Master Pandas in 1 Hour: Data Cleaning, loc vs iloc & Indexing | Python Basics

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Welcome back to Lecture 29 of the Python Programming & Data Science Basics self-paced recorded video course!
In our last lecture, we explored NumPy, but real-world data isn't just numbers—it contains names, dates, addresses, and mixed data types. Today, we are meeting the superstar of data analytics: Pandas!. If NumPy is a superfast engine, Pandas is the entire car equipped with steering, seats, and AC—easy to drive with immense underlying power.

In this comprehensive, hands-on Google Colab tutorial, we will unlock the true power of tabular data and master structured data analysis.

⏳ Video Chapters (Timestamps):
00:00 - Introduction: NumPy vs Pandas
00:54 - Topics Covered in this Lecture
01:25 - Why Pandas? High-Level Data Manipulation
02:16 - Key Advantages: Performance, Ease of Use & Versatility
03:01 - Common Applications: Data Wrangling, EDA & Feature Engineering
04:05 - Pandas Data Structures: 1D Series Explained
07:23 - Pandas Data Structures: 2D DataFrames Explained
10:22 - Essential Attributes: shape, columns, index & dtypes
14:32 - Importing Data: read_csv & read_excel Functions
24:16 - Exporting Data: Saving Files & Using index=False
29:42 - Pro Tip: File Encoding (utf-8-sig) for Special Fonts
34:03 - Data Selection & Indexing: Single vs Multiple Columns
37:25 - Row Selection: Loc (Label-based) vs iLoc (Integer-based)
41:31 - Conditional Filtering (Boolean Indexing)
46:14 - Data Cleaning: Handling Missing Values (isnull, fillna, dropna)
57:40 - Removing Duplicate Records (drop_duplicates, subset, keep)
01:07:02 - Correcting Data Types (astype & to_datetime)
01:16:56 - Memory Optimization: Converting Columns to Category Type
01:23:21 - Professional Tip & Conclusion

📌 About This Course:
This video is part of a complete, self-paced recorded video course designed to take you from absolute beginner to an advanced level in Python and Data Science. If you found this tutorial helpful, please Like 👍, Share, and Subscribe 🔔 for more!
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