The avatar for @jstonge
Jonathan St-Onge
Public
Edited
Jul 4, 2023
3
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complaints@15.db
SELECT * FROM metadata
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gamma_mat.filter(d => d.topic == 0)
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Array.from(new Set(gamma_mat.map(d => d.topic))).map(t => calc_relative_change(gamma_mat, t))
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complaints@15.db
SELECT *
FROM beta
WHERE (model_index = ${model_index[0].model_index} AND level = ${form['sel_lvl']} )
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complaints@15.db
SELECT *
FROM gamma
WHERE (model_index = ${model_index[0].model_index} AND level = ${form['sel_lvl']})
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resdb
SELECT date_pub::DATE as date_pub, compound, airline, ratings::STRING as ratings, text, country
FROM raw_dat
WHERE (date_pub < '2023-01-01')
ORDER BY date_pub
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single_airline = raw_dat.filter(d => d.airline == sel_airline)
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import {Plot} from "@mkfreeman/plot-tooltip"
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complaints@15.db
SELECT model_index FROM metadata WHERE (sent_fname = ${form['sel_sent_fname']} AND agg = ${form['sel_agg']})
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complaints@15.db
SELECT *
FROM beta
WHERE (model_index = ${model_index[0].model_index} AND level = ${form['sel_lvl']})
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model_index[0].model_index
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resdb = DuckDBClient.of({raw_dat: FileAttachment("airline_reviews_original_six_en@3.parquet")})
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function calc_relative_change(gamma_mat, topic) {
const topic_mu = d3.rollup(gamma_mat, v => d3.mean(v, d => d.score), d => d.topic)
return gamma_mat.filter(d => d.topic == topic)
.map(d => ((d.score - topic_mu.get(topic)) / topic_mu.get(topic) * 100).toFixed(3))
}
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function plot_bars(gamma_mat, beta_mat) {
const beta_by_topic = d3.group(beta_mat, d => d.topic, d => d.word)

return Plot.plot({
height: 350,
width: 1200,
x: {
axis: null,
domain: gamma_mat.title
},
y: {
grid: true,
},
color: {
domain: gamma_mat.title,
scheme: "viridis",
legend: true
},
fx: {
domain: d3.groupSort(gamma_mat, v => d3.sum(v, d => -d.score), d => d.topic),
label: null,
tickSize: 6
},
facet: { data: gamma_mat, x: "topic" },
marks: [
Plot.barY(gamma_mat, {x: "title", y: "score", fill: "title",
title: d => `Top words topic ${d.topic}\n${Array.from(beta_by_topic.get(d.topic).keys()).join('\n')}`}),
Plot.ruleY([0])
]
})
}

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