GIS
Christina Takla
2023-04-11
setwd("~/Data110/4.5.23/GIS")
nhdatafile <- "NHD2016.xlsx"
nhdatafilecsv <- "NHD2016.csv"
usshapefile <- "cb_2014_us_county_5m/cb_2014_us_county_5m.shp"
nhfipscode <- "33"
scdatafile <- "SCGOP2016.csv"
scfipscode <- "45"Install libraries/packages
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0 ✔ purrr 1.0.1
## ✔ tibble 3.1.8 ✔ dplyr 1.1.0
## ✔ tidyr 1.3.0 ✔ stringr 1.5.0
## ✔ readr 2.1.3 ✔ forcats 1.0.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()#install.packages("tmap")
#install.packages("tmaptools")
library(tmap)## Warning: package 'tmap' was built under R version 4.2.3library(tmaptools)## Warning: package 'tmaptools' was built under R version 4.2.3library(leaflet)## Warning: package 'leaflet' was built under R version 4.2.3library(sf)## Warning: package 'sf' was built under R version 4.2.3## Linking to GEOS 3.9.3, GDAL 3.5.2, PROJ 8.2.1; sf_use_s2() is TRUE#install.packages("leaflet.extras")
#install.packages("rio")
#install.packages("htmlwidgets")
#install.packages("sf")
#install.packages("sp")
library(leaflet.extras)## Warning: package 'leaflet.extras' was built under R version 4.2.3library(rio)## Warning: package 'rio' was built under R version 4.2.3library(sp) ## Warning: package 'sp' was built under R version 4.2.3#Load the CSV
nhdata <- import(nhdatafilecsv) Eliminate unecessary columns
nhdata <- nhdata[,c("County", "Clinton", "Sanders")] add percents and margins
nhdata$SandersMarginVotes <- nhdata$Sanders - nhdata$Clinton
nhdata$SandersPct <- (nhdata$Sanders - nhdata$Clinton) / (nhdata$Sanders + nhdata$Clinton)
nhdata$ClintonPct <- (nhdata$Clinton - nhdata$Sanders) / (nhdata$Sanders + nhdata$Clinton)
nhdata$SandersMarginPctgPoints <- nhdata$SandersPct - nhdata$ClintonPct Get geographic data
#install.packages("raster")
#install.packages("rgdal")
library(raster)## Warning: package 'raster' was built under R version 4.2.3##
## Attaching package: 'raster'## The following object is masked from 'package:dplyr':
##
## selectlibrary(rgdal)## Warning: package 'rgdal' was built under R version 4.2.3## Please note that rgdal will be retired during 2023,
## plan transition to sf/stars/terra functions using GDAL and PROJ
## at your earliest convenience.
## See https://r-spatial.org/r/2022/04/12/evolution.html and https://github.com/r-spatial/evolution
## rgdal: version: 1.6-5, (SVN revision 1199)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.5.2, released 2022/09/02
## Path to GDAL shared files: C:/Users/takla/AppData/Local/R/win-library/4.2/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ runtime: Rel. 8.2.1, January 1st, 2022, [PJ_VERSION: 821]
## Path to PROJ shared files: C:/Users/takla/AppData/Local/R/win-library/4.2/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.6-0
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal.usgeo <- shapefile("cb_2014_us_county_5m/cb_2014_us_county_5m.shp") ## Warning: [vect] Z coordinates ignoredQuick plot of the shapefile
tmap_options(check.and.fix = TRUE)
qtm(usgeo)## Warning: The shape usgeo is invalid. See sf::st_is_valid
view(usgeo)Subset the data files
nhgeo <- usgeo[usgeo$STATEFP==nhfipscode,] tmap test plot
qtm(nhgeo)
Check the sturcture of the object and adjust to characters
str(nhgeo)## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
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## .. ..$ COUNTYFP: chr [1:10] "009" "011" "007" "001" ...
## .. ..$ COUNTYNS: chr [1:10] "00873178" "00873179" "00873177" "00873174" ...
## .. ..$ AFFGEOID: chr [1:10] "0500000US33009" "0500000US33011" "0500000US33007" "0500000US33001" ...
## .. ..$ GEOID : chr [1:10] "33009" "33011" "33007" "33001" ...
## .. ..$ NAME : chr [1:10] "Grafton" "Hillsborough" "Coos" "Belknap" ...
## .. ..$ LSAD : chr [1:10] "06" "06" "06" "06" ...
## .. ..$ ALAND : int [1:10] 130959956 -2025747080 353249502 1036582289 1799805954 1830366195 955401980 -1875570227 -1883508361 1391587566
## .. ..$ AWATER : int [1:10] 105375486 41604851 90773891 177039345 259517418 57990901 39157548 57788894 158933434 38070546
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## .. .. ..$ : chr [1:2] "x" "y"
## .. .. ..$ : chr [1:2] "min" "max"
## ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
## .. .. ..@ projargs: chr "+proj=longlat +datum=NAD83 +no_defs"
## .. .. ..$ comment: chr "GEOGCRS[\"unknown\",\n DATUM[\"North American Datum 1983\",\n ELLIPSOID[\"GRS 1980\",6378137,298.2572"| __truncated__
## ..$ comment: chr "FALSE"str(nhdata$County)## chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" "Grafton" "Hillsborough" ...nhgeo$NAME <- as.character(nhgeo$NAME) Order each data set by county name
nhgeo <- nhgeo[order(nhgeo$NAME),]
nhdata <- nhdata[order(nhdata$County),]
identical(nhgeo$NAME,nhdata$County) ## [1] TRUEMerge geo data nad results data
library(sf)
nhmap <- merge(nhgeo, nhdata, by.x = "NAME", by.y = "County")
str(nhmap)## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 15 variables:
## .. ..$ NAME : chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" ...
## .. ..$ STATEFP : chr [1:10] "33" "33" "33" "33" ...
## .. ..$ COUNTYFP : chr [1:10] "001" "003" "005" "007" ...
## .. ..$ COUNTYNS : chr [1:10] "00873174" "00873175" "00873176" "00873177" ...
## .. ..$ AFFGEOID : chr [1:10] "0500000US33001" "0500000US33003" "0500000US33005" "0500000US33007" ...
## .. ..$ GEOID : chr [1:10] "33001" "33003" "33005" "33007" ...
## .. ..$ LSAD : chr [1:10] "06" "06" "06" "06" ...
## .. ..$ ALAND : int [1:10] 1036582289 -1883508361 1830366195 353249502 130959956 -2025747080 -1875570227 1799805954 955401980 1391587566
## .. ..$ AWATER : int [1:10] 177039345 158933434 57990901 90773891 105375486 41604851 57788894 259517418 39157548 38070546
## .. ..$ Clinton : int [1:10] 3495 3230 5132 2013 6918 28147 12250 22829 8813 2497
## .. ..$ Sanders : int [1:10] 6005 5638 12441 3639 14245 39245 18107 31065 15881 5915
## .. ..$ SandersMarginVotes : int [1:10] 2510 2408 7309 1626 7327 11098 5857 8236 7068 3418
## .. ..$ SandersPct : num [1:10] 0.264 0.272 0.416 0.288 0.346 ...
## .. ..$ ClintonPct : num [1:10] -0.264 -0.272 -0.416 -0.288 -0.346 ...
## .. ..$ SandersMarginPctgPoints: num [1:10] 0.528 0.543 0.832 0.575 0.692 ...
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## ..$ comment: chr "FALSE"Create a static map
qtm(nhmap, "SandersMarginVotes") ## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
qtm(nhmap, "SandersMarginPctgPoints") 
tm_shape(nhmap) +
tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "PRGn") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8) ## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
Change the theme to classic and view the map
nhstaticmap <- tm_shape(nhmap) +
tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "viridis") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8) +
tm_style("classic")
nhstaticmap ## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
Save the map to jpg
tmap_save(nhstaticmap, filename="nhdemprimary.jpg") ## Map saved to C:\Users\takla\OneDrive\Documents\Data110\4.5.23\GIS\nhdemprimary.jpg## Resolution: 1501.336 by 2937.385 pixels## Size: 5.004452 by 9.791282 inches (300 dpi)Create palette and pop-up window
clintonPalette <- colorNumeric(palette = "Blues", domain=nhmap$ClintonPct)library(scales)##
## Attaching package: 'scales'## The following object is masked from 'package:purrr':
##
## discard## The following object is masked from 'package:readr':
##
## col_factornhpopup <- paste0("County: ", nhmap$NAME,
"Sanders ", percent(nhmap$SandersPct), " - Clinton ", percent(nhmap$ClintonPct)) Generate interactive map
nhmap_projected <- sp::spTransform(nhmap, "+proj=longlat +datum=WGS84")
leaflet(nhmap_projected) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=FALSE,
smoothFactor = 0.2,
fillOpacity = .8,
popup=nhpopup,
color= ~clintonPalette(nhmap$ClintonPct))South Carolina shapefile and data
scdata <- rio::import(scdatafile)scgeo <- usgeo[usgeo@data$STATEFP=="45",]
qtm(scgeo) 
Add a column with percent of votes for each candidate
candidates <- colnames(scdata[2:7])
for(i in 2:7){
j = i + 7
temp <- scdata[[i]] / scdata$Total
scdata[[j]] <- temp
colnames(scdata)[j] <- paste0(colnames(scdata)[i], "Pct")
}
winner <- colnames(scdata[2:7])Winner in each precinct
for(i in 1:nrow(scdata)){
scdata$winner[i] <- names(which.max(scdata[i,2:7]))
} Import spreadsheet with percent of adult population holding at least a 4 year decree
sced <- rio::import("SCdegree.xlsx") str(scgeo$NAME) ## chr [1:46] "Edgefield" "Lee" "Horry" "Allendale" "Marion" "Dorchester" ...str(scdata$County) ## chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" "Barnwell" ...scgeo$NAME <- as.character(scgeo$NAME) Check if county names are in the same format
scgeo <- scgeo[order(scgeo$NAME),]
scdata <- scdata[order(scdata$County),]
identical(scgeo$NAME,scdata$County ) ## [1] TRUEAdd election results and rename county column
scmap <- merge(scgeo, scdata, by.x = "NAME", by.y = "County") Color by strength of win
minpct <- min(c(scdata$`Donald J TrumpPct`, scdata$`Marco RubioPct`, scdata$`Ted CruzPct`
))
maxpct <- max(c(scdata$`Donald J TrumpPct`, scdata$`Marco RubioPct`, scdata$`Ted CruzPct`
)) Create leaflet palettes fo reach layer of the map
trumpPalette <- colorNumeric(palette = "Purples", domain=c(minpct, maxpct))
rubioPalette <- colorNumeric(palette = "Reds", domain = c(minpct, maxpct))
cruzPalette <- colorNumeric(palette = "Oranges", domain = c(minpct, maxpct))
winnerPalette <- colorFactor(palette=c("#984ea3", "#e41a1c"), domain = scmap$winner)
edPalette <- colorNumeric(palette = "Blues", domain=scmap$PctCollegeDegree) Create a pop-up
scpopup <- paste0("<b>County: ", scmap$NAME, "<br />Winner: ", scmap$winner, "</b><br /><
br />Trump: ", percent(scmap$`Donald J TrumpPct`), "<br />Rubio: ", percent(scmap$`Marco
RubioPct`), "<br />Cruz: ", percent(scmap$`Ted CruzPct`), "<br /><br />Pct w college ed:
", sced$PctCollegeDegree, "% vs state-wide avg of 25%")Add the projection
scmap <- sp::spTransform(scmap, "+proj=longlat +datum=WGS84") Basic Interactive Map
leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$winner),
group="Winners" ) %>%
addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "R
ubio")) Top 3 candidates in their own layers with an education layer
scGOPmap <- leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$winner),
group="Winners" ) %>%
addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "Rubio")) %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~trumpPalette(scmap$`Donald J TrumpPct`),
group="Trump") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~rubioPalette(scmap$`Marco RubioPct`),
group="Rubio") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~cruzPalette(scmap$`Ted CruzPct`),
group="Cruz") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~edPalette(sced$PctCollegeDegree),
group="College degs") %>%
addLayersControl(
baseGroups=c("Winners", "Trump", "Rubio", "Cruz", "College degs"),
position = "bottomleft",
options = layersControlOptions(collapsed = FALSE))
scGOPmap Save as a self contained HTML file
htmlwidgets::saveWidget(scGOPmap, file="scGOPwidget2.html")
# save as an HTML file with dependencies in another directory:
htmlwidgets::saveWidget(widget=scGOPmap, file="scGOPprimary_withdependencies.html", selfcontained=FALSE, libdir = "js")