Cited during “The Value of Process” webcast on March 20, 2013.
Examples of my work
http://alignedleft.com/work/
var numTimes = 100; | |
var r = ""; | |
var c = function() { | |
var rand = Math.random(0, 1); | |
if (rand < 0.5) { | |
return "/"; | |
} else { | |
return "\\"; |
Cited during “The Value of Process” webcast on March 20, 2013.
Examples of my work
http://alignedleft.com/work/
Update: This has moved. An updated and maintained version is here: http://alignedleft.com/resources/data-vis-jobs
I posed this question on Twitter:
If you wanted to hire a “data journalist” to support an existing reporting team with data parsing + vis, how would you find that person?
I've documented the responses here. Basically, there seems to be only one job site specifically for data journalists (so far!), and several others, depending on which audience you want to reach (e.g., more focused on development, data vis, or journalism).
Takes mbostock’s shape tweening example as a starting point, then devolves into ridiculousness. Try mousing over paths, and also clicking! Never use this for a real mapping project, except perhaps as inspiration for creating a legitimate outlines-to-Dorling transition.
Click each shape above to move it to the front.
SVG doesn’t include a concept of z-index, layering, or depth, except that elements that exist later in an SVG document are drawn “on top”. But when designing interactive pieces, we often want shapes that the user has selected / clicked / interacted with to be moved “on top,” to prevent occlusion and ensure visibility.
It’s easy to take an element and simply move it to the bottom of its parent container:
var moveToFront = function() {
this.parentNode.appendChild(this);
}
some really important information to share |
Country,Dwellings without basic facilities,Housing expenditure,Rooms per person,Household net adjusted disposable income,Household net financial wealth,Employment rate,Job security,Long-term unemployment rate,Personal earnings,Quality of support network,Educational attainment,Student skills,Years in education,Air pollution,Water quality,Consultation on rule-making,Voter turnout,Life expectancy,Self-reported health,Life satisfaction,Assault rate,Homicide rate,Employees working very long hours,Time devoted to leisure and personal care | |
Australia,1.1,20,2.3,31197,38482,72,4.4,1.06,46585,93,74,512,18.8,13,93,10.5,93,82,85,7.4,2.1,0.8,14.23,14.41 | |
Austria,1,21,1.6,29256,48125,73,3.4,1.07,43837,95,82,500,16.9,27,95,7.1,75,81.1,69,7.5,3.4,0.5,8.61,14.46 | |
Belgium,1.9,20,2.3,27811,78368,62,4.5,3.37,47276,91,71,509,18.8,21,84,4.5,89,80.5,74,7.1,6.6,1.2,4.41,15.71 | |
Brazil,6.7,21,1.4,10310,6875,67,4.8,2.17,7909,90,43,402,16.3,18,67,4,79,73.4,69,7.2,7.9,25.5,10.74,14.97 | |
Canada,0.2,22,2.5,30212,63261,72,6.6,0.9,44017,94,89,522 |
Country,Dwellings without basic facilities,Housing expenditure,Rooms per person,Household net adjusted disposable income,Household net financial wealth,Employment rate,Job security,Long-term unemployment rate,Personal earnings,Quality of support network,Educational attainment,Student skills,Years in education,Air pollution,Water quality,Consultation on rule-making,Voter turnout,Life expectancy,Self-reported health,Life satisfaction,Assault rate,Homicide rate,Employees working very long hours,Time devoted to leisure and personal care | |
Australia,1.1,20,2.3,31197,38482,72,4.4,1.06,46585,93,74,512,18.8,13,93,10.5,93,82,85,7.4,2.1,0.8,14.23,14.41 | |
Austria,1,21,1.6,29256,48125,73,3.4,1.07,43837,95,82,500,16.9,27,95,7.1,75,81.1,69,7.5,3.4,0.5,8.61,14.46 | |
Belgium,1.9,20,2.3,27811,78368,62,4.5,3.37,47276,91,71,509,18.8,21,84,4.5,89,80.5,74,7.1,6.6,1.2,4.41,15.71 | |
Brazil,6.7,21,1.4,10310,6875,67,4.8,2.17,7909,90,43,402,16.3,18,67,4,79,73.4,69,7.2,7.9,25.5,10.74,14.97 | |
Canada,0.2,22,2.5,30212,63261,72,6.6,0.9,44017,94,89,522 |
<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="utf-8"> | |
<title>SVG Resize Test</title> | |
<script type="text/javascript" src="http://d3js.org/d3.v3.js"></script> | |
<style type="text/css"> | |
body { | |
background-color: #50BCE8; |
Country,Rank,Score,ScoreReversedHighGood,UndernourishmentStandard,UnderweightStandard,EnoughtoEatScore,EnoughtoEatScoreReversed,FoodPriceLevelStandard,FoodPriceInflationStandard,AffordScore,AffordScoreReversed,NutritionDiversityStandard,SafeWaterStandard,FoodQualityScore,FoodQualityScoreReversed,DiabetesStandard,ObesityStandard,UnhealthyEatingScore,UnhealthyEatingScoreReversed,RawUndernourish,RawUnderweight,RawFoodPrice,RawInflationVolatility,RawDietDiversity,RawSafeWater,RawDiabetes,RawObesity,Code,Region,Incomegroup,Driver1,Driver2,Driver3,DriverBest,DriverBestF,Driver1a,Driver2a,Driver3a,DriverWorst,DriverWorstF | |
Netherlands,1,6,94,0,0,0,100,6,7,7,93,3,0,2,98,9,25,17,83,13.3,16.6,2.02,0.039440707,57,74.4,8.8,10.3,NLD,Europe & Central Asia,High income: OECD,100,100,100,100,Enough to Eat,7,7,17,17,Unhealthy Eating | |
France,2,8,92,0,0,0,100,14,3,9,91,10,0,5,95,12,24,18,82,4,0.9,2.03,0.082913198,45,97.8,6.3,7.7,FRA,Europe & Central Asia,High income: OECD,100,100,100,100,Enough to Eat,9,9,18,18,Unhealthy Eating | |
Sw |