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.

Arthritis Inflammation

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:

The first three rows of our first file look like this:


Each number represents the number of inflammation bouts that a particular patient experienced on a given day. For example, value “6” at row 3 column 7 of the data set above means that the third patient was experiencing inflammation six times on the seventh day of the clinical study.

So, we want to:

  1. Calculate the average inflammation per day across all patients.
  2. Plot the result to discuss and share with colleagues.

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


You need to understand the concepts of files and directories and how to start a Python interpreter before tackling this lesson. This lesson sometimes references Jupyter Notebook although you can use any Python interpreter mentioned in the Setup.

The commands in this lesson pertain to Python 3.

Getting Started

To get started, follow the directions on the “Setup” page to download data and install a Python interpreter.


Setup Download files required for the lesson
00:00 1. Python Fundamentals What basic data types can I work with in Python?
How can I create a new variable in Python?
Can I change the value associated with a variable after I create it?
00:30 2. Analyzing Patient Data How can I process tabular data files in Python?
01:30 3. Visualizing Tabular Data How can I visualize tabular data in Python?
How can I group several plots together?
02:20 4. Repeating Actions with Loops How can I do the same operations on many different values?
02:50 5. Storing Multiple Values in Lists How can I store many values together?
03:35 6. Analyzing Data from Multiple Files How can I do the same operations on many different files?
03:55 7. Making Choices How can my programs do different things based on data values?
04:25 8. 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?
04:55 9. Errors and Exceptions How does Python report errors?
How can I handle errors in Python programs?
05:25 10. Defensive Programming How can I make my programs more reliable?
06:05 11. Debugging How can I debug my program?
06:55 12. Command-Line Programs How can I write Python programs that will work like Unix command-line tools?
07:25 Finish

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