visualization

Introduction

This dashboard lets users explore different neighborhoods in different cities in Italy using data from ISTAT and other public sources. Currently under development.

This application uses React and has been built with Create React App.

Use

npm i and npm start and you should see a dashboard at localhost:3000

Input data

The visualization requires a geojson file (exported into js) of polygons (the neighborhhods) and json files, and a menu.json file describing the data.

Indicators

Two indicators have been computed:

• tipi di alloggio (tipiAlloggio)

• densità di occupati (densitaOccupati) and printed to the results.js file and results.js file. From the Istat data and from the area of the polygons, in R:

  data.csv <- read.csv(file="data.csv", sep=";", header=TRUE) tableNILAreaMQ.csv <- read.csv(file="tableNILAreaMQ.csv"), sep=";", header=TRUE) data.csv[data.csv=="-"] <- 0 NIL = tableNILAreaMQ.csv[,1] results = c(); for (n in NIL) { nildata.csv = data.csv[which(data.csv[,9]==n), c(3,4,5,6,7,8)]

    numOccupati = as.numeric(nildata.csv[,2])
    densitaOccupati = sum(numOccupati)/tableNILAreaMQ.csv[which(tableNILAreaMQ.csv[,1]==n),2]
  
    #sum(E17*1+E18*2+E19*3+E20*4)/sum(E17+E18+E19+E20)
    numAlloggi1Piano = as.numeric(nildata.csv[,3]
    numAlloggi2Piani = as.numeric(nildata.csv[,4])
    numAlloggi3Piani = as.numeric(nildata.csv[,5])
    numAlloggi4PianiOPiu = as.numeric(nildata.csv[,6])
    numTotAlloggi = sum(numAlloggi1Piano + numAlloggi2Piani + numAlloggi3Piani + numAlloggi4PianiOPiu)
    tipiAlloggio = sum(numAlloggi1Piano + numAlloggi2Piani * 2 + numAlloggi3Piani * 3 + numAlloggi4PianiOPiu * 4) / sum(numTotAlloggi)
    
    results = rbind(results, c(n, densitaOccupati, tipiAlloggio))
  

  } #Write results file write.table(results, "results.csv", row.names=FALSE, sep=";", quote=FALSE)