Board Slides for FoodWheel

Brief

Objective

Overview

This project is slightly different than others you have encountered thus far on Codecademy. Instead of a step-by-step tutorial, this project contains a series of open-ended requirements which describe the project you’ll be building. There are many possible ways to fulfill all of these requirements correctly, and you should expect to use the internet, Codecademy, and other resources when you encounter a problem that you cannot easily solve.

Project Goals

Great job! You’ve passed your Data Analyst interview for FoodWheel!

FoodWheel is a startup delivery service that takes away the struggle of deciding where to eat.

FoodWheel picks you an amazing local restaurant and lets you order through the app. Senior leadership is getting ready for a big board meeting, and as the resident Data Analyst, you have been enlisted to help decipher data and create a presentation to answer several key questions:

  • What cuisines does FoodWheel offer? Which areas should the company search for more restaurants to partner with?
  • How has the average order amount changed over time? What does this say about the trajectory of the company?
  • How much has each customer on FoodWheel spent over the past six months? What can this tell us about the average FoodWheel customer?

Over this project, you will analyze several DataFrames and create several visualizations to help answer these questions.

Use your pandas and matplotlib skills to analyze and visualize the FoodWheel dataset.

Setup Instructions

You have two options for completing this assignment. Either here, within Codecademy’s output terminal, or on your own, in case you’re more comfortable using a Jupyter notebook.

If you choose to do this project on your computer instead of Codecademy, you can download what you’ll need by clicking the “Download” button below. If you need help setting up your computer, be sure to check out our setup guides:

Click “Download” below to download the project folder. Open foodwheel_project.ipynb and follow the steps in the Jupyter Notebook. If you get stuck, you can look at foodwheel_solution.ipynb for the answer.