Udemy - Data Processing - Transformation - Complete Edition Python ETL

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3.2 GB
  • Uploaded Byfreecoursewb
  • Downloads58
  • Last checkedFeb. 20th '22
  • Date uploadedFeb. 18th '22
  • Seeders 5
  • Leechers2

Infohash : D4866E582C48AEDBC69993E167EEBD267A4F1D34

Data Processing/Transformation: Complete Edition Python ETL



https://DevCourseWeb.com

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 3.12 GB | Duration: 7h 12m

ETL | PYTHON | PANDAS | KNIME | DATA TRANSFORMATION

What you'll learn
You will be able to understand how does transformation happens in industry
You will be able to use PANDAS, a python library, to transform raw dataset into required format
You will be able to use KNME, an analytical tool, to perform transformation
You will be able to learn difference between using a tool and a programming language to perform transformation

Description
Requirements

Files:

[ DevCourseWeb.com ] Udemy - Data Processing - Transformation - Complete Edition Python ETL
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Basic Setup
    • 1. Setup Python & Jupyter.mp4 (38.0 MB)
    • 1. Setup Python & Jupyter.srt (7.7 KB)
    • 2. Setup KNIME.mp4 (12.3 MB)
    • 2. Setup KNIME.srt (2.7 KB)
    2. Getting Started
    • 1. Understanding Udemy.mp4 (29.5 MB)
    • 1. Understanding Udemy.srt (6.7 KB)
    • 2. Attachments.mp4 (4.4 MB)
    • 2. Attachments.srt (1.1 KB)
    • 2.1 Amazon e-commerce data.csv (3.0 MB)
    • 2.10 calendar_output.csv (68.3 MB)
    • 2.11 calendar_output.csv (63.7 MB)
    • 2.12 calendar_output.csv (68.3 MB)
    • 2.13 listings_output.csv (8.2 MB)
    • 2.14 listings_output.csv (8.2 MB)
    • 2.15 listings_output.xlsx (3.8 MB)
    • 2.16 listings_output.xlsx (3.8 MB)
    • 2.17 listings.csv (9.1 MB)
    • 2.18 reviews_detailed.csv (170.3 MB)
    • 2.19 Sales data Unpivot.csv (0.3 KB)
    • 2.2 Amazon_e-commerce_data.xlsx (9.0 MB)
    • 2.20 Seller Data.xlsx (246.0 KB)
    • 2.3 Amazon_output_2.xlsx (8.1 MB)
    • 2.4 Amazon_output.xlsx (6.0 MB)
    • 2.5 Amzaon_output_1.xlsx (5.2 MB)
    • 2.6 calendar 1.csv (20.8 MB)
    • 2.7 calendar 2.csv (21.2 MB)
    • 2.8 calendar 3.csv (21.5 MB)
    • 2.9 calendar_output.csv (63.7 MB)
    3. Python Basics
    • 1. Variables.mp4 (29.0 MB)
    • 1. Variables.srt (11.1 KB)
    • 1.1 Python variables & Datatypes.pptx (5.3 MB)
    • 2. Lists.mp4 (29.7 MB)
    • 2. Lists.srt (11.8 KB)
    • 2.1 Lists in Python.pdf (61.8 KB)
    • 3. Tuples and Sets.mp4 (25.7 MB)
    • 3. Tuples and Sets.srt (9.2 KB)
    • 3.1 Tuples and Sets.pptx (426.0 KB)
    • 4. Dictionaries.mp4 (28.1 MB)
    • 4. Dictionaries.srt (9.3 KB)
    • 4.1 Dictionaries.pptx (423.1 KB)
    • 5. Conditions.mp4 (33.3 MB)
    • 5. Conditions.srt (12.5 KB)
    • 5.1 Python Conditions.pptx (427.5 KB)
    • 6. Functions.mp4 (40.3 MB)
    • 6. Functions.srt (16.6 KB)
    • 6.1 Python Functions.pptx (422.4 KB)
    • 7. Loops.mp4 (29.1 MB)
    • 7. Loops.srt (12.2 KB)
    • 7.1 Python Loops.pptx (463.3 KB)
    4. PANDAS Basics
    • 1. Introduction.mp4 (13.1 MB)
    • 1. Introduction.srt (4.7 KB)
    • 1.1 0. Pandas intro.pptx (789.2 KB)
    • 10. High level description (part 2).mp4 (44.2 MB)
    • 10. High level description (part 2).srt (8.5 KB)
    • 11. Unpivot.mp4 (33.1 MB)
    • 11. Unpivot.srt (10.3 KB)
    • 11.1 9. Pandas Unpivot.pptx (419.6 KB)
    • 12. Save Data.mp4 (15.0 MB)
    • 12. Save Data.srt (3.9 KB)
    • 12.1 10. Pandas Save data.pptx (414.8 KB)
    • 13. Joins.mp4 (39.6 MB)
    • 13. Joins.srt (12.0 KB)
    • 13.1 11. Pandas Joins.pptx (696.6 KB)
    • 14. Joins extensive example.mp4 (43.9 MB)
    • 14. Joins extensive example.srt (8.8 KB)
    • 14.1 Seller Data.xlsx (246.0 KB)
    • 2. Create Dataframe & indexing.mp4 (35.0 MB)
    • 2. Create Dataframe & indexing.srt (11.7 KB)
    • 2.1 1. Pandas Creating and Indexing.pptx (476.8 KB)
    • 2.2 Amazon e-commerce data.csv (3.0 MB)
    • 3. Loading & Reading.mp4 (26.2 MB)
    • 3. Loading & Reading.srt (6.0 KB)
    • 3.1 2. Pandas Loading data & reading.pptx (414.7 KB)
    • 4. Adding & Deleting Column.mp4 (35.5 MB)
    • 4. Adding & Deleting Column.srt (9.5 KB)
    • 4.1 3. Pandas Adding and Deleting.pptx (419.4 KB)
    • 5. Concatenate.mp4 (20.2 MB)
    • 5. Concatenate.srt (6.1 KB)
    • 5.1 4. Pandas Concatenate.pptx (417.5 KB)
    • 6. Filtering rows.mp4 (29.7 MB)
    • 6. Filtering rows.srt (8.6 KB)
    • 6.1 5. Pandas Filtering rows.pptx (419.3 KB)
    • 7. Iterate each row.mp4 (40.1 MB)
    • 7. Iterate each row.srt (10.5 KB)
    • 7.1 6. Pandas Iterate each row.pptx (414.8 KB)
    • 8. Re arranging columns.mp4 (15.5 MB)
    • 8. Re arranging columns.srt (3.1 KB)
    • 8.1 7. Pandas Re arranging columns.pptx (415.5 KB)
    • 9. High level description (part 1).mp4 (47.6 MB)
    • 9. High level description (part 1).srt (15.1 KB)
    • 9.1 8. Pandas High level description (2 parts).pptx (438.8 KB)
    5. PANDAS Project
    • 1. Part 1.mp4 (98.8 MB)
    • 1. Part 1.srt (18.7 KB)
    • 1.1 Amazon_e-commerce_data.xlsx (9.0 MB)
    • 2. Part 2.mp4 (39.1 MB)
    • 2. Part 2.srt (9.7 KB)
    • 3. Part 3.mp4 (66.7 MB)
    • 3. Part 3.srt (13.9 KB)
    • 4. Part 4.mp4 (42.1 MB)
    • 4. Part 4.srt (7.7 KB)
    • 5. Part 5.mp4 (48.8 MB)
    • 5. Part 5.srt (8.8 KB)
    • 6. Part 6.mp4 (61.2 MB)
    • 6. Part 6.srt (10.4 KB)
    • 6.1 Amzaon_output_1.xlsx (5.2 MB)
    6. KNIME
    • 1. Introduction.mp4 (12.7 MB)
    • 1. Introduction.srt (4.4 KB)
    • 1.1 What is KNIME.pptx (237.0 KB)
    • 10. Column Splitter.mp4 (20.2 MB)
    • 10. Column Splitter.srt (3.2 KB)
    • 11. Metanode.mp4 (33.9 MB)
    • 11. Metanode.srt (6.6 KB)
    • 12. Excel Writer.mp4 (20.3 MB)
    • 12. Excel Writer.srt (3.4 KB)
    • 13. Rule Engine.mp4 (74.8 MB)
    • 13. Rule Engine.srt (12.6 KB)
    • 14. Joiner.mp4 (53.5 MB)
    • 14. Joiner.srt (10.6 KB)
    • 14.1 Seller Data.xlsx (246.0 KB)
    • 15. Rule Based Row Filter.mp4 (60.6 MB)
    • 15. Rule Based Row Filter.srt (8.4 KB)

    • Code:

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