| next_letter <- local({ | |
| i <- 0 | |
| function() { | |
| i <<- i + 1 | |
| paste0("x_", c(letters, LETTERS))[i] | |
| } | |
| }) | |
| f <- function() { | |
| new_arg <- alist(x = ) |
| a <- 1 | |
| b <- 2 | |
| ftw <- function() | |
| { | |
| vars <- ls(envir = .GlobalEnv) | |
| rm(list = vars, envir = .GlobalEnv) | |
| } | |
| ftw() |
| # rasmusab/beepr package is great for telling you when your R code finishes running. | |
| # But if the code throws an error, the beep will never come, and you won't know that | |
| # it finished running until you visually check. | |
| # Solution: change the error handler to a failure beep. | |
| # Example | |
| foo <- function(success = TRUE) { | |
| if (!success) { | |
| stop("Error!") | |
| } |
| #' The goals here are to: | |
| #' (1) play around with themes to make base graphics less ugly | |
| #' (2) atomically specify multiple plot aspects (data, axes, grid, title) in a single call | |
| #' (3) Recycle last plot theme to easily duplicate its appearance in the next plot | |
| #' The idea is to create a set of customizable functions like `theme()`, which return a list of graphics arguments | |
| #' These can then be passed to `splot`, which will cleanly handle them by passing some to `par` and some to `plot` | |
| #' Different `theme()` functions can then be used to modify color palettes, axes, etc. | |
| merge.list <- | |
| function (x, y) { |
| # A simple approach to visually-weighted regression plots | |
| doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
| toInstall <- c("ggplot2", "reshape2", "MASS") | |
| if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
| lapply(toInstall, library, character.only = TRUE) | |
| # Generate some data: | |
| nn <- 1000 | |
| myData <- data.frame(X = rnorm(nn), |
Please make sure you are using a recent version of R (current version is 3.6.X) - the final digit is the minor version number. The essential numbers are the first two. You can check the version of R you are running via
R.version.string
Please install the latest version of RStudio (https://www.rstudio.com/products/rstudio/download/).
| library(jsonlite) | |
| ## Download | |
| pkgs <- fromJSON("http://crandb.r-pkg.org/-/events") | |
| ## Filter | |
| na_pkgs <- unique(pkgs$name[ is.na(pkgs$date) ]) | |
| events <- pkgs[ ! pkgs$name %in% na_pkgs, c("date", "name", "event")] |
| ## See http://gettinggeneticsdone.blogspot.com/2013/06/customize-rprofile.html | |
| ## Load packages | |
| library(BiocInstaller) | |
| ## Don't show those silly significanct stars | |
| options(show.signif.stars=FALSE) | |
| ## Do you want to automatically convert strings to factor variables in a data.frame? | |
| ## WARNING!!! This makes your code less portable/reproducible. |
| # Animated dplyr joins with gganimate | |
| # * Garrick Aden-Buie | |
| # * garrickadenbuie.com | |
| # * MIT License: https://opensource.org/licenses/MIT | |
| # Note: I used Fira Sans and Fira Mono fonts. | |
| # Use search and replace to use a different font if Fira is not available. | |
| library(tidyverse) | |
| library(gganimate) |
| <script> | |
| (function() { | |
| var divHTML = document.querySelectorAll(".details-open"); | |
| divHTML.forEach(function (el) { | |
| var preNodes = el.getElementsByTagName("pre"); | |
| var outputNode = preNodes[1]; | |
| outputNode.outerHTML = "<details open class='output'><summary>Output</summary>" + outputNode.outerHTML + "</details>"; | |
| }) | |
| })(); | |
| (function() { |