Creating Graphs with Matplotlib

Please Note: Accessing VS Code Server in the browser will require a password. The password is system generated and will either be 24bdf4febea54a8579305316 or can be located on the host itself by logging in via SSH and viewing the config.yaml file.

cat ~/.config/code-server/config.yaml

Within VS Code Server, you will have the opportunity to use the Jupyter Notebook service to render graphs. It will ask you for a password on first use. There is no password; simply place your cursor in the prompt box and press Enter/Return.

Before we can use matplotlib to generate graphs, we'll need to make sure that it is installed.

From within the target_graphs.py file, create a bar chart to display the number of Target stores in each state. It will be useful to use itertools.groupby to collect the information based on the state. It will likely be necessary to change the font size of the axis ticks so that the state abbreviations don't overlap; this can be done with set_yticklabel and set_xticklabel (depending on how the graph is oriented.)

From within the target_graphs.py file, create a line graph that plots the number of Target stores that were opened each year. A line graph works well for charting this because we can visualize the information without adding a new tick label to the axis for years.

From within the target_graphs.py file, create a line graph that plots the total number of Target stores that are open over time. We'll need to calculate the total for each year by using the total from the previous year and adding the number of new stores opened in a given year.