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Linkedin - Python For Data Science Tips Tricks And Techniques
TORRENT SUMMARY
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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
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FILE LIST
Filename
Size
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
