Dropping rows with missing values using Pandas

Last update on May 06 2025 13:19:40 (UTC/GMT +8 hours)

3. Dropping Rows with Missing Values from a Dataset

Write a Pandas program to drop rows with missing values from a dataset.

This exercise demonstrates how to remove rows with missing values from the dataset using dropna().

Sample Solution :

Code :

import pandas as pd

# Load the dataset
df = pd.read_csv('data.csv')

# Drop rows with missing values
df_cleaned = df.dropna()

# Output the cleaned dataset
print(df_cleaned)

Output:

   ID      Name   Age  Gender   Salary  Target
0   1      Sara  25.0  Female  50000.0       0
1   2    Ophrah  30.0    Male  60000.0       1
2   3    Torben  22.0    Male  70000.0       0
3   4  Masaharu  35.0    Male  80000.0       1

Explanation:

Loaded the dataset using Pandas.
Used dropna() to remove rows that contain any missing values.
Displayed the cleaned dataset.

For more Practice: Solve these Related Problems:

Write a Pandas program to drop rows with missing values only in specific columns and report the change in DataFrame size.
Write a Pandas program to drop rows with missing values and then reset the index of the resulting DataFrame.
Write a Pandas program to drop rows that have more than a specified number of missing entries.
Write a Pandas program to drop rows with missing values and compare summary statistics before and after the operation.

Go to:

Python-Pandas Code Editor:

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Next: Filling Missing Values with the Mean.