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Machine Learning with R Quick Start Guide

You're reading from   Machine Learning with R Quick Start Guide A beginner's guide to implementing machine learning techniques from scratch using R 3.5

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781838644338
Length 250 pages
Edition 1st Edition
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Author (1):
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Iván Pastor Sanz Iván Pastor Sanz
Author Profile Icon Iván Pastor Sanz
Iván Pastor Sanz
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Toc

Structuring data

After having acquired our target variable and knowing our dataset, we can now move on to the actual data collection based on our target. Here, we will try acquiring the data of the bank according to different years as described in the Collecting the target variable section.

To do this, we create a new variable extracting only the year when a bank went bankrupt, and then we count the number of banks by year:

failed_banks$year<-as.numeric(format(failed_banks$Closing.Date, "%Y"))

Failed_by_Year<-as.data.frame(table(failed_banks$year))
colnames(Failed_by_Year)<-c("year","Number_of_banks")

print(Failed_by_Year)
## year Number_of_banks
## 1 2000 2
## 2 2001 4
## 3 2002 11
## 4 2003 3
## 5 2004 4
## 6 2007 3
## 7 2008 25
...
You have been reading a chapter from
Machine Learning with R Quick Start Guide
Published in: Mar 2019
Publisher: Packt
ISBN-13: 9781838644338
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