edgar-analysis 0.1.0

A package for analyzing EDGAR financial statements for companies

Edgar Financial Analysis Toolkit

A Python package for extracting and analyzing financial statement data from SEC filings using XBRL data and Yahoo Finance.

Key Features

• Extract financial data from SEC filings using edgartools
• Support for balance sheet, income statement, and cash flow statement items
• Calculate annual, quarterly, and trailing twelve month (TTM) metrics
• Flexible matching of accounting concepts with regex patterns
• Integration with Yahoo Finance in order to find correct accounting items
• Clean, standardized output in pandas DataFrames

Installation

pip install edgartools==3.15.1
pip install yfinance pandas

Dependencies

• Python 3.7+
• edgartools (3.15.1)
• yfinance
• pandas
• numpy
• pydantic

Core Components

Accounting Item Configuration

• AccountingItem class defines how to match and process financial statement items
• Pre-configured items for common metrics (Revenue, Total Assets)
• Flexible matching strategies (concept, label, union, intersection)

Data Extraction

• Uses edgartools to download and parse XBRL filings
• Caches filings for efficient repeated analysis
• Handles both instant (balance sheet) and duration (income statement) items

Analysis Features

• Calculate trailing twelve month (TTM) metrics from quarterly data
• Standardize reporting frequencies (annual, quarterly, TTM)
• Combine SEC data with Yahoo Finance data when available

Configuration

EDGAR Identity

You must set your identity before making requests to EDGAR

from edgar import set_identity
set_identity('[e-mail]')

Usage Example

# Download trailing twelve months Revenue data for the past six quarters 
# and last four annual Total Asset figures for Wallmart, Inc.

from edgar import set_identity
from edgar_analysis.company_analysis import CompanyAnalysis

# Set your identity for SEC EDGAR access
set_identity('[e-mail]')

# Analyze a company
analyst = CompanyAnalysis(ticker='WMT')

# Get revenue data
revenues = analyst.get_revenues(periods=6, frequency='ttm')
print(revenues)

# Get total assets
assets = analyst.get_total_assets(periods=4, frequency='annual')
print(assets)

Plotting Example

# Plot last eight quarterly Revenues for Apple, Inc.
import matplotlib.pyplot as plt
from edgar_analysis.company_analysis import CompanyAnalysis

analyst = CompanyAnalysis(ticker='AAPL')
revenues = analyst.get_revenues(periods=8, frequency='quarterly')

revenues.T.plot()  # Transpose for dates on x-axis
plt.title('Apple Quarterly Revenue')
plt.ylabel('Revenue ($)')
plt.show()

Available Accounting Items

Currently configured items are:

• Revenue (Income Statement)
• Total Assets (Balance Sheet)

The system is designed to be easily extended with additional accounting items.

SEC EDGAR & Yahoo Finance Data Matching

The SEC EDGAR API provides financial data for companies, but accounting item names (labels and contexts) can vary across companies and even change over time for the same company.

To standardize this data, I use regular expressions (regex) to identify accounting items that likely match a desired concept (e.g., "Revenues").

How It Works:

1. Yahoo Finance Data: The script retrieves the latest 4 years and 4 quarters of financial data for free.

2. Matching Process: When reporting dates overlap between SEC EDGAR and Yahoo Finance, the script aligns the data to map the correct accounting line items.

3. Historical Consistency: Since companies often report current and prior-period results, this mapping ensures the correct labels and concepts are linked to their values.

This approach improves accuracy when extracting financial metrics from SEC filings.