You’ve taken some data off an experiment, gathered it in the field, or dumped it from a bunch of simulations and you’ve found some amazing result! How do you quickly show off that result in a beautiful graph? You could use a spreadsheet, but maybe you want to make it reproducible and include the code in your paper.

This week we return to Pandas to look at how to plot data and manipulate graphs with matplotlib.

We used some materials from Christopher Woods’ great “Intermediate Python and Data Analysis Workshop”, which are available from his website here: https://chryswoods.com/python_and_data/README.html

You can download the Jupyter Notebook, along with the two data files we’ll be using:

If `jupyter notebook`

isn’t working for you, try running the following
commands:

```
python3 -m venv pandas
source pandas/bin/activate
pip install jupyter pandas matplotlib==3.0.3
jupyter notebook
```

## Further reading

Here is an interesting example of using Python to analyse an Excel spreadsheet: https://realpython.com/analyzing-obesity-in-england-with-python/