The document discusses 5 things that every data scientist should know about Excel. It begins by noting that Excel has been a secret weapon for decades and is still a useful data tool for data scientists. The 5 things are: 1) Named ranges for creating a makeshift database, 2) Sorting and filtering data in named ranges, 3) Using pivot tables to slice and dice data, 4) Conditional formatting to highlight cells that meet certain criteria, and 5) Visual Basic for advanced programming and custom solutions. The document encourages learning the basics of Excel as well as Visual Basic, noting that Excel is still a respectable data management and programming tool.

1. 4/6/2015 5 things should know about Excel about every data scientist
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Microsoft Excel has been one weapon for decades. I lists the go­to Excel
skills data scientists should master.
5 things should know about Excel about every data
scientist
When is the last time you opened Microsoft Excel to do some data science? If it's been a
while, you're missing out.
It's hard to have a discussion about data science tools (and there's a lot of that going on) ,
and the rest of the darlings in the corral of data science favorites, but what about Excel? I'm
sorry if Excel's not sophisticated enough for your data science needs ­­ or so you think.
Microsoft Excel has been a secret weapon of mine for decades ­­ it has been my ubiquitous
data tool ­­ and becoming a data scientist didn't stop me one bit from using it. Here are five
things about Excel that every data scientist should know.
[http://www.techrepublic.com/blog/10­things/10­steps­to­adding­a­timeline­to­an­excel­2013­
pivottable/]
Inserting a pivot table in a sheet in Excel 2013.
Image: Screenshot by Susan Harkins/TechRepublic

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Named ranges are a quick way to create a makeshift database in Excel. In simple terms, a
named range is a table of data that has a label for easy reference. No need to get fancy:
column headings across the top row and then rows of data below, following the typical
structure of any data table.
There are several ways to assign your custom name to the table, but I find it easiest to just
click in the top left corner (where the cell reference is displayed) and start typing. I typically
think of these as lookup tables, so I usually use the "lkp" prefix when naming them. Put your
primary key in the leftmost column and then use the VLOOKUP function anywhere in your
workbook to find any value in your table.
As soon as you have your named range in place, you can sort and filter with one click of the
filter button. This is a fast and easy way to explore your data set and possibly highlight
interesting rows or cells.
Once the range is in filter mode, it's good to inspect the filter drop­downs to get a sense of
the data in your data set. Excel's okay with combining types, so you can quickly spot data
errors just by looking at the different values in the filter drop­down. There's also an
extremely powerful Advanced Filtering functionality that allows you to filter your data set
based on criteria you specify in another range.
Pivot tables are a quick and easy way to slice and dice data. Although not as fully functional
as a full­blown business intelligence tool, pivot tables in Excel do a respectable job of
quickly cross­tabulating data and calculating counts, sums, and other aggregate metrics.
With your named range in place (are you getting the sense of how fundamental these are
when working with Excel?), click the pivot table button and then tell Excel where you want it
to go. For small jobs, I'll just put the pivot table next to the named range; for larger jobs, I'll
give the pivot table its own sheet. Now just drag and drop columns, rows, and values
(metrics) to dynamically create your cross­tab analysis. It's not Business Objects, but it's not
bad for a spreadsheet tool.
Conditional formatting is fun, and I hope Microsoft expands this functionality a bit in the
future. As its name implies, this feature allows you to format cells based on criteria you
specify (instead of static formatting where the cell always holds the same formatting).
1: Named ranges
2: Sorting and filtering
3: Pivot tables
4: Conditional formatting

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Posted 32 minutes ago by Matti Vuorela
For instance, you could tell Excel to format/highlight all cells in a named range that are
above a certain value. And if you want to get fancy, you can tell Excel to format cells based
on a formula that involves other cells. Excel has some built­in formats that make it easy to
quickly create a heat map or even an icon overlay. However, you're limited on the icons you
can select, and you cannot easily extract the exact color from a heat map. Overall though, it
does the trick for most situations.
We come to the most powerful feature Excel has to offer: Visual Basic. That's right, Visual
Basic. I know what you're thinking ­­ you're far too advanced for Visual Basic, right?
Visual Basic and Excel are awesome in the hands of a data scientist. You already know how
to program, so picking up Visual Basic won't be hard. And Visual Basic opens up a whole
new world of creative solutions with Excel ­­ everything from creating your own Excel­
based neural network, to Monte Carlo simulations, to anything else you can dream up.
Excel does have its limits, so don't push it. For the hard­core work, you're much better off
with R or Python. But don't discount Excel for a quick prototype or proof­of­concept.
Although Excel isn't a top resume­building skill for data scientists, you'd be remiss if you
didn't learn its ins and outs. Over and above the obvious features, which handle statistical
and mathematical formulae pretty well, Excel is a respectable data management and
programming tool.
First learn the basics of named ranges and filtering, and then move on to more advanced
features like pivot tables and conditional formatting. Finally, learn Visual Basic for Excel. It's
really not hard to pick up one more language, and it's well worth the trouble. And don't worry
­­ nobody will take away your data scientist badge for learning Excel.
5: Visual Basic
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