delen/vistext huggingface dataset:
Chart description: Latin America and the carribean have the highest second education rates of just over 1.0 with the lowest education rates been in sub-saharan Africa at a rate of 0.8.

Chart data: Regions Secondary education Sub-Saharan Africa 0.84 Oceania 0.87 Western Asia 0.92 Northern Africa 0.99 Latin America & the Caribbean 1.07 South-Eastern Asia 1.02 Caucasus & Central Asia 0.98 Eastern Asia 1.02 Southern Asia 0.93 Developing regions 0.96

Vega-Lite specification:
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Chart description: The trend of this chart is that it is changing through the years with around 2015 being the highest year shown on the cart. Quickly after plumbing down. Finally there is a large gap in the years where the line is a steady 400 for the most part from 2010 to 2014.

Chart data: Year Company Drive-In sales Dec 31, 2008 567.44 Dec 31, 2009 414.37 Dec 31, 2010 410.82 Dec 31, 2011 404.44 Dec 31, 2012 402.3 Dec 31, 2013 405.36 Dec 31, 2014 436.03 Dec 31, 2015 425.8 Dec 31, 2016 296.1 Dec 31, 2017 240.72

Vega-Lite specification:
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Chart description: Lease revenue was volatile during the first 5 years and looks to be stabilising.

Chart data: Year Lease revenue Dec 31, 2008 3.99 Dec 31, 2009 6.88 Dec 31, 2010 6.02 Dec 31, 2011 6.58 Dec 31, 2012 4.79 Dec 31, 2013 4.29 Dec 31, 2014 5.58 Dec 31, 2015 7.46 Dec 31, 2016 7.44 Dec 31, 2017 7.8

Vega-Lite specification:
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Chart description: Revenue dropped sharply in the 2012-3 period and then fell again, albeit by a lesser amount, during the 2013-14 period, before increasing sharply to almost $8m by 2018.

Chart data: Year Lease revenue Dec 31, 2008 3.99 Dec 31, 2009 6.88 Dec 31, 2010 6.02 Dec 31, 2011 6.58 Dec 31, 2012 4.79 Dec 31, 2013 4.29 Dec 31, 2014 5.58 Dec 31, 2015 7.46 Dec 31, 2016 7.44 Dec 31, 2017 7.8

Vega-Lite specification:
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Chart description: cadilac escalade  had the most sales in the states in 2018 , porsche and bmw the fewest sales.

Chart data: 2018 Large luxury car and SUV models 36032 Cadillac Escalade 21973 Mercedes-Benz GLS-Class 19207 Infiniti QX80 19030 Land Rover Range Rover 17839 Lincoln Navigator 29950 Tesla Model S 14978 Mercedes-Benz S-Class 8271 BMW 7-Series 8114 Porsche Panamera

Vega-Lite specification:
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Chart description: The largest sales were of the Cadillac Escalade and the smallest of the models shown was of the Porsche Panamera.  The sales shown represent less than 200,000 sales in total.

Chart data: Large luxury car and SUV models 2019 Cadillac Escalad  35424; Large luxury car and SUV models: Cadillac Escalade Mercedes-Benz GLS-Clas  22615; Large luxury car and SUV models: Mercedes-Benz GLS-Class BMW X  21574; Large luxury car and SUV models: BMW X7 Infiniti QX8  19113; Large luxury car and SUV models: Infiniti QX80 Land Rover Range Rove  18831; Large luxury car and SUV models: Land Rover Range Rover Lincoln Navigato  18656; Large luxury car and SUV models: Lincoln Navigator Tesla Model   14425; Large luxury car and SUV models: Tesla Model S Mercedes-Benz S-Clas  12503; Large luxury car and SUV models: Mercedes-Benz S-Class BMW 7-Serie  8823; Large luxury car and SUV models: BMW 7-Series Porsche Panamer  6625; Large luxury car and SUV models: Porsche Panamera

Vega-Lite specification:
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Chart description: I can't describe what the line graph is showing. I can't fully make sense of the data.

Chart data: Year 65 years and older Dec 31, 2008 0.1384 Dec 31, 2009 0.1396 Dec 31, 2010 0.1401 Dec 31, 2011 0.1412 Dec 31, 2012 0.1423 Dec 31, 2013 0.1434 Dec 31, 2014 0.1448 Dec 31, 2015 0.1508 Dec 31, 2016 0.1575 Dec 31, 2017 0.1647 Dec 31, 2018 0.172

Vega-Lite specification:
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Chart description: There is a minor increase for the first 6 years of people living to 65 and over, and then from 2015 a larger proportion of people living older than 65 showing potential changes in quality of life.

Chart data: Year 65 years and older Dec 31, 2008 0.1384 Dec 31, 2009 0.1396 Dec 31, 2010 0.1401 Dec 31, 2011 0.1412 Dec 31, 2012 0.1423 Dec 31, 2013 0.1434 Dec 31, 2014 0.1448 Dec 31, 2015 0.1508 Dec 31, 2016 0.1575 Dec 31, 2017 0.1647 Dec 31, 2018 0.172

Vega-Lite specification:
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Chart description: The line chart shows a slight increase in numbers of 15-64 year olds over time.

Chart data: Year 15-64 years Dec 31, 2008 0.6171 Dec 31, 2009 0.6215 Dec 31, 2010 0.626 Dec 31, 2011 0.6302 Dec 31, 2012 0.634 Dec 31, 2013 0.6372 Dec 31, 2014 0.6397 Dec 31, 2015 0.6421 Dec 31, 2016 0.644 Dec 31, 2017 0.6455 Dec 31, 2018 0.6469

Vega-Lite specification:
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Chart description: The line steadily increases just above 0.6 upwards.

Chart data: Year 15-64 years Dec 31, 2008 0.6171 Dec 31, 2009 0.6215 Dec 31, 2010 0.626 Dec 31, 2011 0.6302 Dec 31, 2012 0.634 Dec 31, 2013 0.6372 Dec 31, 2014 0.6397 Dec 31, 2015 0.6421 Dec 31, 2016 0.644 Dec 31, 2017 0.6455 Dec 31, 2018 0.6469

Vega-Lite specification:
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Chart description: Am increasing trend was apparent from around 2014. The highest value, 65 and over, is for 2019.

Chart data: Year 65 years and older Dec 31, 2008 0.0448 Dec 31, 2009 0.0453 Dec 31, 2010 0.0456 Dec 31, 2011 0.0458 Dec 31, 2012 0.046 Dec 31, 2013 0.0465 Dec 31, 2014 0.0475 Dec 31, 2015 0.0488 Dec 31, 2016 0.0505 Dec 31, 2017 0.0525 Dec 31, 2018 0.0546

Vega-Lite specification:
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Chart description: There was a fairly slow increase of those aged at least 65 prior to 2014, but since then the rate has been increasingly rapidly and shows no sign of slowing.

Chart data: Year 65 years and older Dec 31, 2008 0.0448 Dec 31, 2009 0.0453 Dec 31, 2010 0.0456 Dec 31, 2011 0.0458 Dec 31, 2012 0.046 Dec 31, 2013 0.0465 Dec 31, 2014 0.0475 Dec 31, 2015 0.0488 Dec 31, 2016 0.0505 Dec 31, 2017 0.0525 Dec 31, 2018 0.0546

Vega-Lite specification:
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Chart description: The Price Index in the rural areas of India  have risen only marginally over the one year period, from roughly 145 to 150.

Chart data: Month Rural Jun 30, 2019 138.4 Jul 31, 2019 139.2 Aug 31, 2019 140.1 Sep 30, 2019 141 Oct 31, 2019 141.8 Nov 30, 2019 142.8 Dec 31, 2019 143.7 Jan 31, 2020 144.2 Feb 29, 2020 144.4 Mar 31, 2020 147.2 May 31, 2020 148.2 Jun 30, 2020 147.8

Vega-Lite specification:
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Chart description: From July 2019 to around March 2020 Urban slowly increases from approximately 140 to just under 150. It then quickly increases to 155 in April and after this point the graph reaches a plateau.

Chart data: Month Urban Jun 30, 2019 141.4 Jul 31, 2019 142.1 Aug 31, 2019 142.7 Sep 30, 2019 143.5 Oct 31, 2019 144.1 Nov 30, 2019 144.9 Dec 31, 2019 145.6 Jan 31, 2020 146.2 Feb 29, 2020 146.5 Mar 31, 2020 151.8 May 31, 2020 152.7 Jun 30, 2020 151.6

Vega-Lite specification:
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Chart description: The consumer price index gradually grew from July 2019. It's exceeded the maximum of 150 reaching its highest value in April 2020. After a plateau phase, during which the index stayed above 150, a slight decrease was registered.

Chart data: Month Urban Jun 30, 2019 141.4 Jul 31, 2019 142.1 Aug 31, 2019 142.7 Sep 30, 2019 143.5 Oct 31, 2019 144.1 Nov 30, 2019 144.9 Dec 31, 2019 145.6 Jan 31, 2020 146.2 Feb 29, 2020 146.5 Mar 31, 2020 151.8 May 31, 2020 152.7 Jun 30, 2020 151.6

Vega-Lite specification:
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Chart description: There was a dip in GDP IN 2012 which continued to decline until 2016. It the began to rise again and in 2019 it was at the same value as in 2012 (the previously highest GDP).

Chart data: Year Agriculture Dec 31, 2008 0.0113 Dec 31, 2009 0.013 Dec 31, 2010 0.0136 Dec 31, 2011 0.0131 Dec 31, 2012 0.0119 Dec 31, 2013 0.0107 Dec 31, 2014 0.0103 Dec 31, 2015 0.0091 Dec 31, 2016 0.0111 Dec 31, 2017 0.0115 Dec 31, 2018 0.0131

Vega-Lite specification:
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Chart description: In 2010, they had just below 0.25 share which later decreased in 2012 to bottom just below 0.20. This then steadily increased over the years after 2012, finding an all time high in 2017 of 0.30.

Chart data: Year Industry Dec 31, 2008 0.2345 Dec 31, 2009 0.2309 Dec 31, 2010 0.2141 Dec 31, 2011 0.1925 Dec 31, 2012 0.2053 Dec 31, 2013 0.2221 Dec 31, 2014 0.2358 Dec 31, 2015 0.2549 Dec 31, 2016 0.2793 Dec 31, 2017 0.2619 Dec 31, 2018 0.2615

Vega-Lite specification:
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Chart description: AG insurance had the greatest market share between 2015 and 2019 of over 0.2.

Chart data:  leading insurance companies 2016 AG Insuranc  0.224;  leading insurance companies: AG Insurance AX  0.125;  leading insurance companies: AXA KB  0.101;  leading insurance companies: KBC Ethia  0.09;  leading insurance companies: Ethias Belfiu  0.056;  leading insurance companies: Belfius P&  0.059;  leading insurance companies: P&V Allian  0.045;  leading insurance companies: Allianz Balois  0.051;  leading insurance companies: Baloise N  0.047;  leading insurance companies: NN ERGO - DKV - DA  0.04;  leading insurance companies: ERGO - DKV - DAS Argent  0.022;  leading insurance companies: Argenta Federal  0.014;  leading insurance companies: Federale Fide  0.009;  leading insurance companies: Fidea Integral  0.008;  leading insurance companies: Integrale General  0.028;  leading insurance companies: Generali

Vega-Lite specification:
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Chart description: AG Insurance has by far the largest market share at about 0.22. The market share of all other companies is below 0.125. AG Insurance  and AXA are the only companies with a market share above 0.1. 8 of the companies have a market share of 0.05 or less.

Chart data:  leading insurance companies 2018 AG Insuranc  0.217;  leading insurance companies: AG Insurance AX  0.121;  leading insurance companies: AXA KB  0.088;  leading insurance companies: KBC Ethia  0.093;  leading insurance companies: Ethias Belfiu  0.068;  leading insurance companies: Belfius P&  0.057;  leading insurance companies: P&V Allian  0.053;  leading insurance companies: Allianz Balois  0.049;  leading insurance companies: Baloise N  0.049;  leading insurance companies: NN ERGO - DKV - DA  0.036;  leading insurance companies: ERGO - DKV - DAS Argent  0.025;  leading insurance companies: Argenta Federal  0.015;  leading insurance companies: Federale Fide  0.011;  leading insurance companies: Fidea Credim  0.011;  leading insurance companies: Credimo General  0.027;  leading insurance companies: Generali

Vega-Lite specification:
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Chart description: Understanding burden of disease and better understanding of subpopulation are the most popular categories by executives.

Chart data: Current opinion of executives 0.6 Better understanding subpopulations and heterogeneity of treatment effects 0.6 Understanding burdern of disease 0.5 Monitoring patient safety (i.e., pharmacovigilance) 0.35 Comparative effectiveness research 0.2 Supporting regulatory submission and or label expansion 0.15 Accelerating the execution of clinical trials using RWD as a control arm for clinical trials 0.1 Optimizing the design of clinical trials 0.1 Identifying new drug targets/areas of unmet needs 0.05 Design of value-based contracting schemes 0.1 Biomarker hypothesis generation/validation 0 Supporting patient engagement programs 0 Measuring sales performance, targeting, and marketing metrics 0 Informing business development and portfolio strategy (therapeutic area assessment) 0 Informing pricing strategies

Vega-Lite specification:
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Chart description: Migration dropped over 60% between 2003 and 2011 before exceeding its migration records during 2017/2018.

Chart data: Year Inflow Dec 31, 1996 597.65 Dec 31, 1997 513.55 Dec 31, 1998 379.73 Dec 31, 1999 359.33 Dec 31, 2000 193.45 Dec 31, 2001 184.61 Dec 31, 2002 129.14 Dec 31, 2003 119.16 Dec 31, 2004 177.23 Dec 31, 2005 186.38 Dec 31, 2006 286.96 Dec 31, 2007 281.61 Dec 31, 2008 279.91 Dec 31, 2009 191.66 Dec 31, 2010 356.54 Dec 31, 2011 417.68 Dec 31, 2012 482.24 Dec 31, 2013 590.82 Dec 31, 2014 598.62 Dec 31, 2015 575.16 Dec 31, 2016 589.03 Dec 31, 2017 565.68 Dec 31, 2018 701.23

Vega-Lite specification:
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Chart description: 2004 showed the lowest migration from Russia. Since 2010 it has been steadily increasing with highest level in 2019.

Chart data: Year Inflow Dec 31, 1996 597.65 Dec 31, 1997 513.55 Dec 31, 1998 379.73 Dec 31, 1999 359.33 Dec 31, 2000 193.45 Dec 31, 2001 184.61 Dec 31, 2002 129.14 Dec 31, 2003 119.16 Dec 31, 2004 177.23 Dec 31, 2005 186.38 Dec 31, 2006 286.96 Dec 31, 2007 281.61 Dec 31, 2008 279.91 Dec 31, 2009 191.66 Dec 31, 2010 356.54 Dec 31, 2011 417.68 Dec 31, 2012 482.24 Dec 31, 2013 590.82 Dec 31, 2014 598.62 Dec 31, 2015 575.16 Dec 31, 2016 589.03 Dec 31, 2017 565.68 Dec 31, 2018 701.23

Vega-Lite specification:
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Chart description: A slow and steady decrease from 150,000 to 50000 from year  2000 to year  2010. then a sudden increase from 50,000 to 350,000 from year2010 to year  2015.

Chart data: Year Outflow Dec 31, 1996 232.99 Dec 31, 1997 213.38 Dec 31, 1998 214.96 Dec 31, 1999 145.72 Dec 31, 2000 121.17 Dec 31, 2001 106.69 Dec 31, 2002 94.02 Dec 31, 2003 79.8 Dec 31, 2004 69.8 Dec 31, 2005 54.06 Dec 31, 2006 47.01 Dec 31, 2007 39.51 Dec 31, 2008 32.46 Dec 31, 2009 33.58 Dec 31, 2010 36.77 Dec 31, 2011 122.75 Dec 31, 2012 186.38 Dec 31, 2013 310.5 Dec 31, 2014 353.23 Dec 31, 2015 313.21 Dec 31, 2016 377.16 Dec 31, 2017 440.83 Dec 31, 2018 416.13

Vega-Lite specification:
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Chart description: Two of the 12 leading online car and property classifieds worldwide showing the highest  EV/EBITDA (between 60 and 80) from 2020 to 2022, are in the USA and one in India. The remaining ones are in the UK, China, Australia and Norway, with the majority showing an EV/EBITDA of around 20 or below, except for Norway which has EV/EBITDA of around 50.

Chart data: Factor 2022* Zillow (United States) 66.4 Adevinta (Norway) 35.8 Autohome (China) 13.4 REA Group (Australia) 20.9 Scout24 (Germany) 20.9 Rightmove (United Kingdom) 23.2 Auto Trader (United Kingdom) 20.3 Info Edge (India) 75.2 Redfin (United States) 71.8 carsales.com (Australia) 19.4 Bitauto (China) 18.2 Purplebricks (United Kingdom) 15.4

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": "multiColumn/data/6338.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#1A1A1A"}, "x": {"type": "nominal", "axis": {"labelAngle": 45}, "bin": false, "field": "Factor"}, "y": {"type": "quantitative", "axis": {"title": "2022*"}, "field": "2022*"}}, "title": ["Enterprise-value-to-EBITDA (EV/EBITDA) of", "leading online car and property classifieds", "worldwide from 2020 to 2022"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}