jrosell

get_mode <- \(x) {
  r <- table(x)
  names(r[r == max(r)])
}
# For example:
# > get_mode(c(1,2,2,3,3,4))
# 2  3

jrosell

#!/usr/bin/env Rscript

cat("==========================================================================\n")
cat("Example of strategy patern in R: Multiple ways to show routes. \n")

# Problem:
# You build a navigation app for casual travelers and help users quickly orient themselves in any city.
# 
# - The first only build the routes over roads.
# - Next update, you added an option to build walking routes. 

jrosell

library(shiny)
library(shinyjs)

ui <- fluidPage(
    useShinyjs(),
    hidden(
        textInput("my_input", label = "my_input", value = "Initial value")
    ),
    textOutput("my_output"),
    actionButton("my_js_button","Update from JavaScript"),

jrosell

## Preparations

pkgs <- c("tidyverse", "pRecipe", "giscoR", "terra", "rayshader", "patchwork")
rlang::check_installed(pkgs)
suppressPackageStartupMessages({
    invisible(lapply(pkgs, library, character.only = TRUE, quietly = TRUE))
})

jrosell

# Dades per CCAA ===============================================================

library(tidyverse)
library(rvest)
theme_set(theme_minimal())
older_year <- 2002

region <- tibble(
    slug = c("andalucia", "aragon", "asturias", "canarias", "cantabria", "castilla-leon", 
                 "castilla-la-mancha", "cataluna", "ceuta", "melilla", "madrid", "valencia", 

jrosell

# Single grouping in base R: Multiple functions

library(dplyr, warn.conflicts = FALSE)
expected_output <- mtcars %>%
    group_by(cyl) %>%
    summarise(mean = mean(disp), n = n())  %>% 
    as.data.frame()
expected_output

by <- c("cyl")

jrosell

library(tidyverse)

x <- list(a = list(b = 1, c = NULL), d = NULL)

get_list_names <- \(x, y = c()){
  if (!is.null(names(x))){
    for (nm in names(x)) {
      y <- get_list_names(x[[nm]], c(y, nm))
    }
  }

jrosell

# Game of Life using {coro} generators in R
# Inspiration from Jack Diederich's Python implementation: https://gist.github.com/jhrr/2b5a60e9efcb573c9cc4

library(tidyverse)
library(coro)
library(zeallot)

generate_neighbors <- generator(function(point) {
    c(x, y) %<-% point
    yield(c(x + 1, y))

jrosell

# preallocates memory.
fmat <- function(n) {
    res <- matrix(NA, n, n)
    for (i in 1:n) {
        res[i, ] <- runif(n)
    }
    res
}

# rbind each time

jrosell

# R CMD BATCH --vanilla json-benchmark.R
output_dir <- setwd(here::here())
grDevices::dev.set(1)

# simpleBenchmark
file <- system.file("jsonexamples", "twitter.json", package="RcppSimdJson")
jsontxt <- readLines(file)
res <- microbenchmark::microbenchmark(
    jsonify = jsonify::validate_json(jsontxt),
    jsonlite = jsonlite::validate(jsontxt),