delen/vistext huggingface dataset:
Chart description: As shown in the area chart above, there is no steady increase or decrease in the total expenditure on toddlers apparel. One year the expenditure will increase, but then the next it will decrease.

Chart data: Year Infants' and toddlers' apparel Dec 31, 2008 114.49 Dec 31, 2009 114.18 Dec 31, 2010 113.57 Dec 31, 2011 119.66 Dec 31, 2012 116.54 Dec 31, 2013 117.55 Dec 31, 2014 119.74 Dec 31, 2015 115.89 Dec 31, 2016 114.92 Dec 31, 2017 120.32

Vega-Lite specification:
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Chart description: Between 2009 and 2018 there is an upwards trend, but very gradual. It tends to rise and fall over the years with peaks in 2012, 2015 and 2018. The highest expenditure was seen in those 3 years, 12, 15 and 18 reaching 120. Between those years it dips to near 110 but never goes under that price.

Chart data: Year Infants' and toddlers' apparel Dec 31, 2008 114.49 Dec 31, 2009 114.18 Dec 31, 2010 113.57 Dec 31, 2011 119.66 Dec 31, 2012 116.54 Dec 31, 2013 117.55 Dec 31, 2014 119.74 Dec 31, 2015 115.89 Dec 31, 2016 114.92 Dec 31, 2017 120.32

Vega-Lite specification:
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Chart description: The price of men's and boys' apparel was lowest in 2010. The price of men's and boys' apparel has risen since 2010. The price of men's and boys' apparel was highest in 2013. The price of men's and boys' apparel was over 120 for two years.

Chart data: Year Men's and boys' apparel Dec 31, 2008 113.63 Dec 31, 2009 111.91 Dec 31, 2010 114.7 Dec 31, 2011 119.53 Dec 31, 2012 121.59 Dec 31, 2013 120.6 Dec 31, 2014 119.62 Dec 31, 2015 118.83 Dec 31, 2016 117.23 Dec 31, 2017 118.11

Vega-Lite specification:
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Chart description: There appears to be a fairly steady expenditure on women's and girl's apparel between 2010 and 2016 which has remained above 100 during that time. There was a increase to approximately 110 between 2012 to 2014 but them in dropped down again after 2014 to settle again mostly around the 100 region.

Chart data: Year Women's and girls' apparel Dec 31, 2008 108.09 Dec 31, 2009 107.08 Dec 31, 2010 109.17 Dec 31, 2011 112.99 Dec 31, 2012 113.34 Dec 31, 2013 114.36 Dec 31, 2014 111.21 Dec 31, 2015 111.24 Dec 31, 2016 111.02 Dec 31, 2017 110.44

Vega-Lite specification:
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Chart description: There is a slow decline from 2009 up until 2010 in women and girls apparel. From the year onwards  2010 there is a steady increase until the year 2015 where there is stagnation towards the year 2016 and onwards.

Chart data: Year Women's and girls' apparel Dec 31, 2008 108.09 Dec 31, 2009 107.08 Dec 31, 2010 109.17 Dec 31, 2011 112.99 Dec 31, 2012 113.34 Dec 31, 2013 114.36 Dec 31, 2014 111.21 Dec 31, 2015 111.24 Dec 31, 2016 111.02 Dec 31, 2017 110.44

Vega-Lite specification:
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Chart description: From 2009 to 2018 the expenditure figures are quite similar with only slight raises in 2012 and 2014.

Chart data: Year Women's and girls' apparel Dec 31, 2008 108.09 Dec 31, 2009 107.08 Dec 31, 2010 109.17 Dec 31, 2011 112.99 Dec 31, 2012 113.34 Dec 31, 2013 114.36 Dec 31, 2014 111.21 Dec 31, 2015 111.24 Dec 31, 2016 111.02 Dec 31, 2017 110.44

Vega-Lite specification:
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Chart description: The European union, North America and North East Asia have by far the largest contribution of travel and tourism to GDP compared to the other regions. North America has the highest while Central Asia has the lowest.

Chart data: geographic region 2016 North East Asi  1522.6; geographic region: North East Asia North Americ  1771.3; geographic region: North America European Unio  1682.9; geographic region: European Union Latin Americ  328.2; geographic region: Latin America South East Asi  301.1; geographic region: South East Asia Other Europ  278.5; geographic region: Other Europe South Asi  252.9; geographic region: South Asia Middle Eas  227.1; geographic region: Middle East Oceani  182.7; geographic region: Oceania Sub Saharan Afric  108; geographic region: Sub Saharan Africa North Afric  57.7; geographic region: North Africa Caribbea  56.4; geographic region: Caribbean Central Asi  10.8; geographic region: Central Asia

Vega-Lite specification:
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Chart description: This chart shows that South East Asian countries the largest impact on GDP.

Chart data: Country 1-year impact Hong Kong −0.0263 China −0.0105 Taiwan −0.0049 Singapore −0.0047 Malaysia −0.0015 Thailand −0.0015 Philippines −0.001 Korea −0.001 New Zealand −0.0008 Indonesia −0.0008 United States −0.0007 Japan −0.0007 Australia −0.0007 OPEC −0.0007 Eastern Europe −0.0006 India −0.0004

Vega-Lite specification:
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Chart description: Hong Kong and China are the countries which are most impacted by SARS between 2004 and 2013.

Chart data: Country 10-year impact Hong Kong −0.0321 China −0.0234 Taiwan −0.0053 Singapore −0.0051 Malaysia −0.0017 Thailand −0.0015 Philippines −0.0011 Korea −0.0008 New Zealand −0.0008 Indonesia −0.0007 United States −0.0007 Japan −0.0006 Australia −0.0006 OPEC −0.0009 Eastern Europe −0.0005 India −0.0004

Vega-Lite specification:
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Chart description: The most given reason is that it is easier and more convenient  followed closely by it's quicker to use a car.

Chart data: All reasons Response 0.58 It is easier/more convenient by car 0.34 It is quicker by car 0.11 Other 0.12 I prefer to walk/cycle 0.17 Buses are not frequent enough/do not run when I need them 0.1 Buses do not go to/go directly to places where I want to go 0.13 Bus fares are too high 0.12 Journeys take too long by bus 0.04 I have difficulty getting on and off buses 0.07 The nearest bus stop is too far away 0.1 It is cheaper by car 0.04 Not safe on the buses/stops/stations/anti-social behaviour 0.04 I have difficulty getting to the bus stop/station 0.06 I do not know what bus services are available 0.04 Buses are not reliable enough

Vega-Lite specification:
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Chart description: The number of high net worth individuals in North America has gradually increased between 2010 and 2019. There has always been more than three high net worth individuals in North America between 2010 and 2019. There are more than 6 high net worth individuals in North America in 2019. The number of high net worth individuals in North America has doubled between 2010 and 2019.

Chart data: Year North America Dec 31, 2009 3.39 Dec 31, 2010 3.35 Dec 31, 2011 3.73 Dec 31, 2012 4.33 Dec 31, 2013 4.68 Dec 31, 2014 4.78 Dec 31, 2015 5.15 Dec 31, 2016 5.66 Dec 31, 2017 5.68 Dec 31, 2018 6.3

Vega-Lite specification:
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Chart description: The overall trend in this area graph is an upwards trend, meaning the number of high net worth individuals by region is growing each year. The lowest year on the graph is 2010 with around 3 million high net worth individuals and the highest is 2018 with just over 5 million high net worth individuals.

Chart data: Year Europe Dec 31, 2009 3.13 Dec 31, 2010 3.17 Dec 31, 2011 3.41 Dec 31, 2012 3.83 Dec 31, 2013 3.99 Dec 31, 2014 4.18 Dec 31, 2015 4.5 Dec 31, 2016 4.83 Dec 31, 2017 4.8 Dec 31, 2018 5.22

Vega-Lite specification:
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Chart description: The number of high net worth individuals, in Europe, has increased steadily since  2010, from just above 3 million to just above 5 million. There was a minor dip around 2017.

Chart data: Year Europe Dec 31, 2009 3.13 Dec 31, 2010 3.17 Dec 31, 2011 3.41 Dec 31, 2012 3.83 Dec 31, 2013 3.99 Dec 31, 2014 4.18 Dec 31, 2015 4.5 Dec 31, 2016 4.83 Dec 31, 2017 4.8 Dec 31, 2018 5.22

Vega-Lite specification:
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Chart description: Agriculture GDP was flat or declining from 2009 to 2014. It had a substantial increase in 2014/15. It flattened out but still increased until 2017. There is a dip in 2017. After that it continued to rise again.

Chart data: Year Agriculture Dec 31, 2008 0.0148 Dec 31, 2009 0.0138 Dec 31, 2010 0.0126 Dec 31, 2011 0.0116 Dec 31, 2012 0.013 Dec 31, 2013 0.0127 Dec 31, 2014 0.0199 Dec 31, 2015 0.0228 Dec 31, 2016 0.0231 Dec 31, 2017 0.0221 Dec 31, 2018 0.0251

Vega-Lite specification:
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Chart description: There was an ongoing decline from 2009 to 2011. From 2011 there was sustained growth until 2016. There was a small decline from 2016 to 2018 but this has been followed by further growth until 2019. Overall level of GDP across sectors has increased from 0.4 in 2009 to over 0.5 in 2019.

Chart data: Year Services Dec 31, 2008 0.4111 Dec 31, 2009 0.2821 Dec 31, 2010 0.241 Dec 31, 2011 0.2576 Dec 31, 2012 0.2636 Dec 31, 2013 0.3885 Dec 31, 2014 0.4758 Dec 31, 2015 0.5105 Dec 31, 2016 0.4906 Dec 31, 2017 0.4704 Dec 31, 2018 0.5264

Vega-Lite specification:
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Chart description: In 2011 Munich Re suffered Signiant losses compared to their typical yearly loss, this repeated itself in 2017 but not the same extent as 2011.

Chart data: Year Major losses (net) Dec 31, 2007 1507 Dec 31, 2008 1157 Dec 31, 2009 2228 Dec 31, 2010 5048 Dec 31, 2011 1799 Dec 31, 2012 1689 Dec 31, 2013 1162 Dec 31, 2014 1046 Dec 31, 2015 1542 Dec 31, 2016 4314 Dec 31, 2017 2152 Dec 31, 2018 3124

Vega-Lite specification:
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Chart description: The graph shows Norway is dramatically ahead of other countries with the most Winter Olympic Games all-time medals. Next is United States, but the rest of the countries are all on a similar number of medals.

Chart data: Country Gold Norway 132 United States 105 Germany 92 Soviet Union 78 Canada 73 Austria 64 Sweden 57 Switzerland 56 Russia 47 The Netherlands 45

Vega-Lite specification:
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Chart description: Norway has he highest medal count with 140 medals earned between 1924 and 2018, followed by the USA with 105 in the same time period. Of the countries listed, Russia has the fewest medals with 48.

Chart data: Country Gold Norway 132 United States 105 Germany 92 Soviet Union 78 Canada 73 Austria 64 Sweden 57 Switzerland 56 Russia 47 The Netherlands 45

Vega-Lite specification:
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Chart description: The United States is the leading country based on natural gas production in 2014, with values of over 700 billion cubic metres. Whereas on this graph, Australia is seen to produce the least amount of natural gas in 2014, at less than 100 billion cubic metres.

Chart data: 2014 Country 729.1 United States 610.1 Russia 172.6 Iran 160 Qatar 132.8 China 161.3 Canada 55.3 Australia 108.8 Norway 108.2 Saudi Arabia 79.7 Algeria

Vega-Lite specification:
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Chart description: Discounting 06/07, the annual growth of profit for the Otto Group has overall increased until 19/20. The years 07/08, 08/09, and 09/10 show profits at an unusually low level compared to the other results.

Chart data: Business year Revenue 19/20 14263 18/19 13446 17/18 13653 16/17 12512 15/16 12104 14/15 12057 13/14 12001 12/13 11784 11/12 11597 10/11 11404 09/10 10132 08/09 9993 07/08 10058 06/07 11243

Vega-Lite specification:
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Chart description: The revenue and profit was highest in the years 2019/2020 and lowest in the years 2009/2009.

Chart data: Business year Revenue 19/20 14263 18/19 13446 17/18 13653 16/17 12512 15/16 12104 14/15 12057 13/14 12001 12/13 11784 11/12 11597 10/11 11404 09/10 10132 08/09 9993 07/08 10058 06/07 11243

Vega-Lite specification:
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Chart description: Other than a brief period from 07-09 the profits generally rose every year.

Chart data: Business year Revenue 19/20 14263 18/19 13446 17/18 13653 16/17 12512 15/16 12104 14/15 12057 13/14 12001 12/13 11784 11/12 11597 10/11 11404 09/10 10132 08/09 9993 07/08 10058 06/07 11243

Vega-Lite specification:
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Chart description: Otto Group's revenue has been gradually increasing from 11 billion euros in 2006/07 to the highest amount of 14,500 billion in the year 2019 to 2020. There was a slight dipping in revenue  in the period of 2008/2008 to 2009/10 before revenue recovered and continued a gradual upward trend.

Chart data: Business year Revenue 19/20 14263 18/19 13446 17/18 13653 16/17 12512 15/16 12104 14/15 12057 13/14 12001 12/13 11784 11/12 11597 10/11 11404 09/10 10132 08/09 9993 07/08 10058 06/07 11243

Vega-Lite specification:
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Chart description: From 2008 to 2009 production increased to above 150,000 for the first time. Since then, production has steadily decreased every year, with the production in 2018 being the lowest shown, getting closed to 100,000.

Chart data: Packaging paper and board Graphic paper 193501 151489 190208 136385 204469 142866 209982 142047 213955 138756 219455 134600 225624 131078 231022 125501 235544 122624 245782 119678 256138 115571

Vega-Lite specification:
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Chart description: From 2008 onwards, there is a linear progression in the volume of paper produced per year. However, 2018 sees a decline and has an equivalent level of production to 2013. 2017 saw the most amount of paper produced globally.

Chart data: Packaging paper and board Others 193501 45922 190208 44094 204469 46564 209982 46946 213955 47275 219455 48550 225624 49789 231022 51072 235544 52715 245782 54227 256138 48011

Vega-Lite specification:
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Chart description: As time progressed, the volume of paper production decreased from approximately 150 000 in 2008 to approximately 120 000 in 2016 with the fastest rate of decline between 2008 and 2009.

Chart data: Year Graphic paper Dec 31, 2007 151489 Dec 31, 2008 136385 Dec 31, 2009 142866 Dec 31, 2010 142047 Dec 31, 2011 138756 Dec 31, 2012 134600 Dec 31, 2013 131078 Dec 31, 2014 125501 Dec 31, 2015 122624 Dec 31, 2016 119678 Dec 31, 2017 115571

Vega-Lite specification:
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Chart description: Population of 0-14 year olds in China increased slightly between 1990 and 1995, from approximately 320 million to 325 million, before steadily decreasing until 2010 when the population of 0-14 year olds hit roughly 225 million. Since then, population has started to slowly increase again.

Chart data: Year 0-14 years Dec 31, 1989 316.59 Dec 31, 1994 322.18 Dec 31, 1999 290.12 Dec 31, 2004 265.04 Dec 31, 2009 222.59 Dec 31, 2010 221.64 Dec 31, 2011 222.87 Dec 31, 2012 223.29 Dec 31, 2013 225.58 Dec 31, 2014 227.15 Dec 31, 2015 230.08 Dec 31, 2016 233.48 Dec 31, 2017 235.23 Dec 31, 2018 234.92

Vega-Lite specification:
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Chart description: the population of china steadily decreased from 1995 until 2010 then it started to steadily rise.

Chart data: Year 0-14 years Dec 31, 1989 316.59 Dec 31, 1994 322.18 Dec 31, 1999 290.12 Dec 31, 2004 265.04 Dec 31, 2009 222.59 Dec 31, 2010 221.64 Dec 31, 2011 222.87 Dec 31, 2012 223.29 Dec 31, 2013 225.58 Dec 31, 2014 227.15 Dec 31, 2015 230.08 Dec 31, 2016 233.48 Dec 31, 2017 235.23 Dec 31, 2018 234.92

Vega-Lite specification:
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