Python: From None to Machine Learning
latest
  • License
  • Book Writing Progress
  • Python Install
  • Survey
  • References in the Book

Python Basics

  • 1. About
  • 2. Types
  • 3. Sequences
  • 4. Mappings
  • 5. Control Flow
  • 6. Loops
  • 7. Files
  • 8. Functions
  • 9. Object Oriented Programming
  • 10. Recap

Python Standard Library

  • 1. About
  • 2. Datetime and Timezones
  • 3. Serialization
  • 4. Database
  • 5. Regular Expressions
  • 6. Modules and Packages
  • 7. Builtins
  • 8. Locale
  • 9. Looping
  • 10. Type Annotations
  • 11. Object Oriented Programming
  • 12. Mathematics
  • 13. Operating System
  • 14. GUI
  • 15. References

Python Advanced

  • 1. About
  • 2. Annotation
  • 3. Unpacking
  • 4. Functions
  • 5. Decorators
  • 6. Object Oriented Programming
  • 7. Protocols
  • 8. Performance
  • 9. Concurrency
  • 10. Recap

Dragon

  • 1. Dragon (version alpha)
  • 2. Dragon (version beta)
  • 3. Dragon (version release candidate)

Numpy

  • 1. About
  • 2. Array
  • 3. Select
  • 4. Import & Export
  • 5. Math

Pandas

  • 1. About
    • 1.1. Pandas
    • 1.2. Types Basics
  • 2. Import & Export
    • 2.1. Pandas Read
    • 2.2. DataFrame Export
  • 3. Series
    • 3.1. Series Create
    • 3.2. Series Attributes
    • 3.3. Series Index
    • 3.4. Series Sample
    • 3.5. Series Getitem
    • 3.6. Series Slicing
    • 3.7. Series NA
    • 3.8. Series Alter
    • 3.9. Series Sort
    • 3.10. Series Arithmetic
    • 3.11. Series Statistics
    • 3.12. Series Mapping
  • 4. DataFrame
    • 4.1. DataFrame Create
    • 4.2. DataFrame Attributes
    • 4.3. DataFrame Index
    • 4.4. DataFrame Sample
    • 4.5. DataFrame Getitem
    • 4.6. DataFrame Slice
    • 4.7. DataFrame At
    • 4.8. DataFrame Loc
    • 4.9. DataFrame Select
    • 4.10. DataFrame Query
    • 4.11. DataFrame Update
    • 4.12. DataFrame Alter
    • 4.13. DataFrame NA
    • 4.14. DataFrame Sort
    • 4.15. DataFrame Statistics
    • 4.16. DataFrame Mapping
    • 4.17. DataFrame Group By
    • 4.18. DataFrame Aggregations
    • 4.19. DataFrame Join
    • 4.20. DataFrame Plotting
  • 5. Date
    • 5.1. Date and Time Types
    • 5.2. Date and Time Timezones
    • 5.3. Date and Time Shifts
    • 5.4. Date and Time Frequency
    • 5.5. Date and Time Calendar
  • 6. Recap
    • 6.1. Method Chaining
    • 6.2. Pandas Set Option
    • 6.3. Pandas Workflow
  • 7. Case Studies
    • 7.1. Case Study COVID-19

Matplotlib

  • 1. About
  • 2. Figure
  • 3. Style
  • 4. Chart
  • 5. Advanced
  • 6. Recap

Object Oriented Programming

  • 1. Paradigm
  • 2. Python
  • 3. Dynamic Typing

Design Patterns

  • 1. About
  • 2. Annotation
  • 3. UML
  • 4. OOP
  • 5. Idioms
  • 6. Protocols
  • 7. Decorators
  • 8. Behavioral
  • 9. Structural
  • 10. Creational
  • 11. Practices
  • 12. Paradigms

DevSecOps

  • 1. Good Engineering Practices
  • 2. Tests
  • 3. Debugging
  • 4. Type Annotation
  • 5. CI/CD

Network and HTTP

  • 1. HTTP and Web
  • 2. Protocols
  • 3. Transport

Django

  • 1. HTTP
  • 2. Introduction to Django
  • 3. Django Framework Architecture
  • 4. Installation and Running
  • 5. Settings
  • 6. Apps
  • 7. Models
  • 8. URL Router
  • 9. ORM
  • 10. Views
  • 11. Forms
  • 12. REST
  • 13. Staticfiles
  • 14. Templates
  • 15. Templatetags
  • 16. Admin panel
  • 17. Management Commands
  • 18. i18n and l10n
  • 19. Database
  • 20. Cache
  • 21. Signals
  • 22. Auth and Permissions
  • 23. API CORS
  • 24. Standalone scripts
  • 25. Tests and quality
  • 26. Tests
  • 27. CI/CD - Continuous Integration and Deployment
  • 28. Deployment

Data Science

  • 1. Introduction
  • 2. Jupyter
  • 3. Python
  • 4. Data Visualization
  • 5. Scipy

Machine Learning

  • 1. About
  • 2. Introduction
  • 3. Sklearn
  • 4. Model Quality
  • 5. Decision Trees
  • 6. Regressions
  • 7. K-Nearest Neighbors
  • 8. Bayes
  • 9. Support Vector Machines
  • 10. Clustering
  • 11. Neural Networks
  • 12. References

Blogposts

  • 1. Wprowadzenie do Machine Learning w Pythonie

Appendixes

  • 1. History
  • 10.2. Further reading
  • 2. Books
  • 3. Video
  • 4. Python 2 vs. 3
  • 5. Python Intermediate
  • 6. Python in Networking
  • 7. Django Framework
  • 8. Python in Testing
  • 9. Python in Science and Engineering
  • 10. Python in Machine Learning
  • 11. References
Python: From None to Machine Learning
  • Docs »
  • 1. About
  • Edit on GitHub

1. About¶

About¶

  • 1.1. Pandas
  • 1.2. Types Basics

2. Import & Export¶

Import & Export¶

  • 2.1. Pandas Read
  • 2.2. DataFrame Export

3. Series¶

Series¶

  • 3.1. Series Create
  • 3.2. Series Attributes
  • 3.3. Series Index
  • 3.4. Series Sample
  • 3.5. Series Getitem
  • 3.6. Series Slicing
  • 3.7. Series NA
  • 3.8. Series Alter
  • 3.9. Series Sort
  • 3.10. Series Arithmetic
  • 3.11. Series Statistics
  • 3.12. Series Mapping

4. DataFrame¶

DataFrame¶

  • 4.1. DataFrame Create
  • 4.2. DataFrame Attributes
  • 4.3. DataFrame Index
  • 4.4. DataFrame Sample
  • 4.5. DataFrame Getitem
  • 4.6. DataFrame Slice
  • 4.7. DataFrame At
  • 4.8. DataFrame Loc
  • 4.9. DataFrame Select
  • 4.10. DataFrame Query
  • 4.11. DataFrame Update
  • 4.12. DataFrame Alter
  • 4.13. DataFrame NA
  • 4.14. DataFrame Sort
  • 4.15. DataFrame Statistics
  • 4.16. DataFrame Mapping
  • 4.17. DataFrame Group By
  • 4.18. DataFrame Aggregations
  • 4.19. DataFrame Join
  • 4.20. DataFrame Plotting

5. Date¶

Date¶

  • 5.1. Date and Time Types
  • 5.2. Date and Time Timezones
  • 5.3. Date and Time Shifts
  • 5.4. Date and Time Frequency
  • 5.5. Date and Time Calendar

6. Recap¶

Recap¶

  • 6.1. Method Chaining
  • 6.2. Pandas Set Option
  • 6.3. Pandas Workflow

7. Case Studies¶

Case Studies¶

  • 7.1. Case Study COVID-19
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© Copyright 2021, CC-BY-SA-4.0, Matt Harasymczuk <book-python@astrotech.io>, last update: 2021-01-15 Revision cc6c9abe.

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