Programming with Python

The best way to learn how to program is to do something useful, so this introduction to Python is built around a common scientific task: data analysis.

Our real goal isn’t to teach you Python, but to teach you the basic concepts that all programming depends on. We use Python in our lessons because:

  1. we have to use something for examples;
  2. it’s free, well-documented, and runs almost everywhere;
  3. it has a large (and growing) user base among scientists; and
  4. experience shows that it’s easier for novices to pick up than most other languages.

But the two most important things are to use whatever language your colleagues are using, so that you can share your work with them easily, and to use that language well.

We are studying inflammation in patients who have been given a new treatment for arthritis, and need to analyze the first dozen data sets of their daily inflammation. The data sets are stored in comma-separated values (CSV) format: each row holds information for a single patient, and the columns represent successive days. The first few rows of our first file look like this:


We want to:

To do all that, we’ll have to learn a little bit about programming.


Learners need to understand the concepts of files and directories (including the working directory) and how to start a Python interpreter before tackling this lesson. This lesson references the Jupyter (IPython) Notebook although it can be taught through any Python interpreter. The commands in this lesson pertain to Python 3.

Getting Started

To get started, follow the directions in the “Setup” tab to download data to your computer and follow any installation instructions.


Setup Download files required for the lesson
00:00 1. Analyzing Patient Data How can I process tabular data files in Python?
00:30 2. Repeating Actions with Loops How can I do the same operations on many different values?
01:00 3. Storing Multiple Values in Lists How can I store many values together?
01:30 4. Analyzing Data from Multiple Files How can I do the same operations on many different files?
01:50 5. Making Choices How can my programs do different things based on data values?
02:20 6. Creating Functions How can I define new functions?
What’s the difference between defining and calling a function?
What happens when I call a function?
02:50 7. Errors and Exceptions How does Python report errors?
How can I handle errors in Python programs?
03:20 8. Defensive Programming How can I make my programs more reliable?
03:50 9. Debugging How can I debug my program?
04:20 10. Command-Line Programs How can I write Python programs that will work like Unix command-line tools?
04:50 Finish

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