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Found 286 Skills
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating visualizations. Supports CSV, Excel, JSON, Parquet, and more.
Intelligent recommendation system analysis tool that provides implementations of multiple recommendation algorithms, evaluation frameworks, and visual analysis. It requires user behavior data, product information, or rating data for use, supports recommendation algorithms such as collaborative filtering and matrix factorization, and generates personalized recommendation results and evaluation reports.
Generate professional PDF/HTML reports with charts, tables, and narrative from data. Supports templates, branding, and automated report generation.
R statistical programming for data analysis, visualization, and modeling. Use for .r files.
Automatic CSV Data Analysis and Insight Generation Tool
This skill applies Edward Tufte's data visualization principles from "The Visual Display of Quantitative Information" to create high-impact slides. Use when designing presentations, creating charts/graphs, reviewing slides for clarity, or transforming data into visual displays. Triggers on phrases like "make a slide", "create presentation", "design chart", "visualize data", "review my slides", or "make this more impactful".
Braiins Learn - Bitcoin mining profitability calculators, charts, and data dashboard
Create beautiful infographics based on the given text content. Use this when users request creating infographics.
Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.
Set up the Python environment for OpenAlgo indicator analysis. Installs openalgo, plotly, dash, streamlit, numba, yfinance, matplotlib, seaborn, and creates the project folder structure.
Implement, review, or improve data visualizations using Swift Charts. Use when building bar, line, area, point, pie, or donut charts; when adding chart selection, scrolling, or annotations; when plotting functions with vectorized BarPlot, LinePlot, AreaPlot, or PointPlot; when customizing axes, scales, legends, or foregroundStyle grouping; or when creating specialized visualizations like heat maps, Gantt charts, stacked/grouped bars, sparklines, or threshold lines.