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Contents

Labor

These notebooks and exercises were prepared by Andrew Valentine as a class that can be followed in roughly numerical order to progress through more complicated features of python and more difficult problems.

Getting started with python and jupyter

Some simple introductary notebooks to help you learn both notebooks and python at the same time. We ran through some of this in our meet-and-greet with python programming

• Exercise 1 - Getting started

• Exercise 2 - Variables and functions

• Exercise 3 - Loops and conditionals

• Exercise 4 - Guessing Games

Arrays of data and loops

Moving on to data types that bundle multiple items together, thinking about how address individual items in those structures and how to access all of them in turn. This builds upon our quick introduction to python data types

• Exercise 5 - Lists, tuples and dictionaries

• Exercise 6 - More loops

• Exercise 7 - Strings

• Exercise 8 - Reading and writing files

Python idiosyncrasies

• Exercise 9 - Modules

• Exercise 10 - Exception handling

Doing things with python

Here we begin to explore the commonly used packages that are readily available in the python ecosystem. These exercises give you an introduction to the topic and you can dig deeper later.

• Exercise 11 - Numpy

• Exercise 12 - Plotting

• Exercise 13 - Radioactive Decay

• Exercise 14 - Pandas

• Exercise 15 - More plotting

• Exercise 16 - Maps

• Exercise 17 - Fourier analysis and Milankovitch cycles

More advanced material

• Exercise 18 - Object-oriented programming

• Exercise 19 - differential equations

• Exercise 20 - Sorting

There are more in-depth examples that you can now start to work through. These will assume you understand python and are trying to understand the programming process.