2e:null 2f:["$","title",null,{"children":"Which groundhog is the best prognosticator? | Max Bo | Observable"}] 34:T715,offset === "balanced" ? addTooltips( Plot.plot({ caption: "Groundhogs predictions by year, balanced comparison", width, grid: true, color: colorSkew, marks: [ Plot.dot( predictions, Plot.stackY({ x: "year", offset: "silhouette", sort: "conclusion", filter: (d) => isDisplayedGroundhog(d) && d.conclusion, anchor: "left", fill: "conclusion", href: (d) => "https://groundhog-day.com/groundhogs/" + d.slug + "/predictions", target: () => "_blank", title: describePrediction }) ) ] }) ) : addTooltips( Plot.plot({ caption: "Groundhogs predictions by year, opposed comparison", width, grid: true, color: colorSkew, y: { label: "← early spring · longer winter →", labelAnchor: "center", tickFormat: Math.abs }, marks: [ Plot.dot( predictions, Plot.stackY2({ x: "year", y: (d) => d.conclusion === "🌼 early spring" ? 1 : d.conclusion === "❄️ longer winter" ? -1 : 0, fill: "conclusion", filter: (d) => isDisplayedGroundhog(d) && d.conclusion, title: describePrediction, href: (d) => "https://groundhog-day.com/groundhogs/" + d.slug + "/predictions", target: () => "_blank" }) ), Plot.ruleY([0]) ] }) )35:T8cc,addTooltips( Plot.plot({ width, caption: `Groundhogs accuracy moving average (k = ${movingAverageWindow}) by year, overlayed on observed weather 'skew', sorted by ${sortFacetsBy}`, height: 100 * groundhogs.filter(isDisplayedGroundhog).length, facet: { data: predictions, y: "name", marginRight: 100 }, y: { grid: true }, fy: { domain: sortFacetsBy === "predictions" ? _.reverse( _.sortBy( groundhogs.filter(isDisplayedGroundhog), (groundhog) => groundhog.predictionsCount ).map((groundhog) => groundhog.name) ) : _.reverse( _.sortBy(groundhogs.filter(isDisplayedGroundhog), (groundhog) => { const window = _.take( _.reverse(groundhog.predictions), movingAverageWindow ); // accuracy in window return ( window.filter((p) => p.correct === true).length / window.filter((p) => p.correct !== undefined).length ); }) ).map((d) => d.name) }, color: colorSkew, marks: [ Plot.tickX(weather, { x: "year", strokeWidth: 7, strokeOpacity: 0.3, stroke: "skew", href: (d) => "https://groundhog-day.com/predictions/" + d.year?.getFullYear(), target: () => "_blank" }), Plot.text( predictions, Plot.windowY({ anchor: "end", basis: "mean", k: movingAverageWindow, y: "correct", x: "year", filter: isDisplayedGroundhog, title: describePrediction, text: (d) => d.correct === true ? "✅" : d.correct === false ? "❌" : "", href: (d) => "https://groundhog-day.com/groundhogs/" + d.slug + "/predictions", target: () => "_blank" }) ), Plot.lineY( predictions, Plot.windowY({ anchor: "end", basis: "mean", k: movingAverageWindow, filter: isDisplayedGroundhog, y: "correct", x: "year" }) ) ] }) )36:T6d4,groundhogs = { const response = await fetch("https://groundhog-day.com/api/v1/groundhogs"); const json = await response.json(); const groundhogs = json.groundhogs; return groundhogs .map((groundhog) => ({ ...groundhog, lat: parseFloat(groundhog.coordinates?.split(", ")[0]), lon: parseFloat(groundhog.coordinates?.split(",")[1]) })) .map((groundhog) => ({ ...groundhog, predictions: groundhog.predictions.map((prediction) => { // HERE BE DRAGONS: A lot of sparse data here, be careful with undefined and nulls causing problems // can be undefined const conclusion = prediction.shadow === 1 ? "❄️ longer winter" : prediction.shadow === 0 ? "🌼 early spring" : undefined; const year = new Date("2/2/" + prediction.year); // can be undefined const correspondingWeather = weather.find( (w) => w.year?.getTime() === year.getTime() ); // can be undefined const correct = correspondingWeather !== undefined && correspondingWeather.skew !== undefined && conclusion !== undefined ? correspondingWeather.skew === conclusion : undefined; return { ...groundhog, ...prediction, year, conclusion, correct }; }) })) .map((groundhog) => ({ ...groundhog, accuracy: Number( ( groundhog.predictions.filter((p) => p.correct === true).length / // count number of true or false groundhog.predictions.filter((p) => p.correct !== undefined).length ).toFixed(2) ) })); }37:[{"id":"502f06e41e27ff0445682878984115cb389d75adb092e897d243fddba6df67d38cf438e78c93f81d4f0316312928d9238580f3053a2aada371496c41f25829d6","href":"https://static.observableusercontent.com/files/502f06e41e27ff0445682878984115cb389d75adb092e897d243fddba6df67d38cf438e78c93f81d4f0316312928d9238580f3053a2aada371496c41f25829d6","name":"archive.csv","type":"text/csv","lastModified":1679630918489.359,"size":7549}] 32:{"id":"fa7c05413adc8647","slug":"determining-the-accuracy-of-mystical-rodent-prophecies","title":"Which groundhog is the best prognosticator?","thumbnail":"391c3d4a714a1bdac74b2af8d64add0d88094a167008558f0f50cea870894b1f","access_level":"public","create_time":"$D2023-02-02T23:42:55.863Z","update_time":"$D2023-11-26T14:23:27.178Z","view_time":null,"first_public_time":"$D2023-02-02T23:42:55.863Z","fork":false,"stars":5,"starred":false,"owner":{"type":"team","id":"cc48459e4293f942","login":"mjbo","name":"Max Bo","avatar_url":"https://avatars-next.observableusercontent.com/05ae9baba40510a4a22fa7d179f29dd4ffd85fcff859c54a31d42e166ae61dfa","tier":"starter_2024"},"version":2016,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"5bb83a6e9493ea1d","login":"mjbo","name":"Max Bo","avatar_url":"https://avatars-next.observableusercontent.com/05ae9baba40510a4a22fa7d179f29dd4ffd85fcff859c54a31d42e166ae61dfa","tier":null}],"members":[{"type":"individual","id":"5bb83a6e9493ea1d","login":"mjbo","name":"Max Bo","avatar_url":"https://avatars-next.observableusercontent.com/05ae9baba40510a4a22fa7d179f29dd4ffd85fcff859c54a31d42e166ae61dfa","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":{"id":"a5615d262872a60a","slug":"misc","title":"Misc","owner":{"id":"cc48459e4293f942","login":"mjbo","name":"Max Bo"}},"type":"notebook","body":{"title":"Which groundhog is the best prognosticator?","cells":[{"id":0,"value":"# Which groundhog is the best prognosticator?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":624,"value":"

\n ${groundhogs.filter(groundhog => groundhog.isGroundhog).map(groundhog => htl.html`

`)}\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":49,"value":"Given the recent release of [GROUNDHOG-DAY.com](https://groundhog-day.com/), \"the leading data source for North America’s prophetic prognosticators\", it's a perfect opportunity for, you guessed it, datavis. \n\nFor those who haven't seen Groundhog Day (1993), a brief refresher: \n\n> [According to tradition](https://groundhog-day.com/about), if a groundhog sees its shadow on February 2nd, it means six more weeks of winter. No shadow means an early spring.\n\nThis seems like an easily verifiable prediction. Are there [superforcasting](https://en.wikipedia.org/wiki/Superforecaster) groundhogs in our midst?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":656,"value":"## The \"groundhogs\"","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":57,"value":"addTooltips(\n Plot.plot({\n width,\n projection,\n marks: [\n Plot.geo(land50),\n Plot.geo(nation),\n Plot.geo(statesMesh, { strokeOpacity: 0.5 }),\n Plot.image(groundhogs.filter(isDisplayedGroundhog), {\n x: \"lon\",\n y: \"lat\",\n // width: 70,\n preserveAspectRatio: \"xMidYMin slice\",\n r: 25,\n src: \"image\",\n href: (d) => \"https://groundhog-day.com/groundhogs/\" + d.slug,\n target: () => \"_blank\",\n title: describeGroundhog\n })\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1861,"value":"Inputs.table(displayedGroundhogs, {\n columns: [\"image\", \"name\", \"type\", \"city\", \"predictionsCount\"],\n height: 600,\n format: {\n name: (name, i) =>\n html`${name}`,\n image: (image, i) =>\n html`

`,\n\n city: (city, i) => {\n const { region, country } = displayedGroundhogs[i];\n return html`${city}, ${region}, ${country}`;\n }\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":517,"value":"The classification of \"groundhog\" in this dataset is somewhat relaxed:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":496,"value":"addTooltips(\n Plot.plot({\n caption: \"Frequency of type of 'groundhog' seen in dataset\",\n x: {\n tickRotate: 30\n },\n marginBottom: 100,\n marks: [\n Plot.barY(\n groundhogs,\n Plot.groupX(\n { y: \"count\" },\n {\n x: \"type\",\n fill: isDisplayedGroundhog,\n title: describeGroundhog,\n sort: { x: \"y\", reverse: true, limit: 10 },\n href: (d) => \"https://groundhog-day.com/groundhogs/\" + d.slug,\n target: () => \"_blank\"\n }\n )\n ),\n Plot.ruleX([0])\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":686,"value":"We might want to limit our analysis:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":682,"value":"viewof filter = Inputs.radio(Object.values(FILTER_TYPE), {\n label: \"Filter data to:\",\n value: Object.values(FILTER_TYPE)[0]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":751,"value":"## The predictions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":468,"value":"addTooltips(\n Plot.plot({\n caption:\n \"Each groundhogs predictions by year, sorted by total number of made predictions\",\n width,\n grid: true,\n marginLeft: 150,\n color: colorSkew,\n y: {\n domain: _.reverse(\n _.sortBy(\n groundhogs.filter(isDisplayedGroundhog),\n (d) => d.predictionsCount\n ).map((d) => d.name)\n )\n },\n marks: [\n Plot.dot(predictions, {\n r: 5,\n y: \"name\",\n x: \"year\",\n fill: \"conclusion\",\n title: describePrediction,\n href: (d) =>\n \"https://groundhog-day.com/groundhogs/\" + d.slug + \"/predictions\",\n target: () => \"_blank\"\n })\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":601,"value":"viewof offset = Inputs.radio([\"balanced\", \"oppositional\"], {\n label: \"Offset:\",\n value: \"balanced\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":456,"value":"addTooltips(\n Plot.plot({\n width,\n caption: \"Proportion of each prediction type by year\",\n color: colorSkew,\n x: {\n percent: true\n },\n y: {\n label: \"↑ Frequency (%)\"\n },\n fx: {\n ticks: null\n },\n facet: {\n data: predictions,\n x: \"year\"\n },\n marks: [\n Plot.barY(\n predictions,\n Plot.stackY(\n Plot.groupZ(\n { y: \"proportion-facet\" },\n {\n fill: \"conclusion\",\n title: (d) => d.year.toLocaleDateString() + \" \" + d.conclusion,\n filter: (d) => isDisplayedGroundhog(d) && d.conclusion,\n href: (d) =>\n \"https://groundhog-day.com/predictions/\" + d.year.getFullYear(),\n target: () => \"_blank\"\n }\n )\n )\n ),\n Plot.ruleY([0.5])\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":753,"value":"## The accuracy\n\nHere is a plot of whether spring came early or there was more winter (the 'skew') to go: ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":828,"value":"Plot.plot({\n width,\n grid: true,\n caption: \"Observed weather 'skew' by year\",\n color: colorSkew,\n marks: [\n Plot.text(weather, {\n x: \"year\",\n text: \"symbol\",\n fill: \"skew\",\n href: (d) =>\n \"https://groundhog-day.com/predictions/\" + d.year?.getFullYear(),\n target: () => \"_blank\"\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1803,"value":"Let's overlay the status of whether the predictions were right or wrong over the top of the observed weather:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":887,"value":"addTooltips(\n Plot.plot({\n width,\n caption:\n \"Groundhog prediction correctness by year, overlayed on observed weather 'skew', sorted by prediction accuracy\",\n marginLeft: 150,\n color: colorSkew,\n y: {\n domain: _.reverse(\n _.sortBy(\n groundhogs.filter(isDisplayedGroundhog),\n (d) => d.accuracy\n ).map((d) => d.name)\n )\n },\n marks: [\n Plot.tickX(weather, {\n x: \"year\",\n strokeWidth: 7,\n stroke: \"skew\",\n strokeOpacity: 0.3,\n href: (d) =>\n \"https://groundhog-day.com/predictions/\" + d.year?.getFullYear(),\n target: () => \"_blank\"\n }),\n Plot.text(predictions, {\n y: \"name\",\n x: \"year\",\n title: describePrediction,\n text: (d) =>\n d.correct === true ? \"✅\" : d.correct === false ? \"❌\" : \"\",\n href: (d) =>\n \"https://groundhog-day.com/groundhogs/\" + d.slug + \"/predictions\",\n target: () => \"_blank\"\n })\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":947,"value":"sortedAccuracy = displayedGroundhogs","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"sortedAccuracy","database":"$undefined"},{"id":1399,"value":"viewof minimumPredictions = Inputs.range([0, groundhogDaysWithResults.length], {\n label: \"Minimum predictions:\",\n value: 10,\n step: 1\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1647,"value":"addTooltips(\n Plot.plot({\n caption:\n \"Groundhog with highest accuracy, having made some minimum number of predictions\",\n x: {\n label: \"Minimum predictions →\"\n },\n marginTop: 50,\n color: {\n legend: true,\n unknown: \"grey\"\n },\n marks: [\n Plot.tickX(d3.range(0, groundhogDaysWithResults.length), {\n x: (d) => d,\n stroke: (d) => determineWinner(d).name,\n strokeWidth: 6,\n title: (d) => describeGroundhog(determineWinner(d)),\n href: (d) =>\n \"https://groundhog-day.com/groundhogs/\" + determineWinner(d).slug,\n target: () => \"_blank\"\n }),\n Plot.ruleX([minimumPredictions])\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1051,"value":"[${determineWinner(minimumPredictions).name}](${\"https://groundhog-day.com/groundhogs/\"+ determineWinner(minimumPredictions).slug}) is the best prognosticator with at least ${minimumPredictions} predictions, with an accuracy of ${determineWinner(minimumPredictions).accuracy * 100}%: ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1242,"value":"

${describeGroundhog(determineWinner(minimumPredictions))}

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1116,"value":"### Accuracy by region","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1098,"value":"addTooltips(\n Plot.plot({\n caption:\n \"Hexbinned regions of North America, colored by the mean accuracy of groundhogs within that hexbin. Hexbins vary in size based on screen width\",\n color: {\n legend: true,\n type: \"sequential\",\n scheme: \"RdYlGn\",\n range: [0, 1]\n },\n width,\n projection,\n marks: [\n Plot.geo(land50),\n Plot.geo(nation),\n Plot.geo(statesMesh, { strokeOpacity: 0.5 }),\n Plot.hexagon(\n groundhogs,\n Plot.hexbin(\n { fill: \"mean\" },\n {\n x: \"lon\",\n y: \"lat\",\n fill: \"accuracy\",\n title: describeGroundhog,\n filter: isDisplayedGroundhog,\n href: (d) =>\n \"https://groundhog-day.com/groundhogs/\" + d.slug + \"/predictions\",\n target: () => \"_blank\"\n }\n )\n )\n ]\n })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1300,"value":"### Average accuracy over time","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1365,"value":"viewof movingAverageWindow = Inputs.range(\n [groundhogDaysWithResults.length, 1],\n {\n label: \"Moving average lookback\",\n value: groundhogDaysWithResults.length,\n step: 1\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1384,"value":"viewof sortFacetsBy = Inputs.radio(\n [\"predictions\", \"recent moving average accuracy\"],\n { label: \"Sort facets by:\", value: \"predictions\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1305,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":391,"value":"\n---\n\n## Implementation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":355,"value":"### API data\n\n#### Groundhogs","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1048,"value":"All the data cleaning is centralized to this definition. All other definitions are relatively simple transforms. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1609,"value":"groundhogs","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":6,"value":"$36","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":364,"value":"#### Predictions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":24,"value":"predictions","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"predictions = groundhogs.flatMap((groundhog) =>\n groundhog.predictions\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":853,"value":"### Weather","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1901,"value":"https://www.kaggle.com/datasets/groundhogclub/groundhog-day","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1904,"value":"archive = await FileAttachment(\"archive.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"archive","database":"$undefined"},{"id":1918,"value":"https://www.datawalrus.com/groundhog_day.html \n\n> Now that I had all this information I next had to determine the logic for assessing the accuracy of Phil's prediction. To do this I used the NOAA data to see whether February and March were colder or warmer than the national average. This would help me determine if there was an early spring or long winter. **The basic logic was if either February or March had temperatures above the national average then it was an early spring. If both February and March were below the national average temperature then it was a long winter.**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1938,"value":"marchAverage = d3.mean(\n archive\n .filter((year) => year[\"March Average Temperature\"] > 0)\n .map((year) => year[\"March Average Temperature\"])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1925,"value":"febuaryAverage = d3.mean(\n archive\n .filter((year) => year[\"February Average Temperature\"] > 0)\n .map((year) => year[\"February Average Temperature\"])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1944,"value":"hadEarlySpring = (year) => {\n const feb = year[\"February Average Temperature\"];\n const march = year[\"March Average Temperature\"];\n\n // ignore null or undefined\n if (feb > 0 && march > 0) {\n return feb > febuaryAverage || march > marchAverage;\n }\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":768,"value":"weatherTill2016 = archive.map((year) => {\n let skew;\n let symbol;\n\n // leave undefined if no data\n if (hadEarlySpring(year) !== undefined) {\n skew = hadEarlySpring(year) ? \"🌼 early spring\" : \"❄️ longer winter\";\n symbol = hadEarlySpring(year) ? \"🌼\" : \"❄️\";\n }\n\n return {\n ...year,\n year: new Date(\"2/2/\" + year.Year),\n skew,\n symbol\n };\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1287,"value":"We only have weather data until 2016 so we have to get data after that from a different source: https://www.ncei.noaa.gov/news/groundhog-day-forecasts-and-climate-history","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1276,"value":"

![](https://www.ncei.noaa.gov/sites/g/files/anmtlf171/files/styles/max_1300x1300/public/groundhog2023-infographic.png?itok=AfhAAnz9)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1966,"value":"function deriveEarlySpring(d) {\n if (d[\"Punxsutawney Phil\"] === \"Full Shadow\") {\n if (d[\"Phil Correct\"] === \"True\") {\n return false;\n } else {\n return true;\n }\n }\n\n if (d[\"Punxsutawney Phil\"] === \"No Shadow\") {\n if (d[\"Phil Correct\"] === \"True\") {\n return false;\n } else {\n return true;\n }\n }\n\n return undefined;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1976,"value":"weatherAfter2016","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1267,"value":"weatherAfter2016 = [\n { Year: 2022, \"Punxsutawney Phil\": \"Full Shadow\", \"Phil Correct\": \"False\" },\n { Year: 2021, \"Punxsutawney Phil\": \"Full Shadow\", \"Phil Correct\": \"False\" },\n { Year: 2020, \"Punxsutawney Phil\": \"No Shadow\", \"Phil Correct\": \"True\" },\n { Year: 2019, \"Punxsutawney Phil\": \"No Shadow\", \"Phil Correct\": \"False\" },\n { Year: 2018, \"Punxsutawney Phil\": \"Full Shadow\", \"Phil Correct\": \"False\" },\n { Year: 2017, \"Punxsutawney Phil\": \"Full Shadow\", \"Phil Correct\": \"False\" }\n].map((year) => {\n const skew = deriveEarlySpring(year) ? \"🌼 early spring\" : \"❄️ longer winter\";\n const symbol = deriveEarlySpring(year) ? \"🌼\" : \"❄️\";\n\n return {\n ...year,\n year: new Date(\"2/2/\" + year.Year),\n skew,\n symbol\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1978,"value":"weather = [...weatherTill2016, ...weatherAfter2016]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1561,"value":"### Derived data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1415,"value":"displayedGroundhogs = groundhogs.filter(isDisplayedGroundhog)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":137,"value":"groundhogDaysWithResults = _.uniqBy(\n predictions.filter((p) => p.conclusion !== undefined).map((p) => p.year),\n (y) => y.getTime()\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1419,"value":"// From the accuracy table, get the corresponding groundhog that has the highest accuracy above the minimum prediction count\ndetermineWinner = (minimumPredictions) => {\n const winner = _.maxBy(\n sortedAccuracy.filter((d) => d.predictionsCount >= minimumPredictions),\n (d) => d.accuracy\n );\n\n if (!winner) {\n return undefined;\n }\n\n // hydrate\n return groundhogs.find((groundhog) => groundhog.name === winner.name);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":536,"value":"### Color","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":538,"value":"colorSkew = ({\n type: \"categorical\",\n domain: [\"🌼 early spring\", \"❄️ longer winter\"],\n range: [\"goldenrod\", \"steelblue\"],\n legend: true\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":398,"value":"### Geo","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":82,"value":"import {\n countiesMesh,\n statesMesh,\n nation,\n land\n} from \"@observablehq/plot-projections\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1178,"value":"import { land50 } from \"@d3/satellite-explorer\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1155,"value":"projection = ({\n type: \"albers\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":380,"value":"### Tooltips","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":292,"value":"import { addTooltips } from \"@mkfreeman/plot-tooltip\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":846,"value":"describeLocation(groundhogs[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":422,"value":"function describeLocation({ city, region, country, lat, lon }) {\n return `${city}, ${region}, ${country} (${lat}, ${lon})`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":312,"value":"describeGroundhog(groundhogs[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":305,"value":"function describeGroundhog(prediction) {\n const { name, type, active, description, accuracy } = prediction;\n return `${name} (${type})\n${describeLocation(prediction)}\nAccuracy: ${accuracy * 100}%\n${description.split(\". \").join(\".\\n\")}\n`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":329,"value":"describePrediction(predictions[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":307,"value":"function describePrediction(prediction) {\n const { name, type, shadow, conclusion, year, details, active, description } =\n prediction;\n return `${name} (${type}) saw ${\n shadow === 1 ? \"shadow\" : shadow === 0 ? \"no shadow\" : \"N/A\"\n } in ${year.toLocaleDateString(\"en-AU\")}\n${conclusion}\n${describeLocation(prediction)}\n${details}\n${description.split(\". \").join(\".\\n\")}`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":734,"value":"### Filtering","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":704,"value":"FILTER_TYPE = ({\n ALL: \"all shadow casting entities\",\n GROUNDHOG_RESEMBLING: \"entities that resemble groundhogs\",\n ANY_GROUNDHOG: \"groundhogs (dead or alive)\",\n ALIVE_GROUNDHOG: \"actual living groundhogs\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":694,"value":"function isDisplayedGroundhog(groundhog) {\n if (filter === FILTER_TYPE.ALL) {\n return true;\n } else if (filter === FILTER_TYPE.GROUNDHOG_RESEMBLING) {\n return groundhog.type.toLowerCase().includes(\"groundhog\");\n } else if (filter === FILTER_TYPE.ANY_GROUNDHOG) {\n return (\n groundhog.type.toLowerCase() === \"groundhog\" ||\n groundhog.type.toLowerCase() === \"taxidermied groundhog\"\n );\n } else if (filter === FILTER_TYPE.ALIVE_GROUNDHOG) {\n return groundhog.type.toLowerCase() === \"groundhog\";\n }\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W37","stdlib":"1","titling":"auto"}} 33:"$32:body"