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Comment by kfk | Hacker News Reader

I work in finance, I toyed with Python and Pandas and CSV files for a while, it won't do. When you get at it, you soon realize that any kind of decision will have to come from high level numbers, no the billions of rows you hear on HN and, in that area, it makes simply no sense using anything other than Excel.

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Pandas has all sorts of functionality for summarizing data. I can see sticking with the tool you know or preferring a pointy clicky interface, but you are implying the capability to generate those high level numbers is missing, and it isn't.

Just because something can summarize data doesn't mean it's the best tool to use when trying to explain something. Executives and VC's with non-technical backgrounds might be intimidated by someone using relatively complex tools for what, to them, could be a basic spreadsheet on a platform they know how to use themselves. Excel's value comes mostly from the fact that everyone knows how to use it at some level, and the formulas are relatively easy to follow, so your audience knows they could probably reproduce and verify your work.

Valid Point: High-Ranked execs use it and usually try to translate everything into excel sheets. They would really appreciate seeing excel sheets in presentations.

Invalid point: Formulae are easy to follow and audience can easily verify/reproduce your work.

My friend, excel rocks when MAKING a spreadsheet, but it can be hellishly annoying to follow. when you got a long chain of formulae cells, it is very annoying to trace the data through it to see where it is coming form. Sure, a properly labelled Sheet takes care of it, but that's not usually the case. That's the main reason i am very excited about that excel-sheet visualization tool posted here the other day.

It may be hellishly annoying to follow (and trust me, I've had to clean up many Frankenstein-esque spreadsheets), but it's imo easier than any sort of messy code. Which do you think is harder for Average Joe Exec - following poorly documented and messy code, or following a poorly documented and messy spreadsheet?

PS I'm also very excited for that tool. Will make my life so much easier.

I agree with your valid point, re

>> Invalid point: Formulae are easy to follow and audience can easily verify/reproduce your work.

Actually this is another valid point of Excel.

Unless the financial model was done incorrectly (using VBA, complicated formula chains, unclear logic), it is very easy to verify financial model in Excel, which is a big plus.

Excel has been partly to blame for many bugs in mathematical models, in part because of its datatypes and in part because of its builtins. Some of these bugs are not at all easy to spot, depending on how you go about the building and the verifying.

What mathematical models? For your company financial assumptions and forecasts you generally need, in essence, the sum(...) function, percentages and multiplication, repeated ad nauseam, and if any of your formulas even have space for 'not easy to spot' bugs then the bug is in thinking of making such formulas in the first place.

Your spreadsheets would be big because of quantity of different things included, not because of complexity of those things

If it won't take you too long, would you mind sharing a couple of examples?

High level? Think about cash flow forecast. How you do this? You need to model your income statement and balance sheet. Start building up assumptions for: sales (duh), accounts receivables, overdues, your cogs, inventory, possible capex investments, opex, etc.

This is very structured data, you can build up hierarchy trees in python, but it will take you too long. Plus, your models will change, people will want to see things from many different changing angles.

Unfortunately, every time I start writing about controlling people desert the thread around here, but it is a fascinating topic.

Go on. I'd like to hear more.

I answer all on this topic, just shoot me an email

My obvious example is "what do we have to do to break even?"

What a spreadsheet does very well is allow you to quickly run a large set of simulations right next to eachother for comparison. This can be useful in asking questions like, "if we charge $x, and we have $y in fixed expenses, what should our target of support personnel to customers be?"

You can do that perfectly well with R. Heck, R was designed with that kind of workloads in mind. With RStudio you can even present a table which the non-programmers can directly manipulate to test those conditions.

I usually use spreadsheets only as data entry software and then R does the rest.

If your data is entered in a spreadsheet, is it really faster and easier for you to run the data through another tool, rather than just writing the formulas right there in front of you?

You definitely can do it in R, but the formulas are trivial anyway and writing them in code takes as much time as in Excel, can you help me understand what I could gain by using R here?

I imagine that the spreadsheet is there to support an easy input format that anyone can get involved with. The spreadsheet basically only holds the assumptions and the facts. Then all the modeling is done in something where following the flow control is far more readable because you're dealing with long well named variables, which are rare to none existent in most spreadsheets.

When I worked in Wall Street level finance, basically none of the analysts bothered to use anything more than cell address, e.g. /[A-Z]\{0,1}[0-9]\{0,3}/. They basically treated naming their variables like most software engineers treat commenting their code. That shit was impossible to follow because.

The individual formulas may be trivial, but when you have a complex model with many pages representing different aspects of the business internally and external macro aspects, it can get messy fast.

No doubt, but I would be very surprised if one could set up an R simulation quicker than one could set up a comparable spreadsheet. I don't see R and spreadsheets as interchangeable. They are very complimentary technologies.

This looks promising: http://wiki.openoffice.org/wiki/R_and_Calc

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