Public
Edited
Oct 17, 2022
1 fork
incomePerEdLevel6 = FileAttachment("Income per ed level@6.csv").csv({typed: true});
viewof table = Inputs.table(incomePerEdLevel6)
//Need to find variance = (Total Mean individually squared)- (Total mean)^Squared/ Number of years
Year = incomePerEdLevel6.map(t=>t.Year)
HiS_Completed = incomePerEdLevel6.map(t=>parseInt(t["High School Completed Income"].replace(",", "")));
d3.variance(HiS_Completed)
Some_College = incomePerEdLevel6.map(t=>parseInt(t["Some College Income"].replace(",", "")))
d3.variance(Some_College)
Bachelors = incomePerEdLevel6.map(t=>parseInt(t["Bachelor's Degree Income"].replace(",", "")))
d3.variance(Bachelors)
image = FileAttachment("image.png").image()
//Computing average variance
Avg_Variance = [2550128.888888887,6159343.333333332, 5823343.333333343]
Sum_Avg_Variance = function calculateSum(arr) {
var sum = 0;
for (var i = 0; i < arr.length; i++) {
sum += arr[i];
}
return sum;
console.log(calculateSum([Avg_Variance]));
//Compute the standard deviation
const Standard_Deviation = d3.deviation(Avg_Variance);
}
Y_2000 = [37570, 43370, 60000]
Mean_2000= d3.mean(Y_2000);
Y_2005 = [36880, 41700, 53420]
Mean_2005 = d3.mean(Y_2005)
Y_2010 = [35550, 38970, 53410]
Mean_2010 = d3.mean(Y_2010)
Y_2014 = [32800, 34870, 54530]
Mean_2014 = d3.mean(Y_2014)
Y_2015 = [33360, 37820, 54600]
Mean_2015 = d3.mean(Y_2015)
Y_2016 = [34320 ,37630, 53900]
Mean_2016 = d3.mean(Y_2016)
Y_2017 = [33780, 36960 ,54670]
Mean_2017 = d3.mean(Y_2017)
Y_2018 = [35950, 37420, 56380]
Mean_2018 = d3.mean(Y_2018)
Y_2019 = [35410 ,40210, 56430]
Mean_2019 = d3.mean(Y_2019)
Y_2020 = [36560, 39860 ,59650]
Mean_2020 = d3.mean(Y_2020)
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.
