As part of my Data Analytics learning journey, I created a small Pandas practice script that covers the most used operations in real-world data cleaning and analysis.
🔹 What I Practiced
Creating a DataFrame using Python dictionaries
Selecting columns and rows using loc[] and iloc[]
Row slicing and multiple row selection
Conditional filtering using operators and isin()
Handling missing data using:
isnull()
dropna()
fillna() with custom or mean values
🔹 Why This Matters
These are the foundation skills every Data Analyst needs before moving to advanced topics like merge, groupby, and visualization.
It helped me understand how to access, filter, and clean datasets efficiently.
🔹 Code & Repo
👉 Check out the complete code on GitHub:
🔗 GitHub Repository : https://github.com/Ashokkumarrk/Pandas-Practices/tree/main
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