Plot a Dots Chart following WJP style guidelines

wjp_dots() takes a data frame with a specific data structure (usually long shaped) and returns a ggplot object with a dots chart following WJP style guidelines.

Usage

wjp_dots(
  data,
  target,
  grouping,
  colors,
  cvec = NULL,
  order = NULL,
  diffOpac = FALSE,
  opacities = NULL,
  diffShp = FALSE,
  shapes = NA,
  draw_ci = FALSE,
  sd = NULL,
  sample_size = NULL,
  bgcolor = "#ffffff",
  ptheme = WJP_theme()
)

Arguments

data

Data frame containing the data to plot

target

String. Column name of the variable that will supply the values to plot.

grouping

String. Column name of the variable that supplies the Y-Axis labels to show in the plot.

colors

String. Column name of the variable that supplies the grouping values. The plot will show a different color per group.

cvec

Named vector with the colors to apply to the dots. Default is NULL.

order

String. Column name of the variable that contains the custom order for the labels.

diffOpac

Boolean. If TRUE, the plot will expect different levels of opacities for the dots. Default is FALSE.

opacities

Named vector with the opacity levels to apply to the dots. Default is NULL.

diffShp

Boolean. If TRUE, the plot will expect different shapes for the dots. Default is FALSE.

shapes

Named vector with shapes to be displayed. Default is NULL.

draw_ci

Boolean. If TRUE, will draw a binomial confidence interval with target value as parameter of interest.

sd

String. Column name of the variable that supplies the standard error for drawing confidence intervals.

sample_size

String. Column name of the variable that supplies the number of observations for drawing confidence intervals.

bgcolor

String. Hex code for the "white" background in the strips.

ptheme

ggplot theme function to apply to the plot. By default, function applies WJP_theme().

Value

A ggplot object

Examples

library(dplyr)
library(tidyr)
library(haven)
library(ggplot2)

# Always load the WJP fonts if not passing a custom theme to function
wjp_fonts()

# Preparing data
gpp_data <- WJPr::gpp

# Preparing data
data4dots <- gpp_data %>%
  select(country, q1a, q1b, q1c, q1d) %>%
  mutate(
    across(
      !country,
      \(x) case_when(
        x <= 2 ~ 1,
        x <= 4 ~ 0
      )
    )
  ) %>%
  group_by(country) %>%
  summarise(
    across(
      everything(),
      \(x) mean(x, na.rm = T)*100
    ),
    .groups = "keep"
  ) %>%
  pivot_longer(
    !country,
    names_to  = "variable",
    values_to = "percentage" 
  ) %>%
  mutate(
    institution = case_when(
      variable == "q1a" ~ "Institution A",
      variable == "q1b" ~ "Institution B",
      variable == "q1c" ~ "Institution C",
      variable == "q1d" ~ "Institution D",
    )
  )

# Plotting chart
wjp_dots(
  data4dots,             
  target      = "percentage",
  grouping    = "institution",  
  colors      = "country",  
  cvec        = c("Atlantis"  = "#08605F",
                  "Narnia"    = "#9E6240",
                  "Neverland" = "#2E0E02")
)