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Staffelter Hof Winery is Germany's oldest business, established in 862 under the Carolingian dynasty. It has continued to serve customers through dramatic changes in Europe, such as the Holy Roman Empire, the Ottoman Empire, and both world wars. What characteristics enable a business to stand the test of time?

To help answer this question, BusinessFinancing.co.uk researched the oldest company still in business in almost every country and compiled the results into several CSV files. This dataset has been cleaned.

Having useful information in different files is a common problem. While it's better to keep different types of data separate for data storage, you'll want all the data in one place for analysis. You'll use joining and data manipulation to work with this data and better understand the world's oldest businesses.

The Data

businesses and new_businesses

ColumnDescription
businessName of the business (varchar)
year_foundedYear the business was founded (int)
category_codeCode for the business category (varchar)
country_codeISO 3166-1 three-letter country code (char)

countries

ColumnDescription
country_codeISO 3166-1 three-letter country code (varchar)
countryName of the country (varchar)
continentName of the continent the country exists in (varchar)

categories

ColumnDescription
category_codeCode for the business category (varchar)
categoryDescription of the business category (varchar)

Do some quick data quality checks and EDA

Spinner
DataFrameas
df
variable
-- Data quality checks

-- table categories
select 
	count(*) as records_cnt, 
	count(category_code) as category_code_cnt,
	count(category) as category_cnt
from categories;
Spinner
DataFrameas
df1
variable
-- Data quality checks

-- table categories
select 
	count(*) as records_cnt, 
	count(country_code) as category_code_cnt,
	count(country) as category_cnt,
	count(continent) as continent_cnt
from countries;
Spinner
DataFrameas
categories
variable
-- Data quality checks

-- table categories
select 
	count(*) as records_cnt, 
	count(business) as category_code_cnt,
	count(year_founded) as category_cnt,
	count(category_code) as continent_cnt,
	count(country_code) as country_cnt
from public.businesses;
Spinner
DataFrameas
df2
variable
-- Data quality checks

-- table categories
select 
	count(*) as records_cnt, 
	count(business) as category_code_cnt,
	count(year_founded) as category_cnt,
	count(category_code) as continent_cnt,
	count(country_code) as country_cnt
from public.new_businesses;
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DataFrameas
oldest_business_continent
variable
-- What is the oldest business on each continent?

WITH united_business AS (
	SELECT * 
	FROM public.businesses
	UNION
	SELECT * 
	FROM public.new_businesses ),

prep_table AS (
	SELECT 
		continent, country, business, year_founded,
		ROW_NUMBER() OVER(PARTITION BY continent ORDER BY year_founded ASC) as row_number
	FROM united_business as bu
		LEFT JOIN countries as co USING(country_code)
		LEFT JOIN public.categories as ca USING(category_code)

	ORDER BY continent ASC, row_number ASC)
	
SELECT continent, country, business, year_founded
FROM prep_table
WHERE row_number = 1;
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DataFrameas
count_missing
variable
-- How many countries per continent lack data on the oldest businesses
-- Does including the `new_businesses` data change this?
SELECT 
	c.continent,
	count(c.country_code) AS countries_without_businesses
FROM 
	(SELECT *
	 FROM public.businesses
	 UNION 
	 SELECT *
	 FROM public.new_businesses
	) as b
	RIGHT JOIN public.countries as c ON c.country_code = b.country_code
WHERE b.country_code IS NULL
GROUP BY c.continent
;
Spinner
DataFrameas
oldest_by_continent_category
variable
-- Which business categories are best suited to last over the course of centuries?

SELECT 
	continent, 
	category, 
	MIN(year_founded) as year_founded
FROM businesses as bu
	INNER JOIN countries as co USING(country_code)
	INNER JOIN public.categories as ca USING(category_code)
GROUP BY continent, category	
ORDER BY continent, category
;