moarshy

eliocamp

# All this is implemented (plus bugfixes!) in the ggnewscale package: 
# https://github.com/eliocamp/ggnewscale
# If you have any issues, I prefer it if you send them as issues here:
# https://github.com/eliocamp/ggnewscale/issues

#' Allows to add another scale 
#' 
#' @param new_aes character with the aesthetic for which new scales will be 
#' created
#'

jagrosh

Step 1 - Make a Discord Webhook

1. Find the Discord channel in which you would like to send commits and other updates

2. In the settings for that channel, find the Webhooks option and create a new webhook. Note: Do NOT give this URL out to the public. Anyone or service can post messages to this channel, without even needing to be in the server. Keep it safe!

Step 2 - Set up the webhook on Github

1. Navigate to your repository on Github, and open the Settings

Rich-Harris

Stuff I wish I'd known sooner about service workers

I recently had several days of extremely frustrating experiences with service workers. Here are a few things I've since learned which would have made my life much easier but which isn't particularly obvious from most of the blog posts and videos I've seen.

I'll add to this list over time – suggested additions welcome in the comments or via twitter.com/rich_harris.

Use Canary for development instead of Chrome stable

Chrome 51 has some pretty wild behaviour related to console.log in service workers. Canary doesn't, and it has a load of really good service worker related stuff in devtools.

klmr

`<-` = function (body, params) {
    vars = all.vars(substitute(params))
    formals = as.pairlist(setNames(replicate(length(vars), quote(expr = )), vars))
    eval.parent(call('function', formals, substitute(body)))
}

sapply(1 : 4, x -> 2 * x)
# 2 4 6 8

mapply(x ~ y -> x + y,

james2doyle

body {
  -webkit-font-smoothing: antialiased;
  text-rendering: optimizeLegibility;
  -moz-osx-font-smoothing: grayscale;
}

.tree-view-resizer, .editor {
  ::-webkit-scrollbar {
    width: 0.5em;
    height: 0.5em;

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

dhcole

$(function(){

    var formUrl = '/* ex: https://docs.google.com/a/developmentseed.org/spreadsheet/formResponse?formkey=... */';

    // Set up map
    var m = mapbox.map('map').addLayer(mapbox.layer().id(' /* mapbox-account.id */ '));

    // Set up map ui features with point selector
    var ui = mapbox.ui().map(m).auto().pointselector(function(d) {
        // Remove all points except the most recent