2f:T6bf,| Category | Description | | | |---------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|---|---| | Food provision | Providing food to humans, including agriculture and fishing, the processing of food items, cooking, serving, and cleanup | | | | Nonfood provision | Providing raw materials and energy to the technosphere, including mining, lumber, fossil fuels, and renewable energy | | | | Technosphere modification | The construction and maintenance of buildings, infrastructure, and movable artifacts | | | | Maintenance of surroundings | Cleaning surfaces and arranging the spaces that humans inhabit, taking care of accompanying plants and animals, disposing of wastes | | | | Somatic maintenance | Caring for the cleanliness, appearance, and health of human bodies, including medical care and childcare | | | | Deliberate neural restructuring | Education, both formal and informal, research in the academic and private sector, and religious activities | | | | Experience oriented | Engaging in activities to provide desired experiences, including through use of media, interactive hobbies and sports, socializing, and meals | | |30:[{"id":"4f0fee3fc94b1f722df0ded0db987eb89e90522b3dc7c209c52e15f3a8dfc1b2a862a67b38e80fb76014bdf0fe9576b15bca14093170ca4fdff47c70652e9528","href":"https://static.observableusercontent.com/files/4f0fee3fc94b1f722df0ded0db987eb89e90522b3dc7c209c52e15f3a8dfc1b2a862a67b38e80fb76014bdf0fe9576b15bca14093170ca4fdff47c70652e9528","name":"country_regions.csv","type":"text/csv","lastModified":1713907007818.601,"size":23179},{"id":"fd5b74cdd99c0c3d6d5a357cd1d51c24116453a688a1af6e346badf8e8c6ab06bec230d9fe99d5df67f70b49d19fbb310dbf2fe710ae36120e9b9ea12a479357","href":"https://static.observableusercontent.com/files/fd5b74cdd99c0c3d6d5a357cd1d51c24116453a688a1af6e346badf8e8c6ab06bec230d9fe99d5df67f70b49d19fbb310dbf2fe710ae36120e9b9ea12a479357","name":"ghd_all_countries.csv","type":"text/csv","lastModified":1713907007818.601,"size":370927}] 2d:{"title":"#30DayChartChallenge D4: Waffle Chart","cells":[{"id":0,"value":"# #30DayChartChallenge D4: Waffle Chart\n\nData uses a [#TidyTuesday](https://github.com/rfordatascience/tidytuesday/tree/master/data/2023/2023-09-12) dataset from The Global Human Day project. This project looks at how people allocate their time in a day across various activities. The waffle chart below uses Highcharts. ","pinned":false,"hidden":false,"mode":"md"},{"id":21,"value":"viewof selectedCountry = Inputs.select(new Map(countryList), {label: \"Select Country\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":11,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":9,"value":"Highcharts.chart('container', {\n chart: {\n type: 'item'\n },\n title: {text: 'Breakdown of Minutes by Category', align:'left'},\n credits: {enabled:false},\n yAxis: {reversed: true},\n plotOptions: {\n item: {\n marker: {symbol: 'square'},\n }\n },\n series: [{\n name: 'Category',\n colors: ['#00BFB2','#48EB70','#EBCD49','#FF9D13','#F95738','#7F2FFF','#4DEAFF','#DCDCDC'],\n layout: 'vertical',\n data: chartData\n }],\n drilldown: {\n series: [{\n name: 'Somatic maintenance',\n id: 'somatic maintenance',\n data: drilldownData.filter(d=> d.id==='somatic maintenance').map(d=> [[d.name, d.y]])\n }]\n }\n});\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":364,"value":"drilldownData.filter(d=> d.id==='somatic maintenance').map(d=> [[d.name, d.y]])","pinned":true,"hidden":false,"mode":"ojs"},{"id":156,"value":"## More on Data\n\nExcerpt from TidyTuesday:\n\nThe data this week comes from the The Human Chronome Project an initiative based at McGill University in Montreal, from their paper The global human day in PNAS and the associated dataset on Zenodo.\n\nThe daily activities of ≈8 billion people occupy exactly 24 h per day, placing a strict physical limit on what changes can be achieved in the world. These activities form the basis of human behavior, and because of the global integration of societies and economies, many of these activities interact across national borders. This project estimates how all humans spend their time using a generalized, physical outcome–based categorization that facilitates the integration of data from hundreds of diverse datasets.\n\nDefinitions for categories taken directly from the project's [research paper](https://www.pnas.org/doi/10.1073/pnas.2219564120#sec-2).","pinned":false,"hidden":false,"mode":"md"},{"id":171,"value":"### Categories","pinned":false,"hidden":false,"mode":"md"},{"id":153,"value":"$2f","pinned":false,"hidden":false,"mode":"md"},{"id":101,"value":"## Data Wrangling\nLeveraging the power of DuckDB and SQL because I loath wrangling with JS...","pinned":false,"hidden":false,"mode":"md"},{"id":271,"value":"chartData = aggregatedData.map(d=>({name: d.id, drilldown: d.id.toLowerCase(), y: d.value, marker: 'square'}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":33,"value":"select \ncategory as id\n,round(sum(hoursPerDayCombined)*60,0) as value\nfrom filteredData\ngroup by category\norder by 2 desc","pinned":true,"hidden":false,"mode":"sql","output":"aggregatedData","database":"var:filteredData"},{"id":343,"value":"chartData","pinned":true,"hidden":false,"mode":"ojs"},{"id":325,"value":"select \nlower(category) as id\n,subcategory as name\n,round(sum(hoursPerDayCombined)*60,0) as y\nfrom filteredData\ngroup by category, subcategory\norder by 3 desc","pinned":true,"hidden":false,"mode":"sql","output":"drilldownData","database":"var:filteredData"},{"id":27,"value":"filteredData = ghd_all_countries.filter(d=>d.country_iso3===selectedCountry)","pinned":true,"hidden":false,"mode":"ojs"},{"id":368,"value":"'wdsfdgSDGDS'.toLowerCase()","pinned":true,"hidden":false,"mode":"ojs"},{"id":7,"value":"## Import Highcharts","pinned":false,"hidden":false,"mode":"md"},{"id":5,"value":"Highcharts = {\n const Highcharts = await require(\"highcharts\");\n await require(\"highcharts/highcharts-more.js\");\n await require(\"highcharts/modules/sunburst.js\");\n await require(\"highcharts/modules/item-series.js\");\n return Highcharts;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":25,"value":"## Import Data\nData from [#TidyTuesday](https://github.com/rfordatascience/tidytuesday/tree/master/data/2023/2023-09-12)","pinned":false,"hidden":false,"mode":"md"},{"id":17,"value":"ghd_all_countries = await FileAttachment(\"ghd_all_countries.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs"},{"id":161,"value":"country_regions = await FileAttachment(\"country_regions.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs"},{"id":166,"value":"SELECT * FROM \"country_regions\"","pinned":true,"hidden":false,"mode":"sql","output":"","database":"country_regions.csv"},{"id":121,"value":"countries = [...new Set(ghd_all_countries.map(d => d.country_iso3))].sort()","pinned":true,"hidden":false,"mode":"ojs"},{"id":173,"value":"countryList = country_regions\n .filter(d => countries.includes(d.country_iso3))\n .map(d => [d.country_name, d.country_iso3])\n .sort((a, b) => a[0].localeCompare(b[0]));","pinned":true,"hidden":false,"mode":"ojs"},{"id":162,"value":"selectedCountryName = country_regions.filter(d=>d.country_iso3 === selectedCountry)[0].country_name","pinned":true,"hidden":false,"mode":"ojs"},{"id":104,"value":"","pinned":true,"hidden":false,"mode":"html"}],"files":"$W30","stdlib":"1","titling":"auto"}