Understanding the Dataset/Dataset Overview

Our dataset has 64,814 rows/observations in 18 columns as shown below with their descriptions

  1. date_received (date): the date the CFPB sent the complaint to the company
  2. product_name (text): The type of product the consumer identified in the complaint
  3. sub_product (text): The type of sub-product the consumer identified in the complaint (not all Products have Sub-products)
  4. issue (text): The issue the consumer identified in the complaint (possible values are dependent on Product)
  5. sub-issue (text): The sub-issue the consumer identified in the complaint (possible values are dependent on Product and Issue, and not all Issues have corresponding Sub-issues)
  6. cosumer_compliant_narrative (text):
  7. company_public_response (text): This is how the company responded. For example, “Closed with explanation.”
  8. company (text):
  9. state_name (text): The state of the mailing address provided by the consumer
  10. zip_code (text):
  11. tags (text):
  12. consumer_consent_provided (text):
  13. submitted_via (varchar(50)): How the complaint was submitted to the CFPB
  14. date_sent_to_company (date):
  15. company_response_to_consumer:
  16. timely_response (text): whether the company gave a timely response (Yes/No)
  17. consumer_disputed (text):
  18. complaint_id: the unique identification number for a complaint

product_name: 11

  • Bank account or service
  • Consumer Loan
  • Credit card
  • Credit reporting
  • Debt collection
  • Money transfers
  • Mortgage
  • Other financial service
  • Payday loan
  • Prepaid card
  • Student loan

sub_product: 46

  • (CD) Certificate of deposit
  • Auto
  • Cashing a check without an account
  • Check cashing
  • Checking account
  • Conventional adjustable mortgage (ARM)
  • Conventional fixed mortgage
  • Credit card
  • Credit repair
  • Debt settlement
  • Domestic (US) money transfer
  • Electronic Benefit Transfer / EBT card
  • Federal student loan
  • FHA mortgage
  • Foreign currency exchange
  • General purpose card
  • Gift or merchant card
  • Government benefit payment card
  • Home equity loan or line of credit
  • I do not know
  • ID prepaid card
  • Installment loan
  • International money transfer
  • Medical
  • Mobile wallet
  • Money order
  • Mortgage
  • Non-federal student loan
  • Other (i.e. phone, health club, etc.)
  • Other bank product/service
  • Other mortgage
  • Other special purpose card
  • Pawn loan
  • Payday loan
  • Payroll card
  • Personal line of credit
  • Refund anticipation check
  • Reverse mortgage
  • Savings account
  • Second mortgage
  • Title loan
  • Transit card
  • VA mortgage
  • Vehicle lease
  • Vehicle loan

column, count, unique issue,, 91, sub_issue,, 68

1, date_received, date, date, YES, 2, product_name, text, text, YES, 3, sub_product, text, text, YES, 4, issue, text, text, YES, 5, sub_issue, text, text, YES, 6, cosumer_compliant_narrative, text, text, YES, 7, company_public_response, text, text, YES, 8, company, text, text, YES, 9, state_name, text, text, YES, 10, zip_code, text, text, YES, 11, tags, text, text, YES, 12, consumer_consent_provided, text, text, YES, 13, submitted_via, varchar(50), varchar, YES, 14, date_sent_to_company, date, date, YES, 15, company_response_to_consumer, text, text, YES, 16, timely_response, text, text, YES, 17, consumer_disputed, text, text, YES, 18, complaint_id, int, int, YES,

sn columns data_type      
1 date_received date      
2 product_name text      
3 sub_product text      
4 issue text      
5 sub_issue text text YES  
6 cosumer_compliant_narrative text text YES  
7 company_public_response text text YES  
8 company text text YES  
9 state_name text text YES  
10 zip_code text text YES  
11 tags text text YES  
12 consumer_consent_provided text text YES  
13 submitted_via varchar(50) varchar YES  
14 date_sent_to_company date date YES  
15 company_response_to_consumer text text YES  
16 timely_response text      
17 consumer_disputed text      
18 complaint_id int