Data 110 Unit 5 Creating Maps
Kris Sutton
7/3/2021
Using the tutorial from “Creating Maps in R”, I will complete steps 1 – 10 to create a static map and a interactive map.
Machlis, S. (2017, October 31). Create maps in R in 10 (fairly) easy steps. Computerworld. https://www.computerworld.com/article/3038270/create-maps-in-r-in-10-fairly-easy-steps.html?jwsource=cl.
Load the libraries.
##libraries
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.0.5## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.4 v purrr 0.3.4
## v tibble 3.1.2 v dplyr 1.0.6
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## Warning: package 'tibble' was built under R version 4.0.5## Warning: package 'tidyr' was built under R version 4.0.5## Warning: package 'readr' was built under R version 4.0.5## Warning: package 'purrr' was built under R version 4.0.5## Warning: package 'dplyr' was built under R version 4.0.5## Warning: package 'stringr' was built under R version 4.0.5## Warning: package 'forcats' was built under R version 4.0.5## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(tmap)## Warning: package 'tmap' was built under R version 4.0.5library(tmaptools)## Warning: package 'tmaptools' was built under R version 4.0.5library(leaflet)## Warning: package 'leaflet' was built under R version 4.0.5library(sf)## Warning: package 'sf' was built under R version 4.0.5## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1library(leaflet.extras)## Warning: package 'leaflet.extras' was built under R version 4.0.5library(dplyr)
library(rio)## Warning: package 'rio' was built under R version 4.0.5library(sp)## Warning: package 'sp' was built under R version 4.0.5Bringing in files and FIPS codes for New Hampshire and South Carolina.
setwd("C:/Users/kris.sutton/OneDrive - Government of The District of Columbia/Desktop/Personal/Data 110/R Studio/Datasets")
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"
nhdata <- rio::import(nhdatafilecsv)
options(scipen= 999 )Eliminate columns for minor candidates and just use County, Clinton and Sanders columns:
##c function to return array which removes all but the major candidates and county
nhdata <- nhdata[,c("County", "Clinton", "Sanders")]Creating new variables SandersMarginVotes, SandersPct(of votes), ClintonPct(of votes), and SandersMarginPctgPoints(over Clinton).
## difference between Sanders and Clinton votes
nhdata$SandersMarginVotes <- nhdata$Sanders - nhdata$Clinton
## percentage of votes Sanders received
nhdata$SandersPct <- (nhdata$Sanders) / (nhdata$Sanders + nhdata$Clinton)
## percentage of votes Clinton received
nhdata$ClintonPct <- (nhdata$Clinton) / (nhdata$Sanders + nhdata$Clinton)
## percentage of Sanders margin over Clinton
nhdata$SandersMarginPctgPoints <- nhdata$SandersPct - nhdata$ClintonPct
str(nhdata)## 'data.frame': 10 obs. of 7 variables:
## $ County : chr "Belknap" "Carroll" "Cheshire" "Coos" ...
## $ Clinton : int 3495 3230 5132 2013 6918 28147 12250 22829 8813 2497
## $ Sanders : int 6005 5638 12441 3639 14245 39245 18107 31065 15881 5915
## $ SandersMarginVotes : int 2510 2408 7309 1626 7327 11098 5857 8236 7068 3418
## $ 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 ...Quick plot (qtm stands for quick thematic map) of the shapefile and check its structure.
setwd("C:/Users/kris.sutton/OneDrive - Government of The District of Columbia/Desktop/Personal/Data 110/R Studio/Datasets")
library(raster)## Warning: package 'raster' was built under R version 4.0.5##
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## Path to GDAL shared files: C:/Users/kris.sutton/Documents/R/R-4.0.3/library/rgdal/gdal
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## Path to PROJ shared files: C:/Users/kris.sutton/Documents/R/R-4.0.3/library/rgdal/proj
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## Overwritten PROJ_LIB was C:/Users/kris.sutton/Documents/R/R-4.0.3/library/rgdal/projusgeo <- shapefile(("cb_2014_us_county_5m.shp"))## Warning in rgdal::readOGR(dirname(x), fn, stringsAsFactors = stringsAsFactors, :
## Z-dimension discardedqtm(usgeo)
Subset just the NH data from the US shapefile
nhgeo <- usgeo[usgeo$STATEFP==nhfipscode,]tmap test plot of the New Hampshire data
qtm(nhgeo)
Structure of the object.
str(nhgeo)## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 9 variables:
## .. ..$ STATEFP : chr [1:10] "33" "33" "33" "33" ...
## .. ..$ 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 : chr [1:10] "4425927252" "2269220216" "4648216798" "1036582289" ...
## .. ..$ AWATER : chr [1:10] "105375486" "41604851" "90773891" "177039345" ...
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## .. ..- attr(*, "dimnames")=List of 2
## .. .. ..$ : 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"str(nhdata$County)## chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" "Grafton" "Hillsborough" ...Change the county names to plain characters in nhgeo.
nhgeo$NAME <- as.character(nhgeo$NAME)Ordering each data set by county name.
nhgeo <- nhgeo[order(nhgeo$NAME),]
nhdata <- nhdata[order(nhdata$County),]
str(nhgeo)## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 9 variables:
## .. ..$ 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" ...
## .. ..$ NAME : chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" ...
## .. ..$ LSAD : chr [1:10] "06" "06" "06" "06" ...
## .. ..$ ALAND : chr [1:10] "1036582289" "2411458935" "1830366195" "4648216798" ...
## .. ..$ AWATER : chr [1:10] "177039345" "158933434" "57990901" "90773891" ...
## ..@ polygons :List of 10
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
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## .. .. .. ..@ ID : chr "1100"
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
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## .. ..- attr(*, "dimnames")=List of 2
## .. .. ..$ : 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"str(nhdata$County)## chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" "Grafton" "Hillsborough" ...nhmap <- merge(nhgeo, nhdata, by.x = "NAME", by.y = "County")
str(nhmap)## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 15 variables:
## .. ..$ 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 : chr [1:10] "1036582289" "2411458935" "1830366195" "4648216798" ...
## .. ..$ AWATER : chr [1:10] "177039345" "158933434" "57990901" "90773891" ...
## .. ..$ 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] 0.632 0.636 0.708 0.644 0.673 ...
## .. ..$ ClintonPct : num [1:10] 0.368 0.364 0.292 0.356 0.327 ...
## .. ..$ SandersMarginPctgPoints: num [1:10] 0.264 0.272 0.416 0.288 0.346 ...
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## .. .. ..@ projargs: chr "+proj=longlat +datum=NAD83 +no_defs"Create a static map with tmap’s qtm() function. Shows margin votes of Sanders over Clints by county.
qtm(nhmap, "SandersMarginVotes") +
## making legend wider
tm_layout("Sanders Margin Votes", legend.width = 1)
Testing the tm_shape() function.
tm_shape(nhmap) +
tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "PiYG") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8)## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output## 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 = "cividis") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8) +
tm_style("classic")
nhstaticmap## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output## 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.
Stored the static map in a variable, and changed the theme to “classic” style:
Making legend bigger.
nhstaticmap <- nhstaticmap +
tm_layout("Sanders Margin Votes", legend.width = 1)
nhstaticmap## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
Save the map to a jpg file with tmap’s tmap_save():
tmap_save(nhstaticmap, filename="nhdemprimary.jpg") ## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output## Map saved to C:\Users\kris.sutton\OneDrive - Government of The District of Columbia\Desktop\Personal\Data 110\R Studio\Datasets\nhdemprimary.jpg## Resolution: 1501.336 by 2937.385 pixels## Size: 5.004452 by 9.791282 inches (300 dpi)Code for a basic interactive map, this time for Clinton percentages in NH. Creating pallette for Clinton, and a pop up window.
##creating a pallette
clintonPalette <- colorNumeric(palette = "Blues", domain=nhmap$ClintonPct)
library(scales)## Warning: package 'scales' was built under R version 4.0.5##
## Attaching package: 'scales'## The following object is masked from 'package:purrr':
##
## discard## The following object is masked from 'package:readr':
##
## col_factorlibrary(raster)
nhpopup <- paste0("County: ", nhmap$NAME,
"Sanders ", percent(nhmap$SandersPct), " - Clinton ", percent(nhmap$ClintonPct))Now generate the 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$ClintonPct))Bringing in South Carolina data, shapefile and Quick plot of scgeo SC geospatial object.
scdata <- rio::import(scdatafile)
scgeo <- usgeo[usgeo@data$STATEFP=="45",]
qtm(scgeo)
Adding 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$Total
scdata[[j]] <- temp
colnames(scdata)[j] <- paste0(colnames(scdata)[i], "Pct")
}
winner <- colnames(scdata[2:7])
##get winner in each precinct
for(i in 1:nrow(scdata)){
scdata$winner[i] <- names(which.max(scdata[i,2:7]))
}Import spreadsheet with percent of adult population holding at least a 4-yr college degree.
sced <- rio::import("SCdegree.xlsx")Check if county names are in the same format in both files.
str(scgeo$NAME)## chr [1:46] "Edgefield" "Lee" "Horry" "Allendale" "Marion" "Dorchester" ...str(scdata$County)## chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" "Barnwell" ...# Change the county names to plain characters in scgeo:
scgeo$NAME <- as.character(scgeo$NAME)
# Order each data set by county name
scgeo <- scgeo[order(scgeo$NAME),]
scdata <- scdata[order(scdata$County),]
identical(scgeo$NAME,scdata$County )## [1] TRUEAdd the election results and rename county column.
scmap <- merge(scgeo, scdata, by.x = "NAME", by.y = "County")
scmap## class : SpatialPolygonsDataFrame
## features : 46
## extent : -83.35324, -78.54109, 32.0346, 35.2154 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=NAD83 +no_defs
## variables : 23
## names : NAME, STATEFP, COUNTYFP, COUNTYNS, AFFGEOID, GEOID, LSAD, ALAND, AWATER, Jeb Bush, Ben Carson, Ted Cruz, John R Kasich, Marco Rubio, Donald J Trump, ...
## min values : Abbeville, 45, 001, 01244251, 0500000US45001, 45001, 06, 1016985343, 108743547, 21, 32, 44, 12, 92, 160, ...
## max values : York, 45, 091, 01252740, 0500000US45091, 45091, 06, 987179097, 9746224, 6548, 8036, 22899, 7683, 22875, 26445, ...Accounting for 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 for each 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 popup.
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%")
scmap <- sp::spTransform(scmap, "+proj=longlat +datum=WGS84")Basic interactive map of winner by county.
leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$winner),
group="Winners" ) %>%
addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "Rubio")) Top 3 candidates in their own layers and add education layer, store in variable.
scGOPmap <- leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$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), #this data is in the sced table, not scmaps
group="College degs") %>%
addLayersControl(
baseGroups=c("Winners", "Trump", "Rubio", "Cruz", "College degs"),
position = "bottomleft",
options = layersControlOptions(collapsed = FALSE))
scGOPmap Save as self-contained html file.
htmlwidgets::saveWidget(scGOPmap, file="scGOPwidget2.html")
htmlwidgets::saveWidget(widget=scGOPmap, file="scGOPprimary_withdependencies.html", selfcontained=FALSE, libdir = "js")