gapminder: Data from Gapminder
An excerpt of the data available at Gapminder.org. For each of 142 countries, the package provides values for life expectancy, GDP per capita, and population, every five years, from 1952 to 2007.
# install.packages("dslabs") # these are data science labs
library("dslabs")## Warning: package 'dslabs' was built under R version 4.0.2data(package="dslabs")
#(system.file("script", package = "dslabs"))# The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.
# The easiest way to get ggplot2 is to install the whole tidyverse:
# install.packages("tidyverse")
# install.packages("tidyverse")
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#Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.
library(ggrepel)## Warning: package 'ggrepel' was built under R version 4.0.2# Create interactive web graphics from 'ggplot2' graphs
library(plotly)##
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data(gapminder, package = "gapminder")
gg <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
geom_point(aes(size = pop, frame = year, ids = country)) +
scale_x_log10() + xlab("GDP Per Capita") + ylab("Life Expectancy") +
theme(
axis.title.x = element_text(color="blue", size=14, face="bold"),
axis.title.y = element_text(color="#993333", size=14, face="bold"))## Warning: Ignoring unknown aesthetics: frame, idsggplotly(gg)The Graph recreates the animation of the evolution in the relationship between GDP per capita and life expectancy evolved over time. As long as a frame variable is provided, an animation is produced with play/pause button(s) and a slider component for controlling the animation. These components can be removed or customized via the animation_button() and animation_slider() functions. Moreover, various animation options, like the amount of time between frames, the smooth transition duration, and the type of transition easing may be altered via the animation_opts() function. There’s a strong relationship between GDP and life expectancy. The graph show most of developing countries at the bottom compared to the developed.
HTML widgets work just like R plots except they produce interactive web visualizations. A line or two of R code is all it takes to produce a D3 graphic or Leaflet map. HTML widgets can be used at the R console as well as embedded in R Markdown reports and Shiny web applications. hchart is a generic function which takes an object and returns a highcharter object. There are functions whose behavior are similar to the functions of the ggplot2 package like:
hchart works like ggplot2’s qplot. hc_add_series works like ggplot2’s geom_S. hcaes works like ggplot2’s aes.
The gapminder data set comes built in with dslabs.
# install.packages("dslabs") # these are data science labs
library("dslabs")
library(tidyverse)
library(highcharter)## Warning: package 'highcharter' was built under R version 4.0.2## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo## Highcharts (www.highcharts.com) is a Highsoft software product which is## not free for commercial and Governmental use##
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## starslibrary(gapminder)## Warning: package 'gapminder' was built under R version 4.0.2##
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## gapminder#library(dslab)
#glimpse(gapminder)
data(gapminder, package = "gapminder")The function distinct() [dplyr package] can be used to keep only unique/distinct rows from a data frame. The option .kep_all is used to keep all variables in the data.
gp <- gapminder %>%
arrange(desc(year)) %>%
distinct(country, .keep_all = TRUE)
gp2 <- gapminder %>%
select(country, year, pop) %>%
nest(-country) #%>%## Warning: All elements of `...` must be named.
## Did you want `data = c(year, pop)`?gptot <- left_join(gp, gp2, by = "country")
x <- c("Population", "Year", "GDP PerCp", "Life Expectancy", "Continent")
y <- sprintf("{point.%s:.0f}", c("pop", "year", "gdpPercap", "lifeExp", 'continent'))
tltip <- tooltip_table(x, y)
# hchart() is a generic function to draw different charts on the fly. The resulting chart is a highchart object so you can keep modifying with the implmented API. If you are familiar with ggplot2, this function is similar to qplot() of it.
hchart(
gptot,
"point",
hcaes(lifeExp, gdpPercap, name = country, size = pop, group = continent)
) %>%
#hc_yAxis(type = "logarithmic") %>%
hc_xAxis(title = list(text="Life Expectancy")) %>%
hc_yAxis(title = list(text="GDP Per Capita")) %>%
hc_legend(align = "center",
verticalAlign = "bottom",
layout = "horizontal"
) %>%
hc_tooltip(
useHTML = TRUE,
headerFormat = "<b>{point.key}</b>",
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