2f:T42b, 30:T40e,Plot.plot({ width, title: "Traffic Collision in Los Angeles by Area and Victim Sex", subtitle: "This dataset is between January 2015 to March 2025", marginLeft: 100, x:{ label: "Count of Victim", grid: true, nice: true }, y:{ label: "Area" }, color:{ scheme: "Dark2", legend: true, label: "Island", domain: ["F", "M", "X", null] }, marks:[ Plot.barX( traffic_data, Plot.groupY( {x: "count"}, {y:"Area Name", fill:"Victim Sex"} ) ) ], caption: htl.html`

This scatterplot encodes x = number of victims (quantitative), y = area (nominal), and color = gender (categorical). Author: Jessica Liu, Data: Traffic Collision Data from 2010 to Present.

`, })31:[{"id":"78cb18bb130cdabc8f11b7f4ff13b8f786df2008c77a8dc30daf1e0dc53a00a4fdc9f3c5a12efb3f9b8de57606ecd320263e8eb358371861472b19400d3f4c84","href":"https://static.observableusercontent.com/files/78cb18bb130cdabc8f11b7f4ff13b8f786df2008c77a8dc30daf1e0dc53a00a4fdc9f3c5a12efb3f9b8de57606ecd320263e8eb358371861472b19400d3f4c84","name":"Traffic_Collision_Data_from_2015.csv","type":"text/csv","lastModified":1759619739631.603,"size":48668747}] 2d:{"title":"Project Dataset","cells":[{"id":0,"value":"# Project Dataset","pinned":false,"hidden":false,"mode":"md"},{"id":5,"value":"**Expected Grade:** A","pinned":false,"hidden":false,"mode":"md"},{"id":16,"value":"## About This Dataset\n\nThis sections contains some background and description about the dataset\n\n### Institution that Provides the Dataset: \nLos Angeles Police Department\n\n### Dataset Description:\n\nThis dataset contains record of traffic collision incidents reported by the Los Angeles Police Department (LAPD) dating back to 2010. Due to limited file size, the dataset is cropped to 2015 - 2025. The data is transcribe from original paper reports and includes information such as date, location, and incident details. \n\n### Dataset Variable Type: ","pinned":false,"hidden":false,"mode":"md"},{"id":32,"value":"$2f","pinned":false,"hidden":false,"mode":"html"},{"id":28,"value":"## Dataset Preprocess:\n\n### Preprocess Steps: \nBefore loading the dataset into the Observable notebook, I preprocessed it by filtering the data to include only records from 2015 to 2025 and removing unnecessary columns to meet the file size requirement (<50 MB). The deleted columns include _DR Number_, _Date Reported, Area ID, Crime Code, Crime Code Description, _ and _MO Codes_.\n\n### Data\n#### Tidy- Format Data","pinned":false,"hidden":false,"mode":"md"},{"id":82,"value":"traffic_data = FileAttachment(\"Traffic_Collision_Data_from_2015.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"traffic_data","pinned":true,"hidden":false,"mode":"ojs"},{"id":57,"value":"#### Wide-Format Data\n\nI process the original dataset so it shows that each row represents one LAPD area, and the columns show the number of male, female, X, and no report sex victim. ","pinned":false,"hidden":false,"mode":"md"},{"id":99,"value":"collisions_by_area_by_sex = {\n const filtered = traffic_data.filter(\n d => {\n const s = String(d[\"Victim Sex\"] ??\"\").trim().toUpperCase();\n return s ==\"F\" | s == \"M\" | s == \"X\" | s == null\n }\n )\n const tidyCounts = d3.rollups(\n filtered,\n v => v.length,\n d => d[\"Area Name\"],\n d => d[\"Victim Sex\"] ?? \"Null\"\n ).flatMap(([area, bySex]) =>\n Array.from(bySex, ([sex, count]) => ({ area, sex: sex ?? \"Null\", count }))\n );\n const byArea = new Map();\n for (const {area, sex, count} of tidyCounts) {\n if (!byArea.has(area)) byArea.set(area, { area });\n byArea.get(area)[sex] = count ?? 0;\n }\n return Array.from(byArea.values());\n}\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":139,"value":"collisions_by_area_by_sex","pinned":true,"hidden":false,"mode":"ojs"},{"id":154,"value":"## Basic Visualization","pinned":false,"hidden":false,"mode":"md"},{"id":113,"value":"$30","pinned":true,"hidden":false,"mode":"ojs"},{"id":10,"value":"## Data Sources\n\n- Los Angeles Police Department, [Traffic Collision from 2010 to Present](https://data.lacity.org/Public-Safety/Traffic-Collision-Data-from-2010-to-Present/d5tf-ez2w/about_data), March 14, 2025","pinned":false,"hidden":false,"mode":"md"}],"files":"$W31","stdlib":"1","titling":"auto"}

Column Name	Variable Type
Date Occured	continuous (temporal)
Time Occured	continuous (temporal)
Area Name	nominal
Reporting District	discrete
Victim Age	discrete
Victim Sex	nominal
Victim Sex	nominal
Premise Description	nominal
Premise Code	discrete
Address	nominal
Cross Street	nominal
Location	continuous