Use tools for statistical analysis

These tools help investors evaluate company performance, trends, and comparisons using structured and statistical methods.

1. Get year-over-year statistic

What it is: The Get year-over-year statistic tool calculates the year-over-year percentage change for a specific financial or operational metric.

What it’s for: Understanding how a metric (e.g., revenue, earnings) has changed compared to the same period last year.

Example: “What’s the year-over-year revenue growth for Apple?”

Key features:

• Compares to the previous year's value

• Supports time series output

• Accepts optional currency conversion

• Useful for trend and growth analysis

2. Transform table

What it is: The Transform table tool is a tool for sorting, filtering, ranking, or aggregating data in a stock table.

What it’s for: Organizing or restructuring tabular data using natural language instructions.

Example: “Rank these stocks by market cap and show only those above $10 billion.”

Key features:

• Handles complex table transformations

• Supports natural language descriptions

• Great for ranking and filtering

• Not intended for time-based metrics

3. Group transform table per stock

What it is: The Group transform table per stock tool Applies transformations to grouped subsets of stocks within a table.

What it’s for: Analyzing data by sector, region, or custom-defined stock groups.

Example: “Calculate the average market cap for each sector in the S&P 500.”

Key features:

• Operates on individual groups separately

• Useful for sector/industry comparisons

• Supports natural language transformation logic

4. Join tables

What it is: The Join tables tool combines multiple data tables into a single unified table.

What it’s for: Merging different types of data—like performance, valuation, or risk—into one view.

Example: “Create a table with both performance metrics and valuation metrics for these stocks.”

Key features:

• Supports row and column joins

• add_columns=True retains original table rows

• Useful for combining separate datasets

• Optional table naming for clarity

5. Join stock list to table

What it is: The Join stock list to table tool merges a list of stocks with an existing table that includes stock data.

What it’s for: Enriching a list of stocks with performance or metadata from another tool.

Example: “Show my recommendation list along with performance metrics for each stock.”

Key features:

• Combines list data with table info

• Essential when stocks are identified separately

• Bridges gap between list and table formats

6. Table from stock list

What it is: The Table from stock list tool converts a list of stocks into a structured data table.

What it’s for: Creating a new table view from a list of stock identifiers.

Example: “Convert my filtered stock recommendations into a table.”

Key features:

• Preserves metadata and structure

• Ideal starting point for data operations

• Enables column-level modifications

7. Get stock ID list from table

What it is: The Get stock ID list from table tool extracts stock identifiers from any table containing stock data.

What it’s for: Creating a clean list of stocks to use in other tools.

Example: “Get just the stock symbols from this filtered performance table.”

Key features:

• Pulls IDs from any stock-related table

• Simplifies data handoff between tools

• Great for reuse in analysis workflows

8. Get company statistic data

What it is: The Get company statistic data tool retrieves financial or operational metrics for individual companies.

What it’s for: Analyzing specific company statistics like valuation ratios, revenue, or margins.

Example: “What’s the P/E ratio for Tesla compared to other automakers?”

Key features:

• Supports time series and point-in-time data

• Accepts natural language metric requests

• Works for complex financial formulas

9. Get macro statistic data

What it is: The Get macro statistic data tool provides access to broad economic indicators and macro data.

What it’s for: Adding economic context to investment decisions using metrics like interest rates or inflation.

Example: “Show me how interest rates have changed over the past year.”

Key features:

• Covers non-stock data (inflation, GDP, etc.)

• Supports time series for trends

• Complements company-level analysis

10. Filter earnings: Beat or miss

What it is: The Filter earnings: Beat or miss tool filters stocks based on whether they beat or missed earnings/revenue expectations.

What it’s for: Identifying stocks that performed above or below analyst forecasts.

Example: “Show me S&P 500 companies that beat earnings expectations last quarter.”

Key features:

• Works for earnings or revenue

• Supports filtering or informational analysis

• Shows actual vs. expected with surprise %

11. Get expected revenue growth

What it is: The tool Get expected revenue growth analyzes projected revenue or earnings growth from analyst forecasts.

What it’s for: Identifying future growth potential based on market expectations.

Example: “Which technology companies have the highest expected revenue growth?”

Key features:

• Based on forward-looking estimates

• Compares historical and forecast data

• Supports multi-quarter outlooks