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Overview

The yf_field_categories tool returns a categorized grouping of yfinance fields, organizing them by data type and use case. This helps you understand field relationships and build more organized queries.

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Use Cases

  • Discover field groups: Browse fields organized by category (valuation, fundamentals, etc.)
  • Query organization: Build screener queries using related field groups
  • Data exploration: Understand what types of data are available
  • Learning: Discover new fields within categories you’re already using

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Parameters

This tool accepts only output formatting parameters:
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response_format
string
default:"json"
Output format: "json" or "markdown"
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preview_limit
number
default:"25"
Number of rows to preview in markdown format (1-200)
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save
object
Save results to a file

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Response

Returns field categories with:
  • Category name: The grouping name (e.g., “Valuation”, “Fundamentals”, “Performance”)
  • Fields: List of fields in each category
  • Description: What type of data the category represents

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Common Categories

Expect categories such as:
  • Valuation Metrics: P/E, P/B, market cap, enterprise value
  • Fundamentals: Revenue, earnings, profit margins
  • Performance: Returns, volatility, beta
  • Dividends: Yield, payout ratio, dividend history
  • Growth: Revenue growth, earnings growth
  • Analyst Data: Recommendations, price targets, estimates

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Example Usage

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Get All Categories

{
  "response_format": "json"
}

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Save Category Reference

{
  "response_format": "json",
  "save": {
    "format": "json",
    "filename": "field-categories.json"
  }
}

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Preview in Markdown

{
  "response_format": "markdown",
  "preview_limit": 100
}

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Response Example

{
  "data": {
    "Valuation": {
      "description": "Valuation metrics and ratios",
      "fields": [
        "marketCap",
        "enterpriseValue",
        "trailingPE",
        "forwardPE",
        "priceToBook",
        "priceToSales",
        "pegRatio"
      ]
    },
    "Fundamentals": {
      "description": "Core financial metrics",
      "fields": [
        "totalRevenue",
        "netIncome",
        "ebitda",
        "profitMargins",
        "operatingMargins",
        "returnOnEquity",
        "returnOnAssets"
      ]
    },
    "Dividends": {
      "description": "Dividend-related metrics",
      "fields": [
        "dividendYield",
        "payoutRatio",
        "dividendRate",
        "exDividendDate",
        "fiveYearAvgDividendYield"
      ]
    }
  },
  "saved_path": null
}

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Building Queries with Categories

Use category information to build comprehensive screener queries: 
{
  "query": {
    "operator": "and",
    "operands": [
      {"operator": "gt", "operands": ["marketCap", 10000000000]},
      {"operator": "gt", "operands": ["dividendYield", 0.02]},
      {"operator": "lt", "operands": ["trailingPE", 20]}
    ]
  },
  "query_type": "equity"
}

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Tips

Browse categories to discover related fields you might not have considered. For example, if you’re looking at valuation metrics, check the category to find all available valuation ratios.
Categories are organizational tools. The actual field availability depends on the ticker type and data module you’re querying.

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