Data Analysis

IntermediadataContexto mínimo: 64K

Analyzes datasets to extract insights, identify patterns, and generate visualizations. Supports exploratory data analysis (EDA), statistical testing, trend detection, and report generation. Works with CSV, JSON, and database outputs.

data-analysisstatisticsvisualizationpandasedareporting

Casos de uso

  • Exploratory data analysis on new datasets
  • Statistical hypothesis testing
  • Generating Python/R analysis scripts
  • Creating data visualization code (matplotlib, plotly, d3)
  • Building automated reporting pipelines

Prompt de ejemplo

Analyze this dataset and provide insights.

Data sample (first 10 rows):
```csv
[paste CSV data here]
```

Questions to answer:
1. What are the key distributions and summary statistics?
2. Are there any notable correlations between variables?
3. What outliers or anomalies exist?
4. What trends are visible over time?

Deliverables:
- Summary statistics table
- Python code for full EDA (using pandas + matplotlib)
- Key findings in plain language
- Recommended next steps for deeper analysis

Modelos recomendados

claude-opus-4-6gpt-5gemini-2-5-pro

Herramientas compatibles

claude-codecursorgithub-copilotkiroany

Modalidades

Entrada: text, code, file
→
Salida: text, code

Skills relacionadas

sql-generationdocumentation-generator

Autor

OpenModels Community

@openmodelsrun