The avatar for @hannahs-workspace
Observe this
Public
Edited
Jun 11, 2023
3 stars
2
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HHplans.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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HHplans.csv
SELECT
plan,
SUM(mon+tue+wed+thu+fri+sat+sun) AS total_km
FROM HHplans
GROUP BY plan;

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categoryChart = Plot.plot({
marks: [
Plot.barX(
plan_mileage,
Plot.groupY(
{ x: "sum" },
{
x: "total_km",
y: "plan",
fill: "plan", // color by the category
sort: { y: "x", reverse: true, limit: 20 }
}
)
),
Plot.ruleX([0])
],
marginLeft: 200,
marginRight: 100
})
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HHplans.csv
SELECT
plan,
week,
total_distance,
ROUND((total_distance - lag(total_distance, 1, 0) OVER (PARTITION BY plan ORDER BY plan,week))*100/total_distance,0) AS pct_change
FROM (
SELECT
plan,
week,
SUM(mon+tue+wed+thu+fri+sat+sun) AS total_distance
FROM HHplans
GROUP BY plan, week
ORDER BY plan, week
) AS t
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hhplans
Type SQL, then Shift-Enter. Ctrl-space for more options.

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Plot.plot({
style: "overflow: visible;",
color: {legend: true},
y: {grid: true},
marks: [
Plot.ruleY([0]),
Plot.line(weekly_mileage, {
x: "week",
y: "total_distance",
stroke: "plan"
}),
Plot.text(weekly_mileage, {
filter:(d) => d.pct_change>20 && d.pct_change<100,
x: "week",
y: "total_distance",
stroke: "plan",
text: (d) => `+${d.pct_change}%`,
dy: -5,
lineAnchor: "bottom",
fontWeight:'lighter',
fontSize:9,
strokeWidth:0.7
})
],
y: {label: "Distance (km)"}
});
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HHplans.csv
-- slow run
SELECT
1 AS pace,
plan,
SUM(tue+thu+fri) AS weekly_slow_distance
FROM HHplans
GROUP BY plan;
-- SELECT
-- wed_pace AS pace,
-- plan,
-- SUM(wed) AS weekly_distance
-- FROM HHplans
-- GROUP BY plan, wed_pace;

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viewof plan = Inputs.select(plans, {label: "plan"})
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Plot.plot({
marks: [
Plot.rectY(plan, Plot.binX({y: "count"}, {x: "total_distance", fill:"plan"})),
Plot.ruleY([0])
],
color: {
legend: true
},
x: {
domain: [0, 100]
}
})
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plans = d3.group(data, d => d.plan)
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