MA 705: Spring 2022 Prof. 

Cherveny Goals Individual MA705 Project Due: May 5th 

1. Demonstrate mastery of data science tools covered in MA705 (python, working with data frames, visualizations, data collection and cleaning, dashboards) 2. Provide clear data analysis with client needs in mind Description Choose a real-world question and address it as a data scientist using tools learned in MA705. Major components of the project are: Designing an interesting project Collecting and cleaning data Building a dashboard Documenting the project Instructions 1. Topic: Choose a motivating question to anchor your project. This is the hardest part, and doing it well makes the rest of the project easier and more fun. The topic may be anything you like, but answering it should involve a variety of tools learned in MA705. What everyday problems do you face? What hobbies/topics are you interested in? Finance/Real Estate/Health/Sports/Weather Pets/Animals/Plants/Nature Food/Restaurants/Bars/Cooking Music/Movies/TV/Books/Games Products (Coke, McDonalds, Pizza, Cereal) Transportation (Cars/Trains/Flights) No projects on COVID, soccer (Premier, FIFA, etc), or stocks/crypto! The originality, cohesiveness, and challenge of your topic/dashboard will count. 2. Data Collection: Use web scraping, APIs, and publicly available data sets to collect data that may be useful. It very well might be a combination of sources. 3. Data Wrangling: Appropriately clean the raw data, deal with missing values, merge data sets, etc. Prepare at least one nice master data frame for downstream use. You might very well have several data frames or an entire folder of documents or images. MA 705: Spring 2022 Prof. Cherveny 4. Data Presentation: Build a dashboard that presents your analysis in a way that answers the question and allows for customization according to the users interests. At a minimum, your dashboard needs 1.) a table or summary statistics that updates according to user input, and 2.) at least one visualization that updates according to user inputs. Feel very free to include more elements. The challenge and originality involved will be noted. Dont make a complex dashboard for the sake of complexity! Dashboards that arent user-friendly or arent designed with a clear central question in mind will not be viewed favorably. Most projects will not use every tool learned in MA705. A lack of challenge in one step (collecting, cleaning, building dashboard) might be offset by more significant work in another step. You should feel free to incorporate models learned in other courses (if done right!), but you may not hand in this project (or part of it) as your semester project in another course without speaking to both instructors. Moreover, you must speak to me if you want to use tools that significantly differ from those covered in MA705. In no case will projects that are not done in python using the dash module be accepted. You may consult any references (books, media, web). However, you shouldnt consult professionals about this project. Document all data sources and references. Deliverables Primary: A well-designed Dashboard deployed to the web. It should be visually appealing, address a clear motivating question, be self-contained (meaning good labels on everything, with possibly brief text or markdown explanations as needed). It should allow for client customization as described. Other: All supporting .py files and data sets. There should be a README file on GitHub that briefly explains your project, data sources and how you gathered the data; contains a link to the dashboard; and adds anything else youd like me to know. Youll hand in your project by making me a collaborator to your GitHub repo. Your project should be hosted on GitHub and the dashboard deployed to the web using Heroku. Dashboards that arent online/dont run will automatically lose more than a few points. For this reason, I strongly recommended you save your cleaned master data set in pickle format and run the dashboard using that rather than scraping/using an API in real-time (I understand that in practice you might want real-time data, but at best it will slow down the dashboard and at worst Ive seen a few scrapers break or API requests fail due to exhausted call allowance, which means nothing to grade). Project Examples Several past student dashboards that earned high grades are posted. The number of possible topics and dashboards is limitless, so similar projects to these will not earn high grades.