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Hit MVP #1

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b392b5c
Hit MVP
Oct 8, 2019
2fc7b0b
added stretch
Oct 9, 2019
f1aaa24
completed Data Normalization 3nf
Oct 9, 2019
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69 changes: 69 additions & 0 deletions README.md
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Expand Up @@ -36,26 +36,45 @@ Answer the following data queries. Keep track of the SQL you write by pasting it
### find all customers that live in London. Returns 6 records.
> This can be done with SELECT and WHERE clauses

SELECT contact_name
FROM customers
WHERE city = 'London'

### find all customers with postal code 1010. Returns 3 customers.
> This can be done with SELECT and WHERE clauses

SELECT contact_name, postal_code
FROM customers
WHERE postal_code = '1010'

### find the phone number for the supplier with the id 11. Should be (010) 9984510.
> This can be done with SELECT and WHERE clauses

SELECT phone
FROM suppliers
WHERE supplier_id = '11'

### list orders descending by the order date. The order with date 1998-05-06 should be at the top.
> This can be done with SELECT, WHERE, and ORDER BY clauses

SELECT order_id, order_date
FROM orders
ORDER BY order_date DESC

### find all suppliers who have names longer than 20 characters. You can use `length(company_name)` to get the length of the name. Returns 11 records.
> This can be done with SELECT and WHERE clauses

SELECT company_name, supplier_id
FROM suppliers
WHERE length(company_name) > '20'

### find all customers that include the word 'MARKET' in the contact title. Should return 19 records.
> This can be done with SELECT and a WHERE clause using the LIKE keyword

SELECT contact_name
FROM customers
WHERE upper(contact_title) like '%MARKET%'

> Don't forget the wildcard '%' symbols at the beginning and end of your substring to denote it can appear anywhere in the string in question

> Remember to convert your contact title to all upper case for case insenstive comparing so upper(contact_title)
Expand All @@ -71,24 +90,44 @@ Answer the following data queries. Keep track of the SQL you write by pasting it
* the country is 'Middle Earth'
> This can be done with the INSERT INTO clause

INSERT INTO customers(customer_id, company_name, contact_name, address, city, postal_code, country)
VALUES ('SHIRE', 'The Shire', 'Bilbo Baggins', '1 Hobbit-Hole', 'Bag End', '111', 'Middle Earth')

### update _Bilbo Baggins_ record so that the postal code changes to _"11122"_.
> This can be done with UPDATE and WHERE clauses

UPDATE customers
SET postal_code = '11122'
WHERE contact_name = 'Bilbo Baggins'

### list orders grouped by customer showing the number of orders per customer. _Rattlesnake Canyon Grocery_ should have 18 orders.
> This can be done with SELECT, COUNT, JOIN and GROUP BY clauses. Your count should focus on a field in the Orders table, not the Customer table

> There is more information about the COUNT clause on [W3 Schools](https://www.w3schools.com/sql/sql_count_avg_sum.asp)

SELECT c.company_name, COUNT(c.company_name) as orders
FROM orders o RIGHT JOIN customers c
ON o.customer_id = c.customer_id
GROUP BY c.company_name
ORDER BY c.company_name ASC

### list customers names and the number of orders per customer. Sort the list by number of orders in descending order. _Save-a-lot Markets should be at the top with 31 orders followed by _Ernst Handle_ with 30 orders. Last should be _Centro comercial Moctezuma_ with 1 order.
> This can be done by adding an ORDER BY clause to the previous answer

SELECT c.company_name, COUNT(c.company_name) as orders
FROM orders o RIGHT JOIN customers c
ON o.customer_id = c.customer_id
GROUP BY c.company_name
ORDER BY orders DESC

### list orders grouped by customer's city showing number of orders per city. Returns 69 Records with _Aachen_ showing 6 orders and _Albuquerque_ showing 18 orders.
> This is very similar to the previous two queries, however, it focuses on the City rather than the CustomerName

SELECT c.city, COUNT(c.city) as orders
FROM orders o RIGHT JOIN customers c
ON o.customer_id = c.customer_id
GROUP BY c.city
ORDER BY c.city ASC

## Data Normalization

Expand All @@ -102,6 +141,32 @@ Take the following data and normalize it into a 3NF database. You can use the w
| Bob | Joe | Horse | | | | | No | No |
| Sam | Ginger | Dog | Miss Kitty | Cat | Bubble | Fish | Yes | No |

----------------------------------------------------------------------------------------------------------------------

| person id | Person Name | Fenced Yard | City Dweller |
|-----------|-------------|-------------|--------------|
| 1 | Jane | No | Yes |
| 2 | Bob | No | No |
| 3 | Sam | Yes | No |

| Pet type id | Pet Type |
|-------------|----------|
| 1 | Dog |
| 2 | Horse |
| 3 | Cat |
| 4 | Turtle |
| 5 | Fish |

| Person id | Pet type id | Pet name |
|-----------|-------------|------------|
| 1 | 1 | Ellie |
| 2 | 2 | Joe |
| 3 | 1 | Ginger |
| 1 | 3 | Tiger |
| 3 | 3 | Miss Kitty |
| 1 | 4 | Toby |
| 3 | 5 | Bubble |

---
## Stretch Goals

Expand All @@ -112,6 +177,10 @@ Take the following data and normalize it into a 3NF database. You can use the w

> Use a LEFT JOIN to join the Orders table onto the Customers table and check for a NULL value in the OrderID column

DELETE FROM customers
WHERE customer_id NOT IN
(SELECT DISTINCT customer_id FROM orders)

## Create Database and Table

### After creating the database, tables, columns, and constraint, generate the script necessary to recreate the database. This script is what you will submit for review.
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