August 2016
Beginner to intermediate
352 pages
9h 20m
English
Content preview from Foundations for Analytics with Python
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Chapter 3. Excel Files
Microsoft Excel is ubiquitous. We use Excel to store data on customers, inventory, and employees. We use it to track operations, sales, and financials. The list of ways people use Excel in business is long and diverse. Because Excel is such an integral tool in business, knowing how to process Excel files in Python will enable you to add Python into your data processing workflows, receiving data from other people and sharing results with them in ways they’re comfortable with.
Unlike Python’s csv module, there is not a standard module in Python for processing Excel files (i.e., files with the .xls or .xlsx extension). To complete the examples in this section, you need to have the xlrd and xlwt packages. The xlrd and xlwt packages enable Python to process Excel files on any operating system, and they have strong support for Excel dates. If you installed Anaconda Python, then you already have the packages because they’re bundled into the installation. If you installed Python from the Python.org website, then you need to follow the instructions in Appendix A to download and install the two packages.
A few words on terminology: when I refer to an “Excel file” that’s the same thing as an “Excel workbook.” An Excel workbook contains one or more Excel worksheets. In this chapter, I’ll be using the words “file” and “workbook” interchangeably, and I’ll refer to the individual worksheets within a workbook as worksheets.
As we did when working with CSV files in Chapter 2 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.