https://github.com/ganesyk12/odbc_io

Import Export csv Excel with Python [ Just for Learning ]
https://github.com/ganesyk12/odbc_io

excel-csv mssql mssqlserver pandas python

Last synced: about 1 month ago
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Import Export csv Excel with Python [ Just for Learning ]

• Host: GitHub
• URL: https://github.com/ganesyk12/odbc_io
• Owner: Ganesyk12
• License: mit
• Created: 2024-05-18T13:55:22.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-06-13T11:42:41.000Z (6 months ago)
• Last Synced: 2024-10-19T10:43:59.491Z (2 months ago)
• Topics: excel-csv, mssql, mssqlserver, pandas, python
• Language: Python
• Homepage:
• Size: 313 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Python odbc_IO !

  

  



## Exporting and Importing Data from _Excel_ to _SQL Server_ with Python

This project aims to facilitate users in transferring data between Excel files and SQL Server databases using the Python programming language. With this tool, you can easily extract data from Excel files, process it, and save it to the appropriate tables in SQL Server, or vice versa, extract data from SQL Server database and export it to Excel files.

## Key Features: 

-   **Exporting Excel Data to SQL Server**: You can export data from Excel files to SQL Server databases easily and efficiently. This process allows you to update or upload data into existing tables or automatically create new tables.

-   **Importing SQL Server Data to Excel**: This project also enables you to fetch data from tables in SQL Server databases and export them to Excel files. This is useful for generating reports or analyzing data using familiar spreadsheet tools.

-    **Support for Various Excel Formats**: Additionally, the project supports various Excel file formats, including .xls and .xlsx, so you can easily custom with different Excel versions. 

## _Prerequisite_ 💥

-   Microsoft SQL Server 2019  

-   Python 

-   Kaggle Dataset 	[ optional ]

## Installation ⚙

 - Create a Virtual Environtment in your project

   > python -m venv  _your_venv_name_

   
 You can see Documentation of Python venv in  Here. 

 - Activate the venv

   > source ./_your_venv_name_/Scripts/Activate

 - Install the Required Libraries

   > pip install _your_library_Name_

 

	| 	Libraries		| 		Version  	|

	|-----------------|-----------------|

	| Pyodbc				|	  	5.1.0			|

	| Pandas		 		| 		2.2.2			|

	| Pyler				|  	2.1.0			|

## Thanks for Supporting

####  Support me by 👇

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>Author : Ganes Yudha Kusuma

> _Copyright : @2024_