Difference between revisions of "Help:Drawing graphs"

library(OpasnetUtils)
library(ggplot2)
library(xtable)

objects.get("QWYxSEJltnuTn0Xh") # data.time object from 
# http://fi.opasnet.org/fi_wiki/index.php?title=Talvivaaran_kaivoksen_mittauksia&oldid=16176
# data.time
altiste <- "Ni"

head(data.time)

ggplot(data.time, aes(x = Paikka, y = pitoisuusResult, colour = pitoisuusResult)) + 
	geom_point(size = 5) + # point size
	theme_grey(base_size = 24) + # font etc. http://sape.inf.usi.ch/quick-reference/ggplot2/themes
	labs( # label names
		title 	= paste(altiste, "Talvivaaran läheisyydessä"), 
		y 	= paste("Pitoisuus,", data.time$pitoisuusUnit[1]),
		x 	= "Mittauspaikka"
	) +
	theme(axis.text.x = element_text(angle = 90, hjust = 1)) # Turn text and adjust to right

########### Concentrations in time

ggplot(data.time, aes(x = Aika, y = pitoisuusResult, colour = Paikka)) + 
	geom_point(size = 5) + 
	theme_grey(base_size = 24) +
	labs(
		title 	= paste(altiste, "Talvivaaran läheisyydessä"), 
		y 	= paste("Pitoisuus,", data.time$pitoisuusUnit[1]),
		x 	= "Aika"
	) 

# data from http://fi.opasnet.org/fi_wiki/index.php?title=Kivilajien_kemiallinen_koostumus&oldid=16183
objects.get("yRxoBZmZBL5GOP6D")

head(data)
nrow(data)
ggplot(data[data$Observation == "Mean", ], aes(x = Element, y = Result, colour = Sequence)) + 
	geom_point() + 
	theme_grey(base_size = 20)

library(ggplot2)

dat <- data.frame(
	Group = factor(1:5, levels = 1:5, 
		labels = c("Old, GR", "Old, CH", "Old, CZ", "New, all locations", "Renovated, all locations"), ordered = TRUE),
	Mean = c(1.29, 0.83, 0.7, 0.65, 0.6),
	Sd = c(1.09, 0.46, 0.43, 0.1, 0.1)
)

out <- data.frame()
for(i in 1:nrow(dat)) {
	temp <- data.frame(Group = dat$Group[i], Iter = 1:10000, 
 Result = rlnorm(10000, 
meanlog = log(dat$Mean[i]^2 / sqrt(dat$Sd[i]^2 + dat$Mean[i]^2)),
sdlog = sqrt(log(1 + dat$Sd[i]^2 / dat$Mean[i]^2))
))
	out <- rbind(out, temp)
}
head(out)

tapply(out$Result, out$Group, mean)
tapply(out$Result, out$Group, sd)


p <- ggplot(out, aes(x = Result, linetype = Group)) + 
stat_ecdf(size = 1.2) + 
coord_cartesian(xlim = c(0, 3))  + 
theme_grey(base_size = basesize) + 
labs(x = "Air exchange rate (1/h)", y = "Cumulative probability") + 
theme(legend.position=c(.7, .2)) + 
theme(legend.title=element_blank()) +
guides(fill = guide_legend(keywidth = 3, keyheight = 1))

# png(filename = "//cesium/jtue$/_Documents/Alexairexchange.png", width = 800, height = 800)
print(p)
# dev.off()

library(OpasnetUtils)
library(ggplot2)
library(RColorBrewer) # Makes color palettes http://www.cookbook-r.com/Graphs/Colors_%28ggplot2%29/
# http://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palette

a <- data.frame(
	X = c("A", "B", "C", "D"),
	Y = c(1, 3, 2, 4),
	FILL = c("Up", "Middle", "Down", "Up")
)

ggplot(a, aes(x = reorder(X, Y, sum), weight = Y, fill = FILL)) + # X is reordered to decreasing order of Y.
	geom_bar() + coord_flip() + # Flip x and y axes
	theme_gray(base_size = 24) + # increase font
	labs( # Define labels
		title = "Environmental burden of disease in Finland", 
		x = "",
		y = "Impact (DALY/year)"
	) + 
	scale_fill_manual(values = brewer.pal(4, "Set2")) + # Use palette Set2 to define colours. 
	# Always use 4 colours, as the palette depends on the amount of colours used.
	theme(legend.position = c(0.8, 0.2)) # Adjust the legend position.

library(OpasnetUtilsExt)
library(googleVis) # needed only for the example data, otherwise is included automagically


# Check all the examples at
# http://code.google.com/p/google-motion-charts-with-r/wiki/GadgetExamples

# Opasnet wrapper for gvis-functions, plain and simple as that
google.gvis('Motion Chart', Fruits, idvar="Fruit", timevar="Year", options=list(height=350, width=400))


google.gvis('Geo Map', Exports, locationvar="Country", numvar="Profit",options=list(dataMode='regions',height=480,width=640))