Using Pandas to connect to SQL and write SQL queries

 

Exercise

Pandas and The Hello World of SQL Queries!

Here, you'll take advantage of the power of pandas to write the results of your SQL query to a DataFrame in one swift line of Python code!

You'll first import pandas and create the SQLite 'Chinook.sqlite' engine. Then you'll query the database to select all records from the Album table.

Recall that to select all records from the Orders table in the Northwind database, Hugo executed the following command:

df = pd.read_sql_query("SELECT * FROM Orders", engine)

# Import packages
from sqlalchemy import create_engine
import pandas as pd

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

# Execute query and store records in DataFrame: df
df = pd.read_sql_query("Select * FROM Album", engine)

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

# Open engine in context manager and store query result in df1
with engine.connect() as con:
    rs = con.execute("SELECT * FROM Album")
    df1 = pd.DataFrame(rs.fetchall())
    df1.columns = rs.keys()

# Confirm that both methods yield the same result
print(df.equals(df1))

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