delen/vistext huggingface dataset:
Chart description: Business and economics was the most popular area of study. Education was second. There were no students studying the military. Only three subjects had more than 1000 students.

Chart data: field of study Coloured Business, Economics and Management Studies 3209 Education 2111 Engineering 617 Social Sciences 642 Health Professions and Related Clinical Sciences 1178 Public Management and Services 369 Computer and Information Sciences 408 Law 580 Physical Sciences 292 Agriculture, Agricultural Operations and Related Sciences 92 Life Sciences 477 Psychology 560 Communication, Journalism and Related Studies 212 Languages, Linguistics and Literature 369 Architecture and the Built Environment 184 Mathematics and Statistics 102 Visual and Performing Arts 318 Philiosophy, Religion and Theology 135 Family Ecology and Consumer Sciences 28 Military Sciences 0

Vega-Lite specification:
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Chart description: Highest projected growth is in 2017 and 2018. In 2011 growth projected is minus 0.05. 2013 shows lowest projected growth.

Chart data: Year Domestic 2020-2040** 0.019 2019-2039** 0.017 2018-2038** 0.019 2017-2037** 0.009 2016-2036** 0.013 2020 0.019 2019 0.028 2018 0.077 2017 0.095 2016 0.021 2015 0.033 2014 0.023 2013 0.007 2012 0.021 2011 −0.061

Vega-Lite specification:
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Chart description: remains low apart from coal and miscellaneous  - the rest are steady.

Chart data: Commodity group 2006 Miscellaneous mixed shipments, primarily intermoda  8536; Commodity group: Miscellaneous mixed shipments, primarily intermodal Coa  7574; Commodity group: Coal All other carload  2896; Commodity group: All other carloads Chemical  1969; Commodity group: Chemicals Farm product  1590; Commodity group: Farm products Food and similar product  1487; Commodity group: Food and similar products Non-metallic mineral  1470; Commodity group: Non-metallic minerals Motor vehicles and equipmen  1714; Commodity group: Motor vehicles and equipment Waste and scrap materia  701; Commodity group: Waste and scrap material Pulp, paper, and allied product  671; Commodity group: Pulp, paper, and allied products Metallic ore  674; Commodity group: Metallic ores Petroleum and cok  663; Commodity group: Petroleum and coke Metal and product  778; Commodity group: Metal and products Stone, clay, and glass product  570; Commodity group: Stone, clay, and glass products Lumber and wood product  548; Commodity group: Lumber and wood products Forwarder and shipper association traffi  276; Commodity group: Forwarder and shipper association traffic

Vega-Lite specification:
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Chart description: The highest number of carloads transported by US Class I railroads between 2004 and 2009 were ‘Miscellaneous mixed shipments, p…’. Coal was in second place. The least amount of carloads were ‘Forwarder and shipper association…’. 8 out of the 16 commodity groups had fewer than 1,000,000 carloads. 13 commodity groups had 2,000,000 or fewer carloads.

Chart data: Commodity group 2006 Miscellaneous mixed shipments, primarily intermoda  8536; Commodity group: Miscellaneous mixed shipments, primarily intermodal Coa  7574; Commodity group: Coal All other carload  2896; Commodity group: All other carloads Chemical  1969; Commodity group: Chemicals Farm product  1590; Commodity group: Farm products Food and similar product  1487; Commodity group: Food and similar products Non-metallic mineral  1470; Commodity group: Non-metallic minerals Motor vehicles and equipmen  1714; Commodity group: Motor vehicles and equipment Waste and scrap materia  701; Commodity group: Waste and scrap material Pulp, paper, and allied product  671; Commodity group: Pulp, paper, and allied products Metallic ore  674; Commodity group: Metallic ores Petroleum and cok  663; Commodity group: Petroleum and coke Metal and product  778; Commodity group: Metal and products Stone, clay, and glass product  570; Commodity group: Stone, clay, and glass products Lumber and wood product  548; Commodity group: Lumber and wood products Forwarder and shipper association traffi  276; Commodity group: Forwarder and shipper association traffic

Vega-Lite specification:
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Chart description: MIscellaneous mixed shipments is the largest commodity transported by Class 1 Rail with over 8,000,000 carloads. The next highest is Coal with approximately 7,500,000 carloads. The commodity with the fewest carloads is Forwarder and Shipper Associates.

Chart data: 2007 Commodity group 8465 Miscellaneous mixed shipments, primarily intermodal 7480 Coal 2588 All other carloads 2069 Chemicals 1681 Farm products 1493 Food and similar products 1398 Non-metallic minerals 1639 Motor vehicles and equipment 726 Waste and scrap material 652 Pulp, paper, and allied products 662 Metallic ores 671 Petroleum and coke 721 Metal and products 513 Stone, clay, and glass products 456 Lumber and wood products 246 Forwarder and shipper association traffic

Vega-Lite specification:
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Chart description: Coal and mixed shipment is transported the most whilst forwarder is the least transported.

Chart data: 2007 Commodity group 8465 Miscellaneous mixed shipments, primarily intermodal 7480 Coal 2588 All other carloads 2069 Chemicals 1681 Farm products 1493 Food and similar products 1398 Non-metallic minerals 1639 Motor vehicles and equipment 726 Waste and scrap material 652 Pulp, paper, and allied products 662 Metallic ores 671 Petroleum and coke 721 Metal and products 513 Stone, clay, and glass products 456 Lumber and wood products 246 Forwarder and shipper association traffic

Vega-Lite specification:
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Chart description: Coal and miscellaneous items were the most transported in 2009.

Chart data: Commodity group 2009 Miscellaneous mixed shipments, primarily intermoda  6897; Commodity group: Miscellaneous mixed shipments, primarily intermodal Coa  6842; Commodity group: Coal All other carload  2017; Commodity group: All other carloads Chemical  1909; Commodity group: Chemicals Farm product  1531; Commodity group: Farm products Food and similar product  1462; Commodity group: Food and similar products Non-metallic mineral  1054; Commodity group: Non-metallic minerals Motor vehicles and equipmen  912; Commodity group: Motor vehicles and equipment Waste and scrap materia  568; Commodity group: Waste and scrap material Pulp, paper, and allied product  546; Commodity group: Pulp, paper, and allied products Metallic ore  527; Commodity group: Metallic ores Petroleum and cok  479; Commodity group: Petroleum and coke Metal and product  416; Commodity group: Metal and products Stone, clay, and glass product  372; Commodity group: Stone, clay, and glass products Lumber and wood product  285; Commodity group: Lumber and wood products Forwarder and shipper association traffi  188; Commodity group: Forwarder and shipper association traffic

Vega-Lite specification:
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Chart description: The chart shows that from 2010, industry remained above 0.25.

Chart data: Year Industry Dec 31, 2008 0.2474 Dec 31, 2009 0.2685 Dec 31, 2010 0.2707 Dec 31, 2011 0.2728 Dec 31, 2012 0.2678 Dec 31, 2013 0.2701 Dec 31, 2014 0.2706 Dec 31, 2015 0.275 Dec 31, 2016 0.2744 Dec 31, 2017 0.2746 Dec 31, 2018 0.2682

Vega-Lite specification:
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Chart description: Participation increased as the years went on and then decreased.

Chart data: 11-15 years Response 0.564 2019/20 0.583 2018/19 0.604 2017/18 0.609 2016/17 0.703 2015/16 0.69 2014/15 0.736 2013/14 0.733 2012/13 0.774 2011/12 0.71 2010/11 0.709 2009/10 0.724 2008/09

Vega-Lite specification:
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Chart description: In Albania, between 2009 and 2019, there was a steady decline in the proportion of children aged 14 and under. The rate has decreased from around 0.28 in 2009 to around 0.175 in 2019.

Chart data: Year 0-14 years Dec 31, 2008 0.2316 Dec 31, 2009 0.2246 Dec 31, 2010 0.2147 Dec 31, 2011 0.206 Dec 31, 2012 0.1986 Dec 31, 2013 0.1922 Dec 31, 2014 0.1867 Dec 31, 2015 0.1838 Dec 31, 2016 0.1803 Dec 31, 2017 0.1767 Dec 31, 2018 0.174

Vega-Lite specification:
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Chart description: There has been a slight increase in age structure between 2009 and 2019. Although there has been a slight increase in age structure, the figures are very close to each other and it could be argued there has been little if any real change.

Chart data: Year 15-64 years Dec 31, 2008 0.6665 Dec 31, 2009 0.669 Dec 31, 2010 0.6751 Dec 31, 2011 0.6801 Dec 31, 2012 0.6837 Dec 31, 2013 0.686 Dec 31, 2014 0.687 Dec 31, 2015 0.6866 Dec 31, 2016 0.6864 Dec 31, 2017 0.6858 Dec 31, 2018 0.684

Vega-Lite specification:
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Chart description: Poland received the most immigrants from Poland that year at 10,000. This was followed by Germany (around 7,000) and the UK (just under 5,000).  All of the remaining countries received fewer than 2,000 people each.

Chart data: 2018 Country 10057 Ukraine 7133 Germany 4858 United Kingdom 1446 Netherlands 1262 Vietnam 1247 USA 981 Belarus 797 Italy 708 Austria 709 France 862 Ireland 800 China 680 Russia 638 Norway 477 Sweden 435 Belgium 472 Spain

Vega-Lite specification:
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Chart description: In 2018, emigration was at an average across most countries of less then 2000. A handful of countries had substantially higher , examples being Ukraine, UK and Germany. Ukraine was nearly 10k, UK 5k and Germany 7k. All of these countries are geographically located in Europe.

Chart data: 2018 Country 10057 Ukraine 7133 Germany 4858 United Kingdom 1446 Netherlands 1262 Vietnam 1247 USA 981 Belarus 797 Italy 708 Austria 709 France 862 Ireland 800 China 680 Russia 638 Norway 477 Sweden 435 Belgium 472 Spain

Vega-Lite specification:
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Chart description: In 2018 most people emigrating from Poland went to Ukraine, there were 10.000 people that emigrated from Poland to the Ukraine in this year. Spain Sweden and Belgium were the countries with the least amount of people emigrating from Poland with under 1000people durung theyear of 2018.

Chart data: 2018 Country 10057 Ukraine 7133 Germany 4858 United Kingdom 1446 Netherlands 1262 Vietnam 1247 USA 981 Belarus 797 Italy 708 Austria 709 France 862 Ireland 800 China 680 Russia 638 Norway 477 Sweden 435 Belgium 472 Spain

Vega-Lite specification:
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Chart description: This shows the increase in the 18 to 29 age group shows a big increase as the years moved forward.

Chart data: Year Generation aged 18-29 Dec 31, 1971 0.46 Dec 31, 1975 0.51 Dec 31, 1979 0.44 Dec 31, 1983 0.4 Dec 31, 1987 0.47 Dec 31, 1991 0.43 Dec 31, 1995 0.53 Dec 31, 1999 0.48 Dec 31, 2003 0.54 Dec 31, 2007 0.66 Dec 31, 2011 0.6

Vega-Lite specification:
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Chart description: The chart, which has its Y axis sorted by alphabetical order, shows that Spain is the country with the most cases, with almost 40. There are 3 countries with between 10 and 20 cases (Egypt, Greece and Turkey). There are 10 countries with 1 to 10 cases. There are 6 countries (Australia, Canada, Jamaica, Pakistan, Switzwerland and the USA) with 0 cases of sexual assault of British residents.

Chart data: Country 2012/2013 Spain 39 USA 0 Thailand 4 France 5 Greece 12 United Arab Emirates 5 Cyprus 7 Australia 0 India 3 Germany 1 Turkey 16 China 5 Philippines 2 Pakistan 0 Portugal 3 Egypt 20 Canada 0 Switzerland 0 Italy 5 Jamaica 0

Vega-Lite specification:
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Chart description: Wine consumption per capita has stayed at a similar amount from the years 2008 to 2019. However it can be observed that since peaking in 2012, it has been steadily decreasing year on year .

Chart data: Sparkling wine Year 3.4 2019* 3.4 2018 3.5 2017 3.7 2016 3.7 2015 3.9 2014 4 2013 4.2 2012 4.2 2011 3.9 2010 3.9 2009 3.9 2008

Vega-Lite specification:
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Chart description: Agricultural employment has fallen between 2010 and 2020. The sharpest fall was between 2010 and 2013. Employment recovered in 2014 but not back up to the 2010 level. From 2014 to 2020 there has been a steady decline in agricultural employment.

Chart data: Year Agriculture Dec 31, 2009 0.0091 Dec 31, 2010 0.0085 Dec 31, 2011 0.008 Dec 31, 2012 0.0073 Dec 31, 2013 0.0081 Dec 31, 2014 0.008 Dec 31, 2015 0.0078 Dec 31, 2016 0.0076 Dec 31, 2017 0.0074 Dec 31, 2018 0.0073 Dec 31, 2019 0.007

Vega-Lite specification:
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Chart description: The graph presents a slow and steady increase in the distribution of employment, with the number of services plotted in the linear scale increasing from a little below 0.8 in the year 2010 to a little above 0.8 in the year 2020.

Chart data: Year Services Dec 31, 2009 0.7752 Dec 31, 2010 0.7859 Dec 31, 2011 0.79 Dec 31, 2012 0.7976 Dec 31, 2013 0.8164 Dec 31, 2014 0.819 Dec 31, 2015 0.8233 Dec 31, 2016 0.8294 Dec 31, 2017 0.8345 Dec 31, 2018 0.838 Dec 31, 2019 0.8409

Vega-Lite specification:
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Chart description: There has been a steady increase in Distribution of employment by economic sector from 2010 to 2020 in Singapore.

Chart data: Year Services Dec 31, 2009 0.7752 Dec 31, 2010 0.7859 Dec 31, 2011 0.79 Dec 31, 2012 0.7976 Dec 31, 2013 0.8164 Dec 31, 2014 0.819 Dec 31, 2015 0.8233 Dec 31, 2016 0.8294 Dec 31, 2017 0.8345 Dec 31, 2018 0.838 Dec 31, 2019 0.8409

Vega-Lite specification:
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Chart description: The services increased slowly and steadily, but at a slightly higher rate between 2013 and 2014.

Chart data: Year Services Dec 31, 2009 0.7752 Dec 31, 2010 0.7859 Dec 31, 2011 0.79 Dec 31, 2012 0.7976 Dec 31, 2013 0.8164 Dec 31, 2014 0.819 Dec 31, 2015 0.8233 Dec 31, 2016 0.8294 Dec 31, 2017 0.8345 Dec 31, 2018 0.838 Dec 31, 2019 0.8409

Vega-Lite specification:
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Chart description: Coronovirus impacted construction works the most. The only one that went into negative was imports.  The graph shows that all indicators were impacted in some way by coronavirus .

Chart data: Nov '19 main macroeconomic indicators −0.054 Industrial production*** 0.02 Non-farming private sector* 0.027 Services* 0.029 Import** 0.031 Services rendered mainly to enterprises** 0.039 Export** 0.058 Wholesale trade** 0.066 Retail trade*** 0.091 Trade and repair of motor vehicles*** 0.104 Households' consumption* 0.144 Services provided to the population*** 0.272 Construction works***

Vega-Lite specification:
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Chart description: construction work was impacted the most. industrial production was impacted the least having a negative impact.

Chart data: Nov '19 main macroeconomic indicators −0.054 Industrial production*** 0.02 Non-farming private sector* 0.027 Services* 0.029 Import** 0.031 Services rendered mainly to enterprises** 0.039 Export** 0.058 Wholesale trade** 0.066 Retail trade*** 0.091 Trade and repair of motor vehicles*** 0.104 Households' consumption* 0.144 Services provided to the population*** 0.272 Construction works***

Vega-Lite specification:
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Chart description: Construction works was impacted the most by corona virus when over Jan '20. There was a main macroeconomic indicator that actually recovered by the beginning of Jan '20 being industrial production.

Chart data: Jan '20 main macroeconomic indicators −0.021 Industrial production*** 0.103 Non-farming private sector* 0.107 Services* 0.07 Import** 0.138 Services rendered mainly to enterprises** 0.046 Export** 0.131 Wholesale trade** 0.112 Retail trade*** 0.037 Trade and repair of motor vehicles*** 0.13 Households' consumption* 0.174 Services provided to the population*** 0.498 Construction works***

Vega-Lite specification:
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Chart description: The biggest impact of COVID 19 was on construction works. The least impact was on industrial production.

Chart data: main macroeconomic indicators Feb '20 Industrial production*** −0.024 Non-farming private sector* 0.089 Services* 0.124 Import** 0.047 Services rendered mainly to enterprises** 0.169 Export** 0.049 Wholesale trade** 0.129 Retail trade*** 0.138 Trade and repair of motor vehicles*** 0.034 Households' consumption* 0.107 Services provided to the population*** 0.098 Construction works*** 0.246

Vega-Lite specification:
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Chart description: Services to the population decreased the most.  The non farming private sector decreased the least.  Construction works increased the most.  Services rendered mainly to entertainment increased the least.

Chart data: Jul' 20 main macroeconomic indicators −0.065 Industrial production*** −0.029 Non-farming private sector* −0.036 Services* −0.13 Import** 0.008 Services rendered mainly to enterprises** −0.1 Export** 0.037 Wholesale trade** 0.051 Retail trade*** 0.009 Trade and repair of motor vehicles*** −0.086 Households' consumption* −0.244 Services provided to the population*** 0.134 Construction works***

Vega-Lite specification:
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Chart description: I find this graph hard to interpret. Covid-19 seemed to have the most impact on construction workers and the least impact on services provided to the population.

Chart data: Jul' 20 main macroeconomic indicators −0.065 Industrial production*** −0.029 Non-farming private sector* −0.036 Services* −0.13 Import** 0.008 Services rendered mainly to enterprises** −0.1 Export** 0.037 Wholesale trade** 0.051 Retail trade*** 0.009 Trade and repair of motor vehicles*** −0.086 Households' consumption* −0.244 Services provided to the population*** 0.134 Construction works***

Vega-Lite specification:
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Chart description: The highest survival rate for children in China was 0.8, this was for Carcinomas and melanoma. The lowest survival rate was around 0.4, and this was for central nervous system tumours. Renal cancers closely followed Carcinomas and Melanoma cancer with second highest survival rate.

Chart data: type of cancer Shanghai, China (2002-2005) All cancers 0.557 Leukaemias 0.522 Lymphomas 0.588 Central nervous system tumours 0.412 Retinoblastoma 0.75 Renal cancers 0.867 Malignant bone tumours 0.526 Soft tissue sacromas 0.541 Germ cell tumours 0.784 Carcinomas and melanoma** 0.889

Vega-Lite specification:
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