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Linkedin - Python For Data Science Tips Tricks And Techniques

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228 MB
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1
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0
Files
38
Category
Other
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at 7:51pm GMT+1
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Description
Course details

Modern work in data science requires skilled professionals versed in analysis workflows and using powerful tools. Python can play an integral role in nearly every aspect of working with data—from ingest, to querying, to extracting and visualizing. In this course, instructor Ben Sullins highlights tips and tricks you can use right away to improve your skills in Python. Learn how to work with JSON data, CSV files, and Parquet files. Explore ways to read, inspect, and aggregate data using pandas. Plus, find out how to visualize data using basic charts, small multiples, and color in Plotly, as well as how to put the finishing touches on your data visualizations

File list
  • Linkedin - Python For Data Science Tips Tricks And Techniques
  • 1. Introduction/1. Discover new tips and tricks for Python.mp4 4.3 MB
  • 1. Introduction/2. What you should know.mp4 381.8 KB
  • 1. Introduction/3. Using the exercise files.mp4 3.1 MB
  • 1. Introduction/4. Set up on Windows.mp4 6.4 MB
  • 1. Introduction/5. Set up on Mac.mp4 4.9 MB
  • 2. Ingesting Data/1. Working with JSON data.mp4 21.8 MB
  • 2. Ingesting Data/2. Working with CSV files.mp4 7.6 MB
  • 2. Ingesting Data/3. Working with Parquet files.mp4 23.2 MB
  • 2. Ingesting Data/4. Reading data from GitHub API.mp4 13.7 MB
  • 3. Exploring Data/1. Reading data with pandas.mp4 20.9 MB
  • 3. Exploring Data/2. Inspecting DataFrames with pandas.mp4 9.3 MB
  • 3. Exploring Data/3. Aggregating data with pandas.mp4 12.8 MB
  • 3. Exploring Data/4. Exporting data with pandas.mp4 11.9 MB
  • 4. Visualizing Data/1. Basic charts in Plotly.mp4 15.2 MB
  • 4. Visualizing Data/2. Small multiples with Plotly.mp4 14.3 MB
  • 4. Visualizing Data/3. Using color in Plotly.mp4 12.3 MB
  • 4. Visualizing Data/4. Finishing your data visualizations in Plotly.mp4 12.6 MB
  • 5. Conclusion/1. Next steps and additional resources.mp4 1.5 MB
  • Exercise Files/01_01.ipynb 11.7 KB
  • Exercise Files/01_02.ipynb 9.2 KB
  • Exercise Files/01_03.ipynb 2.4 MB
  • Exercise Files/01_04.ipynb 7.3 KB
  • Exercise Files/02_01.ipynb 3.9 KB
  • Exercise Files/02_02.ipynb 18.2 KB
  • Exercise Files/02_03.ipynb 1.7 KB
  • Exercise Files/02_04.ipynb 7 KB
  • Exercise Files/03_01.ipynb 8.3 MB
  • Exercise Files/03_02.ipynb 2.5 MB
  • Exercise Files/03_03.ipynb 14.8 MB
  • Exercise Files/03_04.ipynb 398.1 KB
  • Exercise Files/data/anscombes-quartet-hier.csv 496 B
  • Exercise Files/data/anscombes-quartet.csv 607 B
  • Exercise Files/data/diamonds.csv 2.6 MB
  • Exercise Files/data/MonthlyProductSales.csv 515.1 KB
  • Exercise Files/data/MonthlyProductSales.parquet 74.2 KB
  • Exercise Files/data/MonthlySales.csv 1019 B
  • Exercise Files/data/monthlySalesbyCategoryMultiple.json 1.6 KB
  • Exercise Files/data/mpg.csv 15.7 KB

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