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.
About the instructor: Hi, I’m Prateek Mehta. I am a Chemical Engineering PhD Candidate at the University of Notre Dame. I use Python everyday for my research (which involves computer simulations to design materials for energy conversion and storage). If you have questions about the material, or about anything in general, feel free to reach out at pmehta1@nd.edu or on twitter at @prtk_m.
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.
| Setup | Download files required for the lesson | |
| 09:00 | 1. Running and Quitting | How can I run Python programs? |
| 09:15 | 2. Variables and Assignment | How can I store data in programs? |
| 09:35 | 3. Data Types and Type Conversion |
What kinds of data do programs store?
How can I convert one type to another? |
| 09:55 | 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? |
| 10:20 | 5. Morning Coffee | Break |
| 10:35 | 6. Libraries |
How can I use software that other people have written?
How can I find out what that software does? |
| 10:55 | 7. Reading Tabular Data into DataFrames | How can I read tabular data? |
| 11:15 | 8. Pandas DataFrames | How can I do statistical analysis of tabular data? |
| 11:45 | 9. Plotting | How can I plot my data? |
| 12:15 | 10. Lunch | Break |
| 13:00 | 11. Lists | How can I store multiple values? |
| 13:20 | 12. For Loops | How can I make a program do many things? |
| 13:45 | 13. Looping Over Data Sets | How can I process many data sets with a single command? |
| 14:00 | 14. Writing Functions | How can I create my own functions? |
| 14:25 | 15. Variable Scope |
How do function calls actually work?
How can I determine where errors occurred? |
| 14:45 | 16. Afternoon Coffee | Break |
| 15:00 | 17. Conditionals | How can programs do different things for different data? |
| 15:25 | 18. Programming Style |
How can I make my programs more readable?
How do most programmers format their code? How can programs check their own operation? |
| 15:55 | 19. Wrap-Up |
What have we learned?
What else is out there and where do I find it? |
| 16:15 | 20. Feedback | How did the class go? |
| 16:30 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.