delen/vistext huggingface dataset:
Chart description: There are several music streaming services available for consumers in the United States. The most popular service is Apple Music followed by Pandora Radio and then Spotify. The other streaming services have less than half the uptake of Apple Music.

Chart data: Music Streaming Service Number of mobile only users in millions Apple Music 48.9 Pandora Radio 31.1 Spotify 26.1 Google Play Music 20.7 SoundCloud 18.9 iHeartRadio 13.7 Shazam 10.6 Amazon Music 9.6 TuneIn Radio 5 SiriusXM 3.7

Vega-Lite specification:
{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "data/17814.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#E66C37"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Music Streaming Service"}, "y": {"type": "quantitative", "axis": {"title": "Number of mobile only users in millions"}, "field": "Number of mobile only users in millions"}}, "title": ["Most popular music streaming services in", "the United States as of March 2018 , by number", "of mobile only users (in millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Hines Ward was the player who received the most yards (just over 12,000 yards), followed closely by Antonio Brown who received just over 11,000 yards. 15 of the 20 players received under 6,000 yards. Half of the players received under 4,000 yards. Eric Green received the least yards which was over 2,000.

Chart data: Pittsburgh Steelers Player Receiving yards Hines Ward 12083 Antonio Brown 11207 John Stallworth 8723 Heath Miller 6569 Louis Lipps 6018 Lynn Swann 5462 Elbie Nickel 5131 Buddy Dial 4723 Plaxico Burress 4206 Mike Wallace 4042 Ray Mathews 3919 Santonio Holmes 3835 Roy Jefferson 3671 Yancey Thigpen 3651 Charles Johnson 3400 JuJu Smith-Schuster 3241 Ron Shanklin 3047 Gary Ballman 2949 Bennie Cunningham 2879 Eric Green 2681

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17815.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#DB4437"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "Pittsburgh Steelers Player"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "Receiving yards"}, "field": "Receiving yards"}}, "title": ["Pittsburgh Steelers all-time receiving leaders", "from 1933 to 2020 (in yards)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There is no clear trend or pattern within this bar chart as US states have a high rate of unemployment, with all states ranging from 0.15 to what only as I can conclude as 0.20 as the chart has reached an end. There is however a clear state which stretches the furthest with unemployment which is New Mexico.

Chart data: Underemployment rate State 0.175 New Mexico 0.168 Mississippi 0.162 California 0.16 New York 0.159 Alaska 0.159 Nevada 0.157 Louisiana 0.155 Florida 0.154 West Virginia 0.154 New Jersey

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/17827.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#3580b1"}, "x": {"type": "quantitative", "axis": {"title": "Underemployment rate"}, "field": "Underemployment rate"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "State"}}, "title": ["States with the highest underemployment", "rates in the U.S. 2016"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: People in the US are cooking more oftenThe popularity of takeaways and processed foods is declining.

Chart data: Response Percentage of respondents I cook more often 0.37 I experiment more with food 0.26 I eat more natural or organic foods 0.23 I eat with friends/family more often 0.19 I eat more frozen foods 0.19 I eat more local foods 0.18 I buy semi-prepared food 0.13 I order take-out from restaurants more often 0.07 I eat more processed foods 0.05 None of these 0.26

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/17831.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#c89d29"}, "x": {"type": "nominal", "axis": {"labelAngle": 90}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Percentage of respondents"}, "field": "Percentage of respondents"}}, "title": ["Changes in cooking or eating patterns of", "adults in the United States in 2012 (compared", "to the previous year)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The most significant trend showed that approximately 0.38 percent of adults in the US cooked more often in 2012 than in 2011. Approximately 0.24 percent ate more natural or organic food and 0.26 percent experimented with food, whilst other adults in this percentile made no changes to their cooking or eating patterns.  Between 0.1 and 0.2 percent of adults ate with friends and/or family more, ate more local foods, ate more frozen foods, and bought semi-prepared food. The lowest percentile showed that 0.05 percent ate more processed food and approximately 0.08 percent ordered takeout.

Chart data: Response Percentage of respondents I cook more often 0.37 I experiment more with food 0.26 I eat more natural or organic foods 0.23 I eat with friends/family more often 0.19 I eat more frozen foods 0.19 I eat more local foods 0.18 I buy semi-prepared food 0.13 I order take-out from restaurants more often 0.07 I eat more processed foods 0.05 None of these 0.26

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/17831.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#c89d29"}, "x": {"type": "nominal", "axis": {"labelAngle": 90}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Percentage of respondents"}, "field": "Percentage of respondents"}}, "title": ["Changes in cooking or eating patterns of", "adults in the United States in 2012 (compared", "to the previous year)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The changes in cooking or eating patterns chart shows that I eat more processed foods of having the lowest percent at 0.05 while I cook more often having the highest percent at 0.37. The remainder of percentages falls mostly between 0.1 and 0.25 with I order takeout from restaurants being the only one falling below that value at 0.07.

Chart data: Response Percentage of respondents I cook more often 0.37 I experiment more with food 0.26 I eat more natural or organic foods 0.23 I eat with friends/family more often 0.19 I eat more frozen foods 0.19 I eat more local foods 0.18 I buy semi-prepared food 0.13 I order take-out from restaurants more often 0.07 I eat more processed foods 0.05 None of these 0.26

Vega-Lite specification:
{"config": {"background": "#ffffff", "title": {"anchor": "start", "color": "#000000", "font": "Benton Gothic Bold, sans-serif", "fontSize": 22, "fontWeight": "normal"}, "area": {"fill": "#82c6df"}, "line": {"stroke": "#82c6df", "strokeWidth": 2}, "rect": {"fill": "#82c6df"}, "bar": {"fill": "#82c6df"}, "point": {"color": "#82c6df", "size": 30}, "axis": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "labelFontWeight": "normal", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "axisX": {"labelPadding": 4, "tickSize": 3}, "axisY": {"labelBaseline": "middle", "maxExtent": 45, "minExtent": 45, "tickSize": 2, "titleAlign": "left", "titleAngle": 0, "titleX": -45, "titleY": -11}, "legend": {"labelFont": "Benton Gothic, sans-serif", "labelFontSize": 11.5, "symbolType": "square", "titleFont": "Benton Gothic Bold, sans-serif", "titleFontSize": 13, "titleFontWeight": "normal"}, "range": {"category": ["#ec8431", "#829eb1", "#c89d29", "#3580b1", "#adc839", "#ab7fb4"], "diverging": ["#e68a4f", "#f4bb6a", "#f9e39c", "#dadfe2", "#a6b7c6", "#849eae"], "heatmap": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ordinal": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"], "ramp": ["#fbf2c7", "#f9e39c", "#f8d36e", "#f4bb6a", "#e68a4f", "#d15a40", "#ab4232"]}}, "data": {"url": "data/17831.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#c89d29"}, "x": {"type": "nominal", "axis": {"labelAngle": 90}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Percentage of respondents"}, "field": "Percentage of respondents"}}, "title": ["Changes in cooking or eating patterns of", "adults in the United States in 2012 (compared", "to the previous year)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Eswatini has the highest number of HIV cases per 1000, with Central African Republic having the lowest.

Chart data: Country HIV infections per 1,000 population Eswatini 8.62 Lesotho 7.8 Mozambique 5.25 South Africa 4.94 Botswana 4.36 Equatorial Guinea 4.21 Zambia 2.97 Namibia 2.82 Zimbabwe 2.79 Malawi 2.28 South Sudan 1.56 Guinea-Bissau 1.43 United Republic of Tanzania 1.41 Uganda 1.4 Central African Republic 1.2

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17833.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#5C6BC0"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}, "y": {"type": "quantitative", "axis": {"title": "HIV infections per 1,000 population"}, "field": "HIV infections per 1,000 population"}}, "title": ["Prevalence of new HIV infections in selected", "countries worldwide as of 2018 (per 1,000", "population)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The annual expenditure initially decreased then increased from 2008-2010. The annual expenditure initially decreased then increased from 2010-2012. The annual expenditure initially decreased then increased from 2012-2014. The annual expenditure increased from 2014-2016. The annual expenditure decreased from 2016-2018.

Chart data: Year Average annual expenditure in U.S. dollars Dec 31, 2006 14.47 Dec 31, 2007 13.99 Dec 31, 2008 13.38 Dec 31, 2009 16.07 Dec 31, 2010 14.94 Dec 31, 2011 18.86 Dec 31, 2012 14.01 Dec 31, 2013 20.37 Dec 31, 2014 21.69 Dec 31, 2015 24.62 Dec 31, 2016 22.41 Dec 31, 2017 20.39 Dec 31, 2018 18.44

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/17838.tsv"}, "mark": "line", "encoding": {"color": {"value": "#7b4173"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Average annual expenditure in U.S. dollars"}, "field": "Average annual expenditure in U\\.S\\. dollars"}}, "title": ["Average annual expenditure on non-electric", "cookware per consumer unit in the United", "States from 2007 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There was an all time rise in expenditure in 2016. The years before this are looking very up and down for annual expenditure, with the year 2009 being the lowest and from the year 2016 it continuously drops to 2019.

Chart data: Year Average annual expenditure in U.S. dollars Dec 31, 2006 14.47 Dec 31, 2007 13.99 Dec 31, 2008 13.38 Dec 31, 2009 16.07 Dec 31, 2010 14.94 Dec 31, 2011 18.86 Dec 31, 2012 14.01 Dec 31, 2013 20.37 Dec 31, 2014 21.69 Dec 31, 2015 24.62 Dec 31, 2016 22.41 Dec 31, 2017 20.39 Dec 31, 2018 18.44

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/17838.tsv"}, "mark": "line", "encoding": {"color": {"value": "#7b4173"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Average annual expenditure in U.S. dollars"}, "field": "Average annual expenditure in U\\.S\\. dollars"}}, "title": ["Average annual expenditure on non-electric", "cookware per consumer unit in the United", "States from 2007 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Since 2016, average annual expenditure on non electric cookware has decreased. average annual expenditure on non electric cookware since 2008-12 seems to increase then decrease, then increase again.

Chart data: Year Average annual expenditure in U.S. dollars Dec 31, 2006 14.47 Dec 31, 2007 13.99 Dec 31, 2008 13.38 Dec 31, 2009 16.07 Dec 31, 2010 14.94 Dec 31, 2011 18.86 Dec 31, 2012 14.01 Dec 31, 2013 20.37 Dec 31, 2014 21.69 Dec 31, 2015 24.62 Dec 31, 2016 22.41 Dec 31, 2017 20.39 Dec 31, 2018 18.44

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/17838.tsv"}, "mark": "line", "encoding": {"color": {"value": "#7b4173"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Average annual expenditure in U.S. dollars"}, "field": "Average annual expenditure in U\\.S\\. dollars"}}, "title": ["Average annual expenditure on non-electric", "cookware per consumer unit in the United", "States from 2007 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: There was a dramatic fall in 2013 of people buying non electrical cookware.

Chart data: Year Average annual expenditure in U.S. dollars Dec 31, 2006 14.47 Dec 31, 2007 13.99 Dec 31, 2008 13.38 Dec 31, 2009 16.07 Dec 31, 2010 14.94 Dec 31, 2011 18.86 Dec 31, 2012 14.01 Dec 31, 2013 20.37 Dec 31, 2014 21.69 Dec 31, 2015 24.62 Dec 31, 2016 22.41 Dec 31, 2017 20.39 Dec 31, 2018 18.44

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/17838.tsv"}, "mark": "line", "encoding": {"color": {"value": "#7b4173"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Average annual expenditure in U.S. dollars"}, "field": "Average annual expenditure in U\\.S\\. dollars"}}, "title": ["Average annual expenditure on non-electric", "cookware per consumer unit in the United", "States from 2007 to 2019 (in U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: We can see from the chart that in the year 2019 the budget balance in relation to GDP was the lowest going over -0.08 however since then it has improved and the forecast for 2025 is that it will go up to -0.03.

Chart data: Year Budget balance in relation to GDP 2025* −0.0315 2024* −0.0348 2023* −0.0399 2022* −0.0515 2021* −0.0671 2020 −0.0801 2019 −0.0898 2018 −0.0642 2017 −0.0576 2016 −0.0442 2015 −0.0525

Vega-Lite specification:
{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "data/17843.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#118DFF"}, "x": {"type": "nominal", "axis": {"labelAngle": -90}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Budget balance in relation to GDP"}, "field": "Budget balance in relation to GDP"}}, "title": ["Pakistan : Budget balance between 2015 to", "2025 in relation to GDP"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From the area graph you can see that the retailing floor space has increased from the year 2010.

Chart data: Year Sales floor space in n square-meters Dec 31, 2008 740489 Dec 31, 2009 847523 Dec 31, 2010 938896 Dec 31, 2011 1170353 Dec 31, 2012 1387367 Dec 31, 2013 1835095 Dec 31, 2014 2030031 Dec 31, 2015 2188688 Dec 31, 2016 2392618 Dec 31, 2017 2671629 Dec 31, 2018 2881485

Vega-Lite specification:
{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "data/17844.tsv"}, "mark": "area", "encoding": {"color": {"value": "#439894"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Sales floor space in n square-meters"}, "field": "Sales floor space in n square-meters"}}, "title": ["Total sales floor space of Fast Retailing", "worldwide from fiscal year 2010 to 2019 (in", "square-meters)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The floor space has increased since 2010, from around 750000 sq m to nearly 3000000 sq m.

Chart data: Year Sales floor space in n square-meters Dec 31, 2008 740489 Dec 31, 2009 847523 Dec 31, 2010 938896 Dec 31, 2011 1170353 Dec 31, 2012 1387367 Dec 31, 2013 1835095 Dec 31, 2014 2030031 Dec 31, 2015 2188688 Dec 31, 2016 2392618 Dec 31, 2017 2671629 Dec 31, 2018 2881485

Vega-Lite specification:
{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "data/17844.tsv"}, "mark": "area", "encoding": {"color": {"value": "#439894"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"title": "Sales floor space in n square-meters"}, "field": "Sales floor space in n square-meters"}}, "title": ["Total sales floor space of Fast Retailing", "worldwide from fiscal year 2010 to 2019 (in", "square-meters)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The national debt was at its highest in 2021 and 2022 and at its lowest in 2015.

Chart data: National debt in relation to GDP Year 0.6687 2025* 0.6702 2024* 0.6757 2023* 0.6955 2022* 0.6939 2021* 0.616 2020* 0.5136 2019 0.4499 2018 0.4132 2017 0.3638 2016 0.3222 2015

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/17845.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7298a"}, "x": {"type": "quantitative", "axis": {"title": "National debt in relation to GDP"}, "field": "National debt in relation to GDP"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}}, "title": ["Rwanda : National debt in relation to gross", "domestic product (GDP) from 2015 to 2025"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: National debt in relation to gross domestic product increases steadily year on year between 2015 and 2022 before dipping again.

Chart data: National debt in relation to GDP Year 0.6687 2025* 0.6702 2024* 0.6757 2023* 0.6955 2022* 0.6939 2021* 0.616 2020* 0.5136 2019 0.4499 2018 0.4132 2017 0.3638 2016 0.3222 2015

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/17845.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7298a"}, "x": {"type": "quantitative", "axis": {"title": "National debt in relation to GDP"}, "field": "National debt in relation to GDP"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}}, "title": ["Rwanda : National debt in relation to gross", "domestic product (GDP) from 2015 to 2025"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: It is increasing regularly until 2022. After this year, National debt in relation to GDP will decrease slightly.

Chart data: National debt in relation to GDP Year 0.6687 2025* 0.6702 2024* 0.6757 2023* 0.6955 2022* 0.6939 2021* 0.616 2020* 0.5136 2019 0.4499 2018 0.4132 2017 0.3638 2016 0.3222 2015

Vega-Lite specification:
{"config": {"background": "#333", "title": {"color": "#fff", "subtitleColor": "#fff"}, "style": {"guide-label": {"fill": "#fff"}, "guide-title": {"fill": "#fff"}}, "axis": {"domainColor": "#fff", "gridColor": "#888", "tickColor": "#fff"}, "range": {"category": ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02", "#a6761d", "#666666"]}}, "data": {"url": "data/17845.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7298a"}, "x": {"type": "quantitative", "axis": {"title": "National debt in relation to GDP"}, "field": "National debt in relation to GDP"}, "y": {"type": "nominal", "axis": {"labelAngle": -45}, "bin": false, "field": "Year"}}, "title": ["Rwanda : National debt in relation to gross", "domestic product (GDP) from 2015 to 2025"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The highest number of toiletries, cosmetics and sundries merchant wholesalers in Canada are located in Ontario with over 400. Quebec is has the second highest with 350, followed by British Columbia with over 150 and then Alberta having just under 100. The lowest amount of these wholesalers are located in Yukon and Prince Edward Island.

Chart data: province of Canada Number of establishments Ontario 408 Quebec 355 British Columbia 168 Alberta 83 Saskatchewan 21 Nova Scotia 20 Manitoba 18 New Brunswick 18 Newfoundland and Labrador 16 Prince Edward Island 4 Yukon 1

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17846.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#F4B400"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "province of Canada"}, "y": {"type": "quantitative", "axis": {"title": "Number of establishments"}, "field": "Number of establishments"}}, "title": ["Number of toiletries , cosmetics and sundries", "merchant wholesalers in Canada as of December", "2019 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The bar chart shows that as of the year 2019, Ontario has the highest number of toiletries, cosmetics and sundries. But Yukon has the lowest. The graph also shows that the big cities in Canada have many more than the smaller ones.

Chart data: province of Canada Number of establishments Ontario 408 Quebec 355 British Columbia 168 Alberta 83 Saskatchewan 21 Nova Scotia 20 Manitoba 18 New Brunswick 18 Newfoundland and Labrador 16 Prince Edward Island 4 Yukon 1

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17846.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#F4B400"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "province of Canada"}, "y": {"type": "quantitative", "axis": {"title": "Number of establishments"}, "field": "Number of establishments"}}, "title": ["Number of toiletries , cosmetics and sundries", "merchant wholesalers in Canada as of December", "2019 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Ontario has the most wholesalers peaking at over 400, closely followed by quebec with 350. Prince Edward Island has the fewest amount of cosmetic wholesalers. The provinces in Canada along the x-axis are in alphabetical order starting with Alberta through to Yukon.

Chart data: province of Canada Number of establishments Ontario 408 Quebec 355 British Columbia 168 Alberta 83 Saskatchewan 21 Nova Scotia 20 Manitoba 18 New Brunswick 18 Newfoundland and Labrador 16 Prince Edward Island 4 Yukon 1

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17846.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#F4B400"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "province of Canada"}, "y": {"type": "quantitative", "axis": {"title": "Number of establishments"}, "field": "Number of establishments"}}, "title": ["Number of toiletries , cosmetics and sundries", "merchant wholesalers in Canada as of December", "2019 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: The largest number of cosmetics and sundries merchant wholesalers in Canada as of December 2019 were in the Ontario and Quebec regions. Ontario had just over 400 wholesalers, followed by Quebec with around 350. The third highest number was in British Columbia with about 170 merchant wholesalers. The rest of the regions in Canada had fewer than 100 wholesalers. Alberta had about 80 and the rest noticeably less, hovering around the 20 mark, with Prince Edward Island having 10 or fewer.

Chart data: province of Canada Number of establishments Ontario 408 Quebec 355 British Columbia 168 Alberta 83 Saskatchewan 21 Nova Scotia 20 Manitoba 18 New Brunswick 18 Newfoundland and Labrador 16 Prince Edward Island 4 Yukon 1

Vega-Lite specification:
{"config": {"area": {"fill": "#3366CC"}, "rect": {"fill": "#3366CC"}, "bar": {"fill": "#3366CC"}, "point": {"stroke": "#3366CC"}, "circle": {"fill": "#3366CC"}, "background": "#fff", "padding": {"top": 10, "right": 10, "bottom": 10, "left": 10}, "style": {"guide-label": {"font": "Arial, sans-serif", "fontSize": 12}, "guide-title": {"font": "Arial, sans-serif", "fontSize": 12}, "group-title": {"font": "Arial, sans-serif", "fontSize": 12}}, "title": {"font": "Arial, sans-serif", "fontSize": 14, "fontWeight": "bold", "dy": -3, "anchor": "start"}, "axis": {"gridColor": "#ccc", "tickColor": "#ccc", "domain": false, "grid": true}, "range": {"category": ["#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5C6BC0", "#F06292", "#00796B", "#C2185B"], "heatmap": ["#c6dafc", "#5e97f6", "#2a56c6"]}}, "data": {"url": "data/17846.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#F4B400"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "province of Canada"}, "y": {"type": "quantitative", "axis": {"title": "Number of establishments"}, "field": "Number of establishments"}}, "title": ["Number of toiletries , cosmetics and sundries", "merchant wholesalers in Canada as of December", "2019 , by region"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: In 2019, just under 600,000 single-parent households existed in the Netherlands. It is predicted that the number of such households will increase gradually. In 2050, the increase of single-parent households is expected to plateu.

Chart data: Year Number of households Dec 31, 2018 580436 Dec 31, 2019 586996 Dec 31, 2024 604924 Dec 31, 2029 612486 Dec 31, 2034 622213 Dec 31, 2039 637755 Dec 31, 2044 652587 Dec 31, 2049 660373 Dec 31, 2054 658907 Dec 31, 2059 653958

Vega-Lite specification:
{"config": {"background": "#FFFFFF", "title": {"anchor": "start", "fontSize": 18, "font": "Lato"}, "axisX": {"domain": true, "domainColor": "#000000", "domainWidth": 1, "grid": false, "labelFontSize": 12, "labelFont": "Lato", "tickColor": "#000000", "tickSize": 5, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato"}, "axisY": {"domain": false, "domainWidth": 1, "grid": true, "gridColor": "#DEDDDD", "gridWidth": 1, "labelFontSize": 12, "labelFont": "Lato", "labelPadding": 8, "ticks": false, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "titleAngle": 0, "titleY": -10, "titleX": 18}, "legend": {"labelFontSize": 12, "labelFont": "Lato", "symbolSize": 100, "titleFontSize": 12, "titlePadding": 10, "titleFont": "Lato", "orient": "right", "offset": 10}, "view": {"stroke": "transparent"}, "range": {"category": ["#1696d2", "#ec008b", "#fdbf11", "#000000", "#d2d2d2", "#55b748"], "diverging": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "heatmap": ["#ca5800", "#fdbf11", "#fdd870", "#fff2cf", "#cfe8f3", "#73bfe2", "#1696d2", "#0a4c6a"], "ordinal": ["#cfe8f3", "#a2d4ec", "#73bfe2", "#46abdb", "#1696d2", "#12719e"], "ramp": ["#CFE8F3", "#A2D4EC", "#73BFE2", "#46ABDB", "#1696D2", "#12719E", "#0A4C6A", "#062635"]}, "area": {"fill": "#1696d2"}, "rect": {"fill": "#1696d2"}, "line": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 5}, "trail": {"color": "#1696d2", "stroke": "#1696d2", "strokeWidth": 0, "size": 1}, "point": {"color": "#1696d2", "size": 30}, "text": {"font": "Lato", "color": "#1696d2", "fontSize": 11, "align": "center", "fontWeight": 400, "size": 11}, "style": {"bar": {"fill": "#1696d2", "stroke": null}}}, "data": {"url": "data/17850.tsv"}, "mark": "line", "encoding": {"color": {"value": "#55b748"}, "x": {"type": "temporal", "axis": {}, "bin": false, "field": "Year"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Number of households"}, "field": "Number of households"}}, "title": ["Forecast of the number of single-parent", "households in the Netherlands from 2019 to", "2060"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Transport equipment has by far the highest export value at over 100 billion USD, the next highest being computer and electronic products at around 70 billion USD. At less than 20 billion USD, paper has the lowest export value. The majority of exports have value lower than 40 billion USD, almost all of those below 30 billion USD.

Chart data: Industry Export value in billion U.S. dollars Transportation equipment 101.74 Computer and electronic products 68.68 Chemicals 52.62 Machinery 50.55 Petroleum & coal products 38.98 Electrical equipment 28.72 Food manufactures 24.64 Fabricated metal products 23.1 Plastics & rubber products 20.55 Primary metal mfg 20.45 Oil & gas 18.67 Special classification provisions 17.37 Agricultural products 15.74 Miscellaneous manufactured commodities 14.41 Paper 11.04

Vega-Lite specification:
{"config": {"range": {"category": ["#393b79", "#5254a3", "#6b6ecf", "#9c9ede", "#637939", "#8ca252", "#b5cf6b", "#cedb9c", "#8c6d31", "#bd9e39", "#e7ba52", "#e7cb94", "#843c39", "#ad494a", "#d6616b", "#e7969c", "#7b4173", "#a55194", "#ce6dbd", "#de9ed6"]}}, "data": {"url": "data/17853.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#e7969c"}, "x": {"type": "nominal", "axis": {"labelAngle": -60}, "bin": false, "field": "Industry"}, "y": {"type": "quantitative", "axis": {"labelAngle": -60, "title": "Export value in billion U.S. dollars"}, "field": "Export value in billion U\\.S\\. dollars"}}, "title": ["U.S. merchandise exports that went to NAFTA", "countries in 2019 , by industry classification", "(in billion U.S. dollars)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: A pattern of goods type and trust is possibly visible in this chart. Luxury good buyers and expensive tool buyers tend to have less trust in delivery companies compared to cheaper goods such as food and books.

Chart data: Response Share of respondents Books 0.43 Clothes and apparel 0.4 Consumer packaged goods 0.31 Office supplies 0.3 Pet supplies 0.27 Food/groceries 0.27 Household goods 0.26 Health and beauty 0.24 Consumer electronics 0.23 Sporting goods 0.2 Furniture 0.2 Tools and home improvement 0.19 Luxury goods 0.1

Vega-Lite specification:
{"config": {"range": {"category": ["#4c78a8", "#9ecae9", "#f58518", "#ffbf79", "#54a24b", "#88d27a", "#b79a20", "#f2cf5b", "#439894", "#83bcb6", "#e45756", "#ff9d98", "#79706e", "#bab0ac", "#d67195", "#fcbfd2", "#b279a2", "#d6a5c9", "#9e765f", "#d8b5a5"]}}, "data": {"url": "data/17856.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#f2cf5b"}, "x": {"type": "nominal", "axis": {}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"labelAngle": -45, "title": "Share of respondents"}, "field": "Share of respondents"}}, "title": ["Trust in third-party delivery options according", "to internet users in the United States as", "of March 2019"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: From this bar chart you can see that North America has the highest number of seats in millions and the lowest is Central Asia.

Chart data: geographic region Number of seats in millions North America 24.36 North East Asia 23.04 Western Europe 21.01 South East Asia 9.6 Eastern/ Central Europe 7.93 Middle East 4.57 South Asia 4.55 Upper South America 4.04 Southwest Pacific 2.66 Central America 2.26 North Africa 1.01 Lower South America 1 Southern Africa 0.85 Caribbean 0.7 Eastern Africa 0.53 Central/ Western Africa 0.48 Central Asia 0.36

Vega-Lite specification:
{"config": {"view": {"stroke": "transparent"}, "background": "transparent", "font": "Segoe UI", "header": {"titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleFontSize": 16, "titleColor": "#252423", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C"}, "axis": {"ticks": false, "grid": false, "domain": false, "labelColor": "#605E5C", "labelFontSize": 12, "titleFont": "wf_standard-font, helvetica, arial, sans-serif", "titleColor": "#252423", "titleFontSize": 16, "titleFontWeight": "normal"}, "axisQuantitative": {"tickCount": 3, "grid": true, "gridColor": "#C8C6C4", "gridDash": [1, 5], "labelFlush": false}, "axisBand": {"tickExtra": true}, "axisX": {"labelPadding": 5}, "axisY": {"labelPadding": 10}, "bar": {"fill": "#118DFF"}, "line": {"stroke": "#118DFF", "strokeWidth": 3, "strokeCap": "round", "strokeJoin": "round"}, "text": {"font": "Segoe UI", "fontSize": 12, "fill": "#605E5C"}, "area": {"fill": "#118DFF", "line": true, "opacity": 0.6}, "rect": {"fill": "#118DFF"}, "point": {"fill": "#118DFF", "filled": true, "size": 75}, "legend": {"titleFont": "Segoe UI", "titleFontWeight": "bold", "titleColor": "#605E5C", "labelFont": "Segoe UI", "labelFontSize": 13.333333333333332, "labelColor": "#605E5C", "symbolType": "circle", "symbolSize": 75}, "range": {"category": ["#118DFF", "#12239E", "#E66C37", "#6B007B", "#E044A7", "#744EC2", "#D9B300", "#D64550"], "diverging": ["#DEEFFF", "#118DFF"], "heatmap": ["#DEEFFF", "#118DFF"], "ordinal": ["#DEEFFF", "#c7e4ff", "#b0d9ff", "#9aceff", "#83c3ff", "#6cb9ff", "#55aeff", "#3fa3ff", "#2898ff", "#118DFF"]}}, "data": {"url": "data/17862.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#6B007B"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "geographic region"}, "y": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "Number of seats in millions"}, "field": "Number of seats in millions"}}, "title": ["Seat capacity in the airline industry in", "the week of May 06 , 2019 , by region (in", "millions)"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}