Dropping rows with missing values using Pandas

Last update on December 21 2024 07:41:20 (UTC/GMT +8 hours)

Pandas: Machine Learning Integration Exercise-3 with Solution

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.

Python-Pandas Code Editor:

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