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Files

1. Get Bonus Downloads Here.url182 bytes
2. 1 - Introduction.mp432.7 MB
3. 2 - Course structure and installation.mp419.9 MB
4. 2 - Lecture notebook.txt135 bytes
5. 3 - Lecture notebook.txt110 bytes
6. 3 - Reading data.mp468.3 MB
7. 4 - Exploring a DataFrame.mp443.4 MB
8. 4 - Lecture notebook.txt121 bytes
9. 5 - Data types.mp487.8 MB
10. 5 - Lecture notebook.txt108 bytes
11. 6 - Column operations.mp4236.6 MB
12. 6 - Lecture notebook.txt116 bytes
13. 7 - Date manipulation.mp4181.9 MB
14. 7 - Lecture notebook.txt115 bytes
15. 8 - Lecture notebook.txt117 bytes
16. 8 - String manipulation.mp4154.9 MB
17. 9 - Categorical data.mp474.1 MB
18. 9 - Lecture notebook.txt114 bytes
19. 10 - Lecture notebook.txt112 bytes
20. 10 - Missing values.mp4144.8 MB
21. 11 - Lecture notebook.txt122 bytes
22. 11 - loc and iloc methods.mp4146.7 MB
23. 12 - Filtering DataFrames.mp4240.7 MB
24. 12 - Lecture notebook.txt118 bytes
25. 13 - Combining DataFrames.mp4120.4 MB
26. 13 - Lecture notebook.txt118 bytes
27. 14 - Lecture notebook.txt116 bytes
28. 14 - Merging DataFrames.mp4348.6 MB
29. 15 - Lecture notebook.txt118 bytes
30. 15 - Reshaping DataFrames.mp4101.5 MB
31. 16 - Data analysis.mp4246.9 MB
32. 16 - Lecture notebook.txt111 bytes
33. 17 - Data visualization.mp489.8 MB
34. 17 - Lecture notebook.txt116 bytes
35. 18 - Lecture notebook.txt136 bytes
36. 18 - Time series analysis with Pandas.mp4156.4 MB
37. 19 - Data cleaning and analysis 1 obesity dataset.mp4306.5 MB
38. 19 - Lecture notebook.txt154 bytes
39. 20 - Data cleaning and analysis 2 customer churn dataset.mp4165.4 MB
40. 20 - Lecture notebook.txt163 bytes
41. 21 - Lecture notebook.txt133 bytes
42. 21 - Python dictionaries with Pandas.mp477.9 MB
43. 22 - Lecture notebook.txt114 bytes
44. 22 - Pandas pipelines.mp472.0 MB
45. 23 - Lecture notebook.txt116 bytes
46. 23 - Styling DataFrames.mp479.7 MB
47. 24 - Functions not to forget.mp471.1 MB
48. 24 - Lecture notebook.txt125 bytes
49. Bonus Resources.txt386 bytes

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