In such cases we may have forgotten how we created the graphical display that we were so proud of, and will need to again spend a few hours to recreate it. Often we work on one part of a homework assignment or project for a few hours, then move on to something else, and then return to the original part a few days, months, or sometimes even years later. In addition to making the workflow more efficient, R scripts provide another large benefit. Although this all could be accomplished by typing and re-typing commands at the R Console, it is easier and more effective to write the commands in a script file, which then can be submitted to the R console either a line at a time or all together. Furthermore, each of these representations may require several R commands to create. For example creating an effective graphical representation of data can involve trying out several different graphical representations, and then tens if not hundreds of iterations when fine-tuning the chosen representation. 11.6 A Summary of Useful graphics Functions and Argumentsĭoing work in data science, whether for homework, a project for a business, or a research project, typically involves several iterations.8.4.2 Michigan Campgrounds Server Logic.8.4 More Advanced Shiny App: Michigan Campgrounds.7.2 Programming: Conditional Statements.6.2 Reading Data with Missing Observations.4.7.2 Logical Subsetting and Data Frames. ![]() ![]()
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