Cheatsheets

Cheetsheets including for:

• data.table
• dplyr
• forcats
• ggplot2
• rmarkdown
• shiny

ggplot

Articles

extensions and packages

All Your Figure Are Belong To Us ggplot2 extensions - gallery

• bbplot BBC Visual and Data Journalism cookbook for R graphics
• cowplot Streamlined Plot Theme and Plot Annotations for ‘ggplot2’
• directlabels Easily add direct labels to plots using the directlabels package
• GGally Extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data
• gganimate A Grammar of Animated Graphics
• ggforce Accelerating ggplot2
• gggraph An Implementation of Grammar of Graphics for Graphs and Networks
• gghighlight Highlight Lines and Points in ggplot2
• ggnetwork Geometries to Plot Networks with ggplot2
• ggnewscale Multiple Fill and Color Scales in ‘ggplot2’
• ggpubr ggplot2 Based Publication Ready Plots
• ggrepel Automatically Position Non-Overlapping Text Labels with ‘ggplot2’
• ggparliament Parliament Plots
• ggspatial Spatial Data Framework for ggplot2
• ghibli Studio Ghibli Colour Palettes
• govstyle A package for applying a gov.uk style to plots created in the R package ggplot2
• vdiffr Visual Regression Testing and Graphical Diffing

tips

• check_overlap = TRUE used to prevent labels from overlapping
• end definitions with NULL to make it easier to comment intermediate steps
• ggplotline telling a story with labels, colors, and layout
• Hyperlinking text in a ggplot2 visualization

tidyverse tips

dplyr related

• extract to parse a substring into a variable
• fct_lump within group_by statement
• glimpse instead of str to view data in rows
• group_split split data frame by groups
• janitor package for basic cleaning
• widyr package to widen data, e.g. for forming pairwise comparisons

Other tips

• end magrittr %>% pipes with identity() to make it easier to comment intermediate steps

Modelling

GLM helpers

• Trimming the Fat from glm() Models in R

Modelling packages

• broom Convert Statistical Analysis Objects into Tidy Tibbles
  • Solving the model representation problem with broom
• corrr Correlations in R
• gam Generalized Additive Models
  • GAMs in R by Noah Ross
• lfe::felm() Fit a linear model with multiple group fixed effects
• lime Local Interpretable Model-Agnostic Explanations
• mgcv Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
  • GAMS in R - A Free, Interactive Course using mgcv
• parsnip A Common API to Modeling and Analysis Functions
• Some R Packages for ROC Curves
• smurf Sparse Multi-Type Regularized Feature Modeling
• tidybayes Tidy Data and ‘Geoms’ for Bayesian Models
• tidylo Tidy log odds ratio weighted by uninformative prior
• tidymodels Easily Install and Load the ‘Tidymodels’ Packages
  • A Gentle Introduction to tidymodels
• tidypredict Run Predictions Inside the Database
• tidyroc
• xgboost optimizes splits based upon the objective function (which has a default loss function), e.g. reg:linear –> squared error
• xgboostExplainer An R package that makes xgboost models fully interpretable

Other packages of note

• beepr Easily Play Notification Sounds on any Platform
• funneljoin Join tables based on events occurring in sequence in a funnel
• futures Unified Parallel and Distributed Processing in R for Everyone
• lobstr Visualize R Data Structures with Trees
• loon Interactive Statistical Data Visualization
• redoc Reversible Reproducible Documents
• recipes Preprocessing Tools to Create Design Matrices
  • Using the recipes package for easy pre-processing
• tidygraph A Tidy API for Graph Manipulation
  • Graph analysis using the tidyverse
• tidylog Logging for ‘dplyr’ Functions
• vroom The fastest delimited reader for R

Useful commands

General

clip(object_name) # copy an object to clipboard
do.call("function name") # constructs and executes a function call from a name or a function and a list of arguments to be passed to it
get("object name") # Return the Value of a Named Object
rm(list = ls()) # clear objects from workspace
readRDS() / saveRDS() # Functions to write a single R object to a file, and to restore it
View() # Invoke a spreadsheet-style data viewer on a matrix-like R object
%T>% # Pipe a value forward into a function- or call expression and return the original value instead of the result. This is useful when an expression is used for its side-effect, say plotting or printing.

• Efficient R Programming
• Fix leaky pipes in R
• Piping - end chains with identity() to allow commenting of the last step without errors

Benchmarking

ptm <- proc.time() # Initiate a timer
proc.time() - ptm # Stop the timer
system.time() # time a particular command
 
# alternative library
library("rbenchmark")

Memory usage

source: Advanced R - Memory

library(pryr)
tracemem() # memory address
mem_used() # memory usage of an object
mem_change() # memory change from a command

Other references

Excel

• Contextures Blog Excel Tips and Tutorials
• ExcelIsFun on YouTube
• MrExcel on YouTube
• Peltier Tech Blog
• Tushar Mehta

Blogs

• David Robinson Tidy Tuesday screencast for the weekly Tidy Tuesday social data project
• Eddie’s Math and Calculator Blog
• FiveThirtyEight | Our data
• No Free Hunch | The Official Blog of Kaggle.com
• R-bloggers
• R Studio Blog
• R Views | An R community blog edited by RStudio
• R Weekly
• Revolutions

References

• Assessing data analysis and programming
• An Introduction to Statistical Learning
• blogdown: Creating Websites with R Markdown
• Code Complete, Second Edition
• Elements and Principles of Data Analysis
• The Elements of Statistical Learning
• Happy Git and GitHub for the useR
• Hypothesis tests
• In-depth introduction to machine learning in 15 hours of expert videos
• Reproducible Environments
• Scientists rise up against statistical significance