ggballoonplot: Ballon plot

Description Usage Arguments Examples

View source: R/ggballoonplot.R

Description

Plot a graphical matrix where each cell contains a dot whose size reflects the relative magnitude of the corresponding component. Useful to visualize contingency table formed by two categorical variables.

Usage

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ggballoonplot(
  data,
  x = NULL,
  y = NULL,
  size = "value",
  facet.by = NULL,
  size.range = c(1, 10),
  shape = 21,
  color = "black",
  fill = "gray",
  show.label = FALSE,
  font.label = list(size = 12, color = "black"),
  rotate.x.text = TRUE,
  ggtheme = theme_minimal(),
  ...
)

Arguments

data

a data frame. Can be:

  • a standard contingency table formed by two categorical variables: a data frame with row names and column names. The categories of the first variable are columns and the categories of the second variable are rows.

  • a streched contingency table: a data frame containing at least three columns corresponding, respectively, to (1) the categories of the first variable, (2) the categories of the second varible, (3) the frequency value. In this case, you should specify the argument x and y in the function ggballoonplot()

.

x, y

the column names specifying, respectively, the first and the second variable forming the contingency table. Required only when the data is a stretched contingency table.

size

point size. By default, the points size reflects the relative magnitude of the value of the corresponding cell (size = "value"). Can be also numeric (size = 4).

facet.by

character vector, of length 1 or 2, specifying grouping variables for faceting the plot into multiple panels. Should be in the data.

size.range

a numeric vector of length 2 that specifies the minimum and maximum size of the plotting symbol. Default values are size.range = c(1, 10).

shape

points shape. The default value is 21. Alternaive values include 22, 23, 24, 25.

color

point border line color.

fill

point fill color. Default is "lightgray". Considered only for points 21 to 25.

show.label

logical. If TRUE, show the data cell values as point labels.

font.label

a vector of length 3 indicating respectively the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic", "bold.italic") and the color (e.g.: "red") of point labels. For example font.label = c(14, "bold", "red"). To specify only the size and the style, use font.label = c(14, "plain").

rotate.x.text

logica. If TRUE (default), rotate the x axis text.

ggtheme

function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....

...

other arguments passed to the function ggpar

Examples

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# Define color palette
my_cols <- c("#0D0887FF", "#6A00A8FF", "#B12A90FF",
"#E16462FF", "#FCA636FF", "#F0F921FF")

# Standard contingency table
#:::::::::::::::::::::::::::::::::::::::::::::::::::::::::
# Read a contingency table: housetasks
# Repartition of 13 housetasks in the couple
data <- read.delim(
  system.file("demo-data/housetasks.txt", package = "ggpubr"),
  row.names = 1
  )
data

# Basic ballon plot
ggballoonplot(data)

# Change color and fill
ggballoonplot(data, color = "#0073C2FF", fill = "#0073C2FF")


# Change color according to the value of table cells
ggballoonplot(data, fill = "value")+
   scale_fill_gradientn(colors = my_cols)

# Change the plotting symbol shape
ggballoonplot(data, fill = "value",  shape = 23)+
  gradient_fill(c("blue", "white", "red"))


# Set points size to 8, but change fill color by values
# Sow labels
ggballoonplot(data, fill = "value", color = "lightgray",
              size = 10, show.label = TRUE)+
  gradient_fill(c("blue", "white", "red"))

# Streched contingency table
#:::::::::::::::::::::::::::::::::::::::::::::::::::::::::

# Create an Example Data Frame Containing Car x Color data
carnames <- c("bmw","renault","mercedes","seat")
carcolors <- c("red","white","silver","green")
datavals <- round(rnorm(16, mean=100, sd=60),1)
car_data <- data.frame(Car = rep(carnames,4),
                   Color = rep(carcolors, c(4,4,4,4) ),
                   Value=datavals )

car_data

ggballoonplot(car_data, x = "Car", y = "Color",
              size = "Value", fill = "Value") +
   scale_fill_gradientn(colors = my_cols) +
  guides(size = FALSE)


# Grouped frequency table
#:::::::::::::::::::::::::::::::::::::::::::::::::::::::::
data("Titanic")
dframe <- as.data.frame(Titanic)
head(dframe)
ggballoonplot(
 dframe, x = "Class", y = "Sex",
 size = "Freq", fill = "Freq",
 facet.by = c("Survived", "Age"),
 ggtheme = theme_bw()
)+
  scale_fill_gradientn(colors = my_cols)

# Hair and Eye Color of Statistics Students
data(HairEyeColor)
ggballoonplot( as.data.frame(HairEyeColor),
              x = "Hair", y = "Eye", size = "Freq",
              ggtheme = theme_gray()) %>%
 facet("Sex")

ggpubr documentation built on July 2, 2020, 2:12 a.m.