seaborn-statistical-visualization
CommunityCreate publication-quality statistical graphics.
Authorjaechang-hits
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill simplifies the creation of complex statistical visualizations from data, making data exploration and presentation more efficient and aesthetically pleasing.
Core Features & Use Cases
- Diverse Plot Types: Generates histograms, KDE plots, scatter plots, line plots, box plots, violin plots, heatmaps, and more.
- Data Integration: Seamlessly works with pandas DataFrames, automatically handling statistical estimation and aggregation.
- Publication-Ready Graphics: Produces high-quality static plots suitable for reports and publications.
- Use Case: Visualize the relationship between two variables in your dataset, showing trends, confidence intervals, and distributions across different categories, all with a few lines of Python code.
Quick Start
Use the seaborn-statistical-visualization skill to create a scatter plot of 'total_bill' vs 'tip' from the 'tips' dataset, coloring points by 'day'.
Dependency Matrix
Required Modules
seabornmatplotlibpandas
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: seaborn-statistical-visualization Download link: https://github.com/jaechang-hits/SciAgent-Skills/archive/main.zip#seaborn-statistical-visualization Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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