Data visualization and analysis at the University of Washington, Seattle.
Public
Edited
Jan 11, 2024
38 forks
Importers
6 stars
// average hours of sunshine per year, courtesy of https://usclimatedata.com/
sun = ({
"Seattle": [69,108,178,207,253,268,312,281,221,142,72,52],
"Chicago": [135,136,187,215,281,311,318,283,226,193,113,106],
"New York": [154,171,213,237,268,289,302,271,235,213,169,155],
"San Francisco": [165,182,251,281,314,330,300,272,267,243,189,156],
"Houston": [144,141,193,212,266,298,294,281,238,239,181,146],
"Miami": [222,227,266,275,280,251,267,263,216,215,212,209]
})
// latitude and longitude values, courtesy of https://www.latlong.net/
ll = ({
"Seattle": [47.608013, -122.335167],
"Chicago": [41.881832, -87.623177],
"New York": [40.730610, -73.935242],
"San Francisco": [37.733795, -122.446747],
"Houston": [29.749907, -95.358421],
"Miami": [25.761681, -80.191788]
})
// the months of the year in abbreviated English
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
// wrangle it all together!
table = aq.table(sun)
.fold(aq.all(), { as: ['city', 'sunshine'] })
.lookup(aq.from(ll), ['city', 'key'], { lon: d => d.value[1], lat: d => d.value[0] })
.groupby('city')
.params({ months }).derive({
monthnum: () => op.row_number() - 1,
month: (d, $) => $.months[op.row_number() - 1]
})
.ungroup()
.select('city', 'lon', 'lat', 'month', 'monthnum', 'sunshine')
.orderby('city', 'monthnum')
.reify()
// export table content as array of objects
data = table.objects()
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