| "random<-" <- function(object, position, value) { | |
| object[sample(seq_along(object), 1)] <- value | |
| object | |
| } | |
| # Example: | |
| # > x <- c(1,2,3,4,5) | |
| # > random(x) <- 10 | |
| # > x | |
| # [1] 1 10 3 4 5 |
| infixed_names <- list(intersect = '∩', union = 'U', setdiff = '-') | |
| create_infix_operator <- function(name, base_fn, e) { | |
| name <- paste("%", name, "%", sep = '') | |
| assign(name, function(x, y) get(base_fn, envir = e)(x, y), envir = e) | |
| } | |
| lapply(names(infixed_names), function(name) { | |
| create_infix_operator(infixed_names[[name]], name, e = parent.frame(2)) | |
| }) |
| x <- ls("package:base") | |
| x[substring(x, nchar(x)-1, nchar(x)) == '<-'] | |
| # "[[<-" "[<-" "@<-" "<-" "<<-" "$<-" "attr<-" "attributes<-" "body<-" "class<-" "colnames<-" "comment<-" "diag<-" "dim<-" | |
| # "dimnames<-" "Encoding<-" "environment<-" "formals<-" "is.na<-" "length<-" "levels<-" "mode<-" "mostattributes<-" "names<-" "oldClass<-" "parent.env<-" "regmatches<-" "row.names<-" | |
| # "rownames<-" "split<-" "storage.mode<-" "substr<-" "substring<-" "units<-" |
| `||` <- function(a,b) if(is.null(a)) b else base::`||`(a,b) |
| `%xor%` <- function(x,y) (x || y) && !(x && y) |
| ref_filename <- function(ref) { | |
| attr(ref, "srcfile")$filename | |
| } | |
| frame_text <- function(frame) { | |
| if (identical(frame, .GlobalEnv)) { | |
| structure(pkg = "_global", | |
| "global environment" | |
| ) |
| wrapped <- function(obj) { | |
| structure(obj, class = "wrapped") | |
| } | |
| `[[.wrapped` <- function(obj, x) { | |
| if (x == "predict") { | |
| .subset2(obj, x) | |
| } else { | |
| .subset2(obj, "model")[[x]] | |
| } |
First, visit the Hipchat account API page. You will have to login with you avantcredit.com hipchat account.
Scroll down and create your Hipchat token with the following permissions:
The token should appear in the list above. Copy the token, and then run the following line from your terminal (with the token replaced by your token):
| let @s='^i! git add "$(git rev-parse --show-toplevel)"; git commit -m "^[$a"; git push -q origin `git rev-parse --abbrev-ref HEAD` &^[dd;w^M;@"^M^M^[' |
| Can I use CSV files? What about streaming production data? So I have this SAS file... | |
| You can use any kind of data ingest your heart desires. The built-in import stage comes with support for many common formats (link), but it is easy to add more (link). | |
| If you wish to use your live production data, write a package and add an import adapter (link). | |
| What is a mungebit and why are you making up words? | |
| A mungebit is the correct mathematical abstraction for wrangling a data set in a way that you won't have to bug a software or data engineer to make it "production ready" or live in "the data pipeline." It means you can turn the 90% of time data scientists spend on data wrangling into 10%. |