delen/vistext huggingface dataset:
Chart description: There are 2 different positive trends, 2000 to 2007 and a second trend with a steeper slope from 2009 to 2019. There is a dip in 2008.

Chart data: Year Real GDP in billion U.S. dollars Dec 31, 1999 245.98 Dec 31, 2000 246.06 Dec 31, 2001 252.41 Dec 31, 2002 263.87 Dec 31, 2003 274.71 Dec 31, 2004 282.09 Dec 31, 2005 281.97 Dec 31, 2006 283.21 Dec 31, 2007 285.79 Dec 31, 2008 275.45 Dec 31, 2009 284.86 Dec 31, 2010 290.63 Dec 31, 2011 294.3 Dec 31, 2012 300.63 Dec 31, 2013 309.24 Dec 31, 2014 313.09 Dec 31, 2015 319.13 Dec 31, 2016 325.32 Dec 31, 2017 333.92 Dec 31, 2018 338.75

Vega-Lite specification:
{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "data/8995.tsv"}, "mark": "line", "encoding": {"color": {"value": "#E044A7"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Real GDP in billion U.S. dollars"}, "field": "Real GDP in billion U\\.S\\. dollars"}}, "title": ["Real Gross Domestic Product (GDP) of the", "federal state of Minnesota from 2000 to 2019", "(in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The percentage of African American directors took a sharp dip in 2010 but has been increasing steadily from then to 2018.

Chart data: Response Percentage of African-American directors Dec 31, 2008 0.053 Dec 31, 2009 0.032 Dec 31, 2010 0.077 Dec 31, 2011 0.077 Dec 31, 2012 0.103 Dec 31, 2013 0.083 Dec 31, 2014 0.093 Dec 31, 2015 0.093 Dec 31, 2016 0.109 Dec 31, 2017 0.11 Dec 31, 2018 0.1

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/9001.tsv"}, "mark": "line", "encoding": {"color": {"value": "#829eb1"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Percentage of African-American directors"}, "field": "Percentage of African-American directors"}}, "title": ["Percentage of new African-American directors", "on Fortune 500 boards from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Public Administration has the highest amount at over 600 million. The majority are under 100 million.

Chart data: industry GDP in million chained 2012 Canadian dollars Public administration 639.7 Real estate and rental and leasing 403 Construction 348.5 Health care and social assistance 237.1 Retail trade 142.4 Educational services 142.1 Transportation and warehousing 103.6 Accommodation and food services 92.3 Mining, quarrying, and oil and gas extraction 90.7 Information and cultural industries 87.4 Professional, scientific and technical services 86 Finance and insurance 80.3 Utilities 49.8 Wholesale trade 43.8 Other services (except public administration) 37.2 Administrative and support, waste management and remediation services 32 Manufacturing 18.5 Arts, entertainment and recreation 13.5 Agriculture, forestry, fishing and hunting 5.3 Management of companies and enterprises 4.9

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9002.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e6ab02"}, "x": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "industry"}, "y": {"type": "quantitative", "axis": {"title": "GDP in million chained 2012 Canadian dollars"}, "field": "GDP in million chained 2012 Canadian dollars"}}, "title": ["Gross domestic product of Yukon , Canada", "in 2019 , by industry (in million chained", "2012 Canadian dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Saxony was the German  federal state with the highest Covid  19 infections in 2020.

Chart data: Infection rate per 100,000 people state of Germany 2749 Saxony 2440 Berlin 2259 Bavaria 2019 North Rhine-Westphalia 1989 Hesse 1959 Baden-Württemberg 1874 Bremen 1870 Total 1843 Saarland 1803 Hamburg 1637 Thuringia 1599 Rheinland-Palatinate 1353 Brandenburg 1213 Lower Saxony 1105 Saxony-Anhalt 753 Schleswig Holstein 635 Mecklenburg-West Pomerania

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/900.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec8431"}, "x": {"type": "quantitative", "axis": {"title": "Infection rate per 100,000 people"}, "field": "Infection rate per 100,000 people"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "state of Germany"}}, "title": ["Coronavirus (COVID-19) infection rate in", "Germany in 2020 , by federal state (per 100,000", "inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Saxony had the highest infection rate, per 100,000 people. Mecklenburg-West Pomerania and Schleswig Holstein had the lowest, neither reaching the 1,000 mark.

Chart data: Infection rate per 100,000 people state of Germany 2749 Saxony 2440 Berlin 2259 Bavaria 2019 North Rhine-Westphalia 1989 Hesse 1959 Baden-Württemberg 1874 Bremen 1870 Total 1843 Saarland 1803 Hamburg 1637 Thuringia 1599 Rheinland-Palatinate 1353 Brandenburg 1213 Lower Saxony 1105 Saxony-Anhalt 753 Schleswig Holstein 635 Mecklenburg-West Pomerania

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/900.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec8431"}, "x": {"type": "quantitative", "axis": {"title": "Infection rate per 100,000 people"}, "field": "Infection rate per 100,000 people"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "state of Germany"}}, "title": ["Coronavirus (COVID-19) infection rate in", "Germany in 2020 , by federal state (per 100,000", "inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: As the years have gone by the estimated government spend has decreased. The bar graph clearly shows a decline in expenditure at a steady pace.

Chart data: Year Ratio of government expenditure to GDP 2024* 0.2655 2023* 0.2675 2022* 0.2686 2021* 0.2712 2020* 0.2756 2019* 0.2777 2018* 0.2884 2017 0.2922 2016 0.2784 2015 0.302 2014 0.2853

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9010.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#a6761d"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Ratio of government expenditure to GDP"}, "field": "Ratio of government expenditure to GDP"}}, "title": ["Vietnam : Ratio of government expenditure", "to gross domestic product (GDP) from 2014", "to 2024"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: this graph shows an upwards trend and shows the national debt of oman is increasing. 2022 was a bit of an anomoly as it fell that year which doesnt sit in line with all the other years.

Chart data: Year National debt in relation to GDP 2025* 0.9907 2024* 0.9528 2023* 0.9083 2022* 0.8668 2021* 0.8865 2020* 0.8153 2019* 0.6306 2018 0.5317 2017 0.4642 2016 0.3271 2015 0.1547

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/9014.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ab7fb4"}, "x": {"type": "nominal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "National debt in relation to GDP"}, "field": "National debt in relation to GDP"}}, "title": ["Oman : National debt from 2015 to 2025 in", "relation to gross domestic product (GDP)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The province of Canada with the highest number of snowmobile registrations in 2018 was Quebec with just over 200,000 registrations. Conversely, The province with the lowest number of registrations was Yukon. Most provinces had registrations under/ near 50,000.

Chart data: province of Canada Number of registrations Quebec 201732 Ontario 155000 Alberta 73000 New Foundland 58700 British Columbia 44500 Manitoba 35354 New Brunswick 19550 Saskatchewan 16175 Nunavut 14200 North West Territory 9800 Nova Scotia 7200 Prince Edward Island 2180 Yukon 1805

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9022.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7cb94"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "province of Canada"}, "y": {"type": "quantitative", "axis": {"title": "Number of registrations"}, "field": "Number of registrations"}}, "title": ["Number of snowmobile registrations in Canada", "in 2018 , by province"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Thailand exports the most rubber followed by Indonesia. European countries combined so not export as much as Thailand and Indonesia.

Chart data: Share of global exports Response 0.315 Thailand 0.298 Indonesia 0.084 Côte d’Ivoire 0.076 Vietnam 0.069 Malaysia 0.021 Myanmar 0.02 Laos 0.016 Belgium 0.011 Liberia 0.011 Guatemala 0.008 Singapore 0.007 Netherlands 0.007 France 0.007 Germany 0.006 Luxembourg 0.043 Rest of world

Vega-Lite specification:
{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "data/9024.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#DCDCDC"}, "x": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Share of global exports"}, "field": "Share of global exports"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Response"}}, "title": ["Distribution of the leading natural rubber", "exporting countries in 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From 2001 - 2004 the percentage of the population in Nevada increased and with it came a higher rate of poverty. A year after and it dropped to just over 0.10 in population that was on the poverty line. After this drop it has increased passed 0.15 making it a highest record on this chart. The peak reached the year of 2012 before it slowly declines afterwards. Over the years the poverty level has increased.

Chart data: Response Percentage of population Dec 31, 1999 0.099 Dec 31, 2000 0.097 Dec 31, 2001 0.118 Dec 31, 2002 0.115 Dec 31, 2003 0.126 Dec 31, 2004 0.111 Dec 31, 2005 0.103 Dec 31, 2006 0.107 Dec 31, 2007 0.113 Dec 31, 2008 0.124 Dec 31, 2009 0.149 Dec 31, 2010 0.159 Dec 31, 2011 0.164 Dec 31, 2012 0.158 Dec 31, 2013 0.152 Dec 31, 2014 0.147 Dec 31, 2015 0.138 Dec 31, 2016 0.13 Dec 31, 2017 0.129 Dec 31, 2018 0.125

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/9028.tsv"}, "mark": "line", "encoding": {"color": {"value": "#9E9D24"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Percentage of population"}, "field": "Percentage of population"}}, "title": ["Poverty rate in Nevada from 2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Canada and Mexico are the counties to which USA exports most chemicals. USA exports over £20billion of chemicals to Mexico and Canada.

Chart data: Exports in billion U.S. dollars Country 21.7 Canada 21.2 Mexico 10.1 China 7.4 Brazil 6.1 Japan 6 South Korea 5 Netherlands 4.4 India 3.2 Singapore 3.1 Germany

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9030.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d95f02"}, "x": {"type": "quantitative", "axis": {"title": "Exports in billion U.S. dollars"}, "field": "Exports in billion U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Top destinations for United States chemical", "exports in 2019 , by country (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The US delivered more chemical exports to Canada than any other country in 2019. Mexico was the next largest.. The fewest chemical exports went to Germany.

Chart data: Exports in billion U.S. dollars Country 21.7 Canada 21.2 Mexico 10.1 China 7.4 Brazil 6.1 Japan 6 South Korea 5 Netherlands 4.4 India 3.2 Singapore 3.1 Germany

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9030.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d95f02"}, "x": {"type": "quantitative", "axis": {"title": "Exports in billion U.S. dollars"}, "field": "Exports in billion U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Top destinations for United States chemical", "exports in 2019 , by country (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Hong Kong shows the greatest positive change in carbon monoxide emissions between 1990 and 2017 by a significant amount. Six countries had a positive change whilst five had a negative change, with Denmark showing the greatest negative change.

Chart data: Change in CO2 emissions Country 3.383 China (including Hong Kong) 0.481 Australia 0.306 Canada 0.251 Spain 0.154 Austria 0.086 Japan −0.009 United States −0.114 France* −0.235 Germany −0.29 Russia −0.347 United Kingdom −0.387 Denmark

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9031.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#cedb9c"}, "x": {"type": "quantitative", "axis": {"title": "Change in CO2 emissions"}, "field": "Change in CO2 emissions"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Change in carbon dioxide emissions in selected", "countries between 1990 and 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: This bar chart seems to show that there China (including Hong Kong) has had a very large increase in CO2 emissions, way ahead of other countries. It also shows that Denmark and United Kingdom have had the most decrease in CO2 emissions.

Chart data: Change in CO2 emissions Country 3.383 China (including Hong Kong) 0.481 Australia 0.306 Canada 0.251 Spain 0.154 Austria 0.086 Japan −0.009 United States −0.114 France* −0.235 Germany −0.29 Russia −0.347 United Kingdom −0.387 Denmark

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9031.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#cedb9c"}, "x": {"type": "quantitative", "axis": {"title": "Change in CO2 emissions"}, "field": "Change in CO2 emissions"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Change in carbon dioxide emissions in selected", "countries between 1990 and 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: China has the highest change in CO2 emissions which is an increase of 3.  Denmark and UK have the smallest change in CO2 emissions which is below zero.

Chart data: Change in CO2 emissions Country 3.383 China (including Hong Kong) 0.481 Australia 0.306 Canada 0.251 Spain 0.154 Austria 0.086 Japan −0.009 United States −0.114 France* −0.235 Germany −0.29 Russia −0.347 United Kingdom −0.387 Denmark

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9031.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#cedb9c"}, "x": {"type": "quantitative", "axis": {"title": "Change in CO2 emissions"}, "field": "Change in CO2 emissions"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Change in carbon dioxide emissions in selected", "countries between 1990 and 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The above bar chart shows the number of hospital beds in Denmark from 2000 to 2019. The number of beds decreases year on year with exception of 2002 and 2008. This bucks the trend of a reduction year on year.

Chart data: Number of hospital beds Year 15073 2019** 14077 2018 15037 2017 14871 2016 14380 2015 15174 2014* 17241 2013 17433 2011 * 19405 2010 19296 2009 19615 2008 20159 2007 20613 2006 20902 2005 21462 2004 22281 2003 23040 2002 22604 2001 22927 2000

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/9033.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#0F9D58"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of hospital beds"}, "field": "Number of hospital beds"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Number of hospital beds in Denmark from", "2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of hospital beds in Denmark has decreased in more years that it has increased. The largest decrease was between 2010 and 2011.

Chart data: Number of hospital beds Year 15073 2019** 14077 2018 15037 2017 14871 2016 14380 2015 15174 2014* 17241 2013 17433 2011 * 19405 2010 19296 2009 19615 2008 20159 2007 20613 2006 20902 2005 21462 2004 22281 2003 23040 2002 22604 2001 22927 2000

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/9033.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#0F9D58"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of hospital beds"}, "field": "Number of hospital beds"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Number of hospital beds in Denmark from", "2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The chart shows an overall drop in hospital beds between 2000-2019. It clearly shows the number of beds in a certain year (for example it’s clear to see there were 15000 beds in 2019. It is not clear as to why there is an * marked at the years 2011, 2014 and 2019 from the chart. The bars are the colour green.

Chart data: Number of hospital beds Year 15073 2019** 14077 2018 15037 2017 14871 2016 14380 2015 15174 2014* 17241 2013 17433 2011 * 19405 2010 19296 2009 19615 2008 20159 2007 20613 2006 20902 2005 21462 2004 22281 2003 23040 2002 22604 2001 22927 2000

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/9033.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#0F9D58"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of hospital beds"}, "field": "Number of hospital beds"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Number of hospital beds in Denmark from", "2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of hospital beds available is on a steep downwards trend.

Chart data: Number of hospital beds Year 15073 2019** 14077 2018 15037 2017 14871 2016 14380 2015 15174 2014* 17241 2013 17433 2011 * 19405 2010 19296 2009 19615 2008 20159 2007 20613 2006 20902 2005 21462 2004 22281 2003 23040 2002 22604 2001 22927 2000

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/9033.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#0F9D58"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of hospital beds"}, "field": "Number of hospital beds"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Number of hospital beds in Denmark from", "2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The youth unemployment rate in the United Arab Emirates from 2000 to 2015 has risen overall, but there are lots of peaks and falls along the way including a the highest rate of unemployment in 2005. The times with the lowest rates of unemployment were in about 2008 and 2017.

Chart data: Year Youth unemployment rate Dec 31, 1998 0.0602 Dec 31, 1999 0.0598 Dec 31, 2000 0.063 Dec 31, 2001 0.0684 Dec 31, 2002 0.0734 Dec 31, 2003 0.0787 Dec 31, 2004 0.0809 Dec 31, 2005 0.0713 Dec 31, 2006 0.0598 Dec 31, 2007 0.0582 Dec 31, 2008 0.0693 Dec 31, 2009 0.0746 Dec 31, 2010 0.0728 Dec 31, 2011 0.0741 Dec 31, 2012 0.0767 Dec 31, 2013 0.0703 Dec 31, 2014 0.0651 Dec 31, 2015 0.0583 Dec 31, 2016 0.0785 Dec 31, 2017 0.0705 Dec 31, 2018 0.0734 Dec 31, 2019 0.0751

Vega-Lite specification:
{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "data/9034.tsv"}, "mark": "area", "encoding": {"color": {"value": "#703c5c"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Youth unemployment rate"}, "field": "Youth unemployment rate"}}, "title": ["United Arab Emirates : Youth unemployment", "rate from 1999 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The Real Gross Domestic Product of Maryland has increased over time.

Chart data: Year Real GDP in billion U.S. dollars Dec 31, 1999 250.98 Dec 31, 2000 260.77 Dec 31, 2001 270.88 Dec 31, 2002 277.95 Dec 31, 2003 292.12 Dec 31, 2004 305.99 Dec 31, 2005 311.68 Dec 31, 2006 312.09 Dec 31, 2007 315.86 Dec 31, 2008 314.86 Dec 31, 2009 327.23 Dec 31, 2010 334.31 Dec 31, 2011 334.82 Dec 31, 2012 334.94 Dec 31, 2013 338.73 Dec 31, 2014 345.23 Dec 31, 2015 356.82 Dec 31, 2016 360.03 Dec 31, 2017 368.86 Dec 31, 2018 374.39

Vega-Lite specification:
{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "data/9035.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3e5c69"}, "x": {"type": "temporal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Real GDP in billion U.S. dollars"}, "field": "Real GDP in billion U\\.S\\. dollars"}}, "title": ["Real Gross Domestic Product (GDP) of the", "federal state of Maryland from 2000 to 2019", "(in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The GDP of Maryland has increased between 2000-2019.

Chart data: Year Real GDP in billion U.S. dollars Dec 31, 1999 250.98 Dec 31, 2000 260.77 Dec 31, 2001 270.88 Dec 31, 2002 277.95 Dec 31, 2003 292.12 Dec 31, 2004 305.99 Dec 31, 2005 311.68 Dec 31, 2006 312.09 Dec 31, 2007 315.86 Dec 31, 2008 314.86 Dec 31, 2009 327.23 Dec 31, 2010 334.31 Dec 31, 2011 334.82 Dec 31, 2012 334.94 Dec 31, 2013 338.73 Dec 31, 2014 345.23 Dec 31, 2015 356.82 Dec 31, 2016 360.03 Dec 31, 2017 368.86 Dec 31, 2018 374.39

Vega-Lite specification:
{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "data/9035.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3e5c69"}, "x": {"type": "temporal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Real GDP in billion U.S. dollars"}, "field": "Real GDP in billion U\\.S\\. dollars"}}, "title": ["Real Gross Domestic Product (GDP) of the", "federal state of Maryland from 2000 to 2019", "(in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of hospitals in Austria fell from around 270 in 2000 to 260 in 2003. It then steadily rose from 260 in 2003 to 300 in 2012. The number of hospitals peaked between 2012 and 2015, where they remained at 300. Between 2015 and 2018, the number of hospitals fell from 300 to 270.

Chart data: Year Number of hospitals Dec 31, 1999 269 Dec 31, 2000 264 Dec 31, 2001 267 Dec 31, 2002 261 Dec 31, 2003 263 Dec 31, 2004 264 Dec 31, 2005 264 Dec 31, 2006 270 Dec 31, 2007 267 Dec 31, 2008 267 Dec 31, 2009 268 Dec 31, 2010 273 Dec 31, 2011 277 Dec 31, 2012 278 Dec 31, 2013 279 Dec 31, 2014 278 Dec 31, 2015 273 Dec 31, 2016 271 Dec 31, 2017 264

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9039.tsv"}, "mark": "area", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Number of hospitals"}, "field": "Number of hospitals"}}, "title": ["Number of hospitals in Austria from 2000", "to 2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is very little variation over time in the number of hospitals.

Chart data: Year Number of hospitals Dec 31, 1999 269 Dec 31, 2000 264 Dec 31, 2001 267 Dec 31, 2002 261 Dec 31, 2003 263 Dec 31, 2004 264 Dec 31, 2005 264 Dec 31, 2006 270 Dec 31, 2007 267 Dec 31, 2008 267 Dec 31, 2009 268 Dec 31, 2010 273 Dec 31, 2011 277 Dec 31, 2012 278 Dec 31, 2013 279 Dec 31, 2014 278 Dec 31, 2015 273 Dec 31, 2016 271 Dec 31, 2017 264

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/9039.tsv"}, "mark": "area", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Number of hospitals"}, "field": "Number of hospitals"}}, "title": ["Number of hospitals in Austria from 2000", "to 2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Real estate, renting and leasing are the biggest distribution of gross domestic product in Canada.

Chart data: Share of GDP Response 0.1301 Real estate and rental and leasing 0.1198 Manufacturing 0.0915 Finance and insurance 0.0742 Professional, scientific and technical services 0.0737 Health care and social assistance 0.0733 Public administration 0.0678 Construction 0.0605 Wholesale trade 0.0575 Educational services 0.0491 Retail trade 0.043 Transportation and warehousing 0.0339 Administrative and support, waste management and remediation services 0.0335 Information and cultural industries 0.0212 Accommodation and food services 0.0193 Other services (except public administration) 0.0192 Utilities 0.0092 Agriculture, forestry, fishing and hunting 0.0088 Mining, quarrying, and oil and gas extraction 0.0085 Arts, entertainment and recreation 0.006 Management of companies and enterprises

Vega-Lite specification:
{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "data/9040.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bab0ac"}, "x": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Share of GDP"}, "field": "Share of GDP"}, "y": {"type": "nominal", "axis": {"labelAngle": 0}, "bin": false, "field": "Response"}}, "title": ["Distribution of gross domestic product of", "Ontario , Canada in 2019 , by industry"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Catholicism is the most popular religious affirmation in Canada during 2013. The second most popular is none and the third is Protestant.

Chart data: Share of total population Response 0.39 Catholic* 0.203 Protestants** 0.016 Orthodox 0.063 Other Christian 0.032 Muslim 0.015 Hindu 0.014 Sikh 0.011 Buddhist 0.01 Jewish 0.006 Other 0.239 None

Vega-Lite specification:
{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "data/904.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#beaed4"}, "x": {"type": "quantitative", "axis": {"title": "Share of total population"}, "field": "Share of total population"}, "y": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "Response"}}, "title": ["Canada : Religious affiliation in 2011"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The average drop out rate was fairly consistent between 2008 and 2013 then it began to reduce but not significantly.

Chart data: Dropout rate Year 0.084 2019 0.086 2018 0.089 2017 0.088 2016 0.101 2015 0.098 2014** 0.11 2013 0.12 2012 0.123 2011 0.119 2010 0.111 2009 0.12 2008

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9050.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7969c"}, "x": {"type": "quantitative", "axis": {"title": "Dropout rate"}, "field": "Dropout rate"}, "y": {"type": "nominal", "axis": {"labelAngle": 0}, "bin": false, "field": "Year"}}, "title": ["Annual average dropout rate in Belgium from", "2008 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The dropout rate has been decreasing since 2011, with a few slight anomalies in 2014/15 and 2016/17.

Chart data: Dropout rate Year 0.084 2019 0.086 2018 0.089 2017 0.088 2016 0.101 2015 0.098 2014** 0.11 2013 0.12 2012 0.123 2011 0.119 2010 0.111 2009 0.12 2008

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/9050.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7969c"}, "x": {"type": "quantitative", "axis": {"title": "Dropout rate"}, "field": "Dropout rate"}, "y": {"type": "nominal", "axis": {"labelAngle": 0}, "bin": false, "field": "Year"}}, "title": ["Annual average dropout rate in Belgium from", "2008 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The highest positive percentage change in GDP was in 2000 with 0.08. GDP decreased in the year 2008 with a percentage change of about -0.01. The percentage change in GDP oscillates over time with peaks and troughs. After 2008 there seems to be an upward trend in the percentage change in GDP. The average percentage change throughout the sample is about 0.02. The percentage change in the year 2000 looks like an outlier compared to the rest of the sample.

Chart data: Year Percent change compared to preceding period Dec 31, 1999 0.081 Dec 31, 2000 0.013 Dec 31, 2001 0.003 Dec 31, 2002 0.027 Dec 31, 2003 0.025 Dec 31, 2004 0.02 Dec 31, 2005 0.017 Dec 31, 2006 0.026 Dec 31, 2007 0.009 Dec 31, 2008 −0.01 Dec 31, 2009 0.009 Dec 31, 2010 0.024 Dec 31, 2011 0.021 Dec 31, 2012 0.004 Dec 31, 2013 0.017 Dec 31, 2014 0.04 Dec 31, 2015 0.015 Dec 31, 2016 0.024 Dec 31, 2017 0.034 Dec 31, 2018 0.024

Vega-Lite specification:
{"config": {"area": {"fill": "#30a2da"}, "axis": {"domainColor": "#cbcbcb", "grid": true, "gridColor": "#cbcbcb", "gridWidth": 1, "labelColor": "#999", "labelFontSize": 10, "titleColor": "#333", "tickColor": "#cbcbcb", "tickSize": 10, "titleFontSize": 14, "titlePadding": 10, "labelPadding": 4}, "axisBand": {"grid": false}, "background": "#f0f0f0", "view": {"fill": "#f0f0f0"}, "legend": {"labelColor": "#333", "labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square", "titleColor": "#333", "titleFontSize": 14, "titlePadding": 10}, "line": {"stroke": "#30a2da", "strokeWidth": 2}, "rect": {"fill": "#30a2da"}, "bar": {"binSpacing": 2, "fill": "#30a2da", "stroke": null}, "range": {"category": ["#30a2da", "#fc4f30", "#e5ae38", "#6d904f", "#8b8b8b", "#b96db8", "#ff9e27", "#56cc60", "#52d2ca", "#52689e", "#545454", "#9fe4f8"], "diverging": ["#cc0020", "#e77866", "#f6e7e1", "#d6e8ed", "#91bfd9", "#1d78b5"], "heatmap": ["#d6e8ed", "#cee0e5", "#91bfd9", "#549cc6", "#1d78b5"]}, "point": {"filled": true, "shape": "circle"}, "title": {"anchor": "start", "fontSize": 24, "fontWeight": 600, "offset": 20}}, "data": {"url": "data/9052.tsv"}, "mark": "line", "encoding": {"color": {"value": "#52689e"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Percent change compared to preceding period"}, "field": "Percent change compared to preceding period"}}, "title": ["Annual percent change of the real GDP in", "Massachusetts from 2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}