Baselight

Market Leader Companies With High Revenue

Global Companies ranked by revenue

@kaggle.danishammar_market_leader_companies_with_high_revenue

About this Dataset

Market Leader Companies With High Revenue

Introduction:
This dataset provides comprehensive information on the leading companies globally by revenue. It includes various key metrics and identifiers for each company, facilitating detailed analysis and comparisons. This dataset is gathered from companies market capital website. below i have given the details of the dataset and columns.

About Dataset Columns:
Below is a detailed description of each column in the dataset:

1- Rank:
-Description: This column shows the ranking number of the company based on its Revenue. The rankings are in ascending order, with rank 1 representing the company with the highest market capitalization.
-Data Type: Integer
-Example Values: 1, 2, 3, ...

2-Company:
-Description: This column displays the full name of the company. It helps identify the company being analyzed.
-Data Type: String
-Example Values: "Apple Inc.", "Microsoft Corporation", "Amazon.com Inc."

3-Stock Symbol:
-Description: This column contains the stock symbols (ticker symbols) of the companies, which are used for trading on stock exchanges. This is essential for identifying the company's stock in financial markets.
-Data Type: String
-Example Values: "AAPL", "MSFT", "AMZN"

4- Revenue(USD) in billions:
-Description: This column provides the Revenue of the company in billion US dollars. high revenue are given here according to company balance sheets.
-Data Type: Float (to handle large values with precision)
-Example Values: 2.43, 1.87, 1.76

5-Share Price:
-Description: This column contains the current share price of the respective company in US dollars. It represents the price at which a single share of the company is traded on the stock market.
-Data Type: Float
-Example Values: 145.09, 250.35, 3400.50

6-Company Origin:
-Description: This column provides the country name where the company is headquartered. It helps in understanding the geographical distribution of the leading companies.
-Data Type: String
-Example Values: "United States", "China", "Germany

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