Dark Horse Safety Inc

  • Oil Gas Coal
  • Andrews TX
  • 9 employees
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Company Overview

Headquarters
801 N Main St, Andrews TX
Website
darkhorsesafety.com
Employees
9
Industry
Oil Gas Coal
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Financials & Stats

Revenue

$10B

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Who is Dark Horse Safety Inc

Seems like you're trying to extract information from a dataset and organize it in a specific way. Let's break down what you're asking and how we can achieve it: **Understanding Your Goal** You want to take a dataset (likely a list of companies) and: 1. **Extract key information:** This includes things like company name, industry, location, number of employees, revenue, and a brief description. 2. **Structure the information:** You want to present this information in a consistent format, possibly as a table or a list of dictionaries. 3. **Filter the data:** You're interested in companies that meet certain criteria, such as those in the "Fuel" industry. **How to Approach This** Here's a general approach using Python, which is a great language for data manipulation: 1. **Load the Data:** - You'll need to load your dataset into Python. If it's in a CSV file, you can use the `csv` module. If it's in JSON format, use the `json` module. 2. **Process the Data:** - Use Python's list comprehension or a loop to iterate through each company in your dataset. - Extract the relevant information (name, industry, location, etc.) from each company's data. - Store this extracted information in a new data structure, such as a list of dictionaries. 3. **Filter the Data:** - Use a conditional statement (like `if`) to filter the list of dictionaries, keeping only the companies that belong to the "Fuel" industry. 4. **Present the Results:** - You can print the filtered list of dictionaries, or format it into a table using libraries like `pandas`. **Example (Illustrative)** ```python import json # Load data from a JSON file (replace 'your_data.json' with your file) with open('your_data.json') as f: data = json.load(f) # Filter for companies in the "Fuel" industry fuel_companies = [ company for company in data if company['industry'] == 'Fuel' ] # Print the filtered companies for company in fuel_companies: print(f"Name: {company['name']}") print(f"Industry: {company['industry']}") print(f"Location: {company['location']}") print("-" * 20) ``` **Important Notes:** - **Replace `'your_data.json'` with the actual path to your data file.** - **Adjust the code to match the structure of your dataset.** The example assumes a specific JSON format. Let me know if you have your dataset in a specific format (CSV, JSON, etc.) and I can provide more tailored code!

Dark Horse Safety Inc Industry Tags

Oil & Energy
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Analyze industry trends and opportunities by examining competitors and companies comparable to Dark Horse Safety Inc, including their performance metrics, financials, growth dynamics, and competitive benchmarks.

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FAQ

What is the location of Dark Horse Safety Inc's headquarters?
The headquarters of Dark Horse Safety Inc are situated at 801 N Main St, Andrews TX
What is Dark Horse Safety Inc's official website?
The official website of Dark Horse Safety Inc can be found at darkhorsesafety.com.
What is Dark Horse Safety Inc's current revenue?
As of September 2021, Dark Horse Safety Inc's annual revenue reached $10B.
How many employees does Dark Horse Safety Inc currently have?
Dark Horse Safety Inc employs approximately 9+ people as of September 2021
Which industries is Dark Horse Safety Inc primarily operating in?
Dark Horse Safety Inc operates in the following industries: Fuel
What are Dark Horse Safety Inc's industry tags?
Dark Horse Safety Inc's industry tags include: Oil & Energy

Employee Directory

Key Employees

Marvin Gross

Fire Technician

Phone Email

Nicole Valenzuela

Instructor / Business Development

Phone Email

Karina Bueno

Safety Trainer

Phone Email