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Data & Analytics
Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Showing 2,089–2,112 of 13,012 skills
- Deliverability CheckerCheck email deliverability and DNS configuration. Use when: diagnosing email delivery issues; setting up new email domains; auditing email authentication; checking SPF/DKIM/DMARC; troubleshooting spam folder issuesVotes: 0GitHub stars: 36
- Data VisualizerCreate marketing visualizations from data. Use when: creating charts for reports; visualizing campaign performance; generating dashboards; presenting data insights; exporting charts for presentationsVotes: 0GitHub stars: 36
- Cohort AnalysisAnalyze user retention by cohort. Use when: measuring customer retention; understanding lifecycle patterns; comparing acquisition cohorts; tracking engagement over time; identifying churn risksVotes: 0GitHub stars: 36
- CertifyUse when the user wants to verify that the evolved agent's score is stable and reliable. Runs evaluation multiple times and reports mean ± std.Votes: 0GitHub stars: 36
- Alterlab Vcd InfographicThis skill should be used when the user asks about "infographic", "data visualization", "information design", "data viz", "chart design", "visual storytelling with data", "information graphics", "statistical graphics", "diagram design", "act as an infographic designer", "infographic mode", "data-ink ratio", "chart selection", "dashboard design", "visual data", "Tufte", "ISOTYPE", "icon array", "pie chart", "bar chart", "flow diagram", "process visualization", "data story", or needs expertise ...Votes: 0GitHub stars: 36
- Alterlab VaexOut-of-core tabular analytics with Vaex for billion-row datasets that exceed RAM — lazy evaluation, fast aggregations, big-data visualization, and ML on a single machine. Use when working with large CSV/HDF5/Arrow/Parquet files, computing fast statistics on massive datasets, visualizing big data, or building ML pipelines that do not fit in memory. For distributed clusters prefer dask; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab UsfiscaldataQueries the U.S. Treasury Fiscal Data API across 54 datasets and 182 data tables (no API key required) for federal financial data on national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. ...Votes: 0GitHub stars: 36
- Alterlab UmapNonlinear dimensionality reduction with UMAP — fast manifold learning for 2D/3D visualization, clustering preprocessing (e.g., HDBSCAN), and supervised or parametric UMAP. Use when projecting high-dimensional data to low dimensions for visualization, embedding generation, or as a preprocessing step before clustering. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab Torch GeometricGraph Neural Networks with PyTorch Geometric (PyG) — node and graph classification, link prediction, GCN, GAT, and GraphSAGE layers, heterogeneous graphs, and molecular property prediction. Use when building or training GNNs for geometric deep learning on graph-structured data. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab Stable Baselines3Trains single-agent reinforcement learning agents with Stable-Baselines3 — PPO, SAC, DQN, TD3, DDPG, and A2C behind a scikit-learn-like API. Use for standard single-agent RL experiments, quick prototyping, well-documented algorithm implementations on Gymnasium environments, or adding callbacks and evaluation. For high-throughput parallel training, multi-agent systems, or custom vectorized environments prefer alterlab-pufferlib. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab ShapModel interpretability and explainability with SHAP (SHapley Additive exPlanations) — feature importance and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use when explaining ML model predictions, computing feature importance, debugging models, analyzing bias or fairness, comparing models, or implementing explainable AI across tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model. Part of the AlterLab Aca...Votes: 0GitHub stars: 36
- Alterlab ScveloRun RNA velocity analysis with scVelo on single-cell RNA-seq data — estimate cell-state transitions from spliced/unspliced mRNA dynamics, infer trajectory direction, compute latent time, and identify driver genes. Use when adding directionality to trajectories or studying differentiation dynamics from spliced/unspliced layers (velocyto/STARsolo output); for the general QC, clustering, UMAP, and differential-expression analysis pipeline prefer alterlab-scanpy instead, and for .h5ad data-struct...Votes: 0GitHub stars: 36
- Alterlab Scikit LearnClassical machine learning in Python with scikit-learn — algorithms, preprocessing, pipelines, and best-practice reference documentation. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, feature preprocessing, or building ML pipelines. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab Scikit BioAnalyze biological data with scikit-bio — sequence analysis and alignments, phylogenetic trees, alpha/beta diversity metrics (including UniFrac), ordination (PCoA), PERMANOVA statistics, and FASTA/Newick I/O. Use for microbiome and community-ecology analysis — computing diversity, distance matrices, and ordination from feature tables. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab ReactomeQuery the Reactome REST API for pathway analysis, over-representation/enrichment, gene-to-pathway mapping, disease pathways, molecular interactions, and expression analysis. Use when running pathway enrichment on a gene list, mapping genes to curated biological pathways, or exploring disease pathways for systems biology studies. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab RdkitProvides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization, specialized fingerprint or descriptor algorithms, reaction enumeration, or conformer generation demand direct API control; for a high-level pandas-friendly wrapper over RDKit prefer alterlab-datamol, and for turning m...Votes: 0GitHub stars: 36
- Alterlab QiskitBuilds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical mode...Votes: 0GitHub stars: 36
- Alterlab PytdcLoads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffold or cold-split evaluation, or sourcing labeled molecules for ADMET, toxicity, or DTI modeling. Sources data, splits, and oracles only — defer molecular featurization (ECFP/fingerprints), model tra...Votes: 0GitHub stars: 36
- Alterlab PyopenmsBuild complete mass-spectrometry workflows with pyOpenMS — feature detection, peptide identification, protein quantification, and full LC-MS/MS pipelines across many MS file formats (mzML, mzXML) and algorithms. Use for comprehensive proteomics and MS data processing — for simple spectral comparison and metabolite identification use matchms. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab PyhealthDevelops, tests, and deploys clinical machine learning models with the PyHealth healthcare AI toolkit. Use when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare (RETAIN, SafeDrug, Transformer, GNN). Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab Pydeseq2Run differential gene expression analysis on bulk RNA-seq count matrices with PyDESeq2, the Python port of DESeq2 — size-factor normalization, dispersion estimation, Wald tests, FDR (Benjamini-Hochberg) correction, and volcano/MA plots. Use when identifying differentially expressed genes between conditions from raw bulk RNA-seq counts. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab PubchemQuery PubChem via the PUG-REST API and PubChemPy across 110M+ compounds, searching by name, CID, or SMILES and retrieving molecular properties, bioactivity, and similarity/substructure matches. Use when looking up a chemical compound, converting names/SMILES to CIDs, fetching physicochemical properties, or running cheminformatics structure searches. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab PolarsFast in-memory DataFrame analytics with Polars — lazy evaluation, parallel execution, and an Apache Arrow backend for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory, for 1-100GB datasets, ETL pipelines, or a faster pandas replacement. For larger-than-RAM data prefer dask or vaex. Part of the AlterLab Academic Skills suite.Votes: 0GitHub stars: 36
- Alterlab PlotlyBuilds INTERACTIVE charts with the Plotly Python library (plotly.express / graph_objects) — hover tooltips, zoom/pan, animations, rangesliders, 3D rotation, and standalone HTML/web-embeddable output. Use when a chart must be interactive or web-embedded, for dashboards (incl. Dash), exploratory data analysis, or rotatable 3D plots. For static publication figures defer to alterlab-matplotlib; for static statistical charts (heatmaps, distributions) defer to alterlab-seaborn; for diagrams/schemat...Votes: 0GitHub stars: 36