programming skills for phd researchers (using python)

Note

If you are unable to install all of the software on your own machine, you can still work through the exercises online by clicking the badge below:

This will (eventually) open an online interactive version of the material that you will be able to run from within your web browser.

The aim of this workshop is to provide PhD Researchers with skills and experience to use programming tools for specialized and reproducible analysis. The topics covered include (but are not limited to):

• Introduction to version control using git

• Introduction to the python programming language

• Reading and understanding error messages to fix issues

• Reading and transforming datasets

• Basic statistical analysis

• Project organization

Before moving on to the practicals below, be sure to visit the setup page to make sure that you have the software and materials set up in order to get started.

schedule

session	theme	exercise topic(s)
1	git and conda	introduction to version control using git starting a new project
2	intro to python	introduction to python using jupyterlab debugging code
3	plotting	plotting data using seaborn
4	working with pandas	working with pandas dataframes
5	statistical analysis	basic statistical analysis using python
6	regression	linear regression using python
7	byod1 project work
8	byod project work

exercise solutions

At the end of each of the exercises, I have provided a list of additional exercises for you to practice the skills and concepts covered in each session. On the GitHub page for the workshop, you can find some example solutions that I have provided on the solutions branch. To get there, click the link above, which should take you here:

Next, click the button that says main to show a list of branches, then select solutions:

This will show you the files included on the solutions branch - inside each folder, you should find script or notebook file that contains example solutions for each of the exercise questions:

Remember that as we have discussed in the workshop, these solutions are not the only possible solutions to the questions - there are potentially many different ways to answer the questions!

notes

1

“bring your own data”