aq = require("arquero")
import { Wrangler, op } from "@observablehq/data-wrangler"
timeSeries_values=aq.from(timeSeries)
.select('0','1','2','3','4','5','6','7','8','9','10','artist_song','-13','-12','-11','-10','-9','-8','-7','-6','-5','-4','-3','-2','-1')
.objects() // Uncomment to return an array of objects
Inputs.table(timeSeries_values)
// To use copied code replace "data" with your own variable
timeSeries_values_year=aq.from(timeSeries_values)
.join(aq.from(songRelease), ["artist_song", "artist_song"])
.objects() // Uncomment to return an array of objects
Inputs.table(timeSeries_values_year)
// To use copied code replace "data" with your own variable
noDiggity=aq.from(timeSeries_values_year)
.filter(d => op.match(d["artist_song"], "BLACKstreet"))
.objects() // Uncomment to return an array of objects
Inputs.table(noDiggity)
noDiggity_values=aq.from(noDiggity)
.select('0','1','2','3','4','5','6','7','8','9','10','-13','-12','-11','-10','-9','-8','-7','-6','-5','-4','-3','-2','-1')
.objects()
function round(data){
var x=[];
for(var i=-13;i<11;i++)
{
var y=_math.floor(data[0][i]*100);
var z= noDiggity[0].year;
var birthYear=z+i;
var j=Math.abs(i);
x.push({birth_year:birthYear,remember:y,age:j});
}
return(x);
}
noDiggity_values_round=round(noDiggity_values)
vegaEmbed = require("vega-embed")
Inputs.table(timeSeries_values_year)
Converting all data to column format by enclosing the function in a while loop
function columnTable(data){
var x=[];
var i=0;
while(i<342){
for(var j=-13; j<11 ;j++)
{
var y=_math.floor(data[i][j]*100);
var z= data[i].year;
var birthYear=z+j;
var m= data[i].artist_song;
x.push({birth_year:birthYear,remember:y,artist_song:m, age:j});
}
i++;
}
return(x);
}
columnData=columnTable(timeSeries_values_year)
remGrt_90= aq.from(columnData)
.join_right(aq.from(song_90), ["artist_song", "artist_song"])
.objects() // Uncomment to return an array of objects
Making nearest point work
function topChartRound(data){
var ar=[];
var i=0;
while(i<344){
for(var j=1; j<3 ;j++)
{
var x =_math.floor(data[i]["mean_millennial_recognition"]*100);
var y=_math.floor(data[i]["mean_gen_z_recognition"]*100);
}
ar.push({artist_song:data[i].artist_song,millennial:x,genZ:y})
i++;
}
return(ar);
}
topChartRound_data=topChartRound(topChartData);
Inputs.table(topChartRound_data)
// To use copied code replace "data" with your own variable
topChartRound_fold=aq.from(topChartRound_data)
.fold(['millennial','genZ']).orderby(aq.desc("value"))
.objects() // Uncomment to return an array of objects
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
