ggradar2: deploy a radar to your data

ggradar2 is now available. A large amount of features have been added to make your radar chart powerful. See ggradar2 on my Github

Introduction

ggradar2 is a gg-function to draw a radar plot for data analysis. It is stem from ggradar but has been extended with more cool features.

Install ggradar2

Run the code

1	devtools::install_github("xl0418/ggradar2",dependencies=TRUE)

Use ggradar2

Load data.

library(ggradar2)
data(mtcars)
% Extract the group names. Otherwise, the first column will be chosen as the group names.
group = row.names(mtcars)
df = cbind(group,mtcars)
% The radar chart is not a nice presentation if you want to compare too many groups. Thus here 
% we only focus on 4 groups.
dftest = head(df,4)
% To better distinguish two different styles, 6 groups are selected for illustration.
dftest = dftest[,1:7]

Default style

By default

1	ggradar2(dftest)

returns

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No fill with round grid

If you don’t want to fill the polygon, run

1	ggradar2(dftest,polygonfill = FALSE)

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Web type

A new web type ‘lux’ has been added by webtype.

mini type

1	ggradar2(dftest,webtype = 'mini')

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luxurious type

1	ggradar2(dftest,webtype = 'lux')

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Gird line trend

Use grid.line.trend = 'increase' to plot an outward-increasing grid lines.

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ggradar2(dftest,style = 'sharp',webtype = 'lux',
              group.line.width = 0.5,grid.line.trend = 'increase',gridline.min.linetype = 'solid',
              gridline.max.linetype = 'solid',gridline.min.colour = 'black',gridline.max.colour='black')

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Full score

Use fullscore = c(...) to set the full score to each variable.

1 2	fullscore <- c(100,10,300,150,10,10) a <- ggradar2(dftest,fullscore = fullscore)

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Sharp grid

A new style has been added. Call out the straight line style by running

1	ggradar2(dftest,style = 'sharp')

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Sharp grid without fill

Get rid of the fill

1	ggradar2(dftest,style = 'sharp',polygonfill = FALSE)

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Removing the legend

1 2	ggradar2(dftest,style = 'sharp', polygonfill = FALSE,plot.legend = FALSE)

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Multiple plots by subgroups

# Extract 3 brands of cars out of the data frame
facettest <- df[c(1,2,4,5,8:14),]
# Set the subgroup names
facet1 <- mapply(rep,c('Mazda','Hornet','Merc'),c(2,2,7))
facet1 <- Reduce(c,facet1)
facettest <- cbind(facettest,facet1)
ggradar2(facettest,multiplots = TRUE)

Notice that the column name for the subgroups should be ‘facet1’. Otherwise, ggradar2 could not recognize it.

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