| #!/bin/sh | |
| # Converts a mysqldump file into a Sqlite 3 compatible file. It also extracts the MySQL `KEY xxxxx` from the | |
| # CREATE block and create them in separate commands _after_ all the INSERTs. | |
| # Awk is choosen because it's fast and portable. You can use gawk, original awk or even the lightning fast mawk. | |
| # The mysqldump file is traversed only once. | |
| # Usage: $ ./mysql2sqlite mysqldump-opts db-name | sqlite3 database.sqlite | |
| # Example: $ ./mysql2sqlite --no-data -u root -pMySecretPassWord myDbase | sqlite3 database.sqlite |
| <script src="http://d3js.org/d3.v3.js"></script> | |
| <script type="text/javascript"> | |
| (function(){ | |
| // Probably not idiomatic javascript. | |
| this.countValue=0; | |
| updateView = function(message) { | |
| var svg = d3.select(".d3io").select("svg") |
| library(httr) | |
| library(digest) | |
| library(XML) | |
| s3_request <- function(verb, bucket, path = "/", query = NULL, | |
| content = NULL, date = NULL) { | |
| list( | |
| verb = verb, | |
| bucket = bucket, | |
| path = path, |
| # We first start by creating a way of escaping the characters that have special | |
| # meaning for html, while making sure we don't end up double-escaping at any | |
| # point. The easiest way to do this is to create an S3 class that allows us to | |
| # distinguish between regular text (that needs escaping) and html (that | |
| # doesn't). | |
| # | |
| # We then write an escape method that leaves html unchanged and escapes the | |
| # special characters (&, <, >) in ordinary text. We also add a method for lists | |
| # for convenience |
| \documentclass{article} | |
| \begin{document} | |
| <<names>>= | |
| input$firstname | |
| input$lastname | |
| @ | |
| \end{document} |
| // pre-render d3 charts at server side | |
| var d3 = require('d3') | |
| , jsdom = require('jsdom') | |
| , fs = require('fs') | |
| , htmlStub = '<html><head></head><body><div id="dataviz-container"></div><script src="js/d3.v3.min.js"></script></body></html>' | |
| jsdom.env({ | |
| features : { QuerySelector : true } | |
| , html : htmlStub | |
| , done : function(errors, window) { |
| --- | |
| title : Embedding rCharts | |
| author : Ramnath Vaidyanathan | |
| framework : minimal | |
| highlighter : prettify | |
| hitheme : twitter-bootstrap | |
| mode : standalone | |
| --- | |
| <link href='http://fonts.googleapis.com/css?family=Lora' rel='stylesheet' type='text/css'> |
| Embedding rCharts | |
| ======================================================== | |
| author: Ramnath Vaidyanathan | |
| date: 24-Dec-2013 | |
| Outline | |
| ======= | |
| This is a short demo on how to embed visualizations created using [rCharts](http://rcharts.io) in an RStudio Presentation (called RPres). |
lapply() is a really useful function but it has some limitations. For example, with lapply() there is no way to:
To overcome these problems we could create a variant of lapply() than I'm going to call fapply() (where f is for flexible). Rather than calling the supplied function with with an element of the list extract with [[, it will call it with a sub-list extracted with [.
| library(shinyIncubator) | |
| shinyServer(function(input, output, session) { | |
| output$plot <- renderPlot({ | |
| if (input$go == 0) | |
| return() | |
| # Wrap the entire expensive operation with withProgress | |
| withProgress(session, { | |
| setProgress(message = "Calculating, please wait", |
