2b:null 2c:["$","title",null,{"children":"More 911 emergency calls were made during weekdays than weekends; peaking at 5 PM | Harshit Gajjar | Observable"}] 31:T19c8,## Made-up Insights (Hypothesis) * Weekends tend to see an increase in the volume of 911 emergency calls, which can be attributed to people engaging in outdoor activities and social events. During weekends, people may participate in sports activities, go on hikes, or spend time in public parks. These activities can increase the likelihood of accidents or injuries, resulting in emergency calls for medical assistance. Moreover, many people also tend to consume alcohol during weekends and holidays, which can lead to incidents such as drunk driving accidents or fights. [**Selected**] * **Considerations** * I will need enough data of all the 911 emergency calls in Montgomery County, PA from 2016 to 2019. * I need to iterate all the records and sum all the emergency calls for day of the weeks and across 24 hours of the day. * In terms of the idiom (visualization), I would need to display the emergency calls for each hours of the day across each day of the week. Plotting a Heatmap of Day of the week and hours of the day for all the years (2016-2019) will help me determine the trends and patterns in 911 emergency calls. * Traffic are the most common type of emergency calls reported to the 911 system, followed by Medical Services and fires * **Considerations** * I will need enough data of all the 911 emergency calls in Montgomery County, PA from 2016 to 2019. * I need to iterate all the records and group all the calls by type of call (Traffic, Fire, Police). * In terms of the idiom (visualization), I would need to display the summation of all 911 emergency calls group by type of emergency call across all years. Plotting a barchart will help me determine the number of emergency calls of each type combined for all years (2016-2019) ## Target The target audience for the 911 emergency calls project could include a range of stakeholders involved in emergency response planning and public safety, including: * Emergency service providers: These include first responders, paramedics, firefighters, and police officers who are responsible for providing immediate assistance during emergencies. Insights derived from the project can help these providers prepare for and respond to emergencies more effectively. * Local and state government officials: These officials are responsible for allocating resources and funding to support emergency response services. The project's findings can inform policy decisions and resource allocation to improve the efficiency and effectiveness of emergency services. * Public health organizations: Public health organizations can use the project's insights to develop targeted health education campaigns and programs to prevent emergencies related to health issues, such as mental health or substance abuse. **Idiom used for What, Why, How**: [Selected Idiom](https://observablehq.com/d/de20429e0f221fd4#final_idiom) ## Data Abstraction (What) * **Dataset type:** Table, Temporal * **Attributes used:** * title * Attribute Type - Categorical * Hour * Attribute type - Ordinal * Orientation - cyclic * Day * Attribute type - Ordinal * Orientation - cyclic * **Derived Attributes:** A attributed named "Number of 911 calls" which is summation of total emergency calls for each type. * Attribute Type - Quantitative * Orientation - Sequential * **Availability:** Static * **Time frame of Data:** 2016 - 2019 * **Data Source:** [911 Emergency Calls](https://www.kaggle.com/datasets/mchirico/montcoalert) ## Task Abstraction (Why) To confirm if my selected insights is true we will examine the dataset with the help of the following tasks. * T1: Summarize the emergency calls made across all hours of the day. **[Summarize, Distribution]** * T2: Compare the emergency calls made during weekday vs weekend . **[Compare, Distribution]** * T3: Summarize the number of 911 calls across different types of emergency calls. **[Summarize, Distribution]** * T4: Summarize the emergency calls made across all hours of the day and 7 days of the week for a given type of 911 emergency service **[Summarize, Distribution]** ## Marks and Channels (How) * **Marks:** Area (HeatMap), Line (BarChart) * **Channels for HeatMap:** * **Color Saturation:** To summarize the number of 911 calls made across all 7 days of the week and 24 hours of the day . * Attribute: Number of 911 Calls * Task: T1, T2, T4 * Using **express** * **Expressiveness principle** - "Number of 911 Calls" is a quantitative attribute so it is represented with color saturation * **Effectiveness principle** - The best way to see trends and patterns in number of 911 emergency calls across different days of the week and hours of the day is to use color saturation in a Heatmap. The heatmap will help us analyze the patterns in number of calls. The saturation of color implies higher or smaller count. Darker color here denotes that number of emergency calls are high and light color denotes that number of emergency calls are low. The color saturation at a glance help us see the trends and patterns in 911 emergency calls in Montgomery County, PA. * **Horizontal Position (x-axis):** To show days of the week. * Attribute: Day * Task: T1, T4 * Using **Separate, Order, Align** * **Expressiveness & Effectiveness principle** - It is an ordinal attribute but on the x-axis, so we use position to display it, making it the most effective and expressive * **Vertical Position (y-axis):** To show hours of the day. * Attribute: hour * Task: T2, T4 * Using **Separate, Order, Align** * **Expressiveness & Effectiveness principle** - There are 24 hours in a day and we need to show the emergency call for each hour, so the position is the most expressive and effective best to distinguish them. * **Channels for BarChart:** * **Length:** To show number of 911 calls. * Attribute: Number of 911 calls * Task: T3 * Using **express** * **Expressiveness & Effectiveness principle** - It is an ordinal attribute but on the x-axis, so we use position to display it, making it the most effective and expressive * **Vertical Position (y-axis):** To show type of 911 emergency calls. * Attribute: type * Task: T3 * Using **Separate, Align** * **Expressiveness & Effectiveness principle** - There are 3 different types of emergency call, so the position is the most expressive and effective best to distinguish them.32:[{"id":"24c6eb3b169abdfbc6a7a5a9bfa8a5f51c60b2998fde7f9bc61718d04b956e6013f3c3f0c93c8809afa00314a5b1add7680a4e22fa4e236e8a1de3989d1ecc69","href":"https://static.observableusercontent.com/files/24c6eb3b169abdfbc6a7a5a9bfa8a5f51c60b2998fde7f9bc61718d04b956e6013f3c3f0c93c8809afa00314a5b1add7680a4e22fa4e236e8a1de3989d1ecc69","name":"911data.zip","type":"application/zip","lastModified":1678727601444.699,"size":25402629}] 2f:{"id":"de20429e0f221fd4","slug":null,"title":"More 911 emergency calls were made during weekdays than weekends; peaking at 5 PM","thumbnail":"1c886daad3ab2dfa8fa04c45494b755bc26e87d065dd3ce4da63566036bd90a9","access_level":"public","create_time":"$D2023-03-13T05:31:02.616Z","update_time":"$D2023-03-16T16:24:12.756Z","view_time":null,"first_public_time":"$D2023-03-13T05:31:02.616Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"666e343e9fc70af6","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":"starter_2024"},"version":595,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null}],"members":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"More 911 emergency calls were made during weekdays than weekends; peaking at 5 PM","cells":[{"id":0,"value":"# More 911 emergency calls were made during weekdays than weekends; peaking at 5 PM\nSpanning across years 2016 to 2019\n---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":579,"value":"Insight: Emergency services can be used 24x7, but people in Montgomery County, PA have used 911 services mostly on weekdays and less on weekends.\n\nread more in the notebook..","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":585,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":463,"value":"#### Click on the bar chart on left, to see the data updation on heatmap","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":335,"value":"final_idiom = {\n const selected = vl.selectSingle().encodings(\"y\");\n const colorIfSelected = vl.color().if(selected, \"limegreen\").value(\"#eee\");\n const titles = vl\n .markBar({ tooltip: true })\n .params(selected)\n .encode(\n vl.y().fieldN(\"title\").title(\"Type\"),\n vl.x().count().title(\"Number of 911 calls\"),\n colorIfSelected\n );\n\n const x = vl.x().fieldO(\"timeStamp\").timeUnit(\"day\").title(\"Day of the Week\");\n const y = vl\n .y()\n .fieldO(\"timeStamp\")\n .timeUnit(\"hours\")\n .title(\"Hour of the Day\");\n\n const square = vl\n .markRect({ tooltip: true })\n .transform(vl.filter(selected))\n .width(400)\n .height(400)\n .encode(x, y, vl.color().count().title(\"Number of 911 Calls\"));\n\n return vl.hconcat(titles, square).data(final_data).render();\n\n return titles;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":370,"value":"md`\nCreated by [Harshit Gajjar](https://observablehq.com/@5e2ba07857faed1b?tab=profile)
\nClass: [Data Visualization](https://johnguerra.co/classes/data_visualization_spring_2023/)
\nInstructor: [John Alexis Guerra Gomez](https://observablehq.com/@john-guerra)
\n[Tweet](https://twitter.com/HarshitSFHusky/status/1636402871456653312)
\n[Video](https://youtu.be/FlTmf4yLpKA)\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":374,"value":"## Introduction\nThis project focuses on analyzing the 911 emergency call data in Montgomery County, PA to obtain valuable insights into the types of emergencies reported by people and the patterns in call volume over time. The 911 emergency call system is a vital part of the public safety infrastructure as it provides immediate assistance to those in need. Through data analysis, this project aims to identify trends and patterns that can be used to enhance emergency response planning and improve the overall efficiency and effectiveness of emergency services.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":416,"value":"## Actual Insights\n* In the Montgomery county, PA 911 emergency calls were majorly made during the weekdays (Monday - Friday) as compared to Weekends (Sat- Sun). All the calls made were around a specific time, that is 08:00 to 17:00 pm.\n* On weekday, At 17:00 hours saw a high number of 911 calls made as compared to other hours of the day. On weekends, similar patterns were not observed.\n* On weekday, early in the morning (00:00 to 05:00) least number of 911 emergency calls were made.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":557,"value":"## Chosen Idioms\n* I selected the above idiom as the chosen one which gives me meaningful insights for my dataset.\n* My aim was to identify trends and patterns that can be used to enhance emergency response planning and improve the overall efficiency and effectiveness of emergency services.\n* The heatmap allows to see across the week and during the 24 hours, how are the patterns in 911 emergency calls made. It allows to present large amount of data and help spot outliers quickly\n* Having a bar chart of different types of emergency services, helps to explore the patterns and trends of calls made for a given type of emergency service across the week and 24 hours of the day.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":378,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":458,"value":"## Visual Exploration","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":456,"value":"### Idiom 1: Line Chart","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":120,"value":"viewof year = Inputs.select([\"2016\", \"2017\", \"2018\", \"2019\"], {\n value: \"2015\",\n label: \"Select Year\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":124,"value":"viewof month = Inputs.select(\n [\n \"Jan\",\n \"Feb\",\n \"March\",\n \"Apr\",\n \"May\",\n \"June\",\n \"Jul\",\n \"Aug\",\n \"Sept\",\n \"Oct\",\n \"Nov\",\n \"Dec\"\n ],\n {\n value: \"Jan\",\n label: \"Select Month\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":178,"value":"SelectDateFormat = md`\n## Drag to truncate date and time\nTruncate by: ${viewof timeTruncate}*${timeTruncateSelected}*\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":97,"value":"chart = {\n const x = vl\n .x()\n .fieldO(\"timeStamp\")\n .timeUnit(timeTruncateSelected)\n .title(\"Date-Hours\");\n return vl\n .markLine({ tooltip: true })\n .data(generateYearMonthData(year, month))\n .encode(\n x,\n vl.y().count().scale({ zero: false }).title(\"Number of 911 Calls\")\n )\n .width(1000)\n .height(600)\n .title(`Number of 911 calls made during ${month} ${year}`)\n .render();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":492,"value":"The idea behind this graph was to find trends for a given year and a month. If the number of calls were increasing or decreasing or if there were spike on any given day or hour.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":497,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":211,"value":"datePartHeader = md`## Idiom 2: Bar Parts\n\n

${viewof unitsX}

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":194,"value":"vl\n .markBar({ tooltip: true })\n .encode(\n vl.x().fieldT(\"timeStamp\").timeUnit(unitsX),\n vl.y().count(),\n vl.color().fieldN(\"title\")\n )\n .data(final_data)\n .width(800)\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":499,"value":"The idea behind this bar chart was to see calls of different types of 911 emergency calls across different date parameters. This was to see whether a given year or given month or given date see 911 calls.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":503,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":453,"value":"### Idiom 3: Area Chart","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":233,"value":"vl\n .markArea({ tooltip: true })\n .data(final_data)\n .encode(\n vl.x().fieldT(\"timeStamp\").timeUnit(\"hours\"),\n vl.y().count(),\n // vl.color().fieldO(\"timeStamp\").timeUnit(\"year\").title(\"Year\")\n vl.color().fieldN(\"title\")\n )\n .width(width * 0.85)\n .autosize({ type: \"fit\" })\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":505,"value":"The idea behind the area chart was to analyze the different types of 911 emergency calls across all the years considering all the hours of the day. The idea here is to show the number of emergency calls and the distribution of calls across different hours. The area chart also helps us to determine the number of 911 calls for each type across different hours.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":508,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":451,"value":"### Idiom 4: StreamGraph","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":307,"value":"streamgraph = {\n const selected = vl.selectSingle().encodings(\"y\");\n const colorIfSelected = vl.color().if(selected, \"limegreen\").value(\"#eee\");\n const titles = vl\n .markBar({ tooltip: true })\n .params(selected)\n .encode(\n vl.y().fieldN(\"title\").title(\"Type\"),\n vl.x().count().title(\"Number of 911 calls\"),\n colorIfSelected\n );\n\n const stream = vl\n .markArea({ tooltip: true })\n // .data(final_data)\n .transform(vl.filter(selected))\n .encode(\n vl.x().fieldT(\"timeStamp\").timeUnit(\"hours\"),\n vl.y().count().stack(\"center\").axis(null),\n vl.color().fieldN(\"title\")\n )\n .width(width * 0.6)\n .autosize({ type: \"fit\" });\n\n return vl.hconcat(titles, stream).data(final_data).render();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":512,"value":"The idea behind the streamgraph was to analyze the different types of 911 emergency calls across all the years considering all the hours of the day. The idea here is to show the distribution of calls across different hours. The streamgraph helps user understand the distribution of calls without having to worry about actual values.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":516,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":447,"value":"### Idiom 5: HeatMap","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":364,"value":"vl\n .markRect({ tooltip: true })\n .width(400)\n .height(400)\n .encode(\n vl.x().fieldO(\"timeStamp\").timeUnit(\"year\").title(\"Year\"),\n vl.y().fieldO(\"timeStamp\").timeUnit(\"month\").title(\"Month\"),\n vl.color().count().title(\"Number of 911 Calls\")\n )\n .data(final_data)\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":518,"value":"The idea behind the heatmap was to find outliers. This is used to easily determine if across different years, for any specific month, if there were lots of 911 calls for a month in a given year","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":523,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":24,"value":"## Data Preprocessing","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":564,"value":"### Importing the dataset zip file","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":65,"value":"zip = FileAttachment(\"911data.zip\").zip()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":567,"value":"### Getting the csv file name from zip","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":67,"value":"fileNames = zip.filenames","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":569,"value":"### Raw data from csv file","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":69,"value":"data = zip.file(\"911.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":571,"value":"### Final data used for idioms","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":90,"value":"final_data = cleanData(data)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":543,"value":"final_data","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":217,"value":"viewof unitsX = select({\n options: timeUnits,\n value: [\"hours\"],\n title: \"x\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":573,"value":"### Variables used for data truncation and date parts","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":168,"value":"timeParts = [\"date\", \"hours\", \"minutes\", \"seconds\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":171,"value":"timeUnits = [\n \"year\",\n \"quarter\",\n \"month\",\n \"date\",\n \"week\",\n \"day\",\n \"dayofyear\",\n \"hours\",\n \"minutes\"\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":166,"value":"viewof timeTruncate = html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":174,"value":"timeTruncateSelected = timeParts.slice(0, timeTruncate).join(\" - \")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"### We remove the data for the year 2015 and 2020 (insuffecient data)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":87,"value":"function cleanData() {\n let arr = [];\n\n data.forEach((a) => {\n let year = a[\"timeStamp\"].split(\"-\")[0];\n let title = a[\"title\"].split(\":\")[0];\n if (year !== \"2015\" && year !== \"2020\") {\n arr.push({ ...a, title });\n }\n });\n\n return arr;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":132,"value":"### Generate data for given year and month","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":146,"value":"function generateYearMonthData(year, month) {\n let arr = [];\n\n final_data.forEach((c) => {\n let tarr = c[\"timeStamp\"].split(\"-\");\n\n if (tarr[0] === year && tarr[1] === monthToNum(month)) {\n arr.push(c);\n }\n });\n\n return arr;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":152,"value":"### Mapping month name to number","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":154,"value":"function monthToNum(name) {\n switch (name.toLowerCase()) {\n case \"jan\":\n return \"01\";\n\n case \"feb\":\n return \"02\";\n\n case \"march\":\n return \"03\";\n\n case \"apr\":\n return \"04\";\n\n case \"may\":\n return \"05\";\n\n case \"june\":\n return \"06\";\n\n case \"jul\":\n return \"07\";\n\n case \"aug\":\n return \"08\";\n\n case \"sept\":\n return \"09\";\n\n case \"oct\":\n return \"10\";\n\n case \"nov\":\n return \"11\";\n\n case \"dec\":\n return \"12\";\n }\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":221,"value":"import { select } from \"@jashkenas/inputs\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}} 30:"$2f:body"