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| 10 - Advanced-Pandas-Techniques.ipynb |
4.10Кб |
| 10 - Combining-NumPy-with-Pandas.ipynb |
3.38Кб |
| 10 - Harnessing the Power of Pandas.mp4 |
265.97Мб |
| 10 - Slicing-and-Boolean-Indexing.ipynb |
1.89Кб |
| 11 - Combining-NumPy-with-Pandas.ipynb |
3.38Кб |
| 11 - Linear-Algebra-with-NumPy.ipynb |
3.14Кб |
| 11 - Mastering-Advanced-NumPy-Techniques.ipynb |
1.76Кб |
| 11 - NumPy The Engine of Numerical Computing.mp4 |
332.83Мб |
| 12 - Introduction.mp4 |
44.88Мб |
| 13 - Creating-a-Bar-Plot.ipynb |
25.75Кб |
| 13 - Creating-Simple-Line-Plot.ipynb |
52.47Кб |
| 13 - Foundations of Visualization with Matplotlib.mp4 |
300.24Мб |
| 14 - Customizing-Plot-Styles-and-Themes.ipynb |
46.26Кб |
| 14 - Customizing-the-Diagonal-with-KDE-Plots.ipynb |
272.60Кб |
| 14 - Exploring-Relationships-with-Pair-Plots.ipynb |
240.22Кб |
| 14 - Faceted-Visualizations-with-FacetGrid.ipynb |
60.24Кб |
| 14 - Simple-Seaborn-Plot-with-Built-in-Datasets.ipynb |
70.77Кб |
| 14 - The Art of Statistical Visualization with Seaborn.mp4 |
703.44Мб |
| 14 - Visualizing-Distributions-with-Violin-Plots.ipynb |
309.50Кб |
| 15 - Introduction.mp4 |
47.57Мб |
| 16 - Harnessing the Power of Big Data with Apache Spark.mp4 |
710.82Мб |
| 16 - spark-setup.ipynb |
67.24Кб |
| 17 - docker-compose.yml |
3.22Кб |
| 17 - Docker The Foundation for Seamless Workflow Integration Part 1.mp4 |
630.05Мб |
| 17 - extract-data.ipynb |
3.88Кб |
| 17 - financial-pipeline.py |
2.46Кб |
| 17 - transform-data.ipynb |
3.01Кб |
| 18 - Introduction.mp4 |
54.46Мб |
| 19 - add-tickers-by-sector.ipynb |
8.13Кб |
| 19 - analyze-data.ipynb |
12.57Кб |
| 19 - data-pipeline-with-parallel-enrichment-solution.py |
11.98Кб |
| 19 - docker-compose.yml |
3.32Кб |
| 19 - Docker The Foundation for Seamless Workflow Integration Part 2.mp4 |
1.08Гб |
| 19 - fetch-data-chunk.ipynb |
8.79Кб |
| 19 - fetch-data-with-financials.ipynb |
6.87Кб |
| 19 - generate-report.ipynb |
6.40Кб |
| 19 - requirements.txt |
101б |
| 19 - serial-to-parallel-fetch-assignment-dag.py |
13.86Кб |
| 1 - Introduction.mp4 |
74.28Мб |
| 20 - Bridging Exploratory Analysis and Workflow Automation.mp4 |
286.70Мб |
| 20 - docker-compose.yml |
3.22Кб |
| 20 - extract-data.ipynb |
3.88Кб |
| 20 - financial-pipeline.py |
2.46Кб |
| 20 - new-data-Analysis.ipynb |
17.05Кб |
| 20 - requirements.txt |
45б |
| 20 - Transcript-subtitles-The-key-features-of-a-real-world-financial-pipeline-DAG-en-US.txt |
27.94Кб |
| 20 - transform-data.ipynb |
3.01Кб |
| 21 - analyze-data.ipynb |
12.57Кб |
| 23 - Community and Continued Learning.mp4 |
234.89Мб |
| 2 - Introduction.mp4 |
53.54Мб |
| 3 - Setting Up Your Environment Your Gateway to Productivity.mp4 |
67.86Мб |
| 4 - Core Python Concepts Building Your Programming Foundation.mp4 |
290.79Мб |
| 5 - Python Control Flow Mechanisms.mp4 |
139.56Мб |
| 6 - Dictionaries-Solution.ipynb |
4.43Кб |
| 6 - List.ipynb |
1.79Кб |
| 6 - Python Data Structures.mp4 |
279.01Мб |
| 6 - Tuples.ipynb |
1.63Кб |
| 7 - Coding Challenge Solution.mp4 |
93.10Мб |
| 7 - Dictionaries-Solution.ipynb |
4.43Кб |
| 8 - ErrorHandling.ipynb |
1.17Кб |
| 8 - Error Handling and Debugging Writing Resilient Code.mp4 |
304.76Мб |
| 9 - Introduction.mp4 |
52.50Мб |