Summary and Schedule

This lesson is an introduction to programming in Python 3 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 JupyterLab but can be taught using alternative Python 3 interpreters as well (e.g., repl.it, Anaconda).

Prerequisite

Prerequisites

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

2. Learners must install Python 3 before the class starts.

3. 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 more details.

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. Running and Quitting	How can I run Python programs?
Duration: 00h 30m	2. Variables and Assignment	How can I store data in programs?
Duration: 01h 00m	3. (Talk) The Zen of Python
Duration: 01h 20m	4. Morning Coffee
Duration: 01h 30m	5. Data Types and Type Conversion	What kinds of data do programs store? How can I convert one type to another?
Duration: 02h 00m	6. 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?
Duration: 02h 30m	7. Lunch Break
Duration: 03h 30m	8. Libraries	How can I use software that other people have written? How can I find out what that software does?
Duration: 04h 00m	9. (Talk) Third Party Libraries
Duration: 04h 20m	10. Afternoon Break
Duration: 04h 30m	11. Reading Tabular Data into DataFrames	How can I read tabular data?
Duration: 05h 00m	12. Pandas DataFrames	How can I do statistical analysis of tabular data?
Duration: 05h 30m	13. Plotting	How can I plot my data? How can I save my plot for publishing?
Duration: 06h 00m	14. (Talk) Git Control System
Duration: 06h 20m	15. Day 1 Recap
Duration: 06h 35m	16. Lists	How can I store multiple values?
Duration: 07h 10m	17. Dictionaries	How is a dictionary different from a list?
Duration: 07h 55m	18. Morning Coffee
Duration: 08h 10m	19. For Loops	How can I make a program do many things?
Duration: 09h 10m	20. Lunch Break
Duration: 10h 10m	21. Conditionals	How can programs do different things for different data?
Duration: 10h 55m	22. (Talk) Clean Code
Duration: 11h 15m	23. Afternoon Break
Duration: 11h 25m	24. Looping Over Data Sets	How can I process many data sets with a single command?
Duration: 11h 45m	25. Writing Functions	How can I create my own functions?
Duration: 12h 45m	26. Variable Scope	How do function calls actually work? How can I determine where errors occurred?
Duration: 13h 00m	27. Programming Style	How can I make my programs more readable? How do most programmers format their code? How can programs check their own operation?
Duration: 13h 30m	28. (Talk) Libraries with Compiled Code
Duration: 13h 50m	29. Feedback	How did the class go?
Duration: 14h 05m	30. Wrap-Up	What have we learned? What else is out there and where do I find it?
Duration: 14h 25m	Finish

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

Getting the Data

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The data we will be using is taken from the gapminder dataset. To obtain it, download and unzip the file python-novice-gapminder-data.zip. In order to follow the presented material, you should launch the JupyterLab server in the root directory (see Starting JupyterLab).

Installing Python Using Anaconda

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Please refer to the Python section of the workshop website for installation instructions.

(Fallback)

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If you are unable to install Python and Anaconda on your computer, you can use the following online services to run Python code:

• (With an RWTH SSO Login) https://jupyter.rwth-aachen.de/hub/login
• https://jupyter.org/try (You will likely not be able to save your work)