UofT-DSI | <SQL> - Assignment <1>

02_activities/assignments/DC_Cohort/Assignment1.md

@@ -14,10 +14,10 @@
     * Open a private window in your browser. Copy and paste the link to your pull request into the address bar. Make sure you can see your pull request properly. This helps the technical facilitator and learning support staff review your submission easily.
 
 Checklist:
-- [ ] Create a branch called `assignment-one`.
-- [ ] Ensure that the repository is public.
-- [ ] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
-- [ ] Verify that the link is accessible in a private browser window.
+- [ √] Create a branch called `assignment-one`.
+- [ √] Ensure that the repository is public.
+- [ √] Review [the PR description guidelines](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md#guidelines-for-pull-request-descriptions) and adhere to them.
+- [ √] Verify that the link is accessible in a private browser window.
 
 If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via our Slack. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.
 
@@ -204,6 +204,8 @@ Link if you encounter a paywall: https://archive.is/srKHV or https://web.archive
 Consider, for example, concepts of fariness, inequality, social structures, marginalization, intersection of technology and society, etc.
 
 
-```
-Your thoughts...
-```
+What stayed with me most from the article is that database schemas are not neutral plumbing. They actively stipulate what counts as a “real” family. Validation rules that look tidy on paper can silently legislate social life, turning edge cases into errors and forcing people to contort their identities to fit a form. When basic rights hinge on passing those checks, technical choices become social choices.
+
+Building on that, my core view is: data is logical, but people are complex. We rarely anticipate the full range of human arrangements when we design a “logical” structure. Once personhood is compressed into fields, the meaning of those fields—how institutions define “parent,” “guardian,” “spouse,” or even “gender”—drives the story the data can tell. Because different actors hold different definitions, the same reality can be recorded inconsistently, breeding confusion.
+
+Many conclusions require multiple fields to cohere, and the absence of a single attribute can break an otherwise accurate narrative. That’s why i actually think data science is  fundamentally social science, not just analysis. The data is telling a story, yet the story is always thicker than the schema allows. Static categories without time, multiplicity, or uncertainty flatten lives into yes/no boxes that mislead as much as they inform. If the goal is to let data carry richer truths, we need models that accommodate variance without treating it as failure. That means definitions that are explicit and revisitable, relationships that allow multiple roles over time, and humane exception paths that record context instead of faking compliance. Above all, it means recognizing that what we encode is never just storage—it is a claim about the world, and people live with its consequences.

02_activities/assignments/DC_Cohort/assignment1.sql

@@ -5,49 +5,80 @@
 --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:
 	1.  two conditions using AND
 	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_name,
+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 
+v.vendor_id, 
+v.vendor_name, 
+v.vendor_type, 
+v.vendor_owner_first_name,
+v.vendor_owner_last_name,
+vba.market_date
+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;
 
 
 /* SECTION 3 */
@@ -56,15 +87,28 @@ vendor_id field they both have in common, and sorts the result by vendor_name, t
 /* 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 
 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_id,
+  c.customer_last_name,
+  c.customer_first_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, c.customer_last_name, c.customer_first_name
+HAVING total_spent > 2000
+ORDER BY c.customer_last_name, c.customer_first_name;
 
 --Temp Table
 /* 1. Insert the original vendor table into a temp.new_vendor and then add a 10th vendor: 
@@ -78,6 +122,23 @@ When inserting the new vendor, you need to appropriately align the columns to be
 VALUES(col1,col2,col3,col4,col5) 
 */
 
+DROP TABLE IF EXISTS temp.new_vendor;
+
+CREATE TEMP TABLE new_vendor AS
+SELECT *
+FROM vendor;
+
+INSERT INTO temp.new_vendor
+  (vendor_id, vendor_name, vendor_type, vendor_owner_first_name, vendor_owner_last_name)
+SELECT
+  COALESCE(MAX(vendor_id), 0) + 1,
+  'Thomass Superfood Store',
+  'Fresh Focused',
+  'Thomas',     
+  'Rosenthal'   
+FROM vendor;
+
+SELECT * FROM temp.new_vendor;
 
 
 -- Date
@@ -86,11 +147,23 @@ VALUES(col1,col2,col3,col4,col5)
 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', market_date) AS month,
+  STRFTIME('%Y', market_date) AS year
+FROM customer_purchases;
 
 /* 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!! */
 
+SELECT
+  customer_id,
+  SUM(quantity * cost_to_customer_per_qty) AS total_spent_april_2022
+FROM customer_purchases
+WHERE STRFTIME('%Y', market_date) = '2022'
+  AND STRFTIME('%m', market_date) = '04'
+GROUP BY customer_id
+ORDER BY total_spent_april_2022