delen/vistext huggingface dataset:
Chart description: The Indian Classified 'Info Edge' has the highest Enterprise value at 75. The Chinese 'Autohome' has the lowest value, at 12. Only three companies have an Enterprise value over 60, with 8 companies valuing over 30.

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:
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Chart description: Lawyers receive the highest hourly rate and radio/tv presenters the lowest. 13 of the 20 occupations listed receive under 20 of an hourly rate.

Chart data: Mean hourly wage, nonmetropolitan areas occupation 13.81 Actors 17.38 Broadcast news analysts 23.02 Producers and directors 12.17 Radio and television announcers 17.95 Film and video editors 13.23 Reporters and correspondents 26.49 Administrative law judges, adjudicators, and hearing officers 19.63 Writers and authors 30.22 Advertising and promotions managers 28.08 Art directors 19.18 Multi-media artists and animators 18.14 Artists and related workers, all other 40.32 Lawyers 30.27 Economists 18.79 Historians 19.34 Editors 17.8 Advertising sales agents 18.82 Police and sheriff’s patrol officers 37.98 Financial managers 16.25 Camera operators, television, video, and motion picture

Vega-Lite specification:
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Chart description: Lawyers have the highest wage difference between metropolitan and nonmetropolitan areas. Reporters have the lowest difference in wages. The highest (layer) and the lowest difference (reporters and correspondents) in hourly wage have a difference of around 28. Most occupations has a wage difference of around 20. The wages of financial managers and lawyers are extremely increased in metropolitan areas.

Chart data: Mean hourly wage, nonmetropolitan areas occupation 13.81 Actors 17.38 Broadcast news analysts 23.02 Producers and directors 12.17 Radio and television announcers 17.95 Film and video editors 13.23 Reporters and correspondents 26.49 Administrative law judges, adjudicators, and hearing officers 19.63 Writers and authors 30.22 Advertising and promotions managers 28.08 Art directors 19.18 Multi-media artists and animators 18.14 Artists and related workers, all other 40.32 Lawyers 30.27 Economists 18.79 Historians 19.34 Editors 17.8 Advertising sales agents 18.82 Police and sheriff’s patrol officers 37.98 Financial managers 16.25 Camera operators, television, video, and motion picture

Vega-Lite specification:
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Chart description: Vehicle buyers of the USA most often get their information regarding their vehicles from car dealerships, vehicle manufacturer websites and independent information websites.

Chart data: Response United States Car dealer (both new and used cars) 0.64 Vehicle manufacturer websites 0.56 Search engine 0.32 Information websites/independent car valuation services 0.54 Dealer website 0.44 Family and friends 0.29 Specialist motoring/automotive press 0.17 Web forums, blogs or internet discussion groups 0.13 Print advertising 0.18 Auto shows 0.1 TV advertising 0.16 Independent e-tailer sites 0.11 Manufacturer or dealer social media page 0.07 Car dealer (used cars only) 0.1 Non-specialist motoring/automotive press 0.05

Vega-Lite specification:
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Chart description: In 2012, most people used car dealers as the most frequent source of information when purchasing a vehicle. Non-specialist websites were used the least frequently of any information source. Word of mouth from family and friends remains an important method of obtaining information.

Chart data: Response United States Car dealer (both new and used cars) 0.64 Vehicle manufacturer websites 0.56 Search engine 0.32 Information websites/independent car valuation services 0.54 Dealer website 0.44 Family and friends 0.29 Specialist motoring/automotive press 0.17 Web forums, blogs or internet discussion groups 0.13 Print advertising 0.18 Auto shows 0.1 TV advertising 0.16 Independent e-tailer sites 0.11 Manufacturer or dealer social media page 0.07 Car dealer (used cars only) 0.1 Non-specialist motoring/automotive press 0.05

Vega-Lite specification:
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Chart description: The bar chart shows car buyers in the United Kingdom used car dealers as their main source of information.  It shows car buyers in the United Kingdom used Manufacturer or Dealer soci... as their least used source of information.  There is no clear pattern in the sources used.  Manufacturer websites were the second most used.

Chart data: United Kingdom Response 0.64 Car dealer (both new and used cars) 0.55 Vehicle manufacturer websites 0.36 Search engine 0.43 Information websites/independent car valuation services 0.44 Dealer website 0.32 Family and friends 0.37 Specialist motoring/automotive press 0.19 Web forums, blogs or internet discussion groups 0.18 Print advertising 0.09 Auto shows 0.13 TV advertising 0.13 Independent e-tailer sites 0.08 Manufacturer or dealer social media page 0.17 Car dealer (used cars only) 0.11 Non-specialist motoring/automotive press

Vega-Lite specification:
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Chart description: After looking at the bar chart above, it shows that car dealers (both new and used) is the most popular in Brazil, whereas non-specialist are least popular.

Chart data: Response Brazil Car dealer (both new and used cars) 0.57 Vehicle manufacturer websites 0.42 Search engine 0.34 Information websites/independent car valuation services 0.19 Dealer website 0.39 Family and friends 0.38 Specialist motoring/automotive press 0.32 Web forums, blogs or internet discussion groups 0.17 Print advertising 0.27 Auto shows 0.21 TV advertising 0.27 Independent e-tailer sites 0.11 Manufacturer or dealer social media page 0.19 Car dealer (used cars only) 0.15 Non-specialist motoring/automotive press 0.09

Vega-Lite specification:
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Chart description: The share of train journeys arriving on time in the UK increases overall until 2012/13 and then gradually increases. The mean share of journeys arriving on time is around 0.88.

Chart data: Year All operators 2019/20 0.862 2018/19 0.863 2017/18 0.878 2016/17 0.877 2015/16 0.891 2014/15 0.897 2013/14 0.9 2012/13 0.909 2011/12 0.916 2010/11 0.908 2009/10 0.915 2008/09 0.906 2007/08 0.899 2006/07 0.881

Vega-Lite specification:
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Chart description: There appears to be little change in employment distribution in the ten years shown on the graph.

Chart data: Year Industry Dec 31, 2009 0.2064 Dec 31, 2010 0.2005 Dec 31, 2011 0.1984 Dec 31, 2012 0.1981 Dec 31, 2013 0.2047 Dec 31, 2014 0.2159 Dec 31, 2015 0.2016 Dec 31, 2016 0.2048 Dec 31, 2017 0.1979 Dec 31, 2018 0.1958 Dec 31, 2019 0.194

Vega-Lite specification:
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Chart description: The chart shows that between 2010 and 2018, and possibly onwards, that the Services sector employment steadily maintained itself between 0.8 & 0.6 in relation to the total distribution of New Zealand’s total employment.

Chart data: Year Services Dec 31, 2009 0.7262 Dec 31, 2010 0.7304 Dec 31, 2011 0.7341 Dec 31, 2012 0.7374 Dec 31, 2013 0.7329 Dec 31, 2014 0.7228 Dec 31, 2015 0.7334 Dec 31, 2016 0.733 Dec 31, 2017 0.7442 Dec 31, 2018 0.7476 Dec 31, 2019 0.7505

Vega-Lite specification:
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Chart description: By far, most people associate Football with negative moral values. followed by Basketball, Boxing, and Wrestling. Tennis is the sport that is the least associated with negative moral values, followed by Soccer, Golf, and Auto-racing.

Chart data: Response 35-44 years Football 0.51 Basketball 0.29 Boxing 0.25 Wrestling 0.22 Baseball 0.16 Hockey 0.13 Mixed Martial Arts 0.14 Auto Racing 0.06 Golf 0.04 Soccer 0.03 Tennis 0.02 I don't associate any U.S. professional sports with negative moral values 0.16 Not sure 0.09

Vega-Lite specification:
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Chart description: Golf, soccer and tennis received the least amount of responses and football received the highest. Most sports didnt score over 0.3.

Chart data: Response 55-64 years Football 0.59 Basketball 0.31 Boxing 0.27 Wrestling 0.2 Baseball 0.15 Hockey 0.14 Mixed Martial Arts 0.13 Auto Racing 0.07 Golf 0.03 Soccer 0.02 Tennis 0.01 I don't associate any U.S. professional sports with negative moral values 0.13 Not sure 0.1

Vega-Lite specification:
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Chart description: Budget for salary increases in the United Kingdom Social Housing associations decreased from 2018-2020.

Chart data: Response Increase by 3% 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 0.08 Dec 31, 2018 0.08 Dec 31, 2019 0.03

Vega-Lite specification:
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Chart description: Uusimaa is the most populous region of Finland and has the most foreign languages.

Chart data: region of Finland Foreign languages Uusimaa 236959 Southwest Finland 35809 Satakunta 7927 Kanta-Häme 7221 Pirkanmaa 26166 Päijät-Häme 10994 Kymenlaakso 10180 South Karelia 8092 South Savo 4862 North Savo 7506 North Karelia 6249 Central Finland 9531 South Ostrobothnia 4344 Ostrobothnia 12665 Central Ostrobothnia 2038 North Ostrobothnia 12358 Kainuu 2090 Lapland 5032 Åland 2621

Vega-Lite specification:
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Chart description: Czech Republic produces fewest bakery products with under 1,000,000 while Germany makes the most with over 6,000,000 tonnes.

Chart data: Country 2019 German  6111.6; Country: Germany Franc  4513; Country: France Ital  4169.6; Country: Italy United Kingdo  3876.2; Country: United Kingdom Spai  2412.1; Country: Spain Polan  2053.8; Country: Poland Romani  1828.4; Country: Romania Netherland  1288.8; Country: Netherlands Belgiu  956; Country: Belgium Czech Republi  854.4; Country: Czech Republic

Vega-Lite specification:
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Chart description: The chart shows that Germany had the largest bakery products market in the EU from 2015 to 2019 at around 6000000 tonnes. Czech Republic’s market was the smallest at under 1000000 tonnes.

Chart data: Country 2019 German  6111.6; Country: Germany Franc  4513; Country: France Ital  4169.6; Country: Italy United Kingdo  3876.2; Country: United Kingdom Spai  2412.1; Country: Spain Polan  2053.8; Country: Poland Romani  1828.4; Country: Romania Netherland  1288.8; Country: Netherlands Belgiu  956; Country: Belgium Czech Republi  854.4; Country: Czech Republic

Vega-Lite specification:
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Chart description: The consumption rate is overall falling at a slow speed.

Chart data: Year 1/2 glass per day Dec 31, 2009 0.209 Dec 31, 2010 0.206 Dec 31, 2011 0.19 Dec 31, 2012 0.181 Dec 31, 2013 0.173 Dec 31, 2014 0.177 Dec 31, 2015 0.17 Dec 31, 2016 0.168 Dec 31, 2017 0.162 Dec 31, 2018 0.156

Vega-Lite specification:
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Chart description: Consumption rate of alcoholic beverages has slowly declined from 2010 to 2018There was a slight upwards trend between 2014 and 2016, where it then returned to the previous trajectory and began steadily falling again.

Chart data: Year 1/2 glass per day Dec 31, 2009 0.209 Dec 31, 2010 0.206 Dec 31, 2011 0.19 Dec 31, 2012 0.181 Dec 31, 2013 0.173 Dec 31, 2014 0.177 Dec 31, 2015 0.17 Dec 31, 2016 0.168 Dec 31, 2017 0.162 Dec 31, 2018 0.156

Vega-Lite specification:
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Chart description: It is clear that the age structure between 2010 and 2018 was very similar. Other than the spike up to almost 14 years in 2009, the age structure seemed to stay almost the same all the way until 2018.

Chart data: Year 0-14 years Dec 31, 2008 0.3815 Dec 31, 2009 0.3769 Dec 31, 2010 0.3732 Dec 31, 2011 0.3695 Dec 31, 2012 0.3659 Dec 31, 2013 0.3625 Dec 31, 2014 0.3594 Dec 31, 2015 0.357 Dec 31, 2016 0.3548 Dec 31, 2017 0.3527 Dec 31, 2018 0.3505

Vega-Lite specification:
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Chart description: You can see that from 2010 to 2018 there has been a gradual, steady inclease in age.

Chart data: Year 15-64 years Dec 31, 2008 0.5763 Dec 31, 2009 0.5807 Dec 31, 2010 0.5842 Dec 31, 2011 0.5877 Dec 31, 2012 0.5911 Dec 31, 2013 0.5944 Dec 31, 2014 0.5975 Dec 31, 2015 0.5999 Dec 31, 2016 0.6021 Dec 31, 2017 0.6042 Dec 31, 2018 0.6062

Vega-Lite specification:
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Chart description: The percentage of 65 years and older as part of the population in Pakistan between 2009 and 2019 remained fairly constant.

Chart data: Year 65 years and older Dec 31, 2008 0.0422 Dec 31, 2009 0.0424 Dec 31, 2010 0.0426 Dec 31, 2011 0.0428 Dec 31, 2012 0.043 Dec 31, 2013 0.0431 Dec 31, 2014 0.0431 Dec 31, 2015 0.0432 Dec 31, 2016 0.0431 Dec 31, 2017 0.0431 Dec 31, 2018 0.0432

Vega-Lite specification:
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Chart description: The age structure as represented by the linear scale has only risen very slightly over the 10 year period.

Chart data: Year 65 years and older Dec 31, 2008 0.0422 Dec 31, 2009 0.0424 Dec 31, 2010 0.0426 Dec 31, 2011 0.0428 Dec 31, 2012 0.043 Dec 31, 2013 0.0431 Dec 31, 2014 0.0431 Dec 31, 2015 0.0432 Dec 31, 2016 0.0431 Dec 31, 2017 0.0431 Dec 31, 2018 0.0432

Vega-Lite specification:
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Chart description: The age structure did not fluctuate from 2010 to 2018.

Chart data: Year 65 years and older Dec 31, 2008 0.0422 Dec 31, 2009 0.0424 Dec 31, 2010 0.0426 Dec 31, 2011 0.0428 Dec 31, 2012 0.043 Dec 31, 2013 0.0431 Dec 31, 2014 0.0431 Dec 31, 2015 0.0432 Dec 31, 2016 0.0431 Dec 31, 2017 0.0431 Dec 31, 2018 0.0432

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Chart description: Whilst the months are difficult to sort, it seem that the highest fuel prices are in the winter.

Chart data: Month Los Angeles, CA Oct 20 1.21 Sep 20 1.16 Aug 20 1.29 Jul 20 1.26 Jun 20 1.18 May 20 0.91 Apr 20 0.82 Mar 20 1.27 Feb 20 1.75 Jan 20 1.91 Dec 19 1.96 Nov 19 2.11 Oct 19 2.07

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