advanced-analytics-R/DATA401-exploring-leaflet at main · ashemsu/advanced-analytics-R · GitHub

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## Adefoluke Shemsu
## Week 1 Assignment

# Assignment: Using the leaflet package, recreate the map featured in the image "place_matters_example_map.png" that
# can be found in the Week 1 HW folder. Be sure to alter the aesthetics of the map to match the example image
# as closely as you can.

# First, I'll need to set my working directory and ensure I have the correct packages installed.

setwd("~/Documents/Education/Penn/Classes/DATA 401/Week 1")

library(leaflet) # Disclaimer: For these, I found out in 310 that keeping 'install.packages' function breaks rmd knit process.
library(rgdal)
library(tidyverse)
library(ggmap)


leaflet()%>% # Pulling map on where we will be plugging adding contextual geospacial data.
  addTiles()

leaflet()%>% # Drilling down to city location.
  addTiles()%>%
  setView(lng = -75.1624776, lat = 39.9562897, zoom = 12)%>%
  addMarkers(lat = 39.9562897, lng = -75.1624776, popup = "Philadelphia, PA")

# Next, we'll need to pull crime data associated with this area.

crimestats <- read.csv("place_data.csv")
philly.zip <- readOGR("Zipcodes_Poly", layer = "Zipcodes_Poly", encoding = "UTF-8")

# Merging data with the shape file.

philly.zip@data <- data.frame(philly.zip@data,
                              crimestats[match(philly.zip@data$CODE,
                                               crimestats$CODE),])

# Adding a new variable to classify risk levels.

philly.zip@data$rank[zipcodes@data$Risk <= 24] <- 1
philly.zip@data$rank[24 < philly.zip@data$Risk & philly.zip@data$Risk <= 49] <- 2
philly.zip@data$rank[49 < philly.zip@data$Risk & philly.zip@data$Risk <= 74] <- 3
philly.zip@data$rank[74 < philly.zip@data$Risk] <- 4
philly.zip@data$rank[is.na(philly.zip@data$Risk)] <- 0

# Creating popup object.

phil.popup <- paste("<strong>Zip Code </strong>",
                    philly.zip@data$CODE, "<br>",
                    "<br>",
                    "<strong>Risk Index: </strong>",
                    philly.zip@data$Risk,"%","<br>",
                    "<strong>Poverty: </strong>",
                    philly.zip@data$Poverty,"%","<br>",
                    "<strong>Education: </strong>",
                    philly.zip@data$Education,"%","<br>",
                    "<strong>Unemployment: </strong>",
                    philly.zip@data$Unemployment,"%","<br>",
                    "<strong>Crime: </strong>",
                    philly.zip@data$Crime,"%","<br>",
                    "<strong>ACEs: </strong>",
                    philly.zip@data$ACEs,"%","<br>")

# Selecting color pallete for the map.

map.colors <- colorFactor(c("#FFFFFF",
                            "#FFDB97",
                            "#FF984E",
                            "#F05051",
                            "#D12F2E"),
                          philly.zip@data$rank)

# Mapping layout and creating render function for the server.

leaflet(philly.zip)%>%
  addProviderTiles("CartoDB.Positron")%>%
  addPolygons(stroke = TRUE,
              color="#FFFFFF",
              smoothFactor = 0.2,
              fillOpacity = .8,
              fillColor = ~map.colors(rank),
              weight = 1,
              popup = phil.popup)%>%
  addLegend("bottomright",
            colors = c("#FFFFFF", "#FFDB97","#FF984E","#F05051","#D12F2E"),
            labels = c("No data", "0-24","25-49","50-74","75-98"),
            title = "Risk: Lowest to Highest",
            opacity = 1)