No one told you thisgit add \[Advanced\]\ SQL\ Window\ Functions/

Author: ayushi-b

[Advanced] SQL Window Functions/Lesson 6 - [Advanced] SQL Window Functions.sql

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+/*
+Create a running total of standard_amt_usd (in the orders table) over order time with 
+no date truncation. Your final table should have two columns: one with the amount 
+being added for each new row, and a second with the running total.
+*/
+
+SELECT standard_amt_usd,
+	SUM(standard_amt_usd) OVER (ORDER BY occurred_at) AS running_total
+FROM orders;
+
+
+
+
+
+/*
+Create a running total of standard_amt_usd (in the orders table) over order time, but 
+this time, date truncate occurred_at by year and partition by that same year-truncated 
+occurred_at variable. Your final table should have three columns: One with the amount 
+ing added for each row, one for the truncated date, and a final columns with the running 
+total within each year.
+*/
+
+SELECT standard_amt_usd,
+	DATE_TRUNC('year', occurred_at) year,
+	SUM(standard_amt_usd) OVER (
+      	PARTITION BY DATE_TRUNC('year', occurred_at)
+      	ORDER BY occurred_at
+    ) AS running_total
+FROM orders;
+
+
+
+
+
+/*
+Select the id, account_id, and total variable from the orders table, then create a 
+column called total_rank that ranks this total amount of paper ordered (from 
+highest to lowest) for each account using a partition. Your final table should 
+have these four columns.
+*/
+
+SELECT id,
+	account_id,
+    total,
+    RANK() OVER (
+    	PARTITION BY account_id
+      	ORDER BY total DESC
+    ) total_rank
+FROM orders;
+
+
+
+
+
+/*
+Determine how the current order's total revenue (i.e. from sales of all types 
+of paper) revenue compares to the next order's total revenue. You'll need to 
+use occurred_at and total_amt_usd in the orders table along with LEAD to do 
+so. In your query results, there should be four columns: occurred_at, 
+total_amt_usd, lead, and lead_difference.
+*/
+
+SELECT occurred_at,
+       total_amt_usd,
+       LEAD(total_amt_usd) OVER (ORDER BY occurred_at) AS lead,
+       LEAD(total_amt_usd) OVER (ORDER BY occurred_at) - total_amt_usd AS lead_difference
+FROM (
+SELECT occurred_at,
+       SUM(total_amt_usd) AS total_amt_usd
+  FROM orders 
+ GROUP BY 1
+ ) sub
+
+
+
+
+
+/*
+Use the NTILE functionality to divide the accounts into 4 levels in terms of the
+amount of standard_qty for their orders. Your resulting table should have the
+account_id, the occurred_at time for each order, the total amount of standard_qty 
+paper purchased, and one of four levels in a standard_quartile column.
+*/
+
+SELECT account_id,
+	occurred_at,
+    standard_qty,
+	NTILE(4) OVER (PARTITION BY account_id ORDER BY standard_qty) 
+FROM orders
+ORDER BY 1;
+
+
+
+
+
+/*
+Use the NTILE functionality to divide the accounts into two levels in terms of 
+the amount of gloss_qty for their orders. Your resulting table should have the 
+account_id, the occurred_at time for each order, the total amount of gloss_qty 
+paper purchased, and one of two levels in a gloss_half column.
+*/
+
+SELECT account_id,
+	occurred_at,
+    gloss_qty,
+	NTILE(2) OVER (PARTITION BY account_id ORDER BY gloss_qty) 
+FROM orders
+ORDER BY 1;
+
+
+
+
+
+/*
+Use the NTILE functionality to divide the orders for each account into 100 
+levels in terms of the amount of total_amt_usd for their orders. Your 
+resulting table should have the account_id, the occurred_at time for each 
+order, the total amount of total_amt_usd paper purchased, and one of 100 
+levels in a total_percentile column.
+*/
+
+SELECT account_id,
+	occurred_at,
+    total_amt_usd,
+	NTILE(100) OVER (PARTITION BY account_id ORDER BY total_amt_usd) 
+FROM orders
+ORDER BY 1;
+
+