The example is the name of the file with the download data for March 15, 2012. Then the file names end with the date, in YYYYMMDD representa3on. (There is also a weekly data file available which has a “W_” in this part of the file name.) Next comes an 8-‐digit number which is your Apple developer ID number (shown as eight X’s in the example), followed by another underscore. They always start with the prefix “S_”, followed by “D_” for the daily data file. ![]() The file names we download from Apple all have names like this: S_D_XXXXXXXX_20120315.txt. It is a common text data file format on Macintosh, and is some3mes referred to as a tab-‐separated values (or TSV) file. The first line usually contains column names. In this text data file format, each line represents a row of data column values on the line are separated by a tab character. Each download is a tab-‐delimited text file containing one day’s worth of data. They also provide a Java program called Autoingestion2 which can be used to automate the data download. Star.ng Point Apple’s iTunes Connect website allows us to interac3vely download sales data for our app. We want to take the raw download numbers that Apple provides, load them into JMP, and present them in a useful and pleasing way. Because our app is free, the sales amounts are always zero but it is interes3ng to track the number of downloads. As they do for all iOS app developers, Apple provides us with data on app sales and downloads. Since then we have released several updates, and the app has been downloaded over 10,000 3mes. We have an iPad® app! It’s called Graph Builder1, and it has been in the Apple App Store since March 5, 2012. ![]() Along the way, we learn how to summarize data, add formulas, add complex column proper3es, and add table scripts, all with JSL. This paper presents a case study of a working script that transforms raw iOS sales data into an easy-‐to-‐interpret graph. JSL is a powerful tool for manipula3ng raw data into the form needed for easy visualiza3on in JMP.
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