August 2016
Beginner to intermediate
352 pages
9h 20m
English
Content preview from Foundations for Analytics with Python
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Chapter 5. Applications
Find a Set of Items in a Large Collection of Files
Companies accumulate a lot of files on various aspects of their business. There may be historical files on suppliers, customers, internal operations, and other aspects of business. As we’ve already discussed, this data can be stored in flat, delimited files like CSV files, in Excel workbooks and spreadsheets, or in other storage systems. It is worthwhile to save these files because they provide data for analyses, they can help you track changes over time, and they provide supporting evidence.
But when you have a lot of historical files, it can be difficult to find the data you need. Imagine you have a combination of 300 Excel workbooks and 200 CSV files (you’ve used both file extensions interchangeably over the years) that contain data on supplies you’ve purchased over the past five years. You are now in a discussion with a supplier and you want to find some historical records that contain data that can inform your discussion.
Sure, you can open each file, look for the records you need, and copy and paste the records to a new file, but think about how painstaking, time consuming, and error prone the process will be. This is an excellent situation to use your new Python coding skills to automate the whole process to save time and reduce the number of errors.
In order to simulate searching through hundreds of Excel workbooks and CSV files in a folder of historical files, we need to create the folder of historical ...
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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.