In a previous post, I described how I was captivated by the virtual landscape imagined by the RStudio education team while looking for resources on the RStudio website. In this post, I’ll take a look atCheatsheets another amazing resource hiding in plain sight.

RStudio IDE- - ) ```, RStudio ``` ```. An Introduction to R and RStudio Cheat sheet There are many R cheat sheets out there that provide brief summaries of functions and basic R operation (several of the better ones are listed in the resources section of this document). J f m a m j a s o n j d x j f m a m j a s o n j d x 2018-01-31 11:-01-31 11:-01-31 11:-01-31 11:-01-31 11:-01-31 11. Join and Split strc(., sep = ', collapse = NULL) Join multiple strings into a single string. Strc(letters, LETTERS) strc(., sep = ', collapse = NULL. This cheat sheet will help you to get yourself up to speed in no time! R For Data Science Cheat Sheet: xts eXtensible Time Series (xts) is a powerful package that provides an extensible time series class, enabling uniform handling of many R time series classes by extending zoo.

Apparently, some time ago when I wasn’t paying much attention, cheat sheets evolved from the home made study notes of students with highly refined visual cognitive skills, but a relatively poor grasp of algebra or history or whatever to an essential software learning tool. I don’t know how this happened in general, but master cheat sheet artist Garrett Grolemund has passed along some of the lore of the cheat sheet at RStudio. Garrett writes:

One day I put two and two together and realized that our Winston Chang, who I had known for a couple of years, was the same “W Chang” that made the LaTex cheatsheet that I’d used throughout grad school. It inspired me to do something similarly useful, so I tried my hand at making a cheatsheet for Winston and Joe’s Shiny package. The Shiny cheatsheet ended up being the first of many. A funny thing about the first cheatsheet is that I was working next to Hadley at a co-working space when I made it. In the time it took me to put together the cheatsheet, he wrote the entire first version of the tidyr package from scratch.

It is now hard to imagine getting by without cheat sheets. It seems as if they are becoming expected adjunct to the documentation. But, as Garret explains in the README for the cheat sheets GitHub repository, they are not documentation!

RStudio cheat sheets are not meant to be text or documentation! They are scannable visual aids that use layout and visual mnemonics to help people zoom to the functions they need. … Cheat sheets fall squarely on the human-facing side of software design.

Cheat sheets live in the space where human factors engineering gets a boost from artistic design. If R packages were airplanes then pilots would want cheat sheets to help them master the controls.

The RStudio site contains sixteen RStudio produced cheat sheets and nearly forty contributed efforts, some of which are displayed in the graphic above. The Data Transformation cheat sheet is a classic example of a straightforward mnemonic tool.It is likely that even someone who just beginning to work with dplyr will immediately grok that it organizes functions that manipulate tidy data. The cognitive load then is to remember how functions are grouped by task. The cheat sheet offers a canonical set of classes: “manipulate cases”, “manipulate variables” etc. to facilitate the process. Users that work with dplyr on a regular basis will probably just need to glance at the cheat sheet after a relatively short time.

The Shiny cheat sheet is little more ambitious. It works on multiple levels and goes beyond categories to also suggest process and workflow.

The Apply functions cheat sheet takes on an even more difficult task. For most of us, internally visualizing multi-level data structures is difficult enough, imaging how data elements flow under transformations is a serious cognitive load. I for one, really appreciate the help.

Rstudio Basics Cheat Sheet

Clinical psychology program. Cheat sheets are immensely popular. And even in this ebook age where nearly everything you can look at is online, and conference attending digital natives travel light, the cheat sheets as artifacts retain considerable appeal. Not only are they useful tools and geek art (Take a look at cartography) for decorating a workplace, my guess is that they are perceived as runes of power enabling the cognoscenti to grasp essential knowledge and project it in the world.

When in-person conferences resume again, I fully expect the heavy paper copies to disappear soon after we put them out at the RStudio booth.

I reproduce some of the plots from Rstudio’s ggplot2 cheat sheet using Base R graphics. I didn’t try to pretty up these plots, but you should.

I use this dataset

The main functions that I generally use for plotting are

  • Plotting Functions
    • plot: Makes scatterplots, line plots, among other plots.
    • lines: Adds lines to an already-made plot.
    • par: Change plotting options.
    • hist: Makes a histogram.
    • boxplot: Makes a boxplot.
    • text: Adds text to an already-made plot.
    • legend: Adds a legend to an already-made plot.
    • mosaicplot: Makes a mosaic plot.
    • barplot: Makes a bar plot.
    • jitter: Adds a small value to data (so points don’t overlap on a plot).
    • rug: Adds a rugplot to an already-made plot.
    • polygon: Adds a shape to an already-made plot.
    • points: Adds a scatterplot to an already-made plot.
    • mtext: Adds text on the edges of an already-made plot.
  • Sometimes needed to transform data (or make new data) to make appropriate plots:
    • table: Builds frequency and two-way tables.
    • density: Calculates the density.
    • loess: Calculates a smooth line.
    • predict: Predicts new values based on a model.

All of the plotting functions have arguments that control the way the plot looks. You should read about these arguments. In particular, read carefully the help page ?plot.default. Useful ones are:

  • main: This controls the title.
  • xlab, ylab: These control the x and y axis labels.
  • col: This will control the color of the lines/points/areas.
  • cex: This will control the size of points.
  • pch: The type of point (circle, dot, triangle, etc…)
  • lwd: Line width.
  • lty: Line type (solid, dashed, dotted, etc…).



Different type of bar plot

Continuous X, Continuous Y


Jitter points to account for overlaying points.

Rstudio basics cheat sheet

Rstudio Ide Cheat Sheet

Add a rug plot


Add a Loess Smoother

Loess smoother with upper and lower 95% confidence bands

Rstudio Cheat Sheet Pdf

Loess smoother with upper and lower 95% confidence bands and that fancy shading from ggplot2.

Add text to a plot

Discrete X, Discrete Y

Mosaic Plot

Color code a scatterplot by a categorical variable and add a legend.

par sets the graphics options, where mfrow is the parameter controling the facets.

R Studio Ggplot Cheatsheet

The first line sets the new options and saves the old options in the list old_options. The last line reinstates the old options.

Rstudio Dplyr Cheat Sheet

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