How Can I Convert SQL Query Results into Pandas DataFrames?

Querying SQL Databases with Pandas

In order to efficiently store and manipulate data retrieved from SQL queries, it is necessary to convert the results into Pandas data structures.

Problem Statement:

A user seeks guidance on converting SQL query results into Pandas data structures. A sample query has been provided, and the user has indicated difficulty in understanding the return type of the query.

Solution:

To convert SQL query results to a Pandas DataFrame, the following steps can be taken:

1. Import the necessary libraries:

import pandas as pd
from sqlalchemy import create_engine

2. Create the SQL connection:

engine = create_engine('Your_SQL_Database_Url')
connection = engine.connect()

3. Execute the SQL query and retrieve results:

query = 'Your_SQL_Query'
results = connection.execute(query)

4. Convert results to a Pandas DataFrame:

df = pd.DataFrame(results.fetchall())
df.columns = results.keys()

Additional Considerations:

• Identifying Query Result Type: To determine the return type of the SQL query, you can use the fetchall() method to retrieve all rows of the result set. The output will be a list of tuples, with each tuple representing a row of data.
• Parsing Column Types: If desired, you can further parse the column types of the Pandas DataFrame by examining the description property of the query results.

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