Stacked Bar Chart

This is my first visualization with D3, using data from a project I recently did with Metis. I took the yelp corpus from 1/2 star ratings and took the twitter vocabulary for tweets my model predicted were similar to the 1/2 star ratings and plotted the top 100 words for each (excluding stopwords).

Some things I think are interesting about this are how much the words overlap/how much they don't, and how accurate the words themselves are, despite possibly not occurring in the yelp reviews at all.

Further iterations will possibly include:
- scroll bar side to side
- yelp/twitter button to show only one or the other
- hover over examples
- animations just because animations

forked from mbostock's block: Stacked Bar Chart

forked from emilyinamillion's block: Stacked Bar Chart

<!DOCTYPE html>
<meta charset="utf-8">
<style>

body {
  font: 8px sans-serif;
}

.axis path,
.axis line {
  fill: none;
  stroke: #000;
  shape-rendering: crispEdges;
}

.bar {
  fill: blue;
}

.x.axis path {
  display: none;
}

</style>
<body>

var margin = {top: 20, right: -5, bottom: 50, left: 35},
    width = 961 - margin.left - margin.right,
    height = 500 - margin.top - margin.bottom;

var x = d3.scale.ordinal()
    .rangeRoundBands([0, width], .1);

var y = d3.scale.linear()
    .rangeRound([height, 0]);

var color = d3.scale.ordinal()
    .range(["#D98880", "#A9CCE3",  ]);

var xAxis = d3.svg.axis()
    .scale(x)
    .orient("bottom");

var yAxis = d3.svg.axis()
    //.scale(y)
    .orient("left")
    .tickFormat(d3.format(".2s"));

var svg = d3.select("body").append("svg")
    .attr("width", width + margin.left + margin.right)
    .attr("height", height + margin.top + margin.bottom)
  .append("g")
    .attr("transform", "translate(" + margin.left + "," + margin.top + ")");

d3.csv("fullshebangdata4d3.csv", function(error, data) {
  if (error) throw error;

color.domain(d3.keys(data[0]).filter(function(key) { return key !== "word"; }));

data.forEach(function(d) {
    var y0 = 0;
    d.ages = color.domain().map(function(name) { return {name: name, y0: y0, y1: y0 += +d[name]}; });
    d.total = d.ages[d.ages.length - 1].y1;
  });

data.sort(function(a, b) { return b.total - a.total; });

x.domain(data.map(function(d) { return d.word; }));
  y.domain([0, d3.max(data, function(d) { return d.total; })]);

svg.append("g")
      .attr("class", "x axis")
      .attr("transform", "translate(0," + height + ")")
      .call(xAxis)
  		.selectAll("text")  
			.style("text-anchor", "end")
  		.attr("dx", "-.8em")
			 .attr("dy", "-.80em")
			.attr("transform", "rotate(-90)")
;

svg.append("g")
      .attr("class", "y axis")
      .call(yAxis)
    .append("text")
      .attr("transform", "rotate(-90)")
      .attr("y", 6)
      .attr("dy", "1.43704em")
  		.attr("font-size", "20")
      .style("text-anchor", "end")
      .text("Word Frequency");

var state = svg.selectAll(".word")
      .data(data)
    .enter().append("g")
      .attr("class", "g")
      .attr("transform", function(d) { return "translate(" + x(d.word) + ",0)"; });

state.selectAll("rect")
      .data(function(d) { return d.ages; })
    .enter().append("rect")
      .attr("width", x.rangeBand())
      .attr("y", function(d) { return y(d.y1); })
      .attr("height", function(d) { return y(d.y0) - y(d.y1); })
      .style("fill", function(d) { return color(d.name); });

var legend = svg.selectAll(".legend")
      .data(color.domain().slice().reverse())
    .enter().append("g")
      .attr("class", "legend")
      .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });

legend.append("rect")
      .attr("x", width - 59)
  		.attr("y", 9)
      .attr("width", 27)
      .attr("height", 16)
      .style("fill", color);

legend.append("text")
      .attr("x", width - 67)
      .attr("y", 18)
  		.attr("font-size", 19)
      .attr("dy", ".35em")
      .style("text-anchor", "end")
    .text(function(d) { return d; });
			
});

</script>

https://d3js.org/d3.v3.min.js