Reading from SQL databases in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the pandas library.

Data Analysis Python

import [1] as pd

Drag options to blanks, or click blank then click option'

Asqlite3

Bpandas

Csqlalchemy

Dnumpy

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'numpy' instead of 'pandas' for data frames.

Importing 'sqlite3' when pandas is needed.

We use import pandas as pd to work with data tables easily.

2fill in blank

medium

Complete the code to create a connection to a SQLite database file named 'data.db'.

Data Analysis Python

import sqlite3
conn = sqlite3.[1]('data.db')

Drag options to blanks, or click blank then click option'

Acreate

Bopen

Cstart

Dconnect

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'open' instead of 'connect' causes an error.

Trying to use 'create' which is not a valid method here.

We use sqlite3.connect() to open a connection to the database file.

3fill in blank

hard

Fix the error in the code to read a SQL query into a pandas DataFrame.

Data Analysis Python

df = pd.read_sql_query([1], conn)

Drag options to blanks, or click blank then click option'

ASELECT * FROM table

B"SELECT * FROM table"

CSELECT * FROM table;

D'SELECT * FROM table'

Attempts:

3 left

💡 Hint

Common Mistakes

Writing the query without quotes causes a syntax error.

Adding a semicolon inside the string is optional but not required.

The SQL query must be a string, so it needs quotes around it.

4fill in blank

hard

Fill both blanks to create a DataFrame from a SQL table named 'employees' using pandas.

Data Analysis Python

df = pd.read_sql_table([1], [2])

Drag options to blanks, or click blank then click option'

A'employees'

Bconn

C'data.db'

Dsqlite3

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the database filename instead of the connection object.

Not quoting the table name string.

We pass the table name as a string and the connection object to read the table.

5fill in blank

hard

Fill all three blanks to read data from a SQL database using SQLAlchemy engine and pandas.

Data Analysis Python

from sqlalchemy import [1]
engine = [2]('sqlite:///data.db')
df = pd.read_sql([3], engine)

Drag options to blanks, or click blank then click option'

Acreate_engine

B'SELECT * FROM users'

DEngine

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'Engine' instead of 'create_engine' for import or engine creation.

Passing the query without quotes.

We import create_engine, use it to make an engine, then pass a SQL query string to pd.read_sql.

Practice

1. What is the main purpose of using pandas.read_sql_query() in Python when working with SQL databases?

easy

A. To close the database connection

B. To create a new SQL database

C. To write data from a DataFrame back to the database

D. To run an SQL query and get the result as a DataFrame

Solution

1. Step 1: Understand the function purpose

   pandas.read_sql_query() runs an SQL query on a database connection and returns the result as a pandas DataFrame.

2. Step 2: Compare options with function use

   Creating databases, closing connections, or writing data are not done by this function.

3. Final Answer:

   To run an SQL query and get the result as a DataFrame -> Option D

4. Quick Check:

   read_sql_query() = runs query and returns DataFrame [OK]

Hint: Remember: read_sql_query fetches data as DataFrame [OK]

Common Mistakes:

• Thinking it creates or modifies the database
• Confusing it with connection closing functions
• Assuming it writes data back to the database

2. Which of the following is the correct way to open a connection to a SQLite database file named data.db using Python's sqlite3 module?

easy

A. conn = sqlite3.open('data.db')

B. conn = sqlite3.connect('data.db')

C. conn = sqlite3.start('data.db')

D. conn = sqlite3.create('data.db')

Solution

1. Step 1: Recall sqlite3 connection syntax

   The correct method to open a connection is sqlite3.connect() with the database filename as argument.

2. Step 2: Check other options

   Methods like open, start, or create do not exist in sqlite3 for opening connections.

3. Final Answer:

   conn = sqlite3.connect('data.db') -> Option B

4. Quick Check:

   sqlite3.connect() opens DB connection [OK]

Hint: Use connect() to open SQLite DB connections [OK]

Common Mistakes:

• Using non-existent methods like open() or start()
• Confusing connect() with create()
• Forgetting to pass the database filename as a string

3. Given the following code, what will be the output?

import sqlite3
import pandas as pd
conn = sqlite3.connect(':memory:')
cursor = conn.cursor()
cursor.execute('CREATE TABLE users (id INTEGER, name TEXT)')
cursor.execute("INSERT INTO users VALUES (1, 'Alice')")
cursor.execute("INSERT INTO users VALUES (2, 'Bob')")
df = pd.read_sql_query('SELECT * FROM users WHERE id = 2', conn)
print(df)

medium

A. id name
0 2 Bob

B. id name
0 1 Alice

C. Empty DataFrame with columns [id, name]

D. SyntaxError due to SQL query

Solution

1. Step 1: Understand the SQL query

   The query selects rows from 'users' where id equals 2, so only Bob's row matches.

2. Step 2: Check DataFrame output

   The DataFrame will have one row with id=2 and name='Bob'.

3. Final Answer:

   id name 0 2 Bob -> Option A

4. Quick Check:

   SELECT * WHERE id=2 returns Bob [OK]

Hint: Filter by id=2 returns Bob's row only [OK]

Common Mistakes:

• Confusing id=1 with id=2
• Expecting all rows instead of filtered
• Thinking the query has syntax errors

4. What is wrong with this code snippet for reading data from a SQLite database?

import sqlite3
import pandas as pd
conn = sqlite3.connect('mydb.db')
df = pd.read_sql_query('SELECT * FROM sales', conn)
conn.close()
print(df.head())
print(conn.execute('SELECT * FROM sales'))

medium

A. Trying to execute a query after closing the connection causes an error

B. The SQL query syntax is incorrect

C. pandas.read_sql_query() cannot read from SQLite databases

D. The connection is never closed

Solution

1. Step 1: Identify connection usage

   The connection is closed with conn.close() before the last execute call.

2. Step 2: Understand error cause

   After closing, trying to run conn.execute() causes a runtime error because the connection is no longer open.

3. Final Answer:

   Trying to execute a query after closing the connection causes an error -> Option A

4. Quick Check:

   Closed connection cannot execute queries [OK]

Hint: Don't use connection after closing it [OK]

Common Mistakes:

• Assuming queries work after closing connection
• Thinking SQL syntax is wrong here
• Believing pandas can't read SQLite data

5. You want to read data from a SQL database and filter rows where the column age is greater than 30. Which of the following code snippets correctly does this and returns a pandas DataFrame?

hard

A. df = pd.read_sql_query('SELECT * FROM users WHERE age > 30', 'conn')

B. df = pd.read_sql_query('SELECT * FROM users WHERE age => 30', conn)

C. df = pd.read_sql_query('SELECT * FROM users WHERE age > 30', conn)

D. df = pd.read_sql_query('SELECT * FROM users WHERE age > "30"', conn)

Solution

1. Step 1: Check SQL syntax for filtering

   The correct SQL syntax for greater than is age > 30. df = pd.read_sql_query('SELECT * FROM users WHERE age > 30', conn) uses this correctly.

2. Step 2: Identify errors in other options

   df = pd.read_sql_query('SELECT * FROM users WHERE age => 30', conn) uses invalid operator =>. df = pd.read_sql_query('SELECT * FROM users WHERE age > "30"', conn) compares age to a string which may cause type issues. df = pd.read_sql_query('SELECT * FROM users WHERE age > 30', 'conn') passes connection as a string, which is incorrect.

3. Final Answer:

   df = pd.read_sql_query('SELECT * FROM users WHERE age > 30', conn) -> Option C

4. Quick Check:

   Correct SQL and connection object needed [OK]

Hint: Use > operator and pass connection object, not string [OK]

Common Mistakes:

• Using => instead of >
• Comparing numeric column to string
• Passing connection as string instead of object