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MAIDR (Multimodal Access and Interactive Data Representation) is an R package that makes data visualizations accessible to users with visual impairments. It converts ggplot2 and Base R plots into interactive, accessible formats with:
MAIDR helps data scientists and researchers create inclusive visualizations that everyone can explore, regardless of visual ability.
Install the development version from GitHub:
MAIDR works with two main functions:
show() - Display an interactive plot
in RStudio Viewer or browsersave_html() - Save a plot as a
standalone HTML filelibrary(maidr)
library(ggplot2)
# Create sample data
sales_data <- data.frame(
Product = c("A", "B", "C", "D"),
Sales = c(150, 230, 180, 290)
)
# Create a bar chart
p <- ggplot(sales_data, aes(x = Product, y = Sales)) +
geom_bar(stat = "identity", fill = "steelblue") +
labs(
title = "Product Sales by Category",
x = "Product",
y = "Sales Amount"
) +
theme_minimal()
# Display interactively
show(p)
# Or save as HTML file
save_html(p, "sales_chart.html")MAIDR also works with Base R plotting functions:
library(maidr)
# Create a simple barplot
categories <- c("A", "B", "C", "D")
values <- c(150, 230, 180, 290)
barplot(
values,
names.arg = categories,
col = "steelblue",
main = "Product Sales by Category",
xlab = "Product",
ylab = "Sales Amount"
)
# Note: For Base R plots, call show() with NO arguments
# after creating the plot
show()When you open a MAIDR plot, you can explore it using:
MAIDR plots include:
Plots can be heard through:
MAIDR supports a comprehensive range of visualizations:
facet_wrap() and
facet_grid() in ggplot2par(mfrow/mfcol) for Base RSee the Supported Plot Types vignette for detailed examples of each.
?maidr::show for function detailslibrary(maidr)
library(ggplot2)
# Normal distribution
hist_data <- data.frame(values = rnorm(1000, mean = 100, sd = 15))
p <- ggplot(hist_data, aes(x = values)) +
geom_histogram(bins = 30, fill = "skyblue", color = "black") +
labs(
title = "Distribution of Test Scores",
x = "Score",
y = "Frequency"
) +
theme_minimal()
show(p)library(maidr)
library(ggplot2)
# Create sample data
scatter_data <- data.frame(
height = rnorm(50, 170, 10),
weight = rnorm(50, 70, 8),
gender = sample(c("Male", "Female"), 50, replace = TRUE)
)
p <- ggplot(scatter_data, aes(x = height, y = weight, color = gender)) +
geom_point(size = 3, alpha = 0.7) +
labs(
title = "Height vs Weight",
x = "Height (cm)",
y = "Weight (kg)"
) +
theme_minimal()
show(p)library(maidr)
library(ggplot2)
# Time series data
months <- month.abb[1:12]
temperature <- c(5, 7, 12, 18, 22, 26, 28, 27, 23, 17, 11, 6)
temp_data <- data.frame(
Month = factor(months, levels = months),
Temperature = temperature
)
p <- ggplot(temp_data, aes(x = Month, y = Temperature, group = 1)) +
geom_line(color = "red", linewidth = 1.5) +
geom_point(color = "darkred", size = 3) +
labs(
title = "Average Monthly Temperature",
x = "Month",
y = "Temperature (°C)"
) +
theme_minimal()
show(p)?maidr::show for function documentationhelp(package = "maidr")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.