|
22 | 22 | </select>
|
23 | 23 | <!-- Create a div where the graph will take place -->
|
24 | 24 | <div id="map"></div>
|
| 25 | + <div id="myDiv"></div> |
| 26 | + |
| 27 | + |
25 | 28 | </body>
|
26 | 29 |
|
27 | 30 | <script>
|
|
73 | 76 |
|
74 | 77 | <!-- Choropleth Map -->
|
75 | 78 | <script>
|
76 |
| - var data = [{ |
77 |
| - type: "choroplethmapbox", locations: ['臺北市'], z: [-50], |
78 |
| - geojson: "Taiwan_geo.json" |
79 |
| - }]; |
| 79 | + function getGeometry(json, cityName) { |
| 80 | + //rtype: polygon of zone |
| 81 | + for (var i = 0; i < json["features"].length; i++) { |
| 82 | + if (json["features"][i]["id"] == cityName) { |
| 83 | + return json["features"][i]; |
| 84 | + } |
| 85 | + } |
| 86 | + } |
| 87 | + |
| 88 | + function findWinner(cityData) { |
| 89 | + //rtype: winner party name |
| 90 | + var items = cityData.map(function (i) {//map to ["親民黨", "4.34"] |
| 91 | + return [i["candidate_party"], i['ticket_percentage']]; |
| 92 | + }); |
| 93 | + items.sort(function (a, b) { |
| 94 | + return +b[1] - +a[1]; |
| 95 | + }); |
| 96 | + |
| 97 | + return items[0][0]; |
| 98 | + } |
| 99 | + |
| 100 | + d3.json("Taiwan_geo.json").then((geoJson)=>{ |
| 101 | + //read taiwan geometry data |
| 102 | + var json = geoJson |
| 103 | + d3.csv("/dataset/voteData/cleaned/president/2020/by_city.csv").then( |
| 104 | + (csvData) => { |
| 105 | + cities = Array.from(new Set(d3.map(csvData, (d) => d.city))); //use set to get unique city name and convert to array |
| 106 | + // var data = [{ |
| 107 | + // type: "choroplethmapbox", locations: [cities[0]], z: [-50], |
| 108 | + // geojson: "Taiwan_geo.json" |
| 109 | + // }]; |
| 110 | + var partyInfo = { |
| 111 | + "親民黨": { "color": "rgba(227, 104, 47, 0.8)", "winZone": {"type": "FeatureCollection","features":[]} }, |
| 112 | + "中國國民黨": { "color": "rgba(9, 0, 136, 0.8)", "winZone": {"type": "FeatureCollection","features":[]} }, |
| 113 | + "民主進步黨": { "color": "rgba(64,145,39, 0.8)", "winZone": {"type": "FeatureCollection","features":[]} }, |
| 114 | + }; |
| 115 | + |
| 116 | + for (var i = 0; i < csvData.length; i += 3) { |
| 117 | + var cityData = csvData.slice(i, i + 3); |
| 118 | + var cityName = cityData[0].city |
| 119 | + var winner = findWinner(cityData); |
| 120 | + var cityGeometry = getGeometry(geoJson, cityName) |
| 121 | + partyInfo[winner]["winZone"]['features'].push(cityGeometry) |
| 122 | + } |
| 123 | + var layers = [] |
| 124 | + for(var party in partyInfo){ |
| 125 | + var layer = { |
| 126 | + sourcetype: "geojson", |
| 127 | + source: partyInfo[party]["winZone"], |
| 128 | + type: "fill", |
| 129 | + color: partyInfo[party]['color'], |
| 130 | + } |
| 131 | + layers.push(layer) |
| 132 | + } |
| 133 | + console.log(layers[1]) |
80 | 134 |
|
81 |
| - var layout = {mapbox: {center: {lon: 121, lat: 23.5}, zoom: 7}, |
82 |
| - width: 1000, height:1000}; |
83 | 135 |
|
84 |
| - var config = {mapboxAccessToken: "pk.eyJ1IjoiYTA1MTI4IiwiYSI6ImNsY2JybmJyYTIyZzEzb2w3dGl3cXpkdXYifQ.aIV8apormocbhm8GpqbySg"}; |
| 136 | + var layout = { |
| 137 | + mapbox: { |
| 138 | + center: { lon: 121, lat: 23.5 }, |
| 139 | + zoom: 7, |
| 140 | + style: "light", |
| 141 | + layers:layers |
| 142 | + }, |
| 143 | + width: 1000, |
| 144 | + height: 1000, |
| 145 | + title: '2020' |
| 146 | + }; |
85 | 147 |
|
86 |
| - Plotly.newPlot('map', data, layout, config); |
| 148 | + var config = { |
| 149 | + mapboxAccessToken: |
| 150 | + "pk.eyJ1IjoiYTA1MTI4IiwiYSI6ImNsY2JybmJyYTIyZzEzb2w3dGl3cXpkdXYifQ.aIV8apormocbhm8GpqbySg", |
| 151 | + }; |
| 152 | + |
| 153 | + Plotly.newPlot("map", [ |
| 154 | + { |
| 155 | + type: "scattermapbox", |
| 156 | + lat: [46], |
| 157 | + lon: [-74], |
| 158 | + }, |
| 159 | + ], layout, config); |
| 160 | + } |
| 161 | + ); |
| 162 | + }); |
87 | 163 | </script>
|
88 | 164 |
|
| 165 | +<script> |
| 166 | + d3.json( |
| 167 | + "https://raw.githubusercontent.com/plotly/datasets/master/florida-red-data.json", |
| 168 | + function (redjson) { |
| 169 | + d3.json( |
| 170 | + "https://raw.githubusercontent.com/plotly/datasets/master/florida-blue-data.json", |
| 171 | + function (bluejson) { |
| 172 | + |
| 173 | + console.log(bluejson) |
| 174 | + Plotly.newPlot( |
| 175 | + "myDiv", |
| 176 | + [ |
| 177 | + { |
| 178 | + type: "scattermapbox", |
| 179 | + lat: [46], |
| 180 | + lon: [-74], |
| 181 | + }, |
| 182 | + ], |
| 183 | + { |
| 184 | + title: "Florida Counties", |
| 185 | + height: 600, |
| 186 | + width: 600, |
| 187 | + mapbox: { |
| 188 | + center: { |
| 189 | + lat: 28, |
| 190 | + lon: -84, |
| 191 | + }, |
| 192 | + style: "light", |
| 193 | + zoom: 4.8, |
| 194 | + layers: [ |
| 195 | + { |
| 196 | + sourcetype: "geojson", |
| 197 | + source: redjson, |
| 198 | + type: "fill", |
| 199 | + color: "rgba(163,22,19,0.8)", |
| 200 | + }, |
| 201 | + { |
| 202 | + sourcetype: "geojson", |
| 203 | + source: bluejson, |
| 204 | + type: "fill", |
| 205 | + color: "rgba(40,0,113,0.8)", |
| 206 | + }, |
| 207 | + ], |
| 208 | + }, |
| 209 | + }, |
| 210 | + { |
| 211 | + mapboxAccessToken: "your access token", |
| 212 | + } |
| 213 | + ); |
| 214 | + } |
| 215 | + ); |
| 216 | + } |
| 217 | + ); |
| 218 | +</script> |
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