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"""Breast Dataset""" |
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from typing import List |
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import datasets |
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import pandas |
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VERSION = datasets.Version("1.0.0") |
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_ORIGINAL_FEATURE_NAMES = [ |
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"checking_account_status", |
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"account_life_in_months", |
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"credit_status", |
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"loan_purpose", |
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"current_credit", |
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"current_savings", |
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"employed_since", |
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"installment_rate_percentage", |
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"personal_status_and_sex", |
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"guarantors", |
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"years_living_in_current_residence", |
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"property", |
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"age", |
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"installment_plans", |
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"housing_status", |
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"nr_credit_accounts_in_bank", |
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"job_status", |
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"number_of_people_in_support", |
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"has_registered_phone_number", |
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"is_foreign", |
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"loan_granted", |
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] |
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_BASE_FEATURE_NAMES = [ |
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"checking_account_status", |
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"account_life_in_months", |
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"credit_status", |
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"loan_purpose", |
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"current_credit", |
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"current_savings", |
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"employed_since", |
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"installment_rate_percentage", |
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"sex", |
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"marital_status", |
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"guarantors", |
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"years_living_in_current_residence", |
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"age", |
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"installment_plans", |
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"housing_status", |
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"nr_credit_accounts_in_bank", |
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"job_status", |
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"number_of_people_in_support" |
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"has_registered_phone_number", |
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"is_foreign", |
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"loan_granted" |
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] |
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DESCRIPTION = "Breast dataset for cancer prediction." |
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_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Statlog+%28German+Credit+Data%29" |
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_URLS = ("https://archive.ics.uci.edu/ml/datasets/Statlog+%28German+Credit+Data%29") |
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_CITATION = """ |
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""" |
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urls_per_split = { |
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"train": "https://huggingface.co/datasets/mstz/breast/raw/main/german.data", |
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} |
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features_types_per_config = { |
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"encoding": { |
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"feature": datasets.Value("string"), |
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"original_value": datasets.Value("string"), |
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"encoded_value": datasets.Value("int8"), |
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}, |
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"loan": { |
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"checking_account_status": datasets.Value("int8"), |
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"account_life_in_months": datasets.Value("int8"), |
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"credit_status": datasets.Value("int8"), |
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"loan_purpose": datasets.Value("string"), |
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"current_credit": datasets.Value("int8"), |
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"current_savings": datasets.Value("int8"), |
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"employed_since": datasets.Value("int8"), |
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"installment_rate_percentage": datasets.Value("int8"), |
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"sex": datasets.Value("int8"), |
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"marital_status": datasets.Value("string"), |
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"guarantors": datasets.Value("int8"), |
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"years_living_in_current_residence": datasets.Value("int8"), |
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"age": datasets.Value("int8"), |
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"installment_plans": datasets.Value("string"), |
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"housing_status": datasets.Value("int8"), |
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"nr_credit_accounts_in_bank": datasets.Value("int8"), |
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"job_status": datasets.Value("int8"), |
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"number_of_people_in_support": datasets.Value("int8"), |
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"has_registered_phone_number": datasets.Value("int8"), |
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"is_foreign": datasets.Value("int8"), |
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"loan_granted": datasets.ClassLabel(num_classes=2, names=("no", "yes")) |
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} |
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} |
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features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config} |
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class BreastConfig(datasets.BuilderConfig): |
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def __init__(self, **kwargs): |
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super(BreastConfig, self).__init__(version=VERSION, **kwargs) |
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self.features = features_per_config[kwargs["name"]] |
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class Breast(datasets.GeneratorBasedBuilder): |
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DEFAULT_CONFIG = "loan" |
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BUILDER_CONFIGS = [ |
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BreastConfig(name="encoding", |
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description="Encoding dictionaries for discrete features."), |
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BreastConfig(name="loan", |
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description="Binary classification of loan approval."), |
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] |
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def _info(self): |
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if self.config.name not in features_per_config: |
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raise ValueError(f"Unknown configuration: {self.config.name}") |
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info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE, |
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features=features_per_config[self.config.name]) |
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return info |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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downloads = dl_manager.download_and_extract(urls_per_split) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}), |
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] |
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def _generate_examples(self, filepath: str): |
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data = pandas.read_csv(filepath, header=None) |
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data.columns=_ORIGINAL_FEATURE_NAMES |
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data = self.preprocess(data, config=self.config.name) |
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for row_id, row in data.iterrows(): |
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data_row = dict(row) |
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yield row_id, data_row |
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def preprocess(self, data: pandas.DataFrame, config: str = "cancer") -> pandas.DataFrame: |
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data.loc[:, "checking_account_status"] = data.checking_account_status.apply(self.encode_checking_account_status) |
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data.loc[:, "credit_status"] = data.credit_status.apply(self.encode_credit_status) |
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data.loc[:, "current_savings"] = data.current_savings.apply(self.encode_current_savings) |
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data.loc[:, "employed_since"] = data.employed_since.apply(self.encode_employed_since) |
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data.loc[:, "guarantors"] = data.guarantors.apply(self.encode_guarantors) |
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data.loc[:, "has_registered_phone_number"] = data.has_registered_phone_number.apply(self.encode_has_registered_phone_number) |
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data.loc[:, "housing_status"] = data.housing_status.apply(self.encode_housing_status) |
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data.loc[:, "installment_plans"] = data.installment_plans.apply(self.encode_installment_plans) |
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data.loc[:, "is_foreign"] = data.is_foreign.apply(self.encode_is_foreign) |
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data.loc[:, "job_status"] = data.job_status.apply(self.encode_job_status) |
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data.loc[:, "loan_granted"] = data.loan_granted.apply(self.encode_loan_granted) |
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data.loc[:, "marital_status"] = data.marital_status.apply(self.encode_marital_status) |
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data.loc[:, "sex"] = data.sex.apply(self.encode_sex) |
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data.drop("personal_status_and_sex", axis="columns", inplace=True) |
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data = data[_BASE_FEATURE_NAMES] |
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if config == "loan": |
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return data |
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else: |
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raise ValueError(f"Unknown config: {config}") |
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def encode_checking_account_status(self, status): |
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return self.checking_account_status_encode_dic()[status] |
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def checking_account_status_encode_dic(self): |
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return { |
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"A14": 0, |
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"A11": 1, |
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"A12": 2, |
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"A13": 3, |
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} |
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def decode_checking_account_status(self, code): |
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return self.checking_account_status_decode_dic()[code] |
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def checking_account_status_decode_dic(self): |
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return { |
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0: "A14", |
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1: "A11", |
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2: "A12", |
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3: "A13", |
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} |
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def encode_credit_status(self, status): |
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return self.credit_status_encode_dic()[status] |
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def credit_status_encode_dic(self): |
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return { |
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"A30": 0, |
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"A31": 1, |
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"A32": 2, |
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"A33": 3, |
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"A34": 4, |
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} |
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def decode_credit_status(self, code): |
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return self.credit_status_decode_dic()[code] |
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def credit_status_decode_dic(self): |
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return { |
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0: "A30", |
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1: "A31", |
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2: "A32", |
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3: "A33", |
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4: "A34", |
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} |
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def encode_current_savings(self, status): |
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return self.current_savings_encode_dic()[status] |
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def current_savings_encode_dic(self): |
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return { |
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"A65": 0, |
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"A61": 1, |
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"A62": 2, |
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"A63": 3, |
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"A64": 4, |
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} |
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def decode_current_savings(self, code): |
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return self.current_savings_decode_dic()[code] |
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def current_savings_decode_dic(self): |
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return { |
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0: "A65", |
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1: "A61", |
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2: "A62", |
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3: "A63", |
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4: "A64", |
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} |
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def encode_employed_since(self, status): |
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return self.employed_since_encode_dic()[status] |
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def employed_since_encode_dic(self): |
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return { |
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"A71": 0, |
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"A72": 1, |
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"A73": 2, |
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"A74": 3, |
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"A75": 4, |
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} |
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def decode_employed_since(self, code): |
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return self.employed_since_decode_dic()[code] |
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def employed_since_decode_dic(self): |
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return { |
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0: "A71", |
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1: "A72", |
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2: "A73", |
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3: "A74", |
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4: "A75", |
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} |
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def encode_sex(self, status): |
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return self.sex_encode_dic()[status] |
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def sex_encode_dic(self): |
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return { |
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"A91": 0, |
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"A93": 0, |
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"A94": 0, |
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"A92": 1, |
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"A95": 1, |
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} |
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def decode_sex(self, code): |
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return self.sex_decode_dic()[code] |
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def sex_decode_dic(self): |
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return { |
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0: "A91", |
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1: "A92", |
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} |
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def encode_marital_status(self, status): |
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return self.marital_status_encode_dic()[status] |
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def marital_status_encode_dic(self): |
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return { |
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"A91": 0, |
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"A92": 0, |
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"A93": 1, |
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"A94": 2, |
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"A95": 1, |
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} |
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def decode_marital_status(self, code): |
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return self.marital_status_decode_dic()[code] |
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def marital_status_decode_dic(self): |
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return { |
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0: "A91", |
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1: "A93", |
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2: "A94", |
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} |
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def encode_guarantors(self, status): |
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return self.guarantors_encode_dic()[status] |
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def guarantors_encode_dic(self): |
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return { |
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"A101": 0, |
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"A102": 1, |
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"A103": 2, |
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} |
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def decode_guarantors(self, code): |
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return self.guarantors_decode_dic()[code] |
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def guarantors_decode_dic(self): |
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return { |
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0: "A101", |
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1: "A102", |
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2: "A103", |
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} |
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def encode_installment_plans(self, status): |
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return self.installment_plans_encode_dic()[status] |
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def installment_plans_encode_dic(self): |
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return { |
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"A141": 0, |
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"A142": 1, |
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"A143": 2, |
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} |
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def decode_installment_plans(self, code): |
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return self.installment_plans_decode_dic()[code] |
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def installment_plans_decode_dic(self): |
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return { |
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0: "A141", |
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1: "A142", |
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2: "A143", |
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} |
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def encode_housing_status(self, status): |
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return self.housing_status_encode_dic()[status] |
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def housing_status_encode_dic(self): |
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return { |
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"A153": 0, |
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"A151": 1, |
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"A152": 2, |
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} |
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def decode_housing_status(self, code): |
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return self.housing_status_decode_dic()[code] |
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def housing_status_decode_dic(self): |
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return { |
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0: "A153", |
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1: "A151", |
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2: "A152", |
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} |
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def encode_job_status(self, status): |
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return self.job_status_encode_dic()[status] |
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def job_status_encode_dic(self): |
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return { |
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"A171": 0, |
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"A172": 1, |
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"A173": 2, |
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"A174": 3, |
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} |
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def decode_job_status(self, code): |
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return self.job_status_decode_dic()[code] |
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def job_status_decode_dic(self): |
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return { |
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0: "A171", |
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1: "A172", |
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2: "A173", |
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3: "A174", |
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} |
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def encode_has_registered_phone_number(self, status): |
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return self.has_registered_phone_number_encode_dic()[status] |
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def has_registered_phone_number_encode_dic(self): |
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return { |
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"A191": 0, |
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"A192": 1, |
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} |
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def decode_has_registered_phone_number(self, code): |
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return self.has_registered_phone_number_decode_dic()[code] |
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def has_registered_phone_number_decode_dic(self): |
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return { |
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0: "A191", |
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1: "A192", |
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} |
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def encode_is_foreign(self, status): |
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return self.is_foreign_encode_dic()[status] |
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def is_foreign_encode_dic(self): |
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return { |
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"A191": 0, |
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"A192": 1, |
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} |
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def decode_is_foreign(self, code): |
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return self.is_foreign_decode_dic()[code] |
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def is_foreign_decode_dic(self): |
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return { |
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0: "A191", |
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1: "A192", |
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} |
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def encode_loan_granted(self, status): |
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return self.loan_granted_encode_dic()[status] |
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def loan_granted_encode_dic(self): |
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return { |
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"A201": 0, |
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"A202": 1, |
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} |
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def decode_loan_granted(self, code): |
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return self.loan_granted_decode_dic()[code] |
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def loan_granted_decode_dic(self): |
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return { |
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0: "A201", |
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1: "A202", |
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} |
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