dantalus

  summaryA <- function(data, ...){

    # Example
    #
    # data <- data.frame("A" = rnorm(500, 0, 1),
    #                    "B" = rnorm(500, 0, 1),
    #                    "C" = factor(sample(c("Ca", "Cb"), 500, replace = T)))
    #
    # a <- summaryA(data)
    #

dantalus

Sex & 3 &  &   &   &  \\
\multicolumn{1}{r}{Male} &   & 51\%  & 50\%  & 60\% \\
\multicolumn{1}{r}{Female} &   & 49\%  & 50\%  & 40\% \\
Gestational Age (wks) & 0 & 40.3(39.3 to 41)  & 40.3(39.3 to 41)  & 40.1(39.4 to 41) \\
Birth weight (g) & 3 & 3460(3150 to 3770)  & 3430(3120 to 3720)  & 4390(4065 to 4605) \\
Birth length (cm) & 71 & 50.2(49 to 51.8)  & 50(48.9 to 51.5)  & 53(51.5 to 54) \\
Fat mass (\%) & 531 & 10.9(8.2 to 13.8)  & 10.6(8 to 13.4)  & 16(13.1 to 18.5) \\
Age (yrs) & 0 & 30(28 to 33)  & 30(28 to 33)  & 31(28 to 33) \\
Height (cm) & 0 & 165(161 to 168)  & 165(161 to 168)  & 165(160.2 to 169) \\
Weight (kg) & 0 & 65(59.2 to 74)  & 65(60 to 74)  & 65(58 to 75.8) \\

sbalci

library(foreign) # foreign paketi yükleniyor

# read.spss komutu ile değer etiketlerini almasını ve bunu liste olarak değil de data.frame olarak kaydetmesini istiyoruz
mydata <- read.spss("mydata.sav", use.value.labels = TRUE, to.data.frame = TRUE)

# aktardığımız data.frame'in özellikleri (attr) içinde değişkenlerin etiketleri var, bunları dışarı çıkartıyoruz
VariableLabels <- as.data.frame(attr(mydata, "variable.labels"))

# elde ettiğimiz data.frame'deki satır isimleri değişkenlerin isimleri oluyor, karşılarında da değişken etiketleri var
# satır isimlerini de dışarı çıkartıyoruz

trinker

if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, tidyr, wakefield)

set.seed(10)
dat <- r_data_frame(n = 10000,
        race,
        age,
	    sex
    )

aoles

---
output: html_document
---

```{r setup, include=FALSE}
knit_hooks_source <- knitr::knit_hooks$get("source")
knitr::knit_hooks$set(source = function (x, options) {
  if (!is.null(options$save))
    writeLines(x, options$save)
  knit_hooks_source(x, options)

seasmith

`[.hmmm` <- function (x, i, ...) {
  
  isub <- substitute(i)
  
  is_seq <- identical(as.list(isub)[[1L]], as.name(":"))
  
  if (is_seq) {
    
    end_seq <- as.list(isub)[[3L]]
    is_end <- identical(end_seq, as.name("end"))

thomasp85

library(gganimate) # thomasp85/gganimate
library(cartogram)
library(geogrid) # Need github version jbaileyh/geogrid
library(rnaturalearth)
library(sf)
library(scico)

us <- ne_states('united states of america', returnclass = 'sf')
us <- us[!us$woe_name %in% c('Alaska', 'Hawaii'), ]
us <- st_transform(us, '+proj=eqdc +lat_0=39 +lon_0=-96 +lat_1=33 +lat_2=45 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs')

summerofgeorge

# List the jpg files in the folder

old_files <- list.files("C:/ImageTest", pattern = "*.JPG", full.names = TRUE)
old_files

# Create vector of new files

new_files <- paste0("C:/NewFiles/file_",1:length(old_files),".JPG")
new_files

CGMossa

#TODO: Find a way to restart R without using this particular .Rprofile.
#
# CLEAN_SESSION <- TRUE
CLEAN_SESSION <- FALSE

if (interactive() && !CLEAN_SESSION) {

  # Configure session -------------------------------------------------------
  message("Interactive mode configuration")

DarwinAwardWinner

local({

    ## Put everything in a separate environment and attach that
    ## environment. Re-use the existing one from the search path it
    ## it's available, so that re-executing this file doesn't add a
    ## new environment to the search path every time.
    custom_env <- tryCatch(as.environment("rct_custom_env"),
                           error=function(...) {
                               attach(NULL, name="rct_custom_env")
                               as.environment("rct_custom_env")