IMPRS-gBGC course 'Python' 2017
 

Category: Skill course
Credit points: 0.2 CP per course day

 

1.  Concept

This course addresses everybody who is interested in learning Python from scratch. The course is organized in three parts: "Basics" on day one and two, "Advanced Analysis with Python" on day three and "Data Visualisation" on day four. Please sign up for the modules that are of interest for you. If you have any question ie. regarding the level of detail feel free to address the instructors.

 

2.  Organizational issues

Instructors: Jacob Nelson, Sujan Koirala
Date: February 28, March 6-7 and March 13-14, 2017
Starting time: 9.00 am
Place: Seminar room B0.002 (MPI-BGC)

 

3.  Agenda

DayContent
 
February 28Overview of commonly used programming languages
 
9:00 amIntroduction to Python, R, MATLAB and Julia
 
March 6Basics
 
9:00 am

Intallation and package management

  • Python 2 vs. 3
  • Installation
  • Package management with Anaconda
    • Environments
  • Integrated development environment - spyder
 
pm

Data types

  • Integers, floats, strings, boolean
  • Lists and dictionaries
  • Arrays
  • Data Cubes
 
March 7Basics
 
am

Structure of a Python Program

  • Writing first code
  • Good practices
  • Writing your own module
  • Adding your programs to the Python path

I/O

  • Read data
  • Save data

Mathematical operations in NumPy

  • Arrays
  • Matrices
  • Masks
 
March 13Advanced Analysis with Python
 
am
  • Statistical Analysis
    • SciPy
  • Machine Learning
    • Scikit Learn
  • Pandas
 
March 14Data Visualisation
 
am
  • MatPlotLib
    • Lines and Scatters
    • Maps
  • Interactive Visualization
    • Bokeh
  • Structure of a figure
 
 

 

 

4.  What you need to prepare

Bring a laptop.

Please also make sure that you can access the internet via WLAN (BGC-users, if you have a BGC-account; BGC-guests, if you don't have an account)

 

5.  Material

Python in Earth Science

 

6.  Feedback

The survey gives feedback of 6 participants. Statistics and statements should not be taken as an exhaustive or exclusive list.

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