Public
Edited
Jul 19, 2023
1 star
FileAttachment("population.csv")
// Loading CSV as text only
population_text = FileAttachment("population.csv").text()
// Loading CSV as named data and values - note that everything is a string in this case ( you can notice this by looking at the "" )
FileAttachment("population.csv").csv()
// To convert these strings into dates and numbers, we can set file.csv’s typed option to true. (This is equivalent to passing d3.autoType as the second argument to d3.csvParse, which calls d3.autoType for each row.)
population_data = FileAttachment("population.csv").csv({typed: true})
d3.min(population_data, function(d) { return d.Year; })
d3.max(population_data, function(d) { return d.Year; })
d3.mean(population_data, function(d) { return d["Population estimates"]; })
uniqueListOfYears = {
const listOfYears = population_data.map(row => row.Year);
const uniqueListOfYearsSet = new Set(listOfYears.values());
const uniqueListOfYearsArray = Array.from(uniqueListOfYearsSet)
return uniqueListOfYearsArray.sort();
}
populationEstimatePerYear = {
let sum = 0;
const populationEstimatePerYear = [];
uniqueListOfYears.forEach(key => populationEstimatePerYear.push({year: key, population: 0}));
population_data.forEach(getTotalEstimate);
function getTotalEstimate(row) {
for (let index = 0; index < uniqueListOfYears.length; ++index) {
if(populationEstimatePerYear[index].year == row.Year){
populationEstimatePerYear[index].population += row["Population estimates"] ;
break;
}
}
}
return populationEstimatePerYear;
}
d3.min(population_data, function(d) { return d.Year; })
import {keyStyled} from "@mbostock/keys"
d3 = require("d3@6") // Use the latest Version
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.
