How can I validate data for my machine learning model in Python?

How can I validate data for my machine learning model in Python?

You can validate data by checking for missing values, outliers, and ensuring the data types are correct. Libraries like Pandas and Scikit-learn can help.

What are some common techniques for handling missing values?

Common techniques include removing rows with missing values, filling them with the mean/median, or using interpolation.

How do I detect outliers in my dataset?

You can use methods like the Z-score, IQR (Interquartile Range), or visualization techniques like box plots to detect outliers.

Can you show me a code example for data validation?

Sure! Here's a simple example using Pandas:

import pandas as pd

df = pd.read_csv('data.csv')

# Check for missing values
print(df.isnull().sum())

# Fill missing values with mean
df.fillna(df.mean(), inplace=True)