Explore Financial Data in R | Finance Train

Explore Financial Data in R

November 14, 2019

4 min read

Now that we have the data file in our working directory, we can load it in our R session and start exploring it.

Use the following command to load the data into R.

1> loandata = read.csv("loan_data_2017.csv",stringsAsFactors=FALSE)
2

The “stringsAsFactors = FALSE” parameter turns off the automatic conversion of character strings to factors.

Let's set the seed to 0 so that we can replicate the results.

set.seed(0)

Before we proceed with our analysis, we need to understand what’s contained in the dataset. We may also possibly want to remove unwanted data and transform some data to make it usable for analysis.

Data Summary

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1> str(loandata)
2'data.frame':    133889 obs. of  145 variables:
3 $ id                                        : chr  "" "" "" "" ...
4 $ member_id                                 : logi  NA NA NA NA NA NA ...
5 $ loan_amnt                                 : int  10000 35000 20000 17475 8000 14400 18000 5800 12500 3000 ...
6... (List of all variables)
7

1> unique(loandata$loan_status)
2[1] "Fully Paid"         "Current"            "Late (31-120 days)" "Charged Off"       
3[5] "Late (16-30 days)"  "In Grace Period"    "Default"            ""                  
4>
5

> loandata <- subset(loandata, loan_status!='')

1> loandata %>% group_by(loan_status) %>% summarise(count = n())
2# A tibble: 4 x 2
3  loan_status        count
4  <chr>              <int>
51 Charged Off        15698
62 Default                9
73 Fully Paid         41833
84 Late (31-120 days)  2329
9>
10

Explore Financial Data in R

Data Summary

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Loan Statuses

Loan Statuses: Default and Fully Paid

Plotting Loan Status