Data
Online-P2P-Lending

Online-P2P-Lending

active ARFF CC BY-SA 4.0 Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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P2P Lending I concatenated historical loans from both Prosper and Lending Club 2013 - 2018. Currently only the summary of the loan (terms, origination date, loan amount, status, etc) are up but detailed lender data will come soon. The columns are matched up as accurately as possible but there are estimated columns, see below for more info. Content To come.

18 features

loan_numbernumeric2874088 unique values
0 missing
amount_borrowednumeric6526 unique values
0 missing
termnumeric3 unique values
0 missing
borrower_ratenumeric863 unique values
0 missing
installmentnumeric157310 unique values
0 missing
gradestring7 unique values
0 missing
origination_datestring1459 unique values
0 missing
listing_titlestring14 unique values
863078 missing
principal_balancenumeric568401 unique values
0 missing
principal_paidnumeric641810 unique values
0 missing
interest_paidnumeric686488 unique values
0 missing
late_fees_paidnumeric22590 unique values
0 missing
debt_sale_proceeds_receivednumeric100087 unique values
0 missing
last_payment_datestring2564 unique values
0 missing
next_payment_due_datestring2210 unique values
0 missing
days_past_duenumeric1635 unique values
0 missing
loan_status_descriptionstring5 unique values
0 missing
data_sourcestring2 unique values
0 missing

19 properties

2875146
Number of instances (rows) of the dataset.
18
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
863078
Number of missing values in the dataset.
863078
Number of instances with at least one value missing.
11
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
61.11
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
30.02
Percentage of instances having missing values.
Average class difference between consecutive instances.
1.67
Percentage of missing values.

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