| # lazy data frame | |
| # | |
| # like idata.frame, but exploits lazy evaluation + macro code generation | |
| # instead of active bindings | |
| library(vadr) | |
| lazy.frame <- function(df, enclos=parent.frame(), ...) UseMethod("lazy.frame") | |
| lazy.frame.lazy.frame <- function(df, ...) df |
| # server.R | |
| library("shiny") | |
| shinyServer( | |
| function(input, output){ | |
| output$displayCounter <- renderText({ | |
| c("value of counter:", updateCounter()) | |
| }) |
| vectorised_r <- function(x, y) { | |
| exp(-abs(x - y)) | |
| } | |
| devectorised_r <- function(x, y) { | |
| r <- rep(NA, length(x)) | |
| for(i in seq_along(x)) { | |
| r[i] <- exp(-abs(x[i] - y[i])) | |
| } | |
| r |
| # User facing function | |
| # | |
| # to_math(x[1] + 1^{2 + 4} + 5 + sqrt(y) / 5 %/% 10) | |
| # to_math(paste(x^2, y - 1, z_i)) | |
| # to_math(hat(tilde(ring(x)))) | |
| # to_math(pi*r^2) | |
| # to_math(unknown_call(x, floor(sqrt(z)))) | |
| # to_math(u1(x) + u2(x)) | |
| to_math <- function(x) { | |
| x <- substitute(x) |
Often times when working with data in R, you find yourself needing to summarise a data.frame by a column, a
SELECT SUM(..) or SELECT COUNT(..) in MySQL if you will.
For instance, you may have a lot of page-visits to analyse and you aren't quite certain how to summarise some
of that data using R.
Let's consider the following (trivial) dataset: