Connecting SQL database with Python

 Here, you're going to fire up your very first SQL engine. You'll create an engine to connect to the SQLite database 'Chinook.sqlite', which is in your working directory. Remember that to create an engine to connect to 'Northwind.sqlite', Hugo executed the command

engine = create_engine('sqlite:///Northwind.sqlite')

Here, 'sqlite:///Northwind.sqlite' is called the connection string to the SQLite database Northwind.sqlite. A little bit of background on the Chinook database: the Chinook database contains information about a semi-fictional digital media store in which media data is real and customer, employee and sales data has been manually created.


The Hello World of SQL Queries!

Now, it's time for liftoff! In this exercise, you'll perform the Hello World of SQL queries, SELECT, in order to retrieve all columns of the table Album in the Chinook database. Recall that the query SELECT * selects all columns.

from sqlalchemy import create_engine
import pandas as pd

# Create engine: engine
engine = create_engine('sqlite:///Chinook.sqlite')

# Open engine connection: con
con = engine.connect()


# Perform query: rs
rs = con.execute("Select * FROM Album")

# Save results of the query to DataFrame: df
df = pd.DataFrame(rs.fetchall())

# Close connection
con.close()


# Print head of DataFrame df
print(df.head())
New
with engine.connect() as con:
    rs = con.execute("Select LastName,Title FROM Employee")
    df = pd.DataFrame(rs.fetchmany(size=3))
    
    df.columns = rs.keys()

# Print the length of the DataFrame df
print(len(df))

# Print the head of the DataFrame df
print(df.head())

Code and modules

# Import necessary module
from sqlalchemy import create_engine

# Create engine: engine
engine = create_engine('sqlite:///Northwind.sqlite')


# Import necessary module
from sqlalchemy import create_engine

# Create engine: engine
engine = create_engine("sqlite:///Chinook.sqlite")

# Save the table names to a list: table_names
table_names = engine.table_names()


# Print the table names to the shell
print(table_names)


# Create engine: engine
engine = create_engine("sqlite:///Chinook.sqlite")

# Open engine in context manager
# Perform query and save results to DataFrame: df
with engine.connect() as con:
    rs = con.execute("SELECT * FROM EMPLOYEE WHERE EmployeeId >= 6 ")
    df = pd.DataFrame(rs.fetchall())
    df.columns = rs.keys()

# Print the head of the DataFrame df
print(df.head())



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