updated assignment

02_activities/assignments/DC_Cohort/Assignment1.md

@@ -207,3 +207,10 @@ Consider, for example, concepts of fariness, inequality, social structures, marg
 ```
 Your thoughts...
 ```
+Databases not just as technical tools, but systems reflecting human values. The social implications of how data is organized are familiar from my work in education. This reflection explores how everyday data systems embed assumptions identity, and inclusion. Databases rely on predefined categories, such as gender, family structure, or citizenship. These categories are often taken for granted, but they carry cultural and political weight.  
+
+In my academic environment, student information systems often  Western naming conventions. International students or those from nontraditional families may find that their identities don’t fit neatly into the database. Similarly, learning management systems (LMS) track student engagement through metrics like login frequency or discussion posts. These indicators may not account for neurodiverse learners or cultural differences in participation styles, yet they’re used to assess performance. As a researcher, I’ve also encountered limitations in data collection tools. When conducting surveys, I’m often forced to simplify complex identities into checkboxes, race, ethnicity, language, based on institutional templates. These simplifications can erase nuance and reinforce dominant narratives. Ethical research requires acknowledging these constraints and advocating for more inclusive data practices. 
+
+Beyond academia, media platforms like news aggregators and YouTube also reflect embedded value systems. News algorithms often prioritize Western sources, shaping public understanding of global events. Stories from the Global South or Indigenous communities may be underrepresented or framed through Western perspectives. This influences not only what we read, but how we think about the world. YouTube’s recommendation system is another example. It promotes content based on watch time and engagement, which tends to favour popular creators and mainstream topics. Marginalized voices, such as disabled educators, or those speaking in non-dominant languages, struggle for visibility. The algorithm amplifies what’s already dominant, reinforcing cultural hierarchies. 
+
+As an educator, I believe fairness means recognizing diverse ways of knowing and being. Data systems may exclude overlook informal learning or penalize students who don’t conform to standardized metrics, thus fall short of this ideal. These systems shape access to resources, recognition, and opportunity. Marginalization can occur invisibly through design. For example, if a database doesn’t allow for multiple guardians or chosen family structures, some students may be denied access to services. If a grading algorithm penalizes late submissions without accounting for caregiving responsibilities or mental health, it reinforces inequity. 

02_activities/assignments/DC_Cohort/assignment1.sqbpro

@@ -0,0 +1,154 @@
+<?xml version="1.0" encoding="UTF-8"?><sqlb_project><db path="C:/Users/hhnyn/Desktop/DSI/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="8502"/><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="vendor" custom_title="0" dock_id="1" table="4,6:mainvendor"/><dock_state state="000000ff00000000fd0000000100000002000001fa000002d1fc0100000001fb000000160064006f0063006b00420072006f00770073006500310100000000000001fa0000016200ffffff000001fa0000000000000004000000040000000800000008fc00000000"/><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="92"/><column index="2" value="110"/><column index="3" value="300"/><column index="4" value="74"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table><table schema="main" name="customer_purchases" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="69"/><column index="2" value="65"/><column index="3" value="87"/><column index="4" value="81"/><column index="5" value="56"/><column index="6" value="164"/><column index="7" value="106"/></column_widths><filter_values/><conditional_formats/><row_id_formats/><display_formats/><hidden_columns/><plot_y_axes/><global_filter/></table><table schema="main" name="vendor" show_row_id="0" encoding="" plot_x_axis="" unlock_view_pk="_rowid_" freeze_columns="0"><sort/><column_widths><column index="1" value="65"/><column index="2" value="263"/><column index="3" value="239"/><column index="4" value="159"/><column index="5" value="157"/></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*">/* 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), 
+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 9 AND 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 product_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_type_condensed
+, CASE WHEN product_name like '%Peppers%' or '%peppers%'
+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_booth_assignments
+INNER JOIN vendor
+on	vendor_booth_assignments.vendor_id = vendor.vendor_id 
+ORDER by vendor_name, market_date;
+
+/* SECTION 3 */
+
+-- 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 (vendor_id) as num_times_booth_rented
+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_first_name
+, c.customer_last_name
+, sum(quantity * cost_to_customer_per_qty) as customer_expenditure
+
+
+FROM customer_purchases as cp 
+INNER JOIN customer as c
+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) &gt; 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: 
+Thomass Superfood Store, a Fresh Focused store, owned by Thomas Rosenthal
+
+HINT: This is two total queries -- first create the table from the original, then insert the new 10th vendor. 
+When inserting the new vendor, you need to appropriately align the columns to be inserted 
+(there are five columns to be inserted, I've given you the details, but not the syntax) 
+
+-&gt; To insert the new row use VALUES, specifying the value you want for each column:
+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', '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! */
+SELECT customer_id,
+strftime('%m', market_date) AS purchase_month,
+strftime('%Y', market_date) AS purchase_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
+FROM customer_purchases
+WHERE strftime('%m', market_date) = '04'
+and strftime('%Y', market_date) = '2022'
+GROUP BY customer_id
+
+
+
+
+
+
+</sql><current_tab id="0"/></tab_sql></sqlb_project>

02_activities/assignments/DC_Cohort/assignment1.sql

@@ -4,70 +4,110 @@
 
 --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), 
 filtered by customer IDs between 8 and 10 (inclusive) using either:
 	1.  two conditions using AND
-	2.  one condition using BETWEEN
-*/
--- option 1
+	2.  one condition using BETWEEN*/
 
+-- option 1
+SELECT *
+, quantity * cost_to_customer_per_qty AS price
+FROM customer_purchases 
+WHERE customer_id = 8 AND 9 AND 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” 
+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 product_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_type_condensed
+, CASE WHEN product_name like '%Peppers%' or '%peppers%'
+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_booth_assignments
+INNER JOIN vendor
+on	vendor_booth_assignments.vendor_id = vendor.vendor_id 
+ORDER by vendor_name, market_date;
 
 /* SECTION 3 */
 
 -- 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 (vendor_id) as num_times_booth_rented
+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_first_name
+, c.customer_last_name
+, sum(quantity * cost_to_customer_per_qty) as customer_expenditure
 
 
+FROM customer_purchases as cp 
+INNER JOIN customer as c
+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
-/* 1. Insert the original vendor table into a temp.new_vendor and then add a 10th vendor: 
+/*1. Insert the original vendor table into a temp.new_vendor and then add a 10th vendor: 
 Thomass Superfood Store, a Fresh Focused store, owned by Thomas Rosenthal
 
 HINT: This is two total queries -- first create the table from the original, then insert the new 10th vendor. 
@@ -77,20 +117,37 @@ When inserting the new vendor, you need to appropriately align the columns to be
 -> To insert the new row use VALUES, specifying the value you want for each column:
 VALUES(col1,col2,col3,col4,col5) 
 */
+DROP Table if exists temp.new_vendor_inventory
+CREATE TABLE temp.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', '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! */
-
-
+SELECT customer_id,
+strftime('%m', market_date) AS purchase_month,
+strftime('%Y', market_date) AS purchase_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
+FROM customer_purchases
+WHERE strftime('%m', market_date) = '04'
+and strftime('%Y', market_date) = '2022'
+GROUP BY customer_id
+
+
+
+
+
 

02_activities/assignments/DC_Cohort/assignment1.txt

@@ -0,0 +1,29 @@
+## Section 4:
+You can start this section anytime.
+
+Steps to complete this part of the assignment:
+- Read the article
+- Write, within this markdown file, <1000 words.
+
+### Ethics
+
+Read: Qadri, R. (2021, November 11). _When Databases Get to Define Family._  Wired. <br>
+    https://www.wired.com/story/pakistan-digital-database-family-design/
+
+Link if you encounter a paywall: https://archive.is/srKHV or https://web.archive.org/web/20240422105834/https://www.wired.com/story/pakistan-digital-database-family-design/
+
+**What values systems are embedded in databases and data systems you encounter in your day-to-day life?**
+
+Consider, for example, concepts of fariness, inequality, social structures, marginalization, intersection of technology and society, etc.
+
+
+```
+Your thoughts...
+```
+Databases not just as technical tools, but systems reflecting human values. The social implications of how data is organized are familiar from my work in education. This reflection explores how everyday data systems embed assumptions identity, and inclusion. Databases rely on predefined categories, such as gender, family structure, or citizenship. These categories are often taken for granted, but they carry cultural and political weight.  
+
+In my academic environment, student information systems often  Western naming conventions. International students or those from nontraditional families may find that their identities don’t fit neatly into the database. Similarly, learning management systems (LMS) track student engagement through metrics like login frequency or discussion posts. These indicators may not account for neurodiverse learners or cultural differences in participation styles, yet they’re used to assess performance. As a researcher, I’ve also encountered limitations in data collection tools. When conducting surveys, I’m often forced to simplify complex identities into checkboxes, race, ethnicity, language, based on institutional templates. These simplifications can erase nuance and reinforce dominant narratives. Ethical research requires acknowledging these constraints and advocating for more inclusive data practices. 
+
+Beyond academia, media platforms like news aggregators and YouTube also reflect embedded value systems. News algorithms often prioritize Western sources, shaping public understanding of global events. Stories from the Global South or Indigenous communities may be underrepresented or framed through Western perspectives. This influences not only what we read, but how we think about the world. YouTube’s recommendation system is another example. It promotes content based on watch time and engagement, which tends to favour popular creators and mainstream topics. Marginalized voices, such as disabled educators, or those speaking in non-dominant languages, struggle for visibility. The algorithm amplifies what’s already dominant, reinforcing cultural hierarchies. 
+
+As an educator, I believe fairness means recognizing diverse ways of knowing and being. Data systems may exclude overlook informal learning or penalize students who don’t conform to standardized metrics, thus fall short of this ideal. These systems shape access to resources, recognition, and opportunity. Marginalization can occur invisibly through design. For example, if a database doesn’t allow for multiple guardians or chosen family structures, some students may be denied access to services. If a grading algorithm penalizes late submissions without accounting for caregiving responsibilities or mental health, it reinforces inequity.