Dataset

This dataset was created by Susham Nandi

Contents

NASDAQ Listed Companies Dataset

Description:

This dataset provides comprehensive information on companies listed on the NASDAQ stock exchange. It includes essential details about each company, making it a valuable resource for financial analysis, stock market research, and investment strategies.

Features:

• symbol: The unique ticker symbol used to identify the company's stock on the NASDAQ exchange.
• name: The full name of the company.
• currency: The currency in which the company's stock is traded.
• exchange: The stock exchange where the company is listed (in this case, NASDAQ).
• mic_code: The Market Identifier Code (MIC) for the NASDAQ exchange.
• country: The country where the company is headquartered.
• type: The type of company, such as common stock or preferred stock.
• Usage: This dataset can be used for various purposes including:

Stock Market Analysis:

Analyze stock symbols, company names, and market data.

Financial Modeling:

Incorporate company details into financial models and investment strategies.

Market Research:

Understand the distribution of companies by country and currency.

Data Visualization:

Create visualizations of the NASDAQ market landscape.

Data Source:

The data is sourced from the Twelve Data API, which provides up-to-date financial and stock market information.

Notes: The dataset includes only NASDAQ-listed companies and does not cover other exchanges. Ensure to comply with any data usage policies or licensing agreements associated with the data source. Feel free to adapt the description based on the specific details and attributes of your dataset.

Analysis of ‘Top 1000 Kaggle Datasets’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/notkrishna/top-1000-kaggle-datasets on 28 January 2022.

--- Dataset description provided by original source is as follows ---

From wiki

Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

Kaggle got its start in 2010 by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and Artificial Intelligence education. Its key personnel were Anthony Goldbloom and Jeremy Howard. Nicholas Gruen was founding chair succeeded by Max Levchin. Equity was raised in 2011 valuing the company at $25 million. On 8 March 2017, Google announced that they were acquiring Kaggle.[1][2]

Source: Kaggle

--- Original source retains full ownership of the source dataset ---

Dataset

This dataset was created by Arun

Contents

It contains the following files:

Analysis of ‘Fortune 1000’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/winston56/fortune-500-data-2021 on 13 November 2021.

--- Dataset description provided by original source is as follows ---

Context

Every year Fortune, an American Business Magazine, publishes the Fortune 500, which ranks the top 500 corporations by revenue. This dataset includes the entire Fortune 1000, as opposed to just the top 500.

Content

The Fortune 1000 dataset is from the Fortune website, collected by the processes outlined in this notebook. It contains U.S. company data for the year 2021. The dataset is 1000 rows and 18 columns.

Features

• Company - values are the name of the company
• Rank - The 2021 rank established by Fortune (1-1000)
• Rank Change - The change in the rank from 2020 to 2021. There is only a rank change listed if the company is currently in the top 500 and was previously in the top 500.
• Revenue - Revenue of each company in millions. This is the criteria used to rank each company.
• Profit - Profit of each company in millions.
• Num. of Employees - The number of employees each company employs.
• Sector - The sector of the market the company operates in.
• City - The city where the company's headquarters is located.
• State - The state where the company's headquarters is located
• Newcomer - Indicates whether or not the company is new to the top Fortune 500 ("yes" or "no"). No value will be listed for companies outside of the top 500.
• CEO Founder - Indicates whether the CEO of the company is also the founder ("yes" or "no").
• CEO Woman - Indicates whether the CEO of the company is a woman ("yes" or "no").
• Profitable - Indicates whether the company is profitable or not ("yes" or "no").
• Prev. Rank - The 2020 rank of the company, as established by Fortune. There will only be previous rank data for the top 500 companies.
• CEO - The name of the CEO of the company
• Website - The url of the company website
• Ticker - The stock ticker symbol of public companies. Some rows will have empty values because the company is a private corporation.
• Market Cap - The market cap (or value) of the company in millions. Some rows will have empty values because the company is private. Market valuations were determined on January 20, 2021.

Inspiration

This dataset is made to explore the top corporations in the U.S. Answer questions such as: What percentage of companies have women ceo's? How many companies are newcomers? What percentage of companies have ceos who were also founders? What role does profitability play in ranking?

--- Original source retains full ownership of the source dataset ---

Analysis of ‘🪜 What corporations talk about on social media?’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/corporate-messaginge on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

A data categorization job concerning what corporations actually talk about on social media. Contributors were asked to classify statements as information (objective statements about the company or it's activities), dialog (replies to users, etc.), or action (messages that ask for votes or ask users to click on links, etc.). Added: February 14, 2015 by CrowdFlower | Data Rows: 3118 Download Now

Source: https://www.crowdflower.com/data-for-everyone/

This dataset was created by CrowdFlower and contains around 3000 samples along with Text, Unit State, technical information and other features such as: - Id - Golden - and more.

How to use this dataset

• Analyze Category Gold in relation to Last Judgment At
• Study the influence of Screenname on Trusted Judgments
• More datasets

Acknowledgements

If you use this dataset in your research, please credit CrowdFlower

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Open Data 500 Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/govlab/open-data-500-companies on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Context

The Open Data 500, funded by the John S. and James L. Knight Foundation (http://www.knightfoundation.org/) and conducted by the GovLab, is the first comprehensive study of U.S. companies that use open government data to generate new business and develop new products and services.

Study Goals

• Provide a basis for assessing the economic value of government open data

• Encourage the development of new open data companies

• Foster a dialogue between government and business on how government data can be made more useful

The Govlab's Approach

The Open Data 500 study is conducted by the GovLab at New York University with funding from the John S. and James L. Knight Foundation. The GovLab works to improve people’s lives by changing how we govern, using technology-enabled solutions and a collaborative, networked approach. As part of its mission, the GovLab studies how institutions can publish the data they collect as open data so that businesses, organizations, and citizens can analyze and use this information.

Company Identification

The Open Data 500 team has compiled our list of companies through (1) outreach campaigns, (2) advice from experts and professional organizations, and (3) additional research.

Outreach Campaign

• Mass email to over 3,000 contacts in the GovLab network

• Mass email to over 2,000 contacts OpenDataNow.com

• Blog posts on TheGovLab.org and OpenDataNow.com

• Social media recommendations

• Media coverage of the Open Data 500

• Attending presentations and conferences

Expert Advice

• Recommendations from government and non-governmental organizations

• Guidance and feedback from Open Data 500 advisors

Research

• Companies identified for the book, Open Data Now

• Companies using datasets from Data.gov

• Directory of open data companies developed by Deloitte

• Online Open Data Userbase created by Socrata

• General research from publicly available sources

What The Study Is Not

The Open Data 500 is not a rating or ranking of companies. It covers companies of different sizes and categories, using various kinds of data.

The Open Data 500 is not a competition, but an attempt to give a broad, inclusive view of the field.

The Open Data 500 study also does not provide a random sample for definitive statistical analysis. Since this is the first thorough scan of companies in the field, it is not yet possible to determine the exact landscape of open data companies.

--- Original source retains full ownership of the source dataset ---

This is a dataset that requires a lot of preprocessing with amazing EDA insights for a company. A dataset consisting of sales and profit data sorted by market segment and country/region.

Tips for pre-processing: 1. Check for column names and find error there itself!! 2. Remove '$' sign and '-' from all columns where they are present 3. Change datatype from objects to int after the above two. 4. Challenge: Try removing " , " (comma) from all numerical numbers. 5. Try plotting sales and profit with respect to timeline

Analysis of ‘Indian Company Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yogeshrampariya/indian-company-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset is about Indian recruitment company, who hire best of brains in India in software, banking, manufacturing, analysis and Education background

Columns:

Name: Name of Company Rating : Overall Rating given by Rating agency Reviews: Overall Google Reviews Company: Company type like Public, Private Head_Quarters : Location where headquarter of company is Company_age : How old the company is No_of_Employee : Number of employee company has

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

This dataset will test your coding skills where you will be handling categorical variables, its a classification problem

--- Original source retains full ownership of the source dataset ---

Dataset

This dataset was created by Susham Nandi

Contents

It contains the following files:

Analysis of ‘Brazil Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/brazil-largest-companiese on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

​Source: Economy Watch

This dataset was created by Finance and contains around 0 samples along with Assets ($billion), Sales ($billion), technical information and other features such as: - Profits ($billion) - Market Value ($billion) - and more.

How to use this dataset

• Analyze Assets ($billion) in relation to Sales ($billion)
• Study the influence of Profits ($billion) on Market Value ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Germany Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/germany-largest-companiese on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

​Source: Economy Watch

This dataset was created by Finance and contains around 0 samples along with Profits ($billion), Assets ($billion), technical information and other features such as: - Sales ($billion) - Market Value ($billion) - and more.

How to use this dataset

• Analyze Global Rank in relation to Profits ($billion)
• Study the influence of Assets ($billion) on Sales ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘China Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/china-largest-companiese on 28 January 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

​Source: Economy Watch

This dataset was created by Finance and contains around 100 samples along with Profits ($billion), Market Value ($billion), technical information and other features such as: - Sales ($billion) - Assets ($billion) - and more.

How to use this dataset

• Analyze Global Rank in relation to Profits ($billion)
• Study the influence of Market Value ($billion) on Sales ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Greece Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/greece-largest-companiese on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

​Source: Economy Watch

This dataset was created by Finance and contains around 0 samples along with Market Value ($billion), Assets ($billion), technical information and other features such as: - Profits ($billion) - Market Value ($billion) - and more.

How to use this dataset

• Analyze Assets ($billion) in relation to Profits ($billion)
• Study the influence of Market Value ($billion) on Assets ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘ 4 turkey's biggest company(in stock market)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/egeakyol/4-turkeys-biggest-companyin-stock-market on 28 January 2022.

--- No further description of dataset provided by original source ---

--- Original source retains full ownership of the source dataset ---

Analysis of ‘846 Companies Ranked! (2021)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/axeltorbenson/846-companies-ranked on 28 January 2022.

--- Dataset description provided by original source is as follows ---

This file contains data on 846 companies and their ranking based on 6 characteristics: customer satisfaction, employee engagement and development, innovation, social responsibility, financial strength, and effectiveness. These rank were made by the Drucker Institute. Obviously these rankings are not and can not be accurate, but are the opinion of and are influenced wholly by the ranking criterium of the Drucker Institute.

Source: https://www.drucker.institute/2021-drucker-institute-company-ranking/

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Australia Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/australia-largest-companiese on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

http://www.economywatch.com/companies/forbes-list/

This dataset was created by Finance and contains around 0 samples along with Profits ($billion), Sales ($billion), technical information and other features such as: - Assets ($billion) - Market Value ($billion) - and more.

How to use this dataset

• Analyze Profits ($billion) in relation to Sales ($billion)
• Study the influence of Assets ($billion) on Market Value ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Machine Learning users on Github’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/prosperchuks/machine-learning-users-on-github on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Data was scraped from Github's API.

Columns

LOGIN: shows the user's Github login ID: user's id URL: API link to the user's profile NAME: fullname of the user COMPANY: organization the user's affiliated with BLOG: link to the user's blog site LOCATION: location where the user resides EMAIL: user's email address BIO: about the user

This dataset contains over 600 users from Lagos, Nigeria and Rwanda

Source: https://github.com/ProsperChuks/Github-Data-Ingestion/tree/main/data

--- Original source retains full ownership of the source dataset ---

Analysis of ‘6,000 Largest Companies Ranked by Market Cap’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/prasertk/6000-largest-companies-ranked-by-market-cap on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Context

Largest Companies by Market Cap.

Acknowledgements

Data source: https://companiesmarketcap.com/ Cover image credit: https://www.pexels.com/photo/high-rise-buildings-443383/

--- Original source retains full ownership of the source dataset ---

Analysis of ‘2022 Startups Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/khaiid/startups-by-valuation on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Startups are an interesting field to explore and taking a look at the field can expand your knowledge and let you think outside the box

Content

The dataset has 5 columns (Company, Valuation, Valuation_date, Industry, Country)

Company: Describes company name Valuation: Describes the valuation of the company Valuation_date: Describes the date of valuation Industry: Describes the industry of the company Country: Describes the country of the company

Data Collection

This Data uses material from ( https://en.m.wikipedia.org/wiki/List_of_unicorn_startup_companies ) which is released under the Creative Commons Attribution-Share-Alike License 3.0

Inspiration

What industry has the most startups ? What is the total value of these startups ? How many AI companies are in the top 250 startup companies ?

--- Original source retains full ownership of the source dataset ---