Data Visualization & GIS at Eurostat. Exploring new ways of making maps.
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Eurostat
data = {
//for each region, create object with each cause of death and its rate
let pieData = [];
let all = [
...wholesale,
...retail,
...food,
...employment,
...accommodation,
...totalEmployment,
...centroids
];
let merged = mergeObjectsInArray(all, "id").map((o) => {
o.other =
o.total > o.wholesale + o.retail + o.food + o.employment + o.accommodation
? Math.round(
o.total -
o.wholesale -
o.retail -
o.food -
o.employment -
o.accommodation
)
: 0;
return o;
});
merged.filter((d) => {
let countryCode = d.id.substring(0, 2);
if (!countryCode.includes("EU") && d.value !== null && d.geometry) {
pieData.push(
//pie chart data has to be an array of objects
{
id: d.id,
name: d.name,
geometry: d.geometry,
total: d.total,
// d.wholesale +
// d.retail +
// d.food +
// d.employment +
// d.accommodation +
// d.other, // for some reason the API is returning a total inferior to this (d.total),
data: [
{ name: "Wholesale", value: d.wholesale },
{ name: "Retail", value: d.retail },
{ name: "Food", value: d.food },
{ name: "Employment", value: d.employment },
{ name: "Accommodation", value: d.accommodation },
{ name: "Other", value: d.other }
]
}
);
return d;
}
});
return pieData;
}
wholesale = indexStats(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?geoLevel=nuts${nutsLevel}&indic_sb=V16110&time=${time}&nace_r2=G46`
)
).map((d) => {
d.wholesale = d.value;
return d;
})
retail = indexStats(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?geoLevel=nuts${nutsLevel}&indic_sb=V16110&time=${time}&nace_r2=G47`
)
).map((d) => {
d.retail = d.value;
return d;
})
food = indexStats(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?geoLevel=nuts${nutsLevel}&indic_sb=V16110&time=${time}&nace_r2=I56`
)
).map((d) => {
d.food = d.value;
return d;
})
employment = indexStats(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?geoLevel=nuts${nutsLevel}&indic_sb=V16110&time=${time}&nace_r2=N78`
)
).map((d) => {
d.employment = d.value;
return d;
})
accommodation = indexStats(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?geoLevel=nuts${nutsLevel}&indic_sb=V16110&time=${time}&nace_r2=I55`
)
).map((d) => {
d.accommodation = d.value;
return d;
})
//API IS RETURNING WRONG TOTALS?
totalEmployment = indexTotals(
await d3.json(
`https://ec.europa.eu/eurostat/api/dissemination/statistics/1.0/data/sbs_r_nuts06_r2?indic_sb=V16110&geoLevel=nuts${nutsLevel}&time=${time}&nace_r2=I&nace_r2=N&nace_r2=G`
)
).map((d) => {
d.total = d.value;
return d;
})
indexTotals = function (data) {
// add all values together
let numberOfCategories = data.size[1]; // (e.g. 4) (nace_r2=G47,etc)
let numberofValues = data.size[3]; // (e.g. 129) data.value
// for each GEO code
Object.entries(data.dimension.geo.category.index).forEach((regionCode, i) => {
let index = regionCode[1]; // geo code's index
// for each category (filter), add its results
for (let c = 0; c < numberOfCategories; c++) {
// for each set of results (373)
if (data.value[index + numberofValues * (c + 1)]) {
data.value[index] =
data.value[index] + data.value[index + numberofValues * (c + 1)];
}
}
});
const arr = Object.entries(data.dimension.geo.category.index)
// define our object structure
.map(([key, val]) => ({
id: key,
value: data.value[val] || null,
name: data.dimension.geo.category.label[key]
}));
//sort the array in ascending order by 'value'
return arr.sort((a, b) =>
a.value > b.value ? -1 : b.value > a.value ? 1 : 0
);
}
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