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company <head> Company_ID,Rank,Company,Headquarters,Main_Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value <type> quantitative,quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,1,ExxonMobil,USA,Oil and gas,433.5,41.1,331.1,407.4 <line> 2,3,General Electri...
x=Rank,y=Market_Value,color=none
company <head> Company_ID,Rank,Company,Headquarters,Main_Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value <type> quantitative,quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,1,ExxonMobil,USA,Oil and gas,433.5,41.1,331.1,407.4 <line> 2,3,General Electri...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
count Industry
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
arc
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
x=Industry,y=count Industry,color=none
Companies <head> id,name,Headquarters,Industry,Sales_billion,Profits_billion,Assets_billion,Market_Value_billion <type> quantitative,nominal,nominal,nominal,quantitative,quantitative,quantitative,quantitative <data> 1,JPMorgan Chase,USA,Banking,115.5,17.4,2117.6,182.2 <line> 2,HSBC,UK,Banking,103.3,13.3,2467.9,186.5 <l...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
Citizenship,Net_Worth_Millions
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
max Net_Worth_Millions
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
x=Citizenship,y=max Net_Worth_Millions,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> I want to see which countries have the richest singers, can you visualize...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
Citizenship,Net_Worth_Millions
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
max Net_Worth_Millions
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
x=Citizenship,y=max Net_Worth_Millions,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show different citizenships and the maximum net worth of singers of each ...
x asc
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Can you show me a graph of singer citizenships? <ans> <sep> Step 1. Sele...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Visual representation of the singer's countries of origin. <ans> <sep> S...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> How many singers are from each country? <ans> <sep> Step 1. Select the c...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns:
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns: Ci...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns: Ci...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns: Ci...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns: Ci...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Singer citizenship breakdown. <ans> <sep> Step 1. Select the columns: Ci...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns:
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns: C...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns: C...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns: C...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns: C...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Chart of singer nationalities. <ans> <sep> Step 1. Select the columns: C...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
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singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me singers by country in a graph. <ans> <sep> Step 1. Select the co...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show me the total number by citizenship in a histogram, could you list by...
y asc
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
count Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
bar
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
x=Citizenship,y=count Citizenship,color=none
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> Show the different citizenship of singers and the number of singers of ea...
y asc
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> For each citizenship, how many singers are from that country, and display...
Citizenship
singer <head> Singer_ID,Name,Birth_Year,Net_Worth_Millions,Citizenship <type> quantitative,nominal,temporal,quantitative,nominal <data> 1,Liliane Bettencourt,1944.0,30.0,France <line> 2,Christy Walton,1948.0,28.8,United States <line> <utterance> For each citizenship, how many singers are from that country, and display...
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