Ex 4.2 Visualizing Joined Data Sets:

Objective: Concatenate and visualize two datasets to analyze the relationship between them by identifying the inventory levels for each product category on a monthly basis. The inventory for each month is calculated as the difference between the cumulative sum of all orders and the cumulative sum of all sales made up to and including that month.

  1. Download the Ex4.2_Visualizing_Joined_Datasets.ipynb file.
  2. Using the orders.csv and salesdata.csv data files, work through each of the steps in the Jupyter Notebook which should include both your code and the corresponding output that match the screengrabs of the completed steps 2, 3, 5, and 6 provided below.

Expected output: concatenated orders and salesdata DataFrame showing product categories and monthly values

 

Expected output: inventory DataFrame showing cumulative sum difference between orders and sales by category

 

Expected output: Matplotlib or Seaborn line chart showing inventory levels by product category over months

 

Expected output: combined chart comparing orders and sales trends across product categories over time