gDat <- read.delim("gapminderDataFiveYear.txt")
# change plotting symbol to circle (store original settings in opar)
opar <- par(pch = 19)
# some code that might be needed to make settings work in knitr ```{r
# include = FALSE} knit_hooks$set(setPch = function(before, options, envir)
# { if(before) par(pch = 19) }) opts_chunk$set(setPch = TRUE) ```
# keep 8 random countries and sort by gdp
nC <- 8
set.seed(8)
countriesToKeep <- as.character(sample(levels(gDat$country), size = nC))
jDat <- droplevels(subset(gDat, country %in% countriesToKeep & year == 2007))
jDat <- jDat[order(jDat$gdpPercap), ]
jXlim <- c(min(jDat$gdpPercap), max(jDat$gdpPercap))
jYlim <- c(min(jDat$lifeExp), max(jDat$lifeExp))
head(colors())## [1] "white" "aliceblue" "antiquewhite" "antiquewhite1"
## [5] "antiquewhite2" "antiquewhite3"
jColors <- c("chartreuse3", "#0087FF", "darkgoldenrod1", "peachpuff3", "mediumorchid2",
"turquoise3", "wheat4", "slategray2")
plot(lifeExp ~ gdpPercap, jDat, log = "x", xlim = jXlim, ylim = jYlim, main = "Start your engines ...",
col = jColors)
# can specify colour with integer (indexing into the current palette, which
# can be seen with 'palette()')
plot(lifeExp ~ gdpPercap, jDat, log = "x", xlim = jXlim, ylim = jYlim, col = 1:nC,
main = "the default palette()")
# add names of default palette
with(jDat, text(x = gdpPercap, y = lifeExp, labels = paste(1:nC, palette()),
pos = c(4, rep(1, 7))))
# using predefined color schemes - Brewer
library(RColorBrewer)
display.brewer.all()
display.brewer.pal(n = 8, name = "Dark2")
jBrewColors <- brewer.pal(n = 8, name = "Dark2")
plot(lifeExp ~ gdpPercap, jDat, log = "x", xlim = jXlim, ylim = jYlim, col = jBrewColors,
main = "Dark2 qualitative palette from RColorBrewer")
with(jDat, text(x = gdpPercap, y = lifeExp, labels = jBrewColors, pos = c(4,
rep(1, 7))))
# more builtin colour function: rgb(), col2rgb(), convertColor(),
# colorspace()
# create continent colours using match() create a data frame with a colour
# for each continent
(jColors <- with(jDat, data.frame(continent = levels(continent), color = I(brewer.pal(nlevels(continent),
name = "Dark2")))))## continent color
## 1 Americas #1B9E77
## 2 Asia #D95F02
## 3 Europe #7570B3
data.frame(subset(jDat, select = c(country, continent)), matchRetVal = match(jDat$continent,
jColors$continent))## country continent matchRetVal
## 480 El Salvador Americas 1
## 360 Costa Rica Americas 1
## 1344 Serbia Europe 3
## 1188 Panama Americas 1
## 1512 Taiwan Asia 2
## 540 France Europe 3
## 804 Japan Asia 2
## 1092 Netherlands Europe 3
plot(lifeExp ~ gdpPercap, jDat, log = "x", xlim = jXlim, ylim = jYlim, col = jColors$color[match(jDat$continent,
jColors$continent)], main = "custom color scheme based on Dark2", cex = 2)
legend(x = "bottomright", legend = as.character(jColors$continent), col = jColors$color,
pch = par("pch"), bty = "n", xjust = 1)
# create continent colours using merge()
(jDatColor <- merge(jDat, jColors))
## continent country year pop lifeExp gdpPercap color
## 1 Americas El Salvador 2007 6939688 71.88 5728 #1B9E77
## 2 Americas Costa Rica 2007 4133884 78.78 9645 #1B9E77
## 3 Americas Panama 2007 3242173 75.54 9809 #1B9E77
## 4 Asia Taiwan 2007 23174294 78.40 28718 #D95F02
## 5 Asia Japan 2007 127467972 82.60 31656 #D95F02
## 6 Europe Serbia 2007 10150265 74.00 9787 #7570B3
## 7 Europe France 2007 61083916 80.66 30470 #7570B3
## 8 Europe Netherlands 2007 16570613 79.76 36798 #7570B3
plot(lifeExp ~ gdpPercap, jDatColor, log = "x", xlim = jXlim, ylim = jYlim,
col = color, main = "custom color scheme based on Dark2", cex = 2)
legend(x = "bottomright", legend = as.character(jColors$continent), col = jColors$color,
pch = par("pch"), bty = "n", xjust = 1)
# reset the settings
par(opar)
# LATTICE
library(lattice)
# drop oceania
jDat <- droplevels(subset(gDat, continent != "Oceania"))
# inspect lattice settings
show.settings()
str(trellis.par.get(), max.level = 1)
## List of 35
## $ grid.pars : list()
## $ fontsize :List of 2
## $ background :List of 2
## $ panel.background :List of 1
## $ clip :List of 2
## $ add.line :List of 4
## $ add.text :List of 5
## $ plot.polygon :List of 5
## $ box.dot :List of 5
## $ box.rectangle :List of 5
## $ box.umbrella :List of 4
## $ dot.line :List of 4
## $ dot.symbol :List of 5
## $ plot.line :List of 4
## $ plot.symbol :List of 6
## $ reference.line :List of 4
## $ strip.background :List of 2
## $ strip.shingle :List of 2
## $ strip.border :List of 4
## $ superpose.line :List of 4
## $ superpose.symbol :List of 6
## $ superpose.polygon:List of 5
## $ regions :List of 2
## $ shade.colors :List of 2
## $ axis.line :List of 4
## $ axis.text :List of 5
## $ axis.components :List of 4
## $ layout.heights :List of 19
## $ layout.widths :List of 15
## $ box.3d :List of 4
## $ par.xlab.text :List of 5
## $ par.ylab.text :List of 5
## $ par.zlab.text :List of 5
## $ par.main.text :List of 5
## $ par.sub.text :List of 5
str(trellis.par.get("superpose.symbol"))## List of 6
## $ alpha: num [1:7] 1 1 1 1 1 1 1
## $ cex : num [1:7] 0.8 0.8 0.8 0.8 0.8 0.8 0.8
## $ col : chr [1:7] "#0080ff" "#ff00ff" "darkgreen" "#ff0000" ...
## $ fill : chr [1:7] "#CCFFFF" "#FFCCFF" "#CCFFCC" "#FFE5CC" ...
## $ font : num [1:7] 1 1 1 1 1 1 1
## $ pch : num [1:7] 1 1 1 1 1 1 1
# change plot points symbol, size, colour
xyplot(lifeExp ~ gdpPercap | continent, jDat, group = country, subset = year ==
2007, scales = list(x = list(log = 10, equispaced.log = FALSE)), par.settings = list(superpose.symbol = list(pch = 19,
cex = 1.5, col = c("orange", "blue"))))
# use predefined set of colours
countryColors <- read.delim(file = "gapminderCountryColors.txt", as.is = 3)
str(countryColors)
## 'data.frame': 142 obs. of 3 variables:
## $ continent: Factor w/ 5 levels "Africa","Americas",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ country : Factor w/ 142 levels "Afghanistan",..: 95 39 43 28 118 121 127 69 86 3 ...
## $ color : chr "#7F3B08" "#833D07" "#873F07" "#8B4107" ...
countryColors <- countryColors[match(levels(jDat$country), countryColors$country),
]
str(countryColors)## 'data.frame': 140 obs. of 3 variables:
## $ continent: Factor w/ 5 levels "Africa","Americas",..: 3 4 1 1 2 4 3 3 4 1 ...
## $ country : Factor w/ 142 levels "Afghanistan",..: 1 2 3 4 5 7 8 9 10 11 ...
## $ color : chr "#874D96" "#D2ECB1" "#A34F06" "#C96C0C" ...
xyplot(lifeExp ~ gdpPercap | continent, jDat, group = country, subset = year ==
2007, scales = list(x = list(log = 10, equispaced.log = FALSE)), par.settings = list(superpose.symbol = list(pch = 19,
cex = 1, col = countryColors$color)))
# storing graphical parameters for reuse
(continentColors <- read.delim(file = "gapminderContinentColors.txt", as.is = 3))
## continent nCountries color
## 1 Africa 52 #7F3B08
## 2 Americas 25 #A50026
## 3 Asia 33 #40004B
## 4 Europe 30 #276419
## 5 Oceania 2 #313695
(continentColors <- continentColors[match(levels(jDat$continent), continentColors$continent),
])## continent nCountries color
## 1 Africa 52 #7F3B08
## 2 Americas 25 #A50026
## 3 Asia 33 #40004B
## 4 Europe 30 #276419
coolNewPars <- list(superpose.symbol = list(pch = 21, cex = 2, col = "gray20",
fill = continentColors$color))
xyplot(lifeExp ~ gdpPercap, jDat, subset = year == 2007, scales = list(x = list(log = 10,
equispaced.log = FALSE)), group = continent, auto.key = list(columns = 4),
par.settings = coolNewPars)
# change the actual lattice theme (and restore later)
otp <- trellis.par.get() # store the original theme
trellis.par.set(superpose.symbol = list(pch = 19, cex = 1, col = countryColors$color))
xyplot(lifeExp ~ gdpPercap | continent, jDat, group = country, subset = year ==
2007, scales = list(x = list(log = 10, equispaced.log = FALSE)))
trellis.par.set(otp)
# GGPLOT2
library(ggplot2)
jDat <- droplevels(subset(gDat, continent != "Oceania"))
jYear <- 2007
q <- ggplot(subset(jDat, year == jYear), aes(x = gdpPercap, y = lifeExp)) +
scale_x_log10()
q + geom_point(pch = 21, size = 8, fill = "darkorchid1")
q + geom_point(aes(size = sqrt(pop/pi)), pch = 21)
(r <- q + geom_point(aes(size = sqrt(pop/pi)), pch = 21, show_guide = FALSE) +
scale_size_continuous(range = c(1, 40)))
(r <- r + facet_wrap(~continent))
r + aes(fill = continent)
countryColors <- read.delim(file = "gapminderCountryColors.txt", as.is = 3)
jColors <- countryColors$color
names(jColors) <- countryColors$country
r + aes(fill = country) + scale_fill_manual(values = jColors)
# again, but unhide small countries by reordering rows based on population
jDat <- jDat[with(jDat, order(year, -1 * pop)), ]
ggplot(subset(jDat, year == jYear), aes(x = gdpPercap, y = lifeExp)) + scale_x_log10() +
geom_point(aes(size = sqrt(pop/pi)), pch = 21, show_guide = FALSE) + scale_size_continuous(range = c(1,
40)) + facet_wrap(~continent) + aes(fill = country) + scale_fill_manual(values = jColors)
