Archive for the 'PyXLL' category

New Webinar: Supercharging Excel Analytics with Python

May 05 2014 Published by under PyXLL, Webinars

Python in Excel allows for interactive graphical data selection and cleansingJoin us for a webinar to see how the PyXLL Python for Excel add-in makes it easy to solve your biggest data analysis challenges with advanced Python tools and analytic engines.

Space is limited! Click a session link below to reserve your spot today:

Tuesday, May 13, 2014, 1:00-1:45 PM CDT
Wednesday, May 14, 2014, 8:00-8:45 AM CDT / 2:00-2:45 PM BST
Wednesday, May 21, 2014, 1:00-1:45 PM CDT

Who Should Attend

Anyone who wants a user-friendly solution to leverage the full power of Python’s data analysis libraries and parallel processing capabilities within Excel.

What You’ll Learn

Extending the native analytic capabilities of Excel or implementing Excel-backend analytics on a cluster or in the cloud with VBA, C++, and other legacy languages is challenging and time-consuming. Python’s elegant syntax and extensive ecosystem of analytic packages can greatly simplify the development of advanced analytic tools and cluster/cloud-based backend capabilities in Excel.

We’ll demonstrate how to:

  1. Implement Excel backend parallel computations on local clusters or cloud-based platforms such as Microsoft Azure with Python
  2. Use Python functions to implement advanced, interactive graphical analytic tools in ExcelGitHub_Logo
  3. Reduce risk by storing code in GitHub version control instead of embedded VBA in Excel files

Click a session link below to reserve your spot today:

Tuesday, May 13, 2014, 1:00-1:45 PM CDT
Wednesday, May 14, 2014, 8:00-8:45 AM CDT / 2:00-2:45 PM BST
Wednesday, May 21, 2014, 1:00-1:45 PM CDT

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PyXLL: Deploy Python to Excel Easily

Feb 06 2014 Published by under Canopy, Enthought Canopy, Finance, News, Python, PyXLL

PyXLL Solution Home | Buy PyXLL | Press Release

Today Enthought announced that it is now the worldwide distributor for PyXLL, and we’re excited to offer this key product for deploying Python models, algorithms and code to Excel. Technical teams can use the full power of Enthought Canopy, or another Python distro, and end-users can access the results in their familiar Excel environment. And it’s straightforward to set up and use.

Installing PyXLL from Enthought Canopy

PyXLL is available as a package subscription (with significant discounts for multiple users). Once you’ve purchased a subscription you can easily install it via Canopy’s Package Manager as shown in the screenshots below (note that at this time PyXLL is only available for Windows users). The rest of the configuration instructions are in the Quick Start portion of the documentation. PyXLL itself is a plug-in to Excel. When you start Excel, PyXLL loads into Excel and reads in Python modules that you have created for PyXLL. This makes PyXLL especially useful for organizations that want to manage their code centrally and deploy to multiple Excel users.

Enthought Canopy Package Manager   Install PyXLL from Enthought Canopy's Package Manager

Creating Excel Functions with PyXLL

To create a PyXLL Python Excel function, you use the @xl_func decorator to tell PyXLL the following function should be registered with Excel, what its argument types are, and optionally what its return type is. PyXLL also reads the function’s docstring and provides that in the Excel function description. As an example, I created a module my_pyxll_module.py and registered it with PyXLL via the PyXLL config file. In that module I put a simple function pyfib(): a naive Fibonacci implementation.

When I start Excel, I can access the Excel function wizard and find my pyfib() function and use it. The function documentation in Excel comes from my docstring. PyXLL parses the “n: integer input” portion as the variable documentation.

If I go back and make a change to the function, I can reload PyXLL without restarting Excel and update the cells. If I add another function to my module, it too will get loaded and be available to use in my worksheet.

So if you are developing Python models or functions for a large number of distributed Excel users, you can manage the code centrally. PyXLL will load new versions and new functions from the central repository whenever a user starts Excel. Deployment is very straightforward, and central management of all the code reduces the risk of Excel macros and functions proliferating uncontrolled.

I can also create menu functions using the decorator @xl_menu. PyXLL ships with several examples that you can start with. The one below adds a menu item to the Excel Add-in menu, and pops up a message box when selected.

       

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