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You're reading from  Jupyter for Data Science

Product typeBook
Published inOct 2017
Reading LevelBeginner
PublisherPackt
ISBN-139781785880070
Edition1st Edition
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Dan Toomey
Dan Toomey
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Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
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Analyzing changes in college admissions


We can look at trends in college admissions acceptance rates over the last few years. For this analysis, I am using the data on https://www.ivywise.com/ivywise-knowledgebase/admission-statistics.

First, we read in our dataset and show the summary points, from head to validate:

df <- read.csv("Documents/acceptance-rates.csv")summary(df)head(df)

We see the summary data for school acceptance rates as follows:

It's interesting to note that the acceptance rate varies so widely, from a low of 5 percent to a high of 41 percent in 2017.

Let us look at the data plots, again, to validate that the data points are correct:

plot(df)

From the correlation graphics shown, it does not look like we can use the data points from 2007. The graphs show a big divergence between 2007 and the other years, whereas the other three have good correlations.

So, we have 3 consecutive years of data from 25 major US universities. We can convert the data into a time series using a few steps...

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Jupyter for Data Science
Published in: Oct 2017Publisher: PacktISBN-13: 9781785880070

Author (1)

author image
Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Read more about Dan Toomey