Why am I making you learn R?
Pivot Tables do the same thing!
Austerity and Excel
Debt:GDP ratio
90%+ → −0.1% growth
Austerity and Excel
Debt:GDP ratio
90%+ → −0.1% growth
Austerity and Excel
Austerity and Excel
Austerity and Excel
Debt:GDP ratio = 90%+ → 2.2% growth (!!)
Genes and Excel
Septin 2
Membrane-Associated Ring Finger (C3HC4) 1
2310009E13
Genes and Excel
Septin 2
Membrane-Associated Ring Finger (C3HC4) 1
2310009E13
20% of genetics papers between 2005–2015 (!!!)
R Markdown in real life
Yay bar plots!
We are a lot better at visualizing
line lengths than angles and areas
Oh no bar plots!
Oh no bar plots!
Bar plots and summary statistics
Bar plots and summary statistics
Show more data with strip plots
ggplot(animals, aes(x = animal_type, y = weight, color = animal_type)) + geom_point(position = position_jitter(height = 0), size = 1) + labs(x = NULL, y = "Weight") + guides(color = "none")
Show more data with beeswarm plots
library(ggbeeswarm)ggplot(animals, aes(x = animal_type, y = weight, color = animal_type)) + geom_beeswarm(size = 1) + # Or try this too: # geom_quasirandom() + labs(x = NULL, y = "Weight") + guides(color = "none")
Combine boxplots with points
ggplot(animals, aes(x = animal_type, y = weight, color = animal_type)) + geom_boxplot(width = 0.5) + geom_point(position = position_jitter(height = 0), size = 1, alpha = 0.5) + labs(x = NULL, y = "Weight") + guides(color = "none")
Combine violins with points
ggplot(animals, aes(x = animal_type, y = weight, color = animal_type)) + geom_violin(width = 0.5) + geom_point(position = position_jitter(height = 0), size = 1, alpha = 0.5) + labs(x = NULL, y = "Weight") + guides(color = "none")
Overlapping ridgeplots
library(ggridges)ggplot(animals, aes(x = weight, y = animal_type, fill = animal_type)) + geom_density_ridges() + labs(x = "Weight", y = NULL) + guides(fill = "none")
Lots of alternatives
We'll use a summarized version of the gapminder dataset as an example
library(gapminder)gapminder_continents <- gapminder %>% filter(year == 2007) %>% # Only look at 2007 count(continent) %>% # Get a count of continents arrange(desc(n)) %>% # Sort descendingly by count # Make continent into an ordered factor mutate(continent = fct_inorder(continent))ggplot(gapminder_continents, aes(x = continent, y = n, fill = continent)) + geom_col() + guides(fill = "none") + labs(x = NULL, y = "Number of countries")
Alternatives: Lollipop charts
Since the end of the bar is important, emphasize it the most
ggplot(gapminder_continents, aes(x = continent, y = n, color = continent)) + geom_pointrange(aes(ymin = 0, ymax = n)) + guides(color = "none") + labs(x = NULL, y = "Number of countries")
Alternatives: Waffle charts
Show the individual observations as squares
# This has to be installed in a special way--you can't use the Packages panel. # Run this in your console:# devtools::install_github("hrbrmstr/waffle")library(waffle)ggplot(gapminder_continents, aes(x = continent, y = n, fill = continent)) + geom_waffle(aes(values = n), # geom_waffle() needs a special values aesthetic n_rows = 9, # It has lots of other options too flip = TRUE, na.rm = TRUE) + labs(fill = NULL) + coord_equal() + # Make all the squares square theme_void() # Use a completely empty theme
Alternatives: Heatmaps
If exact counts are less important,
try a heatmap with geom_tile()
Pie charts
Perceptual issues with angle and fill space
Only okay(ish) if there are a few easily distinguishable categories
Treemaps and mosaic plots
Treemaps with the {treemapify} package
Mosaic plots with the {ggmosaic} package
