Match the comparison task and data shape to a chart without distorting scale or uncertainty. Fournir: Question and intended message, Data shape and values, Audience and medium. Résultat attendu: A chart recommendation, data layout, labeling rules, and rejected alternatives.
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ChatGPTRecommend a chart for this spreadsheet result.
Question and intended message:
[message]
Data fields, categories, periods, units, ranges, and sample size:
[data]
Audience, medium, and accessibility constraints:
[audience]
Identify whether the task is comparison, trend, distribution, relationship, composition, or flow. Recommend the simplest chart that answers it, show the exact source-table layout, axis and scale rules, sorting, labels, reference lines, and uncertainty or sample-size annotations. Explain two tempting alternatives and why they are worse. Avoid 3D effects, dual axes unless indispensable, truncated quantitative axes that exaggerate differences, and color-only distinctions.De l'entrée au résultat
Voyez comment un contexte concret transforme cette recette en résultat utilisable.
Use a two-series line chart with markers because the task is change over ordered time plus pattern comparison. Source data should have Month in the first column and separate North/South median columns, with an adjacent table retaining each monthly n for annotation.
Place Month on the horizontal axis in chronological order and Median delivery days on one vertical axis. Lower is better; state that in the subtitle. Use a solid line with circles for North and a dashed line with squares for South so grayscale remains readable. Direct-label the final point of each series and annotate unusually small n, rather than labeling every value. If a service target exists, add one thin reference line. Keep a consistent scale that includes the observed range with reasonable context; disclose any nonzero minimum and never use 3D.
A clustered column chart makes month-to-month trajectories harder to follow. Two separate charts weaken direct regional comparison. A dual-axis chart is unnecessary because both series share units. Include a small source note: monthly medians; n=80–450; medians alone do not show distribution spread.
Classifying the comparison task prevents choosing a chart for decoration rather than meaning.
Explicit scale and annotation rules keep small differences and sample limits honest.
Can a reader answer the stated question from the chart without extra explanation?
Do scale, ordering, and labels represent differences proportionally?
Are groups distinguishable without relying only on color?
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Des réponses pratiques sur le bon moment pour utiliser cette recette, ce qu’il faut fournir et les cas où une vérification humaine reste nécessaire.
For “Choose the right chart for spreadsheet data,” prepare Question and intended message, Data shape and values, and Audience and medium. Replace placeholders only with information you can verify. If a detail is unknown, preserve that uncertainty explicitly instead of asking the model to infer it.
The result is not ready if it does not yet deliver the stated outcome—A chart recommendation, data layout, labeling rules, and rejected alternatives—from the supplied evidence, or if it relies on unresolved assumptions, missing approvals, or invented details. Use the checks as release gates: revise the source inputs or assign a named, authorized reviewer instead of polishing an unsupported output.
The published test record for “Choose the right chart for spreadsheet data” lists ChatGPT as of 2026-08-28. This confirms recorded runs, not guaranteed compatibility or identical results in later product versions. For another tool or version, keep every constraint visible and repeat the result checks before use.
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