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dt_weights_raw = aq.loadCSV(url_weights)
Inputs.table(dt_weights_raw)
dt_weights_raw
.groupby('Sexo')
.count()
.view()
viewof weights1 = dt_weights_raw
.derive({altura_m:d=>d.Altura_Polegadas*.0254, peso_kg: d=>d.Peso_Libras/2.2})
.derive({imc: d=>d.peso_kg/(d.altura_m*d.altura_m)})
.view({height:240})
vl.markBoxplot({size:50})
.data(weights1)
.encode(
vl.y().fieldN('Sexo'),
vl.color().fieldN('Sexo'),
vl.x().fieldQ('altura_m').scale({zero:false})
)
.height(180)
.render()
vl.markCircle({size:2})
.data(weights1)
.encode(
vl.x().fieldQ("altura_m").scale({domain:[1.3,2.1]}),
vl.y().fieldQ("peso_kg").scale({domain:[20.,125]}),
vl.color().fieldN("Sexo")
)
.title("Peso vs Altura")
.width(500)
.render()
get_R2(weights1,'peso_kg','altura_m')
get_R2(weights1
.filter(d=>d.Sexo=="M"),'peso_kg','altura_m')
weights2_raw = aq.fromCSV(await FileAttachment('weights2.csv').text())
Inputs.table(weights2_raw)
five_nums(weights2_raw.columnArray('Age (yrs)'))
weights2_raw
.derive({age_months: d=>12*d['Age (yrs)']})
.select('Age (yrs)','age_months')
.view({height:240})
viewof weights2 = weights2_raw
.derive({faixa_de_idade:d=>(op.trunc(d['Age (yrs)']/10)*10+"-"+(op.trunc(1+d['Age (yrs)']/10)*10-1))},{before:1})
.view({height:240})
pearson_raw=aq.loadCSV(url_pearson)
vl.markPoint({filled:true,size:8})
.data(pearson_raw)
.encode(
vl.x().fieldQ('x'),
vl.y().fieldQ('x_quad')
).render()
viewof pearson_raw_ranked=pearson_raw
.orderby('x_quad')
.derive({x_quad_rank:op.row_number()})
.view({height:240})
vl.markPoint({filled:true,size:8})
.data(pearson_raw_ranked)
.encode(
vl.x().fieldQ('x'),
vl.y().fieldQ('x_quad_rank')
).render()
viewof pearson_folded=pearson_raw
.fold(aq.not('x'),{as:['série','valor']})
.view({height:240})
get_R2(pearson_raw,'x','x_lin')
get_R2(pearson_raw,'x','x_quad')
athletes_rio2016=aq.fromCSV(await FileAttachment("athletes.csv").text())
Inputs.table(athletes_rio2016.filter(d=>d.nationality=="BRA"))
anscombe_raw = aq.loadCSV(url_anscombe)
anscombe_raw
.view({height:240})
avg_stdev(anscombe_raw.columnArray('x1'))
avg_stdev(anscombe_raw.columnArray('x2'))
anscombe_raw.columnNames().map(d=>avg_stdev(anscombe_raw.columnArray(d)))
anscombe_raw.columnNames().map(d=>five_nums(anscombe_raw.columnArray(d)))
vl.markPoint()
.data(anscombe_raw)
.encode(
vl.x().fieldQ("x1"),
vl.y().fieldQ("y1")
)
.title("X1,Y1")
.width(500)
.render()
anscombe_raw
// selectiona e renomeia
.select({x1:'x',y1:'y'})
// .select(aq.endswith('1')).rename({x1:'x',y1:'y'})
.derive({set:1})
.view({height:240})
anscombe_concat = {
const t1 = anscombe_raw.select({x1:'x',y1:'y'}).derive({set:1});
const t2 = anscombe_raw.select({x2:'x',y2:'y'}).derive({set:2});
const t3 = anscombe_raw.select({x3:'x',y3:'y'}).derive({set:3});
const t4 = anscombe_raw.select({x4:'x',y4:'y'}).derive({set:4});
const t1234 = t1.concat([t2,t3,t4]) // concatena as 4 tabelas
.derive({sample:d=>op.row_number()},{before:0}) // adiciona contador de linhas
.relocate('set',{before:1}) // reposiciona coluna 'set' como 2a coluna
return t1234;
}
anscombe_concat.view({height:240})
vl.markCircle({size:50})
.data(anscombe_concat)
.encode(
vl.x().fieldQ("x"),
vl.y().fieldQ("y"),
vl.color().field('set')
)
.title("Quarteto de Anscombe")
.width(500)
.render()
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