Developing Data Products Project 1

Introduction

Create a web page using R Markdown that features a map created with Leaflet. Host your webpage on either GitHub Pages, RPubs, or NeoCities. Your webpage must contain the date that you created the document, and it must contain a map created with Leaflet. We would love to see you show off your creativity! I used the followed site: https://www.maxmind.com/en/free-world-cities-database

Processing Data

First, let’s load global cities open data.

setwd("D:/gilad/DataScience/Developing_Data_Products/Project1")
WorldCities <- read.csv(file = "worldcitiespop.csv", sep = ",")

The above dataset contains approximaty 1.5 million cities around the world. Hence, I will reduce it for only 30 cities on specific country. For example Grat Britain.

GBCities1 <- subset(WorldCities, Country == "gb")

GBCities1 <- head(GBCities1, 30)
GBCities1

##        Country                City          AccentCity Region Population
## 986484      gb            abberley            Abberley     Q4         NA
## 986485      gb            abberton            Abberton     E4         NA
## 986486      gb            abberton            Abberton     Q4         NA
## 986487      gb       abbess roding       Abbess Roding     E4         NA
## 986488      gb        abbey-cwmhir        Abbey-Cwmhir     Y8         NA
## 986489      gb          abbey dore          Abbey Dore     F7         NA
## 986490      gb abbey saint bathans Abbey Saint Bathans     T9         NA
## 986491      gb          abbey town          Abbey Town     C9         NA
## 986492      gb          abbots ann          Abbots Ann     F2         NA
## 986493      gb   abbots bickington   Abbots Bickington     D4         NA
## 986494      gb      abbots bromley      Abbots Bromley     N1         NA
## 986495      gb          abbotsbury          Abbotsbury     D6         NA
## 986496      gb          abbotsford          Abbotsford     T9         NA
## 986497      gb           abbotsham           Abbotsham     D4         NA
## 986498      gb      abbotskerswell      Abbotskerswell     D4         NA
## 986499      gb      abbots langley      Abbots Langley     F8         NA
## 986500      gb        abbots lench        Abbots Lench     Q4         NA
## 986501      gb           abbotsley           Abbotsley     C3         NA
## 986502      gb       abbots ripton       Abbots Ripton     C3         NA
## 986503      gb       abbots worthy       Abbots Worthy     F2         NA
## 986504      gb         abbotts ann         Abbotts Ann     F2         NA
## 986505      gb      abbotts ripton      Abbotts Ripton     C3         NA
## 986506      gb                aber                Aber     Y2         NA
## 986507      gb           aberaeron           Aberaeron     X6         NA
## 986508      gb            aberaman            Aberaman     Y9         NA
## 986509      gb          aberangell          Aberangell     Y8         NA
## 986510      gb           aberarder           Aberarder     V3         NA
## 986511      gb           aberargie           Aberargie     W1         NA
## 986512      gb           aber-arth           Aber-Arth     X6         NA
## 986513      gb           aberayron           Aberayron     X6         NA
##        Latitude Longitude
## 986484 52.30000 -2.366667
## 986485 51.83333  0.916667
## 986486 52.18333 -2.016667
## 986487 51.78333  0.266667
## 986488 52.33333 -3.400000
## 986489 51.96667 -2.900000
## 986490 55.85000 -2.383333
## 986491 54.83333 -3.283333
## 986492 51.18333 -1.516667
## 986493 50.90000 -4.283333
## 986494 52.80000 -1.866667
## 986495 50.66667 -2.600000
## 986496 55.60000 -2.783333
## 986497 51.01667 -4.250000
## 986498 50.50000 -3.616667
## 986499 51.70000 -0.416667
## 986500 52.15000 -1.966667
## 986501 52.18333 -0.200000
## 986502 52.38333 -0.183333
## 986503 51.08333 -1.283333
## 986504 51.18333 -1.516667
## 986505 52.38333 -0.183333
## 986506 53.23333 -4.016667
## 986507 52.25000 -4.250000
## 986508 51.69889 -3.426944
## 986509 52.66667 -3.716667
## 986510 57.30000 -4.266667
## 986511 56.31667 -3.350000
## 986512 52.25000 -4.233333
## 986513 52.25000 -4.250000

Now, we will display GB cities on map with a single flag.

library(leaflet)

## Warning: package 'leaflet' was built under R version 3.4.4

GBIcon <- makeIcon(
  iconUrl = "http://icons.iconarchive.com/icons/pan-tera/flags/128/Great-Britain-Flag-icon.png",
  iconWidth = 31*215/230, iconHeight = 31,
  iconAnchorX = 31*215/230/2, iconAnchorY = 16
)
df <- data.frame(lat = GBCities1$Latitude,
                 lng = GBCities1$Longitude)
df %>% 
  leaflet() %>%
  addTiles() %>%
  addMarkers(icon = GBIcon)

Let’s add some markers clustering as well.

df <- data.frame(lat = GBCities1$Latitude,
                 lng = GBCities1$Longitude)
df %>% 
  leaflet() %>%
  addTiles() %>%
  addMarkers(clusterOptions = markerClusterOptions())