Data provided by the Office of Finance as of December 2021. This dataset reflects the percentage of women and minority-owned businesses that are registered with the City of Los Angeles.

In the past 50 years women's legal status has improved all over the world. But many laws still make it difficult for women to fully participate in economic life whether by getting jobs or starting businesses. Discriminatory rules bar women from certain jobs, restrict access to capital for women-owned firms and limit women's capacity to make legal decisions. Gender differences in laws affect both developing and developed economies, and women in all regions. Women, business, and the law measures restrictions on women s employment and entrepreneurship as well as incentives for women s employment in 143 economies. Women, business, and the law and the World Bank's global financial inclusion global findings database show that in economies with a default full community of property regime, there are on average 10 percentage points more female owned accounts at formal financial institutions than in economies with a default separation of property regime. This report has shown that although much progress has been made in recent decades in gradually dismantling many of the legal restrictions which have hampered women from more fully contributing to national prosperity, there is a large unfinished agenda of reform. Gender equality is important not only for fairness and equity, but also for economic efficiency and is at the center of creating a more prosperous world.

Citation
“World Bank; International Finance Corporation. 2013. Women, Business, and the Law 2014 : Removing Restrictions to Enhance Gender Equality. London: Bloomsbury. © World Bank. https://openknowledge.worldbank.org/handle/10986/20528 License: CC BY-NC-ND 3.0 IGO.”

URI
http://hdl.handle.net/10986/20528

This dataset provides insights into the record number of companies founded by women in the UK in 2023, along with information on gender representation in business and self-employment.

The total number and percentage of private enterprises owned by men or women, by age group of primary owner and enterprise size.

This report presents an analysis of majority women-owned, equally owned and men-owned small and medium enterprises (SMEs) that export. Prior research found that women-owned SMEs were underrepresented amongst exporters. The implications are that businesses owned by women would not benefit as much as the other businesses from the opportunities international trade offers. However, the proportion of women-owned SMEs that export dramatically increased between 2011 and 2017 nearly completely closing the export participation gap. Two factors are identified as having contributed to this important change. First, women’s enterprises tend to be smaller, but a rising number of businesses with 1 to 19 employees exported in 2017 compared to 2011. Second, women-owned SMEs are now better represented in industries prone to exporting. As such, the export gap has significantly narrowed. Nonetheless, the entrepreneurial gap persists, women-owned SMEs still represent less than 16 percent of all SMEs, and a small gap was identified in the proportion of revenues from exports between women-owned enterprises and other firms.

Average percentage of women and men in management positions, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2023.

This dataset contains the Small & Minority Business Resources Department's (SMBR) Strategic Measure for Strategic Direction 2023. It captures contracting data within the City of Austin's MBE/WBE/DBE programs as it relates to prime contractors meeting solicitation goals, as well as certified firm participation breakdowns by racial/ethnic and gender categories. Data can be dis-aggregated by procurement category, SMBR reviewed projects, goal determination, prime contractor ethnicity, prime contractor zip, project cost estimate, and sponsor department. The dataset is captured by fiscal year and stored on the City of Austin network drive in an MS Excel file, and shares information with the SMBR Council Awards Report. View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/Prime-Contractors-Meeting-SMBR-Solicitation-Goals/9q8x-qhyx/edit

Context

This dataset contains all the stats of Gender Statistics 2022 - World Bank.

Details

The Gender Statistics database is a comprehensive source for the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, at least one modern method of contraception. It is usually measured for women ages 15-49 who are married or in union. Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception.

Number of male sole proprietors is the number of newly registered sole proprietors owned by female individuals in the calendar year. A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.

Percentage of women aged 15–49 who have gone through partial or total removal of the female external genitalia or other injury to the female genital organs for cultural or other non-therapeutic reasons. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households. Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered. Women who own house both alone and jointly (% of women age 15-49): Q4 is the percentage of women age 15-49 who alone as well as jointly with someone else own a house which is legally registered with their name or cannot be sold without their signature. "Both alone and jointly" Implies a woman owns a house alone and another house jointly with someone else. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.

Number of infants dying before reaching one year of age. Male population between the ages 75 to 79.

The percentage of respondents who report using mobile money, a debit or credit card, or a mobile phone to make a payment from an account, or report using the internet to pay bills or to buy something online, in the past 12 months. It also includes respondents who report paying bills, sending or receiving remittances, receiving payments for agricultural products, receiving government transfers, receiving wages, or receiving a public sector pension directly from or into a financial institution account or through a mobile money account in the past 12 months, male (% age 15+).

Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.

Metadata

Coverage & Extent

• Granularity List : National
• Temporal Coverage : 1959 - 2021
• Periodicity : Annual
• Acronym : Gender Stats
• Recommended Citation: Gender Statistics, The World Bank
• Languages Supported : English
• Source Type : World Bank Group
• Source: : Gender Statistics, The World Bank
• Harvest Source : World Bank Data API
• Dates
  • First Published Date : Jul 18, 2010
  • Last Updated on : Jun 22, 2022
• Update Frequency : Quarter

Download

kaggle API Command !kaggle datasets download -d azminetoushikwasi/gender-statistics-wb

Disclaimer

The data collected are all publicly available and it's intended for educational purposes only.

Acknowledgement

https://datacatalog.worldbank.org/search/dataset/0037654

Historical Dataset of Urban Assembly School Of Business For Young Women is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2008-2023),Total Classroom Teachers Trends Over Years (2008-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2008-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2008-2023),Hispanic Student Percentage Comparison Over Years (2008-2023),Black Student Percentage Comparison Over Years (2008-2023),White Student Percentage Comparison Over Years (2007-2023),Diversity Score Comparison Over Years (2008-2023),Free Lunch Eligibility Comparison Over Years (2008-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2008-2023)

Dataset Summary About this data: MWBE is a federal program administered through each state. Each state individually establishes its own certification program and requirements. In 2018, the City of Rochester set new goals for the use of minority and women owned businesses (MWBEs) on City contracts. The City of Rochester is committed to providing opportunities for MWBE businesses to participate in and become an integral part of the City's procurement process. This table has information on agreements between primary contractors and consultants (primes) and the City of Rochester, as well as the subcontractors used by those primes. This report pulls information on contracts with payments only. Recently entered agreements may be excluded if there have not been any payments to contractors yet. Data Dictionary:ContractNumber: Unique number assigned to the prime contract in the City of Rochester's financial system. ContractTitle: Title of the agreement between the prime contractor and the City of Rochester. ContractValue: Total value of the agreement between the prime contractor and the City of Rochester. DiversityGoal: This is the percentage of the total value of the agreement that the prime contractor intends to award to minority-owned, women-owned or disadvantaged business entities. Whether or not an MWBE or DBE sub-contractor will count towards this calculation is determined by the prime contractors’ selection when entering sub-contractors into the B2GNow system. AssignedDepartment: The City of Rochester department or bureau responsible for managing the project. ContractType: Agreements are grouped into types depending on what the City is purchasing through the contract. Terms are agreements between the City of Rochester and a contractor to provide a product or service for a set amount of time, or term. Construction is for a set project to build, renovate or update City buildings, properties and infrastructure. Professional Services are agreements for services which require special skills, knowledge, training, expertise, or a high degree of creativity. TierSortOrder: B2GNow generated number assigned to sub-contractors on a project. The numbers are assigned starting at 1 in the order the sub-contractors are entered into the system by the prime contractor. VendorType: This indicates if the business is the prime or sub-contractor. Prime: The business who has made an agreement directly with the City of Rochester to complete a project or provide goods and services. Sub-Contractor: Business hired by the prime contractor or consultant to help complete the agreement with the City of Rochester. BusinessName: Name of the company. GoalType: Indicates if the business is certified as a minority or woman owned business or a certified disadvantaged business entity. Businesses may be certified as both minority and women owned businesses. If businesses have dual certification, their participation is counted to either MBE or WBE goals, based on the selection made by the prime contractor. Blank – This business is not certified. DBE – This business is certified as a disadvantaged business entity (DBE) and their agreement will count toward DBE participation goals. The disadvantaged business enterprise program is administered by the federal Department of Transportation. MBE – This business is New York State certified minority-owned business. WBE – This business is New York State certified woman-owned business. ForCredit: Yes or Blank, indicating whether a certified firm will count toward the project’s participation goals. Ethnicity: Indicates ethnicity or race of MWBE and DBE business owners. Gender: Indicates gender of MWBE and DBE business owners. TotalAward: Total value of agreement between either the prime and City of Rochester or the sub-contractor and the prime. AwardShare: This is an adjustment to show the amount of the contract that will be performed by the business less any sub-contracting agreements. It is calculated differently for Primes and Sub-Contractors. For Primes: SubcontractValue = Total Award – Sum of Sub-Contractor Agreement Values. For Sub-contractors: Award Share = Total Award TotalPayment: The total amount paid to date for the agreement. City: City of the primary business address. State: State of the primary business address. ZIP: ZIP code of the primary business address. Source: This information is pulled from B2GNow, the City of Rochester’s platform for tracking prime contractor and prime consultants’ payments to sub-contractors and their use of MWBEs and DBEs on City contracts. The City began using B2GNow for new contracts in 2019. All agreements with MWBE and DBE goals were entered into B2GNow beginning in 2020. All public works consulting contracting with MWBE goals began being entered in 2021. Data from 2019-2020 may not capture the full use of MWBE and DBE contractors. Last Update: June 30, 2022

Shark Tank India Data set.

Shark Tank India - Season 1 to season 4 information, with 80 fields/columns and 630+ records.

All seasons/episodes of 🦈 SHARKTANK INDIA 🇮🇳 were broadcasted on SonyLiv OTT/Sony TV.

Here is the data dictionary for (Indian) Shark Tank season's dataset.

• Season Number - Season number
• Startup Name - Company name or product name
• Episode Number - Episode number within the season
• Pitch Number - Overall pitch number
• Season Start - Season first aired date
• Season End - Season last aired date
• Original Air Date - Episode original/first aired date, on OTT/TV
• Episode Title - Episode title in SonyLiv
• Anchor - Name of the episode presenter/host
• Industry - Industry name or type
• Business Description - Business Description
• Company Website - Company Website URL
• Started in - Year in which startup was started/incorporated
• Number of Presenters - Number of presenters
• Male Presenters - Number of male presenters
• Female Presenters - Number of female presenters
• Transgender Presenters - Number of transgender/LGBTQ presenters
• Couple Presenters - Are presenters wife/husband ? 1-yes, 0-no
• Pitchers Average Age - All pitchers average age, <30 young, 30-50 middle, >50 old
• Pitchers City - Presenter's town/city or place where company head office exists
• Pitchers State - Indian state pitcher hails from or state where company head office exists
• Yearly Revenue - Yearly revenue, in lakhs INR, -1 means negative revenue, 0 means pre-revenue
• Monthly Sales - Total monthly sales, in lakhs
• Gross Margin - Gross margin/profit of company, in percentages
• Net Margin - Net margin/profit of company, in percentages
• EBITDA - Earnings Before Interest, Taxes, Depreciation, and Amortization
• Cash Burn - In loss in current year; burning/paying money from their pocket (yes/no)
• SKUs - Stock Keeping Units or number of varieties, at the time of pitch
• Has Patents - Pitcher has Patents/Intellectual property (filed/granted), at the time of pitch
• Bootstrapped - Startup is bootstrapped or not (yes/no)
• Part of Match off - Competition between two similar brands, pitched at same time
• Original Ask Amount - Original Ask Amount, in lakhs INR
• Original Offered Equity - Original Offered Equity, in percentages
• Valuation Requested - Valuation Requested, in lakhs INR
• Received Offer - Received offer or not, 1-received, 0-not received
• Accepted Offer - Accepted offer or not, 1-accepted, 0-rejected
• Total Deal Amount - Total Deal Amount, in lakhs INR
• Total Deal Equity - Total Deal Equity, in percentages
• Total Deal Debt - Total Deal debt/loan amount, in lakhs INR
• Debt Interest - Debt interest rate, in percentages
• Deal Valuation - Deal Valuation, in lakhs INR
• Number of sharks in deal - Number of sharks involved in deal
• Deal has conditions - Deal has conditions or not? (yes or no)
• Royalty Percentage - Royalty percentage, if it's royalty deal
• Royalty Recouped Amount - Royalty recouped amount, if it's royalty deal, in lakhs
• Advisory Shares Equity - Deal with Advisory shares or equity, in percentages
• Namita Investment Amount - Namita Investment Amount, in lakhs INR
• Namita Investment Equity - Namita Investment Equity, in percentages
• Namita Debt Amount - Namita Debt Amount, in lakhs INR
• Vineeta Investment Amount - Vineeta Investment Amount, in lakhs INR
• Vineeta Investment Equity - Vineeta Investment Equity, in percentages
• Vineeta Debt Amount - Vineeta Debt Amount, in lakhs INR
• Anupam Investment Amount - Anupam Investment Amount, in lakhs INR
• Anupam Investment Equity - Anupam Investment Equity, in percentages
• Anupam Debt Amount - Anupam Debt Amount, in lakhs INR
• Aman Investment Amount - Aman Investment Amount, in lakhs INR
• Aman Investment Equity - Aman Investment Equity, in percentages
• Aman Debt Amount - Aman Debt Amount, in lakhs INR
• Peyush Investment Amount - Peyush Investment Amount, in lakhs INR
• Peyush Investment Equity - Peyush Investment Equity, in percentages
• Peyush Debt Amount - Peyush Debt Amount, in lakhs INR
• Ritesh Investment Amount - Ritesh Investment Amount, in lakhs INR
• Ritesh Investment Equity - Ritesh Investment Equity, in percentages
• Ritesh Debt Amount - Ritesh Debt Amount, in lakhs INR
• Amit Investment Amount - Amit Investment Amount, in lakhs INR
• Amit Investment Equity - Amit Investment Equity, in percentages
• Amit Debt Amount - Amit Debt Amount, in lakhs INR
• Guest Investment Amount - Guest Investment Amount, in lakhs INR
• Guest Investment Equity - Guest Investment Equity, in percentages
• Guest Debt Amount - Guest Debt Amount, in lakhs INR
• Invested Guest Name - Name of the guest(s) who invested in deal
• All Guest Names - Name of all guests, who are present in episode
• Namita Present - Whether Namita present in episode or not
• Vineeta Present - Whether Vineeta present in episode or not
• Anupam ...

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 ---

This paper analyzes the influence of female participation on the performance and financial risk considering a sample of 218 public companies traded on B3 (Bovespa) from 2010 a 2016. The study also analyzes the influence of female participation on family control companies. Using a random effects methodology and family control dummy and percentage of female presence in boards of director, the study sought to analyze how theses variables and their interactions affect the financial performance of companies. Although the female representation has grown more than 50% in recent years, this share, however, in the board of directors of Brazilian companies is still a minority, close to 9% of the total surveyed. The ownership structure in the family firms is very relevant, with the percentage of 63%. The results suggest a positive relation between female participation and the Tobin-Q, used by value’s proxy, however, this relationship is weaker for firms with a family control. Another result found is that volatility, taken here as a risk’s proxy, is reduced in family run-business.

This dataset tracks annual black student percentage from 2008 to 2023 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 1 School District

This dataset tracks annual white student percentage from 2011 to 2023 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 2 School District

This dataset tracks annual asian student percentage from 2011 to 2023 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 2 School District

This dataset tracks annual hispanic student percentage from 2008 to 2023 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 1 School District

This dataset tracks annual american indian student percentage from 2019 to 2022 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 2 School District

This dataset tracks annual two or more races student percentage from 2013 to 2023 for Urban Assembly School Of Business For Young Women vs. New York and New York City Geographic District # 2 School District

Number of persons on boards of directors that are operating in Canada, by gender and type of corporation, by province and territory, by the North American Industry Classification System (NAICS), and by selected country of control, annual.