ECOLAB INC. (ECL) Key Metrics API

• cURL
• Python
• JavaScript

curl "https://financialdata.net/api/v1/key-metrics?identifier=ECL&key=API_KEY"

import requests

                                                url = 'https://financialdata.net/api/v1/key-metrics?identifier=ECL&key=API_KEY'    
                                                response = requests.get(url)

                                                print(response.json())
                                            

const url = 'https://financialdata.net/api/v1/key-metrics?identifier=ECL&key=API_KEY';
                                            
                                                const response = await fetch(url);
                                                const data = await response.json();

                                                console.log(data);
                                            

[
  {
    "trading_symbol": "ECL",
    "central_index_key": "0000031462",
    "registrant_name": "ECOLAB INC.",
    "fiscal_year": "2025",
    "period_end_date": "2025-12-31",
    "earnings_per_share": 7.33,
    "earnings_per_share_forecast": 8.16,
    "price_to_earnings_ratio": 35.8144611186903,
    "forward_price_to_earnings_ratio": 32.171568627451,
    "earnings_growth_rate": -1.34589502018843,
    "price_earnings_to_growth_ratio": -26.6101446111869,
    "book_value_per_share": 34.6081891987293,
    "price_to_book_ratio": 7.58548788821459,
    "ebitda": 3233700000.0,
    "enterprise_value": 81962016000.0,
    "dividend_yield": 0.0104232893502434,
    "dividend_payout_ratio": 0.373482366544614,
    "debt_to_equity_ratio": 0.842950423711467,
    "capital_expenditures": 828000000.0,
    "free_cash_flow": 2124600000.0,
    "return_on_equity": 0.212428869693372,
    "one_year_beta": 0.540592545017528,
    "three_year_beta": 0.628504168645182,
    "five_year_beta": 0.861595153443826
  },
  ...
]

The API endpoint returns key financial metrics such as price-to-earnings ratio, price-to-book ratio, free cash flow, etc. This information is particularly important for value investors looking to identify undervalued stocks. Data is available for several thousand US and international companies.