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Project - Analyzing Unicorn Companies
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    Did you know that the average return from investing in stocks is 10% per year! But who wants to be average?!

    You have been asked to support an investment firm by analyzing trends in high-growth companies. They are interested in understanding which industries are producing the highest valuations and the rate at which new high-value companies are emerging. Providing them with this information gives them a competitive insight as to industry trends and how they should structure their portfolio looking forward.

    You have been given access to their unicorns database, which contains the following tables:

    dates

    ColumnDescription
    company_idA unique ID for the company.
    date_joinedThe date that the company became a unicorn.
    year_foundedThe year that the company was founded.

    funding

    ColumnDescription
    company_idA unique ID for the company.
    valuationCompany value in US dollars.
    fundingThe amount of funding raised in US dollars.
    select_investorsA list of key investors in the company.

    industries

    ColumnDescription
    company_idA unique ID for the company.
    industryThe industry that the company operates in.

    companies

    ColumnDescription
    company_idA unique ID for the company.
    companyThe name of the company.
    cityThe city where the company is headquartered.
    countryThe country where the company is headquartered.
    continentThe continent where the company is headquartered.
    Unknown integration
    DataFrameavailable as
    df
    variable
    SELECT COUNT(EXTRACT(year FROM d.date_joined)) AS num_unicorns, i.industry
    FROM dates AS d
    JOIN industries AS i
    	USING(company_id)
    WHERE EXTRACT(year FROM d.date_joined) IN (2019, 2020, 2021)
    GROUP BY i.industry
    ORDER BY num_unicorns DESC
    LIMIT 3;
    
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df
    variable
    SELECT i.industry, EXTRACT(year FROM d.date_joined) AS year, COUNT(EXTRACT(year FROM d.date_joined)) AS num_unicorns, ROUND(AVG(f.valuation/100000000,2) AS average_valuation_billions
    FROM industries AS i
    JOIN dates AS d
    	USING(company_id)
    JOIN funding AS f
    	USING(company_id)
    GROUP BY i.industry
    ORDER BY i.industry, year DESC
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df
    variable
    SELECT * FROM funding
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.