{"uid":"cap_ojd7ShcOtdGdmgRR5NXt4","slug":"temperature-observations-string-normalisation-two-measure-correlation-95fcc185","name":"Temperature Observations — String Normalisation + Two-Measure Correlation","description":"Temperature observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied temperature observations records (temperature_c, observation_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-01-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","temperature_c","observation_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"temperature_c":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observation_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","temperature_c":10,"observation_count":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","temperature_c":20,"observation_count":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","temperature_c":15,"observation_count":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","temperature_c":30,"observation_count":4}],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_jJqBf8t_VeBM00Ycwbee0","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Normalises station group strings and computes correlation between temperature_c and observation_count across up to 200 temperature observation rows, returning two analytical reports.","exampleAgentPrompt":"I have temperature observation records with station group names, dates, temperatures in Celsius, and observation counts — can you normalise the station group strings and compute the correlation between temperature_c and observation_count across these rows? Here's my dataset of about 50 rows covering groups 'group-a' and 'group-b' from October 2026.","exampleUseCases":[{"title":"Weather station data quality audit","prompt":"I've got 120 rows of temperature readings from various station groups with messy naming — can you normalise the station_group strings and also tell me whether temperature_c correlates with observation_count across those rows?"},{"title":"Climate dataset correlation check","prompt":"Here are 80 temperature observation records from our monitoring network with dates, temperatures in Celsius, and observation counts per day — please run string normalisation on the station group labels and give me a correlation report between the two numeric measures."},{"title":"Research data preparation for temperature logs","prompt":"I'm preparing temperature observation data for a report — I have 40 rows with row IDs, station groups, dates, temperature_c values, and observation counts. Can you normalise the group name strings and compute a two-measure correlation between temperature and observation count?"}],"resultDescription":"Two analytical reports: (1) a string normalisation report on the station_group field, cleaning and standardising group name values across all input rows; and (2) a correlation report quantifying the statistical relationship between temperature_c and observation_count across the supplied rows (up to 200). No external data is fetched; all analysis is performed locally on the supplied rows.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, date, temperature_c, observation_count) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","All-null temperature_c or observation_count values may prevent meaningful correlation calculation","Malformed JSON body returns an error response"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation of categorical station/group labels AND a two-measure numeric correlation on temperature and observation count fields within a single call on up to 200 rows of temperature observation data. It is a local analytical service with no live lookups or external predictions, making it suitable for offline data preparation and quality workflows where a cheap, deterministic computation ($0.01 USDC for two reports) is preferred over heavyweight analytics platforms.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:51:29.528Z","isFirstParty":false,"canonicalSlug":"temperature-observations-string-normalisation-two-measure-correlation-95fcc185"}