Diverging Lollipop Chart: A Visual Tool for Comparing Data with {healthyR}
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Introduction
A diverging lollipop chart is a useful tool for comparing data that falls into two categories, usually indicated by different colors. This type of chart is particularly well-suited for comparing the differences between two data sets and for identifying which data points are contributing most to the differences.
The R package {healthyR}
offers a function called diverging_lollipop_plt()
that can be used to create a diverging lollipop chart. This function has several parameters that can be used to customize the chart to meet your specific needs.
In conclusion, the diverging lollipop chart is a useful tool for comparing data sets and can provide insights into the differences between two sets of data. The diverging_lollipop_plt()
function from the {healthyR}
package is a great option for creating this type of chart, as it offers a range of customization options to meet your specific needs. Whether you’re working with data related to business, finance, or any other field, a diverging lollipop chart can be a valuable tool in your visual analysis toolkit.
Function
Let’s take a look at the full function call.
diverging_lollipop_plt( .data, .x_axis, .y_axis, .plot_title = NULL, .plot_subtitle = NULL, .plot_caption = NULL, .interactive = FALSE )
Now lets see the arguments that get provided to the parameters.
.data
– The data to pass to the function, must be a tibble/data.frame..x_axis
– The data that is passed to the x-axis. This will also be the x and xend parameters of the geom_segment.y_axis
– The data that is passed to the y-axis. This will also equal the parameters ofyend
andlabel
.plot_title
– Default is NULL.plot_subtitle
– Default is NULL.plot_caption
– Default is NULL.interactive
– Default is FALSE. TRUE returns a plotly plot
Example
Let’s see an example.
library(healthyR) suppressPackageStartupMessages(library(ggplot2)) data("mtcars") mtcars$car_name <- rownames(mtcars) mtcars$mpg_z <- round((mtcars$mpg - mean(mtcars$mpg))/sd(mtcars$mpg), 2) mtcars$mpg_type <- ifelse(mtcars$mpg_z < 0, "below", "above") mtcars <- mtcars[order(mtcars$mpg_z), ] # sort mtcars$car_name <- factor(mtcars$car_name, levels = mtcars$car_name) diverging_lollipop_plt( .data = mtcars, .x_axis = car_name, .y_axis = mpg_z )
Now let’s also see the interactive chart.
diverging_lollipop_plt( .data = mtcars, .x_axis = car_name, .y_axis = mpg_z, .interactive = TRUE )
Voila!
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