Part 2 plans

This page is a list of topics we can consider discussing in part two of the course.

Survey responses

  1. Data visualization

  2. Efficient programming

  3. Using classes/objects

  4. Statistics in Python

  5. Data processing

  6. Image processing

  7. Writing code

  8. Plotting different kinds of diagrams maybe even combine different diagrams in one diagram

  9. General statistic operations isotopic calculations with different data sheets and variables

  10. basic things

  11. understanding programming and basic applications in Geology-related projects

  12. Intuitive, sensitive, non-fiction cartography

  13. information that’ll help me better my skills in programming

  14. Learning to program a map or an app that can be helpful for geological data

  15. Handling data with Python vs. traditional means (eg. Excel)

  16. Data visualisation in diagrams

  17. How to fit data into a diagram mined from a publication

  18. Ways to share our work and entrance into channels dedicated to Python relationship with geochemistry

  19. Use of Python and machine learning to clasify, correlate data

  20. Ideas on how we can stay “Warm” in Python programming throughout our PhD years

  21. Basic python

  22. The application of statistics using python

  23. Python for microscopists

Response themes

Python essentials

  • Writing code

  • Basic things

  • Understanding programming and basic applications in Geology-related projects

  • Information that’ll help me better my skills in programming

  • Basic python

Data visualization

  • Data visualization

  • Plotting different kinds of diagrams maybe even combine different diagrams in one diagram

  • Intuitive, sensitive, non-fiction cartography (?)

  • Data visualisation in diagrams

  • How to fit data into a diagram mined from a publication (?)

Statistics

  • Statistics in Python

  • General statistic operations isotopic calculations with different data sheets and variables

  • The application of statistics using python

Using Python like a programmer

  • Efficient programming

  • Using classes/objects

  • Data processing

  • Handling data with Python vs. traditional means (eg. Excel)

Other: Machine learning/AI

  • Image processing (?)

  • Use of Python and machine learning to clasify, correlate data

Other:

  • Learning to program a map or an app that can be helpful for geological data

  • Ways to share our work and entrance into channels dedicated to Python relationship with geochemistry

  • Ideas on how we can stay “Warm” in Python programming throughout our PhD years

  • Python for microscopists

Suggested topics for part two

Python basics review - Part 2, week 2

  • for loops

  • functions

  • When to use which brackets in Python

    • (), [], {}

Data visualization - Part 2, week 3

  • Making publication quality plots with Matplotlib

  • Making your plots accessible

  • Other suggestions?

Basic geostatistics - Part 2, week 4

  • Reading data from Excel files?

  • Converting equations to Python code

    • Calculating derivatives of array data

  • Other suggestions?

Programming like a pro - Part 2, week 5

  • Batch processing data files

  • Picking the “right” tools for the job

  • Common program elements/tasks/challenges

Other ideas - Part 2, week 6

  • Data interpolation?

  • Linking models and data?

  • Mining data from tables in PDF documents

  • Mining graphs from literature, reconstructing them and plotting our data.

  • Classes in Python

    • Introduce the basic ideas and provide a simple example

  • Next steps and useful resources