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Data Science Foundations: Python Scientific Stack [CoderPad]
2h 26mIntermediate2022-11-09
Authors
Miki Tebeka
CEO at 353Solutions
Course details
Join instructor Miki Tebeka as he dives into the Python scientific stack and shows you how to use it to solve problems. Miki covers the major packages used throughout the data science process: numpy, pandas, matplotlib, scikit-learn, and others. He also guides you through how to load data, analyze data, run models, and display results.
Skills covered
PythonProgramming LanguagesOpen SourceSoftware DevelopmentDeep Dive (X:Y)
Concepts
Introduction
- The Python scientific stack
- What you should know
- Using GitHub Codespaces with this course
- Setup
Visual Studio Code
- Use code cells
- Extensions to the Python language
- Understand markdown cells
NumPy Basics
- NumPy overview
- NumPy arrays
- Slicing
- Learn boolean indexing
- Understand broadcasting
- Understand array operations
- Understand ufuncs
- Challenge - Working with an image
- Solution - Working with an image
pandas
- pandas overview
- Loading CSV files
- Parse time
- Access rows and columns
- Calculate distance
- Display speed box plot
- Challenge - Taxi data mean speed
- Solution - Taxi data mean speed
Folium and Geospatial Data
- Create an initial map
- Draw a track on map
- Using geospatial data with shapely
- Challenge - Draw the running track
- Solution - Draw the running track
NYC Taxi Data
- Examine data
- Load data from CSV files
- Working with categorical data
- Work with data - Hourly trip rides
- Work with data - Rides per hour
- Work with data - Weather data
- Challenge - Graphing taxi data
- Solution - Graphing taxi data
scikit-learn
- scikit-learn introduction
- Linear regression
- Understand train test split
- Preprocess data
- Compose pipelines
- Save and load models
- Challenge - Handwritten digits
- Solution - Handwritten digits
Plotting
- Overview of matplotlib
- Use styles
- Customize pandas output
- Plotting with pandas
- Use Matplotlib with pandas
- Tips and tricks
- Other plotting packages
- Challenge - Stock data bar charts
- Solution - Stock data bar charts
Other Packages
- Other packages overview
- Go faster with Numba
- Understand deep learning
- Work with image processing
- Understand NLP - NLTK
- Working with bigger data
Development Process
- Development process overview
- Understand source control
- Learn code review
- Testing overview
- Testing example
Conclusion
- Next steps