%sh
wget -O chinookdb.zip "https://www.udacity.com/api/nodes/5390363876/supplemental_media/chinook-dbzip/download?_ga=1.43670181.1631387024.1462304289"

import sqlite3
conn = sqlite3.connect('chinook.db')
c = conn.cursor()
for row in c.execute('SELECT count(name) FROM Track Where Composer = "U2"'):
    print row

for row in c.execute('SELECT Title FROM Employee WHERE LastName = "Johnson"'):
    print row

for row in c.execute(" select name from sqlite_master where type = 'table';"):
    print row

def sqlite3run(code):
    for row in c.execute(code):
        print row

%sqlite3run
PRAGMA table_info(Invoice);

%sqlite3run
PRAGMA table_info(InvoiceLine);

%md
Phase 1
"SELECT sql, statement FROM Udacious WHERE queryId = 35;"
Table Name:
Udacious 

Columns:
problemSet INTEGER, node INTEGER,  queryId INTEGER, title TEXT, sql TEXT, statement TEXT"
Awesome.db

%md
All the tables in the zoo database
animals
This table lists individual animals in the zoo. Each animal has only one row. There may be multiple animals with the same name, or even multiple animals with the same name and species.
name — the animal's name (example: 'George')
species — the animal's species (example: 'gorilla')
birthdate — the animal's date of birth (example: '1998-05-18')
diet
This table matches up species with the foods they eat. Every species in the zoo eats at least one sort of food, and many eat more than one. If a species eats more than one food, there will be more than one row for that species.
species — the name of a species (example: 'hyena')
food — the name of a food that species eats (example: 'meat')
taxonomy
This table gives the (partial) biological taxonomic names for each species in the zoo. It can be used to find which species are more closely related to each other evolutionarily.
name — the common name of the species (e.g. 'jackal')
species — the taxonomic species name (e.g. 'aureus')
genus — the taxonomic genus name (e.g. 'Canis')
family — the taxonomic family name (e.g. 'Canidae')
t_order — the taxonomic order name (e.g. 'Carnivora')
If you've never heard of this classification, don't worry about it; the details won't be necessary for this course. But if you're curious, Wikipedia articles Taxonomy and Biological classification may help.
ordernames
This table gives the common names for each of the taxonomic orders in the taxonomy table.
t_order — the taxonomic order name (e.g. 'Cetacea')
name — the common name (e.g. 'whales and dolphins')
The SQL for it
And here are the SQL commands that were used to create those tables. We won't cover the create table command until lesson 4, but it may be interesting to look at:
create table animals (  
       name text,
       species text,
       birthdate date);

create table diet (
       species text,
       food text);  

create table taxonomy (
       name text,
       species text,
       genus text,
       family text,
       t_order text); 

create table ordernames (
       t_order text,
       name text);
Remember: In SQL, we always put string and date values inside single quotes.
Have questions? Head to the forums for discussion with the Udacity Community.

%sqlite3run
SELECT BillingCity, Count(*) as NumTracks FROM Invoice Join InvoiceLine ON Invoice.InvoiceID = InvoiceLine.InvoiceID 
JOIN Track ON InvoiceLine.TrackID = Track.GenreID Join Genre ON Track.GenreID = Genre.GenreID 
WHERE Invoice.BillingCountry = 'France' AND Genre.Name = 'Alternative & Punk'
GROUP BY BillingCity ORDER BY NumTracks DESC

import sqlite3
conn = sqlite3.connect('practice.db')
c = conn.cursor()

%sqlite3run
CREATE TABLE InvoiceLine (
    InvoiceLineID INTEGER PRIMARY KEY,
    InvoiceID INTEGER,
    TrackID INTEGER,
    UnitPrice REAL,
    Quantity INTEGER
    
)

import sqlite3
conn = sqlite3.connect('chinook.db')
c = conn.cursor()

%sqlite3run
SELECT count(*) FROM (SELECT Track.MediaTypeID FROM Track Join Genre ON Track.GenreID = Genre.GenreID WHERE Genre.Name = 'Pop') as t1 Join MediaType ON t1.MediaTypeID = MediaType.MediaTypeID Where MediaType.Name = 'MPEG audio file'

%sqlite3run
SELECT MediaType.Name FROM MediaType

%sqlite3run
SELECT COUNT(*) FROM (SELECT DISTINCT Invoice.CustomerID FROM Invoice Join InvoiceLine ON Invoice.InvoiceID = InvoiceLine.InvoiceID Join Track On InvoiceLine.TrackID = Track.TrackID Join Genre On Track.GenreID = Genre.GenreID WHERE Genre.Name = 'Jazz')

%sqlite3run
SELECT g, count(*) FROM (SELECT Genre.Name as g, Track.milliseconds FROM Track Join Genre ON Track.GenreID = Genre.GenreID WHERE Track.milliseconds < 393599.2121039109) GROUP BY g ORDER BY COUNT(*) DESC

%sqlite3run
SELECT Avg(milliseconds) FROM Track