2e:null 2f:["$","title",null,{"children":"Know Things With Data: 1. Measurement to meaning | David Eads | Observable"}] 34:T7e7,Chicago's public beaches in the summer are one of the great pleasures of the city. Read a book, have a dance party, buy a popsicle from a cart, or cool down in the water on a blazing hot day. It's a great scene, as sweet as urban life gets. A few weeks ago, I went for my customary jog and refreshing swim at a nearby beach. I left right after work around 5:45pm as I do most nights in the summer. Unfortunately for me, the waves were just a bit choppy. A red flag stood stiff in the wind, signaling that no one should go into the lake. I was hot and sweaty, my mid-aged knees were aching from the intervals I'd just run, and a lifeguard chased me out of the water as soon as I tried to wade up to my knees. This is a pattern at the beach I like: The lifeguards carry out a charade of safety, letting small children jump in the waves while chastising healthy adults for minor infractions at worst.

If you hope to ice your aching knees and ankles, you don't want to see the red flag.

If I had only waited until after 7pm when the lifeguards go off duty, I could have gotten into the lake in peace and received the powerful healing energy of the lake in my muscles and mind. Even if the waves are too big to swim, I still want to cool off my muscles and ice my ankles. Experience tells me it seems quite difficult to predict what the lake will be like without observing it. A hot windy day could have placid waters; a cool, windless day could have big choppy waves. Fortunately for us, there's a whole network of sensors in the Great Lakes that monitors lake conditions. In this guide, we'll look at how to take data from a sensor near my beach to decide if it's okay to leave at 5:30 - 6:00pm or if it would be better to wait until after 7pm (or, in extreme cases, if it would be genuinely dangerous to get in the water at all).35:[{"id":"a56bd51e9d89d219ba01f087975104e51c3485df28bf171bc67c6e4b488fc7c85c5cfc78ce2d36214c9827f6e92392066a60de30bf798e150b5698f48951785d","href":"https://static.observableusercontent.com/files/a56bd51e9d89d219ba01f087975104e51c3485df28bf171bc67c6e4b488fc7c85c5cfc78ce2d36214c9827f6e92392066a60de30bf798e150b5698f48951785d","name":"signal-2022-08-19-220337.jpeg","type":"image/jpeg","lastModified":1660967069893.698,"size":291831},{"id":"f9811b6ee382048d6ee352918a165fbf0762b240321961782f233a2b1e430e38ed7d43030354f5d6de234ac7386fb7279b755db5e9df8639200c6a917127d7f5","href":"https://static.observableusercontent.com/files/f9811b6ee382048d6ee352918a165fbf0762b240321961782f233a2b1e430e38ed7d43030354f5d6de234ac7386fb7279b755db5e9df8639200c6a917127d7f5","name":"signal-2022-08-19-220350.jpeg","type":"image/jpeg","lastModified":1660964848651.621,"size":320707},{"id":"a358de296501eda8e63343a88068b6c38154e2e5f805998f4e77c165df4941d880fcad0a1c659aa3c627b540ab4fa10918ee3f5821056e5d52ee9426e99032fd","href":"https://static.observableusercontent.com/files/a358de296501eda8e63343a88068b6c38154e2e5f805998f4e77c165df4941d880fcad0a1c659aa3c627b540ab4fa10918ee3f5821056e5d52ee9426e99032fd","name":"signal-2022-08-20-123236.jpeg","type":"image/jpeg","lastModified":1661020493767.629,"size":623352},{"id":"d14f77d8a316fafd3be9c1fc0d74c3d8ff99f94fbb39a05bb6bea570610e8a76e86818c9290f197b02793163156e49e8e5e9291b1166e86e21fa47e4a6fd2694","href":"https://static.observableusercontent.com/files/d14f77d8a316fafd3be9c1fc0d74c3d8ff99f94fbb39a05bb6bea570610e8a76e86818c9290f197b02793163156e49e8e5e9291b1166e86e21fa47e4a6fd2694","name":"signal-2022-08-20-123454.jpeg","type":"image/jpeg","lastModified":1661057232030.962,"size":354581}] 32:{"id":"347bfd394742dc8c","slug":"measurement-to-meaning-chapter1","title":"Know Things With Data: 1. Measurement to meaning","thumbnail":"c2567fb0d7c4efddc0bbe2aa24e1dd510a76d95d60f47e743e93a64824c04708","access_level":"public","create_time":"$D2022-08-20T03:03:01.761Z","update_time":"$D2022-10-04T12:12:58.491Z","view_time":null,"first_public_time":"$D2022-08-20T03:59:42.594Z","has_unpublished_edits":null,"fork":{"id":"662080314eb2cb2c","slug":"blog-post","title":"Blog Post","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"stars":0,"starred":false,"owner":{"type":"team","id":"9663adceb2af1acb","login":"eads","name":"David Eads","avatar_url":"https://avatars-next.observableusercontent.com/ed73f86cbd46170a17e3bb2a06a1939ef04e5dc379b856148b769d7ac41ab78b","tier":"starter_2024"},"version":456,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"69810cd3cf4bf30c","login":"eads","name":"David Eads","avatar_url":"https://avatars-next.observableusercontent.com/ed73f86cbd46170a17e3bb2a06a1939ef04e5dc379b856148b769d7ac41ab78b","tier":null}],"members":[{"type":"individual","id":"69810cd3cf4bf30c","login":"eads","name":"David Eads","avatar_url":"https://avatars-next.observableusercontent.com/ed73f86cbd46170a17e3bb2a06a1939ef04e5dc379b856148b769d7ac41ab78b","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":{"id":"8bba6ebb2ccd0e93","slug":"measurement-to-meaning","title":"Know Things With Data","owner":{"id":"9663adceb2af1acb","login":"eads","name":"David Eads"}},"type":"notebook","body":{"title":"Know Things With Data: 1. Measurement to meaning","cells":[{"id":0,"value":"# Know Things With Data: 1. Measurement to meaning\n\n**WORK IN PROGRESS**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"

The significant wave height was minimal this day.

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"---\n## Will the beach be closed if I arrive before the life guards go off duty?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"$34","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":113,"value":"

Normal waves: Just noticeable at about 0.35m, with a wave arriving once every two seconds.

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":150,"value":"---\n## Get the most recent measurement","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":152,"value":"The most recent measurement is available as a variable from the notebook where I process the data. We can import it using Observable's [import mechanism](https://observablehq.com/@observablehq/import).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":144,"value":"import { recentData } from \"@eads/waves-on-my-beach\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":321,"value":"We can call `Inputs.table(recentData)` to see the data in a friendly table format.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":147,"value":"Inputs.table(recentData)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"The rows of this dataset are different types of measurement: the speed of the waves, the height of the waves, the surface temperature, and possibly more. The columns represent the name of the measurement, the most recent value of that measurement, and a special score -- the _z-score_, stored in the last_z column -- that puts the value in context.\n\nThe score is the hardest to understand. It's easiest just to see it in action and unpack what's happening.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":301,"value":"## Write a sentence based on the data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":294,"value":"Now that we have the data in variable I named recentData, we can jump right in and see the magic.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":351,"value":"_Based on my own observations_, the \"significant height\" of the waves is a solid predictor of whether the beach will be open or closed, while the speed of the waves has little predictive power.\n\nSo the first step is to get the height of the waves from the collection of measurements and assign it to a variable named heightMeasurement. This is akin to finding just one row in a spreadsheet and plugging it into some calculations.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":347,"value":"// Pluck the height measurement using the \"find\" method\nheightMeasurement = recentData.find(\n (row) => row.parameter_label === \"Significant wave height (meters)\"\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":371,"value":"Code can now make decisions based on the variable defined above.\n\nWe'll use the _z-score_ I mentioned before. It's okay for the score to be a bit inscrutable at the moment. The important thing to know is that I tested it with my own eyes. Every time the score has been greater than 1, the beach is closed. Every time the score is less than 1, the beach is open. Armed with that observation, the computer can tell us is the beach is likely to be open or closed if it's during official hours.\n\nHere's our code with a live update from the beach:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":288,"value":"beachStatusText = {\n if (heightMeasurement.last_z > 1) {\n // A score of >1 means the beach is likely to be closed\n return \"The beach is probably closed.\";\n } else {\n // Otherwise, it's probably open\n return \"The beach is probably open.\";\n }\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":399,"value":"That's it! That's the magic. Everything we do from this point onwards will unpack what the score means and how we use it, then show how to write _lots_ of useful sentences based on multiple measurements. But it all goes back to the code above: Make a decision based on a value.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":391,"value":"

Who wouldn't want to swim under the moon?

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":388,"value":"## @TODO\n\n* Explain the z-score a little.\n* Build a system to write lots of different sentences based on the score.\n* Talk about importance of verification.\n* What would make the tool better?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":384,"value":"---\n# Utilities + appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":218,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 33:"$32:body"