Match the comparison task and data shape to a chart without distorting scale or uncertainty. Provide: Question and intended message, Data shape and values, Audience and medium. Expected result: A chart recommendation, data layout, labeling rules, and rejected alternatives.
Your text stays in this browser. AILesson Prompts does not send it to a model or server.
Unfilled fields remain visible as placeholders, so you can still copy and edit the prompt
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.From input to outcome
See how concrete context turns this recipe into a usable result
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?
Use it with confidence
Practical answers about when to use this recipe, what to provide, and where human review still matters
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.
Keep the work moving
Spreadsheet insights
Convert verified metrics into decisions, changes, risks, and requests without overstating evidence
Open recipeSpreadsheet insights
Turn a dataset and decision into questions its fields can actually answer
Open recipeSpreadsheet insights
Flag unusual values with a method suited to the distribution, then investigate before removal
Open recipeAILesson · Recommended courses
Go from understanding AI to getting things done. Practice prompting, reviewing, and improving results through interactive lessons for work and everyday life.
15 interactive lessons
Start a useful AI conversation, make the answer better, check what matters, and know when the next move is yours.
Explore this course
10 interactive lessons
Learn ChatGPT through three practical workflows: complete a first chat, work from a file, then use Projects to carry a checked plan into a new chat.
Explore this course
7 interactive lessons
Understand how common AI chats learn language patterns, use current messages, build replies, and add sources and tools.
Explore this course