Plotting and Programming in Python

This lesson is an introduction to programming in Python for people with little or no previous programming experience. It uses plotting as its motivating example, and is designed to be used in both Data Carpentry and Software Carpentry workshops. This lesson references the Jupyter Notebook, but can be taught using a regular Python interpreter as well. Please note that this lesson uses Python 3 rather than Python 2.

Under Design

This lesson is currently in its early design stage; please check the design notes to see what we have so far. Contributions are very welcome: we would be particularly grateful for exercises and for commentary on the ones already there.

Prerequisites

Learners need to understand what files and directories are, what a working directory is, and how to start a Python interpreter.

Learners must install Python before the class starts.

Learners must get the gapminder data before class starts: please download and unzip the file python-novice-gapminder-data.zip.

Please see the setup instructions for details.

Schedule

		Setup	Download files required for the lesson
Day 1	09:00	1. Running and Quitting	How can I run Python programs?
	10:00	2. Variables and Assignment	How can I store data in programs?
	11:00	3. Data Types and Type Conversion	What kinds of data do programs store? How can I convert one type to another?
	11:30	4. Built-in Functions and Help	How can I use built-in functions? How can I find out what they do? What kind of errors can occur in programs?
	12:00	Finish
Day 2	09:00	5. Lists & Dictionaries	How can I store multiple values?
	10:30	6. For Loops	How can I make a program do many things?
	11:00	7. Conditionals	How can programs do different things for different data?
	11:30	8. Libraries	How can I use software that other people have written? How can I find out what that software does?
	12:00	Finish
Day 3	09:00	9. Reading Tabular Data into DataFrames	How can I read tabular data?
	10:20	10. Pandas DataFrames	How can I do statistical analysis of tabular data?
	11:40	11. Looping Over Data Sets	How can I process many data sets with a single command?
	12:00	Finish
Day 4	09:00	12. Plotting	How can I plot my data? How can I save my plot for publishing?
	10:30	13. Writing Functions	How can I create my own functions?
	11:20	14. Variable Scope	How do function calls actually work? How can I determine where errors occurred?
	11:40	15. Programming Style	How can I make my programs more readable? How do most programmers format their code? How can programs check their own operation?
	11:50	16. Wrap-Up	What have we learned? What else is out there and where do I find it?
	11:55	17. Feedback	How did the class go?
	12:00	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.