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Data & Analytics
Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Showing 11,569–11,592 of 11,597 skills
- Scientific Pkg PymooMulti-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.Votes: 0GitHub stars: 16
- Scientific Pkg PydicomPython library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, ...Votes: 0GitHub stars: 16
- Scientific Pkg Pydeseq2Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.Votes: 0GitHub stars: 16
- Scientific Pkg PolarsFast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.Votes: 0GitHub stars: 16
- Scientific Pkg PathmlComputational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.Votes: 0GitHub stars: 16
- Scientific Pkg NetworkxComprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.Votes: 0GitHub stars: 16
- Scientific Pkg MatchmsMass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.Votes: 0GitHub stars: 16
- Scientific Pkg HistolabDigital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.Votes: 0GitHub stars: 16
- Scientific Pkg GenimlThis skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.Votes: 0GitHub stars: 16
- Scientific Pkg FlowioParse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.Votes: 0GitHub stars: 16
- Scientific Pkg EtetoolkitPhylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.Votes: 0GitHub stars: 16
- Scientific Pkg DeeptoolsNGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.Votes: 0GitHub stars: 16
- Scientific Pkg DeepchemMolecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.Votes: 0GitHub stars: 16
- Scientific Pkg Datacommons ClientWork with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.Votes: 0GitHub stars: 16
- Scientific Pkg Cellxgene CensusQuery CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, integrate with scanpy/PyTorch, for population-scale single-cell analysis.Votes: 0GitHub stars: 16
- Scientific Pkg BiopythonPrimary 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.Votes: 0GitHub stars: 16
- Scientific Pkg AstropyComprehensive 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.Votes: 0GitHub stars: 16
- Scientific Pkg AeonThis skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.Votes: 0GitHub stars: 16
- Transforming DataTransform raw data into analytical assets using modern transformation patterns, frameworks, and orchestration tools.Votes: 0GitHub stars: 517
- Sampling Bluesky ZeitgeistDEPRECATED - 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.Votes: 0GitHub stars: 150
- Extracting KeywordsExtract keywords from text using YAKE (Yet Another Keyword Extractor), an unsupervised statistical keyword extraction algorithm.Votes: 0GitHub stars: 150
- Exploring DataExploratory 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.Votes: 0GitHub stars: 150
- Charting Vega Lite``` **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? ...Votes: 0GitHub stars: 150
- Rank TrackerThis 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.Votes: 1GitHub stars: 182