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Emile Mathieu
Public
Edited
Oct 27, 2024
3
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wardsAll = ["", "BETHNAL GREEN", "BLACKWALL & CUBITT TOWN", "BOW EAST", "BOW WEST", "BROMLEY NORTH", "BROMLEY SOUTH", "CANARY WHARF", "ISLAND GARDENS", "LANSBURY", "LIMEHOUSE", "MILE END", "POPLAR", "SHADWELL", "SPITALFIELDS & BANGLATOWN", "ST DUNSTAN'S", "ST. KATHARINE'S & WAPPING", "ST PETER'S", "STEPNEY GREEN", "WEAVERS", "WHITECHAPEL"]
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collisions = FileAttachment("TH-LTN-collision@3.csv").csv({typed: true})
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d3.sum(collisions.filter(d => d.Period === "pre LTN"), d => d["number_of_casualties"])
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// collisions_mean = d3.sum(collisions.filter(d => d.Period === "pre LTN"), d => d["number_of_casualties"])
collisions_mean = {
const end = d3.max(collisions.filter(d => d.Period === "pre LTN"), d => d["utcTime"])
const start = d3.min(collisions.filter(d => d.Period === "pre LTN"), d => d["utcTime"])
const nb_year = (end - start) / (365 * 24 * 60 * 60 * 1000)
return d3.sum(collisions.filter(d => d.Period === "pre LTN"), d => d["number_of_casualties"] / nb_year)
}
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preLTN = new Date('2020-06-01') // Assumed date LTNs installed
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// responseTimesMinusE2 = responseTimes.filter(d => d.Postcode_district !== "E2")
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collisions
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