Stepped line graph
Stepped line graphs are similar to line graphs, but the line only changes direction at the points where the data changes. They are often used to visualize data that is measured at discrete intervals.
R
# Create a dataset x <- c (1, 2, 3, 4, 5, 4, 3, 2, 1) # Create a stepped line graph plot (x, type = "s" , main = "Stepped Line Graph of x" , xlab = "Index" , ylab = "Values" , col = "blue" , lwd = 2, lend = "round" ) |
Output:
In this example, we use the plot() function to create a stepped line graph of the “deaths” dataset. The type argument is set to “S” to specify a stepped line graph, and the main, xlab, and ylab arguments are used to add a title and axis labels to the plot.
Graphical Data Analysis in R
Graphical Data Analysis (GDA) is a powerful tool that helps us to visualize and explore complex data sets. R is a popular programming language for GDA as it has a wide range of built-in functions for producing high-quality visualizations. In this article, we will explore some of the most commonly used GDA techniques in the R Programming Language.
For the data visualization, we will be using the mtcars dataset which is a built-in dataset in R that contains measurements on 11 different attributes for 32 different cars.