Assignment one

02_activities/assignments/DC_Cohort/assignment1.sql

@@ -1,20 +1,25 @@
 /* ASSIGNMENT 1 */
 /* SECTION 2 */
 
-
 --SELECT
 /* 1. Write a query that returns everything in the customer table. */
-
-
+SELECT *
+FROM customer;
 
 /* 2. Write a query that displays all of the columns and 10 rows from the cus- tomer table, 
 sorted by customer_last_name, then customer_first_ name. */
-
+SELECT *
+FROM customer
+ORDER BY customer_last_name, customer_first_name
+LIMIT 10;
 
 
 --WHERE
 /* 1. Write a query that returns all customer purchases of product IDs 4 and 9. */
-
+SELECT *
+FROM customer_purchases
+WHERE product_id = 4
+   OR product_id = 9;
 
 
 /*2. Write a query that returns all customer purchases and a new calculated column 'price' (quantity * cost_to_customer_per_qty), 
@@ -23,30 +28,64 @@ filtered by customer IDs between 8 and 10 (inclusive) using either:
 	2.  one condition using BETWEEN
 */
 -- option 1
-
+SELECT 
+*,
+	(quantity * cost_to_customer_per_qty) AS PRICE
+FROM customer_purchases
+WHERE customer_id >= 8
+	AND customer_id <=10;
 
 -- option 2
-
+SELECT 
+  *,
+  (quantity * cost_to_customer_per_qty) AS price
+FROM customer_purchases
+WHERE customer_id BETWEEN 8 AND 10;
 
 
 --CASE
 /* 1. Products can be sold by the individual unit or by bulk measures like lbs. or oz. 
 Using the product table, write a query that outputs the product_id and product_name
 columns and add a column called prod_qty_type_condensed that displays the word “unit” 
 if the product_qty_type is “unit,” and otherwise displays the word “bulk.” */
-
-
+SELECT 
+	product_id,
+	product_name,
+	CASE
+		WHEN product_qty_type = 'unit' THEN 'unit'
+		ELSE 'bulk'
+	END AS prod_qty_type_condensed
+FROM product ;
 
 /* 2. We want to flag all of the different types of pepper products that are sold at the market. 
 add a column to the previous query called pepper_flag that outputs a 1 if the product_name 
 contains the word “pepper” (regardless of capitalization), and otherwise outputs 0. */
-
-
+WITH product_flagged AS (
+    SELECT 
+      product_id,
+      product_name,
+      CASE 
+        WHEN product_qty_type = 'unit' THEN 'unit'
+        ELSE 'bulk'
+      END AS prod_qty_type_condensed
+    FROM product
+)
+SELECT 
+  *,
+  CASE 
+    WHEN LOWER(product_name) LIKE '%pepper%' THEN 1
+    ELSE 0
+  END AS pepper_flag
+FROM product_flagged;
 
 --JOIN
 /* 1. Write a query that INNER JOINs the vendor table to the vendor_booth_assignments table on the 
 vendor_id field they both have in common, and sorts the result by vendor_name, then market_date. */
-
+SELECT *
+FROM vendor AS v
+INNER JOIN vendor_booth_assignments AS vba
+	ON v.vendor_id = vba.vendor_id
+ORDER BY v.vendor_name, vba.market_date;
 
 
 
@@ -55,15 +94,27 @@ vendor_id field they both have in common, and sorts the result by vendor_name, t
 -- AGGREGATE
 /* 1. Write a query that determines how many times each vendor has rented a booth 
 at the farmer’s market by counting the vendor booth assignments per vendor_id. */
-
+SELECT 
+  vendor_id,
+  COUNT(*) AS booth_rental_count
+FROM vendor_booth_assignments
+GROUP BY vendor_id;
 
 
 /* 2. The Farmer’s Market Customer Appreciation Committee wants to give a bumper 
 sticker to everyone who has ever spent more than $2000 at the market. Write a query that generates a list 
 of customers for them to give stickers to, sorted by last name, then first name. 
 
 HINT: This query requires you to join two tables, use an aggregate function, and use the HAVING keyword. */
-
+SELECT
+	c.customer_first_name,
+	c.customer_last_name,
+FROM customer AS c
+INNER JOIN customer_purchases AS cp
+	ON c.customer_id = cp.customer_id
+ GROUP BY c.customer_id, c.customer_first_name, c.customer_last_name
+ HAVING SUM (cp.quantity * cp.cost_to_customer_per_qty)  > 2000
+ ORDER BY c.customer_last_name, c.customer_first_name ;
 
 
 --Temp Table
@@ -78,14 +129,30 @@ When inserting the new vendor, you need to appropriately align the columns to be
 VALUES(col1,col2,col3,col4,col5) 
 */
 
+CREATE TABLE temp.new_vendor AS
+SELECT *
+FROM vendor
+
+INSERT INTO temp.new_vendor
+(vendor_id, vendor_name, vendor_type, cendor_owner_first_name, vendor_owner_last_name)
+VALUES
+(10,'Thomass Superfood Store', ' Fresh Focused store', 'Thomas', 'Rosenthal');
 
+SELECT *
+FROM temp.new_vendor
+ORDER BY vendor_id;
 
 -- Date
 /*1. Get the customer_id, month, and year (in separate columns) of every purchase in the customer_purchases table.
 
 HINT: you might need to search for strfrtime modifers sqlite on the web to know what the modifers for month 
 and year are! */
 
+SELECT
+customer_id,
+strftime('%m', purchase_date) AS month,
+strftime('%Y', purchase_date) AS year
+FROM customer_purchases;
 
 
 /* 2. Using the previous query as a base, determine how much money each customer spent in April 2022. 
@@ -94,3 +161,16 @@ Remember that money spent is quantity*cost_to_customer_per_qty.
 HINTS: you will need to AGGREGATE, GROUP BY, and filter...
 but remember, STRFTIME returns a STRING for your WHERE statement!! */
 
+SELECT
+  customer_id,
+  strftime('%m', purchase_date) AS month,
+  strftime('%Y', purchase_date) AS year
+FROM customer_purchases;
+
+SELECT
+customer_id,
+SUM(quantity * cost_to_customer_per_qty) AS total_spent
+FROM customer_purchases
+WHERE strftime('%m', purchase_date) = '04'
+AND strftime('%Y',purchase_date) = '2022'
+GROUP BY customer_id; 

03_instructional_team/sqbpro_originals/module_2.sqbpro

@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="UTF-8"?><sqlb_project><db path="/Users/thomas/Documents/GitHub/02-intro_sql/05_src/sql/farmersmarket.db" readonly="0" foreign_keys="1" case_sensitive_like="0" temp_store="0" wal_autocheckpoint="1000" synchronous="2"/><attached/><window><main_tabs open="structure browser pragmas query" current="3"/></window><tab_structure><column_width id="0" width="300"/><column_width id="1" width="0"/><column_width id="2" width="100"/><column_width id="3" width="12168"/><column_width id="4" width="0"/><expanded_item id="0" parent="1"/><expanded_item id="1" parent="1"/><expanded_item id="2" parent="1"/><expanded_item id="3" parent="1"/></tab_structure><tab_browse><table title="booth" custom_title="0" dock_id="2" table="4,5:mainbooth"/><dock_state state="000000ff00000000fd000000010000000200000536000003a5fc0100000002fb000000160064006f0063006b00420072006f00770073006500310100000000ffffffff0000000000000000fb000000160064006f0063006b00420072006f00770073006500320100000000000005360000019b00ffffff000005360000000000000004000000040000000800000008fc00000000"/><default_encoding codec=""/><browse_table_settings><table schema="main" name="booth" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="136"/><column index="2" value="164"/><column index="3" value="300"/><column index="4" value="108"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table></browse_table_settings></tab_browse><tab_sql><sql name="SQL 2">/* MODULE 2 */
+<?xml version="1.0" encoding="UTF-8"?><sqlb_project><window><main_tabs open="structure browser pragmas query" current="3"/></window><tab_structure><column_width id="0" width="300"/><column_width id="1" width="0"/><column_width id="2" width="100"/><column_width id="3" width="12168"/><column_width id="4" width="0"/><expanded_item id="0" parent="1"/><expanded_item id="1" parent="1"/><expanded_item id="2" parent="1"/><expanded_item id="3" parent="1"/></tab_structure><tab_browse><table title="booth" custom_title="0" dock_id="2" table="4,5:mainbooth"/><dock_state state="000000ff00000000fd000000010000000200000536000003a5fc0100000002fb000000160064006f0063006b00420072006f00770073006500310100000000ffffffff0000000000000000fb000000160064006f0063006b00420072006f00770073006500320100000000000005360000012300ffffff000005360000000000000004000000040000000800000008fc00000000"/><default_encoding codec=""/><browse_table_settings><table schema="main" name="booth" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="136"/><column index="2" value="164"/><column index="3" value="300"/><column index="4" value="108"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table></browse_table_settings></tab_browse><tab_sql><sql name="SELECT*">/* MODULE 2 */
 /* SELECT */
 
 
@@ -13,11 +13,11 @@ SELECT
 
 
 
-/* 4. Select multiple specific columns * /
+/* 4. Select multiple specific columns */
 
 
 
-/* 5. Add a static value in a column */</sql><sql name="SQL 7">/* MODULE 2 */
+/* 5. Add a static value in a column */</sql><sql name="WHERE">/* MODULE 2 */
 /* WHERE */
 
 /* 1. Select only customer 1 from the customer table */
@@ -38,11 +38,11 @@ WHERE
 
 
 
-/* 5. Nulls and Blanks* /
+/* 5. Nulls and Blanks*/
 
 
 
-/* 6. BETWEEN x AND y */</sql><sql name="SQL 10">/* MODULE 2 */
+/* 6. BETWEEN x AND y */</sql><sql name="CASE">/* MODULE 2 */
 /* CASE */
 
 
@@ -61,7 +61,7 @@ SELECT *
 /* 4. Experiment with selecting a different column instead of just a string value */
 
 
-FROM vendor</sql><sql name="SQL 9">/* MODULE 2 */
+FROM vendor</sql><sql name="DISTINCT">/* MODULE 2 */
 /* DISTINCT */
 
 
@@ -81,15 +81,15 @@ SELECT customer_id FROM customer_purchases
 
 
 
-/* 4. Which vendor has sold products to a customer ... and which product was it * /
+/* 4. Which vendor has sold products to a customer ... and which product was it */
 
 
 
 /* 5. Which vendor has sold products to a customer 
 ... and which product was it? 
 ... AND to whom was it sold*/
 
-</sql><sql name="SQL 8">/* MODULE 2 */
+</sql><sql name="INNER_JOIN">/* MODULE 2 */
 /* INNER JOIN */
 
 
@@ -109,7 +109,7 @@ SELECT customer_id FROM customer_purchases
 -- using table aliases
 
 
-</sql><sql name="SQL 11">/* MODULE 2 */
+</sql><sql name="LEFT_JOIN">/* MODULE 2 */
 /* LEFT  JOIN */
 
 
@@ -141,7 +141,7 @@ LEFT JOIN product AS p
 ...Note how the row count changed from 24 to 23
 */	
 
-</sql><sql name="SQL 12">/* MODULE 2 */
+</sql><sql name="multiple_table_joins">/* MODULE 2 */
 /* Multiple Table JOINs */
 
 
@@ -157,4 +157,4 @@ LEFT JOIN product AS p
 
 Why do we have more rows now?*/
 
-</sql><current_tab id="6"/></tab_sql></sqlb_project>
+</sql><current_tab id="0"/></tab_sql></sqlb_project>

03_instructional_team/sqbpro_originals/module_3.sqbpro

@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="UTF-8"?><sqlb_project><db path="/Users/thomas/Documents/GitHub/02-intro_sql/05_src/sql/farmersmarket.db" readonly="0" foreign_keys="1" case_sensitive_like="0" temp_store="0" wal_autocheckpoint="1000" synchronous="2"/><attached/><window><main_tabs open="structure browser pragmas query" current="3"/></window><tab_structure><column_width id="0" width="300"/><column_width id="1" width="0"/><column_width id="2" width="100"/><column_width id="3" width="12168"/><column_width id="4" width="0"/><expanded_item id="0" parent="1"/><expanded_item id="1" parent="1"/><expanded_item id="2" parent="1"/><expanded_item id="3" parent="1"/></tab_structure><tab_browse><table title="booth" custom_title="0" dock_id="4" table="4,5:mainbooth"/><dock_state state="000000ff00000000fd000000010000000200000536000003a5fc0100000003fb000000160064006f0063006b00420072006f00770073006500310100000000ffffffff0000000000000000fb000000160064006f0063006b00420072006f00770073006500320100000000000005360000000000000000fb000000160064006f0063006b00420072006f00770073006500340100000000ffffffff0000012300ffffff000005360000000000000004000000040000000800000008fc00000000"/><default_encoding codec=""/><browse_table_settings><table schema="main" name="booth" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="136"/><column index="2" value="164"/><column index="3" value="300"/><column index="4" value="108"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table></browse_table_settings></tab_browse><tab_sql><sql name="SQL 1">/* MODULE 3 */
+<?xml version="1.0" encoding="UTF-8"?><sqlb_project><window><main_tabs open="structure browser pragmas query" current="3"/></window><tab_structure><column_width id="0" width="300"/><column_width id="1" width="0"/><column_width id="2" width="100"/><column_width id="3" width="12168"/><column_width id="4" width="0"/><expanded_item id="0" parent="1"/><expanded_item id="1" parent="1"/><expanded_item id="2" parent="1"/><expanded_item id="3" parent="1"/></tab_structure><tab_browse><table title="booth" custom_title="0" dock_id="4" table="4,5:mainbooth"/><dock_state state="000000ff00000000fd000000010000000200000536000003a5fc0100000003fb000000160064006f0063006b00420072006f00770073006500310100000000ffffffff0000000000000000fb000000160064006f0063006b00420072006f00770073006500320100000000000005360000000000000000fb000000160064006f0063006b00420072006f00770073006500340100000000ffffffff0000012300ffffff000005360000000000000004000000040000000800000008fc00000000"/><default_encoding codec=""/><browse_table_settings><table schema="main" name="booth" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="136"/><column index="2" value="164"/><column index="3" value="300"/><column index="4" value="108"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table></browse_table_settings></tab_browse><tab_sql><sql name="COUNT">/* MODULE 3 */
 /* COUNT */
 
 
@@ -18,7 +18,7 @@
     4. How many unique products were bought */
 
 
-</sql><sql name="SQL 10">/* MODULE 3 */
+</sql><sql name="SUM_AVG">/* MODULE 3 */
 /* SUM &amp; AVG */
 
 
@@ -29,7 +29,7 @@
 /* 2. How much does each customer spend on average */
 
 
-</sql><sql name="SQL 11">/* MODULE 3 */
+</sql><sql name="MIN_MAX">/* MODULE 3 */
 /* MIN &amp; MAX */
 
 
@@ -54,7 +54,7 @@
 ... not particularly useful? */
 
 
-</sql><sql name="SQL 12">/* MODULE 3 */
+</sql><sql name="arithmitic">/* MODULE 3 */
 /* Arithmitic */
 
 
@@ -68,7 +68,7 @@ SELECT
 
 /* 3. What about every third?  */
 
-</sql><sql name="SQL 13">/* MODULE 3 */
+</sql><sql name="HAVING">/* MODULE 3 */
 /* HAVING */
 
 
@@ -81,7 +81,7 @@ Filter to customer_id between 1 and 5 and total_cost &gt; 50
 /* 2. How many products were bought?
 Filter to number of purchases between 300 and 500  */
 
-</sql><sql name="SQL 13">/* MODULE 3 */
+</sql><sql name="subquery_joins">/* MODULE 3 */
 /* Subquery FROM */
 
 
@@ -94,7 +94,7 @@ Filter to number of purchases between 300 and 500  */
 /* 2. What is the single item that has been bought in the greatest quantity?*/
 
 
-</sql><sql name="SQL 14">/* MODULE 3 */
+</sql><sql name="subquery_where">/* MODULE 3 */
 /* Subquery WHERE */
 
 
@@ -105,7 +105,7 @@ Filter to number of purchases between 300 and 500  */
 
 /* 2. What is the name of the vendor who sells pie */
 
-</sql><sql name="SQL 15">/* MODULE 3 */
+</sql><sql name="CTE">/* MODULE 3 */
 /* Common Table Expression (CTE) */
 
 
@@ -118,7 +118,7 @@ SELECT
 
 /* ... re-aggregate the daily sales for each WEEK instead now  */
 
-</sql><sql name="SQL 16">/* MODULE 3 */
+</sql><sql name="temp_table">/* MODULE 3 */
 /* Temp Tables */
 
 
@@ -142,7 +142,7 @@ CREATE TABLE temp.new_vendor_inventory AS
 /* 2. put the previous table into another temp table, e.g. as temp.new_new_vendor_inventory  */
 
 
-</sql><sql name="SQL 18">/* MODULE 3 */
+</sql><sql name="dates">/* MODULE 3 */
 /* Date functions */