author: Niccolò Salvini , Jędrzej Dziedziul
date: 2020-05-06
–> see the slides HERE –> see the Shiny APP HERE
This tool has been designed to explore apartements in Milan next to your
preferred location and compute a monthly rent price estimation given the
spatial coordinates and the expected characteristics of the house, such
as: rooms square meters. It is composed by a Shiny deployed from a
bitbucket repo into shinyapps.io and a set
of xaringan slides deployed on Netlify.
House data are scraped from immobiliare.
Full explanation on the slides.
libs = c("rvest", "magrittr", "stringr", "httr",
"furrr", "plotly", "ggplot2", "DT", "readxl", "dplyr")
new.packages = libs[!(libs %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)the first tab-panel in the tab-set let you explore the available houses
on the Milano house market, then once you have find the location of the
apartement you right click it. This will assign a marker in leaflet
object. This marker will be cached in the second tab panel, the price
prediciton calculator, where you can also specify other characteristics
of the desired house. An autoML model will give the estimation in the
lower down part on the left.
In the right drop-down column you can discover other further options to
select and the autoML will do its job in parallel.
this project is still IN ITINERE, but it has stopped since my
university class is completed.
- implement auto-scraping functions
- choose boostrap .css style
- better UX
Quest’opera
è distribuita con Licenza
Creative
Commons Attribuzione 4.0 Internazionale.
