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December 6, 2015 19:21
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Berlin Rent index compared with household income
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| Bezirk | Einwohner2014 | latitude | longitude | average_income | |
|---|---|---|---|---|---|
| Charlottenburg-Wilmersdorf | 326354 | 52.501803 | 13.269939 | 1675 | |
| Friedrichshain-Kreuzberg | 275691 | 52.506400 | 13.444262 | 1500 | |
| Lichtenberg | 268465 | 52.532723 | 13.499279 | 1600 | |
| Marzahn-Hellersdorf | 256173 | 52.522070 | 13.575497 | 1625 | |
| Mitte | 356506 | 52.530008 | 13.381133 | 1550 | |
| Neukölln | 325716 | 52.436025 | 13.442030 | 1425 | |
| Pankow | 384367 | 52.601588 | 13.442373 | 1700 | |
| Reinickendorf | 254000 | 52.600588 | 13.281012 | 1825 | |
| Spandau | 230419 | 52.534185 | 13.200588 | 1600 | |
| Steglitz-Zehlendorf | 299268 | 52.446071 | 13.259939 | 2000 | |
| Tempelhof | 335767 | 52.443873 | 13.389072 | 1800 | |
| Treptow-Köpenick | 249440 | 52.426025 | 13.621330 | 1675 |
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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="utf-8"> | |
| <title>Berlin Rent index compared with household income</title> | |
| <script type="text/javascript" src="//d3js.org/d3.v3.min.js"></script> | |
| <style type="text/css"> | |
| body { | |
| margin: 0; | |
| background-color: grey; | |
| font-family: Helvetica, Arial, sans-serif; | |
| } | |
| #container { | |
| width: 800px; | |
| margin-left: 248px; | |
| margin-right: auto; | |
| margin-top: 10px; | |
| margin-bottom: -1px; | |
| padding: 50px; | |
| background-color: white; | |
| border: 2px solid grey; | |
| } | |
| h1 { | |
| font-size: 24px; | |
| margin: 0; | |
| padding: 3px; | |
| color: black; | |
| } | |
| p { | |
| font-size: 14px; | |
| margin: 10px 0 10px 0; | |
| padding: 3px; | |
| color: black; | |
| } | |
| .label { | |
| font-weight: bold; | |
| font-size: 10px; | |
| width: 60px; | |
| text-anchor: middle; | |
| cursor: default; | |
| background: #ffffff; | |
| } | |
| svg { | |
| background-color: black; | |
| margin-left: 250px; | |
| margin-right: auto; | |
| margin-top: -2px; | |
| margin-bottom: 50px; | |
| padding: 50px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <div id="container"> | |
| <h1>Berlin - rent levels and household incomes per disctrict</h1> | |
| <p><b>Rent levels</b> (average monthly rent per m²) in Berlin districts (2014) compared with <b>average household net incomes</b> (red circles) per district (range: 1425 € [min] - 2000 € [max], data from 2012). <br> Sources: <a href="https://www.statistik-berlin-brandenburg.de/pms/2013/13-08-08c.pdf">statistik-berlin-brandenburg.de (2012)</a> | <a href="http://www.berlinhyp.de/fuer-immobilienkunden/gewerbliche-immobilienfinanzierung/publikationen-fuer-kunden/wohnmarktreportberlin2015.html">Wohnmarktreport Berlin 2015</a></p> | |
| </div> | |
| <script type="text/javascript"> | |
| //Rentindex data to map | |
| //var rentindex = "Unteres_Marktsegment"; | |
| //var rentindex = "Oberes_Marktsegment"; | |
| var rentindex = "Marktsegmente_Median"; | |
| //Width and height | |
| var w = 800; | |
| var h = 700; | |
| //Define map projection | |
| var projection = d3.geo.mercator() | |
| .center([ 13.4, 52.5 ]) | |
| .translate([ w/2, h/2 ]) | |
| .scale([ w/0.0129 ]); | |
| //Define path generator | |
| var path = d3.geo.path() | |
| .projection(projection); | |
| //Define quantize scale to sort data values into buckets of color | |
| //Colors by Cynthia Brewer (colorbrewer2.org), YlOrRd | |
| var color = d3.scale.quantize() | |
| .range([ "#ffffd4", "#fed98e", "#fe9929", "#d95f0e", "#993404" ]); | |
| //.range([ "#ffffe5", "#fff7bc", "#fee391", "#fec44f", "#fe9929", "#ec7014", "#cc4c02", "#993404", "#662506" ]); | |
| //Create SVG | |
| var svg = d3.select("body") | |
| .append("svg") | |
| .attr("width", w) | |
| .attr("height", h); | |
| //Load in rent data | |
| d3.csv("Mieten_BerlinBezirke_2014_csv.csv", function(data) { | |
| //Set input domain for color scale | |
| color.domain([ | |
| d3.min(data, function(d) { return +d[rentindex]; }), | |
| d3.max(data, function(d) { return +d[rentindex]; }) | |
| ]); | |
| //Load in GeoJSON data | |
| d3.json("berlin_bezirke_2.geojson", function(json) { | |
| //Merge the rentindexdata and GeoJSON into a single array | |
| // | |
| //Loop through once for each CO2 data value | |
| for (var i = 0; i < data.length; i++) { | |
| //Grab district name | |
| var dataBezirk = data[i].Bezirk; | |
| //Grab data value, and convert from string to float | |
| var dataValue = +data[i][rentindex]; | |
| //Find the corresponding district inside the GeoJSON | |
| for (var j = 0; j < json.features.length; j++) { | |
| var jsonBezirk = json.features[j].properties.bezirk; | |
| if (dataBezirk == jsonBezirk) { | |
| //Copy the data value into the GeoJSON | |
| json.features[j].properties.rentindex = dataValue; | |
| //Stop looking through the JSON | |
| break; | |
| } | |
| } | |
| } | |
| //Bind data and create one path per GeoJSON feature | |
| svg.selectAll("path") | |
| .data(json.features) | |
| .enter() | |
| .append("path") | |
| .attr("d", path) | |
| .style("fill", function(d) { | |
| //Get data value | |
| var value = d.properties.rentindex; | |
| if (value) { | |
| //If value exists… | |
| return color(value); | |
| } else { | |
| //If value is undefined… | |
| return "#ccc"; | |
| } | |
| }); | |
| // Label the districts | |
| var label = svg.selectAll("text") | |
| .data(json.features) | |
| .enter() | |
| .append("text") | |
| .attr("class", "label") | |
| .attr("transform", function(d) { return "translate(" + path.centroid(d) + ")"; }) | |
| .text(function(d) { return d.properties.bezirk + ": " + d.properties.rentindex + " €" ;} ); | |
| //Load in district data | |
| d3.csv("berlin_bezirke_latlong.csv", function(data) { | |
| //Create a circle for each district | |
| svg.selectAll("circle") | |
| .data(data) | |
| .enter() | |
| .append("circle") | |
| .attr("cx", function(d) { | |
| return projection([d.longitude, d.latitude])[0]; | |
| }) | |
| .attr("cy", function(d) { | |
| return projection([d.longitude, d.latitude])[1]; | |
| }) | |
| .attr("r", function(d) { | |
| //Use Math.sqrt to scale by area (not radius) | |
| //return Math.sqrt(+d.Einwohner2014 / w * 0.5); | |
| //return +d.average_income / w * 5; | |
| //return (Math.pow(+d.Einwohner2014 / 1000 ,2)) * 0.00015; | |
| return (Math.pow(+d.average_income / 1000 ,2)) * 5; | |
| }) | |
| //.style("fill", "blue") | |
| .style("stroke-dasharray", ("5,0")) // make the stroke dashed | |
| .style("stroke-width", 20) // set the stroke width | |
| .style("stroke-opacity", .4) // set the stroke opacity | |
| .style("stroke", "red") // set the line colour | |
| .style("fill", "none") // set the fill colour | |
| // set text to circles | |
| .append("text") | |
| .attr("class", "label") | |
| .attr("transform", function(d) { return "translate(" + path.centroid(d) + ")"; }) | |
| .text(function(d) { return +d.average_income ;} ) | |
| }); | |
| }); //End d3.json() | |
| }); //End d3.csv() | |
| </script> | |
| </body> | |
| </html> |
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| Bezirk | Mietangebote | Unteres_Marktsegment | Oberes_Marktsegment | Marktsegmente_Median | |
|---|---|---|---|---|---|
| Charlottenburg-Wilmersdorf | 7479 | 6.63 | 15.36 | 9.82 | |
| Friedrichshain-Kreuzberg | 6884 | 6.48 | 17.39 | 10.39 | |
| Lichtenberg | 2756 | 5.5 | 11.56 | 7.98 | |
| Marzahn-Hellersdorf | 3144 | 4.75 | 8.8 | 5.96 | |
| Mitte | 9446 | 5.86 | 16.52 | 10 | |
| Neukölln | 4644 | 5.53 | 15.91 | 8.5 | |
| Pankow | 8483 | 5.9 | 15.16 | 9.03 | |
| Reinickendorf | 3485 | 5.31 | 10.5 | 7.08 | |
| Spandau | 3472 | 4.87 | 9.76 | 6.75 | |
| Steglitz-Zehlendorf | 4900 | 6.11 | 13 | 8.58 | |
| Tempelhof | 5064 | 5.87 | 14.49 | 8.47 | |
| Treptow-Köpenick | 4413 | 5.5 | 11.11 | 7.4 |
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