Package 'gapminder'

Country codes

Description

Country codes

Usage

country_codes

Format

Data frame of Gapminder country names and ISO 3166-1 country codes:

country

Country name.

iso_alpha

The 3-letter ISO 3166-1 alpha-3 code.

iso_num

The 3-digit ISO 3166-1 numeric-3 code.

Also includes the countries covered by the supplemental data frame gapminder_unfiltered.

Examples

if (require("dplyr")) {
  gapminder %>%
    filter(year == 2007, country %in% c("Kenya", "Peru", "Syria")) %>%
    select(country, continent) %>%
    left_join(country_codes)
}

---

Gapminder color schemes.

Description

Color schemes for the countries and continents in the Gapminder data.

Usage

country_colors

Format

Named character vectors giving country and continent colors:

country_colors

colors for the 142 countries

continent_colors

colors for the 5 continents

See Also

gapminder for a description of the dataset

Examples

# ggplot2 examples are below these base graphics examples!

# using country_colors with base graphics

# for convenience, integrate the country colors into the data.frame
gap_with_colors <-
  data.frame(gapminder,
    cc = I(country_colors[match(
      gapminder$country,
      names(country_colors)
    )])
  )

# bubble plot, focus just on Africa and Europe in 2007
keepers <- with(
  gap_with_colors,
  continent %in% c("Africa", "Europe") & year == 2007
)
plot(lifeExp ~ gdpPercap, gap_with_colors,
  subset = keepers, log = "x", pch = 21,
  cex = sqrt(gap_with_colors$pop[keepers] / pi) / 1500,
  bg = gap_with_colors$cc[keepers]
)

if (require(ggplot2)) {
  # with ggplot2, just provide country_colors to scale_color_manual():
  # ... + scale_color_manual(values = country_colors) + ...

  # simple line plot for 5 countries
  h_countries <- c("Egypt", "Haiti", "Romania", "Thailand", "Venezuela")
  h_dat <- droplevels(subset(gapminder, country %in% h_countries))
  h_dat$country <- with(h_dat, reorder(country, lifeExp, max))
  ggplot(h_dat, aes(x = year, y = lifeExp)) +
    geom_line(aes(color = country)) +
    scale_colour_manual(values = country_colors) +
    guides(color = guide_legend(reverse = TRUE))

  # spaghetti plot for lots of countries
  ggplot(
    subset(gapminder, continent != "Oceania"),
    aes(x = year, y = lifeExp, group = country, color = country)
  ) +
    geom_line(lwd = 1, show_guide = FALSE) +
    facet_wrap(~continent) +
    scale_color_manual(values = country_colors) +
    theme_bw() +
    theme(strip.text = element_text(size = rel(1.1)))

  # bubble plot for lots of countries
  gap_bit <- subset(gapminder, year == 2007 & continent != "Oceania")
  gap_bit <- gap_bit[with(gap_bit, order(continent, -1 * pop)), ]
  ggplot(gap_bit, aes(x = gdpPercap, y = lifeExp, size = pop)) +
    scale_x_log10(limits = c(150, 115000)) +
    ylim(c(16, 96)) +
    geom_point(pch = 21, color = "grey20", show_guide = FALSE) +
    scale_size_area(max_size = 40) +
    facet_wrap(~continent) +
    coord_fixed(ratio = 1 / 43) +
    aes(fill = country) +
    scale_fill_manual(values = country_colors) +
    theme_bw() +
    theme(strip.text = element_text(size = rel(1.1)))
}

---

Gapminder data

Description

Excerpt of the Gapminder data on life expectancy, GDP per capita, and population by country.

Usage

gapminder

Format

The main data frame gapminder has 1704 rows and 6 variables:

country

factor with 142 levels

continent

factor with 5 levels

year

ranges from 1952 to 2007 in increments of 5 years

lifeExp

life expectancy at birth, in years

pop

population

gdpPercap

GDP per capita (US$, inflation-adjusted)

The supplemental data frame gapminder_unfiltered was not filtered on year or for complete data and has 3313 rows.

Source

https://www.gapminder.org/data/

See Also

country_colors for a nice color scheme for the countries

Examples

str(gapminder)
head(gapminder)
summary(gapminder)
table(gapminder$continent)
aggregate(lifeExp ~ continent, gapminder, median)
plot(lifeExp ~ year, gapminder, subset = country == "Cambodia", type = "b")
plot(lifeExp ~ gdpPercap, gapminder, subset = year == 2007, log = "x")

if (require("dplyr")) {
  gapminder %>%
    filter(year == 2007) %>%
    group_by(continent) %>%
    summarise(lifeExp = median(lifeExp))

  # how many unique countries does the data contain, by continent?
  gapminder %>%
    group_by(continent) %>%
    summarize(n_obs = n(), n_countries = n_distinct(country))

  # by continent, which country experienced the sharpest 5-year drop in
  # life expectancy and what was the drop?
  gapminder %>%
    group_by(continent, country) %>%
    select(country, year, continent, lifeExp) %>%
    mutate(le_delta = lifeExp - lag(lifeExp)) %>%
    summarize(worst_le_delta = min(le_delta, na.rm = TRUE)) %>%
    filter(min_rank(worst_le_delta) < 2) %>%
    arrange(worst_le_delta)
}

---

Gapminder data, unfiltered.

Description

The supplemental data frame gapminder_unfiltered was not filtered on year or for complete data and has 3313 rows. Everything else is as documented in gapminder.

Usage

gapminder_unfiltered

Format

An object of class tbl_df (inherits from tbl, data.frame) with 3313 rows and 6 columns.

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