delen/vistext huggingface dataset:
Chart description: The distribution of gross domestic product rose slightly, then took a sharp drop and has gradually decreased since.

Chart data: Year Industry Dec 31, 2008 0.2708 Dec 31, 2009 0.2705 Dec 31, 2010 0.2749 Dec 31, 2011 0.2768 Dec 31, 2012 0.2295 Dec 31, 2013 0.2319 Dec 31, 2014 0.2274 Dec 31, 2015 0.2261 Dec 31, 2016 0.219 Dec 31, 2017 0.2148 Dec 31, 2018 0.2192

Vega-Lite specification:
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Chart description: The GDP has overall been a on a slow, steady rise. The most significant growth has been between years 2012 and 2013. Since 2018, there has been a small downwards trend.

Chart data: Year Services Dec 31, 2008 0.5799 Dec 31, 2009 0.5852 Dec 31, 2010 0.5801 Dec 31, 2011 0.5859 Dec 31, 2012 0.6084 Dec 31, 2013 0.609 Dec 31, 2014 0.6145 Dec 31, 2015 0.6189 Dec 31, 2016 0.6249 Dec 31, 2017 0.6298 Dec 31, 2018 0.6266

Vega-Lite specification:
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Chart description: Apart from a slight dip between 2010 and 2011, there has been constant growth in the distribution of GDP in Guatemala.

Chart data: Year Services Dec 31, 2008 0.5799 Dec 31, 2009 0.5852 Dec 31, 2010 0.5801 Dec 31, 2011 0.5859 Dec 31, 2012 0.6084 Dec 31, 2013 0.609 Dec 31, 2014 0.6145 Dec 31, 2015 0.6189 Dec 31, 2016 0.6249 Dec 31, 2017 0.6298 Dec 31, 2018 0.6266

Vega-Lite specification:
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Chart description: Unable to understand what the chart is stating, difficult to read and understand the data.

Chart data: Contract Prepaid 17.6 4.2 18.2 4.2 18.2 4.2 18.5 4.5 18.5 4.2 18.6 3.9 19.1 4.2 19.8 3.9 19 3.8 23.7 3.4 24.5 3.6 24.9 3.5 24.5 3.3 24.7 3.2 25.1 3.4 25.3 3.6 25 3.5 24.9 3.5 25.4 3.4 25.7 3.5 25.9 3.4 26 3.2 27.1 3.2 27.7 3.4 27.7 3.3 27.6 3.3 28.2 3.6 28.7 3.8 28.6 3.8 28.8 3.6 29.4 3.7 29.9 3.7 29.9 3.5 29.7 3.3 30.1 3.5 30.2 3.7

Vega-Lite specification:
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Chart description: Following the pandemic in 1918 hourly wages in the planing mills rose sharply. The wages more than doubled in less than two years to 1920. In the early 1920s the hourly rates continued to increase but not as sharply.

Chart data: Year Planing mills Dec 31, 1899 0.31 Dec 31, 1900 0.32 Dec 31, 1901 0.33 Dec 31, 1902 0.35 Dec 31, 1903 0.35 Dec 31, 1904 0.35 Dec 31, 1905 0.36 Dec 31, 1906 0.38 Dec 31, 1907 0.37 Dec 31, 1908 0.37 Dec 31, 1909 0.38 Dec 31, 1910 0.39 Dec 31, 1911 0.39 Dec 31, 1912 0.4 Dec 31, 1913 0.4 Dec 31, 1914 0.41 Dec 31, 1915 0.43 Dec 31, 1916 0.46 Dec 31, 1917 0.51 Dec 31, 1918 0.6 Dec 31, 1919 0.88 Dec 31, 1920 0.95 Dec 31, 1921 0.88 Dec 31, 1922 0.94 Dec 31, 1923 1.03 Dec 31, 1924 1.03 Dec 31, 1925 1.03 Dec 31, 1926 0 Dec 31, 1927 0

Vega-Lite specification:
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Chart description: There was generally a slight year on year increase in hourly wages in planing mills from 1900 to 1918. There was a steep increase of hourly wages in planing mills in 1918 until 1920. This increase continued from 1920 until 1921, but at a slightly slower rate. There was a steep drop from 1921 to 1922. There then followed an increase again until around 1923. The hour wages in planing mills then stayed stable until 1926.

Chart data: Year Planing mills Dec 31, 1899 0.31 Dec 31, 1900 0.32 Dec 31, 1901 0.33 Dec 31, 1902 0.35 Dec 31, 1903 0.35 Dec 31, 1904 0.35 Dec 31, 1905 0.36 Dec 31, 1906 0.38 Dec 31, 1907 0.37 Dec 31, 1908 0.37 Dec 31, 1909 0.38 Dec 31, 1910 0.39 Dec 31, 1911 0.39 Dec 31, 1912 0.4 Dec 31, 1913 0.4 Dec 31, 1914 0.41 Dec 31, 1915 0.43 Dec 31, 1916 0.46 Dec 31, 1917 0.51 Dec 31, 1918 0.6 Dec 31, 1919 0.88 Dec 31, 1920 0.95 Dec 31, 1921 0.88 Dec 31, 1922 0.94 Dec 31, 1923 1.03 Dec 31, 1924 1.03 Dec 31, 1925 1.03 Dec 31, 1926 0 Dec 31, 1927 0

Vega-Lite specification:
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Chart description: In 2004, the majority of the import was from non-EU. In 2013, all of the import was from the EU. From 2005 to 2013, the amount of EU imports increased. From 2013 to 2016, the amount of EU import decreased, then jumped back up in 2017 again.

Chart data: Year EU Dec 31, 2003 72765878 Dec 31, 2004 120258396 Dec 31, 2005 117828546 Dec 31, 2006 120580088 Dec 31, 2007 137997208 Dec 31, 2008 137997989 Dec 31, 2009 189917989 Dec 31, 2010 207049721 Dec 31, 2011 261237315 Dec 31, 2012 276620942 Dec 31, 2013 246236433 Dec 31, 2014 216258333 Dec 31, 2015 156712566 Dec 31, 2016 227857317 Dec 31, 2017 184251204

Vega-Lite specification:
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Chart description: All months throughout the year average a retail price higher than 3; December had the lowest average retail price whereas February and March have the highest.

Chart data: Month 2016 De  3.31; Month: Dec No  3.34; Month: Nov Oc  3.42; Month: Oct Se  3.42; Month: Sep Au  3.56; Month: Aug Ju  3.56; Month: Jul Ju  3.44; Month: Jun Ma  3.52; Month: May Ap  3.6; Month: Apr Ma  3.68; Month: Mar Fe  3.7; Month: Feb Ja  3.67; Month: Jan

Vega-Lite specification:
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Chart description: The name of the graph does not match the graph, this graph only shows details from 2016, overall the price has remained consistent during 2016; between 3 and 4 dollars.

Chart data: Month 2016 De  3.31; Month: Dec No  3.34; Month: Nov Oc  3.42; Month: Oct Se  3.42; Month: Sep Au  3.56; Month: Aug Ju  3.56; Month: Jul Ju  3.44; Month: Jun Ma  3.52; Month: May Ap  3.6; Month: Apr Ma  3.68; Month: Mar Fe  3.7; Month: Feb Ja  3.67; Month: Jan

Vega-Lite specification:
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Chart description: The months on the bar chart aren't in order they are all scattered so makes it harder to observe a trend in certain months. But looking at the months it looks as if peanut butter gets cheaper as the year goes on then peaks at the beginning of the year.

Chart data: Month 2017 De  3.25; Month: Dec No  3.17; Month: Nov Oc  3.2; Month: Oct Se  3.21; Month: Sep Au  3.35; Month: Aug Ju  3.29; Month: Jul Ju  3.25; Month: Jun Ma  3.28; Month: May Ap  3.37; Month: Apr Ma  3.43; Month: Mar Fe  3.47; Month: Feb Ja  3.36; Month: Jan

Vega-Lite specification:
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Chart description: The price stayed quite consistent for all of 2017, with the exception of a small hike in February. Overall the price slowly decreases.

Chart data: Month 2017 De  3.25; Month: Dec No  3.17; Month: Nov Oc  3.2; Month: Oct Se  3.21; Month: Sep Au  3.35; Month: Aug Ju  3.29; Month: Jul Ju  3.25; Month: Jun Ma  3.28; Month: May Ap  3.37; Month: Apr Ma  3.43; Month: Mar Fe  3.47; Month: Feb Ja  3.36; Month: Jan

Vega-Lite specification:
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Chart description: The year 2016-2017 had the biggest increase in distribution of employment. 2018 had the highest distribution of employment.  The years 2014-201 had the lowest distribution of employment.

Chart data: Year Industry Dec 31, 2009 0.256 Dec 31, 2010 0.268 Dec 31, 2011 0.2646 Dec 31, 2012 0.2586 Dec 31, 2013 0.2466 Dec 31, 2014 0.2446 Dec 31, 2015 0.2443 Dec 31, 2016 0.253 Dec 31, 2017 0.269 Dec 31, 2018 0.2714 Dec 31, 2019 0.2735

Vega-Lite specification:
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Chart description: The line appears to increase over time steadily.  There is a very slight reduction in 2017, but this does not affect the overall trajectory over the period shown.  There is one year, 2013, with sudden increase, but the remainder of the years all show similar gradients otherwise.

Chart data: Year Services Dec 31, 2009 0.5206 Dec 31, 2010 0.5198 Dec 31, 2011 0.5258 Dec 31, 2012 0.5285 Dec 31, 2013 0.5548 Dec 31, 2014 0.5613 Dec 31, 2015 0.5696 Dec 31, 2016 0.5748 Dec 31, 2017 0.5717 Dec 31, 2018 0.574 Dec 31, 2019 0.5758

Vega-Lite specification:
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Chart description: Distribution has stayed quite high on the chart throughout the years depicted. 2010 came in just above 0.5 with very little change until 2013. From 2013 to 2017 there was an uptrend bringing services up to 0.58 steadily in those four years. From 2017 to 2020 services have stayed relatively flat at 0.58. 2013 was the year that saw the most growth out of the years depicted.

Chart data: Year Services Dec 31, 2009 0.5206 Dec 31, 2010 0.5198 Dec 31, 2011 0.5258 Dec 31, 2012 0.5285 Dec 31, 2013 0.5548 Dec 31, 2014 0.5613 Dec 31, 2015 0.5696 Dec 31, 2016 0.5748 Dec 31, 2017 0.5717 Dec 31, 2018 0.574 Dec 31, 2019 0.5758

Vega-Lite specification:
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Chart description: Services have increased marginally from 2010 to 2018.

Chart data: Year Services Dec 31, 2009 0.5206 Dec 31, 2010 0.5198 Dec 31, 2011 0.5258 Dec 31, 2012 0.5285 Dec 31, 2013 0.5548 Dec 31, 2014 0.5613 Dec 31, 2015 0.5696 Dec 31, 2016 0.5748 Dec 31, 2017 0.5717 Dec 31, 2018 0.574 Dec 31, 2019 0.5758

Vega-Lite specification:
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Chart description: The servicesincreased by leass than 0.1 percent over the given time.

Chart data: Year Services Dec 31, 2009 0.5206 Dec 31, 2010 0.5198 Dec 31, 2011 0.5258 Dec 31, 2012 0.5285 Dec 31, 2013 0.5548 Dec 31, 2014 0.5613 Dec 31, 2015 0.5696 Dec 31, 2016 0.5748 Dec 31, 2017 0.5717 Dec 31, 2018 0.574 Dec 31, 2019 0.5758

Vega-Lite specification:
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Chart description: Both breeds have a very similar life expectancy. The overall trend is for life expectancy to increase, however, the increase is only slight. There was a small decrease in life expectancy between 2014 and 2016.

Chart data: Year Newfoundland and Labrador 2016-2018 79.8 2015-2017 79.6 2014-2016 79.4 2013-2015 79.3 2012-2014 79.4 2011-2013 79.6 2010-2012 79.6 2009-2011 79.6 2008-2010 79.3 2007-2009 79 2006-2008 78.5 2005-2007 78.2

Vega-Lite specification:
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Chart description: The linear scale shows an increase from 2015 to 2022 in makeup purchases from ester Lauder.

Chart data: Year Makeup Dec 31, 2012 0.1382 Dec 31, 2013 0.1421 Dec 31, 2014 0.1287 Dec 31, 2015 0.1437 Dec 31, 2016 0.1637 Dec 31, 2017 0.1737 Dec 31, 2018 0.1887 Dec 31, 2019 0.2037 Dec 31, 2020 0.2137 Dec 31, 2021 0.2237 Dec 31, 2022 0.2337 Dec 31, 2023 0.2437

Vega-Lite specification:
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Chart description: 17 3q and 17 4q had the most mobile shipments . 15 1q had the least mobile shipments.

Chart data: quarter ZTE 1Q '18 0.11 4Q '17 0.11 3Q '17 0.12 2Q '17 0.12 1Q '17 0.11 4Q '16 0.113 3Q '16 0.095 2Q '16 0.11 1Q '16 0.09 4Q '15 0.08 1Q '15 0.06

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/2226.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#B0B0B0"}, "x": {"type": "nominal", "axis": {"labelAngle": -30}, "bin": false, "field": "quarter"}, "y": {"type": "quantitative", "axis": {"title": "ZTE"}, "field": "ZTE"}}, "title": ["Mobile phone shipments ' share in North", "America by vendor from 1Q'15 to 1Q'18"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: Mobile phone shipments share in North America by vendor do not appear to have a consistent pattern that I can see although I am finding the graph difficult to understand.

Chart data: quarter ZTE 1Q '18 0.11 4Q '17 0.11 3Q '17 0.12 2Q '17 0.12 1Q '17 0.11 4Q '16 0.113 3Q '16 0.095 2Q '16 0.11 1Q '16 0.09 4Q '15 0.08 1Q '15 0.06

Vega-Lite specification:
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Chart description: The overall expenses decrease after 2005. Decreases in expenses are generally followed by minor increases before decreasing again.

Chart data: Year Gas turbine and small scale** Dec 31, 1997 30.79 Dec 31, 1998 37.74 Dec 31, 1999 48.94 Dec 31, 2004 61.1 Dec 31, 2009 48.74 Dec 31, 2010 44.54 Dec 31, 2011 35.67 Dec 31, 2012 37.92 Dec 31, 2013 42.6 Dec 31, 2014 33.24 Dec 31, 2015 30.19 Dec 31, 2016 31.76 Dec 31, 2017 32.43 Dec 31, 2018 28.33

Vega-Lite specification:
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Chart description: The most prevalent type of property stolen and recovered in USA was locally stolen motor vehicles Livestock was the lowest  of  all types and values  of stolen and recovered property.

Chart data: Type of property Stolen Currency, notes, etc. 1423.56 Jewelry and precious metals 1057.76 Clothing and furs 383.19 Locally stolen motor vehicles 5752.24 Office equipment 420.42 Televisions, radios, stereos, etc. 323.39 Firearms 116.16 Household goods 186.26 Consumable goods 160.37 Livestock 14.35 Miscellaneous 3502.1

Vega-Lite specification:
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Chart description: There are 11 categories of Types of property. The majority show nothing recovered. However by far the most recovered is locally stolen motor vehicles at c. $3250000. The second most falls under the category of Miscellaneous.

Chart data: Recovered Type of property 36.98 Currency, notes, etc. 36.89 Jewelry and precious metals 31.17 Clothing and furs 3228.87 Locally stolen motor vehicles 23.24 Office equipment 14.01 Televisions, radios, stereos, etc. 13.5 Firearms 8.18 Household goods 13.38 Consumable goods 1.57 Livestock 453.4 Miscellaneous

Vega-Lite specification:
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Chart description: Overtime, opinions on whether there should be a death penalty fluctuate. A great deal more fluctuation has taken place since the late 200s. More people are not in favour at the beginning of the graph, the 1970s and present day. In contrast, less people are not in favour in the late 1950s, and the 1990s.

Chart data: Response Not in favor Dec 31, 1935 0.38 Dec 31, 1952 0.25 Dec 31, 1959 0.36 Dec 31, 1970 0.4 Dec 31, 1980 0.25 Dec 31, 1990 0.18 Dec 31, 1999 0.28 Dec 31, 2004 0.3 Dec 31, 2005 0.28 Dec 31, 2006 0.27 Dec 31, 2007 0.3 Dec 31, 2008 0.31 Dec 31, 2009 0.29 Dec 31, 2010 0.35 Dec 31, 2011 0.32 Dec 31, 2012 0.35 Dec 31, 2013 0.33 Dec 31, 2014 0.37 Dec 31, 2015 0.37 Dec 31, 2016 0.41 Dec 31, 2017 0.41 Dec 31, 2018 0.42 Dec 31, 2019 0.43

Vega-Lite specification:
{"config": {"background": "#fff", "area": {"fill": "#3e5c69"}, "line": {"stroke": "#3e5c69"}, "rect": {"fill": "#3e5c69"}, "bar": {"fill": "#3e5c69"}, "point": {"color": "#3e5c69"}, "axis": {"domainWidth": 0.5, "grid": true, "labelPadding": 2, "tickSize": 5, "tickWidth": 0.5, "titleFontWeight": "normal"}, "axisBand": {"grid": false}, "axisX": {"gridWidth": 0.2}, "axisY": {"gridDash": [3], "gridWidth": 0.4}, "legend": {"labelFontSize": 11, "padding": 1, "symbolType": "square"}, "range": {"category": ["#3e5c69", "#6793a6", "#182429", "#0570b0", "#3690c0", "#74a9cf", "#a6bddb", "#e2ddf2"]}}, "data": {"url": "multiColumn/data/2239.tsv"}, "mark": "area", "encoding": {"color": {"value": "#3e5c69"}, "x": {"type": "temporal", "axis": {"labelAngle": 30}, "bin": false, "field": "Response"}, "y": {"type": "quantitative", "axis": {"title": "Not in favor"}, "field": "Not in favor"}}, "title": ["Are you in favor of the death penalty for", "a person convicted of murder ?"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: United States had the highest percentage of over 65s with a select number of health conditions whereas New Zealand had the lowest. United States is the highest by a large portion.

Chart data: 3 or more Country 0.19 New Zealand 0.2 Netherlands 0.2 Norway 0.24 Switzerland 0.24 France 0.27 Australia 0.29 Germany 0.3 Sweden 0.3 United Kingdom 0.33 Canada 0.44 United States

Vega-Lite specification:
{"config": {"background": "#f9f9f9", "area": {"fill": "#ab5787"}, "line": {"stroke": "#ab5787"}, "rect": {"fill": "#ab5787"}, "bar": {"fill": "#ab5787"}, "point": {"fill": "#ab5787", "size": 30}, "axis": {"domainColor": "#979797", "domainWidth": 0.5, "gridWidth": 0.2, "labelColor": "#979797", "tickColor": "#979797", "tickWidth": 0.2, "titleColor": "#979797"}, "axisBand": {"grid": false}, "axisX": {"grid": true, "tickSize": 10}, "axisY": {"domain": false, "grid": true, "tickSize": 0}, "legend": {"labelFontSize": 11, "padding": 1, "symbolSize": 30, "symbolType": "square"}, "range": {"category": ["#ab5787", "#51b2e5", "#703c5c", "#168dd9", "#d190b6", "#00609f", "#d365ba", "#154866", "#666666", "#c4c4c4"]}}, "data": {"url": "multiColumn/data/2244.tsv"}, "mark": "bar", "encoding": {"color": {"value": "#d365ba"}, "x": {"type": "quantitative", "axis": {"labelAngle": 30, "title": "3 or more"}, "field": "3 or more"}, "y": {"type": "nominal", "axis": {}, "bin": false, "field": "Country"}}, "title": ["Percentage of seniors aged 65 years and", "older that had a select number of chronic", "conditions as of 2017 , by country"], "$schema": "https://vega.github.io/schema/vega-lite/v4.8.1.json"}
Chart description: United States had the most chronic conditions followed by CanadaNew Zealand had the least chronic conditions.

Chart data: 3 or more Country 0.19 New Zealand 0.2 Netherlands 0.2 Norway 0.24 Switzerland 0.24 France 0.27 Australia 0.29 Germany 0.3 Sweden 0.3 United Kingdom 0.33 Canada 0.44 United States

Vega-Lite specification:
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Chart description: Shows which films are most popular worldwide than others.

Chart data: the X-Men movie series Worldwide Deadpool 783.1 Deadpool 2 734.2 X-Men: The Last Stand 459.4 X-Men: Days of Future Past 747.9 Logan 616.8 X2: X-Men United 407.7 X-Men Origins: Wolverine 373.1 X-Men 296.3 X-Men: Apocalypse 543.9 X-Men: First Class 353.6 The Wolverine 414.8 Dark Phoenix 252.4 The New Mutants 44.61

Vega-Lite specification:
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Chart description: In 2019, unemployment rates in Italy for women were highest in the regions of Sicily, Campania and Calabria. The region with the lowest rate of unemployment for women was Trentino-South Tyrol with a rate of less than 0.05, the only region in Italy below this rate at that time.

Chart data: Women region of Italy 0.228 Campania 0.225 Sicily 0.224 Calabria 0.176 Apulia 0.151 Sardinia 0.147 Molise 0.135 Abruzzo 0.129 Basilicata 0.123 Liguria 0.107 Marche 0.104 Lazio 0.1 Umbria 0.092 Piedmont 0.079 Friuli-Venezia Giulia 0.077 Tuscany 0.074 Veneto 0.072 Aosta Valley 0.068 Lombardy 0.066 Emilia-Romagna 0.047 Trentino-South Tyrol

Vega-Lite specification:
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