Checking for missing values in a Dataset using Pandas
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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