Required information

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For Problems $9,10,$ and uarr, we will be cleaning a data file in preparation for subsequent analysis.

The analysis performed on LendingClub data In the chapter was for the years $2007-2012.$ We now use LendingClub data

for $2013.$

Consider the $2013$ rejected loan data from LendingClub titled "DAA Chapter $1-2$ Data.". SImilar to the analysis done In the chapter, let's

scrub the employment length. Because our analysls requires risk scores, debt$-$to$-$Income data, and employment length, we need to

make sure each of them has valid data.

a$.$ Sort the file based on employment length and remove those observatlons $($the complete row or record$)$ that have a missing score

$("$NA$").$ Note that we are including the employment lengths of zero, different than the analysis in the chapter text.

b$.$ Sort the file based on debt$-$to$-$Income and remove those observations $($the complete row or record$)$ that have a missing score, a

score of zero, or a negatlve score, similar to that done In Problem $10.$

c$.$ Sort the file based on risk score and remove those observations $($the complete row or record$)$ that have a missing score or a score

of zero, slmilar to that done in Problem $9.$

d$.$ There should now be $669\mathrm{.}993$ observations. Any thoughts on what blases are imposed when we remove observations? Is there

another way to do this?

e$.$ Run a PlvotTable analysis to show the number of Excellent Risk Scores but High DTI Bucket loans In each Employment year bucket.

Required:

After completing the steps above, answer the following questions by Inputting the corresponding employment level.