In_class exercise1
## retrieve the datasets
library(datasets)
library(lattice)
VADeaths
## Rural Male Rural Female Urban Male Urban Female
## 50-54 11.7 8.7 15.4 8.4
## 55-59 18.1 11.7 24.3 13.6
## 60-64 26.9 20.3 37.0 19.3
## 65-69 41.0 30.9 54.6 35.1
## 70-74 66.0 54.3 71.1 50.0
## examine the class of the datasets, which is a matrix
class(VADeaths)
## [1] "matrix"
## examine methods available for dotplot
methods("dotplot")
## [1] dotplot.array* dotplot.default* dotplot.formula* dotplot.matrix*
## [5] dotplot.numeric* dotplot.table*
## see '?methods' for accessing help and source code
## draw a dotplot without grouping
dotplot(VADeaths, groups=FALSE)
## draw a dotplot with one column, four rows layout.
## disable the grouping
## set the panel ratio with aspect argument.
## type argument set the point to be joined with the baseline
dotplot(VADeaths, groups=FALSE,
layout=c(1, 4),
aspect=0.7,
origin=0,
type=c("p", "h"),
main="Death Rates in Virginia - 1940", #title
xlab="Rate (per 1000)") ##title for x-axis
## a dotplot with grouping for all the population groups in one panel
## auto.key sets the labels on the right
dotplot(VADeaths, type="o",
auto.key=list(lines=TRUE, space="right"),
main="Death Rates in Virginia - 1940",
xlab="Rate (per 1000)")
## draw a barchart disabling grouping with a single column 4 rows layout.
barchart(VADeaths, groups=FALSE,
layout=c(1, 4),
aspect=0.7,
reference=FALSE,
main="Death Rates in Virginia - 1940",
xlab="Rate (per 100)")
## retrieve data"postdoc" from package"latticeExtra"
data(postdoc, package="latticeExtra")
##draw a barchart computed by pro.table() in a single panel
##auto.key display labels for each group.
##a barchart
barchart(prop.table(postdoc, margin=1),
xlab="Proportion",
auto.key=list(adj=1))
## draw a dotplot in a multiple panel
## enable abbreviation for the lable with
dotplot(prop.table(postdoc, margin=1),
groups=FALSE,
xlab="Proportion",
par.strip.text=list(abbreviate=TRUE, minlength=10))
## draw a dotplot that the order of the fields are changed by panel and prepanel.
dotplot(prop.table(postdoc, margin=1),
groups=FALSE,
index.cond=function(x, y) median(x),
xlab="Proportion",
layout=c(1, 5),
aspect=0.6,
scales=list(y=list(relation="free", rot=0)),
prepanel=function(x, y) {
list(ylim=levels(reorder(y, x)))
},
panel=function(x, y, ...) {
panel.dotplot(x, reorder(y, x), ...)
})
## retrieve the data
data(Chem97, package="mlmRev")
## build a two-way table of gcsescore and gender from Chem97
gcsescore.tab <- xtabs(~ gcsescore + gender, Chem97)
## convert it into a data frame
gcsescore.df <- as.data.frame(gcsescore.tab)
## return "gcsescore" to numeric value.
gcsescore.df$gcsescore <- as.numeric(as.character(gcsescore.df$gcsescore))
## draw a xyplot by fregency against gcsescore under the condition of gender
xyplot(Freq ~ gcsescore | gender,
data = gcsescore.df,
type="h",
layout=c(1, 2),
xlab="Average GCSE Score")
## build a two-way table of score and gender from Chem97
score.tab <- xtabs(~score + gender, Chem97)
## convert it into a data frame
score.df <- as.data.frame(score.tab)
##draw a bar chart displaying the frequency distribution of final score by gender.
barchart(Freq ~ score | gender, score.df, origin=0)
