Cara menggunakan ggballoonplot python

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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

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 # 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") 0.

# 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") 1

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

# 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") 2

point border line color.

# 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") 3

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

# 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") 4

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

# 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") 5

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").

# 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") 6

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

# 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") 7

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(), ....