The avatar for @fgregg
Forest Gregg
Public
Edited
Jan 21, 2023
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ward_effect_array
Type Table, then Shift-Enter. Ctrl-space for more options.

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ward_parameters@2.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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ttc = ttc_summarized
.map((d) =>
Array(d.count).fill({
SR_TYPE: d.SR_TYPE,
WARD: d.WARD,
time_to_completion: d.time_to_completion
})
)
.flat()
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memdb
with days as (
select
SR_TYPE,
WARD,
cast(
julianday(CLOSED_DATE) - julianday(CREATED_DATE) as integer
) as time_to_completion
from
service_requests
where
created_date >= ${form.start_date.toISOString().substring(0, 10)}
AND created_date <= ${form.end_date.toISOString().substring(0, 10)}
and SR_TYPE IN (
'Abandoned Vehicle Complaint',
'Alley Pothole Complaint',
'Building Violation',
'Garbage Cart Maintenance',
'Graffiti Removal Request',
'Inspect Public Way Request',
'Pothole in Street Complaint',
'Rodent Baiting/Rat Complaint',
'Sewer Cleaning Inspection Request',
'Street Light Out Complaint',
'Traffic Signal Out Complaint',
'Tree Debris Clean-Up Request',
'Water On Street Complaint'
)
AND STATUS = 'Completed'
AND time_to_completion > 0
AND WARD IS NOT NULL
AND ORIGIN IN (
'Phone Call',
'Internet',
'Mobile Device',
'Alderman''s Office'
)
)
select
SR_TYPE,
WARD,
time_to_completion,
count(*) as count
from
days
group by
SR_TYPE,
WARD,
time_to_completion
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memdb = new DatasetteClient("https://puddle.bunkum.us/_memory")
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kde = require("fast-kde")
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import { DatasetteClient } from "@fgregg/datasette-client-with-sql-cells-full-results-csv-stream"
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