From f4a5d4ee76781ea814039ebf4fd57180221892ca Mon Sep 17 00:00:00 2001 From: Naiyara Date: Wed, 5 Nov 2025 19:41:56 -0500 Subject: [PATCH 1/4] Completed sql file (does not include sec 1 & 4) --- .../assignments/DC_Cohort/assignment1.sql | 91 +++++--- ...rmers_market_logical_data_model.drawio.pdf | Bin 0 -> 36351 bytes .../live_code/DC/module_2/module_2.sqbpro | 194 +++++++++++++++--- .../live_code/DC/module_3/module_3.sqbpro | 72 +++++-- 4 files changed, 284 insertions(+), 73 deletions(-) create mode 100644 02_activities/assignments/DC_Cohort/naiyara_farmers_market_logical_data_model.drawio.pdf diff --git a/02_activities/assignments/DC_Cohort/assignment1.sql b/02_activities/assignments/DC_Cohort/assignment1.sql index c992e3205..920439274 100644 --- a/02_activities/assignments/DC_Cohort/assignment1.sql +++ b/02_activities/assignments/DC_Cohort/assignment1.sql @@ -1,21 +1,23 @@ /* 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 IN (4, 9); /*2. Write a query that returns all customer purchases and a new calculated column 'price' (quantity * cost_to_customer_per_qty), filtered by customer IDs between 8 and 10 (inclusive) using either: @@ -23,30 +25,57 @@ 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. */ - +SELECT +product_id, +product_name, +CASE +WHEN product_qty_type = 'unit' THEN 'unit' +ELSE 'bulk' +END AS product_qty_condensed, +CASE +WHEN LOWER(product_name) LIKE '%pepper%' THEN 1 +ELSE 0 +END AS pepper_flag +FROM product; --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 +INNER JOIN vendor_booth_assignments +ON vendor.vendor_id = vendor_booth_assignments.vendor_id +ORDER BY vendor_name, market_date; @@ -55,7 +84,11 @@ 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_rentals +FROM vendor_booth_assignments +GROUP BY vendor_id; /* 2. The Farmer’s Market Customer Appreciation Committee wants to give a bumper @@ -63,7 +96,17 @@ sticker to everyone who has ever spent more than $2000 at the market. Write a qu of customers for them to give stickers to, sorted by last name, then first name. HINT: This query requires you to join two tables, use an aggregate function, and use the HAVING keyword. */ - +SELECT +c.customer_id, +c.customer_first_name, +c.customer_last_name, +SUM(cp.quantity * cp.cost_to_customer_per_qty) AS total_spent +FROM customer AS c +JOIN customer_purchases AS cp +ON c.customer_id = cp.customer_id +GROUP BY c.customer_id +HAVING total_spent > 2000 +ORDER BY c.customer_last_name, c.customer_first_name; --Temp Table @@ -78,19 +121,11 @@ When inserting the new vendor, you need to appropriately align the columns to be VALUES(col1,col2,col3,col4,col5) */ +CREATE TEMP TABLE new_vendor AS +SELECT * +FROM vendor +INSERT INTO new_vendor (vendor_id, vendor_name, vendor_type, vendor_owner_first_name, vendor_owner_last_name) +VALUES (10, 'Thomass Superfood Store', 'Fresh Focused store', 'Thomas', 'Rosenthal'); --- Date -/*1. Get the customer_id, month, and year (in separate columns) of every purchase in the customer_purchases table. - -HINT: you might need to search for strfrtime modifers sqlite on the web to know what the modifers for month -and year are! */ - - - -/* 2. Using the previous query as a base, determine how much money each customer spent in April 2022. -Remember that money spent is quantity*cost_to_customer_per_qty. - -HINTS: you will need to AGGREGATE, GROUP BY, and filter... -but remember, STRFTIME returns a STRING for your WHERE statement!! */ diff --git a/02_activities/assignments/DC_Cohort/naiyara_farmers_market_logical_data_model.drawio.pdf b/02_activities/assignments/DC_Cohort/naiyara_farmers_market_logical_data_model.drawio.pdf new file mode 100644 index 0000000000000000000000000000000000000000..c8b7a147b7836e16b5bf4b5109b1c476e77ef2bd GIT binary patch literal 36351 zcmagF18^td(=Hm@8*AfaW81cE^Ot0!Uu@g9Z9Ca`W81c!Y;OMNe7EZRs?I%k-kE-$ z>FMfvtE>9O%rv>8s5l)HJqH}Q|Mvk0$4SIUWN&N@$IA=HAZ`V4HghCm5C<4Jn~9p4 z*qfTcG02+PSvXq~ad0rf@$c4o<#~1Nak@X&Oi}gm^SjvsrVuk_)lNo_DXefo zpo+G2Gv;phH@7nxhwHi9^Y9qp1$=xtBTODV{f&x&tno>oy;!%$j+LOCM`jUBlSQ(a zH|9-%7CvsglyS0_pNxjBUm*hk8p-PW{S8^{x()G|tk{)4HmXQ;u1U?u`#nm9l%J5` 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/* MODULE 2 */ +
/* MODULE 2 */ /* SELECT */ /* 1. Select everything in the customer table */ -SELECT +SELECT * +FROM customer; /* 2. Use sql as a calculator */ - +SELECT 1+1 as addition, 10*5 as multiplication, pi() as pie; /* 3. Add order by and limit clauses */ +SELECT * +FROM customer +ORDER BY customer_first_name +LIMIT 10; +/* 4. Select multiple specific columns */ +SELECT customer_id, customer_first_name +FROM customer; - -/* 4. Select multiple specific columns * / - - - -/* 5. Add a static value in a column *//* MODULE 2 */ +/* 5. Add a static value in a column */ +SELECT 2025 as this_year, 'October' as this_month, customer_id +FROM customer/* MODULE 2 */ /* WHERE */ /* 1. Select only customer 1 from the customer table */ -SELECT * +SELECT * FROM customer -WHERE +WHERE customer_id =1; /* 2. Differentiate between AND and OR */ - +SELECT * +FROM customer +WHERE customer_id = 1 +OR customer_id = 2; /* 3. IN */ - - +SELECT * +FROM customer +WHERE customer_id IN (3,4,5) +OR customer_postal_code IN ('M4M', 'MIL'); /* 4. LIKE */ +SELECT * FROM product +WHERE product_name LIKE '%pepper%'; +/* 5. Nulls and Blanks*/ -/* 5. Nulls and Blanks* / +SELECT * FROM product +WHERE product_size IS NULL -- null +OR product_size = ''; -- blank +/* 6. BETWEEN x AND y */ +SELECT * +FROM customer +WHERE customer_id BETWEEN 1 AND 20; +--dates -/* 6. BETWEEN x AND y *//* MODULE 2 */ +--SELECT market_date +--FROM market_date_info +--WHERE market_date BETWEEN '2022-10-01' AND '2022-10-31'/* MODULE 2 */ /* CASE */ SELECT * /* 1. Add a CASE statement declaring which days vendors should come */ - +, CASE WHEN vendor_type = 'Fresh Focused' THEN 'Wednesday' + WHEN vendor_type = 'Prepared Foods' THEN 'Thursday' + ELSE 'Saturday' +END as day_of_specialty /* 2. Add another CASE statement for Pie Day */ - +, CASE WHEN vendor_name = "Annie's Pies" -- double quotes work here + THEN 'Annie is great' + END as pie_day /* 3. Add another CASE statement with an ELSE clause to handle rows evaluating to False */ +,CASE WHEN vendor_name LIKE '%pie%' + THEN 'Wednesday' + ELSE 'Friday' + END as also_pie_day -/* 4. Experiment with selecting a different column instead of just a string value */ +FROM vendor; -FROM vendor/* MODULE 2 */ +/* 4. Experiment with selecting a different column instead of just a string value */ +SELECT * +,CASE WHEN cost_to_customer_per_qty < '1.00' +THEN cost_to_customer_per_qty*5 +ELSE cost_to_customer_per_qty +END AS inflation + +FROM customer_purchases/* MODULE 2 */ /* DISTINCT */ /* 1. Compare how many customer_ids are the customer_purchases table, one select with distinct, one without */ -- 4221 rows -SELECT customer_id FROM customer_purchases +SELECT customer_id FROM customer_purchases; +SELECT DISTINCT customer_id FROM customer_purchases; /* 2. Compare the difference between selecting market_day in market_date_info, with and without distinct: what do these difference mean?*/ - +SELECT market_day +FROM market_date_info; +-- market only open on two days /* 3. Which vendor has sold products to a customer */ +SELECT vendor_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 */ +SELECT DISTINCT vendor_id, product_id +FROM customer_purchases; /* 5. Which vendor has sold products to a customer ... and which product was it? ... AND to whom was it sold*/ - +SELECT DISTINCT vendor_id, product_id +FROM customer_purchases /* MODULE 2 */ /* INNER JOIN */ @@ -97,7 +141,16 @@ SELECT customer_id FROM customer_purchases ... use an INNER JOIN to see only products that have been purchased */ -- without table aliases +SELECT product_name, -- coming from the product TABLE +vendor_id, -- rest are coming from customer_purchases +market_date, +customer_id, +customer_purchases.product_id, +product.product_id +FROM product +INNER JOIN customer_purchases + ON customer_purchases.product_id = product.product_id; @@ -107,6 +160,17 @@ SELECT customer_id FROM customer_purchases Add customers' first and last names with an INNER JOIN */ -- using table aliases +SELECT DISTINCT +vendor_id, +product_id, +c.customer_id, +customer_first_name, -- coming from customer +customer_last_name -- coming from customer + + +FROM customer_purchases as cp +INNER JOIN customer as c + ON c.customer_id = cp.customer_id /* MODULE 2 */ @@ -116,15 +180,51 @@ SELECT customer_id FROM customer_purchases /* 1. There are products that have been bought ... but are there products that have not been bought? Use a LEFT JOIN to find out*/ +SELECT DISTINCT +p.product_id +,cp.product_id as [cp.product_id] +,product_name + +FROM product as p +LEFT JOIN customer_purchases as cp + ON p.product_id = cp.product_id; + + +/* 2. Directions of LEFT JOINs matter ...*/ +-- only products that have been sold ... because there are no product ids in CP that ARENT in product +SELECT DISTINCT +p.product_id +,cp.product_id as [cp.product_id] +,product_name + +FROM customer_purchases as p +LEFT JOIN product as cp + ON p.product_id = cp.product_id /* 2. Directions of LEFT JOINs matter ...*/ +-- only products that have been sold ... because there are no product ids in CP that ARENT in product +SELECT DISTINCT +p.product_id +,cp.product_id as [cp.product_id] +,product_name +FROM customer_purchases as p +LEFT JOIN product as cp + ON p.product_id = cp.product_id +/* 3. As do which table's values you filter on ... */ +SELECT DISTINCT +p.product_id +,cp.product_id as [cp.product_id] +,product_name -/* 3. As do which values you filter on ... */ +FROM product as p +LEFT JOIN customer_purchases as cp + ON p.product_id = cp.product_id +WHERE p.product_id BETWEEN 1 AND 6 -- if we pick product, 6 rows (1-6), otherwise 5 rows because zinnias not been bought @@ -141,7 +241,12 @@ LEFT JOIN product AS p ...Note how the row count changed from 24 to 23 */ -/* MODULE 2 */ +SELECT * + +FROM product AS p +LEFT JOIN product_category AS pc + ON pc.product_category_id = p.product_category_id + ORDER by pc.product_category_id/* MODULE 2 */ /* Multiple Table JOINs */ @@ -149,12 +254,37 @@ LEFT JOIN product AS p (Which vendor has sold products to a customer AND which product was it AND to whom was it sold) Replace all the IDs (customer, vendor, and product) with the names instead*/ - - - -/* 2. Select product_category_name, everything from the product table, and then LEFT JOIN the customer_purchases table +SELECT DISTINCT +--v.vendor_id +vendor_name +--, product_id +,product_name +--,customer_id -- first/last name +,customer_first_name +,customer_last_name + +FROM customer_purchases as cp +INNER JOIN customer as c + ON c.customer_id = cp.customer_id +INNER JOIN vendor as v + ON v.vendor_id = cp.vendor_id +INNER JOIN product as p + ON p.product_id = cp.product_id; + + +/* 2. Select product_category_name, everything from the product table, +and then LEFT JOIN the customer_purchases table ... how does this LEFT JOIN affect the number of rows? Why do we have more rows now?*/ +SELECT product_category_name, p.*, cp.product_id as productid_in_purchases_table + +FROM product_category as pc +INNER JOIN product as p + ON p.product_category_id = pc.product_category_id +LEFT JOIN customer_purchases as cp + ON cp.product_id = p.product_id + +ORDER BY cp.product_id diff --git a/04_this_cohort/live_code/DC/module_3/module_3.sqbpro b/04_this_cohort/live_code/DC/module_3/module_3.sqbpro index 3d421003d..9459f89d4 100644 --- a/04_this_cohort/live_code/DC/module_3/module_3.sqbpro +++ b/04_this_cohort/live_code/DC/module_3/module_3.sqbpro @@ -1,33 +1,57 @@ -
/* MODULE 3 */ +/* MODULE 3 */ /* COUNT */ /* 1. Count the number of products */ - + SELECT COUNT(product_id) as num_of_product + FROM product; /* 2. How many products per product_qty_type */ - - +SELECT product_qty_type, COUNT(product_id) as num_of_product +FROM product +GROUP BY product_qty_type; /* 3. How many products per product_qty_type and per their product_size */ +SELECT product_size +,product_qty_type +, COUNT(product_id) as num_of_product +FROM product +GROUP BY product_size, product_qty_type - +ORDER BY product_qty_type; /* COUNT DISTINCT 4. How many unique products were bought */ +SELECT COUNT(DISTINCT product_id) as bought_prods +FROM customer_purchases /* MODULE 3 */ /* SUM & AVG */ -/* 1. How much did customers spend each day */ +/* 1. How much did customers spend each (per) day */ +SELECT +market_date +,customer_id +,SUM(quantity*cost_to_customer_per_qty) as total_spend +FROM customer_purchases +GROUP BY market_date,customer_id; /* 2. How much does each customer spend on average */ +SELECT +customer_first_name +,customer_last_name +,ROUND(AVG(quantity*cost_to_customer_per_qty),2) as avg_spend + +FROM customer_purchases as cp +INNER JOIN customer as c + ON c.customer_id = cp.customer_id +GROUP BY c.customer_id /* MODULE 3 */ /* MIN & MAX */ @@ -36,25 +60,47 @@ /* 1. What is the most expensive product ...pay attention to how it doesn't handle ties very well */ - +SELECT product_name, max(original_price) as most_expensive -/* 2. Prove that max is working */ +FROM vendor_inventory as vi +INNER JOIN product as p + ON p.product_id = vi.product_id; + + /* 2. Prove that max is working */ +SELECT DISTINCT +product_name, +original_price +FROM vendor_inventory as vi +INNER JOIN product as p + ON p.product_id = vi.product_id; /* 3. Find the minimum price per each product_qty_type */ +SELECT product_name +,product_qty_type +,min(original_price) +FROM vendor_inventory as vi +INNER JOIN product as p + ON p.product_id = vi.product_id +GROUP BY product_qty_type; /* 4. Prove that min is working */ +SELECT DISTINCT product_name +,product_qty_type +--,min(original_price) +,original_price - +FROM vendor_inventory as vi +INNER JOIN product as p + ON p.product_id = vi.product_id; /* 5. Min/max on a string ... not particularly useful? */ - - -/* MODULE 3 */ +SELECT max(product_name) +FROM product/* MODULE 3 */ /* Arithmitic */ @@ -163,4 +209,4 @@ SELECT b. number of YEARS between now and market_date c. number of HOURS bewtween now and market_date */ - + From ca9332bb6b61ab419fefd295716442caa999d894 Mon Sep 17 00:00:00 2001 From: Naiyara Date: Wed, 5 Nov 2025 20:50:04 -0500 Subject: [PATCH 2/4] New changes: .sql file code completed, section 1 logical data model completed as pdf, section 4 .md file edited in text editor. --- 02_activities/assignments/DC_Cohort/Assignment1.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/02_activities/assignments/DC_Cohort/Assignment1.md b/02_activities/assignments/DC_Cohort/Assignment1.md index f78778f5b..680b43bc3 100644 --- a/02_activities/assignments/DC_Cohort/Assignment1.md +++ b/02_activities/assignments/DC_Cohort/Assignment1.md @@ -205,5 +205,10 @@ Consider, for example, concepts of fariness, inequality, social structures, marg ``` -Your thoughts... +My thoughts on social identity: I suppose databases serve the purpose of binning real-life complexities into distinct categories and binaries, and by virtue of that may not reflect reality. +Something I notice often in different forms (for the eventual purpose of data collection) is racial identity, which can become complicated for +diaspora communities are due to the nature of changing man-made geographical/geopolitical borders. +My thoughts on data use: Often to get different tasks done (medical, government services) +we have to consent to the collection of our data, with general descriptions of their future use, but we do not know for certain what will be enquired from our data/ +demographics in the future. ``` From fd7c9551a4b85e00f80968012caef7b203f369f4 Mon Sep 17 00:00:00 2001 From: Naiyara Date: Wed, 5 Nov 2025 20:52:01 -0500 Subject: [PATCH 3/4] small typo changed in .md file --- 02_activities/assignments/DC_Cohort/Assignment1.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/02_activities/assignments/DC_Cohort/Assignment1.md b/02_activities/assignments/DC_Cohort/Assignment1.md index 680b43bc3..d035abc54 100644 --- a/02_activities/assignments/DC_Cohort/Assignment1.md +++ b/02_activities/assignments/DC_Cohort/Assignment1.md @@ -207,7 +207,7 @@ Consider, for example, concepts of fariness, inequality, social structures, marg ``` My thoughts on social identity: I suppose databases serve the purpose of binning real-life complexities into distinct categories and binaries, and by virtue of that may not reflect reality. Something I notice often in different forms (for the eventual purpose of data collection) is racial identity, which can become complicated for -diaspora communities are due to the nature of changing man-made geographical/geopolitical borders. +diaspora communities and due to the nature of changing man-made geographical/geopolitical borders. My thoughts on data use: Often to get different tasks done (medical, government services) we have to consent to the collection of our data, with general descriptions of their future use, but we do not know for certain what will be enquired from our data/ demographics in the future. From 7ee2db5e901f517d3351f7d2f8104723f1beefbc Mon Sep 17 00:00:00 2001 From: Naiyara Date: Wed, 12 Nov 2025 21:28:29 -0500 Subject: [PATCH 4/4] Completed 3 components of assignment #2 (mk entries on .md, code completion of .sql, added .pdf logical model) --- .../assignments/DC_Cohort/Assignment2.md | 8 + .../assignments/DC_Cohort/assignment2.sql | 163 ++++++++++++++++-- .../assignment2_logical_model.drawio.pdf | Bin 0 -> 43058 bytes .../live_code/DC/module_3/module_3.sqbpro | 27 +-- 4 files changed, 170 insertions(+), 28 deletions(-) create mode 100644 02_activities/assignments/DC_Cohort/assignment2_logical_model.drawio.pdf diff --git a/02_activities/assignments/DC_Cohort/Assignment2.md b/02_activities/assignments/DC_Cohort/Assignment2.md index 9b804e9ee..d7598da39 100644 --- a/02_activities/assignments/DC_Cohort/Assignment2.md +++ b/02_activities/assignments/DC_Cohort/Assignment2.md @@ -55,6 +55,9 @@ The store wants to keep customer addresses. Propose two architectures for the CU ``` Your answer... +To overwrite change: slowly changing dimensions type 1 - old address is overwritten +To retain change: slowly changing dimensions type 2 - old address kept as history, so dates as well as a column indicating if adress is current is important + ``` *** @@ -184,4 +187,9 @@ Consider, for example, concepts of labour, bias, LLM proliferation, moderating c ``` Your thoughts... + +Artificial intelligence programs are intelligent; in the way they are trained and the way calculations and collections of strings can be put together with speed and with logical sense. +Humans, like all biological entities, have are disordered. We are functional systems, but we have biological limitations. We have rapid recall of our brain “databases” based on our senses. Touch, sound, taste brings back memory and result in reaction with often very desirable outcomes for other humans. +Limitation of computational structures include lack of empathy. This is why the efficacy of AI mental health resources should be approached with caution. Emotional judgment calls are a skill acquired by humans through life experience. This can be incredibly difficult to train into a system, if possible, at all. + ``` diff --git a/02_activities/assignments/DC_Cohort/assignment2.sql b/02_activities/assignments/DC_Cohort/assignment2.sql index 5ad40748a..c56cf45d3 100644 --- a/02_activities/assignments/DC_Cohort/assignment2.sql +++ b/02_activities/assignments/DC_Cohort/assignment2.sql @@ -19,8 +19,11 @@ HINT: keep the syntax the same, but edited the correct components with the strin The `||` values concatenate the columns into strings. Edit the appropriate columns -- you're making two edits -- and the NULL rows will be fixed. All the other rows will remain the same.) */ - - +SELECT +product_name || ', ' || +COALESCE(product_size, '') || ' (' || +COALESCE(product_qty_type, 'unit') || ')' AS product_description +FROM product; --Windowed Functions /* 1. Write a query that selects from the customer_purchases table and numbers each customer’s @@ -32,18 +35,49 @@ each new market date for each customer, or select only the unique market dates p (without purchase details) and number those visits. HINT: One of these approaches uses ROW_NUMBER() and one uses DENSE_RANK(). */ - +SELECT +customer_id, +market_date, +ROW_NUMBER() OVER ( +PARTITION BY customer_id +ORDER BY market_date +) AS visit_number +FROM customer_purchases; /* 2. Reverse the numbering of the query from a part so each customer’s most recent visit is labeled 1, then write another query that uses this one as a subquery (or temp table) and filters the results to only the customer’s most recent visit. */ - +SELECT * +FROM ( +SELECT +customer_id, +market_date, +DENSE_RANK() OVER ( +PARTITION BY customer_id +ORDER BY market_date DESC +) AS visit_number +FROM ( + SELECT DISTINCT customer_id, market_date + FROM customer_purchases + ) + ) + WHERE visit_number = 1; /* 3. Using a COUNT() window function, include a value along with each row of the customer_purchases table that indicates how many different times that customer has purchased that product_id. */ - - +SELECT +product_id, +vendor_id, +market_date, +customer_id, + quantity, +cost_to_customer_per_qty, +transaction_time, +COUNT(*) OVER ( +PARTITION BY customer_id, product_id +) AS times_customer_purchased_product +FROM customer_purchases; -- String manipulations /* 1. Some product names in the product table have descriptions like "Jar" or "Organic". @@ -57,11 +91,20 @@ Remove any trailing or leading whitespaces. Don't just use a case statement for Hint: you might need to use INSTR(product_name,'-') to find the hyphens. INSTR will help split the column. */ - +SELECT +product_name, +TRIM( +SUBSTR( +product_name, +INSTR(product_name, '-') + 1 +) +) AS description +FROM product; /* 2. Filter the query to show any product_size value that contain a number with REGEXP. */ - - +SELECT * +FROM product +WHERE product_size REGEXP '[0-9]'; -- UNION /* 1. Using a UNION, write a query that displays the market dates with the highest and lowest total sales. @@ -72,9 +115,34 @@ HINT: There are a possibly a few ways to do this query, but if you're struggling "best day" and "worst day"; 3) Query the second temp table twice, once for the best day, once for the worst day, with a UNION binding them. */ - - - +WITH total_sales_per_day AS ( +SELECT +market_date, +SUM(quantity * cost_to_customer_per_qty) AS total_sales +FROM customer_purchases +GROUP BY market_date +), +ranked_sales AS ( +SELECT +market_date, +total_sales, +RANK() OVER (ORDER BY total_sales DESC) AS best_day_rank, +RANK() OVER (ORDER BY total_sales ASC) AS worst_day_rank +FROM total_sales_per_day +) +SELECT +'Best Day' AS label, +market_date, +total_sales +FROM ranked_sales +WHERE best_day_rank = 1 +UNION +SELECT + 'Worst Day' AS label, + market_date, + total_sales +FROM ranked_sales +WHERE worst_day_rank = 1; /* SECTION 3 */ @@ -89,6 +157,23 @@ Think a bit about the row counts: how many distinct vendors, product names are t How many customers are there (y). Before your final group by you should have the product of those two queries (x*y). */ +WITH vendor_products AS ( +SELECT vi.vendor_id, v.vendor_name, vi.product_id, p.product_name, vi.original_price +FROM vendor_inventory vi + JOIN vendor v ON vi.vendor_id = v.vendor_id +JOIN product p ON vi.product_id = p.product_id +), +customer_count AS ( + SELECT COUNT(*) AS num_customers + FROM customer +) +SELECT + vp.vendor_name, + vp.product_name, + vp.original_price * 5 * cc.num_customers AS total_revenue +FROM vendor_products vp +CROSS JOIN customer_count cc +ORDER BY vp.vendor_name, vp.product_name; -- INSERT @@ -97,19 +182,42 @@ This table will contain only products where the `product_qty_type = 'unit'`. It should use all of the columns from the product table, as well as a new column for the `CURRENT_TIMESTAMP`. Name the timestamp column `snapshot_timestamp`. */ - +CREATE TABLE product_units AS +SELECT * +, CURRENT_TIMESTAMP AS snapshot_timestamp +FROM product +WHERE product_qty_type = 'unit'; /*2. Using `INSERT`, add a new row to the product_units table (with an updated timestamp). This can be any product you desire (e.g. add another record for Apple Pie). */ - - +INSERT INTO product_units ( +product_id, +product_name, +product_size, +product_category_id, +product_qty_type, + snapshot_timestamp +) +VALUES ( + 7, + 'Apple Pie', + '10"', + 3, + 'unit', + CURRENT_TIMESTAMP +); -- DELETE /* 1. Delete the older record for the whatever product you added. HINT: If you don't specify a WHERE clause, you are going to have a bad time.*/ - - +DELETE FROM product_units +WHERE product_id = 7 +AND snapshot_timestamp < ( +SELECT MAX(snapshot_timestamp) + FROM product_units +WHERE product_id = 7 + ); -- UPDATE /* 1.We want to add the current_quantity to the product_units table. @@ -128,6 +236,27 @@ Finally, make sure you have a WHERE statement to update the right row, you'll need to use product_units.product_id to refer to the correct row within the product_units table. When you have all of these components, you can run the update statement. */ +ALTER TABLE product_units +ADD COLUMN current_quantity INT; + +SELECT vi.product_id, vi.quantity +FROM vendor_inventory vi +WHERE vi.market_date = ( +SELECT MAX(market_date) +FROM vendor_inventory +WHERE product_id = vi.product_id +); + +UPDATE product_units +SET current_quantity = COALESCE( + ( +SELECT vi.quantity +FROM vendor_inventory vi + WHERE vi.product_id = product_units.product_id + ORDER BY vi.market_date DESC +LIMIT 1 +), 0 +); diff --git a/02_activities/assignments/DC_Cohort/assignment2_logical_model.drawio.pdf b/02_activities/assignments/DC_Cohort/assignment2_logical_model.drawio.pdf new file mode 100644 index 0000000000000000000000000000000000000000..69b56d866759c9eeaaac4a904f22f0a8c6c63abb GIT binary patch literal 43058 zcmafYb8s(F(`IgL+s=(`+sTb>+t!V3>&CWi+xo?}?alkWyH&e??Wt2w_vxN_s%vWM zJUw&B{)mXtGSaa_lllJ)XlM>X20}YSOK2V*XnHXVYiAQjLV7W417{Nv6C*og6KHxF z6I(N9b3#T|W_D;kK4>RrM-u}ZX!oos&2?KGc0`};njI(q`GK|@U`TMoHR!iE;Bc@5 zPW!~h;AFNkrH6Z%Emt+_aB5CuWE_|(RThM?bWSrjuo`d ziKZ_a(OgmY&IsYW{=?hI6;sjS)pQXiNR$Y0w$2&`(w~1Hx#~7Lm`ju$fdnK!t44Zm zyk^cpLVFA@7dvMj4oeB5T7b)yW!)voxt*VNpe2$PkW^0V9Q9u-jVj}eCT($*>(5-6O&sCKf3_ZeV zrKb!Gh#3e5s0L^iByFAL=Ira*EeAca0s}!_Z=1Jz`}?^Ny`p0YdIwCq;@k>t7XwJZ z!kuMjldJ1OgRVK1T36|gS=glsQULfbJdjW4%x?%J^QawHq%8PlZiTRJ0Z3qpjh2ab zxo61Ui5F||n00#^0F%1nsQS(-utZRJO?B@85S%k`=VX8CW<J;b2$Ot6UvdKFJv~{Y_YFSex@MA$qiCd`ExDujnB}bvQ?%jv|+|Fa?6MX z6rgHo8`^uPEGG-2jA^tti8GB`YeDN;I2*Us1mS;N;C9!0NL#3Cp(FvTjT&67sDnsu zxl=0X-)m_$UFQcxSoD~;Qny=;^?H{r#^I|8w; zB9Yp#9a$ij3$=`YjEo5f&l;gJdN;>Zf`d!o3B7G2PHVd0Yv7=IH>Iv zjk%9KZSd+>rR{2jwVXX777exhDjm3iA7qoEnukWP0kX5tmzSu01I=F&gm|n5qlO~23xYr*Sl8x8l8D>r=KNX8#E8Dk7CioD*{plLHNg9UqF|!Keo4ivD#%;ND@8Gaxx!`FlVi~ zGW!oR1WTTt7uDaL)qk=bKoOCnI;cnX;dIbV6@-n=pcq_LNuY%`}0Ta_X70~(3 z(0LFxWR5Hl-nLtEHiv?{g~0R7DvJJ@n)|STMD_A~Y1S)TPp!Z|h0bB1Q-vxE7@ocy zn~hefHE$l+{Ha=hIz)u}_LS$vRULnGpUI(_T{%QD6_2)$;en%o&?>&;W-4_A2XB?X zYzGr{T0U}Cps>(#6f#My#X#@+xVaSx|_8Bm&x+@=(hRTU*giA6kZt-_x0kypns3 z70mSKlrY&LqIWCMojpr4w_s-QQUj}+8B`*bW4hF+K4e=Nu55&K+on9kAfZb%dYV5{ zfNy%F^T8=SR^ZGx8@ACk)=Na_qcy!H3Dt|ylpiriZNW;cDzj!=%=Thfi@|i}oS#uT zXR~Oa9zl2J+s|XeBh$6Ob7CaFB#jlWL0<3rgLV06D1)cvEHct^-#o0FQe={mg>QKr zpVg8r{-klqlkRxx{H4j7P?4pt+T_@2Y~okx<2J0j+O5Q!ru?+q`GoeO`YzXG!sT~K z^7Qm+dkOF{#q^l~Z7K}1T8N(_m)~YED50eSFM!&2vuC4ZCSf|=f9Xp5{-xvFtO9Lf zYy7{p;K%!qfh2*<0E*yca!kj$ga339jGM+fTVl%BMM1T+TL>wAuxM zI3RmL7R;h4_4Ygs*#wY*0LN@HR_WBvRbY;rfA8C0&D@+FCSExNK7pz;{p4cvc|Ut^ z|4spiUBYz8@q2mY-P;O$!04yBdyd@EaS;6)%wKVQ(>SKnX0RJ~5bz-&+^#k6TdR2T zc^h2#drZ^oew{xZ1D2!fcccS!3ihYTT)`~VDjF4Zv<&DDBYU%<+^zE!_OBI$#Jh&{ zv72}I(|$To7lFXXMU0BhFjj~XPy(EQ#=L{8*=GB47Z5+BeM)uFgjb_s=dU=;u1+fr zGYs~wGeP~yuD|!xK)6x44F2ZW94GA-c{RD{D}6xF5X1U(gluyqgnt7-U^MgS?kRwO z4Tg^;GOYPucfZ><1s;A7HrC=Ig~>e4@K5Q!Co?XLLSMP}u!)D(=-mk}yKUoPyY{xi zg3cpB;XY&gzye40PYHnu)GNk$VZoG5{QlE0s>FL!sWuX{wm?ojo5Q!ebO5VJBuDC? 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/* MODULE 3 */ +
/* MODULE 3 */ /* COUNT */ @@ -188,20 +188,22 @@ CREATE TABLE temp.new_vendor_inventory AS /* 2. put the previous table into another temp table, e.g. as temp.new_new_vendor_inventory */ -/* MODULE 3 */ -/* Date functions */ - - -/* 1. now */ -SELECT +/* 1. now */ +SELECT DISTINCT +DATE('now') as [now] +,DATETIME('now') [rightnow] +,DATE() as[todaysdate] /* 2. strftime */ - - +,strftime('%Y/%m','now') as [1] +,strftime('%Y-%m-%d','now','+50 days') as the_future +,market_date +,strftime('%m-%d-%Y',market_date,'+50 days','-1 year') as the_past /* 3. adding dates, e.g. last date of the month */ - +--last date of last month +,DATE(market_date,'start of month','-1 day') as end_of_prev_month /* 4. difference between dates, @@ -209,4 +211,7 @@ SELECT b. number of YEARS between now and market_date c. number of HOURS bewtween now and market_date */ - + ,market_date + ,julianday('now') - julianday(market_date) as datesbetweenmktdate -- number of days between now and each market date +,(julianday('now') - julianday(market_date)) / 365.25 +,(julianday('now') - julianday(market_date)) * 24