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Prompt

brute-force-plotter — Copilot Instructions

by eyadsibai

AI Summary

Brute Force Plotter is a Python tool that automatically generates multiple visualization types from CSV data with minimal configuration, ideal for data analysts and developers who want quick exploratory data analysis without manual plot design.

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to add the "brute-force-plotter — Copilot Instructions" prompt rules to my project.
Repository: https://github.com/eyadsibai/brute-force-plotter

Please read the repo to find the rules/prompt file, then:
1. Download it to the correct location (.cursorrules, .windsurfrules, .github/prompts/, or project root — based on the file type)
2. If there's an existing rules file, merge the new rules in rather than overwriting
3. Confirm what was added

Description

Tool to visualize data quickly with no brain usage for plot creation

Project Overview

Brute Force Plotter is a Python tool designed to visualize data quickly with minimal configuration. It automatically generates various plots based on data types (categorical, numeric) from CSV files.

Language and Dependencies

• Python Version: Python 3.10+ (tested on Python 3.10, 3.11, and 3.12) • Key Dependencies: • matplotlib (3.10.7) - for plotting • pandas (2.3.3) - for data manipulation • seaborn (0.13.2) - for statistical visualizations • dask (2025.10.0) - for parallel processing • click (8.3.0) - for CLI interface • pyarrow (22.0.0) - for parquet file handling

Project Structure

• src/ - Main source code directory • __init__.py - Package initialization and public API • __main__.py - Entry point for module execution • brute_force_plotter.py - Backward compatibility layer • library.py - Python library interface • core/ - Core functionality • config.py - Global configuration and constants • data_types.py - Data type inference logic • utils.py - Utility functions • plotting/ - Plotting modules • base.py - Base plotting functions and decorators • single_variable.py - 1D distribution plots • two_variable.py - 2D interaction plots • three_variable.py - 3D interaction plots • summary.py - Correlation and missing values plots • timeseries.py - Time series visualizations • maps.py - Geographic map visualizations • stats/ - Statistical exports • export.py - Statistical summary export • cli/ - Command-line interface • commands.py - Click CLI commands • orchestration.py - Plot generation orchestration • example/ - Example data and output • titanic.csv - Sample CSV data • titanic_dtypes.json - Data type definitions • output/ - Generated plots directory • tests/ - Test suite (143 tests, ~96% coverage) • pyproject.toml - Python project configuration and dependencies • uv.lock - Locked dependency versions for reproducibility • README.md - Documentation in Markdown format

Running the Tool

The tool is executed as a Python module: `bash python3 -m src <input_file.csv> <dtypes.json> <output_directory> `

Discussion

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Health Signals

MaintenanceCommitted 5mo ago
Stale
AdoptionUnder 100 stars
48 ★ · Niche
DocsMissing or thin
Undocumented

GitHub Signals

Stars48
Forks5
Issues3
Updated5mo ago
View on GitHub
MIT License

My Fox Den

Community Rating

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Works With

Any AI assistant that accepts custom rules or system prompts

Claude
ChatGPT
Cursor
Windsurf
Copilot
+ more