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Fixing a typo and adding an alternative answer to one of the exercises in Chapter 6. #48

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Fixing a typo and adding an alternative answer to one of the exercises in Chapter 6. #48

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14 changes: 13 additions & 1 deletion Try_It_Yourself/Try_It_Yourself.sql
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Expand Up @@ -296,7 +296,7 @@ GROUP BY state_us_abbreviation;
-- 3,141. That reflects the ongoing adjustments to county-level geographies that
-- typically result from government decision making. Using appropriate joins and
-- the NULL value, identify which counties don't exist in both tables. For fun,
-- search online to nd out why they’re missing
-- search online to find out why they’re missing.

-- Answers:

Expand All @@ -323,6 +323,18 @@ ON c2010.state_fips = c2000.state_fips
AND c2010.county_fips = c2000.county_fips
WHERE c2010.geo_name IS NULL;

-- Counties that exist in either the 2000 data or the 2010 data, but not both,
-- can also be retrieved in a single query using a FULL OUTER JOIN.

SELECT c2010.geo_name AS county_2010,
c2010.state_us_abbreviation AS state_2010,
c2000.geo_name AS county_2000,
c2000.state_us_abbreviation as state_2000
FROM us_counties_2010 AS c2010 FULL OUTER JOIN us_counties_2000 AS c2000
ON c2010.state_fips = c2000.state_fips
AND c2010.county_fips = c2000.county_fips
WHERE c2000.geo_name IS NULL OR c2010.geo_name IS NULL;

-- 2. Using either the median() or percentile_cont() functions in Chapter 5,
-- determine the median of the percent change in county population.

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