Data & Analytics
Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Transform raw data into analytical assets using modern transformation patterns, frameworks, and orchestration tools.
DEPRECATED - Use browsing-bluesky skill instead. Sample and analyze Bluesky firehose to identify trending topics and content clusters. Use when user asks about "what's happening on Bluesky", "Bluesky trends", "zeitgeist", "firehose analysis", or wants to see real-time topic clusters from the network.
Extract keywords from text using YAKE (Yet Another Keyword Extractor), an unsupervised statistical keyword extraction algorithm.
Exploratory data analysis. Use when users upload .csv/.xlsx/.json/.parquet files or request "explore data", "analyze dataset", "EDA", "profile data". Small files get ydata-profiling HTML/JSON reports; large files (over 200MB or 5M rows) get fixed-memory DuckDB/sketch profiling. Also covers near-duplicate row detection, cross-file key overlap ("can these join?"), dataset drift vs a stored baseline, and time-series profiling.
``` **Read sample data and column names to infer what the data represents:** - **Biomedical data?** → Biomarkers, patient outcomes, clinical relevance - **Financial data?** → Trends, comparisons, performance metrics - **Sensor data?** → Temporal patterns, anomalies, correlations - **E-commerce?** → Sales trends, product comparisons, conversions **Ask:** What questions would someone analyzing this data want answered? Examples: - Assay data: Which biomarkers strongest? Patterns across samples? ...
This skill helps you track, analyze, and report on keyword ranking positions over time. It monitors both traditional SERP rankings and AI/GEO visibility to provide comprehensive search performance insights.
Create interactive HTML timelines and project roadmaps with Gantt charts and milestones.
Create interactive HTML dashboards with KPI cards and charts.