jaeddy

Building a new RStudio Server AMI

The steps below can be followed to create a new AMI for use with Amazon EC2 instances that includes the latest versions of R, RStudio, and RStudio Server. The idea is inspired by the work of Louis Aslett, who creates and hosts his own public AMIs for RStudio. My own goal was to create an AMI with RStudio v1.0.0 or higher, such that I could use the recent R Notebooks feature. However, the instructions should generally apply for whenever you might be impatient accessing the latest version of R-related software on AWS (via an interactive browser interface...).

Getting started

1. Create a new EC2 instance with the latest Ubuntu AMI (should be fine to do with Spot); based on Louis Aslett's AMI, I opted to include a general purpose SSD EBS volume with 10GB of storage space
2. SSH into the instance

Downloading/installing RStudio Server

luiscape

#
#  Original solution via StackOverflow:
#    http://stackoverflow.com/questions/35802939/install-only-available-packages-using-conda-install-yes-file-requirements-t
#

#
#  Install via `conda` directly.
#  This will fail to install all
#  dependencies. If one fails,
#  all dependencies will fail to install.

saurabhshri

Install and use pip in a local directory without root/sudo access.

By: @saurabhshri

Why?

Many users when are given server access, do not have root (or sudo) privileges and can not simply do sudo apt-get install python-pip . Here's an easy way you can install and use pip without root (or sudo) access in a local directory. Note : This works without easy_install too.

How?

mugifly

#!/bin/bash

set -e

echo -e "Image Converter for Slack Emoji\nNOTICE: The image will be overwritten."

if [ $# -lt 1 ]; then
	echo "USAGE:"
	echo -e "  ${0} IMG_FILE [IMG_FILE...]\n"
	echo "IMG_FILE:"

gboeing

To distribute a package on pypi

Directory structure

/project/
    /package/
        __init__.py
        module.py
 setup.py

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

benmarwick

library("RWeka")
library("tm")

data("crude")

BigramTokenizer <- function(x) NGramTokenizer(x, Weka_control(min = 2, max = 2))
tdm <- TermDocumentMatrix(crude, control = list(tokenize = BigramTokenizer))

inspect(tdm[340:345,1:10])

jshaw

Byobu Commands
==============

        byobu                              Screen manager


Level 0 Commands (Quick Start)
------------------------------

        <F2>                               Create a new window

jcheng5

library(shiny)
library(ggplot2)

function(input, output) {

  dataset <- reactive({
    diamonds[sample(nrow(diamonds), input$sampleSize),]
  })

  output$plot <- renderPlot({

tmiz

#!/bin/bash

OPENSSL_VERSION="1.0.1g"

curl -O http://www.openssl.org/source/openssl-$OPENSSL_VERSION.tar.gz
tar -xvzf openssl-$OPENSSL_VERSION.tar.gz
mv openssl-$OPENSSL_VERSION openssl_i386
tar -xvzf openssl-$OPENSSL_VERSION.tar.gz
mv openssl-$OPENSSL_VERSION openssl_x86_64
cd openssl_i386