2c:null 2d:["$","title",null,{"children":"CO2 EMISSIONS ANALYSIS TOOL (G2) | UdG | Master's in Data Science | Observable"}] 32:T7d4,### Objectives Examine Emissions in Each Sector: This involves understanding the sources and trends of each sector. Examine countries CO2 emissions: Conduct a study on the CO2 emissions from various sectors by countries. Evaluate Changes Over Time: How emissions in each sector have changed over a specific period. Look for any significant increases or decreases and try to correlate them with relevant policy changes or external factors. Identify Contributing Factors: Investigate the factors that have contributed to changes in emissions. This could include technological advancements, economic shifts, public awareness, or changes in consumer behavior. Understanding these factors will provide context for the effectiveness of policies. ### Introduction As said the main objective is to conduct a comprehensive analysis of emissions in various sectors over time and examine CO2 emissions in each sector. To kickstart this analysis, we choose two initial graphs: **LINE CHART and PIE CHART** where an analysis of CO2 emissions in various sectors over time is shown. These two graphs constitute a vital tool to unravel the evolution of the influence each sector has had on CO2 emissions in relation to other sectors over the years. ### Reason for starting with these graphs: We commence with these graphs for several fundamental reasons: #### Historical and comparative insight: These graphs provide a historical and comparative view of CO2 emissions across different sectors, allowing us to identify trends and patterns over time. #### Contextualization of sectoral influence: By analyzing CO2 emissions sector by sector, we gain a deeper understanding of each sector's relative contribution to the total emissions. This is crucial for formulating mitigation policies and strategies. #### Detection of significant changes: These graphs enable us to detect significant changes in CO2 emissions and assess how certain historical events or economic shifts may have impacted specific sectors.33:Taf1,{ const items = [ {name: "First data collected", date: 1750}, {name: "Discovery of Oil", date: 1850}, {name: "Post-World War II", date: 1940}, {name: "Energy Crises", date: 1970}, {name: "Kyoto Protocol", date: 2005}, {name: "Paris Agreement", date: 2016}, {name: "Last data collected", date: 2021} ]; const margin = {top: 0, right: 7, bottom: 0, left: 7}; const font_size = 10; let range = d3.sort(items, (a, b) => a.date - b.date); range = [range[0].date, range[range.length - 1].date]; let selected_dates = [range[0], range[range.length - 1]]; const band_width = (width - margin.right - margin.left) / (range[1] - range[0]) const svg = d3.create("svg") .attr("width", width + 10) .attr("left", -5) .attr("height", font_size + 5); const ticks = svg.append("g") .attr("label", "tick") .selectAll(`[label="tick"]`) .data(items).enter().append("line") .attr("x1", d => `${band_width * (d.date - range[0]) + margin.left}`) .attr("y1", font_size) .attr("x2", d => `${band_width * (d.date - range[0]) + margin.left}`) .attr("y2", font_size + 5) .attr("stroke", "black") const labels = svg.append("g") .attr("label", "text") .selectAll(`[label="text"]`) .data(items).enter().append("text") .text(d => d.date) .attr("transform", d => `translate(${calculate_text_position(d.date, band_width * (d.date - range[0])) + margin.left},${9})`) .attr("font-size", "10") let range_input = rangeInput({min: range[0], max: range[1], step: 1, width: width, value: selected_dates, theme: theme_simplified}); d3.select(range_input) .on("change", handle_input_change); return html`${svg.node()}${range_input}`; function calculate_text_position(text, x) { const text_width = text_size(text, font_size).width // return x - text_width / 2; return x - text_width / 2 < margin.left? x - text_width / 3 : x - text_width / 2 } function text_size(text, font_size) { if (!d3) return; var container = d3.select('body').append('svg'); container.append('text').attr("transform", "translate(-99999, -99999)").attr("font-size", font_size).text(text); var size = container.node().getBBox(); container.remove(); return { width: size.width, height: size.height }; } function handle_input_change(event) { let target = event.target; const dates = target.value.map(value1 => { const closestObj = items.reduce((prev, curr) => { const prevDiff = Math.abs(prev.date - value1); const currDiff = Math.abs(curr.date - value1); return prevDiff < currDiff ? prev : curr; }); return closestObj.date; }); range_input.value = dates; mutable date_range = dates; } }34:Tbd3,viewof sector_selected = { const bubbles = d3.select( Plot.plot({ width: width, height: 150, marginRight: (width - 700) / 2, marginLeft: (width - 700) / 2, r: {range: [0, 50]}, color: {range: d3.quantize(t => d3.interpolateSpectral(t * 0.8 + 0.1), sectors.length)}, marks: [ Plot.axisX({label: null, tickFormat: d => `${d}\n${total_reduced_data.find(e => e.sector == d).co2.toLocaleString("en")}Mt`}), Plot.axisY({label: null, strokeOpacity: 0, fill: null}), Plot.dot(total_reduced_data, {x: "sector", y: 0, r: "co2", fill: "sector", stroke: "sector"}), () => svg`\n

${list.domain.map(value => {\n return htl.html`

${value}

`;\n })}

\n `;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3217,"value":"schemeSector = Object.create({\n domain: sectors,\n get: function(continent) {\n const index = this.domain.indexOf(continent)\n return index != -1? d3.quantize(t => d3.interpolateSpectral(t * 0.8 + 0.1), this.domain.length)[index] : \"rgb(255, 255, 255)\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3220,"value":"schemeContinent = Object.create({\n domain: continents,\n get: function(continent) {\n const index = this.domain.indexOf(continent)\n return index != -1? d3.quantize(t => d3.interpolateSpectral(t * 0.8 + 0.1), this.domain.length)[index] : \"rgb(255, 255, 255)\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":209,"value":"---\n### General data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":388,"value":"sectors = ['cement', 'coal', 'flaring', 'gas', 'luc', 'oil', 'other']","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2453,"value":"continents = d3.sort(Array.from(new Set(Plot.valueof(country_continent, \"continent\"))));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":415,"value":"world = FileAttachment(\"countries-110m.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":432,"value":"world_land = topojson.feature(world, world.objects.land)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":436,"value":"world_countries = topojson.feature(world, world.objects.countries)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":731,"value":"country_continent = FileAttachment(\"country-by-continent.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3676,"value":"country_continent","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":470,"value":"countries_loc = FileAttachment(\"countries_lon_lat.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1070,"value":"countries_list = country_continent.map(obj => obj.country);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3212,"value":"---\n### Imports","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"import { toc } from \"@nebrius/indented-toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":348,"value":"import {joinArrays} from \"56f7c9059e8ab6d1\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3767,"value":"import {rangeInput} from \"@mootari/range-slider\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":499,"value":"import {Scrubber} from \"@mbostock/scrubber\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1166,"value":"import {boxStyles} from \"@udg-master-data-science/data-playground\" ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1894,"value":"import {Treemap} from \"@d3/treemap-component\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2129,"value":"import {Swatches} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W39","stdlib":"1","titling":"auto"}} 31:"$30:body"