Update (Feb 6, 2014): Enthought is now the exclusive distributor of PyXLL, a solution that helps users avoid “Excel Hell” by making it easy to develop add-ins for Excel in Python. Learn more here.
Didrik Pinte gave an informative, provocatively-titled presentation at the second, in-person New York Quantitative Python User’s Group (NY QPUG) meeting earlier this month.
There are a lot of examples in the press of Excel workflow mess-ups and spreadsheet errors contributing to some eye-popping mishaps in the finance world (e.g. JP Morgan’s spreadsheet issues may have led to the 2012 massive loss at “the London Whale”). Most of these can be traced to similar fundamental issues:
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Data referencing/traceability
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Numerical errors
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Error-prone manual operations (cut & paste, …)
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Tracing IO’s in libraries/API’s
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Missing version control
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Toolchain that doesn’t meet the needs of researchers, analysts, IT, etc.
Python, the coding language and its tool ecosystem, can provide a nice solution to these challenges, and many organizations are already turning to Python-based workflows in response. And with integration tools like PyXLL (to execute Python functions within Excel) and others, organizations can adopt Python-based workflows incrementally and start improving their current “Excel Hell” situation quickly.
For the details check out the video of Didrik’s NY QPUG presentation. He demonstrates a an example solution using PyXLL and Enthought Canopy.
[vimeo 67327735 http://vimeo.com/67327735]
And grab the PDF of his slides here.
QPUG_20130514_ExcelHell_Slides
It would be great to hear your stories about “Excel Hell”. Let us know below.
–Brett Murphy
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