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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
WITH top_industries AS
(SELECT i.industry, COUNT(*)
FROM industries AS i
JOIN dates AS d
ON i.company_id = d.company_id
WHERE EXTRACT (year FROM date_joined) in ('2019','2020','2021')
GROUP BY i.industry
ORDER BY COUNT(*) DESC
LIMIT 3),
yearly_rankings AS
(SELECT COUNT(*) AS num_unicorns, i.industry, EXTRACT (year FROM d.date_joined) AS year, AVG(f.valuation) AS average_valuation
FROM industries as i
JOIN dates AS d
ON i.company_id = d.company_id
JOIN funding AS f
ON d.company_id = f.company_id
GROUP BY i.industry, year)
SELECT yr.industry, yr.year, yr.num_unicorns, ROUND(AVG(yr.average_valuation/1000000000),2) AS average_valuation_billions
FROM yearly_rankings AS yr
WHERE yr.year in ('2019','2020','2021') and yr.industry in (SELECT industry FROM top_industries)
GROUP BY yr.industry, yr.num_unicorns, yr.year
ORDER BY yr.industry, yr.year DESC