29:null 2a:["$","title",null,{"children":"Introduction to data wrangling and analysis in JavaScript - Session 4 Key | Tyler Randall - Data Visualization | Observable"}] 2f:T559,All course materials: - Session 1: [Recording](https://www.youtube.com/watch?v=8vaEcca3iBk&t=60s) | [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQfqImdbMKmUcnO3agCwH3FYXxD4JM37mXbXooApHC14LNOxsYLlKVjUWFXCyxL1Dm_ogaFreDTqg8n/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-1) - Session 2: [Recording](https://www.youtube.com/watch?v=jPUFr6QktQs&t=10s) | [Slides](https://docs.google.com/presentation/d/e/2PACX-1vREbGCYcWAUeQeTdWuEmogi2iHio2anw890AY0v1fH3s1HkOfxzlm6FbrqqPl8qjnVG_U1BIKgiR0iP/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-2) - Session 3: [Recording](https://www.youtube.com/watch?v=4zIfU1rVcPU&t=1s) | [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQqFhwxLmgtNyLn3WSnKya2S_1LaJ45SdcHA_h4ATqAn9_TSbs9NqiLignJXuf1znm627gQuPCLleqt/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-3) - Session 4: [Recording](https://www.youtube.com/watch?v=Ov-NtAj6Ais&t=12s) | [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQYM1misfDLO2jgbXq3f8SJ48OT__1qbT3yjmbZYe7RK72Pyvlus4iOdC3jOzs0yRKjuQxuxTWM6e5X/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-4)30:[{"id":"486fdc7682ad42a8e2733f0d5a5845b4a3c029d05c82ae98313cb1849eb8a1bb35dac7c10e11b206c64b92a94f6ea9da450ab0bc4991c9258eb9502e7708a329","href":"https://static.observableusercontent.com/files/486fdc7682ad42a8e2733f0d5a5845b4a3c029d05c82ae98313cb1849eb8a1bb35dac7c10e11b206c64b92a94f6ea9da450ab0bc4991c9258eb9502e7708a329","name":"us_imports.csv","type":"text/csv","lastModified":1774339812950.46,"size":74347}] 2d:{"id":"d44ffcf15e6a3cb3","slug":null,"title":"Introduction to data wrangling and analysis in JavaScript - Session 4 Key","thumbnail":"75801fb52511a0cb52c0c871d9f6a2010c152f8aad3aabcde471e34c6aa94187","access_level":"public","create_time":"$D2026-03-24T08:10:12.950Z","update_time":"$D2026-03-24T08:37:20.342Z","view_time":null,"first_public_time":"$D2026-03-24T08:42:33.425Z","fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"4ed2d20a5c4515bc","login":"tyler-randall-data-visualization","name":"Tyler Randall - Data Visualization","avatar_url":"https://avatars-next.observableusercontent.com/a505c6134bc3584a60659120f7ce92c9bf46b9062292c998f8bad15db485bd3e","tier":"starter_2024"},"version":57,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"57428a96192d5cd7","login":"tyler-randall","name":"Tyler Randall","avatar_url":"https://avatars-next.observableusercontent.com/3c434fe018a031762e4025fbf40632bee15a9e04314434899fb3ebb8516bf422","tier":null}],"members":[{"type":"individual","id":"57428a96192d5cd7","login":"tyler-randall","name":"Tyler Randall","avatar_url":"https://avatars-next.observableusercontent.com/3c434fe018a031762e4025fbf40632bee15a9e04314434899fb3ebb8516bf422","tier":null,"role":"editor"},{"type":"team","id":"4ed2d20a5c4515bc","login":"tyler-randall-data-visualization","name":"Tyler Randall - Data Visualization","avatar_url":"https://avatars-next.observableusercontent.com/a505c6134bc3584a60659120f7ce92c9bf46b9062292c998f8bad15db485bd3e","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"502ff7d59b83c2d6","slug":"observable-4h-course","title":"Observable 4h Course","owner":{"id":"4ed2d20a5c4515bc","login":"tyler-randall-data-visualization","name":"Tyler Randall - Data Visualization"}},"type":"notebook","body":{"title":"Introduction to data wrangling and analysis in JavaScript - Session 4 Key","cells":[{"id":4,"value":"# Introduction to data wrangling and analysis in JavaScript - Session 4 Key","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"$2f","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":6,"value":"## Today: \n\n- Recap & warmup activity\n- Math transforms (e.g. log transform)\n- Interactive charts for exploration with Observable Plot","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"---\n## Activity 1 - Warm up","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":8,"value":"Here's an array named _fishing_. We'll recap some methods we've practiced over the past few days. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"fishing = [{river: \"San Juan\", species: \"rainbow\", lengthInches: 18.2},\n {river: \"San Juan\", species: \"brown\", lengthInches: 14.1},\n {river: \"San Juan\", species: \"brown\", lengthInches: 21.5},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 9.0},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 12.5},\n {river: \"Rio Grande\", species: \"cutthroat\", lengthInches: 10.6},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 14.5},\n {river: \"Rio Chama\", species: \"rainbow\", lengthInches: 8.5},\n {river: \"Rio Chama\", species: \"rainbow\", lengthInches: 11.5}]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"### A. Add a data table cell below to take a look at *fishing*!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":47,"value":"fishing","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":11,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":12,"value":"### B. Do the following tasks with the *fishing* array to practice skills from Sessions 1 - 3!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"//Group the data by species, then get an array of objects for rainbow trout.\nd3.group(fishing, d => d.species).get(\"rainbow\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"Aside: How else could we get the same subset with filter? ","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"fishing.filter(d => d.species === \"rainbow\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"// Find the mean trout length by river, then get the mean length for the San Juan River:\nriverTroutSize = d3.rollup(\n fishing,\n (v) => d3.mean(v, (d) => d.lengthInches),\n (d) => d.river\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"// Get just the mean trout size for the San Juan River:\nriverTroutSize.get(\"San Juan\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"---\n## Activity 2","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"The *us_imports* data contains a subset of records from the [US Trade Shift report](https://www.usitc.gov/research_and_analysis/trade_shifts.htm), and contains the value (USD) of various imports (by sector and title) for 2015 - 2019 (accessed from data.gov). ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":20,"value":"// Load the us_imports.csv file (attached in this notebook):\nus_imports = FileAttachment(\"us_imports.csv\").csv({typed: true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"---\n### Add a data table cell below to take a look at *us_imports*!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":22,"value":"- Click on the plus sign (+) in the left margin to open the Add cell menu\n- Start typing \"data table\" to find the Data table cell\n- Click to insert an empty Data table cell in your notebook\n- Select *us_imports* as a source in the Data table cell","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":23,"value":"us_imports","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":24,"value":"---\n### Math transforms!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":25,"value":"// Return an array of all values in the 'value' property of us_imports, log transformed\nus_imports.map(d => Math.log(d.value))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"What if we want to add this as a new column? ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":27,"value":"// Create a new array, usLogValue, containing all existing properties and ADDING the log transformed value as a property named logValue:\nusLogValue = us_imports.map(d => ({...d, logValue: Math.log(d.value)}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"Other [Math](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Math) operations we may want to try: \n\n- `Math.log`: natural log\n- `Math.log10`: log base 10 of a number\n- `Math.exp`: exponentiate (base _e_)\n- `Math.sqrt`: square root\n\nAnd properties: \n\n- Math.E\n- Math.PI","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":29,"value":"---\n## Activity 3\n\nCreate a histogram of the log-transformed values (logValue) in _usLogValue_:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":30,"value":"Plot.plot({\n marks: [\n Plot.rectY(usLogValue, Plot.binX({ y: \"count\" }, { x: \"logValue\" })),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"But we can also do this within Observable Plot:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":32,"value":"Plot.plot({\n marks: [\n Plot.rectY(us_imports, Plot.binX({y: \"count\"}, {x: d => Math.log(d.value)})),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"### Use Chart cell to do the same thing:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":34,"value":"Plot.plot({\n color: {\n legend: true\n },\n marks: [\n Plot.auto(usLogValue, {x: \"logValue\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":35,"value":"---\n## Activity 4","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":36,"value":"## Visualization continued - Reducing, customizing, and adding interactivity!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":37,"value":"Observable Inputs are lightweight user interface elements (sometimes called widgets) that let a user change selected values, ranges, colors, and more - and are usually connected to data or charts to make them dynamic.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":38,"value":"Sector keys: \n\n- AG: Agricultural products\n- CH: Chemicals and related products\n- EL: Electronic products\n- EP: Energy-related products\n- FP: Forest products\n- FW: Footwear\n- MM: Minerals and metals\n- MS: Miscellaneous manufactures\n- MT: Machinery\n- TE: Transportation equipment\n- TX: Textiles and apparel\n- XX: Special product classifications in HTS chapters 98 and 99","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":39,"value":"viewof pickSector = Inputs.radio(d3.map(us_imports, d => d.Sector), {label: \"Pick one\", value: \"AG\", unique: true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"viewof height = Inputs.range([400, 1200], {label: \"Chart height:\", step: 1})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"height","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":42,"value":"viewof bgColor = Inputs.color({label: \"Background color:\", value: \"#4682b4\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"Plot.plot({\n marks: [\n Plot.barX(\n us_imports,\n Plot.groupY(\n { x: \"sum\" },\n { x: \"value\", y: \"Sector\", fill: d => d.Sector === pickSector ? \"Orange\" : bgColor, sort: { y: \"x\", reverse: true }}\n )\n ),\n Plot.ruleX([0]),\n Plot.frame()\n ],\n x: { tickFormat: \"s\", label: \"Total import value ($, billions)\"},\n facet: { data: us_imports, x: \"year\" },\n fx: { tickFormat: \"\" },\n width: 900,\n height: height,\n grid: true\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W30","stdlib":"1","titling":"auto"}} 2e:"$2d:body"