Pull request from Pratool and Kiki

.gitignore

@@ -0,0 +1,3 @@
+*.pyc
+.ipynb_checkpoints*
+*.ods

README.md

@@ -1,2 +1,4 @@
-# DataScience16CTW
-This is the base repo for the "Change the World" project for Data Science at Olin College, Spring 2016.
+# Sexual Assault and Immigration
+## Misinterpreted Data and Lies About Immigrants in Sweden
+
+In an exploration of data visualization and data analysis, we hope to elucidate the meaning of the data behind the recent relation behind sexual assault and immigration in Sweden. For the article written around the data gathered in this repository, [click here!](http://skchandra.github.io/DataScience16CTW/)

committed_against.js

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+committedAgainstGroupedBar = function() {
+  var margin = {top: 20, right: 20, bottom: 30, left: 300},
+      width = 850 - margin.left - margin.right,
+      height = 900 - margin.top - margin.bottom;
+
+  var x = d3.scale.linear()
+      .range([0, width]);
+
+  var y0 = d3.scale.ordinal()
+      .rangeRoundBands([height, 0], .1);
+
+  var y1 = d3.scale.ordinal();
+
+  var color = d3.scale.ordinal()
+      .range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]);
+
+  var xAxis = d3.svg.axis()
+      .scale(x)
+      .orient("bottom");
+
+  var yAxis = d3.svg.axis()
+      .scale(y0)
+      .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 + ")");
+
+  var psv = d3.dsv("|", "text/plain");
+
+  queue()
+    .defer(psv, "https://raw.githubusercontent.com/skchandra/DataScience16CTW/master/data/crime_on_distribution_by_origin.txt")
+    .await(ready);
+
+  function ready(error, data) {
+    if (error) throw error;
+
+    var ageNames = d3.keys(data[0]).filter(function(key) { return key !== "type of crime"; });
+
+    data.forEach(function(d) {
+      d.crimes = ageNames.map(function(name) { return {name: name, value: +d[name]}; });
+    });
+
+    y0.domain(data.map(function(d) { return d["type of crime"]; }));
+    y1.domain(ageNames).rangeRoundBands([0, y0.rangeBand()]);
+    x.domain([0, d3.max(data, function(d) { return d3.max(d.crimes, function(d) { return d.value; }); })]);
+
+    svg.append("g")
+        .attr("class", "x axis")
+        .attr("transform", "translate(0," + height + ")")
+        .call(xAxis);
+
+    svg.append("g")
+        .attr("class", "y axis")
+        .call(yAxis)
+      .append("text")
+        .attr("transform", "rotate(-90)")
+        .attr("y", 6)
+        .attr("dy", ".71em")
+        .style("text-anchor", "end")
+        .text("Population");
+
+    var state = svg.selectAll(".state")
+        .data(data)
+      .enter().append("g")
+        .attr("class", "state")
+        .attr("transform", function(d) { return "translate(0," + y0(d["type of crime"]) + ")"; });
+
+    state.selectAll("rect")
+        .data(function(d) { return d.crimes; })
+      .enter().append("rect")
+        .attr("height", y1.rangeBand())
+        .attr("y", function(d) { return y1(d.name); })
+        .attr("x", 0)
+        //.attr("x", function(d) { return x(d.value); })
+        .attr("width", function(d) { return x(d.value); })
+        .style("fill", function(d) { return color(d.name); });
+
+    var legend = svg.selectAll(".legend")
+        .data(ageNames.slice().reverse())
+      .enter().append("g")
+        .attr("class", "legend")
+        .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
+
+    legend.append("rect")
+        .attr("x", width - 18)
+        .attr("width", 18)
+        .attr("height", 18)
+        .style("fill", color);
+
+    legend.append("text")
+        .attr("x", width - 24)
+        .attr("y", 9)
+        .attr("dy", ".35em")
+        .style("text-anchor", "end")
+        .text(function(d) { return d; });
+  }
+}

committed_by.js

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+committedByGroupedBar = function() {
+  var margin = {top: 20, right: 20, bottom: 30, left: 40},
+      width = 960 - margin.left - margin.right,
+      height = 500 - margin.top - margin.bottom;
+
+  var x0 = d3.scale.ordinal()
+      .rangeRoundBands([0, width], .1);
+
+  var x1 = d3.scale.ordinal();
+
+  var y = d3.scale.linear()
+      .range([height, 0]);
+
+  var color = d3.scale.ordinal()
+      .range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]);
+
+  var xAxis = d3.svg.axis()
+      .scale(x0)
+      .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 + ")");
+
+  var psv = d3.dsv("|", "text/plain");
+
+  queue()
+    .defer(psv, "https://raw.githubusercontent.com/skchandra/DataScience16CTW/master/data/crime_distribution_by_origin.txt")
+    .await(ready);
+
+  function ready(error, data) {
+    if (error) throw error;
+
+    var ageNames = d3.keys(data[0]).filter(function(key) { return key !== "type of crime"; });
+
+    data.forEach(function(d) {
+      d.crimes = ageNames.map(function(name) { return {name: name, value: +d[name]}; });
+    });
+
+    x0.domain(data.map(function(d) { return d["type of crime"]; }));
+    x1.domain(ageNames).rangeRoundBands([0, x0.rangeBand()]);
+    y.domain([0, d3.max(data, function(d) { return d3.max(d.crimes, function(d) { return d.value; }); })]);
+
+    svg.append("g")
+        .attr("class", "x axis")
+        .attr("transform", "translate(0," + height + ")")
+        .call(xAxis);
+
+    svg.append("g")
+        .attr("class", "y axis")
+        .call(yAxis)
+      .append("text")
+        .attr("transform", "rotate(-90)")
+        .attr("y", 6)
+        .attr("dy", ".71em")
+        .style("text-anchor", "end")
+        .text("Population");
+
+    var state = svg.selectAll(".state")
+        .data(data)
+      .enter().append("g")
+        .attr("class", "state")
+        .attr("transform", function(d) { return "translate(" + x0(d["type of crime"]) + ",0)"; });
+
+    state.selectAll("rect")
+        .data(function(d) { return d.crimes; })
+      .enter().append("rect")
+        .attr("width", x1.rangeBand())
+        .attr("x", function(d) { return x1(d.name); })
+        .attr("y", function(d) { return y(d.value); })
+        .attr("height", function(d) { return height - y(d.value); })
+        .style("fill", function(d) { return color(d.name); });
+
+    var legend = svg.selectAll(".legend")
+        .data(ageNames.slice().reverse())
+      .enter().append("g")
+        .attr("class", "legend")
+        .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
+
+    legend.append("rect")
+        .attr("x", width - 18)
+        .attr("width", 18)
+        .attr("height", 18)
+        .style("fill", color);
+
+    legend.append("text")
+        .attr("x", width - 24)
+        .attr("y", 9)
+        .attr("dy", ".35em")
+        .style("text-anchor", "end")
+        .text(function(d) { return d; });
+  }
+}

data/2005_immigration_data.csv

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+Citizenship	Code	2005_refugees	2005_fam_reun	2005_labour	2005_students	2005_adopted
+
+EUROPE of which		1648	8366	2085	752	86
+Bulgaria	BGR	-				
+
+Former Yugoslavia there off:		1299	2111			
+Bosnia	BIH	197	543			
+Kosovo	KSV	..				
+Serbia and Montenegro	SRB	1059	1262			
+
+Poland	POL	-	634	*	*	-
+Romania	ROU	4	301	414		-
+Russia	RUS	157	700	376	168	41
+United Kingdom	GBR		641		*	
+Turkey	TUR	76	886	86	207	
+Ukraine	UKR			547		
+Estonia	EST			*	*	
+Croatia	HRV			140		
+Lithuania	LTU			*	*	
+Belarus	BLR			88		
+Germany	DEU		829		*	
+France	FRA				*	
+Greece	GRC				*	
+Latvia	LVA				*	
+Netherlands	NLD				*	
+
+
+AFRICA of which		1991	2864	259	1155	62
+Eritrea	ERI	475	190			
+Ethiopia	ETH	37	178		60	43
+Somalia	SOM	841	770			
+Uganda	UGA	9				
+Egypt	EGY				18	
+Cameroon	CMR				329	
+Nigeria	NGA				301	
+
+
+AMERICA of which		428	2238	1175	998	11
+Chile	CHL	6	356			-
+Colombia	COL	332	103			-
+Cuba	CUB	15				
+Brazil	BRA			143	54	-
+Bolivia	BOL					10
+Guatemala	GTM					-
+Canada	CAN			241	363	
+USA	USA		522	629	213	
+Mexico	MEX				168	
+
+
+ASIA of which		3711	7733	2136	3636	645
+Afghanistan	AFG	387				
+Bangladesh	BGD	44			307	
+Philippines	PHL		373			8
+India	IND		175	760	592	38
+Iraq	IRQ	1692	1705			
+Iran	IRN	230	626	44	266	
+China	CHN	36	498	479	934	450
+Japan	JPN			152	151	
+Pakistan	PAK			35	624	
+Lebanon	LBN	97	277			
+Sri Lanka	LKA	5	85			1
+Syria	SYR	178	427	32		
+Thailand	THA		2095	329		35
+Vietnam		3	283			86
+Korea, Republic	PRK					9
+
+
+OCEANIA of which			235	316	280	
+Australia	AUS			265		
+
+
+OTHERS of which		1081	472	14	16	1
+
+
+TOTAL of which		8859	21908	5985	6837	805
+Females		4185	12511	1512	2367	583
+Males		4674	9397	4473	4470	222