![]() The basic syntax for lab() is : lab(title = "Hello Guru99") The reader should see the story behind the data analysis just by looking at the graph without referring additional documentation. ![]() So far, we haven’t added information in the graphs. Note that other smoothing methods are available se = FALSE: Don’t display the standard error.col = “#C42126”: Code for the red color of the line.The argument stat_smooth() controls for the smoothing method.It is helpful for further use or avoid too complex line of codes graph: You store your graph into the variable graph.my_graph <- ggplot(mtcars, aes(x = log(mpg), y = log(drat))) + You can plot the fitted value of a linear regression. You can add another level of information to the graph. Note that any other transformation can be applied such as standardization or normalization. You transform the x and y variables in log() directly inside the aes() mapping. ![]() ggplot(mtcars, aes(x = log(mpg), y = log(drat))) + One solution to make your data less sensitive to outliers is to rescale them. In rare occasion data comes in a nice bell shape. Rescale the data is a big part of the data scientist job.
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