setwd("C:/Users/munis/Documents/Comm in Data Science/Week 9")
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"
library(tidyverse) # my additions
## -- Attaching packages --------------------------------------- tidyverse 1.2.1 --
## v ggplot2 3.2.1     v purrr   0.3.2
## v tibble  2.1.3     v dplyr   0.8.3
## v tidyr   1.0.0     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.4.0
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(ggplot2)
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
#
library(scales) # referenced below
## 
## Attaching package: 'scales'
## The following object is masked from 'package:purrr':
## 
##     discard
## The following object is masked from 'package:readr':
## 
##     col_factor
# following per original script
library("tmap")
library("tmaptools")
library("leaflet")
library("sf")
## Linking to GEOS 3.6.1, GDAL 2.2.3, PROJ 4.9.3
library("leaflet.extras")
library("dplyr")
nhdata <- rio::import(nhdatafile)
nhdata <- nhdata[,c("County", "Clinton", "Sanders")]
nhdata$SandersMarginVotes <- nhdata$Sanders - nhdata$Clinton
nhdata$SandersPct <- (nhdata$Sanders) / (nhdata$Sanders + nhdata$Clinton) # Will use formatting later to multiply by a hundred
nhdata$ClintonPct <- (nhdata$Clinton) / (nhdata$Sanders + nhdata$Clinton)
nhdata$SandersMarginPctgPoints <- nhdata$SandersPct - nhdata$ClintonPct
usshapefile <- "cb_2014_us_county_5m/cb_2014_us_county_5m.shp"
usgeo <- read_shape(file=usshapefile, as.sf = TRUE)
## Warning: This function is deprecated and has been migrated to github.com/
## mtennekes/oldtmaptools
## Warning in readOGR(dir, base, verbose = FALSE, ...): Z-dimension discarded
qtm(usgeo)

str(usgeo)
## Classes 'sf' and 'data.frame':   3233 obs. of  10 variables:
##  $ STATEFP : Factor w/ 56 levels "01","02","04",..: 1 11 16 37 39 37 28 26 29 10 ...
##  $ COUNTYFP: Factor w/ 328 levels "001","003","005",..: 42 76 74 78 78 38 22 137 291 35 ...
##  $ COUNTYNS: Factor w/ 3233 levels "00023901","00025441",..: 120 430 738 1911 2024 1880 1399 1373 1490 298 ...
##  $ AFFGEOID: Factor w/ 3233 levels "0500000US01001",..: 30 442 844 2189 2302 2158 1669 1589 1764 344 ...
##  $ GEOID   : Factor w/ 3233 levels "01001","01003",..: 30 442 844 2189 2302 2158 1669 1589 1764 344 ...
##  $ NAME    : Factor w/ 1921 levels "Abbeville","Acadia",..: 620 592 945 1291 1665 692 320 1683 284 747 ...
##  $ LSAD    : Factor w/ 11 levels "00","03","04",..: 5 5 5 5 5 5 5 5 1 5 ...
##  $ ALAND   : Factor w/ 3233 levels "1000508842","1001064387",..: 1199 5 2047 452 1721 2091 1880 1194 2397 1215 ...
##  $ AWATER  : Factor w/ 3233 levels "0","10017640",..: 1626 414 1940 1718 1118 2724 2916 2228 1613 497 ...
##  $ geometry:sfc_MULTIPOLYGON of length 3233; first list element: List of 1
##   ..$ :List of 1
##   .. ..$ : num [1:9, 1:2] -88.2 -88.2 -88.2 -88.1 -87.5 ...
##   ..- attr(*, "class")= chr  "XY" "MULTIPOLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA
##   ..- attr(*, "names")= chr  "STATEFP" "COUNTYFP" "COUNTYNS" "AFFGEOID" ...
nhgeo <- usgeo[usgeo$STATEFP==nhfipscode,]
nhgeo <- dplyr::filter(usgeo, STATEFP == nhfipscode)
qtm(nhgeo)

str(nhgeo)
## Classes 'sf' and 'data.frame':   10 obs. of  10 variables:
##  $ STATEFP : Factor w/ 56 levels "01","02","04",..: 30 30 30 30 30 30 30 30 30 30
##  $ COUNTYFP: Factor w/ 328 levels "001","003","005",..: 6 8 5 1 12 3 14 10 2 15
##  $ COUNTYNS: Factor w/ 3233 levels "00023901","00025441",..: 1500 1501 1499 1496 1503 1498 1504 1502 1497 1505
##  $ AFFGEOID: Factor w/ 3233 levels "0500000US01001",..: 1769 1770 1768 1765 1772 1767 1773 1771 1766 1774
##  $ GEOID   : Factor w/ 3233 levels "01001","01003",..: 1769 1770 1768 1765 1772 1767 1773 1771 1766 1774
##  $ NAME    : Factor w/ 1921 levels "Abbeville","Acadia",..: 684 791 416 138 1470 334 1653 1131 282 1657
##  $ LSAD    : Factor w/ 11 levels "00","03","04",..: 5 5 5 5 5 5 5 5 5 5
##  $ ALAND   : Factor w/ 3233 levels "1000508842","1001064387",..: 2494 1831 2526 67 1382 1424 3172 1997 1991 730
##  $ AWATER  : Factor w/ 3233 levels "0","10017640",..: 55 1942 3097 778 1327 2460 1852 2454 638 1817
##  $ geometry:sfc_MULTIPOLYGON of length 10; first list element: List of 1
##   ..$ :List of 1
##   .. ..$ : num [1:327, 1:2] -72.3 -72.3 -72.3 -72.3 -72.3 ...
##   ..- attr(*, "class")= chr  "XY" "MULTIPOLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA
##   ..- attr(*, "names")= chr  "STATEFP" "COUNTYFP" "COUNTYNS" "AFFGEOID" ...
str(nhgeo$NAME)
##  Factor w/ 1921 levels "Abbeville","Acadia",..: 684 791 416 138 1470 334 1653 1131 282 1657
str(nhdata$County)
##  chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" "Grafton" ...
nhgeo$NAME <- as.character(nhgeo$NAME)
nhgeo <- nhgeo[order(nhgeo$NAME),]
nhdata <- nhdata[order(nhdata$County),]
identical(nhgeo$NAME,nhdata$County )
## [1] TRUE
nhmap <- append_data(nhgeo, nhdata, key.shp = "NAME", key.data="County")
## Warning: This function is deprecated and has been migrated to github.com/
## mtennekes/oldtmaptools
## Keys match perfectly.
str(nhmap)
## Classes 'sf' and 'data.frame':   10 obs. of  16 variables:
##  $ STATEFP                : Factor w/ 56 levels "01","02","04",..: 30 30 30 30 30 30 30 30 30 30
##  $ COUNTYFP               : Factor w/ 328 levels "001","003","005",..: 1 2 3 5 6 8 10 12 14 15
##  $ COUNTYNS               : Factor w/ 3233 levels "00023901","00025441",..: 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505
##  $ AFFGEOID               : Factor w/ 3233 levels "0500000US01001",..: 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774
##  $ GEOID                  : Factor w/ 3233 levels "01001","01003",..: 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774
##  $ NAME                   : chr  "Belknap" "Carroll" "Cheshire" "Coos" ...
##  $ LSAD                   : Factor w/ 11 levels "00","03","04",..: 5 5 5 5 5 5 5 5 5 5
##  $ ALAND                  : Factor w/ 3233 levels "1000508842","1001064387",..: 67 1991 1424 2526 2494 1831 1997 1382 3172 730
##  $ AWATER                 : Factor w/ 3233 levels "0","10017640",..: 778 638 2460 3097 55 1942 2454 1327 1852 1817
##  $ Clinton                : num  3495 3230 5132 2013 6918 ...
##  $ Sanders                : num  6005 5638 12441 3639 14245 ...
##  $ SandersMarginVotes     : num  2510 2408 7309 1626 7327 ...
##  $ SandersPct             : num  0.632 0.636 0.708 0.644 0.673 ...
##  $ ClintonPct             : num  0.368 0.364 0.292 0.356 0.327 ...
##  $ SandersMarginPctgPoints: num  0.264 0.272 0.416 0.288 0.346 ...
##  $ geometry               :sfc_POLYGON of length 10; first list element: List of 1
##   ..$ : num [1:33, 1:2] -71.7 -71.7 -71.7 -71.7 -71.7 ...
##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
##   ..- attr(*, "names")= chr  "STATEFP" "COUNTYFP" "COUNTYNS" "AFFGEOID" ...
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) + 
  tm_style_classic()
## Warning in tm_style_classic(): tm_style_classic is deprecated as of tmap
## version 2.0. Please use tm_style("classic", ...) instead
## 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.

nhstaticmap <- tm_shape(nhmap) +
  tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "PRGn") +
  tm_borders(alpha=.5) +
  tm_text("NAME", size=0.8) + 
  tm_style_classic()
## Warning in tm_style_classic(): tm_style_classic is deprecated as of tmap
## version 2.0. Please use tm_style("classic", ...) instead
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_tmap(nhstaticmap, filename="nhdemprimary.jpg")
## Warning in save_tmap(nhstaticmap, filename = "nhdemprimary.jpg"): save_tmap
## is deprecated as of tmap version 2.0. Please use tmap_save instead
## Warning in png(tmp, width = width, height = height, res = res): 'width=7,
## height=7' are unlikely values in pixels
## Map saved to C:\Users\munis\Documents\Comm in Data Science\Week 9\nhdemprimary.jpg
## Resolution: 1501.336 by 2937.385 pixels
## Size: 5.004452 by 9.791282 inches (300 dpi)
clintonPalette <- colorNumeric(palette = "Blues", domain=nhmap$ClintonPct)
library(scales)
nhpopup <- paste0("<b>County: ", nhmap$NAME, "</b><br />Sanders ", percent(nhmap$SandersPct), " - Clinton ", percent(nhmap$ClintonPct))
nhmap <- rename(nhmap, County = NAME)
leaflet(nhmap) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(stroke=FALSE, 
              smoothFactor = 0.2, 
              fillOpacity = .8, 
              popup=nhpopup, 
              color= ~clintonPalette(nhmap$ClintonPct)
              )
## Warning: sf layer has inconsistent datum (+proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs).
## Need '+proj=longlat +datum=WGS84'
nhmap_projected <- sf::st_transform(nhmap, "+proj=longlat +datum=WGS84")
leaflet(nhmap_projected) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(stroke=FALSE, 
              smoothFactor = 0.2, 
              fillOpacity = .8, 
              popup=nhpopup, 
              color= ~clintonPalette(nhmap$ClintonPct)
  )

South Carolina data

scdata <- rio::import(scdatafile)
scgeo <- dplyr::filter(usgeo, STATEFP==scfipscode)
qtm(scgeo)

candidates <- colnames(scdata[2:7])
for(i in 2:7){
  j = i + 7
  temp <- scdata[[i]] / scdata$Total
  scdata[[j]] <- temp
  colnames(scdata)[j] <- paste0(colnames(scdata)[i], "Pct")
}  
for(i in 1:nrow(scdata)){
  scdata$winner[i] <- names(which.max(scdata[i,2:7]))
}
sced <- rio::import("SCdegree.xlsx")
str(scgeo$NAME)
##  Factor w/ 1921 levels "Abbeville","Acadia",..: 554 995 810 35 1073 523 1662 359 100 331 ...
str(scdata$County)
##  chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" ...
scgeo$NAME <- as.character(scgeo$NAME)
scgeo <- scgeo[order(scgeo$NAME),]
scdata <- scdata[order(scdata$County),]
identical(scgeo$NAME,scdata$County )
## [1] TRUE
scmap <- append_data(scgeo, scdata, key.data = "County", key.shp = "NAME")
## Warning: This function is deprecated and has been migrated to github.com/
## mtennekes/oldtmaptools
## Keys match perfectly.
scmap <- rename(scmap, County = NAME)
scmap <- append_data(scmap, sced, key.shp = "County", key.data = "County")
## Warning: This function is deprecated and has been migrated to github.com/
## mtennekes/oldtmaptools
## Keys match perfectly.
minpct <- min(c(scmap$Donald.J.TrumpPct, scmap$Marco.RubioPct , scmap$Ted.CruzPct))
maxpct <- max(c(scmap$Donald.J.TrumpPct, scmap$Marco.RubioPct , scmap$Ted.CruzPct))

Create leaflet palettes for each layer of the map:

winnerPalette <- colorFactor(palette=c("#984ea3", "#e41a1c"), domain = scmap$winner)
trumpPalette <- colorNumeric(palette = "Purples", domain=c(minpct, maxpct))
rubioPalette <- colorNumeric(palette = "Reds", domain = c(minpct, maxpct))
cruzPalette <- colorNumeric(palette = "Oranges", domain = c(minpct, maxpct))
edPalette <- colorNumeric(palette = "Blues", domain=scmap$PctCollegeDegree)
scpopup <- paste0("<b>County: ", scmap$County, "<br />Winner: ", scmap$winner, "</b><br /><br />Trump: ", percent(scmap$Donald.J.TrumpPct), "<br />Rubio: ", percent(scmap$Marco.RubioPct), "<br />Cruz: ", percent(scmap$Ted.CruzPct), "<br /><br />Pct w college ed: ", scmap$PctCollegeDegree, "% vs state-wide avg of 25%")
scmap <- sf::st_transform(scmap, "+proj=longlat +datum=WGS84")
leaflet(scmap) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(stroke=TRUE,
              weight=1,
              smoothFactor = 0.2, 
              fillOpacity = .75, 
              popup=scpopup, 
              color= ~winnerPalette(scmap$winner),
              group="Winners"
  ) %>%
  addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "Rubio"))
scGOPmap2 <- leaflet(scmap) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(stroke=TRUE,
              weight=1,
              smoothFactor = 0.2, 
              fillOpacity = .75, 
              popup=scpopup, 
              color= ~winnerPalette(scmap$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(scmap$PctCollegeDegree),
              group="College degs"
  ) %>%
  
  addLayersControl(
    baseGroups=c("Winners", "Trump", "Rubio", "Cruz", "College degs"),
    position = "bottomleft",
    options = layersControlOptions(collapsed = FALSE)
  ) %>%
  addSearchOSM()
print(scGOPmap2)
htmlwidgets::saveWidget(scGOPmap2, file="scGOPwidget2.html")

save as an HTML file with dependencies in another directory:

htmlwidgets::saveWidget(widget=scGOPmap2, file="scGOPprimary_withdependencies.html", selfcontained=FALSE, libdir = "js")