Coding is one of the most useful and transferable skills in the modern age. This workshop assumes no previous knowledge of Python or computer science. The goal is not to teach you everything about Python, but to give you a gentle introduction through applied learning and practical problem solving so you will be equipped in case you wish to further explore this area.
Just like in experimental labs, it is not always practical to try to understand every detail in full. For example, we consider only the basic fundamentals behind the engineering of the lab instruments like the GC-MS or UV-vis. It is not the best use of our time to fully delve into the materials involved in the construction or the software engineering. As chemists, we are interested in the application and the broad scientific implications.
Likewise, we will try to understand the big picture in our coding labs. Don't get too caught up with how every single line or package works! Instead, focus on the concepts and implications for your area of chemistry.
- Part 1: How to import and plot data from Excel
- How to import data from Excel (pandas)
- How to plot data (matplotlib)
- How to do linear regression (scipy.stats.linregress)
- Part 2: Use your own Excel spreadsheet to visualize your data in Python