# 2023-03-28-NCL

### This document:
# https://hackmd.io/@rseteam-ncl/2023-03-28-NCL

### JupyterHub:
# https://jupyter.ncldata.dev

### Links:
- [Workshop website](https://nclrse-training.github.io/2023-03-28-NCL/)
- [Code of Conduct](https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html)
- [Link to data](https://github.com/carpentries-incubator/python-novice-programming-gapminder/raw/main/files/python-novice-gapminder-data.zip)
- [Pre-workshop survey](https://carpentries.typeform.com/to/wi32rS?slug=2023-03-28-NCL)
- [Post-workshop survey](https://carpentries.typeform.com/to/UgVdRQ?slug=2023-03-28-NCL)

### Attendance - Please sign in with your university email
1. [e-mail]
3. [e-mail]
4. [e-mail]
5. [e-mail]
6. [e-mail]
7. Asma Feriel Khoualdi
8. [e-mail]
9. [e-mail]
10. [e-mail]
11. [e-mail]
12. [e-mail]
13. [e-mail]
14. [e-mail]
15. [e-mail]

import pandas as pd
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1,1)
for filename in glob.glob('data/gapminder_gdp*.csv'):
    dataframe = pd.read_csv(filename)
    # extract {region} from the filename, expected to be in the format 'data/gapminder_gdp_{region}.csv'.
    # we will split the string using the split method and `_` as our separator,
    # retrieve the last string in the list that split returns (`{region}.csv`), 
    # and then remove the `.csv` extension from that string.
    region = filename.split('_')[-1][:-4] 
    dataframe.mean().plot(ax=ax, label=region)
plt.legend()
plt.show()