delen/vistext huggingface dataset:
Chart description: In 2016 approval rates of presidents in office in Honduras have raised by 0.01% percent since 2002.

Chart data: Year Approval rate Dec 31, 2001 0.57 Dec 31, 2002 0.52 Dec 31, 2003 0.44 Dec 31, 2004 0.39 Dec 31, 2005 0.56 Dec 31, 2006 0.56 Dec 31, 2007 0.35 Dec 31, 2009 0.51 Dec 31, 2010 0.52 Dec 31, 2012 0.32 Dec 31, 2014 0.62 Dec 31, 2015 0.49 Dec 31, 2016 0.49 Dec 31, 2017 0.41

Vega-Lite specification:
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Chart description: There is an overall increase in the estimated aggregate revenue of U.S. outdoor advertising companies from 2000 to 2018. Estimated revenue increased greatly from around 2002 and peaked around 2007. Estimated revenue saw a sharp decrease which then levelled out around 2009 and fluctuated very slightly till 2018.

Chart data: Year Estimated revenue in billion U.S. dollars Dec 31, 1999 4.75 Dec 31, 2000 4.51 Dec 31, 2001 4.62 Dec 31, 2002 5.15 Dec 31, 2003 5.93 Dec 31, 2004 7.02 Dec 31, 2005 7.84 Dec 31, 2006 9.11 Dec 31, 2007 8.89 Dec 31, 2008 7.09 Dec 31, 2009 7.09 Dec 31, 2010 7 Dec 31, 2011 7.16 Dec 31, 2012 7.1 Dec 31, 2013 7.16 Dec 31, 2014 7.25 Dec 31, 2015 7.3 Dec 31, 2016 7.38 Dec 31, 2017 7.22

Vega-Lite specification:
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Chart description: CBS Corporation 's entertainment segment revenue Was highest in 2018. CBS Corporation 's entertainment segment revenue Was lowest in 2008.

Chart data: Year Revenue in million U.S. dollars Dec 31, 2007 6879 Dec 31, 2008 6977 Dec 31, 2009 7391 Dec 31, 2010 7457 Dec 31, 2011 7694 Dec 31, 2012 8645 Dec 31, 2013 8309 Dec 31, 2014 8438 Dec 31, 2015 8877 Dec 31, 2016 9164 Dec 31, 2017 10178

Vega-Lite specification:
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Chart description: This measure shows us that response which depicts the total urban population has slowly increased from 2009 to 2019.

Chart data: Response Share of urban population in total population Dec 31, 2008 0.4913 Dec 31, 2009 0.4991 Dec 31, 2010 0.506 Dec 31, 2011 0.5128 Dec 31, 2012 0.5196 Dec 31, 2013 0.5264 Dec 31, 2014 0.5331 Dec 31, 2015 0.5399 Dec 31, 2016 0.5466 Dec 31, 2017 0.5533 Dec 31, 2018 0.5599

Vega-Lite specification:
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Chart description: the graph shows urbanization has increased in the 10 year period.

Chart data: Response Share of urban population in total population Dec 31, 2008 0.4913 Dec 31, 2009 0.4991 Dec 31, 2010 0.506 Dec 31, 2011 0.5128 Dec 31, 2012 0.5196 Dec 31, 2013 0.5264 Dec 31, 2014 0.5331 Dec 31, 2015 0.5399 Dec 31, 2016 0.5466 Dec 31, 2017 0.5533 Dec 31, 2018 0.5599

Vega-Lite specification:
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Chart description: Budget balance in relation to GDP increased dramatically between 2015-2020. After a drop in 2021, budget balance in relation to GDP has become much more stable than in previous years.

Chart data: Budget balance in relation to GDP Year −0.0705 2025* −0.0744 2024* −0.0772 2023* −0.0806 2022* −0.0808 2021* −0.0959 2020* −0.0456 2019 −0.0282 2018 −0.0283 2017 −0.0239 2016 −0.0135 2015

Vega-Lite specification:
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Chart description: The budget balance peaked in 2020 and is set to increase in the future (the prediction.).

Chart data: Budget balance in relation to GDP Year −0.0705 2025* −0.0744 2024* −0.0772 2023* −0.0806 2022* −0.0808 2021* −0.0959 2020* −0.0456 2019 −0.0282 2018 −0.0283 2017 −0.0239 2016 −0.0135 2015

Vega-Lite specification:
{"config": {"view": {"fill": "#e5e5e5"}, "area": {"fill": "#000"}, "line": {"stroke": "#000"}, "rect": {"fill": "#000"}, "bar": {"fill": "#000"}, "point": {"color": "#000", "size": 40}, "axis": {"domain": false, "grid": true, "gridColor": "#FFFFFF", "gridOpacity": 1, "labelColor": "#7F7F7F", "labelPadding": 4, "tickColor": "#7F7F7F", "tickSize": 5.67, "titleFontSize": 16, "titleFontWeight": "normal"}, "legend": {"labelBaseline": "middle", "labelFontSize": 11, "symbolSize": 40}, "range": {"category": ["#000000", "#7F7F7F", "#1A1A1A", "#999999", "#333333", "#B0B0B0", "#4D4D4D", "#C9C9C9", "#666666", "#DCDCDC"]}}, "data": {"url": "data/24983.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#DCDCDC"}, "x": {"type": "quantitative", "axis": {"title": "Budget balance in relation to GDP"}, "field": "Budget balance in relation to GDP"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Year"}}, "title": ["Romania : Budget balance between 2015 to", "2025 in relation to GDP"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Romania's budget balance was at it's lowest in 2015. Romania's budget balance was at it's highest in 2020. The average budget balance has increased significantly since 2020.

Chart data: Budget balance in relation to GDP Year −0.0705 2025* −0.0744 2024* −0.0772 2023* −0.0806 2022* −0.0808 2021* −0.0959 2020* −0.0456 2019 −0.0282 2018 −0.0283 2017 −0.0239 2016 −0.0135 2015

Vega-Lite specification:
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Chart description: Toina was the least affected county with well under 10000 confirmed cases. Budapest had the highest number of confirmed cases at over 60000. Apart from Budapest and Pest the number of confirmed cases per county was under 20,000 with several counties being under 10,000.

Chart data: Number of confirmed cases county of Hungary 63438 Budapest 41880 Pest 19225 Győr-Moson-Sopron 19205 Hajdú-Bihar 18884 Borsod-Abaúj-Zemplén 16576 Szabolcs-Szatmár-Bereg 15371 Csongrád-Csanád 15261 Bács-Kiskun 13507 Veszprém 12843 Jász-Nagykun-Szolnok 12314 Fejér 11462 Békés 10984 Baranya 10696 Vas 10269 Komárom-Esztergom 9665 Zala 9249 Heves 9075 Somogy 8230 Nógrád 6702 Tolna

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/2498.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#666666"}, "x": {"type": "quantitative", "axis": {"labelAngle": -90, "title": "Number of confirmed cases"}, "field": "Number of confirmed cases"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "county of Hungary"}}, "title": ["Number of confirmed coronavirus (COVID-19)", "cases in Hungary as of January 7 , 2021 ,", "by county"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Budapest and Pest were the worst places to possibly contract Covid. Other counties seemed low risk relative to other European nations.

Chart data: Number of confirmed cases county of Hungary 63438 Budapest 41880 Pest 19225 Győr-Moson-Sopron 19205 Hajdú-Bihar 18884 Borsod-Abaúj-Zemplén 16576 Szabolcs-Szatmár-Bereg 15371 Csongrád-Csanád 15261 Bács-Kiskun 13507 Veszprém 12843 Jász-Nagykun-Szolnok 12314 Fejér 11462 Békés 10984 Baranya 10696 Vas 10269 Komárom-Esztergom 9665 Zala 9249 Heves 9075 Somogy 8230 Nógrád 6702 Tolna

Vega-Lite specification:
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Chart description: The best observation one can make is that most of the coronavirus cases hover around 10,000-20,000. The two exceptions are Pest at 40,000 and Budapest, far exceeding the rest at 60,000.

Chart data: Number of confirmed cases county of Hungary 63438 Budapest 41880 Pest 19225 Győr-Moson-Sopron 19205 Hajdú-Bihar 18884 Borsod-Abaúj-Zemplén 16576 Szabolcs-Szatmár-Bereg 15371 Csongrád-Csanád 15261 Bács-Kiskun 13507 Veszprém 12843 Jász-Nagykun-Szolnok 12314 Fejér 11462 Békés 10984 Baranya 10696 Vas 10269 Komárom-Esztergom 9665 Zala 9249 Heves 9075 Somogy 8230 Nógrád 6702 Tolna

Vega-Lite specification:
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Chart description: In 2009, the annual volume of pineapple sold in Germany was the most. The year 2006 was the least.

Chart data: Sales volume in thousand tonnes Year 141.9 2016* 141.1 2015* 139.6 2014* 138 2013* 134.3 2012* 132.6 2011 137.2 2010 149.2 2009 139.8 2008 127.2 2007 115.8 2006

Vega-Lite specification:
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Chart description: All are well attended. Some clubs are much more popular. Bigger cities mean bigger attendance.

Chart data: Average attendance association football club 57942 Manchester United 47589 Arsenal 44134 West Ham United 43757 Tottenham Hotspur 41955 Liverpool 37097 Manchester City 35551 Newcastle United 32023 Chelsea 28848 Everton 28505 Aston Villa 25312 Leicester City 24758 Wolverhampton Wanderers 24370 Sheffield United 23428 Southampton 22369 Brighton & Hove Albion 19913 Norwich City 19784 Crystal Palace 15995 Burnley 15353 Watford 7745 AFC Bournemouth

Vega-Lite specification:
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Chart description: Just over 40% of clubs have over 30,000 attendance over the 2019/2022 season.

Chart data: Average attendance association football club 57942 Manchester United 47589 Arsenal 44134 West Ham United 43757 Tottenham Hotspur 41955 Liverpool 37097 Manchester City 35551 Newcastle United 32023 Chelsea 28848 Everton 28505 Aston Villa 25312 Leicester City 24758 Wolverhampton Wanderers 24370 Sheffield United 23428 Southampton 22369 Brighton & Hove Albion 19913 Norwich City 19784 Crystal Palace 15995 Burnley 15353 Watford 7745 AFC Bournemouth

Vega-Lite specification:
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Chart description: AFC Bournemouth had the lowest average attendance in 2019/2020. Manchester United had by far the highest average attendance at almost 60,000 fans. The London based football clubs had similar average numbers of fans in attendance.

Chart data: Average attendance association football club 57942 Manchester United 47589 Arsenal 44134 West Ham United 43757 Tottenham Hotspur 41955 Liverpool 37097 Manchester City 35551 Newcastle United 32023 Chelsea 28848 Everton 28505 Aston Villa 25312 Leicester City 24758 Wolverhampton Wanderers 24370 Sheffield United 23428 Southampton 22369 Brighton & Hove Albion 19913 Norwich City 19784 Crystal Palace 15995 Burnley 15353 Watford 7745 AFC Bournemouth

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Chart description: The highest level of  US investment in the EU was in holding companies at around 1800  million US dollars. There was very little investment in electrical equipment and mining which both showed at the lowest bar on the chart. Finance was also important as this was the second highest investment level at around 400 million US dollars.The investment in holding companies was similar to the investment of all other industries together.

Chart data: industry Direct investments in billion U.S. dollars Holding companies (non-bank) 1835.31 Finance (except depository institutions and insurance) 394.28 Other industries 241.27 Information 198.33 Chemicals 120.75 Other manufacturing 101.74 Professional, scientific, and technical services 85.69 Wholesale trade 71.52 Machinery 48.94 Food 48.4 Depository Institutions 47.98 Computers and electronic products 40.79 Transportation equipment 25.8 Primary and fabricated metals 22.93 Mining 8.81 Electrical equipment, appliances, and components 6.57

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Chart description: By far the most non-EU citizens working in Italy seems to be employed in 'other services'. Industries and factories follows with over 300,000 non-EU citizens working in Italy. The smallest number of individuals seems to be employed in finance and insurance; information and communication; and PA, defense, mandatory social insurance.

Chart data: sector Number of individuals Industry (factories) 314630 Trade 207863 Hotels and restaurants 195353 Constructions 134416 Real estate, services for business 132370 Agriculture, hunting, fisheries 104580 Transport and storage 78109 Education, health sector, other social services 63056 Information and communication services 5363 Finance and insurance 2249 PA, defense, mandatory social insurance 2145 Other services 444288

Vega-Lite specification:
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Chart description: there are no trends or pattern in this data. the majority of individuals work in other services.

Chart data: sector Number of individuals Industry (factories) 314630 Trade 207863 Hotels and restaurants 195353 Constructions 134416 Real estate, services for business 132370 Agriculture, hunting, fisheries 104580 Transport and storage 78109 Education, health sector, other social services 63056 Information and communication services 5363 Finance and insurance 2249 PA, defense, mandatory social insurance 2145 Other services 444288

Vega-Lite specification:
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Chart description: Over 400,000 of the non EU workers in Italy in 2019 worked in other services. The lowest number of non EU workers in Italy in 2019 worked in the financial sector.

Chart data: sector Number of individuals Industry (factories) 314630 Trade 207863 Hotels and restaurants 195353 Constructions 134416 Real estate, services for business 132370 Agriculture, hunting, fisheries 104580 Transport and storage 78109 Education, health sector, other social services 63056 Information and communication services 5363 Finance and insurance 2249 PA, defense, mandatory social insurance 2145 Other services 444288

Vega-Lite specification:
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Chart description: Edgerrin James has the record for this time frame with 9000, Only 7 players have over 4000. Two players have under 2000. The average is between 2000 and 4000.

Chart data: Indianapolis Colts all-time rushing leaders Rushing yards Edgerrin James 9226 Lydell Mitchell 5487 Marshall Faulk 5320 Eric Dickerson 5194 Lenny Moore 5174 Tom Matte 4646 Joseph Addai 4453 Alan Ameche 4045 Randy McMillan 3876 Curtis Dickey 3490 Dominic Rhodes 2984 Frank Gore 2953 Jerry Hill 2668 Don McCauley 2627 Marlon Mack 2383 Donald Brown 2377 Albert Bentley 2355 Joe Washington 2342 Johnny Unitas 1777 Tony Lorick 1769

Vega-Lite specification:
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Chart description: High amounts of unemployment in 2000 but then dropped over a period to 2010.

Chart data: Year Youth unemployment rate Dec 31, 1998 0.1159 Dec 31, 1999 0.1027 Dec 31, 2000 0.0794 Dec 31, 2001 0.066 Dec 31, 2002 0.0481 Dec 31, 2003 0.0391 Dec 31, 2004 0.0405 Dec 31, 2005 0.0396 Dec 31, 2006 0.0373 Dec 31, 2007 0.0336 Dec 31, 2008 0.0351 Dec 31, 2009 0.0604 Dec 31, 2010 0.0754 Dec 31, 2011 0.082 Dec 31, 2012 0.0791 Dec 31, 2013 0.0668 Dec 31, 2014 0.0603 Dec 31, 2015 0.0519 Dec 31, 2016 0.045 Dec 31, 2017 0.0452 Dec 31, 2018 0.042 Dec 31, 2019 0.0397

Vega-Lite specification:
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Chart description: There has been a small but steady decline in birth rates between the years 2008 to 2018.

Chart data: Year Birth rate per thousand population Dec 31, 2007 17.62 Dec 31, 2008 17.41 Dec 31, 2009 17.33 Dec 31, 2010 17.29 Dec 31, 2011 17.22 Dec 31, 2012 17.05 Dec 31, 2013 16.77 Dec 31, 2014 16.37 Dec 31, 2015 15.88 Dec 31, 2016 15.38 Dec 31, 2017 14.9

Vega-Lite specification:
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Chart description: German travellers have increased their spending from 2006 to 2018 by around 20 million Euros. The only time spending decreased was around 2008, but it increased again after 2010. It may have slightly decreased in 2016 and came back up again after 2018.

Chart data: Year Spending in million euros Dec 31, 2005 58.9 Dec 31, 2006 60.6 Dec 31, 2007 61.3 Dec 31, 2008 58.2 Dec 31, 2009 58.9 Dec 31, 2010 61.7 Dec 31, 2011 63.2 Dec 31, 2012 68.8 Dec 31, 2013 69.9 Dec 31, 2014 71.5 Dec 31, 2015 73.3 Dec 31, 2016 73.6 Dec 31, 2017 79.4 Dec 31, 2018 82.7

Vega-Lite specification:
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Chart description: I can see that the graph shows many relative maximum and minimum points. I can also see that the birth rate has gone down from the start to the end of the graph.

Chart data: Year Crude birth rate Dec 31, 1849 29.99 Dec 31, 1854 27.81 Dec 31, 1859 30.12 Dec 31, 1864 31.67 Dec 31, 1869 30.84 Dec 31, 1874 30.3 Dec 31, 1879 31.24 Dec 31, 1884 28.64 Dec 31, 1889 27.52 Dec 31, 1894 27.68 Dec 31, 1899 28.5 Dec 31, 1904 27.82 Dec 31, 1909 25.98 Dec 31, 1914 22.56 Dec 31, 1919 18.62 Dec 31, 1924 18.77 Dec 31, 1929 17.1 Dec 31, 1934 15.8 Dec 31, 1939 15.05 Dec 31, 1944 18.72 Dec 31, 1949 19.36 Dec 31, 1954 17.2 Dec 31, 1959 17.5 Dec 31, 1964 18.9 Dec 31, 1969 17.6 Dec 31, 1974 14.3 Dec 31, 1979 11.7 Dec 31, 1984 11.6 Dec 31, 1989 11.9 Dec 31, 1994 12 Dec 31, 1999 11.3 Dec 31, 2004 10.1 Dec 31, 2009 10.1 Dec 31, 2014 10.3 Dec 31, 2019 10.3

Vega-Lite specification:
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Chart description: Gucci has the highest number of stores and nearly double that of its nearest rival. Bottega Veneta has the second highest number of stores. These two brands have more stores when added together than the rest of the brands put together.

Chart data: Number of directly operated stores Brand 487 Gucci 268 Bottega Veneta 222 Saint Laurent 155 Balenciaga* 66 Alexander McQueen* 48 Pomellato* 43 Boucheron* 30 Brioni* 28 Qeelin* 27 DoDo*

Vega-Lite specification:
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Chart description: Gucci has the highest number of directly operated stores, at almost 500. Qeelin, Dodo and Brioni all appear to have the least number of directly operated stores.

Chart data: Number of directly operated stores Brand 487 Gucci 268 Bottega Veneta 222 Saint Laurent 155 Balenciaga* 66 Alexander McQueen* 48 Pomellato* 43 Boucheron* 30 Brioni* 28 Qeelin* 27 DoDo*

Vega-Lite specification:
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