This is a continuation of our “Introduction to Python” course, based on the second half of the content offered by the Software Carpentries, and covers topics such as Repeating Actions with Loops, Creating Functions, Defensive Programming and Debugging. The aim is to introduce the students to a number of advanced features and concepts to improve their programming technique. The course is composed of a series of code demonstrations and examples where students will have a chance to practice and ask questions to the instructors.
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.
There are 60 patients, who had their inflammation levels recorded for 40 days. We want to analyze these recordings to study the effect of the new arthritis treatment.
To see how the treatment is affecting the patients in general, we would like to:
- Calculate the average inflammation per day across all patients.
- Plot the result to discuss and share with colleagues.
Data Format
The data sets are stored in comma-separated values (CSV) format:
- each row holds information for a single patient,
- columns represent successive days.
The first three rows of our first file look like this:
0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0
0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1
0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1
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.
In order to analyze this data and report to our colleagues, we’ll have to learn a little bit about programming.
Prerequisites
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.