Kody z rozdziału 5. Graficzna prezentacja danych ,,Przewodnika po programie R’’ wydanie 4.

Aby zainstalować i włączyć pakiet Przewodnik wykonaj poniższe dwie liniki.

devtools::install_github("pbiecek/PrzewodnikPakiet")
library("Przewodnik")

5.1. Znajdź siedem różnic

library("PBImisc")
plot(MDRD12~MDRD7, data = kidney) 

library("lattice")
xyplot(MDRD12~MDRD7, data = kidney) 

library("ggplot2")
qplot(MDRD7, MDRD12, data = kidney)

5.3. Pakiet lattice

library("PBImisc")
library("lattice")
xyplot(MDRD12 ~ MDRD7 | discrepancy.DR, data = kidney)

xyplot(MDRD12 ~ MDRD7 | discrepancy.DR, data = kidney, type=c("p","smooth","r"), col="grey", pch=16, ylab="MDRD 30d", xlab="MDRD 7d")

5.3.4. Panele i mechanizm warunkowania

histogram(~MDRD12 | therapy, data = kidney)

histogram(~MDRD12 | equal.count(donor.age,4), data = kidney)

5.3.5. Mechanizm grupowani

densityplot(~MDRD12, group = therapy, data = kidney,
plot.points = FALSE)

5.3.6. Legenda wykresu

densityplot(~MDRD12, group=therapy, auto.key = TRUE, data = kidney)

densityplot(~MDRD12, group=therapy, data = kidney, auto.key = list(space = "right", columns = 1))

5.3.7. Atlas funkcji graficznych z pakietu lattice

xyplot(MDRD12 + MDRD36 ~ MDRD7 | discrepancy.DR==0, data=kidney, type=c("p","smooth","g"), cex=0.5, auto.key = TRUE)

splom(kidney[,c(9,11,13,15)], type=c("smooth","p"), pch='.')

stripplot(factor(discrepancy.AB)~MDRD7, data = kidney, jitter.data = TRUE, alpha = 0.5)

discrepancy <- equal.count(kidney$discrepancy.AB, number=3)
bwplot(therapy~MDRD12|discrepancy, data=kidney, varwidth = TRUE)

library("Przewodnik")
(wPlec <- table(daneSoc$wyksztalcenie, daneSoc$plec))
##             
##              kobieta mezczyzna
##   podstawowe      22        71
##   srednie         16        39
##   wyzsze          10        24
##   zawodowe         7        15
dotplot(wPlec, groups=FALSE, origin=0, type = c("p","h"))

dotplot(wPlec, type="o", auto.key = list(space="right"))

attach(daneSoc)
tabela <- as.data.frame(table(wyksztalcenie, plec, praca ))
barchart(wyksztalcenie~Freq|plec, groups=praca, auto.key=TRUE, data=tabela)

parallel(~kidney[,c(9:16)], groups=MDRD7<30, data=kidney, alpha=0.2, horizontal.axis = FALSE, scales = list(x = list(rot = 90)))

histogram(~MDRD7 | therapy, data = kidney)

densityplot(~MDRD7 | factor(diabetes), groups=therapy, data=kidney, bw = 8, plot.points="rug", auto.key = TRUE)

library("latticeExtra")
ecdfplot(~MDRD7 | factor(diabetes), groups=therapy, data=kidney, auto.key=list(space="right"))

qq(diabetes ~ MDRD7 | therapy, distribution=qnorm, data=kidney)