Using Microsoft SQL SQLSERVER with Python Pandas

Using Python Pandas dataframe to read and insert data to Microsoft SQL Server.

Cloning the repository

You can follow the steps below to clone the repository.

git clone  https://github.com/tomaztk/MSSQLSERVER_Pandas.git

Quickstart from Microsoft SQL Server

1. Clone the repository
2. Get connection to your SQL Server 2017+
3. Start using MSSQL Server with Python Pandas

-- sample table
SELECT TOP 10 
   name
  ,object_id
FROM sys.tables


EXECUTE sp_execute_external_script @language = N'Python'
      ,@script = N'
      import pandas as pd
      OutputDataSet = pd.DataFrame(InputDataSet);
      '
      , @input_data_1 = N'SELECT TOP 10 name,object_id FROM sys.tables'
WITH RESULT SETS((
        [Name] VARCHAR(150) NOT NULL
       ,[object_ID] CHAR(20) NOT NULL
         ));

Quickstart from Python IDE

1. Clone the repository
2. Open Python IDE
3. Enjoy

import pandas as pd
import pyodbc

sql_conn = pyodbc.connect('DRIVER={ODBC Driver 13 for SQL Server};  \
           SERVER=SQLSERVER2017;DATABASE=master;Trusted_Connection=yes') 
query = "SELECT * FROM sys.tables"
df = pd.read_sql(query, sql_conn)

df.head(3)

Collaboration and contributors

Contributions of any kind is highly appreciated! Fork the repository, add your code.

Contact

Feel free to get in touch for questions regarding Python and MSSQL Server connectivity.