├── .DS_Store ├── .gitignore ├── README.md ├── SparkStarSchema.png ├── create_tables.py ├── data ├── .DS_Store ├── log_data │ └── 2018 │ │ └── 11 │ │ ├── 2018-11-01-events.json │ │ ├── 2018-11-02-events.json │ │ ├── 2018-11-03-events.json │ │ ├── 2018-11-04-events.json │ │ ├── 2018-11-05-events.json │ │ ├── 2018-11-06-events.json │ │ ├── 2018-11-07-events.json │ │ ├── 2018-11-08-events.json │ │ ├── 2018-11-09-events.json │ │ ├── 2018-11-10-events.json │ │ ├── 2018-11-11-events.json │ │ ├── 2018-11-12-events.json │ │ ├── 2018-11-13-events.json │ │ ├── 2018-11-14-events.json │ │ ├── 2018-11-15-events.json │ │ ├── 2018-11-16-events.json │ │ ├── 2018-11-17-events.json │ │ ├── 2018-11-18-events.json │ │ ├── 2018-11-19-events.json │ │ ├── 2018-11-20-events.json │ │ ├── 2018-11-21-events.json │ │ ├── 2018-11-22-events.json │ │ ├── 2018-11-23-events.json │ │ ├── 2018-11-24-events.json │ │ ├── 2018-11-25-events.json │ │ ├── 2018-11-26-events.json │ │ ├── 2018-11-27-events.json │ │ ├── 2018-11-28-events.json │ │ ├── 2018-11-29-events.json │ │ └── 2018-11-30-events.json └── song_data │ └── A │ ├── A │ ├── A │ │ ├── TRAAAAW128F429D538.json │ │ ├── TRAAABD128F429CF47.json │ │ ├── TRAAADZ128F9348C2E.json │ │ ├── TRAAAEF128F4273421.json │ │ ├── TRAAAFD128F92F423A.json │ │ ├── TRAAAMO128F1481E7F.json │ │ ├── TRAAAMQ128F1460CD3.json │ │ ├── TRAAAPK128E0786D96.json │ │ ├── TRAAARJ128F9320760.json │ │ ├── TRAAAVG12903CFA543.json │ │ └── TRAAAVO128F93133D4.json │ ├── B │ │ ├── TRAABCL128F4286650.json │ │ ├── TRAABDL12903CAABBA.json │ │ ├── TRAABJL12903CDCF1A.json │ │ ├── TRAABJV128F1460C49.json │ │ ├── TRAABLR128F423B7E3.json │ │ ├── TRAABNV128F425CEE1.json │ │ ├── TRAABRB128F9306DD5.json │ │ ├── TRAABVM128F92CA9DC.json │ │ ├── TRAABXG128F9318EBD.json │ │ ├── TRAABYN12903CFD305.json │ │ └── TRAABYW128F4244559.json │ └── C │ │ ├── TRAACCG128F92E8A55.json │ │ ├── TRAACER128F4290F96.json │ │ ├── TRAACFV128F935E50B.json │ │ ├── TRAACHN128F1489601.json │ │ ├── TRAACIW12903CC0F6D.json │ │ ├── TRAACLV128F427E123.json │ │ ├── TRAACNS128F14A2DF5.json │ │ ├── TRAACOW128F933E35F.json │ │ ├── TRAACPE128F421C1B9.json │ │ ├── TRAACQT128F9331780.json │ │ ├── TRAACSL128F93462F4.json │ │ ├── TRAACTB12903CAAF15.json │ │ ├── TRAACVS128E078BE39.json │ │ └── TRAACZK128F4243829.json │ └── B │ ├── A │ ├── TRABACN128F425B784.json │ ├── TRABAFJ128F42AF24E.json │ ├── TRABAFP128F931E9A1.json │ ├── TRABAIO128F42938F9.json │ ├── TRABATO128F42627E9.json │ ├── TRABAVQ12903CBF7E0.json │ ├── TRABAWW128F4250A31.json │ ├── TRABAXL128F424FC50.json │ ├── TRABAXR128F426515F.json │ ├── TRABAXV128F92F6AE3.json │ └── TRABAZH128F930419A.json │ ├── B │ ├── TRABBAM128F429D223.json │ ├── TRABBBV128F42967D7.json │ ├── TRABBJE12903CDB442.json │ ├── TRABBKX128F4285205.json │ ├── TRABBLU128F93349CF.json │ ├── TRABBNP128F932546F.json │ ├── TRABBOP128F931B50D.json │ ├── TRABBOR128F4286200.json │ ├── TRABBTA128F933D304.json │ ├── TRABBVJ128F92F7EAA.json │ ├── TRABBXU128F92FEF48.json │ └── TRABBZN12903CD9297.json │ └── C │ ├── TRABCAJ12903CDFCC2.json │ ├── TRABCEC128F426456E.json │ ├── TRABCEI128F424C983.json │ ├── TRABCFL128F149BB0D.json │ ├── TRABCIX128F4265903.json │ ├── TRABCKL128F423A778.json │ ├── TRABCPZ128F4275C32.json │ ├── TRABCRU128F423F449.json │ ├── TRABCTK128F934B224.json │ ├── TRABCUQ128E0783E2B.json │ ├── TRABCXB128F4286BD3.json │ └── TRABCYE128F934CE1D.json ├── etl.ipynb ├── etl.py ├── sql_queries.py └── test.ipynb /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wathon/Data-Modeling-with-Postgres/aedb166845200024174b0a3368f0e549176411e1/.DS_Store -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | 131 | .DS_Store 132 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Sparkify ETL with Postgres and Python 2 | 3 | In this project, we'll learned on data modeling with Postgres and build an ETL pipeline using Python. 4 | 5 | We will follow the following steps: 6 | - Data modeling with Postgres 7 | - Creating star schema database 8 | - ETL pipeline using Python 9 | 10 | ## Project Description 11 | 12 | This project is to create a SQL analytics database for a music streaming startup called Sparkify. Sparkify's analytics team want to understand what songs users are listening on the company's music app. They need an easy way to query to their data. These data are stored in raw JSON logs on user activity on the app, as well as a directory with JSON metadata on the songs in their app on. 13 | 14 | 15 | ### Project Dataset 16 | 17 | - **Song Dataset**: files are partitioned by the first three letters of each song's track ID e.g. */data/song_data.*.json. Sample: 18 | 19 | ``` 20 | {"artist_id": "ARD7TVE1187B99BFB1", "artist_latitude": null, "artist_location": "California - LA", "artist_longitude": null, "artist_name": "Casual", "duration": 218.93179, "num_songs": 1, "song_id": "SOMZWCG12A8C13C480", "title": "I Didn't Mean To", "year": 0} 21 | ``` 22 | 23 | - **Log Dataset**: files in the dataset you'll be working with are partitioned by year and month e.g. */data/log_data.*json. Sample: 24 | 25 | ``` 26 | {"artist": "Stephen Lynch", "auth": "Logged In", "firstName": "Jayden", "gender": "M", "itemInSession": 0, "lastName": "Bell", "length": 182.85669, "level": "free", "location": "Dallas-Fort Worth-Arlington", "method": "TX PUT", "page": "NextSong", "registration": 1.540992.., "sessionId": "829", "song":"Jim Henson's Dead", "status": 200, "ts": 1543537327796, "userAgent": "Mozilla/5.0 (compatible; MSIE 10.0; Windows NT...", "userId": 91} 27 | ``` 28 | 29 | ## Data Modeling 30 | 31 | We will use the Star Schema: 32 | one fact table consist of the measures associated with each event *songplays*, 33 | and referencing four dimensional tables *songs*, *artists*, *users* and *time*, each with a primary key that is being referenced from the fact table. 34 | 35 | On why to use a relational database for this case: 36 | 37 | - The data types are structured (we know before-hand the structure of the jsons we need to analyze, and where and how to extract and transform each field) 38 | - The amount of data we need to analyze is not big enough to require big data related solutions. 39 | - This structure will enable the analysts to aggregate the data efficiently 40 | - Ability to use SQL that is more than enough for this kind of analysis 41 | - We need to use JOINS for this scenario 42 | 43 | ![SparkStar Schema](SparkStarSchema.png) 44 | 45 | ## Project template 46 | 47 | The data files, the project includes seven files: 48 | 1. ***create_tables.py*:** drops and creates your tables. You run this file to reset your tables before each time you run your ETL scripts. 49 | 2. ***etl.ipynb*:** reads and processes a single file from *song_data* and *log_data* and loads the data into your tables. This notebook contains detailed instructions on the ETL process for each of the tables. 50 | 3. ***etl.py*:** reads and processes files from *song_data* and *log_data* and loads them into your tables. You can fill this out based on your work in the ETL notebook. 51 | 4. ***README.md*:** provides discussion on this project. 52 | 5. ***SparkStarSchema.png*:** *ERD* for star schema of this project 53 | 6. ***sql_queries.py*:** contains all your sql queries, and is imported into the last three files above. 54 | 7. ***test.ipynb*:** displays the first few rows of each table to let us check on the database. 55 | 56 | ## How to Run 57 | 58 | 1. Run ***create_tables.py*** to create the database and tables. 59 | 2. Run ***etl.py*** to process for loading, extracting and inserting the data. 60 | 3. Run ***test.ipynb*** to confirm the creation of database and columns. -------------------------------------------------------------------------------- /SparkStarSchema.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wathon/Data-Modeling-with-Postgres/aedb166845200024174b0a3368f0e549176411e1/SparkStarSchema.png -------------------------------------------------------------------------------- /create_tables.py: -------------------------------------------------------------------------------- 1 | import psycopg2 2 | from sql_queries import create_table_queries, drop_table_queries 3 | 4 | 5 | def create_database(): 6 | """ 7 | - Creates and connects to the sparkifydb 8 | - Returns the connection and cursor to sparkifydb 9 | """ 10 | 11 | # connect to default database 12 | conn = psycopg2.connect("host=127.0.0.1 dbname=studentdb user=student password=student") 13 | conn.set_session(autocommit=True) 14 | cur = conn.cursor() 15 | 16 | # create sparkify database with UTF8 encoding 17 | cur.execute("DROP DATABASE IF EXISTS sparkifydb") 18 | cur.execute("CREATE DATABASE sparkifydb WITH ENCODING 'utf8' TEMPLATE template0") 19 | 20 | # close connection to default database 21 | conn.close() 22 | 23 | # connect to sparkify database 24 | conn = psycopg2.connect("host=127.0.0.1 dbname=sparkifydb user=student password=student") 25 | cur = conn.cursor() 26 | 27 | return cur, conn 28 | 29 | 30 | def drop_tables(cur, conn): 31 | """ 32 | Drops each table using the queries in `drop_table_queries` list. 33 | """ 34 | for query in drop_table_queries: 35 | cur.execute(query) 36 | conn.commit() 37 | 38 | 39 | def create_tables(cur, conn): 40 | """ 41 | Creates each table using the queries in `create_table_queries` list. 42 | """ 43 | for query in create_table_queries: 44 | cur.execute(query) 45 | conn.commit() 46 | 47 | 48 | def main(): 49 | """ 50 | - Drops (if exists) and Creates the sparkify database. 51 | 52 | - Establishes connection with the sparkify database and gets 53 | cursor to it. 54 | 55 | - Drops all the tables. 56 | 57 | - Creates all tables needed. 58 | 59 | - Finally, closes the connection. 60 | """ 61 | cur, conn = create_database() 62 | 63 | drop_tables(cur, conn) 64 | create_tables(cur, conn) 65 | 66 | conn.close() 67 | 68 | 69 | if __name__ == "__main__": 70 | main() -------------------------------------------------------------------------------- /data/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wathon/Data-Modeling-with-Postgres/aedb166845200024174b0a3368f0e549176411e1/data/.DS_Store -------------------------------------------------------------------------------- /data/log_data/2018/11/2018-11-01-events.json: -------------------------------------------------------------------------------- 1 | {"artist":null,"auth":"Logged In","firstName":"Walter","gender":"M","itemInSession":0,"lastName":"Frye","length":null,"level":"free","location":"San Francisco-Oakland-Hayward, CA","method":"GET","page":"Home","registration":1540919166796.0,"sessionId":38,"song":null,"status":200,"ts":1541105830796,"userAgent":"\"Mozilla\/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/36.0.1985.143 Safari\/537.36\"","userId":"39"} 2 | {"artist":null,"auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":0,"lastName":"Summers","length":null,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"GET","page":"Home","registration":1540344794796.0,"sessionId":139,"song":null,"status":200,"ts":1541106106796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 3 | {"artist":"Des'ree","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":1,"lastName":"Summers","length":246.30812,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"You Gotta Be","status":200,"ts":1541106106796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 4 | {"artist":null,"auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":2,"lastName":"Summers","length":null,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"GET","page":"Upgrade","registration":1540344794796.0,"sessionId":139,"song":null,"status":200,"ts":1541106132796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 5 | {"artist":"Mr Oizo","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":3,"lastName":"Summers","length":144.03873,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Flat 55","status":200,"ts":1541106352796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 6 | {"artist":"Tamba Trio","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":4,"lastName":"Summers","length":177.18812,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Quem Quiser Encontrar O Amor","status":200,"ts":1541106496796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 7 | {"artist":"The Mars Volta","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":5,"lastName":"Summers","length":380.42077,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Eriatarka","status":200,"ts":1541106673796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 8 | {"artist":"Infected Mushroom","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":6,"lastName":"Summers","length":440.2673,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Becoming Insane","status":200,"ts":1541107053796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 9 | {"artist":"Blue October \/ Imogen Heap","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":7,"lastName":"Summers","length":241.3971,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Congratulations","status":200,"ts":1541107493796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 10 | {"artist":"Girl Talk","auth":"Logged In","firstName":"Kaylee","gender":"F","itemInSession":8,"lastName":"Summers","length":160.15628,"level":"free","location":"Phoenix-Mesa-Scottsdale, AZ","method":"PUT","page":"NextSong","registration":1540344794796.0,"sessionId":139,"song":"Once again","status":200,"ts":1541107734796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\/537.36 (KHTML, like Gecko) Chrome\/35.0.1916.153 Safari\/537.36\"","userId":"8"} 11 | {"artist":"Black Eyed Peas","auth":"Logged In","firstName":"Sylvie","gender":"F","itemInSession":0,"lastName":"Cruz","length":214.93506,"level":"free","location":"Washington-Arlington-Alexandria, DC-VA-MD-WV","method":"PUT","page":"NextSong","registration":1540266185796.0,"sessionId":9,"song":"Pump It","status":200,"ts":1541108520796,"userAgent":"\"Mozilla\/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit\/537.77.4 (KHTML, like Gecko) Version\/7.0.5 Safari\/537.77.4\"","userId":"10"} 12 | {"artist":null,"auth":"Logged In","firstName":"Ryan","gender":"M","itemInSession":0,"lastName":"Smith","length":null,"level":"free","location":"San Jose-Sunnyvale-Santa Clara, CA","method":"GET","page":"Home","registration":1541016707796.0,"sessionId":169,"song":null,"status":200,"ts":1541109015796,"userAgent":"\"Mozilla\/5.0 (X11; Linux x86_64) AppleWebKit\/537.36 (KHTML, like Gecko) Ubuntu Chromium\/36.0.1985.125 Chrome\/36.0.1985.125 Safari\/537.36\"","userId":"26"} 13 | {"artist":"Fall Out Boy","auth":"Logged In","firstName":"Ryan","gender":"M","itemInSession":1,"lastName":"Smith","length":200.72444,"level":"free","location":"San Jose-Sunnyvale-Santa Clara, CA","method":"PUT","page":"NextSong","registration":1541016707796.0,"sessionId":169,"song":"Nobody Puts Baby In The Corner","status":200,"ts":1541109125796,"userAgent":"\"Mozilla\/5.0 (X11; Linux x86_64) AppleWebKit\/537.36 (KHTML, like Gecko) Ubuntu Chromium\/36.0.1985.125 Chrome\/36.0.1985.125 Safari\/537.36\"","userId":"26"} 14 | {"artist":"M.I.A.","auth":"Logged In","firstName":"Ryan","gender":"M","itemInSession":2,"lastName":"Smith","length":233.7171,"level":"free","location":"San Jose-Sunnyvale-Santa Clara, CA","method":"PUT","page":"NextSong","registration":1541016707796.0,"sessionId":169,"song":"Mango Pickle Down River (With The Wilcannia Mob)","status":200,"ts":1541109325796,"userAgent":"\"Mozilla\/5.0 (X11; Linux x86_64) AppleWebKit\/537.36 (KHTML, like Gecko) Ubuntu Chromium\/36.0.1985.125 Chrome\/36.0.1985.125 Safari\/537.36\"","userId":"26"} 15 | {"artist":"Survivor","auth":"Logged In","firstName":"Jayden","gender":"M","itemInSession":0,"lastName":"Fox","length":245.36771,"level":"free","location":"New Orleans-Metairie, LA","method":"PUT","page":"NextSong","registration":1541033612796.0,"sessionId":100,"song":"Eye Of The Tiger","status":200,"ts":1541110994796,"userAgent":"\"Mozilla\/5.0 (Windows NT 6.3; 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"SOZQDIU12A58A7BCF6", "title": "Superconfidential", "duration": 338.31138, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACLV128F427E123.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARDNS031187B9924F0", "artist_latitude": 32.67828, "artist_longitude": -83.22295, "artist_location": "Georgia", "artist_name": "Tim Wilson", "song_id": "SONYPOM12A8C13B2D7", "title": "I Think My Wife Is Running Around On Me (Taco Hell)", "duration": 186.48771, "year": 2005} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACNS128F14A2DF5.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AROUOZZ1187B9ABE51", "artist_latitude": 40.79195, "artist_longitude": -73.94512, "artist_location": "New York, NY [Spanish Harlem]", "artist_name": "Willie Bobo", "song_id": "SOBZBAZ12A6D4F8742", "title": "Spanish Grease", "duration": 168.25424, "year": 1997} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACOW128F933E35F.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARH4Z031187B9A71F2", "artist_latitude": 40.73197, "artist_longitude": -74.17418, "artist_location": "Newark, NJ", "artist_name": "Faye Adams", "song_id": "SOVYKGO12AB0187199", "title": "Crazy Mixed Up World", "duration": 156.39465, "year": 1961} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACPE128F421C1B9.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARB29H41187B98F0EF", "artist_latitude": 41.88415, "artist_longitude": -87.63241, "artist_location": "Chicago", "artist_name": "Terry Callier", "song_id": "SOGNCJP12A58A80271", "title": "Do You Finally Need A Friend", "duration": 342.56934, "year": 1972} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACQT128F9331780.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR1Y2PT1187FB5B9CE", "artist_latitude": 27.94017, "artist_longitude": -82.32547, "artist_location": "Brandon", "artist_name": "John Wesley", "song_id": "SOLLHMX12AB01846DC", "title": "The Emperor Falls", "duration": 484.62322, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACSL128F93462F4.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARAJPHH1187FB5566A", "artist_latitude": 40.7038, "artist_longitude": -73.83168, "artist_location": "Queens, NY", "artist_name": "The Shangri-Las", "song_id": "SOYTPEP12AB0180E7B", "title": "Twist and Shout", "duration": 164.80608, "year": 1964} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACTB12903CAAF15.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR0RCMP1187FB3F427", "artist_latitude": 30.08615, "artist_longitude": -94.10158, "artist_location": "Beaumont, TX", "artist_name": "Billie Jo Spears", "song_id": "SOGXHEG12AB018653E", "title": "It Makes No Difference Now", "duration": 133.32853, "year": 1992} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACVS128E078BE39.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AREBBGV1187FB523D2", "artist_latitude": null, "artist_longitude": null, "artist_location": "Houston, TX", "artist_name": "Mike Jones (Featuring CJ_ Mello & Lil' Bran)", "song_id": "SOOLYAZ12A6701F4A6", "title": "Laws Patrolling (Album Version)", "duration": 173.66159, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/A/C/TRAACZK128F4243829.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARGUVEV1187B98BA17", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Sierra Maestra", "song_id": "SOGOSOV12AF72A285E", "title": "\u00bfD\u00f3nde va Chichi?", "duration": 313.12934, "year": 1997} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABACN128F425B784.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARD7TVE1187B99BFB1", "artist_latitude": null, "artist_longitude": null, "artist_location": "California - LA", "artist_name": "Casual", "song_id": "SOQLGFP12A58A7800E", "title": "OAKtown", "duration": 259.44771, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAFJ128F42AF24E.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR3JMC51187B9AE49D", "artist_latitude": 28.53823, "artist_longitude": -81.37739, "artist_location": "Orlando, FL", "artist_name": "Backstreet Boys", "song_id": "SOPVXLX12A8C1402D5", "title": "Larger Than Life", "duration": 236.25098, "year": 1999} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAFP128F931E9A1.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARPBNLO1187FB3D52F", "artist_latitude": 40.71455, "artist_longitude": -74.00712, "artist_location": "New York, NY", "artist_name": "Tiny Tim", "song_id": "SOAOIBZ12AB01815BE", "title": "I Hold Your Hand In Mine [Live At Royal Albert Hall]", "duration": 43.36281, "year": 2000} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAIO128F42938F9.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR9AWNF1187B9AB0B4", "artist_latitude": null, "artist_longitude": null, "artist_location": "Seattle, Washington USA", "artist_name": "Kenny G featuring Daryl Hall", "song_id": "SOZHPGD12A8C1394FE", "title": "Baby Come To Me", "duration": 236.93016, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABATO128F42627E9.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AROGWRA122988FEE45", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Christos Dantis", "song_id": "SOSLAVG12A8C13397F", "title": "Den Pai Alo", "duration": 243.82649, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAVQ12903CBF7E0.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARMBR4Y1187B9990EB", "artist_latitude": 37.77916, "artist_longitude": -122.42005, "artist_location": "California - SF", "artist_name": "David Martin", "song_id": "SOTTDKS12AB018D69B", "title": "It Wont Be Christmas", "duration": 241.47546, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAWW128F4250A31.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARQ9BO41187FB5CF1F", "artist_latitude": 40.99471, "artist_longitude": -77.60454, "artist_location": "Pennsylvania", "artist_name": "John Davis", "song_id": "SOMVWWT12A58A7AE05", "title": "Knocked Out Of The Park", "duration": 183.17016, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAXL128F424FC50.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARKULSX1187FB45F84", "artist_latitude": 39.49974, "artist_longitude": -111.54732, "artist_location": "Utah", "artist_name": "Trafik", "song_id": "SOQVMXR12A81C21483", "title": "Salt In NYC", "duration": 424.12363, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAXR128F426515F.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARI2JSK1187FB496EF", "artist_latitude": 51.50632, "artist_longitude": -0.12714, "artist_location": "London, England", "artist_name": "Nick Ingman;Gavyn Wright", "song_id": "SODUJBS12A8C132150", "title": "Wessex Loses a Bride", "duration": 111.62077, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAXV128F92F6AE3.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AREDBBQ1187B98AFF5", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Eddie Calvert", "song_id": "SOBBXLX12A58A79DDA", "title": "Erica (2005 Digital Remaster)", "duration": 138.63138, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/A/TRABAZH128F930419A.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR7ZKHQ1187B98DD73", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Glad", "song_id": "SOTUKVB12AB0181477", "title": "Blessed Assurance", "duration": 270.602, "year": 1993} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBAM128F429D223.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARBGXIG122988F409D", "artist_latitude": 37.77916, "artist_longitude": -122.42005, "artist_location": "California - SF", "artist_name": "Steel Rain", "song_id": "SOOJPRH12A8C141995", "title": "Loaded Like A Gun", "duration": 173.19138, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBBV128F42967D7.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR7SMBG1187B9B9066", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Los Manolos", "song_id": "SOBCOSW12A8C13D398", "title": "Rumba De Barcelona", "duration": 218.38322, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBJE12903CDB442.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARGCY1Y1187B9A4FA5", "artist_latitude": 36.16778, "artist_longitude": -86.77836, "artist_location": "Nashville, TN.", "artist_name": "Gloriana", "song_id": "SOQOTLQ12AB01868D0", "title": "Clementina Santaf\u00e8", "duration": 153.33832, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBKX128F4285205.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR36F9J1187FB406F1", "artist_latitude": 56.27609, "artist_longitude": 9.51695, "artist_location": "Denmark", "artist_name": "Bombay Rockers", "song_id": "SOBKWDJ12A8C13B2F3", "title": "Wild Rose (Back 2 Basics Mix)", "duration": 230.71302, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBLU128F93349CF.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARNNKDK1187B98BBD5", "artist_latitude": 45.80726, "artist_longitude": 15.9676, "artist_location": "Zagreb Croatia", "artist_name": "Jinx", "song_id": "SOFNOQK12AB01840FC", "title": "Kutt Free (DJ Volume Remix)", "duration": 407.37914, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBNP128F932546F.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR62SOJ1187FB47BB5", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Chase & Status", "song_id": "SOGVQGJ12AB017F169", "title": "Ten Tonne", "duration": 337.68444, "year": 2005} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBOP128F931B50D.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARBEBBY1187B9B43DB", "artist_latitude": null, "artist_longitude": null, "artist_location": "Gainesville, FL", "artist_name": "Tom Petty", "song_id": "SOFFKZS12AB017F194", "title": "A Higher Place (Album Version)", "duration": 236.17261, "year": 1994} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBOR128F4286200.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARDR4AC1187FB371A1", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Montserrat Caball\u00e9;Placido Domingo;Vicente Sardinero;Judith Blegen;Sherrill Milnes;Georg Solti", "song_id": "SOBAYLL12A8C138AF9", "title": "Sono andati? Fingevo di dormire", "duration": 511.16363, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBTA128F933D304.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARAGB2O1187FB3A161", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Pucho & His Latin Soul Brothers", "song_id": "SOLEYHO12AB0188A85", "title": "Got My Mojo Workin", "duration": 338.23302, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBVJ128F92F7EAA.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AREDL271187FB40F44", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Soul Mekanik", "song_id": "SOPEGZN12AB0181B3D", "title": "Get Your Head Stuck On Your Neck", "duration": 45.66159, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBXU128F92FEF48.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARP6N5A1187B99D1A3", "artist_latitude": null, "artist_longitude": null, "artist_location": "Hamtramck, MI", "artist_name": "Mitch Ryder", "song_id": "SOXILUQ12A58A7C72A", "title": "Jenny Take a Ride", "duration": 207.43791, "year": 2004} -------------------------------------------------------------------------------- /data/song_data/A/B/B/TRABBZN12903CD9297.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARGSAFR1269FB35070", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Blingtones", "song_id": "SOTCKKY12AB018A141", "title": "Sonnerie lalaleul\u00e9 hi houuu", "duration": 29.54404, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCAJ12903CDFCC2.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARULZCI1241B9C8611", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Luna Orbit Project", "song_id": "SOSWKAV12AB018FC91", "title": "Midnight Star", "duration": 335.51628, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCEC128F426456E.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR0IAWL1187B9A96D0", "artist_latitude": 8.4177, "artist_longitude": -80.11278, "artist_location": "Panama", "artist_name": "Danilo Perez", "song_id": "SONSKXP12A8C13A2C9", "title": "Native Soul", "duration": 197.19791, "year": 2003} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCEI128F424C983.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARJIE2Y1187B994AB7", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Line Renaud", "song_id": "SOUPIRU12A6D4FA1E1", "title": "Der Kleine Dompfaff", "duration": 152.92036, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCFL128F149BB0D.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARLTWXK1187FB5A3F8", "artist_latitude": 32.74863, "artist_longitude": -97.32925, "artist_location": "Fort Worth, TX", "artist_name": "King Curtis", "song_id": "SODREIN12A58A7F2E5", "title": "A Whiter Shade Of Pale (Live @ Fillmore West)", "duration": 326.00771, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCIX128F4265903.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARNF6401187FB57032", "artist_latitude": 40.79086, "artist_longitude": -73.96644, "artist_location": "New York, NY [Manhattan]", "artist_name": "Sophie B. Hawkins", "song_id": "SONWXQJ12A8C134D94", "title": "The Ballad Of Sleeping Beauty", "duration": 305.162, "year": 1994} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCKL128F423A778.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARPFHN61187FB575F6", "artist_latitude": 41.88415, "artist_longitude": -87.63241, "artist_location": "Chicago, IL", "artist_name": "Lupe Fiasco", "song_id": "SOWQTQZ12A58A7B63E", "title": "Streets On Fire (Explicit Album Version)", "duration": 279.97995, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCPZ128F4275C32.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR051KA1187B98B2FF", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Wilks", "song_id": "SOLYIBD12A8C135045", "title": "Music is what we love", "duration": 261.51138, "year": 0} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCRU128F423F449.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR8IEZO1187B99055E", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Marc Shaiman", "song_id": "SOINLJW12A8C13314C", "title": "City Slickers", "duration": 149.86404, "year": 2008} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCTK128F934B224.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AR558FS1187FB45658", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "40 Grit", "song_id": "SOGDBUF12A8C140FAA", "title": "Intro", "duration": 75.67628, "year": 2003} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCUQ128E0783E2B.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARVBRGZ1187FB4675A", "artist_latitude": null, "artist_longitude": null, "artist_location": "", "artist_name": "Gwen Stefani", "song_id": "SORRZGD12A6310DBC3", "title": "Harajuku Girls", "duration": 290.55955, "year": 2004} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCXB128F4286BD3.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "ARWB3G61187FB49404", "artist_latitude": null, "artist_longitude": null, "artist_location": "Hamilton, Ohio", "artist_name": "Steve Morse", "song_id": "SODAUVL12A8C13D184", "title": "Prognosis", "duration": 363.85914, "year": 2000} -------------------------------------------------------------------------------- /data/song_data/A/B/C/TRABCYE128F934CE1D.json: -------------------------------------------------------------------------------- 1 | {"num_songs": 1, "artist_id": "AREVWGE1187B9B890A", "artist_latitude": -13.442, "artist_longitude": -41.9952, "artist_location": "Noci (BA)", "artist_name": "Bitter End", "song_id": "SOFCHDR12AB01866EF", "title": "Living Hell", "duration": 282.43546, "year": 0} -------------------------------------------------------------------------------- /etl.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "editable": true 7 | }, 8 | "source": [ 9 | "# ETL Processes\n", 10 | "Use this notebook to develop the ETL process for each of your tables before completing the `etl.py` file to load the whole datasets." 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": 1, 16 | "metadata": { 17 | "editable": true 18 | }, 19 | "outputs": [], 20 | "source": [ 21 | "import os\n", 22 | "import glob\n", 23 | "import psycopg2\n", 24 | "import pandas as pd\n", 25 | "from sql_queries import *" 26 | ] 27 | }, 28 | { 29 | "cell_type": "code", 30 | "execution_count": 2, 31 | "metadata": { 32 | "editable": true 33 | }, 34 | "outputs": [], 35 | "source": [ 36 | "conn = psycopg2.connect(\"host=127.0.0.1 dbname=sparkifydb user=student password=student\")\n", 37 | "cur = conn.cursor()" 38 | ] 39 | }, 40 | { 41 | "cell_type": "code", 42 | "execution_count": 3, 43 | "metadata": { 44 | "editable": true 45 | }, 46 | "outputs": [], 47 | "source": [ 48 | "def get_files(filepath):\n", 49 | " all_files = []\n", 50 | " for root, dirs, files in os.walk(filepath):\n", 51 | " files = glob.glob(os.path.join(root,'*.json'))\n", 52 | " for f in files :\n", 53 | " all_files.append(os.path.abspath(f))\n", 54 | " \n", 55 | " return all_files" 56 | ] 57 | }, 58 | { 59 | "cell_type": "markdown", 60 | "metadata": { 61 | "editable": true 62 | }, 63 | "source": [ 64 | "# Process `song_data`\n", 65 | "In this first part, you'll perform ETL on the first dataset, `song_data`, to create the `songs` and `artists` dimensional tables.\n", 66 | "\n", 67 | "Let's perform ETL on a single song file and load a single record into each table to start.\n", 68 | "- Use the `get_files` function provided above to get a list of all song JSON files in `data/song_data`\n", 69 | "- Select the first song in this list\n", 70 | "- Read the song file and view the data" 71 | ] 72 | }, 73 | { 74 | "cell_type": "code", 75 | "execution_count": 4, 76 | "metadata": { 77 | "editable": true 78 | }, 79 | "outputs": [], 80 | "source": [ 81 | "song_files = get_files(\"data/song_data\")" 82 | ] 83 | }, 84 | { 85 | "cell_type": "code", 86 | "execution_count": 5, 87 | "metadata": { 88 | "editable": true 89 | }, 90 | "outputs": [], 91 | "source": [ 92 | "filepath = song_files[0]" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 6, 98 | "metadata": { 99 | "editable": true 100 | }, 101 | "outputs": [ 102 | { 103 | "data": { 104 | "text/html": [ 105 | "
\n", 106 | "\n", 119 | "\n", 120 | " \n", 121 | " \n", 122 | " \n", 123 | " \n", 124 | " \n", 125 | " \n", 126 | " \n", 127 | " \n", 128 | " \n", 129 | " \n", 130 | " \n", 131 | " \n", 132 | " \n", 133 | " \n", 134 | " \n", 135 | " \n", 136 | " \n", 137 | " \n", 138 | " \n", 139 | " \n", 140 | " \n", 141 | " \n", 142 | " \n", 143 | " \n", 144 | " \n", 145 | " \n", 146 | " \n", 147 | " \n", 148 | " \n", 149 | " \n", 150 | "
artist_idartist_latitudeartist_locationartist_longitudeartist_namedurationnum_songssong_idtitleyear
0ARD7TVE1187B99BFB1NaNCalifornia - LANaNCasual218.931791SOMZWCG12A8C13C480I Didn't Mean To0
\n", 151 | "
" 152 | ], 153 | "text/plain": [ 154 | " artist_id artist_latitude artist_location artist_longitude \\\n", 155 | "0 ARD7TVE1187B99BFB1 NaN California - LA NaN \n", 156 | "\n", 157 | " artist_name duration num_songs song_id title \\\n", 158 | "0 Casual 218.93179 1 SOMZWCG12A8C13C480 I Didn't Mean To \n", 159 | "\n", 160 | " year \n", 161 | "0 0 " 162 | ] 163 | }, 164 | "execution_count": 6, 165 | "metadata": {}, 166 | "output_type": "execute_result" 167 | } 168 | ], 169 | "source": [ 170 | "df = pd.read_json(filepath, dtype={'year': int}, lines=True)\n", 171 | "df.head()" 172 | ] 173 | }, 174 | { 175 | "cell_type": "markdown", 176 | "metadata": { 177 | "editable": true 178 | }, 179 | "source": [ 180 | "## #1: `songs` Table\n", 181 | "#### Extract Data for Songs Table\n", 182 | "- Select columns for song ID, title, artist ID, year, and duration\n", 183 | "- Use `df.values` to select just the values from the dataframe\n", 184 | "- Index to select the first (only) record in the dataframe\n", 185 | "- Convert the array to a list and set it to `song_data`" 186 | ] 187 | }, 188 | { 189 | "cell_type": "code", 190 | "execution_count": 7, 191 | "metadata": { 192 | "editable": true 193 | }, 194 | "outputs": [ 195 | { 196 | "data": { 197 | "text/plain": [ 198 | "['SOMZWCG12A8C13C480', \"I Didn't Mean To\", 'ARD7TVE1187B99BFB1', 0, 218.93179]" 199 | ] 200 | }, 201 | "execution_count": 7, 202 | "metadata": {}, 203 | "output_type": "execute_result" 204 | } 205 | ], 206 | "source": [ 207 | "song_data = df[['song_id', 'title', 'artist_id', 'year', 'duration']].values[0].tolist()\n", 208 | "song_data" 209 | ] 210 | }, 211 | { 212 | "cell_type": "markdown", 213 | "metadata": { 214 | "editable": true 215 | }, 216 | "source": [ 217 | "#### Insert Record into Song Table\n", 218 | "Implement the `song_table_insert` query in `sql_queries.py` and run the cell below to insert a record for this song into the `songs` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `songs` table in the sparkify database." 219 | ] 220 | }, 221 | { 222 | "cell_type": "code", 223 | "execution_count": 8, 224 | "metadata": { 225 | "editable": true 226 | }, 227 | "outputs": [], 228 | "source": [ 229 | "cur.execute(song_table_insert, song_data)\n", 230 | "conn.commit()" 231 | ] 232 | }, 233 | { 234 | "cell_type": "markdown", 235 | "metadata": { 236 | "editable": true 237 | }, 238 | "source": [ 239 | "Run `test.ipynb` to see if you've successfully added a record to this table." 240 | ] 241 | }, 242 | { 243 | "cell_type": "markdown", 244 | "metadata": { 245 | "editable": true 246 | }, 247 | "source": [ 248 | "## #2: `artists` Table\n", 249 | "#### Extract Data for Artists Table\n", 250 | "- Select columns for artist ID, name, location, latitude, and longitude\n", 251 | "- Use `df.values` to select just the values from the dataframe\n", 252 | "- Index to select the first (only) record in the dataframe\n", 253 | "- Convert the array to a list and set it to `artist_data`" 254 | ] 255 | }, 256 | { 257 | "cell_type": "code", 258 | "execution_count": 9, 259 | "metadata": { 260 | "editable": true 261 | }, 262 | "outputs": [ 263 | { 264 | "data": { 265 | "text/plain": [ 266 | "['ARD7TVE1187B99BFB1', 'Casual', 'California - LA', nan, nan]" 267 | ] 268 | }, 269 | "execution_count": 9, 270 | "metadata": {}, 271 | "output_type": "execute_result" 272 | } 273 | ], 274 | "source": [ 275 | "artist_data = df[['artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude']].values[0].tolist()\n", 276 | "artist_data" 277 | ] 278 | }, 279 | { 280 | "cell_type": "markdown", 281 | "metadata": { 282 | "editable": true 283 | }, 284 | "source": [ 285 | "#### Insert Record into Artist Table\n", 286 | "Implement the `artist_table_insert` query in `sql_queries.py` and run the cell below to insert a record for this song's artist into the `artists` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `artists` table in the sparkify database." 287 | ] 288 | }, 289 | { 290 | "cell_type": "code", 291 | "execution_count": 10, 292 | "metadata": { 293 | "editable": true 294 | }, 295 | "outputs": [], 296 | "source": [ 297 | "cur.execute(artist_table_insert, artist_data)\n", 298 | "conn.commit()" 299 | ] 300 | }, 301 | { 302 | "cell_type": "markdown", 303 | "metadata": { 304 | "editable": true 305 | }, 306 | "source": [ 307 | "Run `test.ipynb` to see if you've successfully added a record to this table." 308 | ] 309 | }, 310 | { 311 | "cell_type": "markdown", 312 | "metadata": { 313 | "editable": true 314 | }, 315 | "source": [ 316 | "# Process `log_data`\n", 317 | "In this part, you'll perform ETL on the second dataset, `log_data`, to create the `time` and `users` dimensional tables, as well as the `songplays` fact table.\n", 318 | "\n", 319 | "Let's perform ETL on a single log file and load a single record into each table.\n", 320 | "- Use the `get_files` function provided above to get a list of all log JSON files in `data/log_data`\n", 321 | "- Select the first log file in this list\n", 322 | "- Read the log file and view the data" 323 | ] 324 | }, 325 | { 326 | "cell_type": "code", 327 | "execution_count": 11, 328 | "metadata": { 329 | "editable": true 330 | }, 331 | "outputs": [], 332 | "source": [ 333 | "log_files = get_files(\"data/log_data\")" 334 | ] 335 | }, 336 | { 337 | "cell_type": "code", 338 | "execution_count": 12, 339 | "metadata": { 340 | "editable": true 341 | }, 342 | "outputs": [], 343 | "source": [ 344 | "filepath = log_files[0]" 345 | ] 346 | }, 347 | { 348 | "cell_type": "code", 349 | "execution_count": 13, 350 | "metadata": { 351 | "editable": true 352 | }, 353 | "outputs": [ 354 | { 355 | "data": { 356 | "text/html": [ 357 | "
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artistauthfirstNamegenderitemInSessionlastNamelengthlevellocationmethodpageregistrationsessionIdsongstatustsuserAgentuserId
0Stephen LynchLogged InJaydenM0Bell182.85669freeDallas-Fort Worth-Arlington, TXPUTNextSong1.540992e+12829Jim Henson's Dead2001543537327796Mozilla/5.0 (compatible; MSIE 10.0; Windows NT...91
1ManowarLogged InJacobM0Klein247.56200paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Shell Shock2001543540121796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
2MorcheebaLogged InJacobM1Klein257.41016paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Women Lose Weight (Feat: Slick Rick)2001543540368796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
3Maroon 5Logged InJacobM2Klein231.23546paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Won't Go Home Without You2001543540625796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
4TrainLogged InJacobM3Klein216.76363paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Hey_ Soul Sister2001543540856796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
\n", 503 | "
" 504 | ], 505 | "text/plain": [ 506 | " artist auth firstName gender itemInSession lastName \\\n", 507 | "0 Stephen Lynch Logged In Jayden M 0 Bell \n", 508 | "1 Manowar Logged In Jacob M 0 Klein \n", 509 | "2 Morcheeba Logged In Jacob M 1 Klein \n", 510 | "3 Maroon 5 Logged In Jacob M 2 Klein \n", 511 | "4 Train Logged In Jacob M 3 Klein \n", 512 | "\n", 513 | " length level location method page \\\n", 514 | "0 182.85669 free Dallas-Fort Worth-Arlington, TX PUT NextSong \n", 515 | "1 247.56200 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 516 | "2 257.41016 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 517 | "3 231.23546 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 518 | "4 216.76363 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 519 | "\n", 520 | " registration sessionId song status \\\n", 521 | "0 1.540992e+12 829 Jim Henson's Dead 200 \n", 522 | "1 1.540558e+12 1049 Shell Shock 200 \n", 523 | "2 1.540558e+12 1049 Women Lose Weight (Feat: Slick Rick) 200 \n", 524 | "3 1.540558e+12 1049 Won't Go Home Without You 200 \n", 525 | "4 1.540558e+12 1049 Hey_ Soul Sister 200 \n", 526 | "\n", 527 | " ts userAgent userId \n", 528 | "0 1543537327796 Mozilla/5.0 (compatible; MSIE 10.0; Windows NT... 91 \n", 529 | "1 1543540121796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 530 | "2 1543540368796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 531 | "3 1543540625796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 532 | "4 1543540856796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 " 533 | ] 534 | }, 535 | "execution_count": 13, 536 | "metadata": {}, 537 | "output_type": "execute_result" 538 | } 539 | ], 540 | "source": [ 541 | "df = pd.read_json(filepath, lines=True)\n", 542 | "df.head()" 543 | ] 544 | }, 545 | { 546 | "cell_type": "markdown", 547 | "metadata": { 548 | "editable": true 549 | }, 550 | "source": [ 551 | "## #3: `time` Table\n", 552 | "#### Extract Data for Time Table\n", 553 | "- Filter records by `NextSong` action\n", 554 | "- Convert the `ts` timestamp column to datetime\n", 555 | " - Hint: the current timestamp is in milliseconds\n", 556 | "- Extract the timestamp, hour, day, week of year, month, year, and weekday from the `ts` column and set `time_data` to a list containing these values in order\n", 557 | " - Hint: use pandas' [`dt` attribute](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.html) to access easily datetimelike properties.\n", 558 | "- Specify labels for these columns and set to `column_labels`\n", 559 | "- Create a dataframe, `time_df,` containing the time data for this file by combining `column_labels` and `time_data` into a dictionary and converting this into a dataframe" 560 | ] 561 | }, 562 | { 563 | "cell_type": "code", 564 | "execution_count": 14, 565 | "metadata": { 566 | "editable": true 567 | }, 568 | "outputs": [ 569 | { 570 | "data": { 571 | "text/html": [ 572 | "
\n", 573 | "\n", 586 | "\n", 587 | " \n", 588 | " \n", 589 | " \n", 590 | " \n", 591 | " \n", 592 | " \n", 593 | " \n", 594 | " \n", 595 | " \n", 596 | " \n", 597 | " \n", 598 | " \n", 599 | " \n", 600 | " \n", 601 | " \n", 602 | " \n", 603 | " \n", 604 | " \n", 605 | " \n", 606 | " \n", 607 | " \n", 608 | " \n", 609 | " \n", 610 | " \n", 611 | " \n", 612 | " \n", 613 | " \n", 614 | " \n", 615 | " \n", 616 | " \n", 617 | " \n", 618 | " \n", 619 | " \n", 620 | " \n", 621 | " \n", 622 | " \n", 623 | " \n", 624 | " \n", 625 | " \n", 626 | " \n", 627 | " \n", 628 | " \n", 629 | " \n", 630 | " \n", 631 | " \n", 632 | " \n", 633 | " \n", 634 | " \n", 635 | " \n", 636 | " \n", 637 | " \n", 638 | " \n", 639 | " \n", 640 | " \n", 641 | " \n", 642 | " \n", 643 | " \n", 644 | " \n", 645 | " \n", 646 | " \n", 647 | " \n", 648 | " \n", 649 | " \n", 650 | " \n", 651 | " \n", 652 | " \n", 653 | " \n", 654 | " \n", 655 | " \n", 656 | " \n", 657 | " \n", 658 | " \n", 659 | " \n", 660 | " \n", 661 | " \n", 662 | " \n", 663 | " \n", 664 | " \n", 665 | " \n", 666 | " \n", 667 | " \n", 668 | " \n", 669 | " \n", 670 | " \n", 671 | " \n", 672 | " \n", 673 | " \n", 674 | " \n", 675 | " \n", 676 | " \n", 677 | " \n", 678 | " \n", 679 | " \n", 680 | " \n", 681 | " \n", 682 | " \n", 683 | " \n", 684 | " \n", 685 | " \n", 686 | " \n", 687 | " \n", 688 | " \n", 689 | " \n", 690 | " \n", 691 | " \n", 692 | " \n", 693 | " \n", 694 | " \n", 695 | " \n", 696 | " \n", 697 | " \n", 698 | " \n", 699 | " \n", 700 | " \n", 701 | " \n", 702 | " \n", 703 | " \n", 704 | " \n", 705 | " \n", 706 | " \n", 707 | " \n", 708 | " \n", 709 | " \n", 710 | " \n", 711 | " \n", 712 | " \n", 713 | " \n", 714 | " \n", 715 | " \n", 716 | " \n", 717 | "
artistauthfirstNamegenderitemInSessionlastNamelengthlevellocationmethodpageregistrationsessionIdsongstatustsuserAgentuserId
0Stephen LynchLogged InJaydenM0Bell182.85669freeDallas-Fort Worth-Arlington, TXPUTNextSong1.540992e+12829Jim Henson's Dead2001543537327796Mozilla/5.0 (compatible; MSIE 10.0; Windows NT...91
1ManowarLogged InJacobM0Klein247.56200paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Shell Shock2001543540121796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
2MorcheebaLogged InJacobM1Klein257.41016paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Women Lose Weight (Feat: Slick Rick)2001543540368796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
3Maroon 5Logged InJacobM2Klein231.23546paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Won't Go Home Without You2001543540625796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
4TrainLogged InJacobM3Klein216.76363paidTampa-St. Petersburg-Clearwater, FLPUTNextSong1.540558e+121049Hey_ Soul Sister2001543540856796\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...73
\n", 718 | "
" 719 | ], 720 | "text/plain": [ 721 | " artist auth firstName gender itemInSession lastName \\\n", 722 | "0 Stephen Lynch Logged In Jayden M 0 Bell \n", 723 | "1 Manowar Logged In Jacob M 0 Klein \n", 724 | "2 Morcheeba Logged In Jacob M 1 Klein \n", 725 | "3 Maroon 5 Logged In Jacob M 2 Klein \n", 726 | "4 Train Logged In Jacob M 3 Klein \n", 727 | "\n", 728 | " length level location method page \\\n", 729 | "0 182.85669 free Dallas-Fort Worth-Arlington, TX PUT NextSong \n", 730 | "1 247.56200 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 731 | "2 257.41016 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 732 | "3 231.23546 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 733 | "4 216.76363 paid Tampa-St. Petersburg-Clearwater, FL PUT NextSong \n", 734 | "\n", 735 | " registration sessionId song status \\\n", 736 | "0 1.540992e+12 829 Jim Henson's Dead 200 \n", 737 | "1 1.540558e+12 1049 Shell Shock 200 \n", 738 | "2 1.540558e+12 1049 Women Lose Weight (Feat: Slick Rick) 200 \n", 739 | "3 1.540558e+12 1049 Won't Go Home Without You 200 \n", 740 | "4 1.540558e+12 1049 Hey_ Soul Sister 200 \n", 741 | "\n", 742 | " ts userAgent userId \n", 743 | "0 1543537327796 Mozilla/5.0 (compatible; MSIE 10.0; Windows NT... 91 \n", 744 | "1 1543540121796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 745 | "2 1543540368796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 746 | "3 1543540625796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 \n", 747 | "4 1543540856796 \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4... 73 " 748 | ] 749 | }, 750 | "execution_count": 14, 751 | "metadata": {}, 752 | "output_type": "execute_result" 753 | } 754 | ], 755 | "source": [ 756 | "df = df[df['page'] == 'NextSong'].copy()\n", 757 | "df.head()" 758 | ] 759 | }, 760 | { 761 | "cell_type": "code", 762 | "execution_count": 15, 763 | "metadata": { 764 | "editable": true 765 | }, 766 | "outputs": [ 767 | { 768 | "data": { 769 | "text/plain": [ 770 | "0 2018-11-30 00:22:07.796\n", 771 | "1 2018-11-30 01:08:41.796\n", 772 | "2 2018-11-30 01:12:48.796\n", 773 | "3 2018-11-30 01:17:05.796\n", 774 | "4 2018-11-30 01:20:56.796\n", 775 | "Name: ts, dtype: datetime64[ns]" 776 | ] 777 | }, 778 | "execution_count": 15, 779 | "metadata": {}, 780 | "output_type": "execute_result" 781 | } 782 | ], 783 | "source": [ 784 | "t = pd.to_datetime(df[\"ts\"], unit='ms')\n", 785 | "t.head()" 786 | ] 787 | }, 788 | { 789 | "cell_type": "code", 790 | "execution_count": 16, 791 | "metadata": { 792 | "editable": true 793 | }, 794 | "outputs": [], 795 | "source": [ 796 | "time_data = (t, t.dt.hour, t.dt.day, t.dt.week, t.dt.month, t.dt.year, t.dt.weekday)\n", 797 | "column_labels = ('start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday')" 798 | ] 799 | }, 800 | { 801 | "cell_type": "code", 802 | "execution_count": 17, 803 | "metadata": { 804 | "editable": true 805 | }, 806 | "outputs": [ 807 | { 808 | "data": { 809 | "text/html": [ 810 | "
\n", 811 | "\n", 824 | "\n", 825 | " \n", 826 | " \n", 827 | " \n", 828 | " \n", 829 | " \n", 830 | " \n", 831 | " \n", 832 | " \n", 833 | " \n", 834 | " \n", 835 | " \n", 836 | " \n", 837 | " \n", 838 | " \n", 839 | " \n", 840 | " \n", 841 | " \n", 842 | " \n", 843 | " \n", 844 | " \n", 845 | " \n", 846 | " \n", 847 | " \n", 848 | " \n", 849 | " \n", 850 | " \n", 851 | " \n", 852 | " \n", 853 | " \n", 854 | " \n", 855 | " \n", 856 | " \n", 857 | " \n", 858 | " \n", 859 | " \n", 860 | " \n", 861 | " \n", 862 | " \n", 863 | " \n", 864 | " \n", 865 | " \n", 866 | " \n", 867 | " \n", 868 | " \n", 869 | " \n", 870 | " \n", 871 | " \n", 872 | " \n", 873 | " \n", 874 | " \n", 875 | " \n", 876 | " \n", 877 | " \n", 878 | " \n", 879 | " \n", 880 | " \n", 881 | " \n", 882 | " \n", 883 | " \n", 884 | " \n", 885 | " \n", 886 | " \n", 887 | " \n", 888 | " \n", 889 | "
start_timehourdayweekmonthyearweekday
02018-11-30 00:22:07.796030481120184
12018-11-30 01:08:41.796130481120184
22018-11-30 01:12:48.796130481120184
32018-11-30 01:17:05.796130481120184
42018-11-30 01:20:56.796130481120184
\n", 890 | "
" 891 | ], 892 | "text/plain": [ 893 | " start_time hour day week month year weekday\n", 894 | "0 2018-11-30 00:22:07.796 0 30 48 11 2018 4\n", 895 | "1 2018-11-30 01:08:41.796 1 30 48 11 2018 4\n", 896 | "2 2018-11-30 01:12:48.796 1 30 48 11 2018 4\n", 897 | "3 2018-11-30 01:17:05.796 1 30 48 11 2018 4\n", 898 | "4 2018-11-30 01:20:56.796 1 30 48 11 2018 4" 899 | ] 900 | }, 901 | "execution_count": 17, 902 | "metadata": {}, 903 | "output_type": "execute_result" 904 | } 905 | ], 906 | "source": [ 907 | "time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data)))\n", 908 | "time_df.head()" 909 | ] 910 | }, 911 | { 912 | "cell_type": "markdown", 913 | "metadata": { 914 | "editable": true 915 | }, 916 | "source": [ 917 | "#### Insert Records into Time Table\n", 918 | "Implement the `time_table_insert` query in `sql_queries.py` and run the cell below to insert records for the timestamps in this log file into the `time` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `time` table in the sparkify database." 919 | ] 920 | }, 921 | { 922 | "cell_type": "code", 923 | "execution_count": 18, 924 | "metadata": { 925 | "editable": true 926 | }, 927 | "outputs": [], 928 | "source": [ 929 | "for i, row in time_df.iterrows():\n", 930 | " cur.execute(time_table_insert, list(row))\n", 931 | " conn.commit()" 932 | ] 933 | }, 934 | { 935 | "cell_type": "markdown", 936 | "metadata": { 937 | "editable": true 938 | }, 939 | "source": [ 940 | "Run `test.ipynb` to see if you've successfully added records to this table." 941 | ] 942 | }, 943 | { 944 | "cell_type": "markdown", 945 | "metadata": { 946 | "editable": true 947 | }, 948 | "source": [ 949 | "## #4: `users` Table\n", 950 | "#### Extract Data for Users Table\n", 951 | "- Select columns for user ID, first name, last name, gender and level and set to `user_df`" 952 | ] 953 | }, 954 | { 955 | "cell_type": "code", 956 | "execution_count": 19, 957 | "metadata": { 958 | "editable": true 959 | }, 960 | "outputs": [], 961 | "source": [ 962 | "user_df = df[[\"userId\", \"firstName\", \"lastName\", \"gender\", \"level\"]]" 963 | ] 964 | }, 965 | { 966 | "cell_type": "markdown", 967 | "metadata": { 968 | "editable": true 969 | }, 970 | "source": [ 971 | "#### Insert Records into Users Table\n", 972 | "Implement the `user_table_insert` query in `sql_queries.py` and run the cell below to insert records for the users in this log file into the `users` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `users` table in the sparkify database." 973 | ] 974 | }, 975 | { 976 | "cell_type": "code", 977 | "execution_count": 20, 978 | "metadata": { 979 | "editable": true 980 | }, 981 | "outputs": [], 982 | "source": [ 983 | "for i, row in user_df.iterrows():\n", 984 | " cur.execute(user_table_insert, row)\n", 985 | " conn.commit()" 986 | ] 987 | }, 988 | { 989 | "cell_type": "markdown", 990 | "metadata": { 991 | "editable": true 992 | }, 993 | "source": [ 994 | "Run `test.ipynb` to see if you've successfully added records to this table." 995 | ] 996 | }, 997 | { 998 | "cell_type": "markdown", 999 | "metadata": { 1000 | "editable": true 1001 | }, 1002 | "source": [ 1003 | "## #5: `songplays` Table\n", 1004 | "#### Extract Data and Songplays Table\n", 1005 | "This one is a little more complicated since information from the songs table, artists table, and original log file are all needed for the `songplays` table. Since the log file does not specify an ID for either the song or the artist, you'll need to get the song ID and artist ID by querying the songs and artists tables to find matches based on song title, artist name, and song duration time.\n", 1006 | "- Implement the `song_select` query in `sql_queries.py` to find the song ID and artist ID based on the title, artist name, and duration of a song.\n", 1007 | "- Select the timestamp, user ID, level, song ID, artist ID, session ID, location, and user agent and set to `songplay_data`\n", 1008 | "\n", 1009 | "#### Insert Records into Songplays Table\n", 1010 | "- Implement the `songplay_table_insert` query and run the cell below to insert records for the songplay actions in this log file into the `songplays` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `songplays` table in the sparkify database." 1011 | ] 1012 | }, 1013 | { 1014 | "cell_type": "code", 1015 | "execution_count": 21, 1016 | "metadata": { 1017 | "editable": true 1018 | }, 1019 | "outputs": [], 1020 | "source": [ 1021 | "df['ts'] = pd.to_datetime(df['ts'], unit='ms')\n", 1022 | "for index, row in df.iterrows():\n", 1023 | "\n", 1024 | " # get songid and artistid from song and artist tables\n", 1025 | " cur.execute(song_select, (row.song, row.artist, row.length))\n", 1026 | " results = cur.fetchone()\n", 1027 | "\n", 1028 | " if results:\n", 1029 | " songid, artistid = results\n", 1030 | " else:\n", 1031 | " songid, artistid = None, None\n", 1032 | " # insert songplay record\n", 1033 | " songplay_data = [index+1, row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent]\n", 1034 | " cur.execute(songplay_table_insert, songplay_data)\n", 1035 | " conn.commit()" 1036 | ] 1037 | }, 1038 | { 1039 | "cell_type": "markdown", 1040 | "metadata": { 1041 | "editable": true 1042 | }, 1043 | "source": [ 1044 | "Run `test.ipynb` to see if you've successfully added records to this table." 1045 | ] 1046 | }, 1047 | { 1048 | "cell_type": "markdown", 1049 | "metadata": { 1050 | "editable": true 1051 | }, 1052 | "source": [ 1053 | "# Close Connection to Sparkify Database" 1054 | ] 1055 | }, 1056 | { 1057 | "cell_type": "code", 1058 | "execution_count": 22, 1059 | "metadata": { 1060 | "editable": true 1061 | }, 1062 | "outputs": [], 1063 | "source": [ 1064 | "conn.close()" 1065 | ] 1066 | }, 1067 | { 1068 | "cell_type": "markdown", 1069 | "metadata": { 1070 | "editable": true 1071 | }, 1072 | "source": [ 1073 | "# Implement `etl.py`\n", 1074 | "Use what you've completed in this notebook to implement `etl.py`." 1075 | ] 1076 | }, 1077 | { 1078 | "cell_type": "code", 1079 | "execution_count": null, 1080 | "metadata": { 1081 | "editable": true 1082 | }, 1083 | "outputs": [], 1084 | "source": [] 1085 | } 1086 | ], 1087 | "metadata": { 1088 | "kernelspec": { 1089 | "display_name": "Python 3", 1090 | "language": "python", 1091 | "name": "python3" 1092 | }, 1093 | "language_info": { 1094 | "codemirror_mode": { 1095 | "name": "ipython", 1096 | "version": 3 1097 | }, 1098 | "file_extension": ".py", 1099 | "mimetype": "text/x-python", 1100 | "name": "python", 1101 | "nbconvert_exporter": "python", 1102 | "pygments_lexer": "ipython3", 1103 | "version": "3.6.3" 1104 | } 1105 | }, 1106 | "nbformat": 4, 1107 | "nbformat_minor": 4 1108 | } 1109 | -------------------------------------------------------------------------------- /etl.py: -------------------------------------------------------------------------------- 1 | import os 2 | import glob 3 | import psycopg2 4 | import pandas as pd 5 | from sql_queries import * 6 | 7 | 8 | def process_song_file(cur, filepath): 9 | """Extract data from raw song JSON file and INSERT to 'songs' and 'artists' tables. 10 | 11 | Parameters 12 | ---------- 13 | cur : cursor 14 | cursor of psycopg2 database connection 15 | filepath : file 16 | song data file 17 | """ 18 | # open song file 19 | df = pd.read_json(filepath, dtype={'year': int}, lines=True) 20 | 21 | # insert song record 22 | song_data = df[['song_id', 'title', 'artist_id', 'year', 'duration']].values[0].tolist() 23 | cur.execute(song_table_insert, song_data) 24 | 25 | # insert artist record 26 | artist_data = df[['artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude']].values[0].tolist() 27 | cur.execute(artist_table_insert, artist_data) 28 | 29 | 30 | def process_log_file(cur, filepath): 31 | """Extract data from raw log JSON file and INSERT to 'time', 'users' and 'songplays' tables. 32 | 33 | Parameters 34 | ---------- 35 | cur : cursor 36 | cursor of psycopg2 database connection 37 | filepath : file 38 | log data file 39 | """ 40 | # open log file 41 | df = pd.read_json(filepath, lines=True) 42 | 43 | # filter by NextSong action 44 | df = df[df['page'] == 'NextSong'].copy() 45 | 46 | # convert timestamp column to datetime 47 | t = pd.to_datetime(df["ts"], unit='ms') 48 | 49 | # insert time data records 50 | time_data = (t, t.dt.hour, t.dt.day, t.dt.week, t.dt.month, t.dt.year, t.dt.weekday) 51 | column_labels = ('start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday') 52 | time_df = pd.DataFrame.from_dict(dict(zip(column_labels, time_data))) 53 | 54 | for i, row in time_df.iterrows(): 55 | cur.execute(time_table_insert, list(row)) 56 | 57 | # load user table 58 | user_df = df[["userId", "firstName", "lastName", "gender", "level"]] 59 | 60 | # insert user records 61 | for i, row in user_df.iterrows(): 62 | cur.execute(user_table_insert, row) 63 | 64 | # convert dataframe timestamp column to datetime 65 | df["ts"] = pd.to_datetime(df["ts"], unit='ms') 66 | 67 | # insert songplay records 68 | for index, row in df.iterrows(): 69 | 70 | # get songid and artistid from song and artist tables 71 | cur.execute(song_select, (row.song, row.artist, row.length)) 72 | results = cur.fetchone() 73 | 74 | if results: 75 | songid, artistid = results 76 | else: 77 | songid, artistid = None, None 78 | 79 | # insert songplay record 80 | songplay_data = [index+1, row.ts, row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent] 81 | cur.execute(songplay_table_insert, songplay_data) 82 | 83 | 84 | def process_data(cur, conn, filepath, func): 85 | """Load song_data and log_data files and execute respective function with each file. 86 | 87 | Parameters 88 | ---------- 89 | cur : cursor 90 | cursor of psycopg2 database connection. 91 | conn : connection 92 | connection of psycopg2 93 | filepath : string 94 | directory of files 95 | func : def 96 | function for processing of each file 97 | """ 98 | # get all files matching extension from directory 99 | all_files = [] 100 | for root, dirs, files in os.walk(filepath): 101 | files = glob.glob(os.path.join(root,'*.json')) 102 | for f in files : 103 | all_files.append(os.path.abspath(f)) 104 | 105 | # get total number of files found 106 | num_files = len(all_files) 107 | print('{} files found in {}'.format(num_files, filepath)) 108 | 109 | # iterate over files and process 110 | for i, datafile in enumerate(all_files, 1): 111 | func(cur, datafile) 112 | conn.commit() 113 | print('{}/{} files processed.'.format(i, num_files)) 114 | 115 | 116 | def main(): 117 | conn = psycopg2.connect("host=127.0.0.1 dbname=sparkifydb user=student password=student") 118 | cur = conn.cursor() 119 | 120 | process_data(cur, conn, filepath='data/song_data', func=process_song_file) 121 | process_data(cur, conn, filepath='data/log_data', func=process_log_file) 122 | 123 | conn.close() 124 | 125 | 126 | if __name__ == "__main__": 127 | main() -------------------------------------------------------------------------------- /sql_queries.py: -------------------------------------------------------------------------------- 1 | # DROP TABLES 2 | 3 | songplay_table_drop = "DROP TABLE IF EXISTS songplays" 4 | user_table_drop = "DROP TABLE IF EXISTS users" 5 | song_table_drop = "DROP TABLE IF EXISTS songs" 6 | artist_table_drop = "DROP TABLE IF EXISTS artists" 7 | time_table_drop = "DROP TABLE IF EXISTS time" 8 | 9 | # CREATE TABLES 10 | 11 | songplay_table_create = (""" 12 | CREATE TABLE IF NOT EXISTS songplays ( 13 | songplay_id int PRIMARY KEY, 14 | start_time timestamp NOT NULL, 15 | user_id int NOT NULL, 16 | level varchar, 17 | song_id varchar, 18 | artist_id varchar, 19 | session_id int NOT NULL, 20 | location varchar, 21 | user_agent varchar 22 | ); 23 | """) 24 | 25 | user_table_create = (""" 26 | CREATE TABLE IF NOT EXISTS users ( 27 | user_id int PRIMARY KEY, 28 | first_name varchar, 29 | last_name varchar, 30 | gender varchar, 31 | level varchar 32 | ); 33 | """) 34 | 35 | song_table_create = (""" 36 | CREATE TABLE IF NOT EXISTS songs ( 37 | song_id varchar PRIMARY KEY, 38 | title varchar, 39 | artist_id varchar NOT NULL, 40 | year int, 41 | duration numeric 42 | ); 43 | """) 44 | 45 | artist_table_create = (""" 46 | CREATE TABLE IF NOT EXISTS artists ( 47 | artist_id varchar PRIMARY KEY, 48 | name varchar, 49 | location varchar, 50 | latitude numeric, 51 | longitude numeric 52 | ); 53 | """) 54 | 55 | time_table_create = (""" 56 | CREATE TABLE IF NOT EXISTS time ( 57 | start_time timestamp PRIMARY KEY, 58 | hour int, 59 | day int, 60 | week int, 61 | month int, 62 | year int, 63 | weekday int 64 | ); 65 | """) 66 | 67 | # INSERT RECORDS 68 | 69 | songplay_table_insert = (""" 70 | INSERT INTO songplays (songplay_id, start_time, user_id, level, song_id, artist_id, session_id, location, user_agent) 71 | VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s) 72 | ON CONFLICT (songplay_id) 73 | DO NOTHING 74 | """) 75 | 76 | user_table_insert = (""" 77 | INSERT INTO users (user_id, first_name, last_name, gender, level) 78 | VALUES (%s, %s, %s, %s, %s) 79 | ON CONFLICT (user_id) 80 | DO UPDATE 81 | SET level = EXCLUDED.level; 82 | """) 83 | 84 | song_table_insert = (""" 85 | INSERT INTO songs (song_id, title, artist_id, year, duration) 86 | VALUES (%s, %s, %s, %s, %s) 87 | ON CONFLICT (song_id) 88 | DO NOTHING 89 | """) 90 | 91 | artist_table_insert = (""" 92 | INSERT INTO artists (artist_id, name, location, latitude, longitude) 93 | VALUES (%s, %s, %s, %s, %s) 94 | ON CONFLICT (artist_id) 95 | DO NOTHING 96 | """) 97 | 98 | 99 | time_table_insert = (""" 100 | INSERT INTO time (start_time, hour, day, week, month, year, weekday) 101 | VALUES (%s, %s, %s, %s, %s, %s, %s) 102 | ON CONFLICT (start_time) 103 | DO NOTHING 104 | """) 105 | 106 | # FIND SONGS 107 | 108 | song_select = (""" 109 | SELECT song_id, songs.artist_id FROM songs 110 | JOIN artists ON artists.artist_id = songs.artist_id 111 | WHERE title = %s 112 | AND name = %s 113 | AND duration = %s; 114 | """) 115 | 116 | # QUERY LISTS 117 | 118 | create_table_queries = [songplay_table_create, user_table_create, song_table_create, artist_table_create, time_table_create] 119 | drop_table_queries = [songplay_table_drop, user_table_drop, song_table_drop, artist_table_drop, time_table_drop] -------------------------------------------------------------------------------- /test.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": { 7 | "editable": true 8 | }, 9 | "outputs": [], 10 | "source": [ 11 | "%load_ext sql" 12 | ] 13 | }, 14 | { 15 | "cell_type": "code", 16 | "execution_count": 2, 17 | "metadata": { 18 | "editable": true 19 | }, 20 | "outputs": [ 21 | { 22 | "data": { 23 | "text/plain": [ 24 | "'Connected: student@sparkifydb'" 25 | ] 26 | }, 27 | "execution_count": 2, 28 | "metadata": {}, 29 | "output_type": "execute_result" 30 | } 31 | ], 32 | "source": [ 33 | "%sql postgresql://student:student@127.0.0.1/sparkifydb" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": 3, 39 | "metadata": { 40 | "editable": true 41 | }, 42 | "outputs": [ 43 | { 44 | "name": "stdout", 45 | "output_type": "stream", 46 | "text": [ 47 | " * postgresql://student:***@127.0.0.1/sparkifydb\n", 48 | "5 rows affected.\n" 49 | ] 50 | }, 51 | { 52 | "data": { 53 | "text/html": [ 54 | "\n", 55 | " \n", 56 | " \n", 57 | " \n", 58 | " \n", 59 | " \n", 60 | " \n", 61 | " \n", 62 | " \n", 63 | " \n", 64 | " \n", 65 | " \n", 66 | " \n", 67 | " \n", 68 | " \n", 69 | " \n", 70 | " \n", 71 | " \n", 72 | " \n", 73 | " \n", 74 | " \n", 75 | " \n", 76 | " \n", 77 | " \n", 78 | " \n", 79 | " \n", 80 | " \n", 81 | " \n", 82 | " \n", 83 | " \n", 84 | " \n", 85 | " \n", 86 | " \n", 87 | " \n", 88 | " \n", 89 | " \n", 90 | " \n", 91 | " \n", 92 | " \n", 93 | " \n", 94 | " \n", 95 | " \n", 96 | " \n", 97 | " \n", 98 | " \n", 99 | " \n", 100 | " \n", 101 | " \n", 102 | " \n", 103 | " \n", 104 | " \n", 105 | " \n", 106 | " \n", 107 | " \n", 108 | " \n", 109 | " \n", 110 | " \n", 111 | " \n", 112 | " \n", 113 | " \n", 114 | " \n", 115 | " \n", 116 | " \n", 117 | " \n", 118 | " \n", 119 | " \n", 120 | " \n", 121 | "
songplay_idstart_timeuser_idlevelsong_idartist_idsession_idlocationuser_agent
12018-11-30 00:22:07.79600091freeNoneNone829Dallas-Fort Worth-Arlington, TXMozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2; WOW64; Trident/6.0)
22018-11-30 01:08:41.79600073paidNoneNone1049Tampa-St. Petersburg-Clearwater, FL"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2"
32018-11-30 01:12:48.79600073paidNoneNone1049Tampa-St. Petersburg-Clearwater, FL"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2"
42018-11-30 01:17:05.79600073paidNoneNone1049Tampa-St. Petersburg-Clearwater, FL"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2"
52018-11-30 01:20:56.79600073paidNoneNone1049Tampa-St. Petersburg-Clearwater, FL"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2"
" 122 | ], 123 | "text/plain": [ 124 | "[(1, datetime.datetime(2018, 11, 30, 0, 22, 7, 796000), 91, 'free', None, None, 829, 'Dallas-Fort Worth-Arlington, TX', 'Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2; WOW64; Trident/6.0)'),\n", 125 | " (2, datetime.datetime(2018, 11, 30, 1, 8, 41, 796000), 73, 'paid', None, None, 1049, 'Tampa-St. Petersburg-Clearwater, FL', '\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2\"'),\n", 126 | " (3, datetime.datetime(2018, 11, 30, 1, 12, 48, 796000), 73, 'paid', None, None, 1049, 'Tampa-St. Petersburg-Clearwater, FL', '\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2\"'),\n", 127 | " (4, datetime.datetime(2018, 11, 30, 1, 17, 5, 796000), 73, 'paid', None, None, 1049, 'Tampa-St. Petersburg-Clearwater, FL', '\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2\"'),\n", 128 | " (5, datetime.datetime(2018, 11, 30, 1, 20, 56, 796000), 73, 'paid', None, None, 1049, 'Tampa-St. Petersburg-Clearwater, FL', '\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.78.2 (KHTML, like Gecko) Version/7.0.6 Safari/537.78.2\"')]" 129 | ] 130 | }, 131 | "execution_count": 3, 132 | "metadata": {}, 133 | "output_type": "execute_result" 134 | } 135 | ], 136 | "source": [ 137 | "%sql SELECT * FROM songplays LIMIT 5;" 138 | ] 139 | }, 140 | { 141 | "cell_type": "code", 142 | "execution_count": 4, 143 | "metadata": { 144 | "editable": true 145 | }, 146 | "outputs": [ 147 | { 148 | "name": "stdout", 149 | "output_type": "stream", 150 | "text": [ 151 | " * postgresql://student:***@127.0.0.1/sparkifydb\n", 152 | "5 rows affected.\n" 153 | ] 154 | }, 155 | { 156 | "data": { 157 | "text/html": [ 158 | "\n", 159 | " \n", 160 | " \n", 161 | " \n", 162 | " \n", 163 | " \n", 164 | " \n", 165 | " \n", 166 | " \n", 167 | " \n", 168 | " \n", 169 | " \n", 170 | " \n", 171 | " \n", 172 | " \n", 173 | " \n", 174 | " \n", 175 | " \n", 176 | " \n", 177 | " \n", 178 | " \n", 179 | " \n", 180 | " \n", 181 | " \n", 182 | " \n", 183 | " \n", 184 | " \n", 185 | " \n", 186 | " \n", 187 | " \n", 188 | " \n", 189 | " \n", 190 | " \n", 191 | " \n", 192 | " \n", 193 | " \n", 194 | " \n", 195 | " \n", 196 | " \n", 197 | " \n", 198 | " \n", 199 | " \n", 200 | " \n", 201 | "
user_idfirst_namelast_namegenderlevel
92RyannSmithFfree
78ChloeRothFfree
73JacobKleinMpaid
12AustinRosalesMfree
86AidenHessMfree
" 202 | ], 203 | "text/plain": [ 204 | "[(92, 'Ryann', 'Smith', 'F', 'free'),\n", 205 | " (78, 'Chloe', 'Roth', 'F', 'free'),\n", 206 | " (73, 'Jacob', 'Klein', 'M', 'paid'),\n", 207 | " (12, 'Austin', 'Rosales', 'M', 'free'),\n", 208 | " (86, 'Aiden', 'Hess', 'M', 'free')]" 209 | ] 210 | }, 211 | "execution_count": 4, 212 | "metadata": {}, 213 | "output_type": "execute_result" 214 | } 215 | ], 216 | "source": [ 217 | "%sql SELECT * FROM users LIMIT 5;" 218 | ] 219 | }, 220 | { 221 | "cell_type": "code", 222 | "execution_count": 5, 223 | "metadata": { 224 | "editable": true 225 | }, 226 | "outputs": [ 227 | { 228 | "name": "stdout", 229 | "output_type": "stream", 230 | "text": [ 231 | " * postgresql://student:***@127.0.0.1/sparkifydb\n", 232 | "1 rows affected.\n" 233 | ] 234 | }, 235 | { 236 | "data": { 237 | "text/html": [ 238 | "\n", 239 | " \n", 240 | " \n", 241 | " \n", 242 | " \n", 243 | " \n", 244 | " \n", 245 | " \n", 246 | " \n", 247 | " \n", 248 | " \n", 249 | " \n", 250 | " \n", 251 | " \n", 252 | " \n", 253 | "
song_idtitleartist_idyearduration
SOMZWCG12A8C13C480I Didn't Mean ToARD7TVE1187B99BFB10218.93179
" 254 | ], 255 | "text/plain": [ 256 | "[('SOMZWCG12A8C13C480', \"I Didn't Mean To\", 'ARD7TVE1187B99BFB1', 0, Decimal('218.93179'))]" 257 | ] 258 | }, 259 | "execution_count": 5, 260 | "metadata": {}, 261 | "output_type": "execute_result" 262 | } 263 | ], 264 | "source": [ 265 | "%sql SELECT * FROM songs LIMIT 5;" 266 | ] 267 | }, 268 | { 269 | "cell_type": "code", 270 | "execution_count": 6, 271 | "metadata": { 272 | "editable": true 273 | }, 274 | "outputs": [ 275 | { 276 | "name": "stdout", 277 | "output_type": "stream", 278 | "text": [ 279 | " * postgresql://student:***@127.0.0.1/sparkifydb\n", 280 | "1 rows affected.\n" 281 | ] 282 | }, 283 | { 284 | "data": { 285 | "text/html": [ 286 | "\n", 287 | " \n", 288 | " \n", 289 | " \n", 290 | " \n", 291 | " \n", 292 | " \n", 293 | " \n", 294 | " \n", 295 | " \n", 296 | " \n", 297 | " \n", 298 | " \n", 299 | " \n", 300 | " \n", 301 | "
artist_idnamelocationlatitudelongitude
ARD7TVE1187B99BFB1CasualCalifornia - LANaNNaN
" 302 | ], 303 | "text/plain": [ 304 | "[('ARD7TVE1187B99BFB1', 'Casual', 'California - LA', Decimal('NaN'), Decimal('NaN'))]" 305 | ] 306 | }, 307 | "execution_count": 6, 308 | "metadata": {}, 309 | "output_type": "execute_result" 310 | } 311 | ], 312 | "source": [ 313 | "%sql SELECT * FROM artists LIMIT 5;" 314 | ] 315 | }, 316 | { 317 | "cell_type": "code", 318 | "execution_count": 7, 319 | "metadata": { 320 | "editable": true 321 | }, 322 | "outputs": [ 323 | { 324 | "name": "stdout", 325 | "output_type": "stream", 326 | "text": [ 327 | " * postgresql://student:***@127.0.0.1/sparkifydb\n", 328 | "5 rows affected.\n" 329 | ] 330 | }, 331 | { 332 | "data": { 333 | "text/html": [ 334 | "\n", 335 | " \n", 336 | " \n", 337 | " \n", 338 | " \n", 339 | " \n", 340 | " \n", 341 | " \n", 342 | " \n", 343 | " \n", 344 | " \n", 345 | " \n", 346 | " \n", 347 | " \n", 348 | " \n", 349 | " \n", 350 | " \n", 351 | " \n", 352 | " \n", 353 | " \n", 354 | " \n", 355 | " \n", 356 | " \n", 357 | " \n", 358 | " \n", 359 | " \n", 360 | " \n", 361 | " \n", 362 | " \n", 363 | " \n", 364 | " \n", 365 | " \n", 366 | " \n", 367 | " \n", 368 | " \n", 369 | " \n", 370 | " \n", 371 | " \n", 372 | " \n", 373 | " \n", 374 | " \n", 375 | " \n", 376 | " \n", 377 | " \n", 378 | " \n", 379 | " \n", 380 | " \n", 381 | " \n", 382 | " \n", 383 | " \n", 384 | " \n", 385 | " \n", 386 | " \n", 387 | " \n", 388 | " \n", 389 | "
start_timehourdayweekmonthyearweekday
2018-11-30 00:22:07.796000030481120184
2018-11-30 01:08:41.796000130481120184
2018-11-30 01:12:48.796000130481120184
2018-11-30 01:17:05.796000130481120184
2018-11-30 01:20:56.796000130481120184
" 390 | ], 391 | "text/plain": [ 392 | "[(datetime.datetime(2018, 11, 30, 0, 22, 7, 796000), 0, 30, 48, 11, 2018, 4),\n", 393 | " (datetime.datetime(2018, 11, 30, 1, 8, 41, 796000), 1, 30, 48, 11, 2018, 4),\n", 394 | " (datetime.datetime(2018, 11, 30, 1, 12, 48, 796000), 1, 30, 48, 11, 2018, 4),\n", 395 | " (datetime.datetime(2018, 11, 30, 1, 17, 5, 796000), 1, 30, 48, 11, 2018, 4),\n", 396 | " (datetime.datetime(2018, 11, 30, 1, 20, 56, 796000), 1, 30, 48, 11, 2018, 4)]" 397 | ] 398 | }, 399 | "execution_count": 7, 400 | "metadata": {}, 401 | "output_type": "execute_result" 402 | } 403 | ], 404 | "source": [ 405 | "%sql SELECT * FROM time LIMIT 5;" 406 | ] 407 | }, 408 | { 409 | "cell_type": "markdown", 410 | "metadata": { 411 | "editable": true 412 | }, 413 | "source": [ 414 | "## REMEMBER: Restart this notebook to close connection to `sparkifydb`\n", 415 | "Each time you run the cells above, remember to restart this notebook to close the connection to your database. Otherwise, you won't be able to run your code in `create_tables.py`, `etl.py`, or `etl.ipynb` files since you can't make multiple connections to the same database (in this case, sparkifydb)." 416 | ] 417 | } 418 | ], 419 | "metadata": { 420 | "kernelspec": { 421 | "display_name": "Python 3", 422 | "language": "python", 423 | "name": "python3" 424 | }, 425 | "language_info": { 426 | "codemirror_mode": { 427 | "name": "ipython", 428 | "version": 3 429 | }, 430 | "file_extension": ".py", 431 | "mimetype": "text/x-python", 432 | "name": "python", 433 | "nbconvert_exporter": "python", 434 | "pygments_lexer": "ipython3", 435 | "version": "3.6.3" 436 | } 437 | }, 438 | "nbformat": 4, 439 | "nbformat_minor": 4 440 | } 441 | --------------------------------------------------------------------------------