2b:null 2c:["$","title",null,{"children":"Comparative Analysis Reveals Higher Fatality Rates for Tesla Vehicles in Crash Situations | Kasi Viswanath | Observable"}] 31:Tb20,fatalites = { const brushDate = vl.selectInterval("date").encodings("x"); const teslaColor = "#11dd", otherVehicleColor = "#e1dd"; const teslaDeaths = vl .markLine({ tooltip: true }) .select(brushDate) .encode( vl.x().fieldT("Date").timeUnit(timeTruncateSelected), vl.y().sum("Tesla fatalities").title("Fatalities"), vl.color().value(teslaColor) ); const otherVehicleDeaths = vl .markLine({ tooltip: true }) .encode( vl.x().fieldT("Date").timeUnit(timeTruncateSelected), vl.y().sum("Other vehicle fatalities").title("Fatalities"), vl.color().value(otherVehicleColor) ); const teslaDeathsCount = vl .markArc({ tooltip: true, radius: 40 }) .transform(vl.filter(brushDate)) .encode( vl.theta().count(), vl.fill().value(null), vl.stroke().value(teslaColor) ); const otherVehicleDeathsCount = vl .markArc({ tooltip: true, radius: 40 }) .transform(vl.filter(brushDate)) .encode( vl.theta().count(), vl.fill().value(null), vl.stroke().value(otherVehicleColor) ); const textConfig = { radius: width / 22, align: "center", dy: 50, fontWeight: "bold", fontSize: 15 }; //Adding Count const teslaDeathsCountText = vl .markText(textConfig) .transform(vl.filter(brushDate)) .encode(vl.text().sum("Tesla fatalities"), vl.color().value(teslaColor)); const otherVehicleDeathsCountText = vl .markText(textConfig) .transform(vl.filter(brushDate)) .encode( vl.text().sum("Other vehicle fatalities"), vl.color().value(otherVehicleColor) ); //Adding Label const teslaDeathsCountLabel = vl .markText({ dy: 70, fontWeight: "bold", fontSize: 15 }) .encode(vl.text().value("Tesla fatalities"), vl.color().value(teslaColor)); const otherVehicleDeathsCountLabel = vl .markText({ dy: 70, fontWeight: "bold", fontSize: 15 }) .encode( vl.text().value("Other Vehicle fatalities"), vl.color().value(otherVehicleColor) ); const contryWisedeaths = vl .markBar({ tooltip: true }) .transform(vl.filter(brushDate)) .encode(vl.y().fieldN("Country"), vl.x().sum("Deaths").title("Fatalities")) .width(900); return vl .vconcat( vl.hconcat( vl.layer(teslaDeaths, otherVehicleDeaths).width(700).height(250), vl.vconcat( vl .layer( vl.layer(teslaDeathsCount, teslaDeathsCountLabel), teslaDeathsCountText ) .height(70), vl .layer( vl.layer(otherVehicleDeathsCount, otherVehicleDeathsCountLabel), otherVehicleDeathsCountText ) .height(100) ) ), contryWisedeaths ) .data(selectedIncidents) .render(); }32:Te11,# Introduction Tesla, a leading electric vehicle manufacturer, is known for its emphasis on safety measures in their vehicles. Tesla has proven its commitment to safety by consistently achieving high scores in crash tests conducted by organizations such as the National Highway Traffic Safety Administration (NHTSA) and the European New Car Assessment Programme (Euro NCAP). Tesla's focus on safety measures through technology has contributed significantly to its success in the electric vehicle market, providing customers with peace of mind while driving # Made-up Insights(Hypothesis): - Based on [Tesla's](https://www.tesla.com/VehicleSafetyReport) safety improvements, the likelihood of fatal injuries is higher for drivers of other vehicles who are involved in accidents with Tesla vehicles, compared to Tesla drivers themselves, over a period of time [**Selected**] * **Considerations** - I will need to collect data on Tesla Incidents. - Line Chart may be useful to compare the fatalities of Tesla Vehicle with Other Vehicle - According to [Tesla](https://www.tesla.com/VehicleSafetyReport) stance on safety improvements, the ratio of fatalities to production rate is expected to remain stable over time since they are confident that the implementation of technology can effectively enhance safety measures. * **Considerations** - I will need to collect data on Tesla Incidents and Production details. - Line Chart may be useful to compare the fatalities of Tesla Vehicle with no of tesla vehicles sold till # Target Audience - Consumers considering purchasing a Tesla, automotive industry professionals, safety regulators, journalists covering the automotive industry, and investors interested in the performance and safety of Tesla's products ## Data Abstraction(What): - Dataset type: Table, Temporal - Dataset Availability: Static - Attributes: - Date - Temporal - This attribute describes the date on the incident reported - Country - Categorical - This attribute describes the country where the incident reported - Description - Categorical - This attribute describes the detailed description of the incident - Deaths - Quantitative(Sequential) - This attribute describes the total fatalities count of the incident - Tesla Death - Quantitative(Sequential) - This attribute describes the Tesla Car fatalities count of the incident - Derived Attribute: - Other Vehicle Fatalities - derived from subtracting tesla car fatalities from Total fatalities ## Task Abstraction(Why): - **T1** : Summarize and analyze the distribution of fatal injuries involving Tesla vehicles [**Summarize**,**Distribution**] - **T2** : Compare the trend of fatal injuries for drivers of other vehicles involved in accidents with Tesla vehicles versus Tesla drivers themselves over period of time [**Compare**,**Trend**] - **T3** : Summarize and analyze the distribution of fatal injuries involving Tesla vehicles by country [**Summarize**,**Distribution**] - **T4** : Summarize and analyze the distribution of fatal injuries involving Tesla vehicles by state [**Summarize**,**Distribution**] ## Idiom Abstraction(How): Abstraction for [line chart](https://observablehq.com/d/e18e0715b1fc353f#fatalites) - Mark:- Line |Attributes | Channel|Task|Rationale| |---|---|---|---| |Date|Horizantal Positioning (Separate, Order, and Align )| T2 |The date is ordinal, and the channel help to identify this order |Fatalities|Vetical Positioning (Express)| T2 |Since the fatalities is quantitative we can use express channel33:T983,function WordCloud( text, { size = (group) => group.length, // Given a grouping of words, returns the size factor for that word word = (d) => d, // Given an item of the data array, returns the word marginTop = 0, // top margin, in pixels marginRight = 0, // right margin, in pixels marginBottom = 0, // bottom margin, in pixels marginLeft = 0, // left margin, in pixels width = 640, // outer width, in pixels height = 400, // outer height, in pixels maxWords = 250, // maximum number of words to extract from the text fontFamily = "sans-serif", // font family fontScale = 15, // base font size padding = 0, // amount of padding between the words (in pixels) rotate = 0, // a constant or function to rotate the words invalidation // when this promise resolves, stop the simulation } = {} ) { const words = typeof text === "string" ? text.split(/\W+/g) : Array.from(text); const data = d3 .rollups(words, size, (w) => w) .sort(([, a], [, b]) => d3.descending(a, b)) .slice(0, maxWords) .map(([key, size]) => ({ text: word(key), size })); const svg = d3 .create("svg") .attr("viewBox", [0, 0, width, height]) .attr("width", width) .attr("font-family", fontFamily) .attr("text-anchor", "middle") .attr( "style", "max-width: 100%; height: auto; height: intrinsic;cursor:pointer" ); const g = svg .append("g") .attr("transform", `translate(${marginLeft},${marginTop})`); const cloud = d3Cloud() .size([width - marginLeft - marginRight, height - marginTop - marginBottom]) .words(data) .padding(padding) .rotate(rotate) .font(fontFamily) .fontSize((d) => Math.sqrt(d.size) * fontScale) .on("word", ({ size, x, y, rotate, text }) => { g.append("text") .attr("font-size", size) .attr("transform", `translate(${x},${y}) rotate(${rotate})`) .text(text) .on("click", (evt) => { evt.target.style = "fill:red"; if (mutable Selected.length > 0 && !evt.ctrlKey) { mutable Selected.map((d) => (d.style = "fill:black")); mutable Selected = [evt.target]; } else { mutable Selected.push(evt.target); mutable Selected = mutable Selected; } }); }); cloud.start(); invalidation && invalidation.then(() => cloud.stop()); return svg.node(); }34:[{"id":"494eb27e91bfa6d108775d4c90e849e9b6a01a4a08ecfb665a299f4354eaf12d1d68d18bd3a801c7e6f15ce66478105d29458e05c9e86185587e527a3f05834f","href":"https://static.observableusercontent.com/files/494eb27e91bfa6d108775d4c90e849e9b6a01a4a08ecfb665a299f4354eaf12d1d68d18bd3a801c7e6f15ce66478105d29458e05c9e86185587e527a3f05834f","name":"Tesla Deaths.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1678819107889.028,"size":915958}] 2f:{"id":"e18e0715b1fc353f","slug":null,"title":"Comparative Analysis Reveals Higher Fatality Rates for Tesla Vehicles in Crash 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Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":{"id":"14a0961462b84603","slug":"dataviz","title":"DataViz","owner":{"id":"b760ea566a896d7d","login":"kasivisu4","name":"Kasi Viswanath"}},"type":"notebook","body":{"title":"Comparative Analysis Reveals Higher Fatality Rates for Tesla Vehicles in Crash Situations","cells":[{"id":0,"value":"# Comparative Analysis Reveals Higher Fatality Rates for Tesla Vehicles in Crash Situations\n\nHomework 4: Extracting insights from Temporal data\n- Created by [Kasi Viswanath Vandanapu](https://vandanapuk.sites.northeastern.edu/)\n- Class [CS 7295: Special Topics Course / Information Visualization](https://johnguerra.co/classes/data_visualization_spring_2023/)\n- Professor Name : [John Alexis Guerra Gómez](https://johnguerra.co)\n- [Tweet](https://twitter.com/kasi_vandanapu/status/1636098546469576704) | [Dataset Source](https://www.tesladeaths.com/)\n\nInsights : \n- Observations indicate that Tesla has higher fatalities than other vehicles in the event of a Crash .\n- Since the first quarter of 2021, fatalities involving Tesla vehicles have risen in comparison to fatalities involving other vehicles, suggesting that Tesla's safety performance still lags behind that of other vehicles.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":641,"value":"## Word Cloud on Tesla Fatalities Incident Details\n*Note : **click** the word below to access additional information about corresponding fatalities multi-word selection => ctrl + click *","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":647,"value":"viewof ClearButton = Inputs.button(\"Clear Selection\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":364,"value":"descWordCloud = {\n ClearButton;\n return WordCloud(description, {\n width,\n height: 500,\n invalidation // a promise to stop the simulation when the cell is re-run\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":679,"value":"### Slide to drill down the Date","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":519,"value":" ${viewof timeTruncate}*${timeTruncateSelected}*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":903,"value":"## Fatalities Count","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":966,"value":"Note: Try selecting the date range in line chart (brushing enabled)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":443,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":683,"value":"### Detailed Statewise Tesla Fatalities Count in USA","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":696,"value":"viewof unitsX = Inputs.select(timeUnitOptions, {\n value: [\"year\"],\n label: \"x-axis\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":720,"value":"{\n const teslaFatalites = vl\n .markRect({ tooltip: true })\n .encode(\n vl.y().fieldN(\"State\"),\n vl.x().fieldT(\"Date\").timeUnit(unitsX),\n vl.color().fieldQ(\"Tesla fatalities\").title(\"fatalities\")\n )\n .data(selectedIncidents.filter((d) => d.Country === \"USA\"))\n .title(\"Tesla Fatalities\")\n .width(400)\n .height(400);\n\n const otherVehicleFatalities = vl\n .markRect({ tooltip: true })\n .encode(\n vl.y().fieldN(\"State\"),\n vl.x().fieldT(\"Date\").timeUnit(unitsX),\n vl.color().fieldQ(\"Other vehicle fatalities\")\n )\n .data(selectedIncidents.filter((d) => d.Country === \"USA\"))\n .title(\"Other Vehicle Fatalities\")\n .width(400)\n .height(400);\n\n return vl.hconcat(teslaFatalites, otherVehicleFatalities).render();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":674,"value":"### Selected Cases","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":421,"value":"Inputs.table(selectedIncidents)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":954,"value":"### Demo\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":50,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":27,"value":"### Data Preprocessing\n- Filter the blank rows from the raw data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":10,"value":"teslaDeaths = teslaDeathsWorkBook\n .sheet(\"Deaths\", { headers: true })\n .filter((d) => d[\"Case #\"] > 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":441,"value":"- Update the blank values with 0 and create the following derived field\n - Tesla fatalities = Deaths(total) - other Vehicle fatalities","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":67,"value":"teslaDeathswithQuarter = teslaDeaths.map((d) => {\n d[\"quarter\"] = \"Q\" + (Math.floor(d[\"Date\"].getMonth() / 3) + 1);\n d[\"Other vehicle fatalities\"] =\n d[\"Other vehicle\"] === \"-\" ? 0 : +d[\"Other vehicle\"];\n d[\"Tesla fatalities\"] = d[\"Deaths\"] - d[\"Other vehicle fatalities\"];\n return { ...d };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":624,"value":"- Remove the Stop words","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":355,"value":"description = teslaDeathswithQuarter\n .map((d) => stopword.removeStopwords(d.Description.split(\" \")).join(\" \"))\n .join(\" \")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":377,"value":"mutable Selected = []","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":405,"value":"selectedIncidents = {\n if (Selected.length === 0) {\n return teslaDeathswithQuarter;\n }\n return teslaDeathswithQuarter.filter((d) =>\n Selected.some((v) => d.Description.indexOf(v.innerHTML) != -1)\n );\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"teslaDeathsWorkBook = FileAttachment(\"Tesla Deaths.xlsx\").xlsx()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":360,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":362,"value":"d3Cloud = require(\"d3-cloud@1\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":522,"value":"viewof timeTruncate = html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":526,"value":"timeTruncateSelected = timePartOptions.slice(0, timeTruncate).join(\"\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":524,"value":"timePartOptions = [\"year\", \"quarter\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":702,"value":"timeUnitOptions = [\"year\", \"quarter\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":583,"value":"stopword = require(\"stopword\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W34","stdlib":"1","titling":"auto"}} 30:"$2f:body"