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Python

Microsoft Excel Python Connector

Read, write, and update Excel with Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Microsoft Excel!

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CData Drivers now work with AI Coding tools

Python Connector Libraries for Excel Data Connectivity. Integrate Excel with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Excel data with Python and any Python-based applications.

Features

Access Excel data either as an entire worksheet or from discrete ranges of data within a worksheet
Represent discrete blocks of data as tables through automatic detection or by manually specifying ranges of data
Optionally specify if the first row of data should be used for field names
Read tables that are oriented horizontally or vertically
Support for Excel XLSX file format, 2007 and above
Connect to live Microsoft Excel data, for real-time data access with the Microsoft Excel ODBC Driver
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Generate table schema automatically based on existing Microsoft Excel data or manually for greater control of the content you need
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Excel Connector.

Specifications

Python Database API (DB-API) Modules for Excel with bi-directional access.
Write SQL, get Microsoft Excel data. Access Excel through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Use Excel Spreadsheets as a simple real-time database to power Python-based applications.
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Microsoft Excel

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Excel with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Excel from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Excel
  • Query Excel to retrieve or update data
  • Connect your Excel data with Python data tools.


Connecting to Excel in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.excel as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM ExcelSheet")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("excel///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM ExcelSheet", engine)

df.plot()
plt.show()

Visualize Excel Data with pandas

The data-centric interfaces of the Excel Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

More than read-only: full update/CRUD support

Excel Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the Excel Connector as easily as interacting with a database table.

AI-assisted development with CData CLI

Build Excel integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Excel schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Excel.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI