df2.filter(d => d.type === "male-generic").view()
df2.filter(d => d.type === "female-generic").view()
df2.filter(d => d.type === "epicene").view()
df2.filter(d => d.type === "different" ).view()
data = fetch(`https://query.wikidata.org/sparql?query=${encodeURIComponent(query)}`, {headers: {accept: "application/sparql-results+json"}}).then(response => response.json())
df = aq.from(data.results.bindings.map(res => ({
item: res.item.value,
itemLabel: res.itemLabel.value,
maleform: res.maleform.value,
femaleform: res.femaleform.value,
lang: res.lang.value,
})))
df2 = df.derive(
{id: d => 1*(d.itemLabel === d.maleform & d.itemLabel != d.femaleform)
+ 2*(d.itemLabel !== d.maleform & d.itemLabel === d.femaleform)
+ 3*(d.itemLabel === d.maleform & d.itemLabel === d.femaleform)
+ 4*(d.itemLabel !== d.maleform & d.itemLabel !== d.femaleform)
}
).join_left(
aq.table({ id: [1, 2, 3, 4], type: ["male-generic", "female-generic", "epicene", "different"] }),
"id"
).dedupe()
male_generic = df2.filter(d => d.type === "male-generic").numRows()
female_generic = df2.filter(d => d.type === "female-generic").numRows()
male_female_label = df2.filter(d => d.type === "epicene").numRows()
other_label = df2.filter(d => d.type === "different").numRows()
import {aq, op} from "@uwdata/arquero"
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