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stock-screener

Filter and rank stocks from CSV data by financial metrics using pandas.

276|46|Updated Jan 16, 2026
Search Tags:#python#investment#data analysis#pandas#financial analysis#stock screening
One-click install
npx skills add https://github.com/nicepkg/ai-workflow --skill stock-screener-nicepkg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stock-screener
Source: https://github.com/nicepkg/ai-workflow/tree/main/workflows/stock-trader-workflow/.claude/skills/stock-screener
Command: npx skills add https://github.com/nicepkg/ai-workflow --skill stock-screener-nicepkg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas>=2.0.0, numpy>=1.24.0, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of filtering and analyzing stocks based on various financial metrics, saving investors significant time and effort in stock research.

Core Features & Use Cases

  • Multi-Metric Filtering: Filter stocks using criteria like P/E ratio, market cap, dividend yield, and growth rates.
  • Comparative Analysis: Compare key financial data for multiple stocks side-by-side.
  • Use Case: Quickly identify undervalued stocks with strong growth potential by applying filters for P/E ratio, revenue growth, and profit margin.

Quick Start

Use the stock-screener skill to load 'stocks.csv' and filter for stocks with a P/E ratio between 10 and 20.

Frequently Asked Questions about stock-screener

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I screen stocks by financial metrics using a CSV file?▼

You can screen stocks by financial metrics by loading a CSV file into the tool and filtering based on criteria like P/E ratio, market cap, and dividend yield. It uses pandas to manipulate the data and rank stocks by your specified custom screens.

Can I compare multiple stocks side-by-side based on growth rates and profit margin?▼

Yes, you can compare multiple stocks side-by-side using comparative analysis features. It filters financial data from your CSV to evaluate growth rates, profit margins, and other metrics to help identify undervalued stocks with strong potential.

Does this stock screening tool work with Python and pandas for data analysis?▼

Yes, this stock screening tool works with Python and requires pandas (version 2.0.0 or higher) along with numpy. It leverages pandas for data manipulation and analysis to process financial metrics from your CSV datasets.

What is the best way to filter stocks by P/E ratio and sector analysis in Python?▼

The best way to filter stocks by P/E ratio and conduct sector analysis in Python is by applying custom screens to your CSV data. This approach allows you to quickly isolate and rank stocks within specific sectors using pandas.

What financial data format do I need to perform investment analysis and custom screens?▼

You need financial data formatted as a CSV file to perform investment analysis and apply custom screens. The tool reads the CSV to filter rows based on your defined criteria, such as market cap and dividend yield thresholds.

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