🧹 Data Cleaning with Dropna
Missing data is a common problem. Pandas provides `dropna()` to easily remove rows or columns with null values.
💡 Quick Tip:
Mastering this concept will significantly boost your Python data science skills!
💻 Code Example:
import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan, 3]})
clean_df = df.dropna()
print(clean_df)| Feature | Benefit |
|---|---|
| Efficiency | Optimized for performance |
| Simplicity | Easy to read and write |
Keep exploring and happy coding! 🚀