Pandas — Home

Learn Pandas

Master Pandas for data manipulation and analysis.

Course contents

1. Introduction - What is Pandas
2. Get Started - Your first Pandas program
3. Installation - Setting up Pandas
4. Series - 1D labeled array
5. DataFrame - 2D labeled data structure
6. CSV - Reading/writing CSV
7. JSON - Working with JSON
8. Excel - Excel files
9. SQL - Database operations
10. Selection - Selecting data
11. Filtering - Filtering data
12. Indexing - Index operations
13. Missing Data - Handling NaN
14. Duplicates - Removing duplicates
15. Apply - Applying functions
16. GroupBy - Grouping data
17. Merge - Combining DataFrames
18. Join - Joining DataFrames
19. Concat - Concatenating DataFrames
20. Reshape - Pivot, melt, stack
21. Sort - Sorting data
22. String - String operations
23. DateTime - Date/time handling
24. Timedelta - Time differences
25. Categorical - Categorical data
26. Visualization - Plotting
27. Style - DataFrame styling
28. Export - Saving data
29. Performance - Optimization
30. Memory - Memory management
31. Pipes - Method chaining
32. Windows - Rolling/expanding
33. Cross - Cross-tabulation
34. Cut - Binning data
35. Get Dummies - One-hot encoding
36. Eval/Query - Fast expressions
37. Stata - Stata files
38. Parquet - Columnar format
39. HDF5 - HDF5 format
40. Clipboard - Clipboard data
41. MultiIndex - Hierarchical index
42. Resample - Time resampling
43. Replace - Replacing values
44. Best Practices - Tips and patterns

Who is this course for?

• Data analysts
• Data scientists
• Python developers
• Anyone working with data

Prerequisites

• Python basics
• NumPy fundamentals

Resources

• Pandas Documentation
• Pandas Cookbook