Checking for missing values in a Dataset using Pandas

Last update on December 21 2024 09:14:41 (UTC/GMT +8 hours)

Pandas: Machine Learning Integration Exercise-2 with Solution

Write a Pandas program to check for missing values in a dataset.

This exercise demonstrates how to check for missing values in a dataset, which is a common pre-processing step in machine learning.

Sample Solution :

Code :

import pandas as pd
# Load the dataset
df = pd.read_csv('data.csv')
# Check for missing values in the dataset
missing_values = df.isna().sum()
# Output the result
print(missing_values)

Output:

ID        0
Name      0
Age       1
Gender    0
Salary    1
Target    0
dtype: int64

Explanation:

• Loaded the dataset using pd.read_csv().
• Used isna().sum() to check for missing values in each column.
• Displayed the number of missing values in each column.

Python-Pandas Code Editor:

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