/sql-server-query-to-pandas

How to connect to SQL Server in Python and create a Pandas data frame from a SQL join query.

Primary LanguageJupyter Notebook

SQL Server Query to Pandas

A simple example of connecting to SQL Server in Python, creating a table and returning a query into a Pandas dataframe.

  • The example file shows how to connect to SQL Server from Python and then how to run queries and return query results as a Pandas data frame.
  • Further analysis can be performed using Pandas.

GETTING STARTED

  • Install the packages - 'pandas' and 'pyodbc'
  • Open the included .ipynb file
  • Replace the details in the connection string with your SQL Server credentials
  • Follow the steps in the file included in order to:
    • Create a table
    • Insert data
    • Query the data
    • Turn the data into a list of lists for each row
    • Convert the list of lists into a pandas data frame

NOTES

  • If you are working with SQL Server Express or Developer edition and connect with Windows authentication, this line needs to be added to the connection string:
"Trusted_Connection=yes"
  • This will ignore the UID and PWD and allow you to connect via Windows authentication.