delen/vistext huggingface dataset:
Chart description: Rossmann stores have been very successful opening many more stores outside of Germany.

Chart data: Year Turkey Dec 31, 2009 4 Dec 31, 2010 8 Dec 31, 2011 16 Dec 31, 2012 27 Dec 31, 2013 31 Dec 31, 2014 50 Dec 31, 2015 66 Dec 31, 2016 94 Dec 31, 2017 112 Dec 31, 2018 119

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": "multiColumn/data/1433.tsv"}, "mark": "line", "encoding": {"color": {"value": "#e2ddf2"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Turkey"}, "field": "Turkey"}}, "title": ["Number of Rossmann stores outside of Germany", "from 2008 to 2019 , by country"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Up to 2014, growth was steady.  Following 2014 growth has accelerated. In 2018, growth seems to have steadied a little.

Chart data: Year Turkey Dec 31, 2009 4 Dec 31, 2010 8 Dec 31, 2011 16 Dec 31, 2012 27 Dec 31, 2013 31 Dec 31, 2014 50 Dec 31, 2015 66 Dec 31, 2016 94 Dec 31, 2017 112 Dec 31, 2018 119

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": "multiColumn/data/1433.tsv"}, "mark": "line", "encoding": {"color": {"value": "#e2ddf2"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Turkey"}, "field": "Turkey"}}, "title": ["Number of Rossmann stores outside of Germany", "from 2008 to 2019 , by country"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Rwandan shares of economic sectors in GDP from 2009 to 2019 has remained relatively steady around 0.175.

Chart data: Year Industry Dec 31, 2008 0.1582 Dec 31, 2009 0.1647 Dec 31, 2010 0.1833 Dec 31, 2011 0.184 Dec 31, 2012 0.1778 Dec 31, 2013 0.1773 Dec 31, 2014 0.1764 Dec 31, 2015 0.1703 Dec 31, 2016 0.1728 Dec 31, 2017 0.1723 Dec 31, 2018 0.18

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": "multiColumn/data/1449.tsv"}, "mark": "area", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Industry"}, "field": "Industry"}}, "title": ["Rwanda : Share of economic sectors in the", "gross domestic product (GDP) from 2009 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There was, and still seems to be, and upward trend 8n gate revenues.  The dip in 2011/12 shows that people were not attending as many events, although the dip is not hugely significant.

Chart data: Year North America Dec 31, 2005 14.51 Dec 31, 2006 15.6 Dec 31, 2007 15.98 Dec 31, 2008 15.55 Dec 31, 2009 15.71 Dec 31, 2010 15.33 Dec 31, 2011 15.86 Dec 31, 2012 16.63 Dec 31, 2013 17.21 Dec 31, 2014 17.84

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": "multiColumn/data/1479.tsv"}, "mark": "area", "encoding": {"color": {"value": "#118DFF"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "North America"}, "field": "North America"}}, "title": ["Total gate revenues from sporting events", "worldwide by region from 2006 to 2015 (in", "billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: As the year go on the governments spending and revenue increases year on year.

Chart data: Spending Year 104.29 2024* 101.61 2023* 98.74 2022* 96.11 2021* 93.69 2020* 91.39 2019* 88.63 2018 88.88 2017 83.56 2016 86.49 2015 89.52 2014

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": "multiColumn/data/1485.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e5d8bd"}, "x": {"type": "quantitative", "axis": {"title": "Spending"}, "field": "Spending"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Portugal : Government revenue and spending", "from 2014 to 2024 (in billion euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The southern regions own more cats however London is lower.

Chart data: Cats region in the United Kingdom 0.15 North East 0.17 North West 0.16 Yorks&Humber 0.19 East Midlands 0.18 West Midlands 0.18 East of England 0.14 London 0.2 South East 0.21 South West 0.18 Wales 0.14 Scotland 0.12 Northern Ireland

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": "multiColumn/data/1495.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#7570b3"}, "x": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Cats"}, "field": "Cats"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "region in the United Kingdom"}}, "title": ["Share of households owning pets by type", "and region in the United Kingdom (UK) from", "2016 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of firms with over 250 employees dropped slightly between the years 2001 and 2004 after a small increase in the year 2000.  After 2004, the number of firms with over 250 employees increased at a steady rate each year until 2020.

Chart data: Year Firms with 250 and more employees Dec 31, 1999 0.5199 Dec 31, 2000 0.5224 Dec 31, 2001 0.5166 Dec 31, 2002 0.5143 Dec 31, 2003 0.513 Dec 31, 2004 0.5151 Dec 31, 2005 0.5166 Dec 31, 2006 0.5191 Dec 31, 2007 0.5233 Dec 31, 2008 0.5247 Dec 31, 2009 0.5249 Dec 31, 2010 0.5279 Dec 31, 2011 0.5299 Dec 31, 2012 0.533 Dec 31, 2013 0.5346 Dec 31, 2014 0.5371 Dec 31, 2015 0.5392 Dec 31, 2016 0.5415 Dec 31, 2017 0.5453 Dec 31, 2018 0.5477

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": "multiColumn/data/1503.tsv"}, "mark": "area", "encoding": {"color": {"value": "#d67195"}, "x": {"type": "temporal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Firms with 250 and more employees"}, "field": "Firms with 250 and more employees"}}, "title": ["Distribution of employment in the private", "sector , by firm size in the United States", "2000 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The 3 highest earners are soccer players. Boxing doesn't have many entries but the one entry it does have is a relatively high earner. Football and soccer have the same number of entries, though football's average earnings are slightly lower than soccer.

Chart data: Highest paid athletes Salary/Winnings Roger Federer (tennis) 6.3 Cristiano Ronaldo (soccer) 60 Lionel Messi (soccer) 72 Neymar (soccer) 70.5 LeBron James (basketball) 28.2 Stephen Curry (basketball) 30.4 Kevin Durant (basketball) 28.9 Tiger Woods (golf) 2.3 Kirk Cousins (football) 58 Carson Wentz (football) 55.1 Tyson Fury (boxing) 50 Russell Westbrook (basketball) 29 Lewis Hamilton (auto racing) 42 Rory McIlroy (golf) 22 Jared Goff (football) 47

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": "multiColumn/data/1508.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec008b"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Highest paid athletes"}, "y": {"type": "quantitative", "axis": {"title": "Salary/Winnings"}, "field": "Salary/Winnings"}}, "title": ["Highest paid athletes by earnings from salary", "and endorsements worldwide in 2019/20 (in", "million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The graph shows that on average it is the football/soccer players that are the highest paid. Golf and tennis players are the worst.

Chart data: Highest paid athletes Salary/Winnings Roger Federer (tennis) 6.3 Cristiano Ronaldo (soccer) 60 Lionel Messi (soccer) 72 Neymar (soccer) 70.5 LeBron James (basketball) 28.2 Stephen Curry (basketball) 30.4 Kevin Durant (basketball) 28.9 Tiger Woods (golf) 2.3 Kirk Cousins (football) 58 Carson Wentz (football) 55.1 Tyson Fury (boxing) 50 Russell Westbrook (basketball) 29 Lewis Hamilton (auto racing) 42 Rory McIlroy (golf) 22 Jared Goff (football) 47

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": "multiColumn/data/1508.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec008b"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Highest paid athletes"}, "y": {"type": "quantitative", "axis": {"title": "Salary/Winnings"}, "field": "Salary/Winnings"}}, "title": ["Highest paid athletes by earnings from salary", "and endorsements worldwide in 2019/20 (in", "million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: People answering questions about their religious beliefs have increased since the year 2000.

Chart data: Response Undesignated Dec 31, 1947 0.03 Dec 31, 1949 0.02 Dec 31, 1954 0.01 Dec 31, 1959 0.01 Dec 31, 1964 0 Dec 31, 1969 0 Dec 31, 1974 0.01 Dec 31, 1979 0 Dec 31, 1984 0.01 Dec 31, 1989 0.02 Dec 31, 1994 0.02 Dec 31, 1999 0.02 Dec 31, 2004 0.02 Dec 31, 2009 0.04 Dec 31, 2010 0.03 Dec 31, 2011 0.03 Dec 31, 2012 0.04 Dec 31, 2013 0.04 Dec 31, 2014 0.04 Dec 31, 2015 0.02 Dec 31, 2016 0.04 Dec 31, 2017 0.04 Dec 31, 2018 0.03

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": "multiColumn/data/1513.tsv"}, "mark": "line", "encoding": {"color": {"value": "#e6ab02"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Undesignated"}, "field": "Undesignated"}}, "title": ["What is your religious preference : Protestant", ", Roman Catholic , Jewish , another religion", ", or no religion ?"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Nikes revenue steadily increases over time. Nike makes a profit of approximately 1800 million dollars in 2010 which rises steadily to approximately 5000 million in 2018.

Chart data: Year Apparel Dec 31, 2008 1740 Dec 31, 2009 1740 Dec 31, 2010 2103 Dec 31, 2011 2993 Dec 31, 2012 3591 Dec 31, 2013 3937 Dec 31, 2014 4410 Dec 31, 2015 4746 Dec 31, 2016 4886 Dec 31, 2017 4938 Dec 31, 2018 5260 Dec 31, 2019 4639

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": "multiColumn/data/152.tsv"}, "mark": "line", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Apparel"}, "field": "Apparel"}}, "title": ["Nike 's North American revenue from 2009", "to 2020 , by segment (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The highest distribution of gross domestic product between 2009 and 2019 was in 2016 with the lowest being in 2011. The distribution of gross domestic product between 2009 and 2019 has never dropped below the high 0.4's and is usually in the 0.5's.

Chart data: Year Services Dec 31, 2008 0.5098 Dec 31, 2009 0.5079 Dec 31, 2010 0.4924 Dec 31, 2011 0.5019 Dec 31, 2012 0.5237 Dec 31, 2013 0.5415 Dec 31, 2014 0.5812 Dec 31, 2015 0.5979 Dec 31, 2016 0.558 Dec 31, 2017 0.5202 Dec 31, 2018 0.4973

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": "multiColumn/data/153.tsv"}, "mark": "line", "encoding": {"color": {"value": "#a6761d"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Services"}, "field": "Services"}}, "title": ["Nigeria : Distribution of gross domestic", "product (GDP) across economic sectors from", "2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Year on year sales have increased. All quarters have shown growth in sales across 2016-2018 with exception of Q3. 2016 quarters had a flat seasonality where as 2017and 2018 have a more pronounced seasonality.

Chart data: quarter Component 1Q '16 0.14 2Q '16 0.14 3Q '16 0.15 4Q '16 0.14 1Q '17 0.15 2Q '17 0.17 3Q '17 0.19 4Q '17 0.19 1Q '18 0.25 2Q '18 0.21 3Q '18 0.18 4Q '18 0.21

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": "multiColumn/data/1551.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#744EC2"}, "x": {"type": "nominal", "axis": {"labelAngle": -90}, "bin": false, "field": "quarter"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Component"}, "field": "Component"}}, "title": ["Asus quarterly sales share worldwide from", "2016 to 2020 , by product type"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Gdp remained at a steady rate from 2010 to 2016 when it peaked since then it has started to drop to 2019 where at its lowest level.

Chart data: Year Services Dec 31, 2008 0.5258 Dec 31, 2009 0.5213 Dec 31, 2010 0.5307 Dec 31, 2011 0.5196 Dec 31, 2012 0.5247 Dec 31, 2013 0.5184 Dec 31, 2014 0.5208 Dec 31, 2015 0.5298 Dec 31, 2016 0.5215 Dec 31, 2017 0.5163 Dec 31, 2018 0.4925

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": "multiColumn/data/1562.tsv"}, "mark": "line", "encoding": {"color": {"value": "#ab5787"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Services"}, "field": "Services"}}, "title": ["Cameroon : Distribution of gross domestic", "product (GDP) across economic sectors from", "2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: product has declined since 2016, before then it changed a little but looks relatively steady but in 2016 onwards it clearly dips.

Chart data: Year Services Dec 31, 2007 0.7232 Dec 31, 2008 0.7245 Dec 31, 2009 0.7247 Dec 31, 2010 0.7301 Dec 31, 2011 0.7166 Dec 31, 2012 0.7177 Dec 31, 2013 0.7288 Dec 31, 2014 0.7276 Dec 31, 2015 0.7205 Dec 31, 2016 0.7082 Dec 31, 2017 0.6997

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": "multiColumn/data/1563.tsv"}, "mark": "line", "encoding": {"color": {"value": "#C9C9C9"}, "x": {"type": "temporal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Services"}, "field": "Services"}}, "title": ["Cuba : Distribution of gross domestic product", "(GDP) across economic sectors from 2008 to", "2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: there was a spike in distribution during 2015 or 2016, before showing a sudden dip.

Chart data: Year Services Dec 31, 2008 0.3964 Dec 31, 2009 0.3819 Dec 31, 2010 0.394 Dec 31, 2011 0.3952 Dec 31, 2012 0.4119 Dec 31, 2013 0.4287 Dec 31, 2014 0.4735 Dec 31, 2015 0.481 Dec 31, 2016 0.4566 Dec 31, 2017 0.4399 Dec 31, 2018 0.4594

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": "multiColumn/data/1572.tsv"}, "mark": "area", "encoding": {"color": {"value": "#744EC2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Services"}, "field": "Services"}}, "title": ["Algeria : Distribution of gross domestic", "product (GDP) across economic sectors from", "2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Year on year the money increases at a constant steady rate. Given some of the dates are in the future it can only be forecast not sold fact.

Chart data: Hardware Year 24 2027* 23 2026* 22 2025* 20 2024* 19 2023* 18 2022* 16 2021* 15 2020* 14 2019* 12 2018* 10 2017 9 2016

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": "multiColumn/data/1601.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ad494a"}, "x": {"type": "quantitative", "axis": {"title": "Hardware"}, "field": "Hardware"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Big data revenue worldwide from 2016 to", "2027 , by major segment (in billion U.S.", "dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: With current figures. It is predicted that by 2027 worldwide big data revenue will climb to over 20 billion US dollars, more than doubling in ten years.

Chart data: Hardware Year 24 2027* 23 2026* 22 2025* 20 2024* 19 2023* 18 2022* 16 2021* 15 2020* 14 2019* 12 2018* 10 2017 9 2016

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": "multiColumn/data/1601.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ad494a"}, "x": {"type": "quantitative", "axis": {"title": "Hardware"}, "field": "Hardware"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Big data revenue worldwide from 2016 to", "2027 , by major segment (in billion U.S.", "dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: As the years increase, so does the worldwide big data revenue. 2027 has over double the revenue of 2016.

Chart data: Hardware Year 24 2027* 23 2026* 22 2025* 20 2024* 19 2023* 18 2022* 16 2021* 15 2020* 14 2019* 12 2018* 10 2017 9 2016

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": "multiColumn/data/1601.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ad494a"}, "x": {"type": "quantitative", "axis": {"title": "Hardware"}, "field": "Hardware"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Big data revenue worldwide from 2016 to", "2027 , by major segment (in billion U.S.", "dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The chart shows that the busier tram lines are King's cross and water loo this data allows the workers to identify areas of support needed.

Chart data: 2017  busiest Underground stations in London 97.9 King's Cross St. Pancras 91.3 Waterloo 84.1 Oxford Circus 79.4 Victoria 69.1 London Bridge 67.7 Liverpool Street 62 Stratford 61.8 Bank & Monument* 50.9 Canary Wharf 48.8 Paddington 43.1 Euston 41.3 Tottenham Court Road 40.8 Piccadily Circus 39.3 Green Park 38.8 Bond Street

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": "multiColumn/data/1604.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#1A1A1A"}, "x": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "2017"}, "field": "2017"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": " busiest Underground stations in London"}}, "title": ["Busiest London Underground stations by number", "of passengers in London (UK) 2016 - 2017", "(in million entries and exits)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The two brands with the most new car registrations in France between 2016 and 2018 were Peugeot and Renault. Renault had over 400,000 registrations, and Peugeot followed just below 400,000. The next highest was Citroen with just over 200,000 new registrations. Volkswagen and Dacia both had around 140,000 new registrations. All other car brands in France had 100,000 new car registrations or less between 2016 and 2018.

Chart data: leading car brands 2018 Renaul  406222; leading car brands: Renault Peugeo  389518; leading car brands: Peugeot Citroë  213844; leading car brands: Citroën Volkswage  140313; leading car brands: Volkswagen Daci  140326; leading car brands: Dacia Toyot  97286; leading car brands: Toyota For  82633; leading car brands: Ford Nissa  59606; leading car brands: Nissan Fia  78226; leading car brands: Fiat Mercede  65808; leading car brands: Mercedes Aud  51582; leading car brands: Audi BM  57537; leading car brands: BMW Ope  71619; leading car brands: Opel KI  42313; leading car brands: KIA Hyunda  35542; leading car brands: Hyundai Skod  31423; leading car brands: Skoda Min  27378; leading car brands: Mini Sea  31219; leading car brands: Seat D  24004; leading car brands: DS

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": "multiColumn/data/1610.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#393b79"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "leading car brands"}, "y": {"type": "quantitative", "axis": {"title": "2018"}, "field": "2018"}}, "title": ["Number of new passenger car registrations", "of leading car brands in France between 2016", "and 2018 , by brand"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Most of the cars registered were from French vehicle companies. Peugeot, Renault and Citroen are the most popular cars.

Chart data: leading car brands 2018 Renaul  406222; leading car brands: Renault Peugeo  389518; leading car brands: Peugeot Citroë  213844; leading car brands: Citroën Volkswage  140313; leading car brands: Volkswagen Daci  140326; leading car brands: Dacia Toyot  97286; leading car brands: Toyota For  82633; leading car brands: Ford Nissa  59606; leading car brands: Nissan Fia  78226; leading car brands: Fiat Mercede  65808; leading car brands: Mercedes Aud  51582; leading car brands: Audi BM  57537; leading car brands: BMW Ope  71619; leading car brands: Opel KI  42313; leading car brands: KIA Hyunda  35542; leading car brands: Hyundai Skod  31423; leading car brands: Skoda Min  27378; leading car brands: Mini Sea  31219; leading car brands: Seat D  24004; leading car brands: DS

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": "multiColumn/data/1610.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#393b79"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "leading car brands"}, "y": {"type": "quantitative", "axis": {"title": "2018"}, "field": "2018"}}, "title": ["Number of new passenger car registrations", "of leading car brands in France between 2016", "and 2018 , by brand"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The line/area chart shows a steady incline over the years for the economic sector showing that it is a growing sector and hopeful for the future.

Chart data: Year Services Dec 31, 2009 0.2022 Dec 31, 2010 0.2088 Dec 31, 2011 0.2165 Dec 31, 2012 0.2236 Dec 31, 2013 0.2292 Dec 31, 2014 0.2354 Dec 31, 2015 0.2407 Dec 31, 2016 0.2558 Dec 31, 2017 0.2515 Dec 31, 2018 0.2569 Dec 31, 2019 0.2618

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": "multiColumn/data/1617.tsv"}, "mark": "area", "encoding": {"color": {"value": "#d67195"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "Services"}, "field": "Services"}}, "title": ["Laos : Distribution of employment by economic", "sector from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The average daily time spent watching TV for women in the UK decreased from 2010-2018.

Chart data: Year Women Dec 31, 2009 259 Dec 31, 2010 258 Dec 31, 2011 255 Dec 31, 2012 247 Dec 31, 2013 235 Dec 31, 2014 232 Dec 31, 2015 227 Dec 31, 2016 220 Dec 31, 2017 207 Dec 31, 2018 196

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": "multiColumn/data/1618.tsv"}, "mark": "area", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Women"}, "field": "Women"}}, "title": ["Average daily time spent watching TV per", "individual in the United Kingdom from 2010", "to 2019 , by gender (in minutes)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The average time watching tv has dropped from over 250 in 2010 to slightly under 200 in 2019.

Chart data: Year Women Dec 31, 2009 259 Dec 31, 2010 258 Dec 31, 2011 255 Dec 31, 2012 247 Dec 31, 2013 235 Dec 31, 2014 232 Dec 31, 2015 227 Dec 31, 2016 220 Dec 31, 2017 207 Dec 31, 2018 196

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": "multiColumn/data/1618.tsv"}, "mark": "area", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Women"}, "field": "Women"}}, "title": ["Average daily time spent watching TV per", "individual in the United Kingdom from 2010", "to 2019 , by gender (in minutes)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: For women, the average daily time spent watching television decreased steadily over the period, from over 250 minutes in 2010 to under 200 minutes in 2019.

Chart data: Year Women Dec 31, 2009 259 Dec 31, 2010 258 Dec 31, 2011 255 Dec 31, 2012 247 Dec 31, 2013 235 Dec 31, 2014 232 Dec 31, 2015 227 Dec 31, 2016 220 Dec 31, 2017 207 Dec 31, 2018 196

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": "multiColumn/data/1618.tsv"}, "mark": "area", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Women"}, "field": "Women"}}, "title": ["Average daily time spent watching TV per", "individual in the United Kingdom from 2010", "to 2019 , by gender (in minutes)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is not much that you can observe from this data alone. But as far as the chart reads, 2014 is the lowest and 2018 is the highest.

Chart data: Year Industry Dec 31, 2008 0.1152 Dec 31, 2009 0.1143 Dec 31, 2010 0.1119 Dec 31, 2011 0.1067 Dec 31, 2012 0.109 Dec 31, 2013 0.1052 Dec 31, 2014 0.1104 Dec 31, 2015 0.1167 Dec 31, 2016 0.1124 Dec 31, 2017 0.1177 Dec 31, 2018 0.1132

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": "multiColumn/data/1638.tsv"}, "mark": "line", "encoding": {"color": {"value": "#ab7fb4"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Industry"}, "field": "Industry"}}, "title": ["Luxembourg : Distribution of gross domestic", "product (GDP) across economic sectors from", "2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Musicals were the least popular choice of genre.  The most popular choice by genre were action, closely followed by adventure and comedy.

Chart data: Response Hispanic Comedy 0.85 Adventure 0.84 Action 0.87 Drama 0.77 Thriller/mystery 0.77 Crime 0.81 Documentary 0.71 Romantic comedy 0.66 Live-action 0.68 Animated 0.76 Fantasy 0.7 Sci-fi 0.66 Romance 0.62 Musicals 0.49 Horror 0.65

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": "multiColumn/data/1676.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#AB47BC"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Hispanic"}, "field": "Hispanic"}}, "title": ["Most popular movie genres among adults in", "the United States as of December 2018 , by", "ethnicity"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Imports of cement reduced significantly from 2005. From 2014 they were back up to 2005 levels and steadily increased.

Chart data: by manufacturers Year 935 2018 1114 2017 635 2015 227 2014 117 2013 61 2012 86 2011 61 2010 99 2009 283 2008 255 2007 124 2006 306 2005 609 2004 576 2003 966 2002 1182 2001

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": "multiColumn/data/1680.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#4572a7"}, "x": {"type": "quantitative", "axis": {"labelAngle": 90, "title": "by manufacturers"}, "field": "by manufacturers"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Annual amount of cement imported into Great", "Britain from 2001 to 2018 , by importer (in", "1,000 metric tons)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}