pycse
Use when performing regression analysis with confidence intervals, solving ODEs, fitting models to experimental data, or caching expensive scientific computations - provides convenient wrappers around scipy tha...
Discover tools data analysis skills, compare source repositories and read the instructions for each workflow.
Use when performing regression analysis with confidence intervals, solving ODEs, fitting models to experimental data, or caching expensive scientific computations - provides convenient wrappers around scipy tha...
Comprehensive plotting and visualization in Python - matplotlib (static publication-quality plots), seaborn (statistical visualization), and plotly (interactive plots); includes plot types, customization, best...
Coaches users to transform messy data into clean, analysis-ready formats using Power Query UI. Diagnoses data problems, visualizes goals, and guides step-by-step transformations.
Creates diagrams and animations for STEM education using Matplotlib and Manim. Use for physics diagrams (FBD, vectors), math plots (functions, geometry), flowcharts, or 3Blue1Brown-style animations.
Comprehensive skill for interacting with Grafana's HTTP API to manage dashboards, data sources, folders, alerting, annotations, users, teams, and organizations. Use when Claude needs to (1) Create, read, update...
FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for te...
Calculate ROI for marketing campaigns, investments, and business decisions. Includes break-even analysis, payback period, and comparative ROI.
Use when asked to visualize sales territories, coverage areas, service regions, or geographic boundaries on interactive maps.
Find and visualize correlations between variables in datasets. Use for data exploration, feature selection, or identifying relationships between columns.
Use when asked to calculate statistical power, determine sample size, or plan experiments for hypothesis testing.
Generate organizational hierarchy charts from CSV, JSON, or nested data. Supports multiple layouts, department coloring, and PNG/SVG/PDF export.
Create interactive maps with markers, heatmaps, routes, and choropleth layers. Use when visualizing geographic data, plotting locations, or creating map-based reports.
Perform statistical hypothesis testing, regression analysis, ANOVA, and t-tests with plain-English interpretations and visualizations.
Financial calculations: loans, investments, NPV/IRR, retirement planning, Monte Carlo simulations. Generates tables, charts, and exportable reports.
Generate pivot tables from CSV/Excel with aggregations, filters, and automatic chart creation.
Detect anomalies and outliers in datasets using statistical and ML methods. Use for data cleaning, fraud detection, or quality control analysis.
Analyze text sentiment (positive/negative/neutral) with confidence scores, emotion detection, and visualization. Supports single text, CSV batch, and trend analysis.
Create interactive Sankey diagrams for flow visualization from CSV, DataFrame, or dict data. Supports node/link styling and HTML/PNG/SVG export.
Transform CSV/Excel data into narrative reports with auto-generated insights, visualizations, and PDF export. Auto-detects patterns and creates plain-English summaries.
Compare two datasets to find differences, added/removed rows, changed values. Use for data validation, ETL verification, or tracking changes.
Generate professional PDF/HTML reports with charts, tables, and narrative from data. Supports templates, branding, and automated report generation.
Calculate statistical significance for A/B tests. Sample size estimation, power analysis, and conversion rate comparisons with confidence intervals.
Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.
Analyze survey responses with Likert scale analysis, cross-tabulations, sentiment scoring, and frequency distributions with visualizations.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.