Results for “data-analysis”

Automates scientific research workflows from data analysis to publication, orchestrating multiple agents for hypothesis generation, methodology development, computational experiments, and LaTeX paper writing.

Evaluates US market bubble risk through quantitative data analysis using the Minsky/Kindleberger framework, scoring indicators like Put/Call ratio, VIX, margin debt, breadth, and IPO data.

Organize qualitative research data into an affinity diagram with themes, clusters, and insight statements.

Creates and manages Jupyter notebooks for data analysis, visualization, and reproducible research.

Search real-time news with bias scoring, get live stock/ETF/crypto data with AI analysis, ML options pricing, balanced news synthesis, and meme search via the Helium MCP server.

Transforms scattered competitor data into a decision-ready product strategy report with positioning maps, feature matrices, pricing analysis, and opportunity windows.

This skill should be used when building market data displays, implementing price feeds, or adding technical analysis. Covers prices, market caps, technical analysis, sentiment, and trending tokens.

User research specialist. Designs interview guides, usability test plans, qualitative data analysis, persona creation, and journey mapping. Complements Echo's UI validation. Use when user research design or analysis is needed.

Query real-time and historical cryptocurrency market data via CoinGecko through AIsa — simple prices, coin details, historical charts, OHLC candles, token prices by contract address, market-cap rankings, exchange data and tickers, categories, trending searches, and crypto news. Use when you need crypto market research, price tracking, token lookup, portfolio analysis, or market-cap screening. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

research-synthesis

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.

Query 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Query 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome) with a unified Python interface for cross-database analysis, identifier mapping, and sequence analysis.

Guides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.