Data Science in R: A Case Studies Approach to Computational by Deborah Nolan, Duncan Temple Lang

By Deborah Nolan, Duncan Temple Lang

This booklet provides case experiences in statistical computing for info research. each one case research addresses a statistical program with a spotlight on evaluating varied computational methods and explaining the reasoning in the back of them. The case stories can function fabric for teachers instructing classes in statistical computing and utilized facts. The booklet aids readers in realizing the concept means of information research and the way to cause approximately computing.

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Extra info for Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving

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5) We can wrap this plotting routine into its own function so that we can parameterize the MAC address and angle, and if desired, other plotting parameters. Our function, called surfaceSS(), has 3 arguments: data for the offline summary data frame, and mac and angle, which supply the MAC address and angle to select the subset of the data that we want smoothed and plotted. We call surfaceSS() with a couple of MAC addresses and angles to compare them. To do this, we first modify R’s plotting parameters so that we can place 4 contour plots on one canvas, and we reduce the size allocated to the margins so more of the canvas is dedicated to the heat maps.

We can then rearrange them into the appropriate form. However, we can do this much more simply and generally using the fact that the split parameter for strsplit() can be a regular expression so we can split on any of several characters in a single function call. This means we can use tokens = strsplit(txt[4], "[;=,]")[[1]] to split at a ‘;’, ‘=’ or ‘,’ character. table() take a regular expression as a separator? If so, we can use it instead of readLines(). Unfortunately, it does not. It would slow down the reading of regular text files quite considerably.

0 signal Min. :-53 Max. factor)) Case Studies in Data Science in R 14 mac 00:0f:a3:39:e1:c0:145862 00:0f:a3:39:dd:cd:145619 00:14:bf:b1:97:8a:132962 00:14:bf:3b:c7:c6:126529 00:14:bf:b1:97:90:122315 00:14:bf:b1:97:8d:121325 (Other) :183831 channel 2462000000:189774 2437000000:152124 2412000000:145619 2432000000:126529 2427000000:122315 2442000000:121325 (Other) :120757 scanMac 00:02:2D:21:0F:33:978443 After examining these summaries, we find a couple of anomalies: • There is only one value for scanMac, the MAC address for the hand-held device from which the measurements were taken.

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