delen/vistext huggingface dataset:
Chart description: The graph shows that in over 40 years the population has increased by a quarter.

Chart data: Year Number of residents per square mile Dec 31, 1959 656.9 Dec 31, 1969 729.4 Dec 31, 1979 735.5 Dec 31, 1989 771.3 Dec 31, 1999 814 Dec 31, 2009 839.5 Dec 31, 2010 844.5 Dec 31, 2011 852.1 Dec 31, 2012 858 Dec 31, 2013 864.8 Dec 31, 2014 871.1 Dec 31, 2015 873.3 Dec 31, 2016 879.5 Dec 31, 2017 884.9

Vega-Lite specification:
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Chart description: Crime rates in Berlin were higher than that in other cities in Germany in 2019 per 1000 people.

Chart data: Crime rate per 100 thousand people Country 13746 Berlin 11068 Hamburg 11036 Bremen 7716 Saxony-Anhalt 7386 Saarland 6790 Mecklenburg-Vorpommern 6720 North-Rhein Westphalia 6639 Brandenburg 6419 Saxony 6349 Germany 6272 Lower Saxony 6163 Schleswig-Holstein 5971 Thüringen 5777 Rhineland-Palatinate 5449 Hessen 5037 Baden-Württemberg 4343 Bavaria

Vega-Lite specification:
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Chart description: Berlin has the highest crime rate, Bavaria has the lowest, Berlin has approximately triple the crime rate of Bavaria.

Chart data: Crime rate per 100 thousand people Country 13746 Berlin 11068 Hamburg 11036 Bremen 7716 Saxony-Anhalt 7386 Saarland 6790 Mecklenburg-Vorpommern 6720 North-Rhein Westphalia 6639 Brandenburg 6419 Saxony 6349 Germany 6272 Lower Saxony 6163 Schleswig-Holstein 5971 Thüringen 5777 Rhineland-Palatinate 5449 Hessen 5037 Baden-Württemberg 4343 Bavaria

Vega-Lite specification:
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Chart description: The average crim e rate in germany seems to sit at around 4,000 per 100,000 people. berlin has the most at a little under 14,0000 per 100,000.

Chart data: Crime rate per 100 thousand people Country 13746 Berlin 11068 Hamburg 11036 Bremen 7716 Saxony-Anhalt 7386 Saarland 6790 Mecklenburg-Vorpommern 6720 North-Rhein Westphalia 6639 Brandenburg 6419 Saxony 6349 Germany 6272 Lower Saxony 6163 Schleswig-Holstein 5971 Thüringen 5777 Rhineland-Palatinate 5449 Hessen 5037 Baden-Württemberg 4343 Bavaria

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Chart description: The visualization chart shows that during the period between 2000 and 2019 the U.S. has produced at least 400,000 cwt of potatoes every year. Between 2000 and 2019, the year 2000 had the highest yield of potatoes, with 500,000 cwt of potatoes grown in the U.S. During the ten year period between 2000 and 2010, the potato yield in the U.S. declined from 500,000 down to a low of 400,000.

Chart data: Year Production in thousand cwt Dec 31, 1999 513544 Dec 31, 2000 437673 Dec 31, 2001 458171 Dec 31, 2002 458199 Dec 31, 2003 455806 Dec 31, 2004 423788 Dec 31, 2005 440698 Dec 31, 2006 444875 Dec 31, 2007 415055 Dec 31, 2008 432601 Dec 31, 2009 404549 Dec 31, 2010 430037 Dec 31, 2011 464970 Dec 31, 2012 434652 Dec 31, 2013 442170 Dec 31, 2014 441205 Dec 31, 2015 450324 Dec 31, 2016 450921 Dec 31, 2017 454314 Dec 31, 2018 422890

Vega-Lite specification:
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Chart description: lokks lik there has been a steady decline since 2000.

Chart data: Year Production in thousand cwt Dec 31, 1999 513544 Dec 31, 2000 437673 Dec 31, 2001 458171 Dec 31, 2002 458199 Dec 31, 2003 455806 Dec 31, 2004 423788 Dec 31, 2005 440698 Dec 31, 2006 444875 Dec 31, 2007 415055 Dec 31, 2008 432601 Dec 31, 2009 404549 Dec 31, 2010 430037 Dec 31, 2011 464970 Dec 31, 2012 434652 Dec 31, 2013 442170 Dec 31, 2014 441205 Dec 31, 2015 450324 Dec 31, 2016 450921 Dec 31, 2017 454314 Dec 31, 2018 422890

Vega-Lite specification:
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Chart description: Production increased steadily in numbers as time went on.

Chart data: Year Production in million liters Dec 31, 1994 104.3 Dec 31, 1999 181.6 Dec 31, 2004 209.7 Dec 31, 2005 242.7 Dec 31, 2006 284.1 Dec 31, 2007 312.1 Dec 31, 2008 249 Dec 31, 2009 257.5 Dec 31, 2010 261.1 Dec 31, 2011 253.2 Dec 31, 2012 226.5 Dec 31, 2013 242.4 Dec 31, 2014 228.5 Dec 31, 2015 273.3 Dec 31, 2016 271.4 Dec 31, 2017 309.1 Dec 31, 2018 351.7

Vega-Lite specification:
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Chart description: Revenue increases over time from 2005/06 to 2018/19 other than a dip in 2012/13.  Revenue is between 63 million and 140 million U.S. dollars.

Chart data: Year Revenue in million U.S. dollars 2018/19 138 2017/18 132 2016/17 129 2015/16 121 2014/15 130 2013/14 122 2012/13* 89 2011/12 117 2010/11 105 2009/10 98 2008/09 95 2007/08 97 2006/07 77 2005/06 68

Vega-Lite specification:
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Chart description: The revenue if the Calgary Flames gradually increases from 2005 to 2019.

Chart data: Year Revenue in million U.S. dollars 2018/19 138 2017/18 132 2016/17 129 2015/16 121 2014/15 130 2013/14 122 2012/13* 89 2011/12 117 2010/11 105 2009/10 98 2008/09 95 2007/08 97 2006/07 77 2005/06 68

Vega-Lite specification:
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Chart description: Facebook and Pinterest have the greatest share of traffic.

Chart data: Share of traffic Response 0.1816 Facebook 0.0753 Pinterest 0.0074 Twitter 0.0073 Instagram 0.0017 YouTube 0.0013 Flipboard 0.001 StumbleUpon 0.0007 Buzzfeed 0.0007 Reddit 0.0005 LinkedIn 0.0004 Yummly 0.0003 Google+ 0 Tumblr

Vega-Lite specification:
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Chart description: Facebook was the leading source of referral traffic during the second half of 2017, accountability ting for almost 0.20 of the share of visits. Instagram and twitter were responsible for a very similar number of visits, with less than 0.1 of the traffic share during this period each. Tumblr was the lowest source of referral traffic during this period, with no data visual on the graph.

Chart data: Share of traffic Response 0.1816 Facebook 0.0753 Pinterest 0.0074 Twitter 0.0073 Instagram 0.0017 YouTube 0.0013 Flipboard 0.001 StumbleUpon 0.0007 Buzzfeed 0.0007 Reddit 0.0005 LinkedIn 0.0004 Yummly 0.0003 Google+ 0 Tumblr

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Chart description: Organic chemicals are the most valuable import. Essential oils, graphite, explosives and accessors are the least valuable.

Chart data: type Import value in billion Indian rupees Organic chemicals 996.72 Residual chemicals and allied products 527.8 Manufactured fertilizers 462.67 Inorganic chemicals 394.87 Drugs and drug intemediates in bulk 248.5 Drug formulations, biologicals 141.26 Paint, varnish and allied products 130.27 Cosmetics and toiletries 112.49 Agro chemicals 92.67 Dye intermediates 69.95 Crude fertilizers 58.28 Other chemicals 58.22 Dyes 25.07 Graphite, explosives and accessories 11.52 Essential oils 10.47

Vega-Lite specification:
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Chart description: In 2018, Environmental Protection Department has 0.5% reduced in budget. However, Defense department has the increase of 0.2% budget.

Chart data: department or service Percentage change from 2017 Environmental Protection Agency −0.31 State Department −0.29 Agriculture Department −0.21 Labor Department −0.21 Department of Health and Human Services −0.18 Commerce Department −0.16 Education Department −0.14 Department of Housing and Urban Development −0.13 Transportation Department −0.13 Interior Department −0.12 Energy Department −0.06 Small Business Administration −0.05 Treasury Department −0.04 Justice Department −0.04 NASA −0.01 Department of Veterans Affairs 0.06 Department of Homeland Security 0.07 Defense Department 0.09

Vega-Lite specification:
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Chart description: Greg P Russell has the highest number of Academy Award nominations, Anna Behlmer, Walter Lantz and Walter Scharf have the lowest number of Academy Award nominations.

Chart data: artist Number of Academy Awards nominations Greg P. Russell* 16 Roland Anderson 15 Alex North 15 Thomas Newman 15 Loren L. Ryder 14 George J. Folsey 13 Federico Fellini 12 Rick Kline 11 Diane Warren 11 Walter Lantz 10 Walter Scharf 10 Anna Behlmer 10

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Chart description: The most popular Disney Princess was Snow White. The least popular was Tiana.

Chart data: Response Share of respondents Snow White 0.1 Belle 0.07 Ariel 0.06 Cinderella 0.06 Rapunzel 0.04 Merida 0.04 Mulan 0.04 Moana 0.04 Jasmine 0.03 Elsa 0.03 Aurora 0.02 Pocahontas 0.02 Anna 0.02 Tiana 0.01

Vega-Lite specification:
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Chart description: There are 15 types of music genre on the chart the highest ranking is pop followed by country, the lowest scoring are world beat, Latin American and Ska.

Chart data: Response Share of respondents Pop 0.184 Country 0.153 Other 0.136 Rock 0.131 Christian 0.09 Folk / Singer-Songwriter 0.077 Hip Hop / Rap 0.073 Blues / R&B 0.046 Classical 0.039 Easy listening 0.034 Jazz 0.024 Electronic 0.007 Ska 0.002 Worldbeat 0.002 Latin American 0.002

Vega-Lite specification:
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Chart description: Pop was the most chosen response followed by Country which both exceeded 0.15 share of the respondents.

Chart data: Response Share of respondents Pop 0.184 Country 0.153 Other 0.136 Rock 0.131 Christian 0.09 Folk / Singer-Songwriter 0.077 Hip Hop / Rap 0.073 Blues / R&B 0.046 Classical 0.039 Easy listening 0.034 Jazz 0.024 Electronic 0.007 Ska 0.002 Worldbeat 0.002 Latin American 0.002

Vega-Lite specification:
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Chart description: Novak Djokovic, Rafael Nadal and Roger Federer are marked as the top 3 ATP tennis players by career prize money earned as in August of 2020 a significant difference compared to the other 17 players. The other players do not exceed the 50 million mark by the exception of Andy Murray.

Chart data: Tennis player Prize money earned in million U.S. dollars Novak Djokovic 143.63 Roger Federer 129.95 Rafael Nadal 120.96 Andy Murray 61.54 Pete Sampras 43.28 Stan Wawrinka 34.28 David Ferrer 31.48 Andre Agassi 31.15 Tomas Berdych 29.49 Marin Cilic 27.86 Juan Martin del Potro 25.89 Boris Becker 25.08 Yevgeny Kafelnikov 23.88 Dominic Thiem 23.87 Kei Nishikori 23.85 Jo-Wilfried Tsonga 22.16 Ivan Lendl 21.26 Alexander Zverev 21.01 Lleyton Hewitt 20.89 Andy Roddick 20.64

Vega-Lite specification:
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Chart description: Roger Federer is the third biggest tennis player with career prize money earnings as of August 2020, Rafael Nadal is the second tennis player in order with the most career prize money earnings as of August 2020, while Novak Djokovic is the tennis player with the most career prize money earnings as of August 2020 out of all 20 tennis player included.

Chart data: Tennis player Prize money earned in million U.S. dollars Novak Djokovic 143.63 Roger Federer 129.95 Rafael Nadal 120.96 Andy Murray 61.54 Pete Sampras 43.28 Stan Wawrinka 34.28 David Ferrer 31.48 Andre Agassi 31.15 Tomas Berdych 29.49 Marin Cilic 27.86 Juan Martin del Potro 25.89 Boris Becker 25.08 Yevgeny Kafelnikov 23.88 Dominic Thiem 23.87 Kei Nishikori 23.85 Jo-Wilfried Tsonga 22.16 Ivan Lendl 21.26 Alexander Zverev 21.01 Lleyton Hewitt 20.89 Andy Roddick 20.64

Vega-Lite specification:
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Chart description: The US imports the most leather goods. The Netherlands imports the least leather goods. The US imports more than double the leather goods of any other country.

Chart data: Import value in million U.S. dollars Country 13419 United States 5860 Japan 4898 Hong Kong 4272 France 4018 Germany 3421 United Kingdom 3059 Italy 2006 South Korea 1918 China 1629 Netherlands

Vega-Lite specification:
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Chart description: it is not a very good data search as “other keywords” is larger massively. the other words all reponses have the same popularity as eachother.

Chart data: Searches in thousands keyword 60.5 bet 33.1 bettin calculator 27.1 betting 27.1 betting tips 27.1 betting sites 27.1 football betting tips 22.2 premier league odds 18.1 matched betting 12.1 online betting 9.9 football betting 364.83 other keywords

Vega-Lite specification:
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Chart description: That all keywords are used across all betting platforms and they don't really change. They are all pretty similar.

Chart data: Searches in thousands keyword 60.5 bet 33.1 bettin calculator 27.1 betting 27.1 betting tips 27.1 betting sites 27.1 football betting tips 22.2 premier league odds 18.1 matched betting 12.1 online betting 9.9 football betting 364.83 other keywords

Vega-Lite specification:
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Chart description: The typical search terms to do with betting were included in the graph but it turns out that "other keywords" were searched for more, well over 350 thousand times.

Chart data: Searches in thousands keyword 60.5 bet 33.1 bettin calculator 27.1 betting 27.1 betting tips 27.1 betting sites 27.1 football betting tips 22.2 premier league odds 18.1 matched betting 12.1 online betting 9.9 football betting 364.83 other keywords

Vega-Lite specification:
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Chart description: Most people used keywords not in the bar chart to search for Sports related betting.  Football betting was searched the least.

Chart data: Searches in thousands keyword 60.5 bet 33.1 bettin calculator 27.1 betting 27.1 betting tips 27.1 betting sites 27.1 football betting tips 22.2 premier league odds 18.1 matched betting 12.1 online betting 9.9 football betting 364.83 other keywords

Vega-Lite specification:
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Chart description: After a brief decline around 2000, berry consumption in the US consistently rose up to 2015, when annual consumption topped 10 pounds of berries per capita.

Chart data: Year Per capita consumption in pounds Dec 31, 1999 5.31 Dec 31, 2000 4.75 Dec 31, 2001 5.21 Dec 31, 2002 5.91 Dec 31, 2003 6.24 Dec 31, 2004 6.46 Dec 31, 2005 7.04 Dec 31, 2006 7.13 Dec 31, 2007 7.51 Dec 31, 2008 8.48 Dec 31, 2009 8.61 Dec 31, 2010 9.02 Dec 31, 2011 9.69 Dec 31, 2012 9.85 Dec 31, 2013 10.03 Dec 31, 2014 10.25

Vega-Lite specification:
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Chart description: Cameroon’s unemployment rate dropped drastically in the early to mid-2000s. Although the unemployment rate increased slightly in the late 2000s, this did not reach the highs of the pre-20th century / early 2000s. Generally, unemployment has steadily and slowly decreased since 2010.

Chart data: Year Unemployment rate Dec 31, 1998 0.0774 Dec 31, 1999 0.0759 Dec 31, 2000 0.0746 Dec 31, 2001 0.067 Dec 31, 2002 0.0592 Dec 31, 2003 0.0514 Dec 31, 2004 0.044 Dec 31, 2005 0.0369 Dec 31, 2006 0.0306 Dec 31, 2007 0.033 Dec 31, 2008 0.0377 Dec 31, 2009 0.0411 Dec 31, 2010 0.0397 Dec 31, 2011 0.0384 Dec 31, 2012 0.0371 Dec 31, 2013 0.0353 Dec 31, 2014 0.0351 Dec 31, 2015 0.0347 Dec 31, 2016 0.0341 Dec 31, 2017 0.0336 Dec 31, 2018 0.0338 Dec 31, 2019 0.0343

Vega-Lite specification:
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Chart description: The line chart above is a simple demonstration of the dip in unemployment in Cameroon between 2001 and 2019, which has more than halved during this period from 0.08% to less than 0.04% in 2019. There was a brief rise in the 2007 period, but this began to decrease again gradually over the following years.

Chart data: Year Unemployment rate Dec 31, 1998 0.0774 Dec 31, 1999 0.0759 Dec 31, 2000 0.0746 Dec 31, 2001 0.067 Dec 31, 2002 0.0592 Dec 31, 2003 0.0514 Dec 31, 2004 0.044 Dec 31, 2005 0.0369 Dec 31, 2006 0.0306 Dec 31, 2007 0.033 Dec 31, 2008 0.0377 Dec 31, 2009 0.0411 Dec 31, 2010 0.0397 Dec 31, 2011 0.0384 Dec 31, 2012 0.0371 Dec 31, 2013 0.0353 Dec 31, 2014 0.0351 Dec 31, 2015 0.0347 Dec 31, 2016 0.0341 Dec 31, 2017 0.0336 Dec 31, 2018 0.0338 Dec 31, 2019 0.0343

Vega-Lite specification:
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