![]() ![]() ![]() Since we want ggplot to plot the values as-is, we specify stat = "identity". When we use geom_bar(), by default, stat assumes that we want each bar to show the count of y-variables per x-variable. ![]() stat is used when we want to apply a statistical function to the data and show the results graphically. We also specified stat in the call to geom_bar. the x and y variables are “country” and “lifeExp”, respectively. Since we add the call to geom_bar() to an existing call to ggplot(data = data_graph, aes(x = country, y = lifeExp)), ggplot2 assumes that the x and y variables for geom_bar() are the same as those for ggplot() i.e. This is because of ggplot’s “hierarchy of defaults”. It may seem strange that we didn’t specify the x and y values for the bars, but the bars displayed life expectancy by country anyway. The numbers don’t seem to be right since the life expectancy is close to 100 for all countries - we will fix this later. To build a ggplot, we first use the ggplot() function to specify the default data source and aesthetic mappings: Let’s also make “year” a factor, since it is a discrete variable: Base plot Let’s restrict the data to the countries and years we are interested in, and save this new dataset as data_graph. We can use the following code to install and load packages. We need to install the following packages: Now that we know what we need to include in the graph, let’s move on to writing code.
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