This is a bite-size course to learn Python programming for data visualization. In the CRISP-DM data mining process, data visualization is at the data understanding stage. This course also covers data processing, which is at the data preparation stage.

Content:

1. Getting Started
2. Getting Started 2
3. Getting Started 3
4. Data Mining Process
5. Download Data set
6. Read Data set
7. Bar Chart
8. Histogram
9. Line Chart
10. Multiple Line Chart
11. Pie Chart
12. Box Plot
13. Scatterplot
14. Scatterplot Matrix
15. Save to Image
16. Bar Chart with Seaborn
17. Histogram with Seaborn
18. Line Chart with Seaborn
19. Scatterplot with Seaborn
20. Categorical Plot with Seaborn
21. Boxplot  with Seaborn
22. Scatterplot Matrix  with Seaborn
23. Save to Image
24. Interactive Charts
25. Interactive Charts
26. Interactive Charts
27. Interactive Charts
28. Data Processing: DF.head()
29. Data Processing: DF.tail()
30. Data Processing: DF.describe()
31. Data Processing: Select Variables
32. Data Processing: Select Rows
33. Data Processing: Select Variables and Rows
34. Data Processing: Remove Variables
35. Data Processing: Append Rows
36. Data Processing: Sort Variables
37. Data Processing: Rename Variables
38. Data Processing: GroupBY
39. Data Processing: Remove Missing Values
40. Data Processing: Is There Missing Values
41. Data Processing: Replace Missing Values
42. Data Processing: Remove Duplicates