Total 53,693 skills, Data Processing has 2765 skills
Showing 12 of 2765 skills
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
Validate data quality in market analysis documents and blog articles before publication. Use when checking for price scale inconsistencies (ETF vs futures), instrument notation errors, date/day-of-week mismatches, allocation total errors, and unit mismatches. Supports English and Japanese content. Advisory mode -- flags issues as warnings for human review, not as blockers.
Analyze budget vs actual variances in Excel with drill-down and root cause analysis. Use when performing variance analysis or explaining budget differences. Trigger with phrases like 'excel variance', 'analyze budget variance', 'actual vs budget'.
CData Software integration. Manage data, records, and automate workflows. Use when the user wants to interact with CData Software data.
Geocode addresses and get map data using free OpenStreetMap Nominatim API. Use when: (1) Converting addresses to coordinates, (2) Reverse geocoding coordinates to addresses, (3) Location-based features, or (4) Validating addresses.
Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
Segment integration. Manage Workspaces. Use when the user wants to interact with Segment data.
Calculate present value, future value, NPV, IRR, loan payments, and amortization schedules across all compounding conventions. Use when the user asks about discounting cash flows, valuing an annuity or perpetuity, comparing investments with different timing, building a mortgage amortization table, or evaluating whether a project is worth pursuing. Also trigger when users mention 'what is it worth today', 'how much will I have in 20 years', 'monthly payment on a loan', 'discount rate', 'Gordon growth model', 'effective annual rate', 'continuous compounding', or ask how to compare a lump sum versus a stream of payments.
This skill should be used when writing PostGIS queries, using spatial functions, geography types, raster operations, topology, or any PostGIS features from 3.5+ (2024-2026).
Connect GWAS variants to biological pathways for drug target discovery. Maps disease-associated SNPs to causal genes via eQTL colocalization (GTEx), links genes to enriched pathways (Reactome, KEGG, MetaCyc), and identifies druggable targets within disease-relevant pathways. Use when asked to translate GWAS findings into mechanistic insights, find pathways enriched for disease genes, discover drug targets from genetic evidence, or answer questions like "What pathways are disrupted in type 2 diabetes based on GWAS data?"
Use this skill when you need to create or modify a LookML Explore. This includes defining the Explore, joins, access grants, and basic configuration.