HW#7
Pheobe Buffay
3/13/2022
library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
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## install.packages("USAboundariesData", repos = "https://ropensci.r-universe.dev", type = "source")library(ggplot2)
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## maplibrary(dplyr)
library(grid)
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## select2. Load the data, and clean it up:
#dataset
newdata<- read.csv("1976-2020-president.csv", header = T)
head(newdata)## year state state_po state_fips state_cen state_ic office
## 1 1976 ALABAMA AL 1 63 41 US PRESIDENT
## 2 1976 ALABAMA AL 1 63 41 US PRESIDENT
## 3 1976 ALABAMA AL 1 63 41 US PRESIDENT
## 4 1976 ALABAMA AL 1 63 41 US PRESIDENT
## 5 1976 ALABAMA AL 1 63 41 US PRESIDENT
## 6 1976 ALABAMA AL 1 63 41 US PRESIDENT
## candidate party_detailed writein candidatevotes
## 1 CARTER, JIMMY DEMOCRAT FALSE 659170
## 2 FORD, GERALD REPUBLICAN FALSE 504070
## 3 MADDOX, LESTER AMERICAN INDEPENDENT PARTY FALSE 9198
## 4 BUBAR, BENJAMIN ""BEN"" PROHIBITION FALSE 6669
## 5 HALL, GUS COMMUNIST PARTY USE FALSE 1954
## 6 MACBRIDE, ROGER LIBERTARIAN FALSE 1481
## totalvotes version notes party_simplified
## 1 1182850 20210113 NA DEMOCRAT
## 2 1182850 20210113 NA REPUBLICAN
## 3 1182850 20210113 NA OTHER
## 4 1182850 20210113 NA OTHER
## 5 1182850 20210113 NA OTHER
## 6 1182850 20210113 NA LIBERTARIAN#State map of usa
map("state")
newdata$color <- ifelse(newdata$party_simplified =="DEMOCRAT","Blue",
ifelse(newdata$party_simplified =="REPUBLICAN", "Red", "White"))
typeof(newdata$color)## [1] "character"##final
data_new2 <- newdata %>%
group_by(state, year) %>%
slice_max(candidatevotes) # Top N highest values by group
final <- data_new2 %>% arrange(data_new2$year)
neededvar <- c("year", "state", "state_fips", "party_simplified", "candidate", "color")
myEdata <- final[neededvar]
head(myEdata)## # A tibble: 6 x 6
## # Groups: state, year [6]
## year state state_fips party_simplified candidate color
## <int> <chr> <int> <chr> <chr> <chr>
## 1 1976 ALABAMA 1 DEMOCRAT CARTER, JIMMY Blue
## 2 1976 ALASKA 2 REPUBLICAN FORD, GERALD Red
## 3 1976 ARIZONA 4 REPUBLICAN FORD, GERALD Red
## 4 1976 ARKANSAS 5 DEMOCRAT CARTER, JIMMY Blue
## 5 1976 CALIFORNIA 6 REPUBLICAN FORD, GERALD Red
## 6 1976 COLORADO 8 REPUBLICAN FORD, GERALD RedQuestion 1 Part 1
temp <- filter(myEdata, year==2000)
temp <- temp[match(state.fips$fips, temp$state_fips), ]
map("state", col=temp$color, fill=TRUE)
legend("bottomright", bty="n", legend=c("Democrat", "Republican", "Others"), fill = c("blue", "red", "white"), cex=0.8, title = "Candidates")
title("Presidential Election Results by State in 2000", line=1)
Question 1 Part 2
Presidential lection results by year and state
years=seq(1976, 2020, by=4)
par(mfrow=c(3,4), mar=c(0,0,0,0))
for (i in years) {
temp <- filter(myEdata, year==i)
temp <- temp[match(state.fips$fips, temp$state_fips), ]
map("state", col=temp$color, fill=T)
mtext(i,side=3,line=1)
}
legend("bottomleft", inset = c(-0.15, -0.6), xpd=TRUE, legend = c("Democrat", "Republican", "Others"), fill=c("blue", "red", "white"), bty = "n", title = "Presidential election results by year and state",cex=0.6)
Part 2: Interactive Maps with Leaflet
1. Get familiar with the leaflet package
Open Street Map
myMap <- leaflet() %>%
addProviderTiles(providers$OpenStreetMap)
myMap %>% setView(lat=33.947474, lng=-83.373671, zoom = 12) #for Athens areaTopographic map
TopoMap <- leaflet() %>%
addProviderTiles(providers$OpenTopoMap)
TopoMap %>% setView(lat=33.947474, lng=-83.373671, zoom = 7) #for Athens areaEsri.NatGeoWorldMap
Esrimap <- leaflet() %>%
addProviderTiles(providers$Esri.NatGeoWorldMap)
Esrimap %>% setView(lat=33.947474, lng=-83.373671, zoom = 12) #for Athens areaAdd your own shapefiles
#loading the dataset
zipF<- "C:\\Users\\Asus\\OneDrive - University of Georgia\\PhD\\Spring 2022\\AAEC 8610\\220130_rrc_outline_block_al2.zip"
outDir<- "C:\\Users\\Asus\\OneDrive - University of Georgia\\PhD\\Spring 2022\\AAEC 8610\\dataset"
unzip(zipF,exdir=outDir)sp <- shapefile("C:/Users/Asus/OneDrive - University of Georgia/PhD/Spring 2022/AAEC 8610/T220130_RRC_Outline_Block_AL2.shp")
# Projection is necessary for R to place the coordinates correctly
campShapeFile <- spTransform(sp, CRS("+proj=longlat +datum=WGS84 +no_defs"))
head(campShapeFile)## OBJECTID_1 OBJECTID Block_Let Camp_SSID Block_Name Block_SSID SMSD_Cname
## 0 1 1 I CXB-232 C04X_I CXB-232_I163 Camp 04X
## 1 2 2 B CXB-232 C04X_B CXB-232_B165 Camp 04X
## 2 3 3 F CXB-232 C04X_F CXB-232_F161 Camp 04X
## 3 4 4 C CXB-232 C04X_C CXB-232_C166 Camp 04X
## 4 5 5 E CXB-232 C04X_E CXB-232_E160 Camp 04X
## 5 6 6 H CXB-232 C04X_H CXB-232_H162 Camp 04X
## Camp_Alias NPM_Cname Area_Acres CampName
## 0 Camp 4 Extension Camp 04 Extension 17.579304 Camp 4 Extension
## 1 Camp 4 Extension Camp 04 Extension 19.796469 Camp 4 Extension
## 2 Camp 4 Extension Camp 04 Extension 8.892700 Camp 4 Extension
## 3 Camp 4 Extension Camp 04 Extension 40.189147 Camp 4 Extension
## 4 Camp 4 Extension Camp 04 Extension 17.429451 Camp 4 Extension
## 5 Camp 4 Extension Camp 04 Extension 8.238809 Camp 4 Extension
## Area_SqM Shape_Leng Shape_Le_1 Shape_Area
## 0 71140.9196299387 0.012361753 0.012361755 6.192077e-06
## 1 80113.4668634516 0.010098287 0.010098287 6.973411e-06
## 2 35987.4806593324 0.007094379 0.007094378 3.132450e-06
## 3 162639.706686226 0.023266098 0.023266094 1.415641e-05
## 4 70534.4857807752 0.013253804 0.013253802 6.139350e-06
## 5 33341.2781127569 0.006681391 0.006681390 2.901994e-06• Zoom your map onto South-Eastern Bangladesh (setView(92.14871, 21.18780, zoom = 12)) • Add the shapefile to your map with:
Rohinga <- leaflet(campShapeFile) %>%
addPolygons(color = "#74C476", weight = 1, smoothFactor = 0.5,
opacity = 1.0, fillOpacity = 0.7,
label = campShapeFile$Block_No,
highlightOptions = highlightOptions(color = "white", weight = 2,
bringToFront = TRUE))
Rohinga %>% setView(lat= 21.18780, lng=92.14871, zoom = 13)3. Add tiles from the web
• Start a new leaflet map and zoom onto the USA. • See what happens when you add these tiles (with %>% of course):
leaflet() %>%
addProviderTiles(providers$OpenStreetMap) %>%
setView(lat=35.227085, lng=-80.843124, zoom = 7) %>%
addWMSTiles("http://mesonet.agron.iastate.edu/cgi-bin/wms/nexrad/n0r.cgi",
layers = "nexrad-n0r-900913",
options = WMSTileOptions(format = "image/png", transparent = TRUE),
attribution = "Weather data © 2012 IEM Nexrad")