From Spreadsheets to DataFrames

on YouTube ↗02h 52m

" summary

Quick yes or no: this walks an Excel user through concrete steps not platitudes. It claims to replace tedious spreadsheets by actually downloading SEC data, parsing and transforming with Requests and Pandas, and building a small Flask app that visualizes results. It demos environment setup with Docker and an Airflow scheduling example, shows numbers (millions of rows loaded in seconds), and ends with a refactored script that works end to end so you can replicate it. hands on with Pandas

AI-written summary · about

" chapters (47)

1. 0:00Start
2. 0:38Section One
3. 2:33Real World Python Example
4. 7:33Activate Spreadsheets to Data Frames
5. 9:24Anaconda Navigator
6. 10:02Using an Ide
7. 13:36Comments
8. 14:00Keywords
9. 15:59Text Functions
10. 16:56Input Function
11. 19:27Data Types
12. 20:37Lists
13. 21:55Comparison Operators
14. 22:20Pre-Installed Add-Ins
15. 22:32Excel Add-Ins
16. 24:32The Python Package Index
17. 26:18File Types
18. 27:33Open a File in Python
19. 29:32Data Structures
20. 30:16Dictionaries
21. 32:38For Loop
22. 33:27String Formatting
23. 35:33Sneak Peek of Pandas
24. 36:12Error Messages
25. 36:22Fix Your Error Messages
26. 37:41Install Our Third-Party Packages
27. 38:19Run the Jupiter Notebook
28. 40:31Types of Data Types
29. 41:50Variable Names
30. 43:25Built-In Functions
31. 46:35Methods
32. 51:12Indexing and Slicing
33. 57:49Part Two of the Notebooks
34. 58:57Jupiter Notebooks
35. 1:00:50Lists and Dictionaries
36. 1:05:52Standard Library
37. 1:09:18Path To Create a File Path Dynamically
38. 1:10:04Check if the File Exists
39. 1:10:49Opening a File
40. 1:13:59Find the Location of a Value in a String
41. 1:19:17Preferred Method in Python
42. 1:21:55For Loops
43. 1:26:51Csv Reader
44. 1:27:04The Csv Reader
45. 1:27:35Enumerate
46. 1:35:06Pretty Print
47. 1:39:39Functions

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