In cardiomoon/moonBook2: Functions and Datasets for the 2nd Book by Keon-Woong Moon

Package installation

Package moonBook is available on CRAN and github. Package moonBook2 is available only on github. Please install moonBook2 package using the following R code.

install.packages("devtools")
devtools::install_github("cardiomoon/moonBook")
devtools::install_github("cardiomoon/moonBook2")

Because functions in "moonBook2" make interactive plots using package "ggplot2" and "ggiraph", I strongly recommend you to install the latest version of the package "ggplot2" and "ggiraph" from github using following R command.

devtools::install_github("hadley/ggplot2")
devtools::install_github("davidgohel/ggiraph")

In this vignette, I will show you how to use t

hese functions. 1. ggCor() make an interactive correlation plot 2. ggBoxplot() make an interactive boxplot of a data.frame 3. ggScatter() make an interactive scatterplot with linear regression

ggCor()

ggCor() function draws a heatmap showing the correlation coefficients of a data.frame.

require(ggplot2)
require(ggiraph)
require(moonBook2)
require(mycor)

ggCor(mtcars,interactive=TRUE)

You can zoom-in and zoom-out the plots with your mouse wheel. You can label the r values on the heatmap.

ggCor(mtcars,label=TRUE,interactive=TRUE)

You can change the colors of heatmap by using the color argument.

ggCor(mtcars,colors=c("red","white","blue"),interactive=TRUE)

ggBoxplot()

ggBoxplot() draws boxplots of all numeric variables in a data.frame. You can use this plot for navigate the outliers in a dataframe.

ggBoxplot(iris,interactive=TRUE)

You can make a horizontal boxplot by setting the horizontal argument TRUE.

ggBoxplot(mtcars,horizontal=TRUE,interactive=TRUE)

You can rescale the variables by setting the rescale argument TRUE.

ggBoxplot(mtcars,rescale=TRUE,horizontal=TRUE,interactive=TRUE)

You can change the theme.

p<-ggBoxplot(mtcars,horizontal=TRUE)+theme_bw()
ggiraph(code=print(p),zoom_max=10)

ggScatter()

ggScatter() draws interactive scatterplot with regression line. By default, loess regression line(s) are added to plot.

require(moonBook)
ggScatter(radial,xvar="height",yvar="weight",interactive=TRUE)

If you want to fit a linear regression model, set the method argument "lm". You can see the regression formula with hovering your mouse on the regression line.

ggScatter(radial,xvar="height",yvar="weight",method="lm",interactive=TRUE)

You can use colorvar to diffentiate groups.

ggScatter(radial,xvar="height",yvar="weight",colorvar="sex",method="lm",interactive=TRUE)

You can get faceted plots by setting the argument facet TRUE.

ggScatter(radial,xvar="height",yvar="weight",colorvar="sex",facet=TRUE,method="lm",interactive=TRUE)

You can use formula to obtain seperate regression lines.

ggScatter(NTAV~age|smoking,data=radial,fullrange=TRUE,method="lm",se=FALSE,interactive=TRUE)

You can make faceted plots using continuous variables. If you select a continuous variable as the "colorvar" and set the facet TRUE, You can get faceted plot.

ggScatter(acs,yvar="weight",xvar="height",colorvar="age",method="lm",facet=TRUE,interactive=TRUE)

You can use a continuous variable as the "colorvar" without faceting.

ggScatter(acs,yvar="weight",xvar="height",colorvar="age",method="lm",interactive=TRUE)

You can changed the number of facets by setting the cut_number parameter.

ggScatter(acs,yvar="weight",xvar="height",colorvar="age",cut_number=4,method="lm",facet=TRUE,interactive=TRUE)

cardiomoon/moonBook2 documentation built on May 13, 2019, 12:40 p.m.