Assignment7
#install.packages("readxl")
#install.packages("xlsx")library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(rgdal)## Loading required package: sp## rgdal: version: 1.4-8, (SVN revision 845)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 2.4.2, released 2019/06/28
## Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/rgdal/gdal
## GDAL binary built with GEOS: FALSE
## Loaded PROJ.4 runtime: Rel. 5.2.0, September 15th, 2018, [PJ_VERSION: 520]
## Path to PROJ.4 shared files: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/rgdal/proj
## Linking to sp version: 1.3-2library(countrycode)
library(ggmap)## Loading required package: ggplot2## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.## Please cite ggmap if you use it! See citation("ggmap") for details.library(readxl)
library(leaflet)
library(DT)
library(taucharts)
library(sp)cities<-read_excel("OAP_database.xls", sheet = 4)## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * … and 2 more problemscities<-cities[-c(1:2),]
cities <-cities[,c(3,2,4)]
names(cities)<-c("City","Country","PMLevel") # Renaming 3 columns
str(cities)## Classes 'tbl_df', 'tbl' and 'data.frame': 1099 obs. of 3 variables:
## $ City : chr "Alger" "Buenos Aires" "Adelaide" "Brisbane" ...
## $ Country: chr "Algeria" "Argentina" "Australia" "Australia" ...
## $ PMLevel: chr "42" "38" "13.5" "18.166666666666668" ...Worst 100 cities with high levels of PM2.5
cities$PMLevel<-as.numeric(cities$PMLevel)
str(cities)## Classes 'tbl_df', 'tbl' and 'data.frame': 1099 obs. of 3 variables:
## $ City : chr "Alger" "Buenos Aires" "Adelaide" "Brisbane" ...
## $ Country: chr "Algeria" "Argentina" "Australia" "Australia" ...
## $ PMLevel: num 42 38 13.5 18.2 13.8 ...cities$PMLevel<-round(cities$PMLevel,2)
cities %>% arrange(-PMLevel)%>%top_n(100)%>% datatable(rownames=FALSE)## Selecting by PMLevelWhich countries contribute the highest number of cities in the top 100 on PM10?
tmp<-cities%>%arrange(-PMLevel)%>%top_n(100)%>%
group_by(Country)%>%summarise(number_of_cities=length(Country))## Selecting by PMLevel## Selecting by PMLevel
tmp<-tmp%>%arrange(-number_of_cities)##Bar chart of countries with top 100 cities
tmp$Country<-forcats::fct_inorder(tmp$Country)
tauchart(tmp)%>%tau_bar("number_of_cities","Country",horizontal = "TRUE")%>% tau_legend()%>% tau_tooltip()## Neither color nor size aesthetics have been mapped. Legend plugin will be active but not displayed.Geographic Map of 100 Cities with highest levels of PM2.5
cities100<-cities%>%arrange(-PMLevel)%>%top_n(100)## Selecting by PMLevel## Selecting by PMLevel
cities100$CityCountry<-paste(cities100$City,cities100$Country,sep=", ")
head(cities100)## # A tibble: 6 x 4
## City Country PMLevel CityCountry
## <chr> <chr> <dbl> <chr>
## 1 Ahwaz Iran (Islamic Republic… 372 Ahwaz, Iran (Islamic Republic of)
## 2 Ulaanbaatar Mongolia 279 Ulaanbaatar, Mongolia
## 3 Sanandaj Iran (Islamic Republic… 254 Sanandaj, Iran (Islamic Republic …
## 4 Ludhiana India 251 Ludhiana, India
## 5 Quetta Pakistan 251. Quetta, Pakistan
## 6 Kermanshah Iran (Islamic Republic… 229 Kermanshah, Iran (Islamic Republi…register_google(key = "AIzaSyBO05QXAr_5L489qT03HCBzkLKirbcPPqQ")
register_google(key ="AIzaSyACnU62tBGJH53m-XGxDHBjuREJQ8NgJQU")
locs<-geocode(cities100$CityCountry)## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Ahwaz,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Ulaanbaatar,+Mongolia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Sanandaj,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Ludhiana,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Quetta,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kermanshah,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Peshawar,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Gaborone,+Botswana&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Yasouj,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kanpur,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Lahore,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Delhi,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Karachi,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Islamabad,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Lucknow,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Rawalpindi,+Pakistan&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Uromiyeh,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Qom,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Indore,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=khoramabad,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Agra,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Al+Ain,+United+Arab+Emirates&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Riyadh,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Al-Hafouf,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Lanzhou,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kolkata,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Van,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Dakar,+Senegal&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Makkah,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Xining,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Urumqi,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Faridabad,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Greater+Cairo,+Egypt&key=xxx-XGxDHBjuREJQ8NgJQU## "Greater Cairo, Egypt" not uniquely geocoded, using "17 mohammed mazhar, zamalek, giza governorate, egypt"## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Mexicali,+Mexico&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Jabalpur,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Dhaka,+Bangladesh&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Mumbai,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Dhanbad,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Ilam,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Jeddah,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Allahabad,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Bushehr,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kerman,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Jinan,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kuwait+City,+Kuwait&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Lagos,+Nigeria&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Beijing,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Dammam,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Patna,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Sarajevo,+Bosnia+and+Herzegovina&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Abu+Dhabi,+United+Arab+Emirates&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Meerut,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Xi'an,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Jaipur,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Qazvin,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Medan,+Indonesia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Chengdu,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Hefei,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Shenyang,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Yanbu,+Saudi+Arabia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kathmandu+Valley,+Nepal&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Taiyuan,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Varanasi,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Chongqing,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Wuhan,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Esfahan,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Shijiazhuang,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Konya,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Kars,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Hamedan,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Arak,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Harbin,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Tianjin,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Nanjing,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Denizli,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Zhengzhou,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Pune,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Hatay,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Nagpur,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Accra,+Ghana&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Hangzhou,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Tehran,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Yangon,+Myanmar&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Erzurum,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Bhopal,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Changsha,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Vijayawada,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Tecate,+Mexico&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Yinchuan,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Bangalore,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Rajkot,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Mandalay,+Myanmar&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Hyderabad,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Visakhapatnam,+India&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Mashhad,+Iran+(Islamic+Republic+of)&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Sfax,+Tunisia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Tunis,+Tunisia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Bizerte,+Tunisia&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Changchun,+China&key=xxx-XGxDHBjuREJQ8NgJQU## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Balikesir,+Turkey&key=xxx-XGxDHBjuREJQ8NgJQU## Using ggplot2
cities100$lat<-locs$lat
cities100$lon<-locs$lon
worldmap <- borders("world", fill="light grey", colour = "white") # create a layer of borders
worldmap <- ggplot() + worldmap
#Now Layer the cities on top
worldmap <- worldmap + geom_point(data=cities100,aes(x=lon, y=lat,size=PMLevel),alpha=.4,color="red")
worldmap + theme_void()
The Map - Interactive
cities100$popup<-paste("<table><tr><td>City:", cities100$City,"<br>Country:",cities100$Country, "<br>Annual Mean PM10 Level:", cities100$PMLevel,"</td></tr></table>")
leaflet(cities100)%>%#addTiles()%>%
addProviderTiles("CartoDB.Positron") %>%
setView(0, 0, zoom = 2) %>%
addCircles(stroke=FALSE, fillOpacity = .5, color="red", radius=~PMLevel*1000,popup=~popup)## Assuming "lon" and "lat" are longitude and latitude, respectively## Assuming "lon" and "lat" are longitude and latitude, respectivelycountries<-read_excel("OAP_database.xls", sheet = 5)## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * … and 13 more problemscountries<-countries[-c(1:2),c(2:3)]
names(countries)<-c("Country","PMLevel") # Renaming 3 columns
str(countries)## Classes 'tbl_df', 'tbl' and 'data.frame': 91 obs. of 2 variables:
## $ Country: chr "Estonia" "Mauritius" "Australia" "New Zealand" ...
## $ PMLevel: chr "11.132999999999999" "11.65" "13.179790073011779" "15" ...countries$PMLevel<-round(as.numeric(countries$PMLevel),2)
head(countries)## # A tibble: 6 x 2
## Country PMLevel
## <chr> <dbl>
## 1 Estonia 11.1
## 2 Mauritius 11.6
## 3 Australia 13.2
## 4 New Zealand 15
## 5 Ireland 15.2
## 6 Luxembourg 17.5countries$iso3c=countrycode(countries$Country,"country.name","iso3c")
countries$iso3c<-as.factor(countries$iso3c)
url <- "http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/50m/cultural/ne_50m_admin_0_countries.zip"
folder <- getwd()
file <- basename(url)
download.file(url, file)
unzip(file, exdir = folder)
#
world <- readOGR(dsn = folder,
layer = "ne_50m_admin_0_countries",
encoding = "UTF-8",
verbose = FALSE)
##############
world <- sp::merge(world, countries,
by.x = "ISO_A3",
by.y = "iso3c",
sort = FALSE,duplicateGeoms=TRUE)
#
pal <- colorNumeric(
palette = "Reds",
domain = countries$PMLevel
)
world_popup <- paste(world$ADMIN, ", PM10 Level:", world$PMLevel,sep = "")
#
leaflet(data = world) %>%
addTiles() %>%
setView(0, 0, zoom = 2) %>%
addPolygons(fillColor = ~pal(world$PMLevel),
fillOpacity = 1,
color = "#000000",
weight = 1,
label=~world_popup)%>% addLegend("bottomright", pal = pal, values = ~PMLevel,title = "Amount of PM10 level",opacity = 1)