- Write a shiny app with a Readme.md
- Deploy the app on the local server
- Share server and ui codes on github
- Write a 5 slides pitch using RMD presentation.
- Add the presentation in the repo
- Some form of input (widget: textbox, radio button, checkbox, ...)
- Some operation on the ui input in server.R
- Reactive output displayed as a result of server calculations
- User friendly
- Shiny doc only
- App directory (Shiny)
- Presentation directory
- Scripts directory (includes all other types of scripts such as the preprocessing scipt)
- Find the "average availability over 30 days" of listings per each city.
- Find the "average revenue of over 30 days" of listings per each city.
- Compare the distribution of estimated availability for the next 30 days of listings per each city.
- Compare the distribution of estimated revenue for the next 30 days of listings per each city.
- Compare the distribution of estimated revenue for the next 30 days of listings per each city & for each house size (# of bedrooms). --> remove NaN
- Compare the distribution of estimated revenue for the next 30 days of listings per each city & for each room type (room_type). --> élargir les viz
For each city :
- What is the proportion of each room type?
- What is the proportion of each house size (# of bedroom)?
- What is the proportion of each neighborhood?
- What is the average availability over the next 30 days for each room type / house size / neighborhood? -> Metric
- What is the average revenue over the next 30 days for each room type / house size / neighborhood? -> Metric
- What is the distribution of availability over the next 30 days for each room type / house size / neighborhood? -> Distrib plot
- What is the distribution of revenue over the next 30 days for each room type / house size / neighborhood? -> Distrib plot
For each city :
- Fetch the price of squaremeter in each city : fixed cost
- Fetch the price of the electricity and water in each city : variable cost
- Compute the breakeven point in days and in € : Fixed Cost / (Income-variable cost)