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Project - Analyzing Unicorn Companies
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
| Column | Description | 
|---|---|
| company_id | A unique ID for the company. | 
| date_joined | The date that the company became a unicorn. | 
| year_founded | The year that the company was founded. | 
funding
| Column | Description | 
|---|---|
| company_id | A unique ID for the company. | 
| valuation | Company value in US dollars. | 
| funding | The amount of funding raised in US dollars. | 
| select_investors | A list of key investors in the company. | 
industries
| Column | Description | 
|---|---|
| company_id | A unique ID for the company. | 
| industry | The industry that the company operates in. | 
companies
| Column | Description | 
|---|---|
| company_id | A unique ID for the company. | 
| company | The name of the company. | 
| city | The city where the company is headquartered. | 
| country | The country where the company is headquartered. | 
| continent | The continent where the company is headquartered. | 
DataFrameas
df
variable
SELECT i.industry AS industry,
	   EXTRACT(YEAR FROM d.date_joined) AS yearr,
	   COUNT(d) AS num_unicorns,
	   ROUND(AVG(f.valuation)/1000000000, 2) AS average_valuation_billions
FROM industries i
INNER JOIN dates d
	ON i.company_id = d.company_id
INNER JOIN funding f
	ON i.company_id = f.company_id
GROUP BY yearr, i.industry
HAVING EXTRACT(YEAR FROM d.date_joined) IN (2019, 2020, 2021)
	AND industry IN 
		(SELECT i.industry
		FROM industries i
		INNER JOIN dates AS d
		ON i.company_id = d.company_id
		WHERE EXTRACT(year FROM d.date_joined) IN (2019, 2020, 2021)
		GROUP BY industry
		ORDER BY COUNT(d.date_joined) DESC
		LIMIT 3)
ORDER BY industry, yearr DESC;