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_AutomatedDashboardDeviation-1.Rmd
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_AutomatedDashboardDeviation-1.Rmd
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---
title: "Dashboard visualizations in R: Deviation"
author: "Kristian Larsen"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: scroll
---
```
from: https://datascienceplus.com/automated-dashboard-visualizations-with-deviation-in-r/?fbclid=IwAR2JcAMQ4eNRMrEBPGL79HDbS818vGZX0evs-ateBX0d9SRFIilY7U44Szw
```
```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(plotly)
theme_set(theme_bw())
# Data Prep
data("mtcars") # load data
mtcars$`car name` <- rownames(mtcars) # create new column for car names
mtcars$mpg_z <- round((mtcars$mpg - mean(mtcars$mpg))/sd(mtcars$mpg), 2) # compute normalized mpg
mtcars$mpg_type <- ifelse(mtcars$mpg_z < 0, "below", "above") # above / below avg flag
mtcars <- mtcars[order(mtcars$mpg_z), ] # sort
mtcars$`car name` <- factor(mtcars$`car name`, levels = mtcars$`car name`) # convert to factor to retain sorted order in plot.
```
Row
-----------------------------------------------------------------------
### Chart A: Diverging Barcharts
```r
ggplot(mtcars, aes(x=`car name`, y=mpg_z, label=mpg_z)) +
geom_bar(stat='identity', aes(fill=mpg_type), width=.5) +
scale_fill_manual(name="Mileage",
labels = c("Above Average", "Below Average"),
values = c("above"="#00ba38", "below"="#f8766d")) +
labs(subtitle="Normalised mileage from 'mtcars'",
title= "Diverging Bars") +
coord_flip()
ggplotly(p = ggplot2::last_plot())
```
### Chart B: Diverging Lollipop Chart
```r
library(ggplot2)
theme_set(theme_bw())
ggplot(mtcars, aes(x=`car name`, y=mpg_z, label=mpg_z)) +
geom_point(stat='identity', fill="black", size=6) +
geom_segment(aes(y = 0,
x = `car name`,
yend = mpg_z,
xend = `car name`),
color = "black") +
geom_text(color="white", size=2) +
labs(title="Diverging Lollipop Chart",
subtitle="Normalized mileage from 'mtcars': Lollipop") +
ylim(-2.5, 2.5) +
coord_flip()
ggplotly(p = ggplot2::last_plot())
```
Row
-----------------------------------------------------------------------
### Cart C: Diverging Dot Plot
```r
library(ggplot2)
theme_set(theme_bw())
# Plot
ggplot(mtcars, aes(x=`car name`, y=mpg_z, label=mpg_z)) +
geom_point(stat='identity', aes(col=mpg_type), size=6) +
scale_color_manual(name="Mileage",
labels = c("Above Average", "Below Average"),
values = c("above"="#00ba38", "below"="#f8766d")) +
geom_text(color="white", size=2) +
labs(title="Diverging Dot Plot",
subtitle="Normalized mileage from 'mtcars': Dotplot") +
ylim(-2.5, 2.5) +
coord_flip()
ggplotly(p = ggplot2::last_plot())
```