delen/vistext huggingface dataset:
Chart description: Attendance at Division I FBS Football games was highest in 2008. Attendance at Division I FBS Football games has a trend of decreasing between 2008 and 2019.

Chart data: Year Average attendance Dec 31, 2002 52098 Dec 31, 2003 52718 Dec 31, 2004 51879 Dec 31, 2005 53114 Dec 31, 2006 54844 Dec 31, 2007 52369 Dec 31, 2008 52055 Dec 31, 2009 52648 Dec 31, 2010 50435 Dec 31, 2011 49224 Dec 31, 2012 48989 Dec 31, 2013 44372 Dec 31, 2014 43817 Dec 31, 2015 41718 Dec 31, 2016 40506 Dec 31, 2017 41093 Dec 31, 2018 40935

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/12160.tsv"}, "mark": "line", "encoding": {"color": {"value": "#6793a6"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Average attendance"}, "field": "Average attendance"}}, "title": ["Average attendance at Division I FBS college", "football bowl games from 2003 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Child abuse is over 2,000 cases compared to the next highest of only 600.

Chart data: crime types Number of crimes Child abuse within the family 2101 Violation of family obligations 631 Sexual violence 637 Child abandonment 510 Sexual intercourse with a minor 444 Aggravated sexual assault 403 Abuse of correction and discipline measures 403 Abduction of person incapable of consent 237 Child pornography 251 Corruption of minors 164 Possession of pornographic material 88 Child prostitution 56 Voluntary manslaughter 14

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/12166.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#beaed4"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "crime types"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Number of crimes"}, "field": "Number of crimes"}}, "title": ["Number of committed and reported crimes", "against underage children in Italy in 2019", ", by type of crime"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2018 China produced over 4 times the amount of zinc than the United states.

Chart data: Share of production Response 0.338 China 0.116 Peru 0.058 India 0.067 United States 0.087 Australia 0.054 Mexico 0.043 Bolivia 0.027 Kazakhstan 0.022 Canada 0.186 Other countries

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/12167.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "quantitative", "axis": {"title": "Share of production"}, "field": "Share of production"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Response"}}, "title": ["Distribution of zinc mine production worldwide", "in 2018 , by country"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Signal Iduna Park has the highest capacity of all venues. Exactly half of the venues have capacity under 40,000. Five venues have capacity over 60,000. All venues have capacity over 20,000. Signal Iduna Park has almost four times the capacity of An der Alten Försterei.

Chart data: association football venue Capacity Signal Iduna Park (Borussia Dortmund) 81365 Allianz Arena (FC Bayern Munich) 75024 Olympiastadion (Hertha BSC Berlin) 74400 Veltins Arena (FC Schalke 04) 62271 Mercedes-Benz Arena (VfB Stuttgart) 60449 Borussia-Park (Borussia Mönchengladbach) 54022 Deutsche Bank Park (Eintracht Frankfurt) 51500 Red Bull Arena (Leipzig) 42558 Wohninvest Weserstadion (SV Werder Bremen) 42100 Opel Arena (1. FSV Mainz 05) 34000 WWK Arena (FC Augsburg) 30660 WWK ARENA (FC Augsburg) 30660 BayArena (Bayer 04 Leverkusen) 30210 PreZero Arena (TSG Hoffeneim) 30150 Volkswagen Arena (VfL Wolfsburg) 30000 SchücoArena (Arminia Bielefeld) 26515 Schwarzwald Stadion (SC Freiburg) 24000 An der Alten Försterei (1. FC Union Berlin) 22012

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/1216.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#C9C9C9"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "association football venue"}, "y": {"type": "quantitative", "axis": {"title": "Capacity"}, "field": "Capacity"}}, "title": ["Stadiums of the clubs of German soccer Bundesliga", "by capacity 2020/21 season"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Signal Iduna Park has the biggest capacity whereas An Der Alten Forsterei has the smallest capacity.

Chart data: association football venue Capacity Signal Iduna Park (Borussia Dortmund) 81365 Allianz Arena (FC Bayern Munich) 75024 Olympiastadion (Hertha BSC Berlin) 74400 Veltins Arena (FC Schalke 04) 62271 Mercedes-Benz Arena (VfB Stuttgart) 60449 Borussia-Park (Borussia Mönchengladbach) 54022 Deutsche Bank Park (Eintracht Frankfurt) 51500 Red Bull Arena (Leipzig) 42558 Wohninvest Weserstadion (SV Werder Bremen) 42100 Opel Arena (1. FSV Mainz 05) 34000 WWK Arena (FC Augsburg) 30660 WWK ARENA (FC Augsburg) 30660 BayArena (Bayer 04 Leverkusen) 30210 PreZero Arena (TSG Hoffeneim) 30150 Volkswagen Arena (VfL Wolfsburg) 30000 SchücoArena (Arminia Bielefeld) 26515 Schwarzwald Stadion (SC Freiburg) 24000 An der Alten Försterei (1. FC Union Berlin) 22012

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/1216.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#C9C9C9"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "association football venue"}, "y": {"type": "quantitative", "axis": {"title": "Capacity"}, "field": "Capacity"}}, "title": ["Stadiums of the clubs of German soccer Bundesliga", "by capacity 2020/21 season"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Revenue between 2007 and 2009 went down by almost 3000 million dollars. Since 2009-2015 there has been a steady increase in revenue peaking at about 13000 million dollars.

Chart data: Year Revenue (in million U.S. dollars) Dec 31, 2005 12783 Dec 31, 2006 13017 Dec 31, 2007 11599 Dec 31, 2008 10393 Dec 31, 2009 10405 Dec 31, 2010 10700 Dec 31, 2011 11135 Dec 31, 2012 11652 Dec 31, 2013 12290 Dec 31, 2014 12955

Vega-Lite specification:
{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "data/12174.tsv"}, "mark": "line", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Revenue (in million U.S. dollars)"}, "field": "Revenue (in million U\\.S\\. dollars)"}}, "title": ["Nevada casino gaming market revenue from", "2006 to 2015 (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: All of the cruise liners have a good score of 80 or more. Crystal ocean cruises has the best score by a minimal amount, with Viking ocean cruises next.

Chart data: midsize-ship cruise lines Score* Crystal Ocean Cruises 96.06 Viking Ocean Cruises 95.14 Seabourn Cruise Lines 93.29 Regent Seven Seas Cruises 91.1 Oceania Cruises 87.92 Silversea Cruises 87.91 Azamara Club Cruises 87.9 Holland America Line 87.38 Cunard Line 86.85 Celebrity Cruise 86.1 P&O Cruises 85.38 MSC Cruises 85.17 Bahamas Paradise Cruise Line 84.39 Marella Cruises 84.21 Norwegian Cruise Line 82.9 Princess Cruises 81.15

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/12177.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#8ca252"}, "x": {"type": "nominal", "axis": {"labelAngle": -90}, "bin": false, "field": "midsize-ship cruise lines"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Score*"}, "field": "Score*"}}, "title": ["Best-rated midsize-ship cruise lines by", "travelers in the United States as of October", "2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The Uusimaa region has the largest number of registered cars (700,000) followed by southwest Finland and Pirkanmaa (250,000). All of the other regions each have less than 200,000 registered cars.

Chart data: Number of registered passenger cars region of Finland 710457 Uusimaa 249883 Pirkanmaa 245531 Southwest Finland 197087 North Ostrobothnia 137118 Central Finland 123537 Satakunta 123208 North Savo 110550 South Ostrobothnia 100461 Päijät-Häme 100336 Ostrobothnia 96826 Kymenlaakso 93805 Kanta-Häme 93223 Lapland 84769 North Karelia 78207 South Savo 70853 South Karelia 38826 Kainuu 36365 Central Ostrobothnia

Vega-Lite specification:
{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "data/12182.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#94aace"}, "x": {"type": "quantitative", "axis": {"title": "Number of registered passenger cars"}, "field": "Number of registered passenger cars"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "region of Finland"}}, "title": ["Number of registered passenger cars on the", "road in Finland in 2018 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The most popular year is 2016. The least popular year is 2010. 10 of the 11 years stated had more than 2 million viewers.

Chart data: Number of TV viewers in millions Year 2.6 2019* 2.58 2018 2.85 2017 3.63 2016 3.28 2015 3.36 2014 3.37 2013 3.23 2012 2.88 2011 1.69 2010 3.12 2009

Vega-Lite specification:
{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "data/12183.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#f1e2cc"}, "x": {"type": "quantitative", "axis": {"title": "Number of TV viewers in millions"}, "field": "Number of TV viewers in millions"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Number of TV viewers of the Eurovision Song", "Contest in Sweden from 2009 to 2019 (in millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Youth unemployment fell from 0.5 in the year 2000 to about 0.22 in about 2008.  It has since risen to 0.3.

Chart data: Year Youth unemployment rate Dec 31, 1998 0.4813 Dec 31, 1999 0.5056 Dec 31, 2000 0.4706 Dec 31, 2001 0.459 Dec 31, 2002 0.4347 Dec 31, 2003 0.3418 Dec 31, 2004 0.3071 Dec 31, 2005 0.239 Dec 31, 2006 0.2733 Dec 31, 2007 0.2395 Dec 31, 2008 0.2151 Dec 31, 2009 0.2184 Dec 31, 2010 0.2252 Dec 31, 2011 0.2755 Dec 31, 2012 0.2502 Dec 31, 2013 0.2534 Dec 31, 2014 0.2973 Dec 31, 2015 0.2559 Dec 31, 2016 0.2964 Dec 31, 2017 0.2966 Dec 31, 2018 0.2951 Dec 31, 2019 0.2966

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/12185.tsv"}, "mark": "line", "encoding": {"color": {"value": "#a6761d"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Youth unemployment rate"}, "field": "Youth unemployment rate"}}, "title": ["Algeria : Youth unemployment rate from 1999", "to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: I can see that in 2010, the poverty level was much higher, by overall does not seem to stay high for too long.

Chart data: Response Percentage of population Dec 31, 1999 0.107 Dec 31, 2000 0.104 Dec 31, 2001 0.085 Dec 31, 2002 0.097 Dec 31, 2003 0.09 Dec 31, 2004 0.115 Dec 31, 2005 0.103 Dec 31, 2006 0.101 Dec 31, 2007 0.106 Dec 31, 2008 0.114 Dec 31, 2009 0.127 Dec 31, 2010 0.115 Dec 31, 2011 0.118 Dec 31, 2012 0.123 Dec 31, 2013 0.122 Dec 31, 2014 0.102 Dec 31, 2015 0.119 Dec 31, 2016 0.113 Dec 31, 2017 0.11 Dec 31, 2018 0.102

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/12189.tsv"}, "mark": "line", "encoding": {"color": {"value": "#E044A7"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Percentage of population"}, "field": "Percentage of population"}}, "title": ["Poverty rate in Vermont from 2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: This bar chart shows the increase or decrease in sales of ethnic hair care brands in America. From this chart you can see that the vast majority of these brands have had a decrease in sales while only a few have a positive percentage change.

Chart data: Brand Percent change in sales Organic Root Stimulator −0.116 SoftSheen-Carson Dark & Lovely −0.112 Africa's Best −0.093 Luster's Pink Smooth Touch −0.084 African Pride Olive Miracle 0.154 SoftSheen-Carson Optimum Care −0.195 Ultra Sheen Supreme −0.157 Soft & Beautiful Just for Me −0.215 Luster's S-Curl −0.054 Africa's Best Organic −0.086 Luster's Pink 0.049 Motions −0.192 Pro-Line Comb-Thru −0.052 Dr. Miracle's −0.346 Dr. Miracle's Thermaceutical −0.201 Smart Perm 0.1 Soft and Beautiful Botanicals −0.29 Luster's Pink ShortLooks 0.137 Pro-Line Soft & Beautiful −0.314

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/12194.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#f0027f"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Brand"}, "y": {"type": "quantitative", "axis": {"title": "Percent change in sales"}, "field": "Percent change in sales"}}, "title": ["Sales growth of leading 20 ethnic hair care", "brands in the United States in 2014"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: African Pride Olive Miracle, Luster's Pink, Luster's Pink Short Cuts and Smart Perm have had increases in sales in 2014. The remaining 14 brands had decreases.

Chart data: Brand Percent change in sales Organic Root Stimulator −0.116 SoftSheen-Carson Dark & Lovely −0.112 Africa's Best −0.093 Luster's Pink Smooth Touch −0.084 African Pride Olive Miracle 0.154 SoftSheen-Carson Optimum Care −0.195 Ultra Sheen Supreme −0.157 Soft & Beautiful Just for Me −0.215 Luster's S-Curl −0.054 Africa's Best Organic −0.086 Luster's Pink 0.049 Motions −0.192 Pro-Line Comb-Thru −0.052 Dr. Miracle's −0.346 Dr. Miracle's Thermaceutical −0.201 Smart Perm 0.1 Soft and Beautiful Botanicals −0.29 Luster's Pink ShortLooks 0.137 Pro-Line Soft & Beautiful −0.314

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/12194.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#f0027f"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Brand"}, "y": {"type": "quantitative", "axis": {"title": "Percent change in sales"}, "field": "Percent change in sales"}}, "title": ["Sales growth of leading 20 ethnic hair care", "brands in the United States in 2014"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is a year on year increase which is predicted to continue to rise at the same rate as it currently is. In 2018 it reached a total of 50 million inhabitants.

Chart data: Year Inhabitants in millions 2025* 53.26 2024* 52.79 2023* 52.32 2022* 51.85 2021* 51.39 2020* 50.88 2019 50.37 2018 49.83 2017 49.29 2016 48.75 2015 48.2

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/12195.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bd9e39"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Inhabitants in millions"}, "field": "Inhabitants in millions"}}, "title": ["Colombia : Total population from 2015 to", "2025 (in million inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The DROC has the highest prison occupancy level (it is not stated whether this is per capita or based on raw numbers).  Closely behind are Haiti, Bolivia, and Phillipines.  China, Russia, and the U.S. are not represented in the graph.

Chart data: Occupancy level Country 6.169 Republic of Congo 4.636 Philippines 4.544 Haiti 3.72 Guatemala 3.639 Bolivia 3.192 Uganda 3.03 Zambia 2.866 Lebanon 2.57 Burundi 2.553 Sudan 2.413 Peru 2.374 Madagascar 2.338 Grenada 2.323 Chad 2.233 Mali 2.221 Liberia 2.202 Sierra Leone 2.152 El Salvador 2.151 Bangladesh 2.107 Mozambique

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/12209.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#000000"}, "x": {"type": "quantitative", "axis": {"title": "Occupancy level"}, "field": "Occupancy level"}, "y": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "Country"}}, "title": ["Countries with the highest prison occupancy", "level as of June 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The greatest number of Presidents elected between 1789 and 2021 from one state, originated from Virginia.  Thirteen states were responsible for just one elected US President between 1789 and 2021.

Chart data: State Number of presidents Virginia 8 Ohio 7 New York 5 Massachusetts 4 North Carolina 2 Pennsylvania 2 Texas 2 Vermont 2 Arkansas 1 California 1 Connecticut 1 Georgia 1 Hawaii 1 Illinois 1 Iowa 1 Kentucky 1 Missouri 1 Nebraska 1 New Hampshire 1 New Jersey 1 South Carolina* 1

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/12212.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bab0ac"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "State"}, "y": {"type": "quantitative", "axis": {"title": "Number of presidents"}, "field": "Number of presidents"}}, "title": ["Number of U.S. presidents born in each state", ", from those elected between 1789 and 2021"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of viewers increased from zero in July 2019 to nearly 40,000 by November 2019.  This then declined to just over 10,000 in January 2020.  In February 2020, viewers increased rapidly to 120,000.  Since February 2020, numbers have decreased, but have not fallen below 70,000 at any point.

Chart data: Month Number of viewers in thousands Jun 30, 2019 0.73 Jul 31, 2019 4.23 Aug 31, 2019 16.92 Sep 30, 2019 31.13 Oct 31, 2019 37.75 Nov 30, 2019 23.8 Dec 31, 2019 12.13 Jan 31, 2020 12.93 Feb 29, 2020 129.59 Mar 31, 2020 111.43 Apr 30, 2020 123.03 May 31, 2020 120.54 Jun 30, 2020 118.19 Jul 31, 2020 113.27 Aug 31, 2020 102.65 Sep 30, 2020 102.44 Oct 31, 2020 69.79 Nov 30, 2020 88.47

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/12213.tsv"}, "mark": "area", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Number of viewers in thousands"}, "field": "Number of viewers in thousands"}}, "title": ["Average viewers of Call of Duty : Warzone", "on Twitch worldwide from September 2019 to", "December 2020 (in 1000s)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The growth rate of HICP April to September is above 0.010. In August, July and October the HICP growth rate were the highest.

Chart data: Month Growth rate of HICP Dec '18 0.017 Nov '18 0.02 Oct '18 0.022 Sep '18 0.021 Aug '18 0.022 Jul '18 0.022 Jun '18 0.021 May '18 0.02 Apr '18 0.015 Mar '18 0.015 Feb '18 0.014 Jan '18 0.016

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/12215.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#1b9e77"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Growth rate of HICP"}, "field": "Growth rate of HICP"}}, "title": ["Monthly inflation rate in the European Union", "28 from January to December 2018 (HICP compared", "to same month in the previous year)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: from 2000 the median income in Canada has almost doubled (although there are dips), from 45,000 to over 80,000.

Chart data: Year Median income in Canadian dollars Dec 31, 1999 50800 Dec 31, 2000 53500 Dec 31, 2001 55000 Dec 31, 2002 56000 Dec 31, 2003 58100 Dec 31, 2004 60600 Dec 31, 2005 63600 Dec 31, 2006 66550 Dec 31, 2007 68860 Dec 31, 2008 68410 Dec 31, 2009 69860 Dec 31, 2010 72240 Dec 31, 2011 74540 Dec 31, 2012 76550 Dec 31, 2013 78870 Dec 31, 2014 80940 Dec 31, 2015 82110 Dec 31, 2016 84950 Dec 31, 2017 87930

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/1221.tsv"}, "mark": "area", "encoding": {"color": {"value": "#fc4f30"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Median income in Canadian dollars"}, "field": "Median income in Canadian dollars"}}, "title": ["Median annual family income in Canada from", "2000 to 2018 (in Canadian dollar)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2019, the Willis Tower in Chicago had the most floors of any skyscraper in the usa, with almost 120 floors. The majority of the largest u.s skyscrapers in 2019 were located in New York.

Chart data: Number of floors Building (city) 108 Willis Tower(Chicago) 104 One World Trade Center(New York City) 102 Empire State Building(New York City) 100 875 North Michigan Avenue(Chicago) 98 Trump International Hotel & Tower(Chicago) 96 432 Park Avenue(New York City) 83 Aon Center(Chicago) 77 Chrysler Building(New York City) 73 53W53(New York) 73 Wilshire Grand Center (Los Angeles) 73 30 Hudson Yards(New York)

Vega-Lite specification:
{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "data/12223.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e6f5c9"}, "x": {"type": "quantitative", "axis": {"title": "Number of floors"}, "field": "Number of floors"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Building (city)"}}, "title": ["Ranking of skyscrapers in the U.S. as of", "2019 , by number of floors"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Levels of employment in Italy have remained fairly steady over the entire time period show in the chart. However, there has been a slight steady increase in employment levels in Italy throughout the years 2012-2020.

Chart data: Year Employment in millions 2020* 23.35 2019* 23.31 2018 23.22 2017 23.02 2016 22.76 2015 22.47 2014 22.28 2013 22.19 2012 22.57 2011 22.6 2010 22.53

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/12225.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#beaed4"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Employment in millions"}, "field": "Employment in millions"}}, "title": ["Italy : Employment from 2010 to 2020 (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Employment in 2020 is higher than it was in 2010. There is a slight dip in employment in the years 2013 to 2015 but then a small but steady increase up to 2018. Between 2018 and 2020 employment was just about the same rate.

Chart data: Year Employment in millions 2020* 23.35 2019* 23.31 2018 23.22 2017 23.02 2016 22.76 2015 22.47 2014 22.28 2013 22.19 2012 22.57 2011 22.6 2010 22.53

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/12225.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#beaed4"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Employment in millions"}, "field": "Employment in millions"}}, "title": ["Italy : Employment from 2010 to 2020 (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Employment has remained largely steady in Italy over ten years between 2010 and 2020. There was a slight decline in employment in 2013, but this steadily increased over the coming years. The highest rates of employment can be seen in 2019 and 2020.

Chart data: Year Employment in millions 2020* 23.35 2019* 23.31 2018 23.22 2017 23.02 2016 22.76 2015 22.47 2014 22.28 2013 22.19 2012 22.57 2011 22.6 2010 22.53

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/12225.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#beaed4"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Employment in millions"}, "field": "Employment in millions"}}, "title": ["Italy : Employment from 2010 to 2020 (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The team with the most amount of followers is San Francisco shock with 110,000 followers.  The team with the least followers is florida mayhem. Most of the other teams have around 40,000 followers.

Chart data: Number of followers in thousands esports team 112 San Francisco Shock 78.2 Dallas Fuel 75.2 Houston Outlaws 63.5 Seoul Dynasty 53.4 London Spitfire 51.2 Los Angeles Valiant 44.3 New York Exclesior 42.5 Los Angeles Gladiators 41.2 Boston Uprising 40.7 Philadelphia Fusion 36 Shanghai Dragons 33.4 Florida Mayhem

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/12226.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#b79a20"}, "x": {"type": "quantitative", "axis": {"title": "Number of followers in thousands"}, "field": "Number of followers in thousands"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "esports team"}}, "title": ["Leading Overwatch League teams on Twitter", "worldwide as of February 2018 , by number", "of followers (in 1,000s)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The San sanfracisco shock has 110000 followers that is the highest followers.

Chart data: Number of followers in thousands esports team 112 San Francisco Shock 78.2 Dallas Fuel 75.2 Houston Outlaws 63.5 Seoul Dynasty 53.4 London Spitfire 51.2 Los Angeles Valiant 44.3 New York Exclesior 42.5 Los Angeles Gladiators 41.2 Boston Uprising 40.7 Philadelphia Fusion 36 Shanghai Dragons 33.4 Florida Mayhem

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/12226.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#b79a20"}, "x": {"type": "quantitative", "axis": {"title": "Number of followers in thousands"}, "field": "Number of followers in thousands"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "esports team"}}, "title": ["Leading Overwatch League teams on Twitter", "worldwide as of February 2018 , by number", "of followers (in 1,000s)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: All universities scored above 0.7. Cambridge and Oxford both score very highly.

Chart data: Complete University Guide score higher education institution 1 University of Cambridge 0.99 University of Oxford 0.96 University of St Andrews 0.94 London School of Economics 0.91 Imperial College London 0.9 Loughborough University 0.9 Durham University 0.89 Lancaster University 0.87 University of Bath 0.86 University College London 0.85 University of Warwick 0.83 University of Exeter 0.81 University of Birmingham 0.81 University of Bristol 0.81 University of Edinburgh 0.8 University of Leeds 0.8 University of Manchester 0.8 University of Southampton 0.79 University of Glasgow 0.77 King's College London

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/12235.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "quantitative", "axis": {"title": "Complete University Guide score"}, "field": "Complete University Guide score"}, "y": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "higher education institution"}}, "title": ["The Complete University Guide 's top twenty", "universities in the United Kingdom in 2021", ", by overall score"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: University of Cambridge has the highest complete iniversity guide score for 2021 of 1.0 in comparison to Kings college London which has a score of around 0.7.

Chart data: Complete University Guide score higher education institution 1 University of Cambridge 0.99 University of Oxford 0.96 University of St Andrews 0.94 London School of Economics 0.91 Imperial College London 0.9 Loughborough University 0.9 Durham University 0.89 Lancaster University 0.87 University of Bath 0.86 University College London 0.85 University of Warwick 0.83 University of Exeter 0.81 University of Birmingham 0.81 University of Bristol 0.81 University of Edinburgh 0.8 University of Leeds 0.8 University of Manchester 0.8 University of Southampton 0.79 University of Glasgow 0.77 King's College London

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/12235.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "quantitative", "axis": {"title": "Complete University Guide score"}, "field": "Complete University Guide score"}, "y": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "higher education institution"}}, "title": ["The Complete University Guide 's top twenty", "universities in the United Kingdom in 2021", ", by overall score"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The chart shows that University of Cambridge is the highest scoring top 20 university, closely followed by University of Oxford. These are the only unis to be close to the maximum score, while most of the others hover at or around 80%.

Chart data: Complete University Guide score higher education institution 1 University of Cambridge 0.99 University of Oxford 0.96 University of St Andrews 0.94 London School of Economics 0.91 Imperial College London 0.9 Loughborough University 0.9 Durham University 0.89 Lancaster University 0.87 University of Bath 0.86 University College London 0.85 University of Warwick 0.83 University of Exeter 0.81 University of Birmingham 0.81 University of Bristol 0.81 University of Edinburgh 0.8 University of Leeds 0.8 University of Manchester 0.8 University of Southampton 0.79 University of Glasgow 0.77 King's College London

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/12235.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "quantitative", "axis": {"title": "Complete University Guide score"}, "field": "Complete University Guide score"}, "y": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "higher education institution"}}, "title": ["The Complete University Guide 's top twenty", "universities in the United Kingdom in 2021", ", by overall score"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}