data-explorer

SKILLFlusso di lavorocommunity
v1.0.0communityMITAggiornato 6 mesi faFonte →

Systematic dataset analysis: schema inspection, data quality, distribution, correlations, and findings with numbers.

Community-submitted skill. Not yet reviewed by the Forge team. Full prompt content may not be available.Request review →
22Stelle
3Client
2Formati
6 mesi faUltimo aggiornamento
Skill
Autorecommunity
Versione1.0.0
LicenzaMIT
CategoriaFlusso di lavoro
Formatiskill.md, system-prompt
PromptNon pubblicato
Compatibilità
Claude✓ Supportato
Cursor
Copilot
ChatGPT✓ Supportato
Gemini✓ Supportato
Descrizione

Approaches unknown datasets in five structured phases: schema inspection, data quality analysis (nulls, cardinality), distribution analysis (histograms, outliers), relationship discovery (correlations, group-bys), and findings reported with concrete numbers — never vague adjectives.

Casi d’uso
Data analysisEDAData qualityBusiness intelligence
Parole chiave
data-analysisedastatisticsdata-qualitypandas