title: “G4D- Asignment No 1(i)” author: “Miriam Kasebele” date: “31 10 2018” output: html_document: df_print: paged
Introduction This is an R Markdown Notebook aimed at learning how to make thematic maps. It is based on the cartography R package developed by Timothée Giraud as well as on code written by Bhaskar Karambelkar.
The G4D Assignment No. 1 comprises two tasks: (i) to reproduce and publish a notebook similar to this one; and (ii) to add new examples of R mapping functionalities to the notebook based on the geospatial data processing skills learned at Data Camp. The assignment can be done using RStudio Cloud (for editing the document) and RPubs (for publishing the document).
Static Mapping
library(rgdal)## Loading required package: sp## rgdal: version: 1.3-6, (SVN revision 773)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 2.1.3, released 2017/20/01
## Path to GDAL shared files: /usr/share/gdal/2.1
## GDAL binary built with GEOS: TRUE
## Loaded PROJ.4 runtime: Rel. 4.9.2, 08 September 2015, [PJ_VERSION: 492]
## Path to PROJ.4 shared files: (autodetected)
## Linking to sp version: 1.3-1library(sf)## Linking to GEOS 3.5.1, GDAL 2.1.3, PROJ 4.9.2library(sp)library(cartography)library(rgdal)
### getting vector datadownload.file("http://data.biogeo.ucdavis.edu/data/diva/adm/TZA_adm.zip",
destfile = "./data/TZA_adm.zip" , mode='wb')unzip("./data/TZA_adm.zip", exdir = "./data")spcol <- readOGR(dsn = "./data/TZA_adm1.shp", verbose = FALSE)
class(spcol)## [1] "SpatialPolygonsDataFrame"
## attr(,"package")
## [1] "sp"spcol@data$COLOUR <- "#FFFFFF"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 0] <- "#006837"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 1] <- "#52BE80"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 2] <- "#28B463"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 3] <- "#D4EFDF"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 4] <- "#138D75"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 5] <- "#76D7C4"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 6] <- "#A3E4D7"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 7] <- "#D0ECE7"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 8] <- "#FAE5D3"
spcol@data$COLOUR[(as.numeric(as.character(spcol@data$ID_1)) %% 10) == 9] <- "#A9CCE3"
plot(spcol, col=spcol$COLOUR, main = "Tanzania's Departments")
library(sf)
sfcol <- st_read(dsn = "./data/TZA_adm1.shp", quiet = TRUE)
class(sfcol)## [1] "sf" "data.frame"sfcol$COLOUR <- spcol@data$COLOUR
plot(st_geometry(sfcol), col=sfcol$COLOUR, main = "Tanzania's Departments")
oldw <- getOption("warn")
options(warn = -1)
options(warn = oldw)library(cartography)data(nuts2006)plot(nuts0.spdf, border = NA, col = NA, bg = "#A6CAE0")
# Plot non european space
plot(world.spdf, col = "#E3DEBF", border=NA, add=TRUE)
# Plot a layer of countries borders
plot(nuts0.spdf, border = "grey20", lwd = 3, add = TRUE)
# Plot a layer of NUTS1
plot(nuts1.spdf, border = "grey30", lwd = 2, add = TRUE)
# Plot a layer of NUTS2
plot(nuts2.spdf, border = "grey40", lwd = 0.5, add = TRUE)
# Plot a layer of NUTS3
plot(nuts3.spdf, border = "grey20", lwd = 0.1, add = TRUE)
# Layout plot
layoutLayer(title = "Most Populated Countries in Europe", # title of the map
author = "Author:Miriam Kasebele", #
sources = "Sources: Eurostat", #
scale = NULL, # no scale
col = NA, # no color for the title box
coltitle = "black", # color of the title
frame = TRUE,
bg = "#A6CAE0", # background of the map
extent = nuts0.spdf) # set the extent of the map
# Non European space
plot(world.spdf, col = "#AAB7B8", border = NA, add = TRUE)
# European (EU28) countries
plot(nuts0.spdf, col = "#F12BD0",border = "white", lwd = 1, add = TRUE)
# Selection of the 10 most populated countries of Europe
dflab <- nuts0.df[order(nuts0.df$pop2008, decreasing = TRUE),][1:10,]
# Label creation
dflab$lab <- paste(dflab$id, "\n", round(dflab$pop2008/1000000,0), "M", sep ="")
# Label plot of the 10 most populated countries
labelLayer(spdf = nuts0.spdf, # SpatialPolygonsDataFrame used to plot he labels
df = dflab, # data frame containing the lables
txt = "lab", # label field in df
col = "#690409", # color of the labels
cex = 0.6, # size of the labels
font = 2) # label font
# Add an explanation text
text(x = 5477360, y = 4177311, labels = "The 10 most populated countries of Europe
Total population 2008 [millions]", cex = 0.7, adj = 0)
# Compute the compound annual growth rate
nuts2.df$cagr <- (((nuts2.df$pop2008 / nuts2.df$pop1999)^(1/9)) - 1) * 100
# Set a custom color palette
cols <- carto.pal(pal1 = "green.pal", # first color gradient
n1 = 2, # number of colors in the first gradiant
pal2 = "red.pal", # second color gradient
n2 = 4) # number of colors in the second gradiant
# Plot a layer with the extent of the EU28 countries with only a background color
plot(nuts0.spdf, border = NA, col = NA, bg = "#A6CAE0")
# Plot non european space
plot(world.spdf, col = "#E3DEBF", border=NA, add=TRUE)
# Plot the compound annual growth rate
choroLayer(spdf = nuts2.spdf, # SpatialPolygonsDataFrame of the regions
df = nuts2.df, # data frame with compound annual growth rate
var = "cagr", # compound annual growth rate field in df
breaks = c(-2.43,-1,0,0.5,1,2,3.1), # list of breaks
col = cols, # colors
border = "grey40", # color of the polygons borders
lwd = 0.5, # width of the borders
legend.pos = "right", # position of the legend
legend.title.txt = "Compound Annual\nGrowth Rate", # title of the legend
legend.values.rnd = 2, # number of decimal in the legend values
add = TRUE) # add the layer to the current plot
# Plot a layer of countries borders
plot(nuts0.spdf,border = "grey20", lwd=0.75, add=TRUE)
# Layout plot
layoutLayer(title = "Demographic Trends", author = "cartography",
sources = "Eurostat, 2008", frame = TRUE, col = NA,
scale = NULL,coltitle = "black",
south = TRUE) # add a south arrow
##Interactive Mapping
library(ggplot2)
library(ggiraph)
library(rnaturalearth)
library(readr)
library(RCurl)## Loading required package: bitops###Loading required bitops
urlfile <- "https://raw.github.com/bhaskarvk/user2017.geodataviz/master/inst/extdata/africa-internet_usage-2015.csv"
internet_usage <- read.csv(urlfile)
head(internet_usage)## Country.Name Country.Code
## 1 Algeria DZA
## 2 Angola AGO
## 3 Bahrain BHR
## 4 Benin BEN
## 5 Botswana BWA
## 6 Burkina Faso BFA
## Series.Name Series.Code
## 1 Individuals using the Internet (% of population) IT.NET.USER.ZS
## 2 Individuals using the Internet (% of population) IT.NET.USER.ZS
## 3 Individuals using the Internet (% of population) IT.NET.USER.ZS
## 4 Individuals using the Internet (% of population) IT.NET.USER.ZS
## 5 Individuals using the Internet (% of population) IT.NET.USER.ZS
## 6 Individuals using the Internet (% of population) IT.NET.USER.ZS
## X2014..YR2014. X2015..YR2015. X2016..YR2016.
## 1 25.00000 38.200000 ..
## 2 10.20000 12.400000 ..
## 3 90.50313 93.478301 ..
## 4 6.00000 6.787703 ..
## 5 18.50000 27.500000 ..
## 6 9.40000 11.387646 ..names(internet_usage) <- c("Country Name", "Country Code", "Series Name", "Series Code",
"2014 [YR2014]", "2015 [YR2015]", "2015 [YR20156]")
names(internet_usage)## [1] "Country Name" "Country Code" "Series Name" "Series Code"
## [5] "2014 [YR2014]" "2015 [YR2015]" "2015 [YR20156]"world <- sf::st_as_sf(rnaturalearth::countries110)
##str(world)
length(unique(world$iso_a3))## [1] 175africa <- dplyr::filter(world, region_un=='Africa') %>%
dplyr::left_join(internet_usage %>% dplyr::select(
`Country Code`, `2015 [YR2015]`
) %>% dplyr::rename("iso_a3"=`Country Code`, internet.usage.2015=`2015 [YR2015]`),
by = 'iso_a3') %>%
st_transform(crs="+proj=laea +lon_0=18.984375")## Warning: Column `iso_a3` joining character vector and factor, coercing into
## character vectorhead(africa)## Simple feature collection with 6 features and 64 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -2664406 ymin: -2941948 xmax: 1306017 ymax: 1690992
## epsg (SRID): NA
## proj4string: +proj=laea +lat_0=0 +lon_0=18.984375 +x_0=0 +y_0=0 +ellps=WGS84 +units=m +no_defs
## scalerank featurecla labelrank sovereignt sov_a3
## 1 1 Admin-0 country 3 Angola AGO
## 2 1 Admin-0 country 6 Burundi BDI
## 3 1 Admin-0 country 5 Benin BEN
## 4 1 Admin-0 country 3 Burkina Faso BFA
## 5 1 Admin-0 country 4 Botswana BWA
## 6 1 Admin-0 country 4 Central African Republic CAF
## adm0_dif level type admin adm0_a3
## 1 0 2 Sovereign country Angola AGO
## 2 0 2 Sovereign country Burundi BDI
## 3 0 2 Sovereign country Benin BEN
## 4 0 2 Sovereign country Burkina Faso BFA
## 5 0 2 Sovereign country Botswana BWA
## 6 0 2 Sovereign country Central African Republic CAF
## geou_dif geounit gu_a3 su_dif subunit
## 1 0 Angola AGO 0 Angola
## 2 0 Burundi BDI 0 Burundi
## 3 0 Benin BEN 0 Benin
## 4 0 Burkina Faso BFA 0 Burkina Faso
## 5 0 Botswana BWA 0 Botswana
## 6 0 Central African Republic CAF 0 Central African Republic
## su_a3 brk_diff name name_long brk_a3
## 1 AGO 0 Angola Angola AGO
## 2 BDI 0 Burundi Burundi BDI
## 3 BEN 0 Benin Benin BEN
## 4 BFA 0 Burkina Faso Burkina Faso BFA
## 5 BWA 0 Botswana Botswana BWA
## 6 CAF 0 Central African Rep. Central African Republic CAF
## brk_name brk_group abbrev postal formal_en
## 1 Angola <NA> Ang. AO People's Republic of Angola
## 2 Burundi <NA> Bur. BI Republic of Burundi
## 3 Benin <NA> Benin BJ Republic of Benin
## 4 Burkina Faso <NA> B.F. BF Burkina Faso
## 5 Botswana <NA> Bwa. BW Republic of Botswana
## 6 Central African Rep. <NA> C.A.R. CF Central African Republic
## formal_fr note_adm0 note_brk name_sort name_alt mapcolor7
## 1 <NA> <NA> <NA> Angola <NA> 3
## 2 <NA> <NA> <NA> Burundi <NA> 2
## 3 <NA> <NA> <NA> Benin <NA> 1
## 4 <NA> <NA> <NA> Burkina Faso <NA> 2
## 5 <NA> <NA> <NA> Botswana <NA> 6
## 6 <NA> <NA> <NA> Central African Republic <NA> 5
## mapcolor8 mapcolor9 mapcolor13 pop_est gdp_md_est pop_year lastcensus
## 1 2 6 1 12799293 110300 NA 1970
## 2 2 5 8 8988091 3102 NA 2008
## 3 2 2 12 8791832 12830 NA 2002
## 4 1 5 11 15746232 17820 NA 2006
## 5 5 7 3 1990876 27060 NA 2011
## 6 6 6 9 4511488 3198 NA 2003
## gdp_year economy income_grp wikipedia
## 1 NA 7. Least developed region 3. Upper middle income NA
## 2 NA 7. Least developed region 5. Low income NA
## 3 NA 7. Least developed region 5. Low income NA
## 4 NA 7. Least developed region 5. Low income NA
## 5 NA 6. Developing region 3. Upper middle income NA
## 6 NA 7. Least developed region 5. Low income NA
## fips_10 iso_a2 iso_a3 iso_n3 un_a3 wb_a2 wb_a3 woe_id adm0_a3_is
## 1 <NA> AO AGO 024 024 AO AGO NA AGO
## 2 <NA> BI BDI 108 108 BI BDI NA BDI
## 3 <NA> BJ BEN 204 204 BJ BEN NA BEN
## 4 <NA> BF BFA 854 854 BF BFA NA BFA
## 5 <NA> BW BWA 072 072 BW BWA NA BWA
## 6 <NA> CF CAF 140 140 CF CAF NA CAF
## adm0_a3_us adm0_a3_un adm0_a3_wb continent region_un subregion
## 1 AGO NA NA Africa Africa Middle Africa
## 2 BDI NA NA Africa Africa Eastern Africa
## 3 BEN NA NA Africa Africa Western Africa
## 4 BFA NA NA Africa Africa Western Africa
## 5 BWA NA NA Africa Africa Southern Africa
## 6 CAF NA NA Africa Africa Middle Africa
## region_wb name_len long_len abbrev_len tiny homepart
## 1 Sub-Saharan Africa 6 6 4 NA 1
## 2 Sub-Saharan Africa 7 7 4 NA 1
## 3 Sub-Saharan Africa 5 5 5 NA 1
## 4 Sub-Saharan Africa 12 12 4 NA 1
## 5 Sub-Saharan Africa 8 8 4 NA 1
## 6 Sub-Saharan Africa 20 24 6 NA 1
## internet.usage.2015 geometry
## 1 12.400000 MULTIPOLYGON (((-294686.1 -...
## 2 4.866224 MULTIPOLYGON (((1148567 -49...
## 3 6.787703 MULTIPOLYGON (((-1799514 69...
## 4 11.387646 MULTIPOLYGON (((-2387715 10...
## 5 27.500000 MULTIPOLYGON (((712546.6 -2...
## 6 4.563264 MULTIPOLYGON (((-409783.7 8...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, unionx<-data.frame(a=letters[1:7])
y<-data.frame(a=letters[4:10])
class(x$a) ## [1] "factor"# [1] "factor"
# NOTE these are different
levels(x$a)## [1] "a" "b" "c" "d" "e" "f" "g"# [1] "a" "b" "c" "d" "e" "f" "g"
levels(y$a)## [1] "d" "e" "f" "g" "h" "i" "j"# [1] "d" "e" "f" "g" "h" "i" "j"m <- left_join(x,y)## Joining, by = "a"## Warning: Column `a` joining factors with different levels, coercing to
## character vector# Joining by: "a"
# Warning message:
# joining factors with different levels, coercing to character vector
class(m$a)## [1] "character"# [1] "character"africa.centers <- st_centroid(africa)## Warning in st_centroid.sf(africa): st_centroid assumes attributes are
## constant over geometries of xafrica.spdf <- methods::as(africa, 'Spatial')
africa.spdf@data$id <- row.names(africa.spdf@data)
africa.tidy <- broom::tidy(africa.spdf)## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector## Regions defined for each Polygonsoldw <- getOption("warn")
options(warn = -1)
options(warn = oldw)library(htmlwidgets)
library(hrbrthemes)africa.tidy <- dplyr::left_join(africa.tidy, africa.spdf@data, by='id')``
g <- ggplot(africa.tidy) +
geom_polygon_interactive(
color='black',
aes(long, lat, group=group, fill=internet.usage.2015,
tooltip=sprintf("%s<br/>%s",iso_a3,internet.usage.2015))) +
hrbrthemes::theme_ipsum() +
colormap::scale_fill_colormap(
colormap=colormap::colormaps$copper, reverse = T) +
labs(title='Internet Usage in Africa in 2015', subtitle='As Percent of Population',
caption='Source: World Bank Open Data.')