eliocamp

ditto <- function(expr) {
  plus_fun <- function(e1, e2) {
    if (is.list(e1)) {
      c(e1, list(e2))
    } else {
      list(e1, e2)
    }

  }

eliocamp

tutorial.js <- system.file("lib", "tutorial", "tutorial.js", package = "learnr")
tutorial_format.js <- system.file("rmarkdown", "templates", "tutorial", "resources", "tutorial-format.js", package = "learnr")


changes <- list(
  run_code = list(
    text = "Correr Código",
    file = tutorial.js,
    pattern = 'var run_button = add_submit_button("fa-play", "btn-success",',
    code = 'var run_button = add_submit_button("fa-play", "btn-success", "{text}", false)'

eliocamp

#' Adds tags to facets
#'
#' @export
facet_tags <- function(position = "tl", tag_pool = letters, open = "", close = ")", stroke = 0.15, stroke.color = "white",
                 color = "black") {
  if (!is.list(position)) {
    position <- switch(position,
                       tl = list(x = 0, y = 1, hjust = 0, vjust = 1),
                       tr = list(x = 1, y = 1, hjust = 1, vjust = 1),
                       bl = list(x = 0, y = 0, hjust = 0, vjust = 0),

eliocamp

## List system dependenceis for a local project (with a DESCRIPTION file) 
## and create an "apt install" command that installs them. Put it in your
## dockerfile and be happy. 

library(magrittr)

all_types <- c("Imports", "Depends", "Suggests")
description_file <- here::here("DESCRIPTION")

direct_deps <- all_types %>% 

eliocamp

#!/bin/bash
read -p "Usuario en el servidor: " USUARIO
read -p "Servidor: " SERVER

read -p "Puerto [4572]: " PUERTO
PUERTO=${PUERTO:-4572}

read -p "Nombre del tunel (y el comando) [rstudioserver]: " NOMBRE
NOMBRE=${NOMBRE:-rstudioserver}

eliocamp

library(data.table)
library(magrittr)
library(ggplot2)


url_movility <- "https://raw.githubusercontent.com/githubmg/reduccion_movilidad/master/data/Global_Mobility_Report.csv"
url_deaths <- "https://raw.githubusercontent.com/githubmg/reduccion_movilidad/master/data/time_series_covid19_deaths_global.csv"


mov <- fread(url_movility) %>% 

eliocamp

# This is an experiment to wrap CDO in R in a intuitive and pipe friendly way. 
# Usage:
#  cdo_* will create a string with a commmand. If any of the "input_file" arguments
#  is a cdo command, it will append "-" to it so that it can be chained. 
#  This is good for efficiency as it will allow you to apply multiple 
#  operations without having to write to disk the intermediate files. 


## "Internal" functions in which the magic happens
.enchain <- function(input) {

eliocamp

library(ggplot2)
library(data.table)
library(magrittr)

# From https://www.ssa.gov/oact/babynames/limits.html
file <- "https://www.ssa.gov/oact/babynames/state/namesbystate.zip"
destination <- "/home/elio/Downloads/babies.zip"
download.file(file, destination)

dir <- "/home/elio/Downloads/babies"

eliocamp

library(data.table)
library(magrittr)
library(ggplot2)
set.seed(42)
do_bench <- function(N) {
  dt <- suppressWarnings(data.table(x = rnorm(N), 
                   group = letters[1:3]))
  
  pipe <- function() {
    dt %>% 

eliocamp

---
title: "Tweet thread"
author: "Elio Campitelli"
output: github_document
---


```{r}
knitr::opts_chunk$set(dev = "png", 
                      tweet_this = TRUE)