delen/vistext huggingface dataset:
Chart description: There are significant fluctuations between 2006 and 2019. The trend seems to be for it to slump, then recover, then slump again.

Chart data: Year Year-on-year change Dec 31, 2005 0.11 Dec 31, 2006 0.061 Dec 31, 2007 −0.008 Dec 31, 2008 0.059 Dec 31, 2009 0.059 Dec 31, 2010 0.057 Dec 31, 2011 0.086 Dec 31, 2012 0.066 Dec 31, 2013 0.069 Dec 31, 2014 0.036 Dec 31, 2015 0.061 Dec 31, 2016 0.075 Dec 31, 2017 0.11 Dec 31, 2018 0.093

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/7731.tsv"}, "mark": "line", "encoding": {"color": {"value": "#52d2ca"}, "x": {"type": "temporal", "axis": {"labelAngle": -90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Year-on-year change"}, "field": "Year-on-year change"}}, "title": ["Growth of travel and tourism industry 's", "contribution to GDP in China from 2006 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2019, little or no advanced technology product weapons were imported to the US.  The category with the highest import levels of almost USD250billion was Information and Communications.  With the exception of Information and Communications, all other categories' value was less than $60billion USD.  Advanced Materials and Nuclear barely register on the chart.

Chart data: Volume of trade goods in billion U.S. dollars industry 247.57 Information & Communications 60.71 Aerospace 54.7 Life Science 45.19 Biotechnology 41.86 Electronics 23.59 Opto-Electronics 17.1 Flexible Manufacturing 2.88 Advanced Materials 2.06 Nuclear Technology 0.92 Weapons

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/7739.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#8c6d31"}, "x": {"type": "quantitative", "axis": {"title": "Volume of trade goods in billion U.S. dollars"}, "field": "Volume of trade goods in billion U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "industry"}}, "title": ["Volume of U.S. imports of advanced technology", "products in 2019 , by group (in billion U.S.", "dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2019 The US imported a lot of information & communications advanced technology products compared to the other industries that use advanced technology products. On the opposite of the spectrum, not a lot of weapon advanced technology was imported in the year of 2019.

Chart data: Volume of trade goods in billion U.S. dollars industry 247.57 Information & Communications 60.71 Aerospace 54.7 Life Science 45.19 Biotechnology 41.86 Electronics 23.59 Opto-Electronics 17.1 Flexible Manufacturing 2.88 Advanced Materials 2.06 Nuclear Technology 0.92 Weapons

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/7739.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#8c6d31"}, "x": {"type": "quantitative", "axis": {"title": "Volume of trade goods in billion U.S. dollars"}, "field": "Volume of trade goods in billion U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "industry"}}, "title": ["Volume of U.S. imports of advanced technology", "products in 2019 , by group (in billion U.S.", "dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The revenue of McDermott International was highest in 2019 but lowest in 2009.

Chart data: Year Revenue in million U.S. dollars Dec 31, 2008 3281.8 Dec 31, 2009 2403.7 Dec 31, 2010 3445.1 Dec 31, 2011 3641.6 Dec 31, 2012 2658.9 Dec 31, 2013 2300.9 Dec 31, 2014 3070.3 Dec 31, 2015 2636 Dec 31, 2016 2984.8 Dec 31, 2017 6705 Dec 31, 2018 8431

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/7749.tsv"}, "mark": "area", "encoding": {"color": {"value": "#fed9a6"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Revenue in million U.S. dollars"}, "field": "Revenue in million U\\.S\\. dollars"}}, "title": ["McDermott International 's revenue from", "2009 to 2019 (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The revenue from 2010 to 2017 remains mainly consistent although there are minor peaks and troughs, there is a steady average. However 2018 and 2019 show a much greater level of revenue, more than doubling the average for the prior seven years.

Chart data: Year Revenue in million U.S. dollars Dec 31, 2008 3281.8 Dec 31, 2009 2403.7 Dec 31, 2010 3445.1 Dec 31, 2011 3641.6 Dec 31, 2012 2658.9 Dec 31, 2013 2300.9 Dec 31, 2014 3070.3 Dec 31, 2015 2636 Dec 31, 2016 2984.8 Dec 31, 2017 6705 Dec 31, 2018 8431

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/7749.tsv"}, "mark": "area", "encoding": {"color": {"value": "#fed9a6"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Revenue in million U.S. dollars"}, "field": "Revenue in million U\\.S\\. dollars"}}, "title": ["McDermott International 's revenue from", "2009 to 2019 (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The share of global GDP from 2015 has been very slightly falling from just over 0.15 to 2019 and is projected to continue that trend until 2025 when it will be below 0.15.

Chart data: Share of global GDP Response 0.1478 2025* 0.1502 2024* 0.1527 2023* 0.155 2022* 0.1568 2021* 0.1598 2020* 0.1593 2019 0.1601 2018 0.1608 2017 0.1625 2016 0.1641 2015

Vega-Lite specification:
{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "data/774.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "quantitative", "axis": {"title": "Share of global GDP"}, "field": "Share of global GDP"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Response"}}, "title": ["United States ' share of global gross domestic", "product (GDP) adjusted for purchasing power", "parity (PPP) from 2015 to 2025"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The average ticket price maintains over 100 dollars for 5 years straight.

Chart data: Year Average ticket price in U.S. dollars Dec 31, 2005 74.96 Dec 31, 2006 80.7 Dec 31, 2007 86.99 Dec 31, 2008 86.99 Dec 31, 2009 114.64 Dec 31, 2010 120.85 Dec 31, 2011 117.94 Dec 31, 2012 110.28 Dec 31, 2013 105.66 Dec 31, 2014 105.66 Dec 31, 2015 110.54 Dec 31, 2017 94.16 Dec 31, 2018 94.16

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/7755.tsv"}, "mark": "line", "encoding": {"color": {"value": "#e7ba52"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Average ticket price in U.S. dollars"}, "field": "Average ticket price in U\\.S\\. dollars"}}, "title": ["Average ticket price for New York Jets home", "games from 2006 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: in 2018 was sell cigaretes in the value of 60.000 dolars.

Chart data: Sales in million U.S. dollars product category 65365 Cigarettes 29153 Packaged beverages 21422 Beer/malt beverages 15691 Other tobacco products 10970 Edible grocery 8464 General merchandise 7176 Candy 6527 Salty snacks 3661 Non-edible grocery 3369 Wine & liquor 3350 Fluid milk products 2532 Alternative snacks 2024 Ice cream & frozen novelties 1562 Health & beauty care 1066 Ice 1002 Publications 653 Packaged sweet snacks 7512 All other merchandise

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/7758.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#fff2ae"}, "x": {"type": "quantitative", "axis": {"title": "Sales in million U.S. dollars"}, "field": "Sales in million U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "product category"}}, "title": ["In-store merchandise sales of convenience", "stores in the United States in 2018 , by", "product category (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Throughout all regions of italy, the average age is about 35. The highest age is roughly 38 years old and the lowest age is roughly 34 years old.

Chart data: region of Italy Age in years Aosta Valley 38.2 Liguria 37.4 Emilia-Romagna 37.3 Tuscany 36.9 Friuli-Venezia Giulia 36.9 Sardinia 36.6 Lazio 36.5 Trentino-South Tyrol 36.5 Piedmont 36.4 Umbria 36.1 Lombardy 36.1 Veneto 35.8 Marche 35.8 Abruzzo 35.8 Basilicata 35.2 Molise 34.9 Apulia 34.3 Calabria 33.9 Sicily 33.7 Campania 33.7

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/7760.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "region of Italy"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "Age in years"}, "field": "Age in years"}}, "title": ["Average age of men at first marriage in", "Italy in 2018 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The crude birth rate in the United States has declined since 1800.

Chart data: Year Crude birth rate Dec 31, 1799 48.33 Dec 31, 1804 47.91 Dec 31, 1809 47.2 Dec 31, 1814 46.5 Dec 31, 1819 47.72 Dec 31, 1824 54.69 Dec 31, 1829 53.84 Dec 31, 1834 52.99 Dec 31, 1839 52.14 Dec 31, 1844 50.68 Dec 31, 1849 48.8 Dec 31, 1854 46.93 Dec 31, 1859 45.05 Dec 31, 1864 43.63 Dec 31, 1869 42.5 Dec 31, 1874 41.38 Dec 31, 1879 40.25 Dec 31, 1884 38.67 Dec 31, 1889 36.8 Dec 31, 1894 34.92 Dec 31, 1899 33.05 Dec 31, 1904 31.53 Dec 31, 1909 30.33 Dec 31, 1914 29.72 Dec 31, 1919 27.92 Dec 31, 1924 26.3 Dec 31, 1929 22.48 Dec 31, 1934 19.16 Dec 31, 1939 19.02 Dec 31, 1944 21.36 Dec 31, 1949 24.76 Dec 31, 1954 24.1 Dec 31, 1959 23.8 Dec 31, 1964 21 Dec 31, 1969 17.6 Dec 31, 1974 15.6 Dec 31, 1979 14.8 Dec 31, 1984 15.3 Dec 31, 1989 15.7 Dec 31, 1994 15.5 Dec 31, 1999 14.3 Dec 31, 2004 14 Dec 31, 2009 13.8 Dec 31, 2014 12.5 Dec 31, 2019 12

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/7761.tsv"}, "mark": "line", "encoding": {"color": {"value": "#56cc60"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Crude birth rate"}, "field": "Crude birth rate"}}, "title": ["Crude birth rate in the United States from", "1800 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The period with the highest number of mergers and acquisitions was June 14. The lowest period was Aug 14.

Chart data: Number of deals Month 1222 Jun 15 1030 May 15 1107 Apr 15 1166 Mar 15 1097 Feb 15 1076 Jan 15 1235 Dec 14 1152 Nov 14 1167 Oct 14 1222 Sep 14 912 Aug 14 1253 Jul 14 1171 Jun 14 1070 May 14 1185 Apr 14 1062 Mar 14

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/7764.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "quantitative", "axis": {"title": "Number of deals"}, "field": "Number of deals"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Number of merger and acquisition transactions", "in Europe from March 2014 to June 2015"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of mergers and acquisition in Europe between March 2014 and June 2015 has been reasonably stable between 1000 and 1200.

Chart data: Number of deals Month 1222 Jun 15 1030 May 15 1107 Apr 15 1166 Mar 15 1097 Feb 15 1076 Jan 15 1235 Dec 14 1152 Nov 14 1167 Oct 14 1222 Sep 14 912 Aug 14 1253 Jul 14 1171 Jun 14 1070 May 14 1185 Apr 14 1062 Mar 14

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/7764.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "quantitative", "axis": {"title": "Number of deals"}, "field": "Number of deals"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Number of merger and acquisition transactions", "in Europe from March 2014 to June 2015"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: 1200 transactions were held in 4 of the months shown. The smallest number of transactions was in Aug 14.

Chart data: Number of deals Month 1222 Jun 15 1030 May 15 1107 Apr 15 1166 Mar 15 1097 Feb 15 1076 Jan 15 1235 Dec 14 1152 Nov 14 1167 Oct 14 1222 Sep 14 912 Aug 14 1253 Jul 14 1171 Jun 14 1070 May 14 1185 Apr 14 1062 Mar 14

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/7764.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "quantitative", "axis": {"title": "Number of deals"}, "field": "Number of deals"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Number of merger and acquisition transactions", "in Europe from March 2014 to June 2015"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The highest value of dried food imported to UK was around year 2016 and it was worth approximately 140000 £. The lowes value was in year 2001 and it was 50000£ only. From visualiation I can tell that from 2001 till 2016 values of dried food importe to UK was mostly increasing.

Chart data: Year Import value in thousand GBP Dec 31, 2000 48998 Dec 31, 2001 53751 Dec 31, 2002 60050 Dec 31, 2003 69912 Dec 31, 2004 78046 Dec 31, 2005 84444 Dec 31, 2006 92859 Dec 31, 2007 110377 Dec 31, 2008 104431 Dec 31, 2009 106686 Dec 31, 2010 116192 Dec 31, 2011 111232 Dec 31, 2012 123773 Dec 31, 2013 143189 Dec 31, 2014 166989 Dec 31, 2015 174737 Dec 31, 2016 152042 Dec 31, 2017 153248 Dec 31, 2018 142239

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/7765.tsv"}, "mark": "line", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Import value in thousand GBP"}, "field": "Import value in thousand GBP"}}, "title": ["Value of dried fruit imported to the United", "Kingdom (UK) from 2001 to 2019 (in 1,000", "GBP)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The amount of children as a population has decreased from 2005 to 2018.

Chart data: Response Percentage of total population Dec 31, 2004 0.3 Dec 31, 2005 0.3 Dec 31, 2006 0.3 Dec 31, 2007 0.29 Dec 31, 2008 0.28 Dec 31, 2009 0.28 Dec 31, 2010 0.27 Dec 31, 2011 0.27 Dec 31, 2012 0.26 Dec 31, 2013 0.25 Dec 31, 2014 0.25 Dec 31, 2015 0.25 Dec 31, 2016 0.24 Dec 31, 2017 0.24 Dec 31, 2018 0.24

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/7771.tsv"}, "mark": "line", "encoding": {"color": {"value": "#8b8b8b"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Percentage of total population"}, "field": "Percentage of total population"}}, "title": ["Share of children in total population in", "Malaysia from 2005 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The GDP of CuraASSaoA  has remained fairly the same between 2008 and 2019.

Chart data: Year GDP in million ANG 2019* 5552.2 2018* 5599 2017* 5578.8 2016 5588.9 2015 5641.9 2014 5653.5 2013 5634.2 2012 5604.7 2011 5439.3 2010 5282.9 2009 5135.8 2008 5071.9

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/7772.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "GDP in million ANG"}, "field": "GDP in million ANG"}}, "title": ["Gross Domestic Product (GDP) \u00c2 of Cura\u00c3\u00a7ao\u00c2", "from 2008 to 2019 (in million ANG)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: GDP increases between 2008 and 2012. It then largely stagnates between 2012 and 2019 with minor increases until 2015 and minor decreases from 2016 to 2019.

Chart data: Year GDP in million ANG 2019* 5552.2 2018* 5599 2017* 5578.8 2016 5588.9 2015 5641.9 2014 5653.5 2013 5634.2 2012 5604.7 2011 5439.3 2010 5282.9 2009 5135.8 2008 5071.9

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/7772.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "GDP in million ANG"}, "field": "GDP in million ANG"}}, "title": ["Gross Domestic Product (GDP) \u00c2 of Cura\u00c3\u00a7ao\u00c2", "from 2008 to 2019 (in million ANG)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The highest net premiums were Swiss RE Ltd at 36 million dollars. The lowest net premiums were Korean Insurance Company at 5 million dollars. Most of the leading global insurers net premiums were under 15 million dollars.

Chart data: business Net premiums written in million U.S. dollars Swiss Re Ltd. 35.62 Munich Re Co. 33.15 Hannover Re 17.23 SCOR S.E. 14.57 Berkshire Hathaway Inc 12.71 Lloyd's 11.58 Reinsurance Group of America Inc 10.11 China Reinsurance (Group) Corp 7.86 Great West Lifeco 6.2 Korean Reinsurance Company 5.55

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/7774.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6793a6"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "business"}, "y": {"type": "quantitative", "axis": {"title": "Net premiums written in million U.S. dollars"}, "field": "Net premiums written in million U\\.S\\. dollars"}}, "title": ["Leading global reinsurers in 2016 , by gross", "reinsurance premiums written (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Swiss RE Limited records the highest net premiums with roughly 35 million dollars, Korean reinsurance company appears to record the lowest with 5 million dollars.

Chart data: business Net premiums written in million U.S. dollars Swiss Re Ltd. 35.62 Munich Re Co. 33.15 Hannover Re 17.23 SCOR S.E. 14.57 Berkshire Hathaway Inc 12.71 Lloyd's 11.58 Reinsurance Group of America Inc 10.11 China Reinsurance (Group) Corp 7.86 Great West Lifeco 6.2 Korean Reinsurance Company 5.55

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/7774.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6793a6"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "business"}, "y": {"type": "quantitative", "axis": {"title": "Net premiums written in million U.S. dollars"}, "field": "Net premiums written in million U\\.S\\. dollars"}}, "title": ["Leading global reinsurers in 2016 , by gross", "reinsurance premiums written (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The capital expenditure of the US chemical industry raised between 2004 to 2019. The capital expenditure of the US chemical industry between 2004 and 2019 was between $18B and $35B.

Chart data: Capital expenditure in million U.S. dollars Year 35100 2019* 33400 2018* 31300 2017* 31500 2016* 31000 2015* 26700 2014* 28900 2013* 28800 2012* 25758 2011 20339 2010 23625 2009 23839 2008 27412 2007 18151 2006 18056 2005 18857 2004

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/7775.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#c89d29"}, "x": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Capital expenditure in million U.S. dollars"}, "field": "Capital expenditure in million U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Capital expenditure of the United States", "chemical industry from 2004 to 2019 (in million", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The Championship game, Kentucky vs. Connecticut had the highest TV rating, 13 in 2014. The lowest  TV ratings were for the Sweet 16 games. The Elite and Final Games had the next highest ratings after the Championship game.

Chart data: group name and match TV ratings Championship Game - Kentucky vs. Connecticut (Apr. 7) 12.4 Final 4 - Kentucky vs. Wisconsin (Apr. 5) 9.2 Final 4 - Connecticut vs. Florida (Apr. 5) 6.9 Elite 8 - Kentucky vs. Michigan (Mar. 30) 8.9 Elite 8 - Connecticut vs. Michigan St. (Mar. 30) 6.1 Elite 8 - Wisconsin vs. Arizona (Mar. 29) 5.8 Elite 8 - Dayton vs. Florida (Mar. 29) 4.3 Sweet 16 - Kentucky vs. Louisville (Mar. 28) 5.9 Sweet 16 - Tennessee vs. Michigan (Mar. 28) 5 Sweet 16 - UCLA vs. Florida (Mar. 27) 4.7 Sweet 16 - Dayton vs. Stanford (Mar. 27) 4.6 Sweet 16 - Michigan St. vs. Virginia (Mar. 28) 3 Sweet 16 - SDSU vs. Arizona (Mar. 27) 2 Sweet 16 - Baylor vs. Wisconsin (Mar. 27) 1.9 Sweet 16 - Connecticut vs. Iowa St. (Mar. 28) 1.8

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/7776.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ff9e27"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "group name and match"}, "y": {"type": "quantitative", "axis": {"title": "TV ratings"}, "field": "TV ratings"}}, "title": ["NCAA March Madness basketball tournament", "TV ratings in 2014 , selected games"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: the sweet 16 games don't seem to be getting as many ratings as the rest, majority of the ratings are above 4, sweet 16 played the most games.

Chart data: group name and match TV ratings Championship Game - Kentucky vs. Connecticut (Apr. 7) 12.4 Final 4 - Kentucky vs. Wisconsin (Apr. 5) 9.2 Final 4 - Connecticut vs. Florida (Apr. 5) 6.9 Elite 8 - Kentucky vs. Michigan (Mar. 30) 8.9 Elite 8 - Connecticut vs. Michigan St. (Mar. 30) 6.1 Elite 8 - Wisconsin vs. Arizona (Mar. 29) 5.8 Elite 8 - Dayton vs. Florida (Mar. 29) 4.3 Sweet 16 - Kentucky vs. Louisville (Mar. 28) 5.9 Sweet 16 - Tennessee vs. Michigan (Mar. 28) 5 Sweet 16 - UCLA vs. Florida (Mar. 27) 4.7 Sweet 16 - Dayton vs. Stanford (Mar. 27) 4.6 Sweet 16 - Michigan St. vs. Virginia (Mar. 28) 3 Sweet 16 - SDSU vs. Arizona (Mar. 27) 2 Sweet 16 - Baylor vs. Wisconsin (Mar. 27) 1.9 Sweet 16 - Connecticut vs. Iowa St. (Mar. 28) 1.8

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/7776.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ff9e27"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "group name and match"}, "y": {"type": "quantitative", "axis": {"title": "TV ratings"}, "field": "TV ratings"}}, "title": ["NCAA March Madness basketball tournament", "TV ratings in 2014 , selected games"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The gross profit of the Puma Group has steadily risen over the years. Profit is at its highest in the years after 2015. Profits rose the most between 2000 and 2005 and then again from 2015.

Chart data: Year Gross profit in million euros Dec 31, 1992 62.8 Dec 31, 1994 79 Dec 31, 1999 176.4 Dec 31, 2004 929.8 Dec 31, 2005 1199.3 Dec 31, 2006 1241.7 Dec 31, 2007 1306.6 Dec 31, 2008 1243.1 Dec 31, 2009 1344.8 Dec 31, 2010 1493.4 Dec 31, 2011 1579 Dec 31, 2012 1387.5 Dec 31, 2013 1385.4 Dec 31, 2014 1540.2 Dec 31, 2015 1656.4 Dec 31, 2016 1954.3 Dec 31, 2017 2249.4 Dec 31, 2018 2686.4

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/7786.tsv"}, "mark": "area", "encoding": {"color": {"value": "#00ACC1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Gross profit in million euros"}, "field": "Gross profit in million euros"}}, "title": ["Gross profit of the Puma Group worldwide", "from 1993 to 2019 (in million euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From 1960 until 1980 there was a drop in the number of journeys in historical national rail passenger journeys in the UK. There was a sharp increase in the number of journeys in historical national rail passenger journeys from 2000 until 2015. 1985 had the lowest number of national historic rail passenger journeys in the period observed from 1950 until 2020.

Chart data: Year Number of journeys in millions Dec 31, 1949 1010 Dec 31, 1954 994 Dec 31, 1959 1037 Dec 31, 1964 865 Dec 31, 1969 824 Dec 31, 1974 730 Dec 31, 1979 760 Dec 31, 1984 686 Dec 31, 1989 810 Dec 31, 1994 761 Dec 31, 1999 957 Dec 31, 2004 1076 Dec 31, 2009 1356 Dec 31, 2014 1656 Dec 31, 2015 1718 Dec 31, 2016 1731 Dec 31, 2017 1708 Dec 31, 2018 1758 Dec 31, 2019 1745

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/7788.tsv"}, "mark": "line", "encoding": {"color": {"value": "#F4B400"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "Number of journeys in millions"}, "field": "Number of journeys in millions"}}, "title": ["Total historical national rail passenger", "journeys in the United Kingdom (UK) from", "1950 to 2020 (in millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: That during the years the value has increased to a point of nearly 50%.

Chart data: December value Chained Consumer Price Index (1999=100) 2019* 144.73 2018 141.7 2017 139.55 2016 137.22 2015 134.79 2014 134.21 2013 133.51 2012 131.77 2011 129.84 2010 126.14 2009 124.54 2008 121.56 2007 121.3 2006 117 2005 114.4 2004 111.2 2003 107.8 2002 106 2001 103.9 2000 102.6

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/7789.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#7b4173"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "December value"}, "y": {"type": "quantitative", "axis": {"title": "Chained Consumer Price Index (1999=100)"}, "field": "Chained Consumer Price Index (1999=100)"}}, "title": ["Chained consumer price index (C-CPI-U) of", "all urban consumers in the United States", "from 2000 to 2019 , at year-end"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The fertility rate in Afghanistan has gone down by an average of 2 children per woman, at a steady rate between 2008 and 2016.

Chart data: Year Number of children born per woman Dec 31, 2007 6.37 Dec 31, 2008 6.18 Dec 31, 2009 5.98 Dec 31, 2010 5.77 Dec 31, 2011 5.56 Dec 31, 2012 5.36 Dec 31, 2013 5.16 Dec 31, 2014 4.98 Dec 31, 2015 4.8 Dec 31, 2016 4.63 Dec 31, 2017 4.47

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/7791.tsv"}, "mark": "area", "encoding": {"color": {"value": "#b9cc98"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Number of children born per woman"}, "field": "Number of children born per woman"}}, "title": ["Afghanistan : Fertility rate from 2008 to", "2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}