The next part is the geometric feature with which we want to present the data. To plot using ggplot2 I have called the ggplot( ) function and pass the data argument (experiment), then in the aesthetic part supplied the x-axis feature/variable “x = date” and y-axis feature/variable “y = car_count” and also provided the “site” as colour fill argument. In ggplot the plotting comprised of data, aesthetics (data attributes) and geometric (point, line, bar etc.).
The ggplot2 package is very simple but powerful. Hence, here we pick up the ggplot2 library for making a bar plot. To present count data comparison, bar plot would be a best suited graphical representation. So here, you can see the data frame “experiment” based on the observations. To gather more data we made another observation on 14th January. So, we selected two road location site 1 and site 2 and standing in front of the road on January 7th we started counting cars passing through for one hour (9 am to 10 am). Assume, we are researchers and for fun, we want to know how many cars are passing through the arterial road in-front of our house. In this article, we are going to leverage the potential of ggplot2 for making bar plots.īefore starting with ggplot2, we need to have some data first. R statistical programming language has one beautiful library called ggplot2 which is developed based on the concept of the grammar of graphics. Styling bar plot (making it publication-ready).
The height of the bar represents its numeric value. Each label of the category variable is represented as a bar. It shows the relationship between a numeric and a categorical variable. A bar plot (or bar chart) is one of the most common types of graphics used in research or presentation.
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