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<title>Voters transfers during Czech presidential elections 2013</title>
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text-shadow: 0 1px 0 #fff;
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stroke-opacity: .2;
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<a class="navbar-brand" href="#">Voters transfers during Czech presidential elections 2013</a>
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<div style="position:fixed;top:50px;z-index:1000;">
<div class="alert alert-info" >The data is from <a href="//volebnikalkulacka.cz/volba-prezidenta-cr-2013/kalkulacka-vyzkum.php">research</a> conducted among users of voting advice application <a href="//volebnikalkulacka.cz">Volební kalkulačka</a>. It is weighted so the 1st round of the real elections and the 2nd round of the real elections match the 1st and last round of the potentional <a href="//en.wikipedia.org/wiki/Instant-runoff_voting">instant-runoff voting (alternative vote) electoral system</a>.</div>
</div>
<div style="padding-bottom:130px"></div>
<p id="chart"></p>
<p>The analysis flow:
<ol><li>get weights from <a href="//bl.ocks.org/michalskop/8155694/">this bl.ock</a> (compare)</li>
<li>extract_everything_weighted.py -> responses_weighted_info.csv</li>
<li>cal3_2.py -> sankey2.json</li>
</ol>
</p>
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calc3_2.py
import json
import csv
i = 0
data = []
with open("responses_weighted_info.csv","r") as fin:
finreader = csv.reader(fin)
for row in finreader:
if i == 0:
keys = row
else:
j = 0
val = {}
for item in row:
val[keys[j]] = item
j = j + 1
data.append(val)
i = i + 1
people = {
"zeman": {"name":"Zeman","color":"#FF0000"},
"schwarzenberg":{"name":"Schwarzenberg","color":"#880088"},
"fischer":{"name":"Fischer","color":"#0000FF"},
"dienstbier":{"name":"Dienstbier","color":"#FFA500"},
"franz":{"name":"Franz","color":"#000000"},
"roithova":{"name":"Roithová","color":"#FFFF00"},
"fischerova":{"name":"Fischerová","color":"#00AA00"},
"sobotka":{"name":"Sobotka","color":"#000088"},
"bobosikova":{"name":"Bobošíková","color":"#FFFF44"}
}
r1 = {}
r2 = {}
for jsonvar in data:
for key in people:
if (int(jsonvar[key]) == 1):
try:
r1[key]
except:
r1[key] = float(jsonvar['weight'])
else:
r1[key] = r1[key] + float(jsonvar['weight'])
if (int(jsonvar['zeman']) < int(jsonvar['schwarzenberg'])):
name = 'zeman'
else:
name = 'schwarzenberg'
try:
r2[key]
except:
r2[key] = {}
try:
r2[key][name]
except:
r2[key][name] = float(jsonvar['weight'])
else:
r2[key][name] = r2[key][name] + float(jsonvar['weight'])
out = {}
out["nodes"] = []
out["links"] = []
j = 0
toj1 = {}
toj2 = {'zeman':9, 'schwarzenberg': 10}
for item in r2:
toj1[item] = j
j = j + 1
for item in r2:
for item2 in r2[item]:
out["links"].append({"source":toj1[item],"target":toj2[item2],"value":r2[item][item2]})
node = people[item]
node['j'] = toj1[item]
out["nodes"].append(node)
print out['nodes']
for item2 in toj2:
node = people[item2]
node['j'] = toj2[item2]
print node
out["nodes"].append(node)
print out['nodes']
with open('sankey2.json', 'w') as outfile:
json.dump(out, outfile)
extract_everything_weighted.py
import json
import pickle
import collections
j = 0
weights = {}
with open("weights.csv","r") as fw:
for wrow in fw:
if (j>0):
war = wrow.split("\t")
weights[war[0].strip('"')] = {"zeman":war[1],"schwarzenberg":war[2].rstrip()}
j = j + 1
responses = []
i = 0
def one_input(jsonvar,w):
try:
jsonvar[w]
except:
return ""
else:
return jsonvar[w].encode("utf-8")
inputs = [
"input-attend",
"input-previously",
"input-change_mind",
"input-change_result",
"input-looking_for_info",
"input-info_from",
"input-info_from-other",
"input-negative_vote",
"input-sex",
"input-occupation",
"input-age",
"input-place",
]
with open("research.txt","r") as fin:
for row in fin:
ar = row.split("\t")
jsonvar = json.loads(ar[3])
newvar = {}
newvar["order"] = {}
try:
if "input-sort-bobosikova" in jsonvar:
newvar["order"]["bobosikova"] = int(jsonvar["input-sort-bobosikova"])
if "input-sort-dienstbier" in jsonvar:
newvar["order"]["dienstbier"] = int(jsonvar["input-sort-dienstbier"])
if "input-sort-fischer" in jsonvar:
newvar["order"]["fischer"] = int(jsonvar["input-sort-fischer"])
if "input-sort-fischerova" in jsonvar:
newvar["order"]["fischerova"] = int(jsonvar["input-sort-fischerova"])
if "input-sort-franz" in jsonvar:
newvar["order"]["franz"] = int(jsonvar["input-sort-franz"])
if "input-sort-roithova" in jsonvar:
newvar["order"]["roithova"] = int(jsonvar["input-sort-roithova"])
if "input-sort-schwarzenberg" in jsonvar:
newvar["order"]["schwarzenberg"] = int(jsonvar["input-sort-schwarzenberg"])
if "input-sort-sobotka" in jsonvar:
newvar["order"]["sobotka"] = int(jsonvar["input-sort-sobotka"])
if "input-sort-zeman" in jsonvar:
newvar["order"]["zeman"] = int(jsonvar["input-sort-zeman"])
cc = 0
for n in range(1, 10):
if n in newvar["order"].values():
cc = cc + 1
if (cc == 9):
minikey = min(newvar["order"], key=newvar["order"].get)
if (newvar["order"]['zeman'] < newvar["order"]['schwarzenberg']):
newvar["weight"] = weights[minikey]['zeman']
else:
newvar["weight"] = weights[minikey]['schwarzenberg']
info = {}
for iinput in inputs:
info[iinput] = one_input(jsonvar,iinput)
newvar["info"] = info
newvar["session"] = ar[0]
newvar["date"] = ar[2]
responses.append(newvar)
i = i + 1
except:
nothing = 1
print (i)
with open("responsesw", 'wb') as f:
pickle.dump(responses, f)
writer = csv.writer(open('responses_weighted_info.csv', 'wb'))
vals = []
vals.append("weight")
vals.append("session")
vals.append("date")
k = 0
for jsonvar in responses:
if (k == 0):
print sorted(jsonvar["order"])
for key in sorted(jsonvar["order"]):
vals.append(key)
for key in sorted(jsonvar["info"]):
vals.append(key)
writer.writerow(vals)
vals = []
vals.append(jsonvar["weight"])
vals.append(jsonvar["session"])
vals.append(jsonvar["date"])
for key in sorted(jsonvar["order"]):
vals.append(jsonvar["order"][key])
for key in sorted(jsonvar["info"]):
vals.append(jsonvar["info"][key])
writer.writerow(vals)
k = k + 1
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nodes.forEach(function(node) {
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var nodesByBreadth = d3.nest()
.key(function(d) { return d.x; })
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.entries(nodes)
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initializeNodeDepth();
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relaxLeftToRight(alpha);
resolveCollisions();
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return (size[1] - (nodes.length - 1) * nodePadding) / d3.sum(nodes, value);
});
nodesByBreadth.forEach(function(nodes) {
nodes.forEach(function(node, i) {
node.y = i;
node.dy = node.value * ky;
});
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links.forEach(function(link) {
link.dy = link.value * ky;
});
}
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nodesByBreadth.forEach(function(nodes, breadth) {
nodes.forEach(function(node) {
if (node.targetLinks.length) {
var y = d3.sum(node.targetLinks, weightedSource) / d3.sum(node.targetLinks, value);
node.y += (y - center(node)) * alpha;
}
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function weightedSource(link) {
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}
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var y = d3.sum(node.sourceLinks, weightedTarget) / d3.sum(node.sourceLinks, value);
node.y += (y - center(node)) * alpha;
}
});
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return center(link.target) * link.value;
}
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nodesByBreadth.forEach(function(nodes) {
var node,
dy,
y0 = 0,
n = nodes.length,
i;
nodes.sort(ascendingDepth);
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node = nodes[i];
dy = y0 - node.y;
if (dy > 0) node.y += dy;
y0 = node.y + node.dy + nodePadding;
}
dy = y0 - nodePadding - size[1];
if (dy > 0) {
y0 = node.y -= dy;
for (i = n - 2; i >= 0; --i) {
node = nodes[i];
dy = node.y + node.dy + nodePadding - y0;
if (dy > 0) node.y -= dy;
y0 = node.y;
}
}
});
}
function ascendingDepth(a, b) {
return a.y - b.y;
}
}
function computeLinkDepths() {
nodes.forEach(function(node) {
node.sourceLinks.sort(ascendingTargetDepth);
node.targetLinks.sort(ascendingSourceDepth);
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nodes.forEach(function(node) {
var sy = 0, ty = 0;
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link.sy = sy;
sy += link.dy;
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node.targetLinks.forEach(function(link) {
link.ty = ty;
ty += link.dy;
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function ascendingSourceDepth(a, b) {
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function ascendingTargetDepth(a, b) {
return a.target.y - b.target.y;
}
}
function center(node) {
return node.y + node.dy / 2;
}
function value(link) {
return link.value;
}
return sankey;
};
sankey2.json
{"nodes": [{"color": "#FF0000", "j": 0, "name": "Zeman"}, {"color": "#0000FF", "j": 1, "name": "Fischer"}, {"color": "#000088", "j": 2, "name": "Sobotka"}, {"color": "#00AA00", "j": 3, "name": "Fischerov\u00e1"}, {"color": "#880088", "j": 4, "name": "Schwarzenberg"}, {"color": "#FFA500", "j": 5, "name": "Dienstbier"}, {"color": "#FFFF00", "j": 6, "name": "Roithov\u00e1"}, {"color": "#FFFF44", "j": 7, "name": "Bobo\u0161\u00edkov\u00e1"}, {"color": "#000000", "j": 8, "name": "Franz"}, {"color": "#FF0000", "j": 9, "name": "Zeman"}, {"color": "#880088", "j": 10, "name": "Schwarzenberg"}], "links": [{"source": 0, "target": 9, "value": 2790.5571821537496}, {"source": 1, "target": 10, "value": 1047.5224641621242}, {"source": 1, "target": 9, "value": 821.216577535129}, {"source": 2, "target": 9, "value": 124.29282014560727}, {"source": 2, "target": 10, "value": 201.01950443805762}, {"source": 3, "target": 10, "value": 223.2901354058806}, {"source": 3, "target": 9, "value": 151.02618457187057}, {"source": 4, "target": 10, "value": 2683.7191693245986}, {"source": 5, "target": 10, "value": 317.3477186395925}, {"source": 5, "target": 9, "value": 1511.133203338977}, {"source": 6, "target": 9, "value": 264.6438013542945}, {"source": 6, "target": 10, "value": 293.5786808489737}, {"source": 7, "target": 9, "value": 181.63681352259297}, {"source": 7, "target": 10, "value": 81.02099977453234}, {"source": 8, "target": 9, "value": 443.06499016264905}, {"source": 8, "target": 10, "value": 337.3208891152333}]}