-- 1 -- What are the column names? SELECT * FROM transaction_data LIMIT 10;
-- 2 -- Find the full_names and emails -- of the transactions listing 20252 as the zip code. SELECT full_name, email, zip FROM transaction_data WHERE zip = 20252; -- 3 -- Use a query to find the names -- and emails associated with these transactions. SELECT full_name, email FROM transaction_data WHERE full_name = 'Art Vandelay' OR full_name LIKE '% der %';
-- 4 -- Find the ip_addresses and emails listed with these transactions. SELECT ip_address, email FROM transaction_data WHERE ip_address LIKE '10.%';
-- 5 -- Find the emails in transaction_data with -- ‘temp_email.com’ as a domain. SELECT email FROM transaction_data WHERE email LIKE '%temp_email.com';
-- 6 -- The finance department is looking for a specific transaction. -- They know that the transaction occurred from an ip address starting -- with ‘120.’ and their full name starts with ‘John’.
-- Can you find the transaction? SELECT * FROM transaction_data WHERE full_name LIKE 'John%' AND ip_address LIKE '120.%';
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-- 1 -- What are the column names? SELECT * FROM users LIMIT 20;
-- 2 -- Find the email addresses and birthdays of users whose -- birthday is between 1980-01-01 and 1989-12-31. SELECT email, birthday FROM users WHERE birthday >= '1980-01-01' AND birthday <= '1989-12-31'; -- 3 -- Find the emails and creation date of users -- whose created_at date matches this condition.
SELECT email, created_at FROM users WHERE created_at < '2017-05-01'; -- 4 -- Find the emails of the users who received the ‘bears’ test. SELECT email FROM users WHERE test = 'bears';
-- 5 -- Find all the emails of all users who -- received a campaign on website BBB.
SELECT email FROM users WHERE campaign LIKE 'BBB%';
-- 6 -- Find all the emails of all users who received ad copy 2 in -- their campaign. SELECT email FROM users WHERE campaign LIKE '%-2';
-- 7 -- Find the emails for all users who received both a campaign and a test. -- These users will have non-empty entries in the -- campaign and test columns. SELECT email FROM users WHERE campaign IS NOT NULL AND test IS NOT NULL;
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-- 1 -- What are the column names? SELECT * FROM orders LIMIT 10;
-- 2 -- How recent is this data? SELECT DISTINCT order_date FROM orders ORDER BY order_date DESC;
-- 3 -- Instead of selecting all the columns using *, -- write a query that selects only the special_instructions column.
-- Limit the result to 20 rows. SELECT special_instructions FROM orders LIMIT 20;
-- 4 -- Can you edit the query so that we are only -- returning the special instructions that are not empty? SELECT special_instructions FROM orders WHERE special_instructions IS NOT NULL;
-- 5 -- Let’s go even further and sort the instructions -- in alphabetical order (A-Z).
SELECT special_instructions FROM orders WHERE special_instructions IS NOT NULL ORDER BY special_instructions ASC;
-- 6 -- Let’s search for special instructions that have the word ‘sauce’.
-- Are there any funny or interesting ones?
SELECT special_instructions FROM orders WHERE special_instructions LIKE '%sauce%';
-- 7 -- Let’s search for special instructions that have the word ‘door’. -- Any funny or interesting ones?
SELECT special_instructions FROM orders WHERE special_instructions LIKE '%door%'; -- 8 -- Let’s search for special instructions that have the word ‘box’. -- Any funny or interesting ones? SELECT special_instructions FROM orders WHERE special_instructions LIKE '%box%';
-- 9 -- Instead of just returning the special instructions, also return their order ids.
-- For more readability: -- Rename id as ‘#’ -- Rename special_instructions as ‘Notes’ SELECT id AS '#', special_instructions AS 'Notes' FROM orders WHERE special_instructions LIKE '%box%';
-- 10 -- Challenge -- They have asked you to query the customer who made the phrase. -- Return the item_name restaurant_id, and user_id for the person created the phrase.