delen/vistext huggingface dataset:
Chart description: The British forces had more of the QF 18 pounder gun than any other gun that is on the graph. This is followed by the QF 4.5 inch howitzer, however, there is at least 600 more 18 pounder guns than there is the 4.5 inch howitzer.

Chart data: Number of guns Weapon type 808 QF 18 pounder gun 202 QF 4.5 inch Howitzer 128 BL 60 pounder gun 104 BL 6 inch Howitzer 60 BL 9.2-inch Howitzer 32 QF 4.7-inch naval gun Mk I 20 BL 6-inch naval gun Mk VII 11 BL 12-inch Howitzer 6 BL 15-inch Howitzer 1 BL 9.2-inch naval gun Mk IX 1 BL 12-inch naval gun Mk X

Vega-Lite specification:
{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "data/16357.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#386cb0"}, "x": {"type": "quantitative", "axis": {"title": "Number of guns"}, "field": "Number of guns"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Weapon type"}}, "title": ["Artillery and heavy guns used by the British", "forces during the First Battle of the Somme", "in 1916"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Troon Golf manages the most number of courses at over 250 in its portfolio.

Chart data: Golf course management company Number of golf courses Troon Golf 278 ClubCorp 200 Billy Casper Golf 158 Pacific Golf Management 156 Accordia Golf Co., Ltd. 134 KemperSports 109 Blue Green Groupe Saur 105 American Golf Corp. 76 Arcis Golf 70 OB Sports 67.5 Landscapes Golf Management 60.5 GreatLIFE Golf & Fitness 54 ClubLink 53 Marriott Golf 51 Century Golf Partners / Arnold Palmers Golf Management 46 UGOLF 43 ClubSpecialists International (CSI) 38.5 CourseCo, Inc 38.5 Touchstone Golf 36 Crown Golf 32

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/1635.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#c4c4c4"}, "x": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "Golf course management company"}, "y": {"type": "quantitative", "axis": {"title": "Number of golf courses"}, "field": "Number of golf courses"}}, "title": ["Golf course management companies by the", "number of golf courses worldwide in 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: We can see a varying rate of decrease of nitrogen dioxide in Spanish cities.

Chart data: city NO2 level variation Barcelona −0.83 Madrid −0.73 Valencia −0.64 Castellón −0.76 Zaragoza −0.52 Bilbao −0.66 Alicante −0.68 Málaga −0.55 Gijón −0.65 Sevilla −0.36

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/16360.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6d904f"}, "x": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "city"}, "y": {"type": "quantitative", "axis": {"title": "NO2 level variation"}, "field": "NO2 level variation"}}, "title": ["Variation in the level of nitrogen dioxide", "registered during the coronavirus crisis", "in selected Spanish cities between 10 - 14", "March and 15 - 20 March 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is a general trend of more wage and salary workers each year in the united states from 1979 to 2019.  The years 1990 to 2000 and 2010 to 2019 saw the biggest increases in total number of wage and salary workers.

Chart data: Year Number of workers in millions Dec 31, 1978 87.53 Dec 31, 1979 87.64 Dec 31, 1980 88.52 Dec 31, 1981 87.37 Dec 31, 1982 88.29 Dec 31, 1983 92.19 Dec 31, 1984 94.52 Dec 31, 1985 96.9 Dec 31, 1986 99.3 Dec 31, 1987 101.41 Dec 31, 1988 103.48 Dec 31, 1989 104.88 Dec 31, 1990 103.72 Dec 31, 1991 104.67 Dec 31, 1992 106.1 Dec 31, 1993 107.99 Dec 31, 1994 110.04 Dec 31, 1995 111.96 Dec 31, 1996 114.53 Dec 31, 1997 116.73 Dec 31, 1998 118.96 Dec 31, 1999 122.09 Dec 31, 2000 122.23 Dec 31, 2001 121.83 Dec 31, 2002 122.36 Dec 31, 2003 123.55 Dec 31, 2004 125.89 Dec 31, 2005 128.24 Dec 31, 2006 129.77 Dec 31, 2007 129.38 Dec 31, 2008 124.49 Dec 31, 2009 124.07 Dec 31, 2010 125.19 Dec 31, 2011 127.58 Dec 31, 2012 129.11 Dec 31, 2013 131.43 Dec 31, 2014 133.74 Dec 31, 2015 136.1 Dec 31, 2016 137.89 Dec 31, 2017 140.1 Dec 31, 2018 141.74

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/16362.tsv"}, "mark": "area", "encoding": {"color": {"value": "#e6f5c9"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Number of workers in millions"}, "field": "Number of workers in millions"}}, "title": ["Total number of wage and salary workers", "in the United States from 1979 to 2019 (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is an upward trend in the number of workers from 1979 to 2019. The lowest value is at 90 million workers in 1979 and the highest value is at 140 million workers in 2019.

Chart data: Year Number of workers in millions Dec 31, 1978 87.53 Dec 31, 1979 87.64 Dec 31, 1980 88.52 Dec 31, 1981 87.37 Dec 31, 1982 88.29 Dec 31, 1983 92.19 Dec 31, 1984 94.52 Dec 31, 1985 96.9 Dec 31, 1986 99.3 Dec 31, 1987 101.41 Dec 31, 1988 103.48 Dec 31, 1989 104.88 Dec 31, 1990 103.72 Dec 31, 1991 104.67 Dec 31, 1992 106.1 Dec 31, 1993 107.99 Dec 31, 1994 110.04 Dec 31, 1995 111.96 Dec 31, 1996 114.53 Dec 31, 1997 116.73 Dec 31, 1998 118.96 Dec 31, 1999 122.09 Dec 31, 2000 122.23 Dec 31, 2001 121.83 Dec 31, 2002 122.36 Dec 31, 2003 123.55 Dec 31, 2004 125.89 Dec 31, 2005 128.24 Dec 31, 2006 129.77 Dec 31, 2007 129.38 Dec 31, 2008 124.49 Dec 31, 2009 124.07 Dec 31, 2010 125.19 Dec 31, 2011 127.58 Dec 31, 2012 129.11 Dec 31, 2013 131.43 Dec 31, 2014 133.74 Dec 31, 2015 136.1 Dec 31, 2016 137.89 Dec 31, 2017 140.1 Dec 31, 2018 141.74

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/16362.tsv"}, "mark": "area", "encoding": {"color": {"value": "#e6f5c9"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Number of workers in millions"}, "field": "Number of workers in millions"}}, "title": ["Total number of wage and salary workers", "in the United States from 1979 to 2019 (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The U.S. olive production has fluctuated drastically year on year between 2000 and 2018.

Chart data: Year Production in thousand tons Dec 31, 1999 53 Dec 31, 2000 134 Dec 31, 2001 103 Dec 31, 2002 118 Dec 31, 2003 108 Dec 31, 2004 142 Dec 31, 2005 24 Dec 31, 2006 133 Dec 31, 2007 67 Dec 31, 2008 46 Dec 31, 2009 206 Dec 31, 2010 71 Dec 31, 2011 160 Dec 31, 2012 166 Dec 31, 2013 95 Dec 31, 2014 179 Dec 31, 2015 165 Dec 31, 2016 192 Dec 31, 2017 53.6

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/16364.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Production in thousand tons"}, "field": "Production in thousand tons"}}, "title": ["U.S. olive production from 2000 to 2018", "(in 1,000 tons)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The graph shows dramatic year on year differences in tons of production of US olives ranging from a low of 20 tons in 2006 to a high of 210 tons in 2010 with an overall upward trend.

Chart data: Year Production in thousand tons Dec 31, 1999 53 Dec 31, 2000 134 Dec 31, 2001 103 Dec 31, 2002 118 Dec 31, 2003 108 Dec 31, 2004 142 Dec 31, 2005 24 Dec 31, 2006 133 Dec 31, 2007 67 Dec 31, 2008 46 Dec 31, 2009 206 Dec 31, 2010 71 Dec 31, 2011 160 Dec 31, 2012 166 Dec 31, 2013 95 Dec 31, 2014 179 Dec 31, 2015 165 Dec 31, 2016 192 Dec 31, 2017 53.6

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/16364.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Production in thousand tons"}, "field": "Production in thousand tons"}}, "title": ["U.S. olive production from 2000 to 2018", "(in 1,000 tons)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Most people interviewed believe that being abusive to someone is classed as trolling.

Chart data: Share of respondents Response 0.52 Deliberately making inflammatory statements 0.54 Being abusive to someone because of their opinion 0.5 Picking on another person or small group of people for any reason 0.42 Deliberately making controversial statements 0.35 Using a comments section or chatroom to further one's own opinion, even if it has nothing to do with the topic of said comments section/chatroom 0.47 Calling someone else (e.g. fellow commentator, article writer, etc.) an offensive name 0.46 Belittling someone for not understanding a concept or previously presented piece of information 0.17 Being stubborn about one's own opinion 0.02 Other 0.05 Not applicable - no behavior constitutes internet trolling 0.14 Don't know

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/16378.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec8431"}, "x": {"type": "quantitative", "axis": {"title": "Share of respondents"}, "field": "Share of respondents"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Response"}}, "title": ["Which of the following behaviors do you", "think constitute internet trolling ?"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The responses that constitute internet trolling are said to be many equal reasons with the biggest response being abusive towards someone.

Chart data: Share of respondents Response 0.52 Deliberately making inflammatory statements 0.54 Being abusive to someone because of their opinion 0.5 Picking on another person or small group of people for any reason 0.42 Deliberately making controversial statements 0.35 Using a comments section or chatroom to further one's own opinion, even if it has nothing to do with the topic of said comments section/chatroom 0.47 Calling someone else (e.g. fellow commentator, article writer, etc.) an offensive name 0.46 Belittling someone for not understanding a concept or previously presented piece of information 0.17 Being stubborn about one's own opinion 0.02 Other 0.05 Not applicable - no behavior constitutes internet trolling 0.14 Don't know

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/16378.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ec8431"}, "x": {"type": "quantitative", "axis": {"title": "Share of respondents"}, "field": "Share of respondents"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Response"}}, "title": ["Which of the following behaviors do you", "think constitute internet trolling ?"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From 2010 to 2015 attacks were cosistant at around 2000. From 2014 to 2018 there is a steady rise to around 4500 attacks. A small plateau occurs after 2018 staying at 4500.

Chart data: Year ATM related physical attacks Dec 31, 2009 2062 Dec 31, 2010 1818 Dec 31, 2011 1920 Dec 31, 2012 2102 Dec 31, 2013 1980 Dec 31, 2014 2657 Dec 31, 2015 2974 Dec 31, 2016 3584 Dec 31, 2017 4549 Dec 31, 2018 4571

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/16380.tsv"}, "mark": "line", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "ATM related physical attacks"}, "field": "ATM related physical attacks"}}, "title": ["Number of ATM-related physical attacks in", "selected European countries from 2010 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: This graph shows there has been an increase of ATM related physical attacks from 2010 to 2019. these attacks have more than doubled from just over 2000 to about 4500 in 2019. The lowest year for attacks was 2011, the only time the attacks dropped below 2000 in a year.

Chart data: Year ATM related physical attacks Dec 31, 2009 2062 Dec 31, 2010 1818 Dec 31, 2011 1920 Dec 31, 2012 2102 Dec 31, 2013 1980 Dec 31, 2014 2657 Dec 31, 2015 2974 Dec 31, 2016 3584 Dec 31, 2017 4549 Dec 31, 2018 4571

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/16380.tsv"}, "mark": "line", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "ATM related physical attacks"}, "field": "ATM related physical attacks"}}, "title": ["Number of ATM-related physical attacks in", "selected European countries from 2010 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The trend shows that the GDP per year grows incrementally by around 2000 million Canadian dollars in the time period of 19 years. The pattern plateaued slightly between 2005 and 2010, but still grew, but the sharpest increase came between 2015 and 2019, rising nearly 1000 million Canadian dollars in that period.

Chart data: Year GDP in million chained 2012 Canadian dollars Dec 31, 1999 4191.4 Dec 31, 2000 4139.5 Dec 31, 2001 4340.2 Dec 31, 2002 4415.8 Dec 31, 2003 4545.9 Dec 31, 2004 4690.6 Dec 31, 2005 4804.3 Dec 31, 2006 4781.6 Dec 31, 2007 4836.1 Dec 31, 2008 4845.2 Dec 31, 2009 4948.2 Dec 31, 2010 5043.5 Dec 31, 2011 5090.7 Dec 31, 2012 5187.4 Dec 31, 2013 5205.6 Dec 31, 2014 5280.7 Dec 31, 2015 5393.8 Dec 31, 2016 5632.2 Dec 31, 2017 5788.9 Dec 31, 2018 6052

Vega-Lite specification:
{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "data/16388.tsv"}, "mark": "line", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "GDP in million chained 2012 Canadian dollars"}, "field": "GDP in million chained 2012 Canadian dollars"}}, "title": ["Gross domestic product of Prince Edward", "Island , Canada from 2000 to 2019 (in million", "chained 2012 Canadian dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2008 Barrick Gold 's average gold (price per ounce) was just under 1000. This rose quickly to well over 1500 in 2012 before decreasing to just over a thousand in 2015. It has been steadily increasing to 2019 to around 1250.

Chart data: Year Price in U.S. dollars per ounce Dec 31, 2007 872 Dec 31, 2008 985 Dec 31, 2009 1228 Dec 31, 2010 1578 Dec 31, 2011 1669 Dec 31, 2012 1407 Dec 31, 2013 1265 Dec 31, 2014 1157 Dec 31, 2015 1248 Dec 31, 2016 1258 Dec 31, 2017 1270 Dec 31, 2018 1396

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/16406.tsv"}, "mark": "area", "encoding": {"color": {"value": "#4285F4"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "Price in U.S. dollars per ounce"}, "field": "Price in U\\.S\\. dollars per ounce"}}, "title": ["Barrick Gold 's average realized gold price", "per ounce from 2008 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Total number of marriages in France is declining year on year.

Chart data: Year Number of marriages 2004 278439 2005 283036 2006 273914 2007 273669 2008 265404 2009 251478 2010 251654 2011 236826 2012 245930 2013 238592 2014 241300 2015 236300 2016 232700 2017* 226700 2018* 228300 2019* 221000

Vega-Lite specification:
{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "data/1641.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "nominal", "axis": {"labelAngle": -90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Number of marriages"}, "field": "Number of marriages"}}, "title": ["Total number of marriages in France from", "2004 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Between 2015 and 2019. Spains GDP was fairly static. This declined slightly in 2020 and predictions up to 2025 remain stable.

Chart data: Share of global GDP Response 0.0135 2025* 0.0138 2024* 0.0139 2023* 0.0139 2022* 0.0139 2021* 0.0136 2020* 0.0149 2019 0.015 2018 0.0152 2017 0.015 2016 0.0146 2015

Vega-Lite specification:
{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "data/16439.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#E66C37"}, "x": {"type": "quantitative", "axis": {"title": "Share of global GDP"}, "field": "Share of global GDP"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Response"}}, "title": ["Spain : 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 brand page with the highest amount of local fans is 'Amazon UK', with just under 6 million local fans. The brand page with the least amount of local fans is 'eBay.co.uk', with just over 2 million local fans.

Chart data: Local fans in millions Brand page 5.73 Amazon UK 4.86 UNREEL 3.84 The Body Coach 3.23 British Airways 2.66 Next 2.64 Tesco 2.57 SportsDirect.com 2.37 Cadbury Creme Egg 2.25 AutoCAD 2.2 eBay.co.uk

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/1643.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#3e5c69"}, "x": {"type": "quantitative", "axis": {"title": "Local fans in millions"}, "field": "Local fans in millions"}, "y": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "Brand page"}}, "title": ["Most popular brand pages on Facebook in", "the United Kingdom (UK) as of March 2020", "(in million local fans)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The population of Niger has been steadily increasing since 2016 when it was 20 million.  It is predicted that by 2024 the population will be just under 30 million.

Chart data: Year Inhabitants in millions Dec 31, 2014 20 Dec 31, 2015 20.79 Dec 31, 2016 21.6 Dec 31, 2017 22.44 Dec 31, 2018 23.31 Dec 31, 2019 24.21 Dec 31, 2020 25.13 Dec 31, 2021 26.08 Dec 31, 2022 27.07 Dec 31, 2023 28.08 Dec 31, 2024 29.13

Vega-Lite specification:
{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "data/16446.tsv"}, "mark": "area", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Inhabitants in millions"}, "field": "Inhabitants in millions"}}, "title": ["Niger : Estimated total population from", "2015 to 2025 (in million inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Birth rate in Alberta had a steady incline from the year 2001 to 2016 before the rate hit a steady decline to 2020.

Chart data: Year Number of births 2019-2020* 51996 2018-2019 52321 2017-2018 52986 2016-2017 54786 2015-2016 56925 2014-2015 56333 2013-2014 54782 2012-2013 53076 2011-2012 51315 2010-2011 50853 2009-2010 51522 2008-2009 51308 2007-2008 49949 2006-2007 47558 2005-2006 43193 2004-2005 41345 2003-2004 40635 2002-2003 39450 2001-2002 37602 2000-2001 37197

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/16450.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Number of births"}, "field": "Number of births"}}, "title": ["Number of births in Alberta , Canada from", "2001 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The amount of births rose gradually up until 2010, before slightly decreasing and then rising above 54,000 births up until 2017. From 2018 the births have been slowly decreasing in numbers.

Chart data: Year Number of births 2019-2020* 51996 2018-2019 52321 2017-2018 52986 2016-2017 54786 2015-2016 56925 2014-2015 56333 2013-2014 54782 2012-2013 53076 2011-2012 51315 2010-2011 50853 2009-2010 51522 2008-2009 51308 2007-2008 49949 2006-2007 47558 2005-2006 43193 2004-2005 41345 2003-2004 40635 2002-2003 39450 2001-2002 37602 2000-2001 37197

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/16450.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Number of births"}, "field": "Number of births"}}, "title": ["Number of births in Alberta , Canada from", "2001 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The number of births in Alberta, Canada has increased from 2010 to 2010. The number of births  in Alberta declined slightly in 2010 and 2011 - 2012The number births in Alberta  increased slightly in 2013 - 2016. The number of births in Alberta fell from 2016 to 2020.

Chart data: Year Number of births 2019-2020* 51996 2018-2019 52321 2017-2018 52986 2016-2017 54786 2015-2016 56925 2014-2015 56333 2013-2014 54782 2012-2013 53076 2011-2012 51315 2010-2011 50853 2009-2010 51522 2008-2009 51308 2007-2008 49949 2006-2007 47558 2005-2006 43193 2004-2005 41345 2003-2004 40635 2002-2003 39450 2001-2002 37602 2000-2001 37197

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/16450.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#adc839"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Number of births"}, "field": "Number of births"}}, "title": ["Number of births in Alberta , Canada from", "2001 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From 2016 volume of cargo in metric tons has always been above 600.

Chart data: Volume in million metric tons Financial Year 699.17 FY 2019 679.5 FY 2018 648.47 FY 2017 605.89 FY 2016 581.34 FY 2015 555.49 FY 2014 545.83 FY 2013 560.19 FY 2012 570.09 FY 2011 561.09 FY 2010

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/16453.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Volume in million metric tons"}, "field": "Volume in million metric tons"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Financial Year"}}, "title": ["Volume of cargo handled in major ports across", "India from financial year 2010 to 2019 (in", "million metric tons)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Every year had a refinery capacity of above 1,200 barrels per day. Between 2015 & 2019 this time period had the highest refinery capacity amount.

Chart data: Year Refinery capacity in 1,000 barrels per day Dec 31, 1999 1277 Dec 31, 2000 1278 Dec 31, 2001 1282 Dec 31, 2002 1282 Dec 31, 2003 1284 Dec 31, 2004 1274 Dec 31, 2005 1274 Dec 31, 2006 1236 Dec 31, 2007 1280 Dec 31, 2008 1280 Dec 31, 2009 1274 Dec 31, 2010 1276 Dec 31, 2011 1279 Dec 31, 2012 1279 Dec 31, 2013 1279 Dec 31, 2014 1298 Dec 31, 2015 1298 Dec 31, 2016 1299 Dec 31, 2017 1299 Dec 31, 2018 1309

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/16454.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3690c0"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "Refinery capacity in 1,000 barrels per day"}, "field": "Refinery capacity in 1,000 barrels per day"}}, "title": ["Oil refinery capacities of the Netherlands", "between 2000 to 2019 (in 1,000 barrels daily", ")"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Russel sheik has the most employees. Tychy has the least. Zaragoza has exactly 5000 employees. Eisenach and Ellesmere Port have the same amount of employees.

Chart data: Number of employees city 14180 Rüsselsheim (plant) 5120 Zaragoza 2890 Gliwice 2130 Kaiserslautern 1870 Ellesmere Port 1850 Eisenach 1450 Aspern 1340 Luton 1200 Szentgotthárd 480 Tychy

Vega-Lite specification:
{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "data/16471.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#54a24b"}, "x": {"type": "quantitative", "axis": {"title": "Number of employees"}, "field": "Number of employees"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "city"}}, "title": ["Number of employees at Opel/Vauxhall in", "selected European cities in 2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Switzerland, UAE and China import the most with Switzerland leading.

Chart data: Import value in million U.S. dollars Country 16512.6 Switzerland 13792 China, Hong Kong SAR 13555 United Arab Emirates 11894.4 United States 5406.3 France 3664.7 United Kingdom 3241.6 Singapore 2441.8 Germany 2364 Italy 2285.4 Japan

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/16473.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#4572a7"}, "x": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "Import value in million U.S. dollars"}, "field": "Import value in million U\\.S\\. dollars"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Leading importing countries of gold , silverware", ", and jewelry worldwide in 2018 (in million", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The Brazilian states Acre and Alagoas have the highest femicide rates in 2019. The Brazilian states Tocantins and Amazonas have the lowest femicide rate in 2019.

Chart data: Number of femicides per 100,000 women States Of Brazil 2.5 Acre 2.5 Alagoas 2.3 Mato Grosso 2.1 Mato Grosso do Sul 2.1 Federal District 2 Roraima 1.8 Sergipe 1.8 Paraíba 1.7 Rio Grande do Sul 1.7 Piauí 1.7 Amapá 1.6 Santa Catarina 1.6 Espírito Santo 1.5 Paraná 1.4 Maranhão 1.3 Bahia 1.3 Minas Gerais 1.2 Rio Grande do Norte 1.1 Pernambuco 1.1 Goiás 1.1 Pará 0.9 Rio de Janeiro 0.8 Rondônia 0.8 São Paulo 0.7 Ceará 0.6 Amazonas 0.6 Tocantins

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/16476.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#000000"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of femicides per 100,000 women"}, "field": "Number of femicides per 100,000 women"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "States Of Brazil"}}, "title": ["Femicide rates in Brazil in 2019 , by state", "(number of femicides per 100,000 women)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}