Data Rich Reports

Session 4–Visualizing Data

Bar Charts

Retreive Code

Go here to download the code
Download the whole folder
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The Grammar of Graphics

Data viz has a language with its own grammar
Basic components include:
- Data we are trying to visualize
- Aesthetics (dimensions)
- Geom (e.g. bar, line, scatter plot)
- Color scales
- Themes
- Annotations

Let’s load our packages and import our data…

library(readr)
library(ggplot2)

dem_summary <- read_csv("dem_summary.csv")

ggplot(dem_summary, aes(x = region, y = polyarchy))

And then let’s start with the first two elements, the data and the aesthetic…

library(readr)
library(ggplot2)

dem_summary <- read_csv("dem_summary.csv")

ggplot(dem_summary, aes(x = region, y = polyarchy))

This gives us the axes without any visualization:

Now let’s add a geom. In this case we want a bar chart so we add geom_col().

ggplot(dem_summary, aes(x = region, y = polyarchy)) + 
  geom_col()

That gets the idea across but looks a little depressing, so…

…let’s change the color of the bars by specifying fill = "steelblue".

ggplot(dem_summary, aes(x = region, y = polyarchy)) + 
  geom_col(fill = "steelblue")

Note how color of original bars is simply overwritten:

Now let’s add some labels with the labs() function:

ggplot(dem_summary, aes(x = region, y = polyarchy)) + 
  geom_col(fill = "steelblue") +
  labs(
    x = "Region", 
    y = "Avg. Polyarchy Score", 
    title = "Democracy by region, 1990 - present", 
    caption = "Source: V-Dem Institute"
    )

And that gives us…

Next, we reorder the bars with fct_reorder() from the forcats package.

library(forcats)

ggplot(dem_summary, aes(x = fct_reorder(region, -polyarchy), y = polyarchy)) +
  geom_col(fill = "steelblue") + 
  labs(
    x = "Region", 
    y = "Avg. Polyarchy Score", 
    title = "Democracy by region, 1990 - present", 
    caption = "Source: V-Dem Institute"
    )

Note that we could also use the base R reorder() function here.

This way, we get a nice, visually appealing ordering of the bars according to levels of democracy…

Now let’s change the theme to theme_minimal().

ggplot(dem_summary, aes(x = reorder(region, -polyarchy), y = polyarchy)) +
  geom_col(fill = "steelblue") + 
  labs(
    x = "Region", 
    y = "Avg. Polyarchy Score", 
    title = "Democracy by region, 1990 - present", 
    caption = "Source: V-Dem Institute"
    ) + theme_minimal()

Gives us a clean, elegant look.

Note that you can also save your plot as an object to modify later.

dem_bar_chart <- ggplot(dem_summary, aes(x = reorder(region, -polyarchy), y = polyarchy)) +
  geom_col(fill = "steelblue")

Which gives us…

dem_bar_chart

Now let’s add back our labels…

dem_bar_chart <- dem_bar_chart +
  labs(
    x = "Region", 
    y = "Avg. Polyarchy Score", 
    title = "Democracy by region, 1990 - present", 
    caption = "Source: V-Dem Institute"
    )

So now we have…

dem_bar_chart

And now we’ll add back our theme…

dem_bar_chart <- dem_bar_chart + theme_minimal()

Voila!

dem_bar_chart

Change the theme. There are many themes to choose from.

dem_bar_chart + theme_bw()

Your Turn!

glimpse() the data
Find a new variable to visualize
Make a bar chart with it
Change the color of the bars
Order the bars
Add labels
Add a theme
Try saving your plot as an object
Then change the labels and/or theme

10:00

Line Charts

Line Chart Setup

library(vdemdata)
library(tidyverse)

dem_waves_ctrs <- vdem |>
  select(
    country = country_name,     
    year, 
    polyarchy = v2x_polyarchy, 
  ) |>
  filter( 
    country %in% c("United States of America", # select countries in this list
                   "Japan", 
                   "Portugal")
    )

02:00

Line Chart

Here is the code…

# in this ggplot() call, we add a third dimension for line color
ggplot(dem_waves_ctrs, aes(x = year, y = polyarchy, color = country)) +
  geom_line(linewidth = 1) + # our geom is a line with a width of 1
  labs(
    x = "Year", 
    y = "Polyarchy Score", 
    title = 'Democracy in countries representing three different "waves"', 
    caption = "Source: V-Dem Institute", 
    color = "Country" # make title of legend to upper case
  )

Use geom_line() to specify a line chart…

# in this ggplot() call, we add a third dimension for line color
ggplot(dem_waves_ctrs, aes(x = year, y = polyarchy, color = country)) +
  geom_line(linewidth = 1) + # our geom is a line with a width of 1
  labs(
    x = "Year", 
    y = "Polyarchy Score", 
    title = 'Democracy in countries representing three different "waves"', 
    caption = "Source: V-Dem Institute", 
    color = "Country" # make title of legend to upper case
  )

Add third dimension to the aes() call for line color…

# in this ggplot() call, we add a third dimension for line color
ggplot(dem_waves_ctrs, aes(x = year, y = polyarchy, color = country)) +
  geom_line(linewidth = 1) + # our geom is a line with a width of 1
  labs(
    x = "Year", 
    y = "Polyarchy Score", 
    title = 'Democracy in countries representing three different "waves"', 
    caption = "Source: V-Dem Institute", 
    color = "Country" # make title of legend to upper case
  )

Modify the legend title…

# in this ggplot() call, we add a third dimension for line color
ggplot(dem_waves_ctrs, aes(x = year, y = polyarchy, color = country)) +
  geom_line(linewidth = 1) + # our geom is a line with a width of 1
  labs(
    x = "Year", 
    y = "Polyarchy Score", 
    title = 'Democracy in countries representing three different "waves"', 
    caption = "Source: V-Dem Institute", 
    color = "Country" # make title of legend to upper case
  )

Problem

Color Blindness

Color Vision Deficiency (CVD) or color blindness affects 8 percent of men and 1 in 200 women
There are different types of CVD but most common is red-green color blindness
Therefore, don’t include red and green in the same chart!
Look for color blind safe palettes

Solution: Use a colorblind safe color scheme like viridis…

Use scale_color_viridis_d() in this case to specify the viridis color scheme…

# in this ggplot() call, we add a third dimension for line color
ggplot(dem_waves_ctrs, aes(x = year, y = polyarchy, color = country)) +
  geom_line(linewidth = 1) + # our geom is a line with a width of 1
  labs(
    x = "Year", 
    y = "Polyarchy Score", 
    title = 'Democracy in countries representing three different "waves"', 
    caption = "Source: V-Dem Institute", 
    color = "Country" # make title of legend to upper case
  ) +
  scale_color_viridis_d(option = "mako", end = .8) # use viridis color palette

Better!

Palettes

There are a number of viridis palettes
See this reference to view different palettes and options
You can also use scale_color_viridis_c() to specify a continuous color scale
Also check out the paletteer package for easy access to many more palettes

Your Turn!

See table three of this article
Select three countries to visualize
Adjust setup code to filter data on those countries
Visualize with geom_line()
Use scale_color_viridis_d() to specify a viridis color scheme

10:00

Bonus Material

Superfun Data Visualization

library(gganimate)
library(gapminder)

ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('linear')

Superfun Data Visualization

library(gganimate)
library(gapminder)

ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('linear')

Extended `vdemdata` Example

# Load packages
library(vdemdata) # to download V-Dem data
library(dplyr)

# Download the data
democracy <- vdem |> # download the V-Dem dataset
  filter(year == 2015)  |> # filter year, keep 2015
  select(                  # select (and rename) these variables
    country = country_name,     # the name before the = sign is the new name  
    vdem_ctry_id = country_id,  # the name after the = sign is the old name
    year, 
    polyarchy = v2x_polyarchy, 
    gdp_pc = e_gdppc, 
    region = e_regionpol_6C
    ) |>
  mutate(
    region = case_match(region, # replace the values in region with country names
                     1 ~ "Eastern Europe", 
                     2 ~ "Latin America",  
                     3 ~ "Middle East",   
                     4 ~ "Africa", 
                     5 ~ "The West", 
                     6 ~ "Asia")
  )

# View the data
glimpse(democracy)

Use filter() to select years…

# Download the data
democracy <- vdem |> 
  filter(year == 2015)  |> # keep 2015
  select(                 
    country = country_name,       
    vdem_ctry_id = country_id,  
    year, 
    polyarchy = v2x_polyarchy, 
    gdp_pc = e_gdppc, 
    region = e_regionpol_6C
    ) |>
  mutate(
    region = case_match(region,
                     1 ~ "Eastern Europe", 
                     2 ~ "Latin America",  
                     3 ~ "Middle East",   
                     4 ~ "Africa", 
                     5 ~ "The West", 
                     6 ~ "Asia")
  )

Use select() to choose variables…

# Download the data
democracy <- vdem |> 
  filter(year == 2015)  |> 
  select(                  # select (and rename) these variables
    country = country_name,     # the name before the = sign is the new name  
    vdem_ctry_id = country_id,  # the name after the = sign is the old name
    year, 
    polyarchy = v2x_polyarchy, 
    gdp_pc = e_gdppc, 
    region = e_regionpol_6C
    ) |>
  mutate(
    region = case_match(region, 
                     1 ~ "Eastern Europe", 
                     2 ~ "Latin America",  
                     3 ~ "Middle East",   
                     4 ~ "Africa", 
                     5 ~ "The West", 
                     6 ~ "Asia")
  )

Use mutate with case_match() to Recode Region….

# Download the data
democracy <- vdem |>
  filter(year == 2015)  |> 
  select(                  
    country = country_name,     
    vdem_ctry_id = country_id,  
    year, 
    polyarchy = v2x_polyarchy, 
    gdp_pc = e_gdppc, 
    region = e_regionpol_6C
    ) |>
  mutate(
    region = case_match(region, # replace the values in region with country names
                     1 ~ "Eastern Europe", 
                     2 ~ "Latin America",  
                     3 ~ "Middle East",   
                     4 ~ "Africa", 
                     5 ~ "The West", 
                     6 ~ "Asia")
                    # number on the left of the ~ is the V-Dem region code
                    # we are changing the number to the country name on the right
                    # of the equals sign
  )

Visualize It!

library(ggplot2)

ggplot(democracy, aes(x = gdp_pc, y = polyarchy)) + 
  geom_point(aes(color = region)) + 
  geom_smooth(method = "lm", linewidth = 1) + 
  scale_x_log10(labels = scales::label_number(prefix = "$", suffix = "k")) +
  labs(
    x= "GDP per Capita", 
    y = "Polyarchy Score",
    title = "Wealth and democracy in 2015", 
    caption = "Source: V-Dem Institute", 
    color = "Region"
    ) +
  scale_color_viridis_d(option = "inferno", end = .8)

Try it Yourself

Go to the V-Dem Codebook
Select a democracy indicator from Part 2.1 (high level indicators) to visualize
Note the indicator code (e.g. “v2x_polyarchy” for the polyarchy score)
Change the code and download the data so you can visualize it
Now make a scatter plot of your indicator versus GDP

Coding Assignment 1

Let’s get started on the first assignment
Instructions for Coding Assignment 1 are here
Due by 11:59pm on Sunday, February 25

Data Rich Reports

Bar Charts

Retreive Code

The Grammar of Graphics

Your Turn!

Line Charts

Line Chart Setup

Line Chart

Problem

Color Blindness

Better!

Palettes

Your Turn!

Bonus Material

Superfun Data Visualization

Superfun Data Visualization

Superfun Data Visualization

Extended vdemdata Example

Visualize It!

Visualize It!

Try it Yourself

Coding Assignment 1

Coding Assignment 1

Extended `vdemdata` Example