29:null 2a:["$","title",null,{"children":"Introduction to data wrangling and analysis in JavaScript - Session 4 Follow-along notebook | Sisi's workspace | Observable"}] 2f:T452,Course materials: - Session 1: [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQfqImdbMKmUcnO3agCwH3FYXxD4JM37mXbXooApHC14LNOxsYLlKVjUWFXCyxL1Dm_ogaFreDTqg8n/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-1) - Session 2: [Slides](https://docs.google.com/presentation/d/e/2PACX-1vREbGCYcWAUeQeTdWuEmogi2iHio2anw890AY0v1fH3s1HkOfxzlm6FbrqqPl8qjnVG_U1BIKgiR0iP/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-2) - Session 3: [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQqFhwxLmgtNyLn3WSnKya2S_1LaJ45SdcHA_h4ATqAn9_TSbs9NqiLignJXuf1znm627gQuPCLleqt/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-3) - Session 4: [Slides](https://docs.google.com/presentation/d/e/2PACX-1vQYM1misfDLO2jgbXq3f8SJ48OT__1qbT3yjmbZYe7RK72Pyvlus4iOdC3jOzs0yRKjuQxuxTWM6e5X/pub?start=false&loop=false&delayms=3000) | [Follow-along notebook](https://observablehq.com/@demoteam/intro-js-session-4)30:[{"id":"486fdc7682ad42a8e2733f0d5a5845b4a3c029d05c82ae98313cb1849eb8a1bb35dac7c10e11b206c64b92a94f6ea9da450ab0bc4991c9258eb9502e7708a329","href":"https://static.observableusercontent.com/files/486fdc7682ad42a8e2733f0d5a5845b4a3c029d05c82ae98313cb1849eb8a1bb35dac7c10e11b206c64b92a94f6ea9da450ab0bc4991c9258eb9502e7708a329","name":"us_imports.csv","type":"text/csv","lastModified":1771833695434.638,"size":74347}] 2d:{"id":"37eaa1d0f0cf9b4a","slug":null,"title":"Introduction to data wrangling and analysis in JavaScript - Session 4 Follow-along notebook","thumbnail":"7c03f6bb69159092ad4f1b15ac20a9aeff354af5aa09e2135963693242833fab","access_level":"public","create_time":"$D2026-02-23T08:01:35.434Z","update_time":"$D2026-04-07T14:46:41.658Z","view_time":null,"first_public_time":"$D2026-03-03T09:19:08.906Z","fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"599673c968292864","login":"sisis-workspace","name":"Sisi's workspace","avatar_url":"https://avatars-next.observableusercontent.com/f1786244e936a9f8d148c3a816d893f84882eaa9ce32969ef3b6825677c6943f","tier":"starter_2024"},"version":332,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"aa99df3a6fb6674d","login":"sisi2","name":"Sisi","avatar_url":"https://avatars-next.observableusercontent.com/d31c20cac024f6372a84a376a83cae25107276e3c424f915425b5e7f65ee4623","tier":null}],"members":[{"type":"individual","id":"aa99df3a6fb6674d","login":"sisi2","name":"Sisi","avatar_url":"https://avatars-next.observableusercontent.com/d31c20cac024f6372a84a376a83cae25107276e3c424f915425b5e7f65ee4623","tier":null,"role":"editor"},{"type":"team","id":"599673c968292864","login":"sisis-workspace","name":"Sisi's workspace","avatar_url":"https://avatars-next.observableusercontent.com/f1786244e936a9f8d148c3a816d893f84882eaa9ce32969ef3b6825677c6943f","tier":"starter_2024","role":"viewer"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"4524f2ac73013384","slug":"data-wrangling-hw","title":"Data wrangling HW","owner":{"id":"599673c968292864","login":"sisis-workspace","name":"Sisi's workspace"}},"type":"notebook","body":{"title":"Introduction to data wrangling and analysis in JavaScript - Session 4 Follow-along notebook","cells":[{"id":0,"value":"# Introduction to data wrangling and analysis in JavaScript - Session 4 Follow-along notebook","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":11,"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":"$undefined"},{"id":12,"value":"---\n## Activity 1 - Warm up","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":13,"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":"$undefined"},{"id":14,"value":"fishing = [{river: \"San Juan\", species: \"rainbow\", lengthInches: 18.2},\n {river: \"San Juan\", species: \"brown\", lengthInches: 14.1},\n {river: \"San Juan\", species: \"brown\", lengthInches: 21.5},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 9.0},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 12.5},\n {river: \"Rio Grande\", species: \"cutthroat\", lengthInches: 10.6},\n {river: \"Rio Grande\", species: \"brown\", lengthInches: 14.5},\n {river: \"Rio Chama\", species: \"rainbow\", lengthInches: 8.5},\n {river: \"Rio Chama\", species: \"rainbow\", lengthInches: 11.5}]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"### A. Add a data table cell below to take a look at *fishing*!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":191,"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 *fishing* as a source in the Data table cell","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":269,"value":"fishingdata = fishing","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"fishingdata","database":"$undefined"},{"id":17,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":18,"value":"### B. Do the following tasks with the *fishing* array to practice skills from Sessions 1 - 3!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":20,"value":"//Group the data by species, then get an array of objects for rainbow trout.\nd3.group(fishing, d =>d.species)\n .get(\"rainbow\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":73,"value":"showMe(`d3.group(fishing, d => d.species).get(\"rainbow\")`, {\n dependencies: { fishing }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"Aside: How else could we get the same subset with filter? ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":22,"value":"// Use Array.filter to get a subset only for rainbow trout in fishing:\nfishing.filter(d => d.species == \"rainbow\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":78,"value":"showMe(`fishing.filter(d => d.species === \"rainbow\")`, {\n dependencies: { fishing }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"// Find the mean trout length by river:\nd3.rollup(\n fishing,\n v => d3.mean(v, d => d.lengthInches),\n d => d.river)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":82,"value":"showMe(\n `riverTroutSize = d3.rollup(\n fishing,\n (v) => d3.mean(v, (d) => d.lengthInches),\n (d) => d.river\n)`,\n { dependencies: { fishing } }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"// Get just the mean trout size for the San Juan River:\nd3.rollup(\n fishing,\n v => d3.mean(v, d => d.lengthInches),\n d => d.river)\n .get(\"San Juan\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":86,"value":"showMe(`riverTroutSize.get(\"San Juan\")`, { dependencies: { fishing } })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"---\n## Activity 2","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":27,"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":"$undefined"},{"id":28,"value":"// Load the us_imports.csv file (attached in this notebook):\nus_imports = FileAttachment(\"us_imports.csv\").csv({typed: true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":29,"value":"---\n### Add a data table cell below to take a look at *us_imports*!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":30,"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":"$undefined"},{"id":278,"value":"usdata = us_imports","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"usdata","database":"$undefined"},{"id":61,"value":"---\n### Math transforms!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":33,"value":"// Return an array of all values in the 'value' property of us_imports, log transformed\nus_imports.map(d => Math.log(d.value))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":91,"value":"showMe(`logValues = us_imports.map(d => Math.log(d.value))`, {\n dependencies: { us_imports }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"What if we want to add this as a new column? ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":35,"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, \n logValue:Math.log(d.value)}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":95,"value":"showMe(\n `usLogValue = us_imports.map(d => ({...d, logValue: Math.log(d.value)}))`,\n {\n dependencies: { us_imports }\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"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":"$undefined"},{"id":37,"value":"---\n## Activity 3\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":158,"value":"\nCreate a histogram of the log-transformed values (logValue) in _usLogValue_:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":294,"value":"Plot.plot({\n marks: [\n Plot.rectY(usLogValue, Plot.binX({y: \"count\"}, {x: \"logValue\"})),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":100,"value":"showMe(\n `Plot.plot({\n marks: [\n Plot.rectY(usLogValue, Plot.binX({y: \"count\"}, {x: \"logValue\"})),\n Plot.ruleY([0])\n ]\n})`,\n {\n dependencies: { us_imports }\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"Now try doing the transform _within_ Observable Plot:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":297,"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":106,"value":"showMe(\n `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})`,\n {\n dependencies: { us_imports }\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"### Use Chart cell to do the same thing:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":161,"value":"Insert a Chart cell below, choose usLogValue as a source, and create a histogram of the log-transformed values.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":43,"value":"---\n## Activity 4","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":44,"value":"## Visualization continued - Reducing, customizing, and adding interactivity!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":45,"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.\n\nIn this activity, we'll customize the chart below, then make it interactive (in multiple ways!).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":299,"value":"Plot.plot({\n marks: [\n Plot.barX(\n us_imports,\n Plot.groupY(\n { x: \"sum\" },\n {\n x: \"value\",\n y: \"Sector\",\n sort: { y: \"x\", reverse: true }\n }\n )\n )\n ],\n x: { tickFormat: \".1s\" },\n width: 900\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":329,"value":"us_imports","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":301,"value":"viewof selectedSector = Inputs.select(\n [\"All\",\"AG\",\"CH\",\"EL\",\"EP\",\"FP\",\"FW\",\"MM\",\"MS\",\"MT\",\"TE\",\"TX\",\"XX\"],\n { label: \"Which sector?\", value: \"All\" }\n)\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":303,"value":"Plot.plot({\n marks: [\n Plot.barX(\n selectedSector === \"All\"\n ? us_imports\n : us_imports.filter(d => d.Sector === selectedSector),\n Plot.groupY(\n { x: \"sum\" },\n {\n x: \"value\",\n y: \"Sector\"\n }\n )\n )\n ],\n x: { tickFormat: \".1s\" },\n width: 500\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"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":"$undefined"},{"id":264,"value":"showMe(\n `Plot.plot({\n marks: [\n Plot.barX(\n us_imports,\n Plot.groupY(\n { x: \"sum\" },\n {\n x: \"value\",\n y: \"Sector\",\n sort: { y: \"x\", reverse: true }\n }\n )\n )\n ],\n x: { tickFormat: \".1s\" },\n width: 900\n})`,\n {\n dependencies: { us_imports }\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":69,"value":"import { showMe } from \"@observablehq/show-me\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":137,"value":"import { addTooltips } from \"@mkfreeman/plot-tooltip\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W30","stdlib":"1","titling":"auto"}} 2e:"$2d:body"