age')
print("Extracted Column:")
print(age_series)
print("\nDataFrame after removing 'Age':")
print(df)

Output

Removing 'Age' column:
Extracted Column:
0    25
1    30
2    35
Name: Age, dtype: int64

DataFrame after removing 'Age':
    Name  Salary
0  Arjun  70000
1    Ram  80000
2   Priya  90000

Using the Removed Column

The returned Series can be reused for further operations.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Remove the 'Salary' column and calculate its mean
salary_series = df.pop('Salary')
print("Mean of the 'Salary' column:")
print(salary_series.mean())

Output

Mean of the 'Salary' column:
80000.0

Attempting to Remove a Non-Existent Column

If you try to remove a column that doesn’t exist, a KeyError is raised.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Attempt to pop a non-existent column
try:
    df.pop('Department')
except KeyError as e:
    print("Error:", e)

Output

Error: 'Department'

Combining pop with Other Operations

The pop method can be combined with other pandas operations to streamline workflows.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Pop a column and add it as a new column after transformation
age_series = df.pop('Age')
df['Age in Months'] = age_series * 12
print("DataFrame after transforming and adding 'Age' back:")
print(df)

Output

DataFrame after transforming and adding 'Age' back:
    Name  Salary  Age in Months
0  Arjun  70000            300
1    Ram  80000            360
2   Priya  90000            420

Summary

In this tutorial, we explored the DataFrame.pop method in pandas. Key takeaways include:

• Using pop to remove and return a column as a Series.
• Handling errors when trying to remove non-existent columns.
• Reusing the returned Series for further operations.

The DataFrame.pop method is a powerful tool for efficiently removing and extracting columns from a DataFrame.