data.frame

require(ztable)
options(ztable.type="html")
options(ztable.zebra=1)
options(ztable.zebra.color="platinum")
options(ztable.colnames.bold=TRUE)
ztable(head(mtcars))

ztable(head(mtcars),zebra=NULL,size=3,
       caption="Table 1. Non-zebra Table with small size")

ztable(head(mtcars[c(1:7)]),zebra=2,zebra.color="lightcyan",size=7,
       caption="Table 2. Left-sided caption at botom with large font",
       caption.placement="bottom",caption.position="l") 

aov object

‘ztable()’ can be used for ‘aov’ object. When used for ‘aov’ object, the function call is added as footer to the table. The parameter ‘show.footer’ can be used whether or not include footer in the table. Dafault value is TRUE.

out <- aov(mpg ~ ., data=mtcars)
ztable(out)

Linear model : ‘lm’ object

‘ztable()’ can be used for ‘lm’ object. When used for ‘lm’ object, the function call is added as footer to the table, too.

fit <- lm(mpg ~ cyl + disp + wt + drat + am, data=mtcars)
ztable(fit)

Analysis of Variance Table : ‘anova’ object

‘ztable()’ can be used for ‘anova’ object to show the anova table. When used for ‘anova’ object, headings of anova are added as headings to the table. The parameter ‘show.footer’ can be used whether or not include footer in the table. Dafault value is TRUE.

a=anova(fit)
str(a)

Classes ‘anova’ and ‘data.frame’: 6 obs. of 5 variables: $ Df : int 1 1 1 1 1 26 $ Sum Sq : num 8.18e+02 3.76e+01 8.22e+01 4.29e-04 9.26e-02 … $ Mean Sq: num 8.18e+02 3.76e+01 8.22e+01 4.29e-04 9.26e-02 … $ F value: num 1.13e+02 5.19 1.14e+01 5.93e-05 1.28e-02 … $ Pr(>F) : num 5.94e-11 3.12e-02 2.36e-03 9.94e-01 9.11e-01 … - attr(*, “heading”)= chr “Analysis of Variance Table” “Response: mpg”

ztable(a)

This is examples of another ‘anova’ object. The models in this anova tables showed as table headings. You can decide whether or not include the headings in the tableby using parameter ‘show.heading’(default: TRUE).

fit2 <- lm(mpg ~ cyl+wt, data=mtcars)
b=anova(fit2,fit)
str(b)

Classes ‘anova’ and ‘data.frame’: 2 obs. of 6 variables: $ Res.Df : num 29 26 $ RSS : num 191 188 $ Df : num NA 3 $ Sum of Sq: num NA 2.77 $ F : num NA 0.128 $ Pr(>F) : num NA 0.943 - attr(*, “heading”)= chr “Analysis of Variance Table” “Model 1: mpg ~ cyl + wt2: mpg ~ cyl + disp + wt + drat + am”

ztable(b)

ztable(b,show.heading=FALSE)

Generalized linear model ; ‘glm’ object

‘ztable()’ can be used for ‘glm’(generalized linear model) object. In this time, ‘ztable()’ shows the odds ratio(OR) and 95% confidence interval as well as atandard R output.

require(survival)

## Loading required package: survival
## Loading required package: splines

data(colon)
attach(colon)
out <- glm(status ~ rx+obstruct+adhere+nodes+extent, data=colon, family=binomial)
ztable(out)

Again, ‘ztable()’ also shows the anova table of this model.

ztable(anova(out))

More ‘aov’ object

op <- options(contrasts = c("contr.helmert", "contr.poly"))
npk.aov <- aov(yield ~ block + N*P*K, npk) 
ztable(npk.aov,zebra=1)

More ‘lm’ object

ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
ztable(lm.D9)

ztable(anova(lm.D9),align="|c|rrrr|r|")

More ‘glm’ object

counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
d.AD <- data.frame(treatment, outcome, counts)
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
ztable(glm.D93)

Principal Components Analysis : ‘prcomp’ object

‘ztable()’ can be used in principal components analysis. Followings are examples of ztable() of ‘prcomp’ object.

data(USArrests)
pr1 <- prcomp(USArrests) 
ztable(pr1)

ztable(summary(pr1))

Survival Analysis : ‘coxph’ object

‘ztable()’ can be used in principal components analysis. When used for Cox proportional hazard model, ‘ztable()’ showed the hazard ratio and 95% confidence interval ready for publication to medical journal.

colon$TS = Surv(time,status==1) 
out=coxph(TS~rx+obstruct+adhere+differ+extent+surg+node4,data=colon)
ztable(out)

Customize the zebra striping colors

If you wanted to use several colors for zebra striping, you can set the parameter ‘zebra’ to zero(e.g. zebra=0) and set the ‘zebra.color’ parameter with vector of your favorite colors. Your favorite colors are used to zebra striping. For your convienience, ten colors are predifned for this purpose. The predefined colors are: c(“peach”,“peach-orange”,“peachpuff”,“peach-yellow”,“pear”,“pearl”,“peridot”,“periwinkle”,“pastelred”, “pastelgray”).

ztable(head(mtcars,15),zebra=0,zebra.color=NULL) 

The color names used for this purpose are predefined in the data ‘zcolors’ included in ‘ztable’ package. Please type ‘?zcolors’ in R console for help file or just type ‘zcolors’. You can see 749 color names defined in data ‘zcolors’.

Place two or more ztables or figures side by side

If you wanted to place two or more ztables or figures side by side, you can use function parallelTables(). Function parallelTables() takes three parameters. The first parameter width is a numeric vector specifies the width to which the tables or figures should be scaled. The second parameter is a list of ztable or names of valid figure. The 3rd parameter ‘type’ is the type of table to produce. Possible values for type are “latex” or “html”. Default value is “latex”. See the examples.

z=ztable(head(mtcars[1:3]),tabular=TRUE,zebra.color="peach-orange")
z1=ztable(head(iris[1:3]),tabular=TRUE,zebra=2)

parallelTables(width=c(0.5,0.5),list(z,z1),type="html")

parallelTables(width=c(0.5,0.5),list(z,"figures/ztable3.png"),type="html")

mpg cyl disp Mazda RX4 21.00 6.00 160.00 Mazda RX4 Wag 21.00 6.00 160.00 Datsun 710 22.80 4.00 108.00 Hornet 4 Drive 21.40 6.00 258.00 Hornet Sportabout 18.70 8.00 360.00 Valiant 18.10 6.00 225.00

Vertical striping

If you wanted to vertical striping table, you can get it by set the parameter zebra.type 2. You can change the ztables parameters when printing.

z1=ztable(head(iris),zebra=2)
z1

print(z1,zebra.type=2)

print(z1,zebra=1,zebra.type=2,zebra.colnames=TRUE)

More tailoring zebra striping

You can update parameters of ztable with ‘update_ztable’ function.

options(ztable.zebra.color=NULL)
(z1=ztable(head(iris),zebra=0,zebra.type=2))

You can change the background color of colnames rows by setting zebra.colnames=TRUE.

update_ztable(z1,colnames.bold=TRUE,zebra.colnames=TRUE)

You can customize the striping when printing.

print(z1,zebra.color=c(rep("white",5),"peach"),zebra.colnames=TRUE)

Change the background color of all cells

You can change the background color of all cells by setting the zebra.type=0.

ztable(head(iris),zebra=0,zebra.type=0)

ztable(head(iris),zebra=0,zebra.type=0,zebra.color=zcolors$name,zebra.colnames=TRUE)

Diagonal striping

You can make diagonal striping with use of zebra.color greater/lesser than column length by 1.

ztable(head(iris),zebra=0,zebra.type=0,zebra.color=1:7,zebra.colnames=TRUE)

ztable(head(mtcars[,1:9]),zebra=0,zebra.type=0,zebra.color=1:9,zebra.colnames=TRUE)

Two hundred background colors

This is demonstration of 200 background colors. All 749 colors are available in package ztable. Please type ?zcolors.

mycolor=rep("white",6)
for(i in 1:40){
    mycolor=c(mycolor,"white",zcolors$name[((i-1)*5+1):((i-1)*5+5)])
}
a=c(zcolors$name[1:5])
for(i in 2:40){
    a=rbind(a,zcolors$name[((i-1)*5+1):((i-1)*5+5)])
}
a=data.frame(a,stringsAsFactors=FALSE,row.names=NULL)
ztable(a,zebra=0,zebra.type=0,zebra.color=mycolor,include.rownames=FALSE,
       include.colnames=FALSE,longtable=TRUE)