Udemy – Python Step by Step - Build a Data Analysis Program 2015

1. 01 Getting Started/001 A few words about Python.mp417.51MB
2. 01 Getting Started/002 Easily installing Python and its specialized libraries.mp433.83MB
3. 01 Getting Started/003 Spyder and iPython.mp413.35MB
4. 02 Python Basics/001 Variables.mp45.32MB
5. 02 Python Basics/002 Strings and numbers.mp410.64MB
6. 02 Python Basics/003 If, else, and indentation.mp49.3MB
7. 02 Python Basics/004 Functions.mp46.57MB
8. 02 Python Basics/005 Sequences.mp45.52MB
9. 02 Python Basics/006 Collections.mp46.92MB
10. 02 Python Basics/007 Working with sequences and strings.mp417.03MB
11. 02 Python Basics/008 Iterating.mp411.1MB
12. 03 Working with Files and Folders/001 Working with files.mp411.19MB
13. 03 Working with Files and Folders/002 Working with folders.mp49.94MB
14. 03 Working with Files and Folders/003 Handling files easily.mp43.6MB
15. 03 Working with Files and Folders/004 Manipulating directory paths.mp420.32MB
16. 03 Working with Files and Folders/005 Iterating through files.mp424.71MB
17. 04 Downloading Files from FTP Sites/001 Introduction to section Downloading files from FTP sites.mp42.8MB
18. 04 Downloading Files from FTP Sites/002 Logging in to an FTP site and browsing through FTP files.mp421.73MB
19. 04 Downloading Files from FTP Sites/003 Running Python code from the editor.mp418.16MB
20. 04 Downloading Files from FTP Sites/004 Creating an FTP function.mp49.34MB
21. 04 Downloading Files from FTP Sites/005 Downloading an FTP file.mp450.51MB
22. 04 Downloading Files from FTP Sites/006 Practical No.1 Creating a FTP File Downloader.mp474.8MB
23. 05 Working with Archive Files/001 Extracting ZIP, TAR, GZ and other archive file formats.mp412.81MB
24. 05 Working with Archive Files/002 Extracting RAR files.mp48.63MB
25. 05 Working with Archive Files/003 Practical No.2 Creating a batch archive extractor.mp432.28MB
26. 06 Reading and Writing TXT and CSV Data Files/001 Introduction to section Reading and writing TXT and CSV data files.mp44.01MB
27. 06 Reading and Writing TXT and CSV Data Files/002 Reading delimited TXT and CSV files.mp435.89MB
28. 06 Reading and Writing TXT and CSV Data Files/003 Exporting data back to files.mp421.06MB
29. 06 Reading and Writing TXT and CSV Data Files/004 Reading fixed width TXT files.mp48.96MB
30. 06 Reading and Writing TXT and CSV Data Files/005 Exporting data back to HTML and other fIle formats.mp44.81MB
31. 07 A tour with pandas/001 Introducing pandas - the great Python data analysis library.mp425.48MB
32. 07 A tour with pandas/002 Practical No.4 Calculating and adding columns to CSV files.mp426.5MB
33. 08 Concatenating and Joining Tables of Data with Pandas/001 Practical No.5 Concatenating multiple CSV files.mp438.33MB
34. 08 Concatenating and Joining Tables of Data with Pandas/002 Practical No. 6 Joining data based on a matching column.mp425.19MB
35. 09 Pivoting Data/001 Practical No. 7 Pivoting large amounts of data.mp448.2MB
36. 10 Visualizing Data/001 How to perform visualizations in Python.mp416.15MB
37. 10 Visualizing Data/002 More visualization techniques.mp471.39MB
38. 10 Visualizing Data/003 Practical No. 8 Generating an image file graph.mp421.66MB
39. 11 Mapping Spatial Data/001 Creating KML Google Earth files.mp418.98MB
40. 11 Mapping Spatial Data/002 Practical No, 9 Creating KML Google Earth fIles from CSV.mp456.94MB
41. 12 Putting everything together/001 Practical No. 9 Polishing the program, I.mp427.34MB
42. 12 Putting everything together/002 Practical No. 10 Polishing the program, II.mp438.44MB
43. 12 Putting everything together/003 Practical No. 11 Creating a Python module out of your program.mp434.02MB