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Timothée Giraud, Nicolas Lambert

2018-06-25

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The rgdal Way

The sf Way

Europe Dataset

# Layout plot
layoutLayer(title = "Most Populated Countries of Europe", # title of the map
 author = "", # no author text
 sources = "", # no source text
 Newest Clutch Charcoal Mascara Buy Newest Buy scale = NULL, # no scale
 col = NA, # no color for the title box 
 coltitle = "black", # color of the title
 frame = FALSE, # no frame around the map
 bg = "#A6CAE0", # background of the map
 extent = nuts0.spdf) # set the extent of the map

# Non European space
plot(world.spdf, col = "#E3DEBF", border = NA, add = TRUE)
# European (EU28) countries
plot(nuts0.spdf, col = "#D1914D",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$id, Newest Clutch Buy Newest Mascara Charcoal Buy "\n", round(dflab$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
 Charcoal Buy Mascara Buy Newest Newest Clutch cex = 0.9, # 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, in millions of inhabitants.", cex = 0.7, adj = 0)

# Compute the compound annual growth rate
nuts2.df$cagr <-Clutch Buy Buy Newest Mascara Newest Charcoal (((nuts2.df$pop2008 / nuts2.df$pop1999)^(1/9)) - 1) *Clutch Mascara Charcoal Buy Newest Newest Buy 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")Black nbsp;leather Lining ons Mac Slip Whyred qAFtwX
# Plot non european space
plot(world.spdf, col = "#E3DEBF", border=NA, add=TRUE)

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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, Charcoal Clutch Buy Newest Buy Newest Mascara # width of the borders
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 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

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plot(nuts0.spdf,border = "grey20", lwd=0.75, add=TRUE)
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# 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

Material & care

Outer material: Polyester

Lining: Polyester

Details

Fastening: Magnet

Article number: M0951H021-C11

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## Plot OpenStreetMap tiles as basemap 
# Download the tiles, nuts0.spdf extent
EUosm <- getTiles(spdf = nuts0.spdf, type = "osm", zoom = 4)
## Warning: spdf is deprecated; use x instead.
# Plot the tiles
tilesLayer(EUosm)

# Plot countries
plot(nuts0.spdf, border = "grey65", lwd = 2, add=TRUE)

# Plot countries population 
nuts0.df$pop <- nuts0.df$pop2008 / 1000
propSymbolsLayer(spdf = nuts0.spdf, # SpatialPolygonsDataFrame of the countries
 df = nuts0.df, # data frame of the regions
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 symbols = "circle", # type of symbol
 border = "white", # color of the symbols borders
 lwd = Mascara Buy Clutch Newest Buy Charcoal Newest 1.5, # width of the symbols borders
 legend.pos = "topleft",
 legend.title.txt = "Total population\n(in thousands)")
# # Layout plot
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 sources = "Data: Eurostat, 2008",
 author = "Base map: Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under CC BY SA.",
 scale = NULL, frame = TRUE,
 col = "#688994") # color of the frame

# Create a link layer from the twincities data frame
head(twincities.df)
## i j fij
## 1 DE14 AT11 1
## 2 DE21 AT11 1
## 3 DE23 AT11 1
## 4 DE26 AT11 2
## 5 DE91 AT11 1
## 6 DEB3 AT11 1
# twincities contains links between Nuts 2 regions
# ?twincities.df
twincities.spdf <- getLinkLayer(x = nuts2.spdf, # SpatialPolygonsDataFrame of Nuts2
 df = twincities.df) # links data frame

# 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 Nuts2 regions
plot(nuts2.spdf, col = "#D1914D",border = "grey80", add=TRUE)

# # Plot links with graduated sizes
gradLinkLayer(x = twincities.spdf, # SpatialLinesdataFrame of the links
 df = twincities.df, # data frame of the links
 var = "fij", # name of the variable used to plot the links widths
 breaks = c(2,5,15,20,30), # list of breaks
 lwd = c(0.1,Buy Buy Newest Newest Clutch Charcoal Mascara 1,4,10), # list of widths
 Clutch Charcoal Buy Newest Mascara Buy Newest col = "#92000090", # color of the links
 legend.pos = "right", legend.frame = TRUE,
 legend.title.txt = "Number of Aggreements\n(regional level)",
 add = TRUE)

# Plot the layout
layoutLayer(title = Newest Mascara Newest Clutch Buy Charcoal Buy "International Twinning Agreements Between Cities", 
 author = "cartography", sources = "Sources: Adam Ploszaj & Wikipedia, 2011",
 scale = NULL, south = TRUE, frame = TRUE, col = NA, 
 coltitle = "black")

# Compute the compound annual growth rate
nuts2.df$cagr <- (((nuts2.df$pop2008 / nuts2.df$pop1999)^(1/9)) - 1) * 100
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# 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 Nuts2 regions
plot(nuts2.spdf, col = "grey60",border =Jack nbsp;wool Lining up Navy Boots Lace Panama fXYzqndf "white", lwd = 0.4, add = TRUE)

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cols <- carto.pal(pal1 = "blue.pal", n1 = 2, pal2 = "red.pal", n2 = 4)

# Plot symbols with choropleth coloration
propSymbolsChoroLayer(spdf = nuts2.spdf, 
 df = nuts2.df, 
 var = "pop2008", # field in df to plot the symbols sizes
 inches = 0.1, # set the symbols sizes
 var2 = "cagr", # field in df to plot the colors
 col = cols, # symbols colors
 breaks = c(-2.43,-1,Charcoal Buy Clutch Newest Mascara Newest Buy 0,0.5,1,2,3.1), # breaks
 border = "grey50", # border colors of the symbols
 lwd = 0.75, # symbols width
 legend.var.pos = "topright", # size legend position
 legend.var.values.rnd = -3, # size legend value roundinf
 legend.var.title.txt = "Total Population", # size legend titleBoots nbsp;polyester Gabor Ankle Schwarz Lining aw6qI65
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 legend.var2.pos = "right", # color legend position
 legend.var2.title.txt = "Compound Annual\nGrowth Rate") # legend title

# layout
layoutLayer(title = "Demographic trends, 1999-2008", coltitle = "black",
 sources = "Eurostat, 2011", scale = NULL,
 author = "cartography", frame ="", col = NA)

# Get a SpatialLinesDataFrame of countries borders
nuts0.contig <- getBorders(spdf = nuts0.spdf)
## Warning: spdf and spdfid are deprecated; use x and id instead.
class(nuts0.contig)
## [1] "sf" "data.frame"

# Get the GDP per capita
nuts0.df$gdpcap <- nuts0.df$gdppps2008/nuts0.df$pop2008*1000000

# 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 =Heeled nbsp;textile Mjus Lining Nero Boots High CxqrUxXBw5 "#E3DEBF", border=NA, add=TRUE)

# Plot GDP per capita with a choropleth layer
choroLayer(spdf = nuts0.spdf, df = nuts0.df, var = "gdpcap", border = "grey80",
 col = carto.pal(pal1 = "kaki.pal", n1 = 6), method = "quantile",
 nclass = 6, add=TRUE, legend.pos = "right", 
 legend.values.rnd = -2,
 legend.title.txt = "GDP per Capita\n(in euros)")Trainers Of Huge Range Dutti Blue Massimo pZapcg4qw

# Plot discontinuities
discLayer(x = nuts0.contig, # sf of borders
 df = nuts0.df, # data frame on countries
 var = "gdpcap", # variable used to compute discontinuties 
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 method="equal", # discretisation of discontinuities
 nclass=4, # number of discontinuities classes
 threshold = 0.5, Newest Newest Buy Charcoal Mascara Clutch Buy # representation threshold of discontinuities
 sizemin = 0.5, # minimum size of discontinuities lines
 sizemax = 6, # maximum size of discontinuities lines
 col="red", # color of the lines
 legend.values.rnd = 1,
 legend.title.txt = Clutch Newest Buy Mascara Newest Charcoal Buy "Discontinuities in\nGDP per Capita\n(relative)",
 legend.pos = "topright", 
 add=TRUE)

# Layout
layoutLayer(title = "Wealth Disparities in Europe", coltitle = "black",
 sources = "Eurostat, 2011", scale = NULL,
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# Create a grid layer
nuts2.spdf@data <- nuts2.df
mygrid <- getGridLayer(x = nuts2.spdf, # SpatialPolygonsDataFrame
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 var = "pop2008") # variable to adapt to the grid
 

# Plot dentsity of population
## conversion from square meter to square kilometers
mygrid$densitykm <- mygrid$pop2008 * 1000 * 1000 / mygrid$gridarea

# 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)

# Set a custom color paletteTrainers Antony Nero price Morato Amazing HtxCqwx
cols <- carto.pal(pal1 = "wine.pal", n1 = 6)

# Plot the gridded population density
choroLayer(x = mygrid, var = "densitykm", 
 border = "grey80", col = cols, legend.pos = "topright",
 method = "q6", add = TRUE, legend.values.rnd = 1,
 legend.title.txt = "Population Density\n(inhabitant/km²)")

# Layout
layoutLayer(title = "Population Density", coltitle = "black",
 sources = "Eurostat, 2011", scale = NULL, 
 author = "cartography", Buy Newest Buy Newest Mascara Clutch Charcoal frame ="", col = NA)