Datasets:
Tasks:
Text Classification
Sub-tasks:
topic-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
1M<n<10M
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
License:
| import csv | |
| import os | |
| import textwrap | |
| import datasets | |
| from datasets import TextClassification | |
| logger = datasets.logging.get_logger(__name__) | |
| _DESCRIPTION = textwrap.dedent( | |
| """\ | |
| The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming a commercial relationship with the consumer, or after 15 days, whichever comes first. Complaints referred to other regulators, such as complaints about depository institutions with less than $10 billion in assets, are not published in the Consumer Complaint Database. The database generally updates daily. | |
| There are multiple Text Classification problems that can be solved with this dataset: | |
| - Complaint Type Identification | |
| - Complaint Sub-Product Identification | |
| - Complaint from vulnerable or Service-person | |
| """ | |
| ) | |
| _CITATION = """\ | |
| """ | |
| _BASE_DOWNLOAD_URL = "https://files.consumerfinance.gov/ccdb/complaints.csv.zip" | |
| _HOMEPAGE = "https://www.consumerfinance.gov/data-research/consumer-complaints/" | |
| _LICENSE = "https://cfpb.github.io/source-code-policy/" | |
| _SUPPORTED_VERSIONS = [ | |
| datasets.Version("1.0.0", "Initial Version"), | |
| ] | |
| _DEFAULT_VERSION = datasets.Version("1.0.0", "Initial Version") | |
| _url = _BASE_DOWNLOAD_URL | |
| _TAGS = ["Servicemember", "Older American", "Older American, Servicemember", ""] | |
| _SUB_PRODUCT_CATEGORIES = [ | |
| "Credit reporting", | |
| "General-purpose credit card or charge card", | |
| "Checking account", | |
| "Other debt", | |
| "Second mortgage", | |
| "Conventional home mortgage", | |
| "I do not know", | |
| "Credit card debt", | |
| "Medical debt", | |
| "Federal student loan servicing", | |
| "FHA mortgage", | |
| "Conventional fixed mortgage", | |
| "Loan", | |
| "Other (i.e. phone, health club, etc.)", | |
| "Store credit card", | |
| "Installment loan", | |
| "Credit card", | |
| "Medical", | |
| "Mobile or digital wallet", | |
| "Private student loan", | |
| "Non-federal student loan", | |
| "Domestic (US) money transfer", | |
| "VA mortgage", | |
| "Vehicle loan", | |
| "Auto debt", | |
| "Payday loan", | |
| "Conventional adjustable mortgage (ARM)", | |
| "Other personal consumer report", | |
| "Payday loan debt", | |
| "Savings account", | |
| "Virtual currency", | |
| "Other bank product/service", | |
| "Other type of mortgage", | |
| "Other banking product or service", | |
| "Other mortgage", | |
| "International money transfer", | |
| "Lease", | |
| "General-purpose prepaid card", | |
| "Home equity loan or line of credit (HELOC)", | |
| "Government benefit card", | |
| "Mortgage debt", | |
| "Personal line of credit", | |
| "Home equity loan or line of credit", | |
| "Federal student loan debt", | |
| "Private student loan debt", | |
| "Credit repair services", | |
| "Title loan", | |
| "Auto", | |
| "Vehicle lease", | |
| "Mortgage", | |
| "Reverse mortgage", | |
| "General purpose card", | |
| "CD (Certificate of Deposit)", | |
| "Federal student loan", | |
| "Payroll card", | |
| "Debt settlement", | |
| "Check cashing service", | |
| "Traveler's check or cashier's check", | |
| "Gift card", | |
| "(CD) Certificate of deposit", | |
| "Money order", | |
| "Foreign currency exchange", | |
| "Refund anticipation check", | |
| "Gift or merchant card", | |
| "Cashing a check without an account", | |
| "ID prepaid card", | |
| "Mobile wallet", | |
| "Government benefit payment card", | |
| "Pawn loan", | |
| "Other special purpose card", | |
| "Check cashing", | |
| "Credit repair", | |
| "Traveler’s/Cashier’s checks", | |
| "Transit card", | |
| "Student prepaid card", | |
| "Electronic Benefit Transfer / EBT card", | |
| "", | |
| ] | |
| _PRODUCT_CATEGORIES = [ | |
| "Credit reporting, credit repair services, or other personal consumer reports", | |
| "Debt collection", | |
| "Mortgage", | |
| "Credit card or prepaid card", | |
| "Checking or savings account", | |
| "Credit reporting", | |
| "Student loan", | |
| "Money transfer, virtual currency, or money service", | |
| "Credit card", | |
| "Vehicle loan or lease", | |
| "Bank account or service", | |
| "Payday loan, title loan, or personal loan", | |
| "Consumer Loan", | |
| "Payday loan", | |
| "Money transfers", | |
| "Prepaid card", | |
| "Other financial service", | |
| "Virtual currency", | |
| ] | |
| class ConsumerComplaints(datasets.GeneratorBasedBuilder): | |
| """Consumer Complaints dataset.""" | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "Date Received": datasets.Value("timestamp[s]"), | |
| "Product": datasets.features.ClassLabel(names=_PRODUCT_CATEGORIES), | |
| "Sub Product": datasets.features.ClassLabel(names=_SUB_PRODUCT_CATEGORIES), | |
| "Issue": datasets.Value("string"), | |
| "Sub Issue": datasets.Value("string"), | |
| "Complaint Text": datasets.Value("string"), | |
| "Company Public Response": datasets.Value("string"), | |
| "Company": datasets.Value("string"), | |
| "State": datasets.Value("string"), | |
| "Zip Code": datasets.Value("string"), | |
| "Tags": datasets.features.ClassLabel(names=_TAGS), | |
| "Consumer Consent Provided": datasets.Value("string"), | |
| "Submitted via": datasets.Value("string"), | |
| "Date Sent To Company": datasets.Value("string"), | |
| "Company Response To Consumer": datasets.Value("string"), | |
| "Timely Response": datasets.Value("string"), | |
| "Consumer Disputed": datasets.Value("string"), | |
| "Complaint ID": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| task_templates=[ | |
| TextClassification(text_column="Complaint Text", label_column="Product"), | |
| TextClassification(text_column="Complaint Text", label_column="Sub Product"), | |
| TextClassification(text_column="Complaint Text", label_column="Tags"), | |
| ], | |
| ) | |
| def _split_generators(self, dl_manager): | |
| path = dl_manager.download_and_extract(_url) | |
| path = os.path.join(path, "complaints.csv") | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"filepath": path}, | |
| ) | |
| ] | |
| def _generate_examples(self, filepath): | |
| """Generate consumer complaints examples.""" | |
| with open(filepath, encoding="utf-8") as csv_file: | |
| csv_reader = csv.reader( | |
| csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True | |
| ) | |
| next(csv_reader) # skip header row | |
| for id_, row in enumerate(csv_reader): | |
| ( | |
| date_received, | |
| product, | |
| sub_product, | |
| issue, | |
| sub_issue, | |
| complaint_text, | |
| company_public_response, | |
| company, | |
| state, | |
| zip_code, | |
| tags, | |
| consumer_consent_provided, | |
| submitted_via, | |
| date_sent_to_company, | |
| company_response_to_consumer, | |
| timely_response, | |
| consumer_disputed, | |
| complaint_id, | |
| ) = row | |
| yield id_, { | |
| "Date Received": date_received, | |
| "Product": product, | |
| "Sub Product": sub_product, | |
| "Issue": issue, | |
| "Sub Issue": sub_issue, | |
| "Complaint Text": complaint_text, | |
| "Company Public Response": company_public_response, | |
| "Company": company, | |
| "State": state, | |
| "Zip Code": zip_code, | |
| "Tags": tags, | |
| "Consumer Consent Provided": consumer_consent_provided, | |
| "Submitted via": submitted_via, | |
| "Date Sent To Company": date_sent_to_company, | |
| "Company Response To Consumer": company_response_to_consumer, | |
| "Timely Response": timely_response, | |
| "Consumer Disputed": consumer_disputed, | |
| "Complaint ID": complaint_id, | |
| } | |