Programming Cheatsheets

Cheatsheet for R

Please contribute additional tasks and solutions.

Read/write files

File format	Package	Function(s)	Tutorial
xls(x)	`readxl`	`read_excel()`	Overview

Transforming data frames

Task	Package	Function(s)	Tutorial
Wide-to-long	`tidyr`	`gather()`, `pivot_longer()`
Long-to-wide	`tidyr`	`spread()`, `pivot_wider()`
Summarize columns	`dplyr`	`summarize()`, `count()`
Order data frame	`base`	`order()`
	`dplyr`	`arrange()`
Summarize data frame	`skimr`	`skim()`
	`base`	`str()`
Merge data frames	`dplyr`	`bind_cols()`, `bind_rows()`, `left_join()`, `right_join()` + other *_join()s
Select rows	`base`	`df[..., ]`
	`dplyr`	`filter()`
Select columns	`base`	`df[, ...]`
	`dplyr`	`select()`

Model functions

Task	Package	Function(s)	Tutorial
Linear mixed effects	`lme4`	`lmer()`, `glmer()`
Bayesian modeling	`brms`	`brm()`
Support-vector machines	`e1071`	`svm()`
	`parsnip`	`svm_poly()`, `svm_rbf()`
Naïve Bayes	`e1071`	`naiveBayes()`
	`parsnip`/`discrim`	`naive_Bayes()`
Random Forest	`randomForest`	`randomForest()`
	`parsnip`	`rand_forest()`
Neural network	`keras`	Framework
	`tensorflow`	Framework
	`nnet`	`nnet()`,`multinom()` (note: single-hidden-layer only)
GAMLSS	`gamlss`	`gamlss()`
LQM(M)	`lqmm`	`lqm()`, `lqmm()`
Nearest Neighbour	`parsnip`	`nearest_neighbor()`

Model evaluation

Task	Package	Function(s)	Tutorial
Evaluate predictions	`cvms`	`evaluate()` - regression and classification. Also: ID-level evaluation.	ID evaluation
	`yardstick`	TODO
Create confusion matrix	`cvms`	`evaluate()` or `confusion_matrix()` - see also `plot_confusion_matrix()`	Create confusion matrix
	`yardstick`	`conf_mat()`
	`caret`	`confusionMatrix()`
Cross-validation	`cvms` + `groupdata2`	`cross_validate()` for `lm()`/`lmer()`/`glm()`/`glmer()` or `cross_validate_fn()` for most others	Cross-validate custom model functions
	`caret`	`trainControl`? TODO
	`tidymodels`	TODO

Plotting with ggplot2

Task	Package	Function(s)	Tutorial
Combine ggplots	`patchwork`	`+`, `/`, `	`
Add images	`ggimage`	`geom_image()`, `geom_bgimage()`, `geom_icon()`
Add pokemons	`ggimage`	`geom_pokemon()`
Plot confusion matrix	`cvms`	`plot_confusion_matrix()`	Create confusion matrix

Sharing code examples

Task	Package	Function(s)	Tutorial
Create reproducible example	`reprex`	`reprex()`, `reprex:::prex_rtf()` (dev version)	Use `prex_rtf()`

Cheatsheet for Python