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<title>Preparing the LendingClubData Dataset</title>
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<h1 class="title toc-ignore">Preparing the LendingClubData Dataset</h1>
<h4 class="author"><em>Ryan Kuhn</em></h4>
<div id="introduction" class="section level3">
<h3>Introduction</h3>
<p>Lending Club (LC) publishes data on all of the loans issued on their platform since 2007. The data is updated on a quarterly basis- roughly 6 weeks after the quarter close. The LendingClubData package contains a dataset with this historical data. It will be updated as new data is published. The following is the code used to obtain the data from Lending Club.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(LendingClubData)
<span class="kw">library</span>(dplyr)</code></pre></div>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">Links<-<span class="st"> </span><span class="kw">character</span>()
Links[<span class="dv">1</span>]<-<span class="st"> "LoanStats3a.csv"</span>
Links[<span class="dv">2</span>]<-<span class="st"> "LoanStats3b.csv"</span>
Links[<span class="dv">3</span>]<-<span class="st"> "LoanStats3c.csv"</span>
Links[<span class="dv">4</span>]<-<span class="st"> "LoanStats3d.csv"</span>
Links[<span class="dv">5</span>]<-<span class="st"> "LoanStats_2016Q1.csv"</span>
Links[<span class="dv">6</span>]<-<span class="st"> "LoanStats_2016Q2.csv"</span>
Links[<span class="dv">7</span>]<-<span class="st"> "LoanStats_2016Q3.csv"</span></code></pre></div>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">path<-<span class="kw">tempdir</span>()
<span class="kw">lapply</span>(<span class="kw">paste0</span>(<span class="st">"https://resources.lendingclub.com/"</span>,Links,<span class="st">".zip"</span>),
GetLoanData,
<span class="dt">directory=</span>path)
df_list<-<span class="st"> </span><span class="kw">lapply</span>(<span class="kw">paste0</span>(path,<span class="st">"</span><span class="ch">\\</span><span class="st">"</span>,Links),
Prep_Loan_Data)
dat<-<span class="st"> </span>plyr::<span class="kw">rbind.fill</span>(df_list)</code></pre></div>
<p>The dataset is too big to be hosted on Github as a single file, even compressed as an .rda file. To get around this limitation, I have split the dataset into two data frames and then created a function which combines them again.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">split<-<span class="st"> </span><span class="kw">floor</span>(<span class="kw">nrow</span>(dat)/<span class="dv">2</span>)
LendingClubData_1<-<span class="st"> </span>dat[<span class="dv">1</span>:split,]
LendingClubData_2<-<span class="st"> </span>dat[(split<span class="dv">+1</span>):<span class="kw">nrow</span>(dat),]
<span class="kw">save</span>(LendingClubData_1, <span class="dt">file=</span><span class="st">"data/LendingClubData_1.rda"</span>)
<span class="kw">save</span>(LendingClubData_2, <span class="dt">file=</span><span class="st">"data/LendingClubData_2.rda"</span>)</code></pre></div>
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