Datasets:

delen

/

vistext

like 0

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/6492.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7969c"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "insurance companies"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Life insurance and capitalization"}, "field": "Life insurance and capitalization"}}, "title": ["Value of direct personal insurance premiums", "written in France in 2018 , by insurance", "companies (in million euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

insurance companies Life insurance and capitalization Crédit Agricole Assurances 21177 Caisse Nationale de Prévoyance 17799 Axa France Assurance 10836 BNP Paribas Cardiff 13822 Crédit Mutuel 12593 Société Générale Insurance 10419 BPCE 10059 Generali 7117 Allianz 4821 Groupama-Gan 2639 Aviva 4633 Covéa (GMF-MAAF-MMA) 3469 AG2R La Mondiale 4393 Swiss Life 3288 Macif 1917 HSBC Assurances 2019 MACSF 1386 Other companies** 7139

Many of the insurance providers saw a value of under 500 million euros.

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/649.tsv"}, "mark": "line", "encoding": {"color": {"value": "#8c6d31"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Chrome"}, "field": "Chrome"}}, "title": ["Market share held by the leading internet", "browsers in Europe from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Chrome Dec 31, 2008 0.0313 Dec 31, 2009 0.1034 Dec 31, 2010 0.2012 Dec 31, 2011 0.303 Dec 31, 2012 0.3723 Dec 31, 2013 0.4177 Dec 31, 2014 0.4489 Dec 31, 2015 0.4971 Dec 31, 2016 0.5129 Dec 31, 2017 0.5651 Dec 31, 2018 0.5985

Chrome's market share has increased in a fairly linear fashion from below 0.1 in 2009, to 0.6 in 2019.

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/649.tsv"}, "mark": "area", "encoding": {"color": {"value": "#8c6d31"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Safari"}, "field": "Safari"}}, "title": ["Market share held by the leading internet", "browsers in Europe from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Safari Dec 31, 2008 0.029 Dec 31, 2009 0.0412 Dec 31, 2010 0.0527 Dec 31, 2011 0.0721 Dec 31, 2012 0.0897 Dec 31, 2013 0.1148 Dec 31, 2014 0.1106 Dec 31, 2015 0.1133 Dec 31, 2016 0.1209 Dec 31, 2017 0.1139 Dec 31, 2018 0.1192

market looks to have reached its peak increase was linear between 2010-2014.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/649.tsv"}, "mark": "line", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Edge Legacy"}, "field": "Edge Legacy"}}, "title": ["Market share held by the leading internet", "browsers in Europe from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Edge Legacy Dec 31, 2008 0 Dec 31, 2009 0 Dec 31, 2010 0 Dec 31, 2011 0 Dec 31, 2012 0 Dec 31, 2013 0 Dec 31, 2014 0.0054 Dec 31, 2015 0.0309 Dec 31, 2016 0.0451 Dec 31, 2017 0.0479 Dec 31, 2018 0.0514

In Europe the market share of the leading internet browsers rose sharply between 2014 and 2018. The highest rate of growth was during 2014. Market share growth rate started to slow down during the years 2016 to 2019.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/649.tsv"}, "mark": "area", "encoding": {"color": {"value": "#bf5b17"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Other"}, "field": "Other"}}, "title": ["Market share held by the leading internet", "browsers in Europe from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Other Dec 31, 2008 0.01 Dec 31, 2009 0.0081 Dec 31, 2010 0.0065 Dec 31, 2011 0.0096 Dec 31, 2012 0.0206 Dec 31, 2013 0.0304 Dec 31, 2014 0.0334 Dec 31, 2015 0.0346 Dec 31, 2016 0.0331 Dec 31, 2017 0.0288 Dec 31, 2018 0.027

SINCE 2009 AND UNTIL 2019 INCLUSIVE THE MARKET SHARE HELD BY THE LEADING INTRANET BROWSERS HAS MORE THAN TREBLED FROM POINT 0.010 TO 0.035.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/64.tsv"}, "mark": "area", "encoding": {"color": {"value": "#829eb1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "25 and over"}, "field": "25 and over"}}, "title": ["National minimum wage in the United Kingdom", "(UK) from 1999 to 2020 , by wage category", "(in GBP per hour)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 25 and over Dec 31, 1998 0 Dec 31, 1999 0 Dec 31, 2000 0 Dec 31, 2001 0 Dec 31, 2002 0 Dec 31, 2003 0 Dec 31, 2004 0 Dec 31, 2005 0 Dec 31, 2006 0 Dec 31, 2007 0 Dec 31, 2008 0 Dec 31, 2009 0 Dec 31, 2010 0 Dec 31, 2011 0 Dec 31, 2012 0 Dec 31, 2013 0 Dec 31, 2014 0 Dec 31, 2015 7.2 Dec 31, 2016 7.5 Dec 31, 2017 7.83 Dec 31, 2018 8.21 Dec 31, 2019 8.72

The data for the national minimum wage in the UK starts from 2016. There is no data shown before this date. The NMW commenced at £7.50 in 2016 and has steadily and evenly to £8.50 in 2020.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/64.tsv"}, "mark": "area", "encoding": {"color": {"value": "#829eb1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "25 and over"}, "field": "25 and over"}}, "title": ["National minimum wage in the United Kingdom", "(UK) from 1999 to 2020 , by wage category", "(in GBP per hour)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 25 and over Dec 31, 1998 0 Dec 31, 1999 0 Dec 31, 2000 0 Dec 31, 2001 0 Dec 31, 2002 0 Dec 31, 2003 0 Dec 31, 2004 0 Dec 31, 2005 0 Dec 31, 2006 0 Dec 31, 2007 0 Dec 31, 2008 0 Dec 31, 2009 0 Dec 31, 2010 0 Dec 31, 2011 0 Dec 31, 2012 0 Dec 31, 2013 0 Dec 31, 2014 0 Dec 31, 2015 7.2 Dec 31, 2016 7.5 Dec 31, 2017 7.83 Dec 31, 2018 8.21 Dec 31, 2019 8.72

The uk didn’t have a minimum wage before 2016. Between 2016 the minimum wage grew from just £7 to just over £8.20. The national minimum wage has never decreased, it has only ever increased.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/64.tsv"}, "mark": "area", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "18 to 21*"}, "field": "18 to 21*"}}, "title": ["National minimum wage in the United Kingdom", "(UK) from 1999 to 2020 , by wage category", "(in GBP per hour)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 18 to 21* Dec 31, 1998 3 Dec 31, 1999 3.2 Dec 31, 2000 3.5 Dec 31, 2001 3.5 Dec 31, 2002 3.8 Dec 31, 2003 4.1 Dec 31, 2004 4.25 Dec 31, 2005 4.45 Dec 31, 2006 4.6 Dec 31, 2007 4.77 Dec 31, 2008 4.83 Dec 31, 2009 0 Dec 31, 2010 0 Dec 31, 2011 0 Dec 31, 2012 0 Dec 31, 2013 0 Dec 31, 2014 0 Dec 31, 2015 0 Dec 31, 2016 0 Dec 31, 2017 0 Dec 31, 2018 0 Dec 31, 2019 0

No data is shown from 2008 onwards and so I cannot come to a full conclusion for this graph.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/6511.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#f0027f"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "destination of most affordable one-way tickets"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "End of March 2020"}, "field": "End of March 2020"}}, "title": ["Prices of most affordable one-way tickets", "of Aeroflot for domestic flights in Russia", "from end of March to June 2020 , by destination", "(in Russian rubles)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

destination of most affordable one-way tickets End of March 2020 Moscow - Krasnodar 2800 Moscow - Mineralnye Vody 2800 Moscow - Saint Petersburg 2400 Moscow - Volgograd 3400 Moscow - Yekaterinburg 3900 Moscow - Perm 3500

Moscow to Saint Peters burg was the cheapest flight and Moscow to yekaterinburg being the most expensive.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6511.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d09393"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "destination of most affordable one-way tickets"}, "y": {"type": "quantitative", "axis": {"title": "April and May 2020"}, "field": "April and May 2020"}}, "title": ["Prices of most affordable one-way tickets", "of Aeroflot for domestic flights in Russia", "from end of March to June 2020 , by destination", "(in Russian rubles)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

destination of most affordable one-way tickets April and May 2020 Moscow - Krasnodar 5900 Moscow - Mineralnye Vody 5900 Moscow - Saint Petersburg 4900 Moscow - Volgograd 6900 Moscow - Yekaterinburg 6600 Moscow - Perm 6900 Moscow - Omsk 9500

There is a general consistency in costings other than the Omsk data which appears to be an outlier.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/6511.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#5C6BC0"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "destination of most affordable one-way tickets"}, "y": {"type": "quantitative", "axis": {"title": "June 2020"}, "field": "June 2020"}}, "title": ["Prices of most affordable one-way tickets", "of Aeroflot for domestic flights in Russia", "from end of March to June 2020 , by destination", "(in Russian rubles)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

destination of most affordable one-way tickets June 2020 Moscow - Krasnodar 3000 Moscow - Mineralnye Vody 2400 Moscow - Saint Petersburg 2600 Moscow - Volgograd 3100 Moscow - Yekaterinburg 3200 Moscow - Perm 3100 Moscow - Omsk 5000 Moscow - Novosibirsk 5600 Moscow - Kazan 3000 Moscow - Krasnoyarsk 7100 Moscow - Irkutsk 9000 Moscow - Ufa 2500 Moscow - Sochi 2600

The most expensive route is Moscow - Irkutsk, which costs around 9,000 rubles. Three other destinations stand out as being noticeably more expensive than the majority: Krasnoyarsk (7,000 rubles), Novosibirsk (5,600 rubles) and Omsk (5,000). Other than the aforementioned routes, all the remaining nine are much cheaper, ranging from 2,200 rubles to 2,600 rubles.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/6511.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#5C6BC0"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "destination of most affordable one-way tickets"}, "y": {"type": "quantitative", "axis": {"title": "June 2020"}, "field": "June 2020"}}, "title": ["Prices of most affordable one-way tickets", "of Aeroflot for domestic flights in Russia", "from end of March to June 2020 , by destination", "(in Russian rubles)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

destination of most affordable one-way tickets June 2020 Moscow - Krasnodar 3000 Moscow - Mineralnye Vody 2400 Moscow - Saint Petersburg 2600 Moscow - Volgograd 3100 Moscow - Yekaterinburg 3200 Moscow - Perm 3100 Moscow - Omsk 5000 Moscow - Novosibirsk 5600 Moscow - Kazan 3000 Moscow - Krasnoyarsk 7100 Moscow - Irkutsk 9000 Moscow - Ufa 2500 Moscow - Sochi 2600

The most expensive flight on this bar chart is Moscow to Irkutsk. In Mar to Jun 2020 there were 9 flights costing less than 8000 rubels. Four flights from Moscow cost over 4000 rubels one way in Mar to Jun 2020.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6517.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#1A1A1A"}, "x": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"title": "2016"}, "field": "2016"}}, "title": ["Monthly rate of change in foreign exchange", "earnings from tourism in India from 2015", "to 2016 , with estimates until 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Month 2016 De 0.147; Month: Dec No 0.104; Month: Nov Oc 0.118; Month: Oct Se 0.109; Month: Sep Au 0.07; Month: Aug Ju 0.128; Month: Jul Ju 0.059; Month: Jun Ma 0.029; Month: May Ap 0.073; Month: Apr Ma 0.087; Month: Mar Fe 0.066; Month: Feb Ja 0.045; Month: Jan

There are two months which are less than 0.05. There are five months which are more than 0.10. There are five months which are between 0.05 and 0.10. No months are below 0.05. No months are above 0.15.

{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "multiColumn/data/6517.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#fbb4ae"}, "x": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "2018*"}, "field": "2018*"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Monthly rate of change in foreign exchange", "earnings from tourism in India from 2015", "to 2016 , with estimates until 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2018* Month −0.087 Dec −0.097 Nov −0.085 Oct −0.022 Sep 0.098 Aug 0.075 Jul 0.055 Jun −0.006 May 0.076 Apr 0.191 Mar 0.206 Feb 0.203 Jan

From March to February appears to be the months with the highest tourism income for India in 2018September through Mary appears to be the lowest tourism income in 2018.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/6528.tsv"}, "mark": "line", "encoding": {"color": {"value": "#829eb1"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Foreign"}, "field": "Foreign"}}, "title": ["Population of Finland from 2009 to 2019", ", by nationality"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Foreign Dec 31, 2008 155705 Dec 31, 2009 167954 Dec 31, 2010 183133 Dec 31, 2011 195511 Dec 31, 2012 207511 Dec 31, 2013 219675 Dec 31, 2014 229765 Dec 31, 2015 243639 Dec 31, 2016 249452 Dec 31, 2017 257572 Dec 31, 2018 267629

The graph shows a strong trend in the increase of foreign nationals. The graph shows a continuing upward trend.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/652.tsv"}, "mark": "area", "encoding": {"color": {"value": "#000000"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Brand value (Brand Finance)"}, "field": "Brand value (Brand Finance)"}}, "title": ["Manchester City brand/team value from 2011", "to 2020 (in million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Brand value (Brand Finance) Dec 31, 2010 170 Dec 31, 2011 302 Dec 31, 2012 332 Dec 31, 2013 510 Dec 31, 2014 800 Dec 31, 2015 905 Dec 31, 2016 1021 Dec 31, 2017 1331 Dec 31, 2018 1407 Dec 31, 2019 0

The value of the brand increased year on year, suggesting that the value of the brand increased.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6532.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#54a24b"}, "x": {"type": "quantitative", "axis": {"title": "Male"}, "field": "Male"}, "y": {"type": "nominal", "axis": {"labelAngle": -30}, "bin": false, "field": "news topic"}}, "title": ["Gender distribution of journalists in print", "news media in the United States as of November", "2017 , by news topic"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Male news topic 0.9 Sports 0.67 Technology and media 0.66 International news and politics 0.64 Business and economy 0.63 Arts and culture 0.61 U.S. elections 0.59 U.S. policy 0.59 Legal 0.57 Weather 0.56 Crime and police 0.55 Science and environment 0.54 Religion 0.54 Social and justice 0.52 Education 0.51 Entertainment 0.48 Lifestyle and leisure 0.42 Health

The bar graph indicates that certain categories have a higher prevalence (i.e. more than half) of male journalists covering that topic in print news media. The topic with the highest prevalence of male journalists as compared to female journalists is sports. The topics with the most equal distribution of male and female journalists covering them in print media are health and lifestyle and leisure.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6532.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#54a24b"}, "x": {"type": "quantitative", "axis": {"title": "Male"}, "field": "Male"}, "y": {"type": "nominal", "axis": {"labelAngle": -30}, "bin": false, "field": "news topic"}}, "title": ["Gender distribution of journalists in print", "news media in the United States as of November", "2017 , by news topic"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Male news topic 0.9 Sports 0.67 Technology and media 0.66 International news and politics 0.64 Business and economy 0.63 Arts and culture 0.61 U.S. elections 0.59 U.S. policy 0.59 Legal 0.57 Weather 0.56 Crime and police 0.55 Science and environment 0.54 Religion 0.54 Social and justice 0.52 Education 0.51 Entertainment 0.48 Lifestyle and leisure 0.42 Health

The bar chart graph shows the distribution of Journalist news topics as of November 2017, shows that the Male gender in Health was a little over 0.4 in November, which was at its lowest news media level. And the highest was Sport in this month, which rated at around 0.9. Sport was the most common topic for that month in the United States.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/6538.tsv"}, "mark": "line", "encoding": {"color": {"value": "#3e5c69"}, "x": {"type": "temporal", "axis": {"labelAngle": -30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Hepatitis A"}, "field": "Hepatitis A"}}, "title": ["Number of new cases of hepatitis A and B", "in the U.S. from 1970 to 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Hepatitis A Dec 31, 1969 56797 Dec 31, 1979 29087 Dec 31, 1984 23210 Dec 31, 1987 28507 Dec 31, 1988 35821 Dec 31, 1989 31441 Dec 31, 1990 24378 Dec 31, 1991 23112 Dec 31, 1992 24238 Dec 31, 1993 26796 Dec 31, 1994 31582 Dec 31, 1995 31032 Dec 31, 1996 30021 Dec 31, 1997 23229 Dec 31, 1998 17047 Dec 31, 1999 13397 Dec 31, 2000 10609 Dec 31, 2001 8795 Dec 31, 2002 7653 Dec 31, 2003 5683 Dec 31, 2004 4488 Dec 31, 2005 3579 Dec 31, 2006 2979 Dec 31, 2007 2585 Dec 31, 2008 1987 Dec 31, 2009 1670 Dec 31, 2010 1398 Dec 31, 2011 1562 Dec 31, 2012 1781 Dec 31, 2013 1239 Dec 31, 2014 1390 Dec 31, 2015 2007 Dec 31, 2016 3365

Since 1970 hepatitis A has been on the decrease, aside from 1985 and 1995 where it spiked. In 50 years Since 1970 we have seen hepatitis a cases go from almost 60,000 down to around 200.

{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "multiColumn/data/6538.tsv"}, "mark": "line", "encoding": {"color": {"value": "#118DFF"}, "x": {"type": "temporal", "axis": {"labelAngle": -90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Hepatitis B"}, "field": "Hepatitis B"}}, "title": ["Number of new cases of hepatitis A and B", "in the U.S. from 1970 to 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Hepatitis B Dec 31, 1969 8310 Dec 31, 1979 19015 Dec 31, 1984 26611 Dec 31, 1987 23177 Dec 31, 1988 23419 Dec 31, 1989 21102 Dec 31, 1990 18003 Dec 31, 1991 16126 Dec 31, 1992 13361 Dec 31, 1993 12517 Dec 31, 1994 10805 Dec 31, 1995 10637 Dec 31, 1996 10416 Dec 31, 1997 10258 Dec 31, 1998 7694 Dec 31, 1999 8036 Dec 31, 2000 7843 Dec 31, 2001 7996 Dec 31, 2002 7526 Dec 31, 2003 6212 Dec 31, 2004 5119 Dec 31, 2005 4713 Dec 31, 2006 4519 Dec 31, 2007 4033 Dec 31, 2008 3405 Dec 31, 2009 3374 Dec 31, 2010 2903 Dec 31, 2011 2895 Dec 31, 2012 3050 Dec 31, 2013 2791 Dec 31, 2014 3370 Dec 31, 2015 3218 Dec 31, 2016 3409

The number of new hepatits B cases peaked in the late 1980's but it has since declined.

{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "multiColumn/data/6538.tsv"}, "mark": "line", "encoding": {"color": {"value": "#118DFF"}, "x": {"type": "temporal", "axis": {"labelAngle": -90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Hepatitis B"}, "field": "Hepatitis B"}}, "title": ["Number of new cases of hepatitis A and B", "in the U.S. from 1970 to 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Hepatitis B Dec 31, 1969 8310 Dec 31, 1979 19015 Dec 31, 1984 26611 Dec 31, 1987 23177 Dec 31, 1988 23419 Dec 31, 1989 21102 Dec 31, 1990 18003 Dec 31, 1991 16126 Dec 31, 1992 13361 Dec 31, 1993 12517 Dec 31, 1994 10805 Dec 31, 1995 10637 Dec 31, 1996 10416 Dec 31, 1997 10258 Dec 31, 1998 7694 Dec 31, 1999 8036 Dec 31, 2000 7843 Dec 31, 2001 7996 Dec 31, 2002 7526 Dec 31, 2003 6212 Dec 31, 2004 5119 Dec 31, 2005 4713 Dec 31, 2006 4519 Dec 31, 2007 4033 Dec 31, 2008 3405 Dec 31, 2009 3374 Dec 31, 2010 2903 Dec 31, 2011 2895 Dec 31, 2012 3050 Dec 31, 2013 2791 Dec 31, 2014 3370 Dec 31, 2015 3218 Dec 31, 2016 3409

Over the last 40 years there have been about 9000 cases of hepatitis B with a sharp increase from 1970 to 1984 where it peeked at 30000 per year. Then after that a steady decline to its current level of about 8000 per year.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6559.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d6a5c9"}, "x": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "2013"}, "field": "2013"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "province of Canada"}}, "title": ["Total circulation of community newspapers", "in Canada from 2013 to 2019 , by province", "and territory (in 1,000s)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2013 province of Canada 7805.49 Ontario 4868.76 Quebec 3782.07 British Columbia 1029.01 Alberta 842.77 Saskatchewan 382.03 Nova Scotia 460.44 Manitoba 313.36 New Brunswick 54.95 Newfoundland/Labrador 30.81 Northwest Territory 14.31 Prince Edward Island 15.52 Nunavut Territory 13.78 Yukon Territory

Ontario, Canada has the highest circulation of community papers from 2013 to 2019 at almost 8000. Quebec, Canada had the second highest circulation of community papers from 2013 to 2019. New Brunswick, Canada had the lowest circulation of community papers from 2013 to 2019.

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/6559.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#bd9e39"}, "x": {"type": "quantitative", "axis": {"title": "2015"}, "field": "2015"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "province of Canada"}}, "title": ["Total circulation of community newspapers", "in Canada from 2013 to 2019 , by province", "and territory (in 1,000s)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2015 province of Canada 8739.15 Ontario 5297.98 Quebec 3818.78 British Columbia 1375.7 Alberta 489.24 Saskatchewan 477.21 Nova Scotia 431.24 Manitoba 219.53 New Brunswick 53.77 Newfoundland/Labrador 30.98 Northwest Territory 14.55 Prince Edward Island 14.27 Nunavut Territory 10.84 Yukon Territory

Ontario has a substantially higher volume of community newspapers in circulation than the other provinces in Canada. There are four provinces which do not have any community newspapers in circulation.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/655.tsv"}, "mark": "line", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Industry"}, "field": "Industry"}}, "title": ["Mexico : Distribution of the workforce across", "economic sectors from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Industry Dec 31, 2009 0.244 Dec 31, 2010 0.243 Dec 31, 2011 0.2406 Dec 31, 2012 0.2431 Dec 31, 2013 0.2481 Dec 31, 2014 0.2516 Dec 31, 2015 0.2575 Dec 31, 2016 0.2601 Dec 31, 2017 0.2613 Dec 31, 2018 0.2614 Dec 31, 2019 0.2619

I t shows that there is not a lot of difference.It has maybe gone up by0.01.

{"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": "multiColumn/data/6563.tsv"}, "mark": "area", "encoding": {"color": {"value": "#ff9e27"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Women"}, "field": "Women"}}, "title": ["Average age at the time of divorce in the", "Netherlands from 2008 to 2018 , by gender"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Women Dec 31, 2007 41.8 Dec 31, 2008 42.2 Dec 31, 2009 42.5 Dec 31, 2010 42.7 Dec 31, 2011 42.9 Dec 31, 2012 43 Dec 31, 2013 43.5 Dec 31, 2014 43.7 Dec 31, 2015 44 Dec 31, 2016 44.2 Dec 31, 2017 44.3

Between the years of 2008 and 2016 the average age of divorce for women in the Netherlands was over 40. The average age of divorce between 2008 and 2016 for women in the Netherlands has steadily increased.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/6565.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "occupation"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "12 books and over"}, "field": "12 books and over"}}, "title": ["Number of book readers in Italy in 2019", ", by occupation and number of books read", "(in 1,000 readers)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

occupation 12 books and over Middle management, white collar 939 Retired 733 Student 370 Housewife 316 Executive, employer, professional 255 Unemployed person with work experience 191 Blue collar, apprentice 178 Self-employed, family worker 165 Unemployed person without work experience 37 Other condition 26

the group with the largest number of book readers was middle management, and unemployed without work experience (and other) was the lowest.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6573.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Cardiology"}, "field": "Cardiology"}}, "title": ["Market size for biomarkers in the United", "States from 2015 to 2024 , by condition (in", "million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Cardiology Dec 31, 2014 2400 Dec 31, 2015 2900 Dec 31, 2016 3000 Dec 31, 2017 3500 Dec 31, 2018 4000 Dec 31, 2019 4600 Dec 31, 2020 5400 Dec 31, 2021 6200 Dec 31, 2022 7100 Dec 31, 2023 8200

The market size for Cardiology biomarkers has significantly increased since 2015 and has been predicted that this will continue until 2024. The rise is linear and steady over the years showing no clea sign of deviatiion.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6573.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Cardiology"}, "field": "Cardiology"}}, "title": ["Market size for biomarkers in the United", "States from 2015 to 2024 , by condition (in", "million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Cardiology Dec 31, 2014 2400 Dec 31, 2015 2900 Dec 31, 2016 3000 Dec 31, 2017 3500 Dec 31, 2018 4000 Dec 31, 2019 4600 Dec 31, 2020 5400 Dec 31, 2021 6200 Dec 31, 2022 7100 Dec 31, 2023 8200

The market size grew every year from 2015 to 2024. In 2024, the market size it at the highest. The highest market size is just over 8 billion dollars.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6573.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Cardiology"}, "field": "Cardiology"}}, "title": ["Market size for biomarkers in the United", "States from 2015 to 2024 , by condition (in", "million U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Cardiology Dec 31, 2014 2400 Dec 31, 2015 2900 Dec 31, 2016 3000 Dec 31, 2017 3500 Dec 31, 2018 4000 Dec 31, 2019 4600 Dec 31, 2020 5400 Dec 31, 2021 6200 Dec 31, 2022 7100 Dec 31, 2023 8200

The general trend increases from just above 2,000 cardiology bio markers in 2016 reaching 8,000 in 2022.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/6594.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#4285F4"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "New car"}, "field": "New car"}}, "title": ["Preferences for buying a car in the United", "Kingdom (UK) in 2015 , by type of car and", "region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Response New car London 0.19 South East 0.1 South West 0.15 Wales 0.28 East Anglia 0.14 East Midlands 0.13 West Midlands 0.1 Yorks/Humb 0.1 North West 0.2 North 0.21 Scotland 0.19

Wales has significantly more has more preference for new cars than other cities.

{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "multiColumn/data/65.tsv"}, "mark": "line", "encoding": {"color": {"value": "#D9B300"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Apple"}, "field": "Apple"}}, "title": ["Revenue comparison of Apple , Google , Alphabet", ", and Microsoft from 2008 to 2019 (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Apple Dec 31, 2007 37.5 Dec 31, 2008 42.9 Dec 31, 2009 65.2 Dec 31, 2010 108.2 Dec 31, 2011 156.5 Dec 31, 2012 170.9 Dec 31, 2013 182.8 Dec 31, 2014 233.72 Dec 31, 2015 215.64 Dec 31, 2016 229.23 Dec 31, 2017 265.6 Dec 31, 2018 260.17

The revenue for Apple steadily increases in the 10 year period the chart shows.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/65.tsv"}, "mark": "line", "encoding": {"color": {"value": "#74a9cf"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Microsoft"}, "field": "Microsoft"}}, "title": ["Revenue comparison of Apple , Google , Alphabet", ", and Microsoft from 2008 to 2019 (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Microsoft Dec 31, 2007 60.42 Dec 31, 2008 58.44 Dec 31, 2009 62.48 Dec 31, 2010 69.94 Dec 31, 2011 73.72 Dec 31, 2012 77.85 Dec 31, 2013 86.83 Dec 31, 2014 93.58 Dec 31, 2015 85.32 Dec 31, 2016 89.95 Dec 31, 2017 110.36 Dec 31, 2018 125.84

Microsoft revenue grew from 2008 to 2019. Year on year, revenue decreased in 2009 and 2016 and increased in all the other years. The sharpest increase was from 2017 onwards. The revenue reached a peak in 2015 before decreasing. They recovered their value by 2018.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/65.tsv"}, "mark": "line", "encoding": {"color": {"value": "#74a9cf"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Microsoft"}, "field": "Microsoft"}}, "title": ["Revenue comparison of Apple , Google , Alphabet", ", and Microsoft from 2008 to 2019 (in billion", "U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Microsoft Dec 31, 2007 60.42 Dec 31, 2008 58.44 Dec 31, 2009 62.48 Dec 31, 2010 69.94 Dec 31, 2011 73.72 Dec 31, 2012 77.85 Dec 31, 2013 86.83 Dec 31, 2014 93.58 Dec 31, 2015 85.32 Dec 31, 2016 89.95 Dec 31, 2017 110.36 Dec 31, 2018 125.84

There is a steep increase of revenue between 2017 and 2020.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6603.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1A1A1A"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Deaths"}, "field": "Deaths"}}, "title": ["Total number of births , deaths and birth", "excess in the Netherlands from 2008 to 2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Deaths Dec 31, 2007 135136 Dec 31, 2008 134235 Dec 31, 2009 136058 Dec 31, 2010 135741 Dec 31, 2011 140813 Dec 31, 2012 141245 Dec 31, 2013 139223 Dec 31, 2014 147134 Dec 31, 2015 148997 Dec 31, 2016 150214 Dec 31, 2017 153363

Then number of births, deaths and birth excess in the Netherlands peaked in 2018 at over 150,000. The lowest year was 2011.

{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "multiColumn/data/6603.tsv"}, "mark": "area", "encoding": {"color": {"value": "#a6761d"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Excess births"}, "field": "Excess births"}}, "title": ["Total number of births , deaths and birth", "excess in the Netherlands from 2008 to 2018"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Excess births Dec 31, 2007 49498 Dec 31, 2008 50680 Dec 31, 2009 48339 Dec 31, 2010 44319 Dec 31, 2011 35146 Dec 31, 2012 30096 Dec 31, 2013 35958 Dec 31, 2014 23376 Dec 31, 2015 23523 Dec 31, 2016 19622 Dec 31, 2017 15162

The total number of births and deaths in the netherlands have been declining for the year 2008.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/660.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#000000"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"title": "2017"}, "field": "2017"}}, "title": ["Average retail price for roasted coffee", "in Canada from January 2015 to June 2020", "(in Canadian dollars per 300 grams)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Month 2017 De 6.31; Month: Dec No 6.39; Month: Nov Oc 6.47; Month: Oct Se 6.46; Month: Sep Au 6.58; Month: Aug Ju 6.53; Month: Jul Ju 6.59; Month: Jun Ma 6.5; Month: May Ap 6.6; Month: Apr Ma 6.44; Month: Mar Fe 6.27; Month: Feb Ja 6.29; Month: Jan

The average retail price for roasted coffee in Canada hasn't fluctuated very much.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/660.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#9E9D24"}, "x": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "2020"}, "field": "2020"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Average retail price for roasted coffee", "in Canada from January 2015 to June 2020", "(in Canadian dollars per 300 grams)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2020 Month 5.04 Jun 4.88 May 4.99 Apr 5 Mar 5.02 Feb 4.95 Jan

In 2020, from the months January to May, the average retail price of roasted coffee stayed roughly the same, at just under 5 CAD per 300g.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6612.tsv"}, "mark": "area", "encoding": {"color": {"value": "#ab5787"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "0-14 years"}, "field": "0-14 years"}}, "title": ["Sudan : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 0-14 years Dec 31, 2008 0.4315 Dec 31, 2009 0.4299 Dec 31, 2010 0.4276 Dec 31, 2011 0.4248 Dec 31, 2012 0.4218 Dec 31, 2013 0.4185 Dec 31, 2014 0.415 Dec 31, 2015 0.4119 Dec 31, 2016 0.4085 Dec 31, 2017 0.4051 Dec 31, 2018 0.4016

The y axis representing the ages of 0 to 14 years has an indice of 0.0 to 0.4 but does not explain the value of indice (eg. percentage of population). It is therefore impossible to evaluate and describe what this area chart is showing, other than the area fills from around 0.42 in 2009 to 0.4 on the furthest point on y axis, just beyond year 2018, all along on the x axis. It looks like a square with a small wedge cut out from the right.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6612.tsv"}, "mark": "area", "encoding": {"color": {"value": "#ab5787"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "0-14 years"}, "field": "0-14 years"}}, "title": ["Sudan : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 0-14 years Dec 31, 2008 0.4315 Dec 31, 2009 0.4299 Dec 31, 2010 0.4276 Dec 31, 2011 0.4248 Dec 31, 2012 0.4218 Dec 31, 2013 0.4185 Dec 31, 2014 0.415 Dec 31, 2015 0.4119 Dec 31, 2016 0.4085 Dec 31, 2017 0.4051 Dec 31, 2018 0.4016

The number of children between the ages of 0-14 years has steadily decreased in Sudan from 2009 to 2019.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6612.tsv"}, "mark": "line", "encoding": {"color": {"value": "#d98445"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "65 years and older"}, "field": "65 years and older"}}, "title": ["Sudan : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 65 years and older Dec 31, 2008 0.0324 Dec 31, 2009 0.0327 Dec 31, 2010 0.033 Dec 31, 2011 0.0334 Dec 31, 2012 0.0337 Dec 31, 2013 0.0341 Dec 31, 2014 0.0344 Dec 31, 2015 0.0349 Dec 31, 2016 0.0354 Dec 31, 2017 0.0358 Dec 31, 2018 0.0363

I can see that over time, the percentage of people over age 65 in Sudan is getting gradually larger. I can observe for the line never dips below 0.03 and how it stays under 0.04.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6616.tsv"}, "mark": "area", "encoding": {"color": {"value": "#C9C9C9"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Group life insurance"}, "field": "Group life insurance"}}, "title": ["Number of persons covered by life insurance", "on the domestic market in Italy from 2004", "to 2017 , by type of contract (in millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Group life insurance Dec 31, 2003 6.06 Dec 31, 2004 7.63 Dec 31, 2005 10.69 Dec 31, 2006 12.24 Dec 31, 2007 13.79 Dec 31, 2008 12.98 Dec 31, 2009 13.98 Dec 31, 2010 12.49 Dec 31, 2011 10.35 Dec 31, 2012 9.86 Dec 31, 2013 9.9 Dec 31, 2014 9.08 Dec 31, 2015 9.11 Dec 31, 2016 8.7

2004 shows the lowest amount of people in Italy with life insurance at around 6 million. This increases as the Years go on and reach dramatic increase in years 2008-2010 to 14 million people. By 2011 this has dipped to 10 million people and is slowly decreasing through years 2011-2016.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/6620.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ab7fb4"}, "x": {"type": "quantitative", "axis": {"title": "United States"}, "field": "United States"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Quarter"}}, "title": ["Employment rate in major developed countries", "from Q2 2016 to Q2 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

United States Quarter 0.6253 Q2 2020 0.7141 Q1 2020 0.7168 Q4 2019 0.7146 Q3 2019 0.712 Q2 2019 0.7108 Q1 2019 0.7095 Q4 2018 0.7073 Q3 2018 0.7069 Q2 2018 0.7053 Q1 2018 0.7026 Q4 2017 0.7027 Q3 2017 0.7009 Q2 2017 0.6981 Q1 2017 0.6951 Q4 2016 0.6938 Q3 2016 0.6924 Q2 2016

Employment appears to be consistently higher in the first quarter of the year for the years shown, and less so in the others, especially in the second quarter of the year.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/6620.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ab7fb4"}, "x": {"type": "quantitative", "axis": {"title": "United States"}, "field": "United States"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Quarter"}}, "title": ["Employment rate in major developed countries", "from Q2 2016 to Q2 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

United States Quarter 0.6253 Q2 2020 0.7141 Q1 2020 0.7168 Q4 2019 0.7146 Q3 2019 0.712 Q2 2019 0.7108 Q1 2019 0.7095 Q4 2018 0.7073 Q3 2018 0.7069 Q2 2018 0.7053 Q1 2018 0.7026 Q4 2017 0.7027 Q3 2017 0.7009 Q2 2017 0.6981 Q1 2017 0.6951 Q4 2016 0.6938 Q3 2016 0.6924 Q2 2016

The employment rate in the USA was the lowest in 2020. Apart from 2020 the employment rate in the USA remained almost constant.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/6625.tsv"}, "mark": "line", "encoding": {"color": {"value": "#0570b0"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Industry"}, "field": "Industry"}}, "title": ["Greenhouse gas emissions volume in the European", "Union from 1990 to 2017 , by sector (in kilotonnes", "of CO2-equivalent)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Industry Dec 31, 1989 1353316 Dec 31, 1990 1278810 Dec 31, 1991 1223264 Dec 31, 1992 1187343 Dec 31, 1993 1213676 Dec 31, 1994 1246159 Dec 31, 1995 1239324 Dec 31, 1996 1236184 Dec 31, 1997 1178137 Dec 31, 1998 1121533 Dec 31, 1999 1140578 Dec 31, 2000 1107678 Dec 31, 2001 1084204 Dec 31, 2002 1103340 Dec 31, 2003 1111856 Dec 31, 2004 1104392 Dec 31, 2005 1093474 Dec 31, 2006 1108157 Dec 31, 2007 1054599 Dec 31, 2008 877769 Dec 31, 2009 927264 Dec 31, 2010 907848 Dec 31, 2011 874313 Dec 31, 2012 863762 Dec 31, 2013 862470 Dec 31, 2014 860258 Dec 31, 2015 857770 Dec 31, 2016 877315

In 1990 greenhouse gas emissions from the European Union were at their highest; almost 1,400,000 kilotonnes. Since then emissions have continuously decreased, and in 2017 stood around 900,000. This is a large decrease of around 500,000 kilotonnes. Despite the decline, the end of the line graph suggests that in 2016 the emissions have begun to rise again.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/6625.tsv"}, "mark": "area", "encoding": {"color": {"value": "#AB47BC"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Residential/commercial"}, "field": "Residential/commercial"}}, "title": ["Greenhouse gas emissions volume in the European", "Union from 1990 to 2017 , by sector (in kilotonnes", "of CO2-equivalent)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Residential/commercial Dec 31, 1989 728514 Dec 31, 1990 779624 Dec 31, 1991 725378 Dec 31, 1992 739146 Dec 31, 1993 691489 Dec 31, 1994 695594 Dec 31, 1995 759936 Dec 31, 1996 712213 Dec 31, 1997 700633 Dec 31, 1998 688987 Dec 31, 1999 666271 Dec 31, 2000 713171 Dec 31, 2001 683021 Dec 31, 2002 697859 Dec 31, 2003 695076 Dec 31, 2004 691137 Dec 31, 2005 687546 Dec 31, 2006 613011 Dec 31, 2007 661021 Dec 31, 2008 645333 Dec 31, 2009 686910 Dec 31, 2010 594963 Dec 31, 2011 612073 Dec 31, 2012 616751 Dec 31, 2013 525657 Dec 31, 2014 556390 Dec 31, 2015 567325 Dec 31, 2016 568900

There is a steady decline in the value from approximately 700,000 at the start of the period to approximately 550,000 at the end of the period. There appears to two different rates of reduction, between 1990 and 2005 where the reduction is at a slower rate, and between 2005 and 2017 where it accelerates. The data is somewhat noisy with individual years being slightly above or below the average.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/6625.tsv"}, "mark": "area", "encoding": {"color": {"value": "#5C6BC0"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "Waste"}, "field": "Waste"}}, "title": ["Greenhouse gas emissions volume in the European", "Union from 1990 to 2017 , by sector (in kilotonnes", "of CO2-equivalent)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Waste Dec 31, 1989 240421 Dec 31, 1990 244026 Dec 31, 1991 246078 Dec 31, 1992 247041 Dec 31, 1993 246587 Dec 31, 1994 247432 Dec 31, 1995 246648 Dec 31, 1996 243614 Dec 31, 1997 240153 Dec 31, 1998 234734 Dec 31, 1999 231455 Dec 31, 2000 227377 Dec 31, 2001 223464 Dec 31, 2002 217386 Dec 31, 2003 208856 Dec 31, 2004 202009 Dec 31, 2005 195842 Dec 31, 2006 189111 Dec 31, 2007 181139 Dec 31, 2008 175139 Dec 31, 2009 167818 Dec 31, 2010 162056 Dec 31, 2011 157924 Dec 31, 2012 151173 Dec 31, 2013 145493 Dec 31, 2014 143160 Dec 31, 2015 140109 Dec 31, 2016 138866

The volume of greenhouse gas emissions has been steadily declining since 1995.

{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "multiColumn/data/6625.tsv"}, "mark": "area", "encoding": {"color": {"value": "#fbb4ae"}, "x": {"type": "temporal", "axis": {"labelAngle": 60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "International aviation"}, "field": "International aviation"}}, "title": ["Greenhouse gas emissions volume in the European", "Union from 1990 to 2017 , by sector (in kilotonnes", "of CO2-equivalent)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year International aviation Dec 31, 1989 69141 Dec 31, 1990 68038 Dec 31, 1991 73588 Dec 31, 1992 77666 Dec 31, 1993 81150 Dec 31, 1994 85760 Dec 31, 1995 89898 Dec 31, 1996 94072 Dec 31, 1997 100919 Dec 31, 1998 109470 Dec 31, 1999 115442 Dec 31, 2000 113824 Dec 31, 2001 110793 Dec 31, 2002 115225 Dec 31, 2003 122972 Dec 31, 2004 131053 Dec 31, 2005 136547 Dec 31, 2006 141127 Dec 31, 2007 141760 Dec 31, 2008 131143 Dec 31, 2009 131712 Dec 31, 2010 135415 Dec 31, 2011 133524 Dec 31, 2012 134731 Dec 31, 2013 136880 Dec 31, 2014 141218 Dec 31, 2015 148008 Dec 31, 2016 158268

Greenhouse gas emissions volume has nearly tripled since 1990. The largest single jump is from 1990 - 2000 from approximately 75,000 to 125,000.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6625.tsv"}, "mark": "line", "encoding": {"color": {"value": "#79706e"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "International shipping"}, "field": "International shipping"}}, "title": ["Greenhouse gas emissions volume in the European", "Union from 1990 to 2017 , by sector (in kilotonnes", "of CO2-equivalent)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year International shipping Dec 31, 1989 110721 Dec 31, 1990 109111 Dec 31, 1991 110811 Dec 31, 1992 111563 Dec 31, 1993 111333 Dec 31, 1994 111444 Dec 31, 1995 119280 Dec 31, 1996 129403 Dec 31, 1997 134933 Dec 31, 1998 129483 Dec 31, 1999 136180 Dec 31, 2000 141412 Dec 31, 2001 146477 Dec 31, 2002 148657 Dec 31, 2003 158212 Dec 31, 2004 162326 Dec 31, 2005 174044 Dec 31, 2006 181961 Dec 31, 2007 183308 Dec 31, 2008 164257 Dec 31, 2009 161437 Dec 31, 2010 163103 Dec 31, 2011 150518 Dec 31, 2012 142456 Dec 31, 2013 139311 Dec 31, 2014 138245 Dec 31, 2015 145122 Dec 31, 2016 145765

Emmision steady growth between 1990 and 2007/8. The level of 180,000 was reached. Decrease can be seen since than. Reaching just below 150,000 in 2015.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6629.tsv"}, "mark": "line", "encoding": {"color": {"value": "#f2cf5b"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Total"}, "field": "Total"}}, "title": ["Total and pedestrian fatalities in U.S.", "traffic crashes from 2001 to 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Total Dec 31, 2000 42196 Dec 31, 2001 43005 Dec 31, 2002 42884 Dec 31, 2003 42836 Dec 31, 2004 43510 Dec 31, 2005 42708 Dec 31, 2006 41259 Dec 31, 2007 37423 Dec 31, 2008 33883 Dec 31, 2009 32999 Dec 31, 2010 32479 Dec 31, 2011 33782 Dec 31, 2012 32894 Dec 31, 2013 32744 Dec 31, 2014 35485 Dec 31, 2015 37806 Dec 31, 2016 37133

There was a decrease in fatalities before the number rose again.

{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "multiColumn/data/6629.tsv"}, "mark": "area", "encoding": {"color": {"value": "#cccccc"}, "x": {"type": "temporal", "axis": {"labelAngle": 45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Pedestrian"}, "field": "Pedestrian"}}, "title": ["Total and pedestrian fatalities in U.S.", "traffic crashes from 2001 to 2017"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Pedestrian Dec 31, 2000 4901 Dec 31, 2001 4851 Dec 31, 2002 4774 Dec 31, 2003 4675 Dec 31, 2004 4892 Dec 31, 2005 4795 Dec 31, 2006 4669 Dec 31, 2007 4414 Dec 31, 2008 4109 Dec 31, 2009 4302 Dec 31, 2010 4457 Dec 31, 2011 4818 Dec 31, 2012 4779 Dec 31, 2013 4910 Dec 31, 2014 5495 Dec 31, 2015 6080 Dec 31, 2016 5977

The pattern in pedestrian fatalities is unsteady. Fatalities reached a low in about 2008 of roughly 4,000, nearly 1,000 fatalities lower than the starting point in 2001. Between 2001 and 2016, fatalities generally increased rapidly to roughly 6,000 before decreasing slightly in 2017.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6638.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#94aace"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}, "y": {"type": "quantitative", "axis": {"title": "2007"}, "field": "2007"}}, "title": ["Estimated change in GDP in selected countries", "due to economic crisis in percent"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Country 2007 Irelan 6; Country: Ireland Japa 2.4; Country: Japan German 2.5; Country: Germany Finlan 4.2; Country: Finland Netherland 3.5; Country: Netherlands Luxembour 5.2; Country: Luxembourg Ital 1.6; Country: Italy Portuga 1.9; Country: Portugal Great Britai 3; Country: Great Britain Belgiu 2.6; Country: Belgium Franc 2.1; Country: France Austri 3.1; Country: Austria Spai 3.7; Country: Spain US 2; Country: USA Sloveni 6.8; Country: Slovenia Canad 2.7; Country: Canada Slovaki 10.4; Country: Slovakia Malt 3.6; Country: Malta Greec 4; Country: Greece Cypru 4.4; Country: Cyprus

Slovakia saw the biggest change in GDP with over 10%.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/6638.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6793a6"}, "x": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "2008"}, "field": "2008"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Country"}}, "title": ["Estimated change in GDP in selected countries", "due to economic crisis in percent"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2008 Country −2.3 Ireland −0.6 Japan 1.3 Germany 0.9 Finland 2 Netherlands 0.7 Luxembourg −1 Italy 0 Portugal 0.7 Great Britain 1.1 Belgium 0.7 France 1.8 Austria 1.2 Spain 1.1 USA 3.5 Slovenia 0.5 Canada 6.4 Slovakia 1.6 Malta 2.9 Greece 3.7 Cyprus

Slovakia has the highest estimated change in GDP at 6%. Ireland has the lowest estimated change in GDP at -2.2%.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/6638.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#7fc97f"}, "x": {"type": "quantitative", "axis": {"title": "2009 *"}, "field": "2009 *"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Country"}}, "title": ["Estimated change in GDP in selected countries", "due to economic crisis in percent"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2009 * Country −8 Ireland −6.2 Japan −5.6 Germany −5.2 Finland −4.8 Netherlands −4.8 Luxembourg −4.4 Italy −4.1 Portugal −4.1 Great Britain −3.8 Belgium −3 France −3 Austria −3 Spain −2.8 USA −2.7 Slovenia −2.5 Canada −2.1 Slovakia −1.5 Malta −0.2 Greece 0.3 Cyprus

Almost all countries showed some degree of GDP drop with the only exception being Cyprus showing slightly improved GDP. The average GDP drop in 2009 was between -2 and -6 with only Ireland and Japan having a drop greater than -6. Only 2 countries, Malta and Greece showed a drop of less than -2 but greater than 0.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6639.tsv"}, "mark": "line", "encoding": {"color": {"value": "#1A1A1A"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Did not use the internet in the last three months"}, "field": "Did not use the internet in the last three months"}}, "title": ["Internet usage frequency in Great Britain", "from 2006 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Did not use the internet in the last three months Dec 31, 2005 0.4 Dec 31, 2006 0.33 Dec 31, 2007 0.29 Dec 31, 2008 0.24 Dec 31, 2009 0.23 Dec 31, 2010 0.2 Dec 31, 2011 0.18 Dec 31, 2012 0.15 Dec 31, 2013 0.13 Dec 31, 2014 0.13 Dec 31, 2015 0.1 Dec 31, 2016 0.1 Dec 31, 2017 0.09 Dec 31, 2018 0.07 Dec 31, 2019 0.05

The number of people not using the Internet in the last 3 months has steadily declined between 2006 and 2018.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6639.tsv"}, "mark": "line", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "Daily"}, "field": "Daily"}}, "title": ["Internet usage frequency in Great Britain", "from 2006 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Daily Dec 31, 2005 0.35 Dec 31, 2006 0.45 Dec 31, 2007 0.49 Dec 31, 2008 0.55 Dec 31, 2009 0.6 Dec 31, 2010 0.64 Dec 31, 2011 0.68 Dec 31, 2012 0.73 Dec 31, 2013 0.76 Dec 31, 2014 0.77 Dec 31, 2015 0.82 Dec 31, 2016 0.8 Dec 31, 2017 0.86 Dec 31, 2018 0.87 Dec 31, 2019 0.89

From the line chart provided I can read that daily usage of internet was growing steadily each year, to reach around 0.9 in 2020.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6656.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#a99cbc"}, "x": {"type": "quantitative", "axis": {"title": "Migration balance"}, "field": "Migration balance"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Total immigration , total emigration and", "the migration balance in the Netherlands", "in 2019 , by age"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Migration balance Year 10057 Younger than 10 years 22234 10-20 years 35942 20-30 years 24114 30-40 years 11604 40-50 years 3510 50-60 years −156 60-70 years 469 70-80 years 241 80-90 years 20 90 years and older

The majority of immigrants to the Netherlands are younger, and likely professionals or students due to age.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6658.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Elementary education"}, "field": "Elementary education"}}, "title": ["Annual Flemish education budget in Belgium", "from 2010 to 2019 , by educational level", "(in thousand euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Elementary education Dec 31, 2009 3195164 Dec 31, 2010 3315165 Dec 31, 2011 3467787 Dec 31, 2012 3641127 Dec 31, 2013 3711241 Dec 31, 2014 3737469 Dec 31, 2015 3875231 Dec 31, 2016 3966934 Dec 31, 2017 4080732 Dec 31, 2018 4234309

The budget has increased every year shown. The budget has increased by over €1million over the years shown. The smallest increase in budget was between 2013 and 2015.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6658.tsv"}, "mark": "area", "encoding": {"color": {"value": "#1696d2"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "Elementary education"}, "field": "Elementary education"}}, "title": ["Annual Flemish education budget in Belgium", "from 2010 to 2019 , by educational level", "(in thousand euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Elementary education Dec 31, 2009 3195164 Dec 31, 2010 3315165 Dec 31, 2011 3467787 Dec 31, 2012 3641127 Dec 31, 2013 3711241 Dec 31, 2014 3737469 Dec 31, 2015 3875231 Dec 31, 2016 3966934 Dec 31, 2017 4080732 Dec 31, 2018 4234309

has increased every year from 2010 (3 000 000) though between 2013 and 2015 it was the slowest increase and 2019 level approaching 4 500 000.

{"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": "multiColumn/data/6658.tsv"}, "mark": "area", "encoding": {"color": {"value": "#9fe4f8"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Tertiary education"}, "field": "Tertiary education"}}, "title": ["Annual Flemish education budget in Belgium", "from 2010 to 2019 , by educational level", "(in thousand euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Tertiary education Dec 31, 2009 1652037 Dec 31, 2010 1669649 Dec 31, 2011 1644017 Dec 31, 2012 1683089 Dec 31, 2013 1746645 Dec 31, 2014 1707300 Dec 31, 2015 1753481 Dec 31, 2016 1882633 Dec 31, 2017 1885147 Dec 31, 2018 1975264

The budget was at approx 1600000 in 20010 and steadily increased to just below 2000000 in 2019.

{"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": "multiColumn/data/6658.tsv"}, "mark": "area", "encoding": {"color": {"value": "#9fe4f8"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Tertiary education"}, "field": "Tertiary education"}}, "title": ["Annual Flemish education budget in Belgium", "from 2010 to 2019 , by educational level", "(in thousand euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Tertiary education Dec 31, 2009 1652037 Dec 31, 2010 1669649 Dec 31, 2011 1644017 Dec 31, 2012 1683089 Dec 31, 2013 1746645 Dec 31, 2014 1707300 Dec 31, 2015 1753481 Dec 31, 2016 1882633 Dec 31, 2017 1885147 Dec 31, 2018 1975264

The graph shows positive correlation between the education level an years meaning the average education budget has increased.

{"config": {"background": "#666", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#fbb4ae", "#b3cde3", "#ccebc5", "#decbe4", "#fed9a6", "#ffffcc", "#e5d8bd", "#fddaec", "#f2f2f2", "#b3e2cd", "#fdcdac", "#cbd5e8", "#f4cae4", "#e6f5c9", "#fff2ae", "#f1e2cc", "#cccccc"]}}, "data": {"url": "multiColumn/data/6674.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#fbb4ae"}, "x": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "2017"}, "field": "2017"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "airports in Poland"}}, "title": ["Volume of freight on board reported by airports", "in Poland from 2017 to 2019 (in 1,000 kg)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2017 airports in Poland 84389.44 Warsaw Chopin Airport 15233.86 Katowice-Pyrzowice* 5118.05 Gdańsk Lech Wałęsa Airport 392.78 Rzeszów-Jasionka 944.06 Wrocław-Strachowice 466.4 Poznań-Ławica 129.64 Szczecin-Goleniów 23.55 Bydgoszcz-Szwederowo 0.11 Kraków-Balice 0 Łódź-Lublinek 0.01 Port Lotniczy Lublin

Warsaw Chopin Airport had the biggest volume of freight on board from 2017 to 2019, and it was over 80000. Next one was Katowice-Pyrzowice, with nearly 20000. Third airport with the biggest volume of freight on board was Gdańsk Lech Wałęsa Airport and it was about 5000. Three airports (Poznań-Ławica, Rzeszów-Jasionka and Wrocław-Starachowice) had a very small volume of freight, less than 1000. The last four airports (Bydgoszcz-Szwederowo, Kraków-Balice, Port Lotniczy Lublin, Łódź-Lublinek) had zero volume of freight on board.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/667.tsv"}, "mark": "area", "encoding": {"color": {"value": "#182429"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Agriculture"}, "field": "Agriculture"}}, "title": ["Spain : Distribution of the workforce across", "economic sectors from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Agriculture Dec 31, 2009 0.042 Dec 31, 2010 0.041 Dec 31, 2011 0.0422 Dec 31, 2012 0.043 Dec 31, 2013 0.0424 Dec 31, 2014 0.0412 Dec 31, 2015 0.0422 Dec 31, 2016 0.0435 Dec 31, 2017 0.042 Dec 31, 2018 0.0409 Dec 31, 2019 0.04

Distribution of labor in the agricultural sector between 2010 and 2020 fluctuates between 0.4 and 0.45.

{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/667.tsv"}, "mark": "line", "encoding": {"color": {"value": "#74a9cf"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Industry"}, "field": "Industry"}}, "title": ["Spain : Distribution of the workforce across", "economic sectors from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Industry Dec 31, 2009 0.2297 Dec 31, 2010 0.2176 Dec 31, 2011 0.2067 Dec 31, 2012 0.1975 Dec 31, 2013 0.1945 Dec 31, 2014 0.199 Dec 31, 2015 0.1961 Dec 31, 2016 0.2006 Dec 31, 2017 0.2033 Dec 31, 2018 0.2028 Dec 31, 2019 0.2018

The workforce in industry in 2010 sits around 0.24, drops linearly to just below 0.2 in 2014 and then remains around that figure until 2020.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6689.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#79706e"}, "x": {"type": "quantitative", "axis": {"title": "Republicans and allies"}, "field": "Republicans and allies"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "State"}}, "title": ["Estimated cost per eligible voter for political", "TV ads and campaigns in the 2014 U.S. midterm", "elections , by state and political party", "(in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Republicans and allies State 5.87 Alaska 6.78 Iowa 5.97 Arkansas 5.01 New Hampshire 6.05 Kentucky 4.49 Colorado 3.94 North Carolina 2.87 Louisiana 2.1 South Dakota 3.72 Georgia 2.01 Michigan 1.42 Kansas 2.35 Montana 3.32 Mississippi 2.03 Maine 0.02 Hawaii 0.77 Minnesota 1.08 Oregon 1.55 West Virginia 0.68 Virginia 0.6 New Mexico 1.66 Oklahoma 1.53 Nebraska 0 Delaware 0.93 South Carolina 0.72 Tennessee 0.14 Illinois 0 Rhode Island 0.04 Texas 0.08 Wyoming

Only 4 states exceeded the expenditure of all others - these were Alaska, Arkansas, Iowa and Kentucky. Delaware, Hawaii, Rhode Island and Texas had no expenditure per voter. Illinois, Minnesota, New Mexico, Tennessee and Virginia all had very low expenditures compared to others.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6693.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d2d2d2"}, "x": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "2018"}, "field": "2018"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Month"}}, "title": ["Monthly export value of farm and fishing", "products in Canada from 2015 to 2020 (in", "billion Canadian dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2018 Month 2.93 Dec 2.83 Nov 3 Oct 2.82 Sep 2.88 Aug 2.93 Jul 2.97 Jun 2.91 May 2.85 Apr 2.84 Mar 2.51 Feb 2.81 Jan

The highest value of products exported in Canada was seen in October, with the lowest value seen in February.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6701.tsv"}, "mark": "line", "encoding": {"color": {"value": "#8aa453"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "0-14 years"}, "field": "0-14 years"}}, "title": ["Malta : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 0-14 years Dec 31, 2008 0.1539 Dec 31, 2009 0.1499 Dec 31, 2010 0.1479 Dec 31, 2011 0.1459 Dec 31, 2012 0.1441 Dec 31, 2013 0.1429 Dec 31, 2014 0.1423 Dec 31, 2015 0.1421 Dec 31, 2016 0.1423 Dec 31, 2017 0.1428 Dec 31, 2018 0.1433

After a slight decline in age structure,the chart appears to show a fairly stable age structure from 2012 all the way to 2018. Signs of a slight increase 2019 onwards.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6701.tsv"}, "mark": "line", "encoding": {"color": {"value": "#8aa453"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "0-14 years"}, "field": "0-14 years"}}, "title": ["Malta : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 0-14 years Dec 31, 2008 0.1539 Dec 31, 2009 0.1499 Dec 31, 2010 0.1479 Dec 31, 2011 0.1459 Dec 31, 2012 0.1441 Dec 31, 2013 0.1429 Dec 31, 2014 0.1423 Dec 31, 2015 0.1421 Dec 31, 2016 0.1423 Dec 31, 2017 0.1428 Dec 31, 2018 0.1433

The trend in Malta for 0-14yrs has not changed dramatically in the years 2010 to 2018 although it did dip down in the early years, it then leveled out around 2016 and even seems to be increasing slightly in the last few years.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6701.tsv"}, "mark": "area", "encoding": {"color": {"value": "#999999"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "15-64 years"}, "field": "15-64 years"}}, "title": ["Malta : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 15-64 years Dec 31, 2008 0.6953 Dec 31, 2009 0.6932 Dec 31, 2010 0.6899 Dec 31, 2011 0.6857 Dec 31, 2012 0.6807 Dec 31, 2013 0.6752 Dec 31, 2014 0.6698 Dec 31, 2015 0.6641 Dec 31, 2016 0.6588 Dec 31, 2017 0.6537 Dec 31, 2018 0.6485

This was very difficult to describe. It shows a general decline of ages 15-64 years from 2010 to 2019.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/6701.tsv"}, "mark": "line", "encoding": {"color": {"value": "#666666"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 0, "title": "65 years and older"}, "field": "65 years and older"}}, "title": ["Malta : Age structure from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 65 years and older Dec 31, 2008 0.1508 Dec 31, 2009 0.1569 Dec 31, 2010 0.1622 Dec 31, 2011 0.1684 Dec 31, 2012 0.1752 Dec 31, 2013 0.1819 Dec 31, 2014 0.1879 Dec 31, 2015 0.1938 Dec 31, 2016 0.1989 Dec 31, 2017 0.2035 Dec 31, 2018 0.2082

This chart shows 2019 as recording the highest age structure in Matla for 65 years and older.

{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "multiColumn/data/6708.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#4D4D4D"}, "x": {"type": "quantitative", "axis": {"labelAngle": -30, "title": "2010"}, "field": "2010"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "injury type"}}, "title": ["Number of medical malpractice payments made", "in the U.S. from 2010 to 2013 , by injury", "type"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2010 injury type 3404 Death 1475 Significant permanent injury 1192 Minor permanent injury 1117 Major temporary injury 1062 Major permanent injury 919 Minor temporary injury 562 Quadriplegic, brain damage, lifelong care 175 Emotional injury only 201 Insignificant injury 92 Cannot be determined *

The most malpractice payments between 2010 to 2013 was paid for malpractice leasing to death.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6727.tsv"}, "mark": "line", "encoding": {"color": {"value": "#4572a7"}, "x": {"type": "temporal", "axis": {"labelAngle": -60}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "65 years and older"}, "field": "65 years and older"}}, "title": ["Ivory Coast : Age structure from 2009 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 65 years and older Dec 31, 2008 0.0288 Dec 31, 2009 0.0286 Dec 31, 2010 0.0286 Dec 31, 2011 0.0285 Dec 31, 2012 0.0283 Dec 31, 2013 0.0281 Dec 31, 2014 0.028 Dec 31, 2015 0.0282 Dec 31, 2016 0.0284 Dec 31, 2017 0.0286 Dec 31, 2018 0.0287

Ivory Coast’s population over 65 has remained relatively constant in the years 2009-2019, hitting it’s lowest point in 2015.

{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "multiColumn/data/672.tsv"}, "mark": "area", "encoding": {"color": {"value": "#e6ab02"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Europe, Middle East and Africa"}, "field": "Europe, Middle East and Africa"}}, "title": ["Global box office revenue from 2004 to 2019", ", by region (in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Europe, Middle East and Africa Dec 31, 2003 10.4 Dec 31, 2004 9.9 Dec 31, 2005 9.7 Dec 31, 2006 8.7 Dec 31, 2007 9.7 Dec 31, 2008 9.9 Dec 31, 2009 10.4 Dec 31, 2010 10.8 Dec 31, 2011 10.7 Dec 31, 2012 10.9 Dec 31, 2013 10.6 Dec 31, 2014 10 Dec 31, 2015 9.8 Dec 31, 2016 10.2 Dec 31, 2017 10.1 Dec 31, 2018 10.3

The peak for the global box office revenue happened between 2007 and 2015.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/672.tsv"}, "mark": "area", "encoding": {"color": {"value": "#c89d29"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "U.S./Canada"}, "field": "U\\.S\\./Canada"}}, "title": ["Global box office revenue from 2004 to 2019", ", by region (in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year U.S./Canada Dec 31, 2003 10.6 Dec 31, 2004 10.6 Dec 31, 2005 9.6 Dec 31, 2006 9.6 Dec 31, 2007 9.6 Dec 31, 2008 10.6 Dec 31, 2009 10.6 Dec 31, 2010 10.2 Dec 31, 2011 10.8 Dec 31, 2012 10.9 Dec 31, 2013 10.4 Dec 31, 2014 11.1 Dec 31, 2015 11.4 Dec 31, 2016 11.1 Dec 31, 2017 11.9 Dec 31, 2018 11.4

The global box office revenue has gradually increased from 2004 to 2018. The global box office has fluctuated since it plateaued around 2008.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6741.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#00609f"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of LTC deaths per million population"}, "field": "Number of LTC deaths per million population"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "Country"}}, "title": ["Total rate of COVID-19 deaths compared to", "deaths among long-term care residents in", "select countries worldwide as of May 2020", "(per million population)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Number of LTC deaths per million population Country 1 Australia 19 Israel 25 Norway 5 Slovenia 3 Hungary 13 Austria 34 Germany 32 Portugal 142 Canada 112 OECD average 91 U.S. 184 Ireland 50 Netherlands 208 France 176 Italy 150 U.K. 379 Spain 400 Belgium

Belgium had the highest number of Ltc deaths. Hungary and Slovenia had the least amount.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/6751.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#71598e"}, "x": {"type": "quantitative", "axis": {"title": "Currently use"}, "field": "Currently use"}, "y": {"type": "nominal", "axis": {"labelAngle": 30}, "bin": false, "field": "Response"}}, "title": ["Use of social networks among travel companies", "in the United States as of the first quarter", "of 2014"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Currently use Response 0.84 Facebook 0.66 Twitter 0.56 YouTube 0.48 Google+ 0.5 LinkedIn 0.35 Instagram 0.37 Pinterest 0.17 Foursquare 0.14 WhatsApp 0.06 Vine 0.09 Tumblr

In the first quarter of 2014 travel companies in the United States used Facebook the most. In the first quarter of 2014 travel companies in the United States used vine the least.

{"config": {"background": "#000", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0", "#f0027f", "#bf5b17", "#666666"]}}, "data": {"url": "multiColumn/data/6753.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "city or region of United Kingdom"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "2018"}, "field": "2018"}}, "title": ["Merger and acquisitions (M & A) transaction", "volume in the United Kingdom (UK) in 2018", "and 2019 , by city or region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

city or region of United Kingdom 2018 Londo 3105; city or region of United Kingdom: London South Eas 1135; city or region of United Kingdom: South East Midland 1037; city or region of United Kingdom: Midlands North Wes 897; city or region of United Kingdom: North West Yorkshire and Humbe 624; city or region of United Kingdom: Yorkshire and Humber East of Englan 575; city or region of United Kingdom: East of England Scotlan 799; city or region of United Kingdom: Scotland South Wes 538; city or region of United Kingdom: South West North Eas 298; city or region of United Kingdom: North East Northern Irelan 228; city or region of United Kingdom: Northern Ireland Wale 212; city or region of United Kingdom: Wales

Southern regions of the UK tend to have a higher transaction volume than the North.

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/6761.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#9c9ede"}, "x": {"type": "quantitative", "axis": {"labelAngle": 90, "title": "2014"}, "field": "2014"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Leading ten Italian wineries"}}, "title": ["Leading ten Italian wineries in Italy from", "2014 to 2018 , by turnover (in million euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2014 Leading ten Italian wineries 551 C.Riunite/CIV/GIV 349 GIV 314 Caviro 202 Cantineriunite/CIV 185 Antinori 160 Zonin 159 Martini 171 Mezzacorona 159 Cavit 137 Botter

LEADING TEN ITALIAN WINNERS IN ITALY FROM 2014 TO 2018 BY TURNOVER IN WHICH c.RIUNITE/CIV/GIV GAIN MORE THAN EVERY1.

{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "multiColumn/data/6761.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#de9ed6"}, "x": {"type": "quantitative", "axis": {"title": "2017"}, "field": "2017"}, "y": {"type": "nominal", "axis": {"labelAngle": 60}, "bin": false, "field": "Leading ten Italian wineries"}}, "title": ["Leading ten Italian wineries in Italy from", "2014 to 2018 , by turnover (in million euros)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

2017 Leading ten Italian wineries 610 C.Riunite/CIV/GIV 385 GIV 304 Caviro 226 Cantineriunite/CIV 220 Antinori 196 Zonin 192 Martini 185 Mezzacorona 183 Cavit 180 Botter

The best performing Italian winery for the years 2014-2018 was C.Riunite/CIV/GIV, outperforming the others by a fair margin.

{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "multiColumn/data/676.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Race"}, "y": {"type": "quantitative", "axis": {"title": "EU import tariffs applied to U.S. goods"}, "field": "EU import tariffs applied to U\\.S\\. goods"}}, "title": ["Trade weighted average of applied import", "tarrifs in the EU and U.S. , by sector in", "2013"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Race EU import tariffs applied to U.S. goods Processed foods 0.064 Manufacturing 0.0413 Transport 0.0351 Agri-forestry-fishing 0.0284 Chemicals 0.0235 Metals 0.0189 Electric machinery and equipment 0.0168 Minerals 0.0109 Machinery 0.0106 Other 0.0066

processed food has a much higher trade weighted average than any other race by at least 0.02. Most races average between 0.01 and 0.04 in terms of EU transport tariffs.

{"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": "multiColumn/data/6774.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#56cc60"}, "x": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "02.03-08.03"}, "field": "02\\.03-08\\.03"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "food products"}}, "title": ["Fastest growing convenience food products", "online sales during the coronavirus (COVID-19)", "outbreak in Russia from January to March", "2020 , by product"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

02.03-08.03 food products 2.49 Energy drinks 2.09 Pasta 1.46 Vegetable oil 1.5 Instant soups 1.51 Porridge 0.38 Chocolate paste 1.32 Souces 0.79 Sterilized milk 0.99 Flakes 0.71 Water

Energy drinks saw the fastest growth. Chocolate paste saw the slowest growth.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6788.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#ab5787"}, "x": {"type": "quantitative", "axis": {"labelAngle": 45, "title": "Concert/Show/Entertainment"}, "field": "Concert/Show/Entertainment"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "stadiums/arenas"}}, "title": ["Stadiums in Germany ranked by number of", "events hosted in the first half of 2013"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Concert/Show/Entertainment stadiums/arenas 1 Veltins-Arena (Gelsenkirchen) 1 Borussia-Park (Mönchengladbach) 5 Commerzbank-Arena (Frankfurt) 1 BayArena (Leverkusen) 4 Voith-Arena (Heidenheim) 42 HDI-Arena (Hannover) 3 Mercedes-Benz Arena (Stuttgart) 1 Grundig Stadion (Nurnberg)

hannover is the clear cut winner, with the best concert event, and no other stadium or arena could touch hannover in the first half of 2013.

{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "multiColumn/data/6788.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6B007B"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Other events***"}, "field": "Other events***"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "stadiums/arenas"}}, "title": ["Stadiums in Germany ranked by number of", "events hosted in the first half of 2013"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Other events*** stadiums/arenas 368 Signal Iduna Park (Dortmund) 49 Veltins-Arena (Gelsenkirchen) 1 Commerzbank-Arena (Frankfurt) 14 HDI-Arena (Hannover) 14 Grundig Stadion (Nurnberg)

Signai lndua Park stadium in Germany hosted the most events in the first part of 2013.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/678.tsv"}, "mark": "area", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Agriculture"}, "field": "Agriculture"}}, "title": ["South Korea : Distribution of employment", "by economic sector from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Agriculture Dec 31, 2009 0.066 Dec 31, 2010 0.0637 Dec 31, 2011 0.0613 Dec 31, 2012 0.0598 Dec 31, 2013 0.0558 Dec 31, 2014 0.0511 Dec 31, 2015 0.0482 Dec 31, 2016 0.0478 Dec 31, 2017 0.05 Dec 31, 2018 0.0488 Dec 31, 2019 0.0477

There was a decrease in employment in the agriculture sector in South Korea between 2010 and 2017. Employment in the agriculture sector in South Korea increased to 0.05 in 2018 and decreased to 0.475 in 2020.

{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "multiColumn/data/678.tsv"}, "mark": "area", "encoding": {"color": {"value": "#D9B300"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Industry"}, "field": "Industry"}}, "title": ["South Korea : Distribution of employment", "by economic sector from 2010 to 2020"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Industry Dec 31, 2009 0.2502 Dec 31, 2010 0.2485 Dec 31, 2011 0.2458 Dec 31, 2012 0.2452 Dec 31, 2013 0.2477 Dec 31, 2014 0.252 Dec 31, 2015 0.2499 Dec 31, 2016 0.2507 Dec 31, 2017 0.252 Dec 31, 2018 0.2513 Dec 31, 2019 0.2501

Between 2010 and 2020 employment in the industry sector of South Korea has remained fairly static at around 0.25. The fall and rise between 2010 and 2015 is so small as to be impossible to put a number on in the context of this representation.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6800.tsv"}, "mark": "line", "encoding": {"color": {"value": "#d2d2d2"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "15-64 years"}, "field": "15-64 years"}}, "title": ["Mozambique : Age structure from 2009 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 15-64 years Dec 31, 2008 0.5123 Dec 31, 2009 0.5125 Dec 31, 2010 0.5125 Dec 31, 2011 0.5128 Dec 31, 2012 0.5135 Dec 31, 2013 0.5149 Dec 31, 2014 0.5168 Dec 31, 2015 0.5188 Dec 31, 2016 0.5214 Dec 31, 2017 0.5244 Dec 31, 2018 0.5275

The relation ship between age structure and year increases along the y-axis, showing us that there is a slight but definite increase in age structure as the years progress.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6800.tsv"}, "mark": "line", "encoding": {"color": {"value": "#d2d2d2"}, "x": {"type": "temporal", "axis": {"labelAngle": 90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "15-64 years"}, "field": "15-64 years"}}, "title": ["Mozambique : Age structure from 2009 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 15-64 years Dec 31, 2008 0.5123 Dec 31, 2009 0.5125 Dec 31, 2010 0.5125 Dec 31, 2011 0.5128 Dec 31, 2012 0.5135 Dec 31, 2013 0.5149 Dec 31, 2014 0.5168 Dec 31, 2015 0.5188 Dec 31, 2016 0.5214 Dec 31, 2017 0.5244 Dec 31, 2018 0.5275

The Mozambique age structure of 15-64 years 0.5in 2010. This figure has remained steady and increasing very minimally to nearly 0.6 in 2018.

{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "multiColumn/data/6800.tsv"}, "mark": "line", "encoding": {"color": {"value": "#83bcb6"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "65 years and older"}, "field": "65 years and older"}}, "title": ["Mozambique : Age structure from 2009 to", "2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year 65 years and older Dec 31, 2008 0.0306 Dec 31, 2009 0.0301 Dec 31, 2010 0.03 Dec 31, 2011 0.0299 Dec 31, 2012 0.0296 Dec 31, 2013 0.0293 Dec 31, 2014 0.029 Dec 31, 2015 0.029 Dec 31, 2016 0.029 Dec 31, 2017 0.0289 Dec 31, 2018 0.0288

on average, over a 10 year period the number of above 65 years has declined 0.003. 0.0015 each 5 years respectively. Each year there has been either a decline or levelling in the overall number of less than 65s. There has been no increase in the number of over 65 years old. From these trends we can deduce that the overall population of over 65s is reducing and the number of under 65s is increasing at the rate 0.003 per 10 years or 0.0003 per year.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/680.tsv"}, "mark": "area", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Agriculture"}, "field": "Agriculture"}}, "title": ["Argentina : Share of economic sectors in", "the gross domestic product (GDP) from 2009", "to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Agriculture Dec 31, 2008 0.0527 Dec 31, 2009 0.0713 Dec 31, 2010 0.07 Dec 31, 2011 0.0578 Dec 31, 2012 0.0605 Dec 31, 2013 0.0671 Dec 31, 2014 0.0516 Dec 31, 2015 0.0626 Dec 31, 2016 0.0548 Dec 31, 2017 0.061 Dec 31, 2018 0.072

The share of Agriculture fluctuates over the years but generally stays above 0.05.

{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "multiColumn/data/680.tsv"}, "mark": "area", "encoding": {"color": {"value": "#F06292"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Agriculture"}, "field": "Agriculture"}}, "title": ["Argentina : Share of economic sectors in", "the gross domestic product (GDP) from 2009", "to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Agriculture Dec 31, 2008 0.0527 Dec 31, 2009 0.0713 Dec 31, 2010 0.07 Dec 31, 2011 0.0578 Dec 31, 2012 0.0605 Dec 31, 2013 0.0671 Dec 31, 2014 0.0516 Dec 31, 2015 0.0626 Dec 31, 2016 0.0548 Dec 31, 2017 0.061 Dec 31, 2018 0.072

The lowest share of GDP for agriculture occurred in 2015. The highest share occurred in 2019. Agriculture shared more than 0.5 each year between 2009 and 2019.

{"config": {"background": "#fff", "area": {"fill": "#4572a7"}, "line": {"stroke": "#4572a7", "strokeWidth": 2}, "rect": {"fill": "#4572a7"}, "bar": {"fill": "#4572a7"}, "point": {"color": "#4572a7", "strokeWidth": 1.5, "size": 50}, "axis": {"bandPosition": 0.5, "grid": true, "gridColor": "#000000", "gridOpacity": 1, "gridWidth": 0.5, "labelPadding": 10, "tickSize": 5, "tickWidth": 0.5}, "axisBand": {"grid": false, "tickExtra": true}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 50, "symbolType": "square"}, "range": {"category": ["#4572a7", "#aa4643", "#8aa453", "#71598e", "#4598ae", "#d98445", "#94aace", "#d09393", "#b9cc98", "#a99cbc"]}}, "data": {"url": "multiColumn/data/680.tsv"}, "mark": "line", "encoding": {"color": {"value": "#8aa453"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Services"}, "field": "Services"}}, "title": ["Argentina : Share of economic sectors in", "the gross domestic product (GDP) from 2009", "to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Services Dec 31, 2008 0.5331 Dec 31, 2009 0.515 Dec 31, 2010 0.5181 Dec 31, 2011 0.5366 Dec 31, 2012 0.5392 Dec 31, 2013 0.5294 Dec 31, 2014 0.5581 Dec 31, 2015 0.5612 Dec 31, 2016 0.5697 Dec 31, 2017 0.5548 Dec 31, 2018 0.5363

The growth in this area has been balanced and not dropped below 0.5 but remained quite level and appears to be keeping at this level.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/6810.tsv"}, "mark": "line", "encoding": {"color": {"value": "#829eb1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Female"}, "field": "Female"}}, "title": ["Total population of Antigua and Barbuda", "from 2008 to 2018 , by gender (in 1,000 inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Female Dec 31, 2007 44.67 Dec 31, 2008 45.3 Dec 31, 2009 45.91 Dec 31, 2010 46.49 Dec 31, 2011 47.04 Dec 31, 2012 47.56 Dec 31, 2013 48.06 Dec 31, 2014 48.54 Dec 31, 2015 49.01 Dec 31, 2016 49.44 Dec 31, 2017 49.87

The female population of Antigua and Barbuda has seen a very steady rise, from 45 in 1000 in 2008 to 50 in 1000 in 2018.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6810.tsv"}, "mark": "area", "encoding": {"color": {"value": "#fdbf11"}, "x": {"type": "temporal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Total"}, "field": "Total"}}, "title": ["Total population of Antigua and Barbuda", "from 2008 to 2018 , by gender (in 1,000 inhabitants)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Year Total Dec 31, 2007 85.4 Dec 31, 2008 86.75 Dec 31, 2009 88.03 Dec 31, 2010 89.25 Dec 31, 2011 90.41 Dec 31, 2012 91.52 Dec 31, 2013 92.56 Dec 31, 2014 93.57 Dec 31, 2015 94.53 Dec 31, 2016 95.43 Dec 31, 2017 96.29

population is increasing steadily every yea rfrom 2016.

{"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": "multiColumn/data/6814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#30a2da"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "relationship problems or loss"}, "y": {"type": "quantitative", "axis": {"title": "Known mental health condition"}, "field": "Known mental health condition"}}, "title": ["Distribution of U.S. suicides that had a", "known mental health condition as of 2015", ", by relationship problems or loss"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

relationship problems or loss Known mental health condition Any relationship problem/loss 0.396 Intimate partner problem 0.241 Perpetrator of interpersonal violence in past month 0.014 Victim of interpersonal violence in past month 0.006 Family relationhip problem 0.093 Other relationship problem (nonintimate) 0.021 Argument or conflict (not specified) 0.136 Death of a loved one (any) 0.088 Nonsuicide death 0.069 Suicide of family or friend 0.023

Intimate partner problems had the highest volume once any problem is taken out of the equation.

{"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": "multiColumn/data/6814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#30a2da"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "relationship problems or loss"}, "y": {"type": "quantitative", "axis": {"title": "Known mental health condition"}, "field": "Known mental health condition"}}, "title": ["Distribution of U.S. suicides that had a", "known mental health condition as of 2015", ", by relationship problems or loss"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

relationship problems or loss Known mental health condition Any relationship problem/loss 0.396 Intimate partner problem 0.241 Perpetrator of interpersonal violence in past month 0.014 Victim of interpersonal violence in past month 0.006 Family relationhip problem 0.093 Other relationship problem (nonintimate) 0.021 Argument or conflict (not specified) 0.136 Death of a loved one (any) 0.088 Nonsuicide death 0.069 Suicide of family or friend 0.023

Death of loved one contributes to lower suicide rate than family relationship problem.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#51b2e5"}, "x": {"type": "quantitative", "axis": {"title": "No known mental health condition"}, "field": "No known mental health condition"}, "y": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "relationship problems or loss"}}, "title": ["Distribution of U.S. suicides that had a", "known mental health condition as of 2015", ", by relationship problems or loss"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

No known mental health condition relationship problems or loss 0.451 Any relationship problem/loss 0.302 Intimate partner problem 0.03 Perpetrator of interpersonal violence in past month 0.003 Victim of interpersonal violence in past month 0.085 Family relationhip problem 0.021 Other relationship problem (nonintimate) 0.175 Argument or conflict (not specified) 0.072 Death of a loved one (any) 0.057 Nonsuicide death 0.017 Suicide of family or friend

I genuinely do not understand what this graph is trying to show. I can't work out whether it means the person had a mental health condition or not. The y-axis is also extremely confusing by how the text is presented.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#51b2e5"}, "x": {"type": "quantitative", "axis": {"title": "No known mental health condition"}, "field": "No known mental health condition"}, "y": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "relationship problems or loss"}}, "title": ["Distribution of U.S. suicides that had a", "known mental health condition as of 2015", ", by relationship problems or loss"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

No known mental health condition relationship problems or loss 0.451 Any relationship problem/loss 0.302 Intimate partner problem 0.03 Perpetrator of interpersonal violence in past month 0.003 Victim of interpersonal violence in past month 0.085 Family relationhip problem 0.021 Other relationship problem (nonintimate) 0.175 Argument or conflict (not specified) 0.072 Death of a loved one (any) 0.057 Nonsuicide death 0.017 Suicide of family or friend

Any relationship problem/loss is the largest recorded quantifiable factor relating to US suicides.

{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/6814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#51b2e5"}, "x": {"type": "quantitative", "axis": {"title": "No known mental health condition"}, "field": "No known mental health condition"}, "y": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "relationship problems or loss"}}, "title": ["Distribution of U.S. suicides that had a", "known mental health condition as of 2015", ", by relationship problems or loss"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

No known mental health condition relationship problems or loss 0.451 Any relationship problem/loss 0.302 Intimate partner problem 0.03 Perpetrator of interpersonal violence in past month 0.003 Victim of interpersonal violence in past month 0.085 Family relationhip problem 0.021 Other relationship problem (nonintimate) 0.175 Argument or conflict (not specified) 0.072 Death of a loved one (any) 0.057 Nonsuicide death 0.017 Suicide of family or friend

Suicides tend to occur with relationship problems. Surprisingly the suicide rate appears low after violence situations.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6824.tsv"}, "mark": "line", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Female"}, "field": "Female"}}, "title": ["Monthly prevalence of health-related workplace", "absenteeism among full-time workers during", "the 2017\u00e2\u20ac ? 018 influenza season , by gender"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Month Female Sep 30, 2017 0.021 Oct 31, 2017 0.023 Nov 30, 2017 0.028 Dec 31, 2017 0.036 Jan 31, 2018 0.032 Feb 28, 2018 0.025 Mar 31, 2018 0.023 Apr 30, 2018 0.024 May 31, 2018 0.021 Jun 30, 2018 0.017 Jul 31, 2018 0.018 Aug 31, 2018 0.022

The absenteeism of females changes to reach a maximum (0.036) and then decreases to the similar level compared with the beginning (0.02). The beginning is in October. The minimum reaches 0.018 in around July. The maximum is in Feburary.

{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "multiColumn/data/6824.tsv"}, "mark": "line", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Month"}, "y": {"type": "quantitative", "axis": {"labelAngle": 60, "title": "Female"}, "field": "Female"}}, "title": ["Monthly prevalence of health-related workplace", "absenteeism among full-time workers during", "the 2017\u00e2\u20ac ? 018 influenza season , by gender"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Month Female Sep 30, 2017 0.021 Oct 31, 2017 0.023 Nov 30, 2017 0.028 Dec 31, 2017 0.036 Jan 31, 2018 0.032 Feb 28, 2018 0.025 Mar 31, 2018 0.023 Apr 30, 2018 0.024 May 31, 2018 0.021 Jun 30, 2018 0.017 Jul 31, 2018 0.018 Aug 31, 2018 0.022

Workplace absenteeism for women was higher during the 2017 influenza season.

{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "multiColumn/data/682.tsv"}, "mark": "area", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Emigration"}, "field": "Emigration"}}, "title": ["Immigration , emigration , and migration", "balance in the Netherlands from 2009 to 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}

Response Emigration Dec 31, 2008 111897 Dec 31, 2009 121351 Dec 31, 2010 133194 Dec 31, 2011 144491 Dec 31, 2012 145669 Dec 31, 2013 147862 Dec 31, 2014 149509 Dec 31, 2015 151545 Dec 31, 2016 154292 Dec 31, 2017 157366 Dec 31, 2018 161029

As time has passed the balance between Immigration, emigration and migration has increased with a rise from just over 100 000 in 2010 to just under 150 000 in 2012. Since then the balance has slowed, rising from just under 150 000 in 2012 to just over 150 000 in 2018.