SELECT id, occurred_at,total_amt_usd//select what rows to show
FROM orders //from what table
ORDER BY occurred_at DESC//A to Z order + DESC Z to A (descend) LIMIT 10//quantity of rows to show
////////////////////////////////////////////////////////////////////////////////////////
ORDER BY account_id,total_amt_usd DESC//account_id gets organized A to Z, and then total_amt_usd DESC Z to A
//////////////////////////////////////////////////////////////////////////////////////////////
SELECT *//select every column
FROM orders
WHERE total_amt_usd < 500//WHERE filters and shows data according to <,>,=,<=,>=,!=, LIMIT 10;
//////////////////////////////////////////////////////////////////////////////////////////////////
SELECT name, website, primary_poc
FROM accounts
WHERE name = 'Exxon Mobil';//for non numeric data ///////////////////////////////////////////////////////////////////////////////////////////////////
SELECT id, (standard_amt_usd/total_amt_usd)*100 AS std_percent, total_amt_usd//arithemtic operations, AS renames the new table created from the operation
FROM orders
LIMIT 10;
//////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT *
FROM accounts
WHERE name LIKE '%s%'//LIKE looks for any similar string in the data '%something%' , % symbol means strings, so %s strings before s nothing after, s& , wild cards//nothing before and strings after s, %s% before and after s strings
//////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT name, primary_poc, sales_rep_id
FROM accounts
WHERE name IN ('Walmart', 'Target', 'Nordstrom');//IN looks for more than one operator with an specific information, specific values
//////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT name, primary_poc, sales_rep_id
FROM accounts
WHERE name NOT IN ('Walmart', 'Target', 'Nordstrom');//NOT gives you the opposite of what you looking for ,this case everything that is not //WALMART,TARGET,NORDSTROM
SELECT name
FROM accounts
WHERE name NOT LIKE 'C%';//using LIKE, gives you all the names that do not start with C
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT *
FROM orders
WHERE standard_qty > 1000 AND poster_qty = 0 AND gloss_qty = 0;//AND gives you the option to add more than paramater from diferent columns
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT name
FROM accounts
WHERE name NOT LIKE 'C%' AND name LIKE '%s';//can be used with different other reserved words, this case, names that do NOT start with C and //names that end in S
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT occurred_at, gloss_qty FROM orders
WHERE gloss_qty BETWEEN 24 AND 29;//BETWEEN is used instead of AND when we look for data in the same column, this case gloss_qty //between 24 and 29, includes 24 and 29
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT *
FROM web_events
WHERE channel IN ('organic', 'adwords') AND occurred_at BETWEEN '2016-01-01' AND '2017-01-01'//more complicated code, IN looks for organic OR adwords, //and BETWEEN gives you the date stamp , format is important
ORDER BY occurred_at DESC;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT id
FROM orders
WHERE gloss_qty > 4000 OR poster_qty > 4000;//OR statement works like in normal programming, or this or that, exclusive ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT *
FROM orders
WHERE standard_qty = 0 AND (gloss_qty > 1000 OR poster_qty > 1000);//parenthesis are important for the logic too
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT *
FROM accounts
WHERE (name LIKE 'C%' OR name LIKE 'W%') //parenthesis again for the logic
AND ((primary_poc LIKE '%ana%' OR primary_poc LIKE '%Ana%') AND primary_poc NOT LIKE '%eana%');
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT orders.*, accounts.*//JOIN works as FROM, this case select everything from both tables and join them on id and account id
FROM accounts
JOIN orders
ON accounts.id = orders.account_id;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT orders.standard_qty, orders.gloss_qty, //here you specify SELECT standard_qty from orders table, with the period format//(orders.standard_qty),and so on, FROM orders, and JOIN with accounts, on those two //columns,account_id and id
orders.poster_qty, accounts.website, accounts.primary_poc
FROM orders
JOIN accounts
ON orders.account_id = accounts.id
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT a.primary_poc, w.occurred_at,w.channel,a.name//SELECT those columns with the alias made in FROM, following what column with the dot
FROM web_events w//FROM web_events alias (w) JOIN accounts a//JOIN with accounts alias (a)
ON w.account_id = a.id//ON using the alias and the PK(primary key) and FK(foreign key)
WHERE a.name = 'Walmart'//WHERE name from account (a)table a.name = 'Walmart' SELECT r.name region, s.name rep, a.name account//SELECT columns with the alias already set up, and what column from those tables adding //names to the tables or will not show all the data
FROM sales_reps s//FROM sales_reps alias (s)
JOIN region r//JOIN region alias (r)
ON s.region_id = r.id//ON PK = FK
JOIN accounts a//JOIN a third table accounts alias (a)
ON a.sales_rep_id = s.id//ON PK = FK
ORDER BY a.name DESC//ORDER BY account alias (a) a.name
SELECT r.name region, a.name account, o.total_amt_usd/(o.total + 0.01) unit_price//SELECT columns from tables with alias, dot notation to select what from those tables
//adding names or the columns will not show up
FROM orders o//FROM orders alias (o)
JOIN accounts a//JOIN accounts alias (a)
ON o.account_id = a.id//ON PK = FK using alias and the specific name of the KEYS (dot notation)
JOIN sales_reps s//JOIN third table sales_reps alias (s)
ON a.sales_rep_id = s.id// ON PK = FK
JOIN region r//JOIN a fourth table region alias r
ON s.region_id = r.id//ON PK = FK
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT r.name region, s.name rep, a.name account//after alias each columns new a new alias, or wont show up, because they share (name)
FROM sales_reps s
JOIN region r
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
WHERE r.name = 'Midwest'
ORDER BY a.name;
SELECT r.name region, s.name rep, a.name account
FROM sales_reps s
JOIN region r
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
WHERE r.name = 'Midwest' AND s.name LIKE 'S%'
ORDER BY a.name;
SELECT r.name region, s.name rep, a.name account
FROM sales_reps s
JOIN region r
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
WHERE r.name = 'Midwest' AND s.name LIKE '% K%'//to pull LAST NAMES that beging with K, ORDER BY a.name;
SELECT r.name region, a.name account, o.total_amt_usd/(o.total + 0.01) unit_price
FROM region r
JOIN sales_reps s
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
WHERE o.standard_qty > 100;
SELECT r.name region, a.name account, o.total_amt_usd/(o.total + 0.01) unit_price
FROM region r
JOIN sales_reps s
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
WHERE o.standard_qty > 100 AND o.poster_qty > 50
ORDER BY unit_price;
SELECT r.name region, a.name account, o.total_amt_usd/(o.total + 0.01) unit_price
FROM region r
JOIN sales_reps s
ON s.region_id = r.id
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
WHERE o.standard_qty > 100 AND o.poster_qty > 50
ORDER BY unit_price DESC;
SELECT DISTINCT a.name, w.channel//SELECT DISTINCT pulls the non repeating and unique data
FROM accounts a
JOIN web_events w
ON a.id = w.account_id
WHERE a.id = '1001';
SELECT o.occurred_at, a.name, o.total, o.total_amt_usd
FROM accounts a
JOIN orders o
ON o.account_id = a.id
WHERE o.occurred_at BETWEEN '01-01-2015' AND '01-01-2016'//BETWEEN for dates
ORDER BY o.occurred_at DESC;
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT COUNT (orders.poster_amt_usd) IDs//COUNT gives you how many rows a table has, doesnt count NULL values
FROM orders;
SELECT SUM(poster_qty) AS total_poster_sales//SUM gives you the sum of and specific column
FROM orders;
SELECT SUM(standard_amt_usd)/SUM(standard_qty) AS standard_price_per_unit //SUM can be used in the middle of a math expresion FROM orders;
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT MIN(occurred_at)//MIN gives you the minimun value of that column
FROM orders;
SELECT MAX(occurred_at)//MAX gives you the maximum value of that column
FROM web_events;
SELECT AVG(standard_qty) mean_standard, AVG(gloss_qty) mean_gloss, //AVG gives you the average value of that column
AVG(poster_qty) mean_poster, AVG(standard_amt_usd) mean_standard_usd, AVG(gloss_amt_usd) mean_gloss_usd, AVG(poster_amt_usd) mean_poster_usd
FROM orders;
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT a.name, o.occurred_at
FROM accounts a
JOIN orders o
ON a.id = o.account_id
ORDER BY occurred_at
LIMIT 1;
SELECT SUM(o.total_amt_usd) TotalUsd, a.name CompanyName
FROM orders o
JOIN accounts a
ON o.account_id = a.id
GROUP BY CompanyName//GROUP BY, groups the date and does the operation there, is like minitables inside the big table
ORDER BY TotalUsd
SELECT w.occurred_at, w.channel, a.name
FROM web_events w
JOIN accounts a
ON w.account_id = a.id ORDER BY w.occurred_at DESC
LIMIT 1;
SELECT COUNT (w.channel) ChannelCount, w.channel NameOfChannel
FROM web_events w
GROUP BY NameOfChannel
SELECT a.primary_poc
FROM web_events w
JOIN accounts a
ON a.id = w.account_id
ORDER BY w.occurred_at
LIMIT 1;
SELECT a.name, MIN(total_amt_usd) smallest_order
FROM accounts a
JOIN orders o
ON a.id = o.account_id
GROUP BY a.name
ORDER BY smallest_order;
SELECT r.name, COUNT(*) num_reps
FROM region r
JOIN sales_reps s
ON r.id = s.region_id
GROUP BY r.name
ORDER BY num_reps;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
AND SUBSTRING(RD.RECEIVE_DATE,1,10) BETWEEN '2022-01-25' and '2022-04-30' //to use dates , in a better way
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT a.name, AVG(o.standard_qty)AVG_standard, AVG(o.gloss_qty) AVG_gloss, AVG(o.poster_qty)AVG_poster
FROM accounts a
JOIN orders o
ON a.id = o.account_id
GROUP BY a.name
ORDER BY a.name DESC//DESC Z-A
SELECT SR.name, WE.channel, COUNT(WE.channel) channel_count
FROM sales_reps SR
JOIN accounts
ON SR.id = accounts.sales_rep_id
JOIN web_events WE
ON accounts.id = WE.account_id
GROUP BY WE.channel , SR.name
ORDER BY channel_count DESC //GROUP BY name and channel, channel will give the COUNT of those channels in the table, under the same name
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT s.name, s.id, COUNT(*) numb_counts
FROM sales_reps s JOIN accounts a
ON s.id = a.sales_rep_id
GROUP BY s.name, s.id//GROUP BY will group all of the people under same name (Lola,Lola,Lola as only one Lola), the by ID, and the COUNT
HAVING COUNT(*) > 5// will count those groups individually
ORDER BY COUNT(*)
SELECT a.name,a.id, COUNT(*) numb_orders
FROM accounts a
JOIN orders o
ON a.id = o.account_id
GROUP BY a.name, a.id
HAVING COUNT(*) > 20
ORDER BY numb_orders
SELECT a.name,a.id, COUNT(*) numb_orders
FROM accounts a
JOIN orders o
ON a.id = o.account_id
GROUP BY a.name, a.id
ORDER BY numb_orders DESC//ORDER BY DESC to get Z-A and limiting the result as 1 to show the MAX
LIMIT 1
SELECT a.name name_of ,a.id id , SUM(o.total_amt_usd) total_sum//SUM is used to add the total_amt_us of each account under the same order FROM accounts a
JOIN orders o
ON a.id = o.account_id
GROUP BY a.name, a.id
HAVING SUM(o.total_amt_usd) >30000
ORDER BY total_sum
SELECT a.id, a.name, w.channel, COUNT(*) use_of_channel//SELECT a.id a.name and w.channel FROM tables (accounts a) and (web_events w)
FROM accounts a//COUNT(*) will count everything on the table that we created using the above columns
JOIN web_events w//so,wont count the whole DATA set, just the new DATA we pulled.
ON a.id = w.account_id
GROUP BY a.id, a.name, w.channel//GROUP BY , uses what we have on SELECT
HAVING COUNT(*) > 6 AND w.channel = 'facebook'//HAVING is used like WHERE, but HAVING is for operations like SUM , COUNT, etc
ORDER BY use_of_channel;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
field1 AS last_name//AS renames the column name , for an easier work, does not change the data base
table AS costumers
SELECT last_name
FROM costumers
WHERE last_name LIKE 'CH%';
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT country FROM apt-philosophy-358219.costumer_data.customer_address
WHERE LENGTH(country) > 2//LENGTH gives the lenght of certain cell
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT DISTINCT customer_id FROM apt-philosophy-358219.costumer_data.customer_address
WHERE SUBSTR (country, 1, 2) = 'US'//SUBSTR gives a portion of a string, goes like from what column, starting point and # of characters after the starting point
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT DISTINCT customer_id FROM apt-philosophy-358219.costumer_data.customer_address
WHERE TRIM(state) = 'OH'//TRIM eliminates any extra space in words
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT MIN(length) AS min_length, MAX(length) AS max_length//MIN and MAX gives the respective for certain cell data
FROM apt-philosophy-358219.cars.car_info
SELECT * FROM apt-philosophy-358219.cars.car_info
WHERE num_of_doors IS NULL//NULL checks for empty cells
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
UPDATE cars.car_info//UPDATES data in table SET num_of_doors = 'four'
WHERE make = 'dodge'
AND fuel_type ='gas'
AND body_style ='sedan'
DELETE cars.car_info//DELETES certain rows in a table
WHERE compression_ratio = 70;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
SELECT CAST(purchase_price AS FLOAT64)//CAST converts data types, here from string to float
FROM apt-philosophy-358219.customer_data.customer_purchase
ORDER BY CAST(purchase_price AS FLOAT64) DESC
SELECT CAST(date As date) AS date_only , purchase_price//CAST converts date time format to only date
FROM apt-philosophy-358219.customer_data.customer_purchase
WHERE date BETWEEN '2020-12-01' AND '2020-12-31'
SELECT CONCAT(product_code, product_color)//CONCAT concatenates 2 columns and show them as a new column
FROM apt-philosophy-358219.customer_data.customer_purchase
WHERE product = 'couch'
SELECT COALESCE(product, product_code) AS code_info//COALESCE looks for NULL values and replace them with whatever column you select
FROM apt-philosophy-358219.customer_data.customer_purchase