dsparks

doInstall <- TRUE
toInstall <- c("zoo")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

ftseIndex <- EuStockMarkets[, 4]
plot(ftseIndex, col = "GRAY")

# Calculate 10-day rolling mean, quickly:
smoothIndex <- rollmean(x = ftseIndex,  # original series

ralfbecher

// Convert weekname (eg. format YYYY/WW) to date:
=MakeWeekDate(subfield(field, '/', 1), subfield(field, '/', 2), 0)

ChrisBeeley

function(input, output) { 
  
  output$textDisplay <- renderTable({ 
    
    getMat = matrix(
      c(paste(input$checkGroup, collapse=','), class(input$checkGroup),
        input$boxInput, class(input$boxInput),
        as.character(as.Date(input$theDate, origin = "1970-01-01")), class(input$theDate),
        paste(as.character(as.Date(input$dateRange[[1]], origin = "1970-01-01")),
              as.character(as.Date(input$dateRange[[2]], origin = "1970-01-01")), 

stefanwalther

// '.\' is the current path
// Define the path here, if required ...
SET basePath = '.\'; 

TRACE ---------------------------------------------------------------;
TRACE Saving tables ... ;
TRACE ~~;

For i = 0 To NoOfTables() -1
     

benmarwick

# Here are a few methods for getting text from PDF files. Do read through 
# the instructions carefully! NOte that this code is written for Windows 7,
# slight adjustments may be needed for other OSs

# Tell R what folder contains your 1000s of PDFs
dest <- "G:/somehere/with/many/PDFs"

# make a vector of PDF file names
myfiles <- list.files(path = dest, pattern = "pdf",  full.names = TRUE)

jennybc

---
title: "Quicky and dirty: side-by-side plot and table"
author: "Omar AlOmeir"
output: 
  html_document:
    css: two_columns.css
---

Code from Omar AlOmeir, posted by Jenny Bryan

hadley

If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?

I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:

• Statistical knowledge
• Programming/hacking skills
• Domain expertise

Statistical knowledge

steadyfish

# using dplyr finctions in non-interactive mode
# examples

library(plyr)
library(dplyr)

d1 = data_frame(x = seq(1,20),y = rep(1:10,2),z = rep(1:5,4))
head(d1)

#### single table verbs ####

mapsam

Namecheap > Github pages

Pointing your domains to a gh-pages branch requires three steps.

1. Add the Github IPs as A records on Namecheap.
   185.199.108.153
   185.199.109.153
   185.199.110.153
   185.199.111.153

wdullaer

/* Adjusted to give override background and text colour */
.highlight pre, pre, .highlight .hll {
  background-color: #49483E;
  border: 1px solid #ccc;
  padding: 6px 10px;
  border-radius: 3px;
  color: #FFFFFF;
}

.gist pre {