#14 NumPy, Matplotlib & Seaborn Explained | Data Science for Beginners in Tamil

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In Episode 14, we cover essential Python libraries—NumPy, Matplotlib, and Seaborn—to help you perform numeric operations and create compelling data visualizations. Perfect for beginners and intermediate learners wanting to boost their data analysis skills.

Learn how to:
✅ Efficiently manipulate arrays with NumPy (including repeat functions and axis operations)
✅ Visualize data distributions using histograms and bar charts with Matplotlib
✅ Understand discrete vs continuous data for smarter plotting
✅ Handle insurance data sets to analyze real-world examples
✅ Troubleshoot common Python module import errors

⏳Timestamps for Quick Navigation:
[00:01] – Introduction & Episode Overview
[01:14] – Importing NumPy: Best Practices & Case Sensitivity in Python
[02:29] – NumPy Array Operations: Repeating Elements & Axis Explained
[04:37] – Working with DataFrames: Insurance Data Example
[06:55] – Importing Matplotlib & Troubleshooting Installation Issues
[09:28] – Creating Histograms: Visualizing Insurance Charges Distribution
[11:48] – Discrete vs Continuous Data: What You Need to Know
[15:00] – Introduction to Seaborn for Advanced Data Visualization
[17:32] – Understanding Python Libraries: What They Are & Why Use Them
[18:43] – Summary & What’s Next

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Python data analysis tutorial
NumPy array operations explained
Matplotlib histogram tutorial
Python data visualization for beginners
Discrete vs continuous data Python
Python Seaborn tutorial
Insurance data analysis Python
Python libraries for data science
Beginner Python data visualization
Data science with Python libraries