matplot(xmat, type = 'l', col = c('red', 'green', 'blue', 'orange')) or a custom vector (which will recycle to the number of columns, following standard R vector recycling rules). However, any (or both) of these aesthetics can be fixed to a single value. Note that, by default, matplot varies both color ( col) and linetype ( lty) because this increases the number of possible combinations before they get repeated. Much more convenient in this situation is to use the matplot function, which only requires one call and automatically takes care of axis limits and changing the aesthetics for each column to make them distinguishable. However, this is both tedious, and causes problems because, among other things, by default the axis limits are fixed by plot to fit only the first column. One way to plot all of these observations on the same graph is to do one plot call followed by three more points or lines calls. Here is an example of a matrix containing four sets of random draws, each with a different mean. Matplot is useful for quickly plotting multiple sets of observations from the same object, particularly from a matrix, on the same graph.
Using pipe assignment in your own package %%: How to ?.String manipulation with stringi package.Standardize analyses by writing standalone R scripts.Reshaping data between long and wide forms.Reading and writing tabular data in plain-text files (CSV, TSV, etc.).Non-standard evaluation and standard evaluation.Network analysis with the igraph package.Implement State Machine Pattern using S4 Class.I/O for geographic data (shapefiles, etc.).I/O for foreign tables (Excel, SAS, SPSS, Stata).Feature Selection in R - Removing Extraneous Features.
Extracting and Listing Files in Compressed Archives.Date-time classes (POSIXct and POSIXlt).Empirical Cumulative Distribution Function.*apply family of functions (functionals).Lines(data$var2, as.numeric(data$group), col = 2)Īxis(2, labels = as.character(data$group), at = as.
Plot(data$var1, as.numeric(data$group), type = "l", Lines(as.numeric(data$group), data$var2, col = 2)Īxis(1, labels = as.character(data$group), at = as.numeric(data$group)) Plot(as.numeric(data$group), data$var1, type = "l", You can set the factor variable on the X-axis or on the Y-axis: par(mfrow = c(1, 2)) If you want to plot the data as a line graph in R you can transform the factor variable into numeric with the is.numeric function and create the plot. Consider the following sample data: # Dataĭata <- ame(group = as.factor(c("Group 1", "Group 2", "Group 3")), In addition to creating line charts with numerical data, it is also possible to create them with a categorical variable. Matplot(data, type = "l", main = "matplot function") You can plot all the columns at once with the function: # Plot all columns at once The matplot and matlines functionsĪ better approach when dealing with multiple variables inside a data frame or a matrix is the matplot function. Note that the lines function is not designed to create a plot by itself, but to add a new layer over a already created plot.