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Datasets / Generated

Energy readings

Hourly kWh and temperature for three sites over a quarter.

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6,483 rows4 columns Generated

Worked examples

Each of these is a real run: the pipeline picked the columns, shaped the rows and chose the form. Open the trace to see what it decided and why.

Daily kWh by site

Hourly readings are rolled up to days: at hourly resolution three sites over a quarter is 6,000 points of noise, not a trend.

Daily energy use by site010k20k30k40kJan 01Jan 12Jan 23Feb 03Feb 14Feb 25Mar 08Mar 19Mar 30DayPlant CPlant APlant B
show daily energy use per site — 273 rows charted from 6,483, drawn as a line
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How it decided
Finding the data660 ms

Energy readings: 6,483 rows, 4 columns. reading_at, site and kwh.

Shaping the data10 ms

6,483 rows in, 273 out across 3 columns. Hourly readings are rolled up to days: at hourly resolution three sites over a quarter is 6,000 points of noise, not a trend.

Choosing the chart25 ms

line. A measure over time, one line per site.

Applying defaults1 ms

Palette, spacing, axis titles and legend placement applied. 0 issues found.

Daily energy against average temperature

Correlation is a question about two measures, so both go on axes and neither goes on time - the days become the points.

Energy use against temperature010k20k30k40k11.85833333333333411.89166666666666610.904166666666667Temperature CPlant CPlant APlant B
is consumption correlated with temperature? — 273 rows charted from 6,483, drawn as a scatter
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How it decided
Finding the data2732 ms

Energy readings: 6,483 rows, 4 columns. temperature_c and kwh per day, split by site.

Shaping the data43 ms

6,483 rows in, 273 out across 4 columns. Correlation is a question about two measures, so both go on axes and neither goes on time - the days become the points.

Choosing the chart11 ms

scatter. Two measures and no time axis is a scatter. Three sites is the cap for a scatter here, because adjacent points must stay separable for a colour-blind reader.

Applying defaults1 ms

Palette, spacing, axis titles and legend placement applied. 0 issues found.

Schema

4 columns, typed as the pipeline sees them — which is how it knows what can go on a time axis and what can be summed.

Column TypeExample
reading_atdate2025-01-01
sitetextPlant A
kwhnumber507.03
temperature_cnumber10.5

First 8 rows

reading_atsitekwhtemperature_c
2025-01-01Plant A507.0310.5
2025-01-01Plant B248.366.8
2025-01-01Plant C924.9410.4
2025-01-01T01:00:00Plant A680.7610.0
2025-01-01T01:00:00Plant B341.498.6
2025-01-01T01:00:00Plant C958.814.2
2025-01-01T02:00:00Plant A918.5116.1
2025-01-01T02:00:00Plant B485.5815.7

Ask it something else

show daily energy use per sitewhat time of day peaks hardest?is consumption correlated with temperature?
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