A simple, step-by-step visualization of Dijkstra's algorithm. Adapted from a previous post by sdjacobs.
exporting_country,United States,China,Germany,France,United Kingdom,Japan,Italy,Canada,Korea,Spain,Netherlands,India,Mexico,Belgium,Russian Federation,Australia,Switzerland,Chinese Taipei,Brazil,Singapore,Poland,Ireland,Sweden,Saudi Arabia,Austria,Malaysia,Turkey,Thailand,Denmark,Indonesia,Czech Republic,Norway,Greece,Finland,Hungary,"Hong Kong, China",Portugal,Viet Nam,South Africa,Luxembourg,Israel,Slovak Republic,Romania,Philippines,Argentina,Chile,New Zealand,Bulgaria,Slovenia,Lithuania,Latvia,Estonia,Cyprus,Cambodia,Malta,Iceland,Brunei Darussalam | |
United States,1,111955.9,74435,51782.3,77745.3,89562.1,24319.9,213176.9,44279.2,21442.1,33111.1,28761.5,126533.1,15768.9,13912.6,28923.3,12717.2,24182.8,33361.2,25467.1,6441.3,44732.8,11847.8,18816.2,6383.9,19952.4,9994.3,12478.9,9168.9,11288.5,3893.6,8359.9,6815.9,5666.1,4141.2,9852.9,2673.7,4453.2,7556.4,5353.9,11168.5,1673.4,1887.7,8626.4,8175.5,9872.5,4132.5,1114.5,1297.4,778,656.4,676,734.7,843.3,635,687.3,592.7 | |
China,289963.9,1,68753.2,42191.1,39545.3,111 |
<!DOCTYPE html> | |
<meta charset="utf-8"> | |
<link rel="stylesheet" href="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css"> | |
<style> | |
html{ | |
background-color: #000; | |
} | |
body { | |
width: 1024px; |
{ | |
"name": "Overall Winner", | |
"winners": [ | |
{ | |
"name": "Winner Left 1", | |
"winners": [ | |
{"name": "Winner Left 3"}, | |
{"name": "Winner Left 4"} | |
] | |
}, |
This is a pivot chart in D3.js to visualize data from the top 1,000 male and female athletes in the 2015 CrossFit Open. You can view statistics on workouts and lifts by groups of athletes based on attributes like height, weight, age, region, or 2015 CrossFit Open rank. Using the controls on the right side, you can modify what data is displayed. The control panel is scrollable. Scroll down to access the Metric
and Filters
. Other controls are hidden in dropdown menus like Zoom
options and Order
of the groups.
Groups
refer to how many bars there are. There will be a bar for each possible combination from the groups selected. Value
and Metric
determine the height of the bars. If Sum
is seleted as a metric, bars can be stacked. Filters
exclude data if you find there are too many groups or you want to focus on a particular subset of athletes. For instance, you may only want to look at female athletes or athletes ranked in the top 100. The
if(!d3.chart) d3.chart = {}; | |
d3.chart.brush = function() { | |
var g; | |
var data; | |
var width = 600; | |
var height = 30; | |
var dispatch = d3.dispatch(chart, "filter"); | |
function chart(container) { |
if(!d3.chart) d3.chart = {}; | |
d3.chart.brush = function() { | |
var g; | |
var data; | |
var width = 600; | |
var height = 30; | |
var dispatch = d3.dispatch(chart, "filter"); | |
function chart(container) { |
if(!d3.chart) d3.chart = {}; | |
d3.chart.brush = function() { | |
var g; | |
var data; | |
var width = 600; | |
var height = 30; | |
var dispatch = d3.dispatch(chart, "filter"); | |
function chart(container) { |
var Network = module.exports = View.extend({ | |
// ... | |
/** | |
* Initialize the edge index. | |
*/ | |
_initEdges: function() { | |
this.edgeIndex = new rbush(); |
This is a simple demonstration of the use of a constraint-based force layout to represent the dependency hierarchy. Subgraphs are not repeated as they are in the console rendering. As a result, we don't have to make any special provision for dependency cycles.
The Floyd-Warshall algorithm is used to display relative path distances. Floyd-Warshall has been extended with path reconstruction as well to show the shortest path solutions between nodes.
It is possible the display could be improved further through hierarchical grouping to highlight the commonly repeated subgraphs (e.g. the subgraph including the path L->I->O->P->Q).