In this illustration, the Gapminder package is used for plotting charts. This data set comes with six variables including country, continent, year, life expectancy, population and GDP per capita.
Let’s install the package, load the data and examine the dataset:
install.packages("gapminder", repos = "https://cran.r-project.org")
library(gapminder)
summary(gapminder) # Summary of Gapminder dataset
str(gapminder) # Structure of dataset
gm=gapminder
head(gm)
summary(gm)
Simple Scatterplot:
library(ggplot2)
p <- ggplot(data = gm,
mapping = aes(x = gdpPercap,
y = lifeExp)) # Shows nothing. Why?
p + geom_point()
theme_bw()
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First, we need to start the data component, then add the aesthetic mapping defining the basics (i.e. variables), followed by the geometric objects. Here is an alternative:
# Alternative
p <- ggplot(data=gm, aes(x=gdpPercap, y=lifeExp))
What is still missing?
p + geom_point()
Now, we can add more features to the chart.
# Add some color grouping
p <- ggplot(data = gm,
mapping = aes(x = gdpPercap,
y = lifeExp, color=continent))
p + geom_point()
Now you can knit the Markdown file and publish it to either Rpub or your own github website!— title: “RMarkdown demo” author: “Collin DeVore” date: “March 27, 2019” output: html_document —
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
summary(cars)
You can also embed plots, for example:
Note that the echo = FALSE
parameter was added to the code chunk to prevent printing of the R code that generated the plot.