dpastoor

vs Questions

---

1. http://stackoverflow.com/questions/804115 (rebase vs merge).
2. https://www.atlassian.com/git/tutorials/merging-vs-rebasing (rebase vs merge)
3. https://www.atlassian.com/git/tutorials/undoing-changes/ (reset vs checkout vs revert)
4. http://stackoverflow.com/questions/2221658 (HEAD^ vs HEAD~) (See git rev-parse)
5. http://stackoverflow.com/questions/292357 (pull vs fetch)
6. http://stackoverflow.com/questions/39651 (stash vs branch)
7. http://stackoverflow.com/questions/8358035 (reset vs checkout vs revert)

dpastoor

Run go install and

• gogitlocalstats -add /path/to/folder will scan that folder and its subdirectories for repositories to scan
• gogitlocalstats -email your@email.com will generate a CLI stats graph representing the last 6 months of activity for the passed email. You can configure the default in main.go, so you can run gogitlocalstats without parameters.

Being able to pass an email as param makes it possible to scan repos for collaborators activity as well.

dpastoor

We're excited to have you attend one of our workshops! Here's a JavaScript (re)fresher to help you get up-to-speed on some features of the language we'll be using.

Let and Const

JavaScript has always had var:

var name = 'Ryan'

dpastoor

Create a Meteor app and put the client_/server_ files in a client/server directories. Also, create a public dir to save the uploaded files.

dpastoor

Update: The timings are now updated with runs from R v3.1.0.

A small note on this tweet from @KevinUshey and this tweet from @ChengHLee:

The number of rows, while is important, is only one of the factors that influence the time taken to perform the join. From my benchmarking experience, the two features that I found to influence join speed, especially on hash table based approaches (ex: dplyr), much more are:

• The number of unique groups.
• The number of columns to perform the join based on - note that this is also related to the previous point as in most cases, more the columns, more the number of unique groups.

That is, these features influence join speed in spite of having the same number of rows.

dpastoor

import os
import random
import string
import tempfile
import subprocess

def random_id(length=8):
    return ''.join(random.sample(string.ascii_letters + string.digits, length))

TEMPLATE_SERIAL = """

dpastoor

library("shiny")
library("plotly")
library("ggplot2")

shinyServer(function(input, output) {
  output$text <- renderText({
    ggiris <- qplot(Petal.Width, Sepal.Length, data=iris, color=Species)
    py <- plotly("RgraphingAPI", "ektgzomjbx")
    res <- py$ggplotly(ggiris)
    iframe <- paste("<iframe height=\"600\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"", 

dpastoor

#’ Create a Kaplan-Meier plot using ggplot2
#’
#’ @param sfit a \code{\link[survival]{survfit}} object
#’ @param returns logical: if \code{TRUE}, return an ggplot object
#’ @param xlabs x-axis label
#’ @param ylabs y-axis label
#’ @param ystratalabs The strata labels. \code{Default = levels(summary(sfit)$strata)}
#’ @param ystrataname The legend name. Default = “Strata”
#’ @param timeby numeric: control the granularity along the time-axis
#’ @param main plot title

dpastoor

#' Simplified loading and installing of packages
#'
#' This is a wrapper to \code{\link{require}} and \code{\link{install.packages}}.
#' Specifically, this will first try to load the package(s) and if not found
#' it will install then load the packages. Additionally, if the 
#' \code{update=TRUE} parameter is specified it will check the currently 
#' installed package version with what is available on CRAN (or mirror) and 
#' install the newer version.
#' 
#' @param pkgs a character vector with the names of the packages to load.

dpastoor

library(shiny)

shinyServer(function(input,output){
  
  output$distPlot<-reactivePlot(function(){
    dist<-rnorm(input$obs)
    p<-qplot(dist,binwidth=0.1)+geom_vline(xintercept=mean(dist))+theme_dpi()
    p<-p+coord_cartesian(xlim=c(-4,4))+geom_vline(xintercept=median(dist),color=I("red"))
    print(p)
  })