École de printemps Calcul Québec 2019¶

Data Analysis with Python - Objectives¶

Go to the Compute Canada wiki and search for "École 2019".
Upload the submission file proposed on the wiki to the cluster: ecole2019.calculquebec.cloud
Create a directory on the cluster to contain the submission script, and move the script into it.
Increase the task duration to 2 minutes using nano.
Modify the account using nano to use: def-sponsor00
Submit the task.
Retrieve the result files to your computer.

Import the OpenRefine project generated by the task (projet.json).
Undo the operation that eliminated rows with missing extermination data.
Replace missing extermination count data with 0.
Add a "quadrimester" (four-month period) column:
- January to April = 1
- May to August = 2
- September to December = 3
Save the resulting dataset.

Upload the result to Jupyter.
Open the resulting dataset with Pandas.
Calculate the average number of exterminations per district.
Calculate the sum of exterminations by quadrimester (four-month period) per year.
Plot a stacked histogram:
- of the total number of exterminations by quadrimester (four-month period), per year.
- of the total number of exterminations by year, by quadrimester (four-month period).
Discuss the differences between the two graphs.

```bash title="job.sh"

/project/def-sponsor00/projet/bin/simulation_punaises.py 5000