Using Python Pandas dataframe to read and insert data to Microsoft SQL Server
Last updated Jun 25, 2026
32
Stars
15
Forks
0
Issues
0
Stars/day
Attention Score
21
Language breakdown
No language data available.
▸ Files
click to expand
README
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
- Clone the repository
- Get connection to your SQL Server 2017+
- Start using MSSQL Server with Python Pandas
sql
-- sample table
SELECT TOP 10
name
,object_id
FROM sys.tables
EXECUTE spexecuteexternal_script @language = N'Python' ,@script = N' import pandas as pd OutputDataSet = pd.DataFrame(InputDataSet); ' , @inputdata1 = 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
- Clone the repository
- Open Python IDE
- Enjoy
python
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.readsql(query, sqlconn)
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.🔗 More in this category