Udemy - Build A Data Analysis Library From Scratch In Python [TP]

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[Tutorialsplanet.NET] Udemy - Build a Data Analysis Library from Scratch in Python 1. Project Genesis
  • 1. Project Overview.mp4 (145.8 MB)
  • 1. Project Overview.vtt (10.1 KB)
  • 1.1 GitHub Home Page.html (0.1 KB)
  • 2. Pandas Cub Examples.mp4 (253.8 MB)
  • 2. Pandas Cub Examples.vtt (14.4 KB)
  • 3. Downloading the Material from GitHub.mp4 (51.3 MB)
  • 3. Downloading the Material from GitHub.vtt (2.8 KB)
10. Pivot Tables
  • 1. Pivot Tables Part 1.mp4 (147.0 MB)
  • 1. Pivot Tables Part 1.vtt (13.9 KB)
  • 2. Pivot Tables Part 2.mp4 (79.9 MB)
  • 2. Pivot Tables Part 2.vtt (8.4 KB)
  • 3. Pivot Tables Part 3.mp4 (44.4 MB)
  • 3. Pivot Tables Part 3.vtt (4.0 KB)
  • 4. Pivot Tables Part 4.mp4 (104.5 MB)
  • 4. Pivot Tables Part 4.vtt (8.2 KB)
  • 5. Pivot Tables Part 5.mp4 (91.9 MB)
  • 5. Pivot Tables Part 5.vtt (8.6 KB)
11. Documentation, Strings, and Reading CSVs
  • 1. Automatically Add Documentation.mp4 (88.3 MB)
  • 1. Automatically Add Documentation.vtt (8.3 KB)
  • 2. String-only Methods.mp4 (164.9 MB)
  • 2. String-only Methods.vtt (13.9 KB)
  • 3. The read_csv Function part 1.mp4 (111.1 MB)
  • 3. The read_csv Function part 1.vtt (10.6 KB)
  • 4. The read_csv Function Part 2.mp4 (83.8 MB)
  • 4. The read_csv Function Part 2.vtt (8.1 KB)
  • 5. Conclusion.mp4 (18.4 MB)
  • 5. Conclusion.vtt (5.2 KB)
2. Environment Setup
  • 1. Opening the Project in VS Code.mp4 (58.4 MB)
  • 1. Opening the Project in VS Code.vtt (3.4 KB)
  • 2. Setting up the Development Environment.mp4 (157.6 MB)
  • 2. Setting up the Development Environment.vtt (8.7 KB)
  • 3. Test-Driven Development.mp4 (139.9 MB)
  • 3. Test-Driven Development.vtt (7.5 KB)
  • 4. Installing an IPython Kernel for Jupyter.mp4 (243.7 MB)
  • 4. Installing an IPython Kernel for Jupyter.vtt (13.1 KB)
3. Getting Ready to Code
  • 1. Inspecting the __init__.py File.mp4 (111.1 MB)
  • 1. Inspecting the __init__.py File.vtt (6.1 KB)
  • 2. Importing Pandas Cub.mp4 (113.4 MB)
  • 2. Importing Pandas Cub.vtt (6.4 KB)
  • 3. Manually Test in a Jupyter Notebook.mp4 (149.6 MB)
  • 3. Manually Test in a Jupyter Notebook.vtt (8.6 KB)
  • 4. Getting Ready to Start.mp4 (37.6 MB)
  • 4. Getting Ready to Start.vtt (2.0 KB)
4. DataFrame Construction
  • 1. Check DataFrame Constructor Input Types.mp4 (379.2 MB)
  • 1. Check DataFrame Constructor Input Types.vtt (19.4 KB)
  • 2. Check Array Lengths.mp4 (76.1 MB)
  • 2. Check Array Lengths.vtt (5.5 KB)
  • 3. Convert Unicode Arrays to Object.mp4 (142.4 MB)
  • 3. Convert Unicode Arrays to Object.vtt (10.3 KB)
5. Basic Properties and Visual Representation
  • 1. Implementing the __len__ Special Method.mp4 (114.6 MB)
  • 1. Implementing the __len__ Special Method.vtt (10.3 KB)
  • 2. Return Columns as a List.mp4 (69.0 MB)
  • 2. Return Columns as a List.vtt (6.6 KB)
  • 3. Set New Column Names.mp4 (127.4 MB)
  • 3. Set New Column Names.vtt (10.5 KB)
  • 4. The shape Property.mp4 (43.6 MB)
  • 4. The shape Property.vtt (4.0 KB)
  • 5. Visual Notebook Representation.mp4 (130.9 MB)
  • 5. Visual Notebook Representation.vtt (10.9 KB)
  • 6. The values Property.mp4 (36.3 MB)
  • 6. The values Property.vtt (3.3 KB)
  • 7. The dtypes Property.mp4 (114.7 MB)
  • 7. The dtypes Property.vtt (10.4 KB)
6. Subset Selection
  • 1. Select a Single Column.mp4 (74.4 MB)
  • 1. Select a Single Column.vtt (5.9 KB)
  • 10. Create a New Column.mp4 (186.6 MB)
  • 10. Create a New Column.vtt (14.5 KB)
  • 2. Select Multiple Columns.mp4 (47.7 MB)
  • 2. Select Multiple Columns.vtt (4.1 KB)
  • 3. Boolean Selection.mp4 (110.0 MB)
  • 3. Boolean Selection.vtt (9.7 KB)
  • 4. Check for Simultaneous Selection.mp4 (106.0 MB)
  • 4. Check for Simultaneous Selection.vtt (7.6 KB)
  • 5. Select a Single Cell.mp4 (114.6 MB)
  • 5. Select a Single Cell.vtt (9.0 KB)
  • 6. Select Rows as Booleans, Lists, or Slices.mp4 (127.8 MB)
  • 6. Select Rows as Booleans, Lists, or Slices.vtt (10.5 KB)
  • 7. Multiple Column Simultaneous Selection.mp4 (76.3 MB)
  • 7. Multiple Column Simultaneous Selection.vtt (6.2 KB)
  • 8. Column Slices.mp4 (99.6 MB)
  • 8. Column Slices.vtt (8.0 KB)
  • 9. Tab Completion for Columns.mp4 (29.2 MB)
  • 9. Tab Completion for Columns.vtt (3.9 KB)
7. Basic Methods
  • 1. head and tail Methods.mp4 (34.2 MB)
  • 1. head and tail Methods.vtt (3.5 KB)
  • 2. Generic Aggregation Methods.mp4 (95.1 MB)
  • 2. Generic Aggregation Methods.vtt (9.4 KB)
  • 3. The isna Method.mp4 (57.7 MB)
  • 3. The isna Method.vtt (5.1 KB)
  • 4. The count Method.mp4 (58.2 MB)
  • 4. The count Method.vtt (4.9 KB)
  • 5. The unique Method.mp4 (62.8 MB)
  • 5. The unique Method.vtt (5.9 KB)
  • 6. The nunique Method.mp4 (36.6 MB)
  • 6. The nunique Method.vtt (3.5 KB)
8. Value Counts
  • 1. The value_counts Method.mp4 (103.9 MB)
  • 1. The value_counts Method.vtt (8.8 KB)
  • 2. Normalize value_counts.mp4 (36.9 MB)
  • 2. Normalize value_counts.vtt (3.6 KB)
9. Other Methods and Operators
  • 1. The rename Method.mp4 (49.4 MB)
  • 1. The rename Method.vtt (4.4 KB)
  • 2. The drop Method.mp4 (40.6 MB)
  • 2. The drop Method.vtt (3.8 KB)
  • 3. Non-Aggregation Methods.mp4 (140.9 MB)

  • Description

    Udemy - Build A Data Analysis Library From Scratch In Python [TP]

    Immerse yourself in a long, comprehensive project that teaches advanced Python concepts to build an entire library

    For more Udemy Courses: https://tutorialsplanet.net



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Udemy - Build A Data Analysis Library From Scratch In Python [TP]

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Download torrent
5.8 GB
seeders:8
leechers:25
Udemy - Build A Data Analysis Library From Scratch In Python [TP]

Torrent hash: 225B1DC8D157562CFACC0AB5A20C2E1944B7ED4E