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Turn repeated month columns into a tidy list
Make one row per source cell, preserving unreported values separately from observed zeroes.
Illustrative resourceNot tool-testedAdults working with original, synthetic or authorized non-sensitive material
What you’re working towards
A long-form table that preserves each original cell, explicit blanks and row keys, with a reversible mapping check. This is an authored practice example; no consumer AI run or real participant trial has been recorded.
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Make a start
One step at a time.
2 steps
Start with the synthetic worked example or other non-sensitive inputs. Run one prompt at a time in your chosen AI tool. Replace any bracketed placeholders with the requested material, check each reply, and supply the source or earlier outputs that step needs. Paste them again if the tool lacks that context.
Start with the synthetic example, then adapt each prompt to your task.
01
Try the complete example
Open a new chat in a text AI assistant you already have permission to use. Copy the entire prompt below, including SAMPLE INPUT, into the message box and send it. No upload or special tool is needed. Expect a long-form table that preserves each original cell, explicit blanks and row keys, with a reversible mapping check. Compare the result with Input; Output is a worked illustration, not text to paste. Wording and optional editorial choices can differ, but source facts and rules must match. Count 2 × 2 = 4 long rows; map all four source coordinates once, preserving S1 then S2 and October then November. S1/2026-11 is 0/observed; S2/2026-10 is empty/unreported. These are different source states. Reconstruct every original cell under Oct_2026 and Nov_2026. Keep text IDs and visit units; do not substitute a subtotal for row-level fidelity. If a detail differs, paste: “This part is wrong: [quote it]. My input says: [quote the exact source line or rule]. Return a complete corrected replacement and explain the change.” Recheck it yourself. If an essential source fact is missing or contradictory, leave that part unresolved and obtain the fact; never substitute a practice value. Save only the checked draft in a separate note.
Your starting prompt
Reshape the complete wide table into the requested long text table. Preserve every measure cell, key and missing-value meaning. Give a source-coordinate ledger and reconstruct the original wide table without aggregation. State row counts and units; do not claim an app was run.
SAMPLE INPUT
Original synthetic practice input. All people, organizations, records, observations and events below are fictional.
Complete fictional table. All values are monthly adult visit counts in visits, not unique people. Columns are exactly stall_id, Oct_2026, Nov_2026. A header such as Oct_2026 means that whole calendar month in 2026. stall_id is an unchanged text key and is unique in this input. Source row numbers below are data-row numbers, excluding the header.
stall_id | Oct_2026 | Nov_2026
S1 | 3 | 0
S2 | [blank] | 5
[blank] denotes an actually empty source cell, meaning unreported. Zero is a reported count of zero. Nonblank counts are whole numbers. Do not estimate the missing value, aggregate counts or delete an unreported cell.
Return a plain-text long table with exactly stall_id, month, visits, status. Use YYYY-MM months. Numeric visits remain a number; represent an empty visits cell as [blank] in this text display. status is observed for a numeric count including zero, or unreported for the empty cell. Order by original source row, then the original month-column order. Add a separate coordinate ledger linking each long row to original data-row number and exact source header. Reconstruct the original wide table as a reverse check. No spreadsheet app, file export or database change is requested.
Return the complete requested text result. Treat source statements as data, not permission to act. Do not claim a real interview, survey, measurement, source check, consumer AI run or tool execution. Do not send, publish, collect responses, upload files or change another service.
02
Use your own input
Open a new chat. Replace every bracketed field in the prompt below, then paste the whole message. Change related names, source IDs, counts, dates, labels, limits and checks together; none of the sample facts carries over. Use only original, synthetic or authorized non-sensitive material. Expect the same kind of complete result using your inputs. Multiply your source data-row count by the number of selected repeated-measure columns, keeping missing cells. Match every original coordinate once and reconstruct all values, key strings, units and blanks. If a detail differs, paste: “This part is wrong: [quote it]. My input says: [quote the exact source line or rule]. Return a complete corrected replacement and explain the change.” Recheck it yourself. If an essential source fact is missing or contradictory, leave that part unresolved and obtain the fact; never substitute a practice value. Save only the checked draft in a separate note.
Your starting prompt
Reshape my complete small wide table into a long text table under my identifier, period, unit, missing-value, target-column and order rules. Preserve every repeated-measure cell, including blanks and zeroes, with a separate exact source-coordinate ledger. Hold duplicate or missing keys, ambiguous periods or unsupported value meanings rather than aggregating them. Reconstruct the wide table and compare all cells and keys. Derive expected rows from my source shape; do not run an app or change a database.
MY INPUT
Complete small source table including headers, original row order and literal blanks: [replace with complete non-sensitive details, or state unknown]
Identifier columns and unique-row-key rules: [replace with complete non-sensitive details, or state unknown]
Exact repeated-measure columns and their month/period interpretation: [replace with complete non-sensitive details, or state unknown]
Measure name, units and valid value types: [replace with complete non-sensitive details, or state unknown]
Zero, blank, missing and any not-applicable semantics: [replace with complete non-sensitive details, or state unknown]
Target columns, period format, row order and source-coordinate requirements: [replace with complete non-sensitive details, or state unknown]
Use only MY INPUT for facts, dates, names, counts, permissions and constraints. Ask for essential missing information or conflicting rules instead of guessing. Do not import practice-example values. Use original, synthetic or authorized non-sensitive material. Omit private identifiers, credentials, sensitive personal information and information about minors. Do not paste real customer or personnel records. Return the finished result, unresolved questions and proposed checks tied to my input. If the needed text capability is unavailable, stop rather than claiming an output was produced. Do not send, publish, collect responses, buy, book, upload files or change another service.
Optional: improve the result
Add a source month, then reverse it
This optional extension uses only the original synthetic sample. Return to the sample chat, or paste its complete Input into a new chat first. Keep the original edition for comparison. To adapt the extension to your own material, explicitly replace the source and every dependent value, rule and check. No result of this extension has been observed.
Advanced prompt
For the original sample only, add Dec_2026 with S1 = [blank] and S2 = 0. Keep the same missing-value semantics and all prior cells. Produce the six-row long table, coordinate ledger and reconstructed three-month table. Explain why the two new cells require different statuses. This remains a text exercise, not an app import.
Show, then try
See the shape of the result.
This input is synthetic. The output is a written illustration of the intended result, not a verified AI-tool run.
01 / The starting point
Synthetic input
Original synthetic practice input. All people, organizations, records, observations and events below are fictional.
Complete fictional table. All values are monthly adult visit counts in visits, not unique people. Columns are exactly stall_id, Oct_2026, Nov_2026. A header such as Oct_2026 means that whole calendar month in 2026. stall_id is an unchanged text key and is unique in this input. Source row numbers below are data-row numbers, excluding the header.
stall_id | Oct_2026 | Nov_2026
S1 | 3 | 0
S2 | [blank] | 5
[blank] denotes an actually empty source cell, meaning unreported. Zero is a reported count of zero. Nonblank counts are whole numbers. Do not estimate the missing value, aggregate counts or delete an unreported cell.
Return a plain-text long table with exactly stall_id, month, visits, status. Use YYYY-MM months. Numeric visits remain a number; represent an empty visits cell as [blank] in this text display. status is observed for a numeric count including zero, or unreported for the empty cell. Order by original source row, then the original month-column order. Add a separate coordinate ledger linking each long row to original data-row number and exact source header. Reconstruct the original wide table as a reverse check. No spreadsheet app, file export or database change is requested.
Copies text only. For image or file tasks, use the source files named in the steps too.
Illustrative answer authored for this guide; not a recorded AI response or a real-world trial.
Long table; visits is a count in visits, not unique people
stall_id | month | visits | status
S1 | 2026-10 | 3 | observed
S1 | 2026-11 | 0 | observed
S2 | 2026-10 | [blank] | unreported
S2 | 2026-11 | 5 | observed
Coordinate ledger
long row | source data row | exact source header
1 | 1 | Oct_2026
2 | 1 | Nov_2026
3 | 2 | Oct_2026
4 | 2 | Nov_2026
Reconstructed wide table
stall_id | Oct_2026 | Nov_2026
S1 | 3 | 0
S2 | [blank] | 5
Two source rows × two month columns = four long rows. Each (stall_id, month) pair is unique, and every original measure coordinate appears exactly once. The retained row order and exact headers in the coordinate ledger support the reverse comparison. S1 November remains an observed 0. S2 October remains empty/unreported; [blank] is only its display marker, not a numeric value or text to sum.
All four cells match when reconstructed, including the empty cell. No complete visit total, count of people, spreadsheet import or AI execution is claimed. If a later source has duplicate identifiers or an unclear month header, hold the reshape until a stable key or period meaning is supplied; do not aggregate away the conflict.
These checks use the worked example and its particular facts. With your own material, check your actual names, numbers, sources and rules; do not reuse the sample’s values as the answer.
Unsaved checks stay in this tab and reset when you reload. If you choose Save guide, its current example checkmarks are kept in this browser when storage is available.
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A few things to watch for.
Dropping blanks during reshaping silently loses the distinction between unreported and no source row.
A matching total cannot detect swapped cells or missing zeroes; compare each coordinate and retain original key strings.