2b:null 2c:["$","title",null,{"children":"Assignment 2 - Dataviz | Northeastern University John A. Guerra Gomez classes | Observable"}] 31:T475,## Example Insights 1) Less than 50% of the crimes in Boston occur between 8am and 8pm (Daytime) (Selected insight) T1. To Compare the number of Crimes between 8am to 8pm and the rest of the day. (Compare, Distribution) This task can be visualized using a pie chart with two slices, one depicting day time and the other depicting night time. 2) The safest day of the week is Wednesday. T2. To Identify which day of the week has the lowest number of crimes. (Identify, Extremes) This task can be easily visualized by a simple horizontal bar chart, representing the days on the y-axis, and the number of reports for each day on the x-axis. 3) The most crime recorded street in Boston from 2023 to the present is Washington Street with 5000 reports. T3. To Identify the most crimes reported in a single street. (Identify, Extremes) This would require another bar chart as well, with the top 5 streets with most crime reports arranged in descending order, with the y-axis representing street names and the x-axis representing the number of crime reports.32:[{"id":"1d0e056ea14d4e4ed7d5d0e6a2f489ba157a2a8286eba7ed73f719a1dc9fa373b13786aa4c6a852e2c31e1e4b371fc247f12961b2af4e8fcbabbd07a4e92401a","href":"https://static.observableusercontent.com/files/1d0e056ea14d4e4ed7d5d0e6a2f489ba157a2a8286eba7ed73f719a1dc9fa373b13786aa4c6a852e2c31e1e4b371fc247f12961b2af4e8fcbabbd07a4e92401a","name":"Boston Crime 2023-Present.csv","type":"text/csv","lastModified":1727191059736.946,"size":25373378}] 2f:{"id":"e8e4bbed73eba53d","slug":null,"title":"Assignment 2 - Dataviz","thumbnail":"1a14706e0040f593a2bbf505c02ad4c52c970c9d3163771be2ae50aaabbc84f1","access_level":"public","create_time":"$D2024-09-24T15:12:01.749Z","update_time":"$D2024-10-08T22:55:03.054Z","view_time":null,"first_public_time":"$D2024-09-26T23:53:18.056Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"afbaa6d30585fd36","login":"nujguerra","name":"Northeastern University John A. Guerra Gomez classes","avatar_url":"https://avatars-next.observableusercontent.com/04e5ef72b3edcda1296894b5d1ecaa9c92ef5d52d69e65e4c115de5534928fe9","tier":"education_2026","bio":""},"version":468,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"c43a3832073d59e0","login":"jonathan-tarun-rajasekaran","name":"Jonathan Tarun Rajasekaran","avatar_url":"https://avatars-next.observableusercontent.com/7236be39798128ec4d4f3c6f7847b6409a07099a3c87825dcc50c3ec2860644e","tier":null,"bio":""}],"members":[{"type":"individual","id":"c43a3832073d59e0","login":"jonathan-tarun-rajasekaran","name":"Jonathan Tarun Rajasekaran","avatar_url":"https://avatars-next.observableusercontent.com/7236be39798128ec4d4f3c6f7847b6409a07099a3c87825dcc50c3ec2860644e","tier":null,"role":"editor"},{"type":"team","id":"afbaa6d30585fd36","login":"nujguerra","name":"Northeastern University John A. Guerra Gomez classes","avatar_url":"https://avatars-next.observableusercontent.com/04e5ef72b3edcda1296894b5d1ecaa9c92ef5d52d69e65e4c115de5534928fe9","tier":"education_2026","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Assignment 2 - Dataviz","cells":[{"id":0,"value":"# Assignment 2 - Dataviz\n\nThis is a data visualization project made by [Jonathan Tarun Rajasekaran](https://observablehq.com/d/8586f881717414c5) from Northeastern University, Oakland for the course CS7295 under Professor John Alexis Guerra Gomez.\n\nThis visualization is done using a dataset from data.boston.gov , it contains crime reports from the year 2023 to the present (I have downloaded the dataset on the 23rd of September). The visualization aims to compare the number of crimes that happen during the day against those that happen at night. \n\nCheck the [Contents](#contents) to guide you through this project.\n\nLink to the class: https://johnguerra.co/classes/data_visualization_fall_2024/","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"intro","database":"$undefined"},{"id":173,"value":"## Is Boston as Unsafe during the day as it is at night? If not more?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"viz","database":"$undefined"},{"id":78,"value":"chart = {\n const arc =\n vl.markArc({tooltip: true}).encode(\n vl.order().count().sort(\"descending\"),\n vl.theta().fieldQ(\"Number of Crimes\"),\n vl.color().fieldN(\"Time of Day\").scale({scheme: \"category10\"}),\n vl.text().fieldQ(\"Number of Crimes\"),\n);\n\n const textConfig = { radius: width / 10, align: \"center\", dy: 7 };\n const textName = arc\n .markText(textConfig)\n .encode(\n vl.text(),\n vl.detail().fieldQ(\"Number of Crimes\"), // Without this we will get only the totals\n vl.color().value(\"Black\")\n );\n\n const textValue = textName\n .markText({ ...textConfig, dy: -75, fontWeight: \"bold\", fontSize: 14 })\n .encode(vl.text().fieldQ(\"Number of Crimes\"));\n\n return vl\n .layer(arc, textName, textValue)\n .title(\"Crime Reports: Day vs Night (2023 - Present) [134,116 Records]\")\n .data(values)\n .render();\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":226,"value":"# Contents\n1. [ Introduction](#intro) \n2. [ Visualization](#chart) \n3. [ Example Insights](exins) \n4. [ Selected Task](#seltas) \n5. [ Real Insight](#realins) \n6. [ Description of Process](#desc) \n7. [ Data Abstraction](#dataabs)\n - 7.1 Dataset Link\n - 7.2 Dataset type\n - 7.3 Attributes\n - 7.4 Data Availability\n8. [ Data Processing](#dp)\n9. [ Users](#users)\n10. [ Task Abstraction](#taskabs)\n11. [ How Abstraction](#howabs)\n12. [ YouTube Video](#yt)\n13. [ Tweet](#x)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"contents","database":"$undefined"},{"id":38,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"exins","database":"$undefined"},{"id":69,"value":"## Selected Task\n\nThe Task that i have decided to visualize is Task 1\n\n1) Less than 50% of the crimes in Boston occur between 8am and 8pm (Daytime)\n\nT1. To Compare the number of Crimes between 8am to 8pm and the rest of the day. (Compare, Distribution)\n\nIn terms of the idiom (visualization) i would have to group up the crimes between 8am to 8pm and their total would be represented as one part of the area in the visualization to represent the distribution against the total number of crimes between 8pm to 8am (Night time).","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"celtas","database":"$undefined"},{"id":170,"value":"## Real Insight\n\nWell over 50% of the crimes are found to happen during the day time (8 am to 7:59pm).\n\nThis is a complete contrast to what i thought when i had made up the example insight. \n\nThis is an insight as it is not obvious, as a user myself i did not know this information. The user can now understand that they have to be just as careful and cautious during day time as they are during the night.\n\nThe common thinking is that crimes usually happen after dark, this is found to be very wrong as there are way more crimes happening during the day time.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"realins","database":"$undefined"},{"id":175,"value":"## Description of Process\n\nPeople often mention, \"be careful when you go out at night\", \"it is not safe to go out alone at night\". But i have never heard anyone ask me to be as careful when i go out during the day. So I decided to find out the actual statistics of it.\n\nFor this task I have chosen to represent it as a pie chart. In the pie chart i have used two attributes - \"Time of Day\" and \"Number of Crimes\".","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"desc","database":"$undefined"},{"id":76,"value":"## Data Abstraction\n\nDataset Link - https://data.boston.gov/dataset/6220d948-eae2-4e4b-8723-2dc8e67722a3/resource/b973d8cb-eeb2-4e7e-99da-c92938efc9c0/download/tmpjmzxqq_4.csv\n\nThis dataset consists of all the crimes reported in Boston from 2023 to Present.\n\nDataset Type: \nIt is a table. It has 134,116 records and 18 attributes.\n\nAttributes: \n\n1) Time of Day: (Derived) It is a derived attribute, I have grouped all the hours from 8:00 to 19:00 as daytime and the rest as night time, using the \"HOUR\" attribute from the original dataset. (Hour is an Quantitative Attribute). The derived attribute \"Time of Day\" is a Categorical attribute. (Computation steps)\n\n2) Number of Crimes: (Derived) It is a derived attribute, it is the sum of all the crime for each hour (represented by \"HOUR\" attribute in dataset) under each category. It is a quantitative atrribute.\n\n\nData Availability: \nStatic data\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"dataabs","database":"$undefined"},{"id":356,"value":"## Data Processing\n\n1) Time of Day: For this attribute, I grouped up the hours from 8 to 19 (Same as 8:00 am to 7:59 pm) as one category [(Day)](#dayCrimes) and the remaining hours (Same as 8:00 pm to 7:59 am) in the other category [(Night)](#nightCrimes), in the dataset the hours are represented by the \"HOUR\" attribute (Click on the links for steps). \n\n2) Number of Crimes: To compute this attribute, I added up the totals for each category and stored them in variables ([Total_day_crimes](#totdaycrimes) and [Total_night_crimes](totnightcrimes)). Click on links for information on how to compute the variables","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"dp","database":"$undefined"},{"id":189,"value":"## Users\n\nMade for anyone who wants to be safe while travelling to, visiting or living in Boston. It can also be used by the police department to allocate more resources when crime is more likely to happen.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"users","database":"$undefined"},{"id":195,"value":"## Task Abstraction\n\nT1: To Compare the number of crimes that occur during the daytime (From 8:00 am to 7:59 pm) with the number of crimes that occur during the night (From 8:00 pm to 7:59 am). (Compare, Distribution) ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"taskabs","database":"$undefined"},{"id":200,"value":"## How Abstraction\n\nMarks:\n\n1. Arc (Area)\n\nChannels:\n\n1. Spatial Region, represents the \"Time of Day\" attribute (Categorical), each slice in the arc represents a category.\n\n2. Color Hue, represents the \"Time of Day\" attribute (Categorical), each color represents what time of the day it is (Day or Night).\n\n3. Area, represents the \"Number of Crimes\" attribute (Quantitative)\n\n
\nArc was the best mark to use because we have only two categories, and this is the easiest way to compare two categories. Spatial region and color hue are two of the best channels for categorical attributes and hence they were chosen. Area (of each slice in the arc) is used to represent our quantitative attribute, although this channel is lower on the rankings, I thought it is the best option when comparing two quantities.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"howabs","database":"$undefined"},{"id":187,"value":"# YouTube Video\n\nClick [here](https://youtu.be/amHlty5ZRno) to check out my Youtube video explaining the insight.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"yt","database":"$undefined"},{"id":191,"value":"# Tweet\n\nClick [here](https://x.com/JonathanTa84074/status/1839866124357292112) to check out my tweet on the insight.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"x","database":"$undefined"},{"id":80,"value":"values = [\n {\"Time of Day\": \"Night (\"+ nightime + \")\", \"Number of Crimes\": 48041},\n {\"Time of Day\": \"Day (\" + daytime + \")\", \"Number of Crimes\": 86075}\n ]\n\n// if i use variables in the \"Number of Crimes\" attribute it is not displaying on my chart\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":82,"value":"daytime = \"8:00am to 7:59pm\";","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":89,"value":"nightime = \"8:00pm to 7:59am\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":394,"value":"// Adding up all the crimes in the category \"Night\"\n\ntotnightcrimes = aq.from(nightCrimes)\n.groupby(\"HOUR\")\n.count({as: \"Crimes_Reported\"})\n.rollup({ Total_Night_Crimes: d => aq.op.sum(d.Crimes_Reported) })\n.view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"// Adding up all the crime reports from the category \"Day\"\n\ntotdaycrimes = aq.from(dayCrimes)\n.groupby(\"HOUR\")\n.count({as: \"Crimes_Reported\"})\n.rollup({ Total_Day_Crimes: d => aq.op.sum(d.Crimes_Reported) })\n.view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"dayCrimes = data.filter(d => +d.HOUR >=8 && +d.HOUR <=19)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":381,"value":"nightCrimes = data.filter(d => +d.HOUR <8 || +d.HOUR >19)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"viewof maxCount = Inputs.range([0, 30000], {label: \"Max Count of Incidents\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"navio(data)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"Inputs.table(data)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"viewof df = aq.from(data)\n.groupby(\"HOUR\")\n.count({as: \"Crimes_Reported\"})\n.view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"data2 = aq.from(data)\n.groupby(\"DAY_OF_WEEK\")\n.count({as: \"Crimes_Reported\"})\n.view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"data = FileAttachment(\"Boston Crime 2023-Present.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"import {vl} from \"@vega/vega-lite-api-v5\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"import {navio} from \"@john-guerra/navio\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"import { aq } from \"@uwdata/arquero\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1"}} 30:"$2f:body"