Draft Lessons¶

Python for Big Data

• Python for Big Data
  • An Example with Pandas, NumPy and Matplotlib
    • Set Up Directories and Get Test Data
    • Load Data in Pandas
    • Working with DataFrames
    • Plotting with Matplotlib and NumPy
    • More DataFrame Manipulation and Plotting
    • Saving Plots to PDF
    • Next Steps and Exercises
  • Summary of Useful Libraries
    • Numpy
    • MatplotLib
    • Pandas
  • Other Useful Libraries
    • Scipy
    • ggplot
    • seaborn
    • Bokeh
    • pygal
    • Network and Graphs
    • REST
  • Other Examples
• Python Fingerprint Example

Useful Tools and Tips

• Refcards
• 4.1. Linux Shell
  • 4.1.1. File commands
  • 4.1.2. Search commands
  • 4.1.3. Help
  • 4.1.4. Keyboard Shortcuts
  • 4.1.5. .bashrc and .bash_profile
  • 4.1.6. Exercise
• 2.2. LaTeX
  • 2.2.1. Characters
  • 2.2.2. Highlighting Text
  • 2.2.3. Sections
  • 2.2.4. Empty Lines
  • 2.2.5. Itemize
  • 2.2.6. Enumerate
  • 2.2.7. Descriptions
  • 2.2.8. Images
  • 2.2.9. Tables
  • 2.2.10. Labels
  • 2.2.11. Math
  • 2.2.12. ACM Proceedings Format
  • 2.2.13. IEEE Proceedings Format
  • 2.2.14. Bibliography
  • 2.2.15. Introduction
  • 2.2.16. LaTeX vs. X
  • 2.2.17. Editing
  • 2.2.18. LyX
  • 2.2.19. WYSIWYG locally
  • 2.2.20. Installation
  • 2.2.21. Paperia
  • 2.2.22. The LaTeX Cycle
  • 2.2.23. Generating Images
  • 2.2.24. Bibliographies
  • 2.2.25. Slides
  • 2.2.26. Links
  • 2.2.27. Tips
• Ubuntu Development Configurations
  • Development Configuration
• Using SSH Keys
  • Using SSH from Windows
  • Using SSH on Mac OS X
  • Generate a SSH key
  • Add or Replace Passphrase for an Already Generated Key
  • Upload the key to gitlab
  • Exercise

Contributing

• 1.5. Contributing
  • 1.5.1. MD vs. RST
  • 1.5.2. Using GitHub
  • 1.5.3. Creating a Pull Request in GitHub
  • 1.5.4. Adding bibligraphic references
  • 1.5.5. Exercise