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"""Long-Term-Care-Aggregated-Data.ipynb |
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Automatically generated by Colaboratory. |
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Original file is located at |
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https://colab.research.google.com/drive/14YdgB8b4TtNetbHpTstGH7W4DLa3Yyxq |
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""" |
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from datasets import GeneratorBasedBuilder, DownloadManager, DatasetInfo, Array3D, BuilderConfig, SplitGenerator, Version |
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from datasets.features import Features, Value, Sequence |
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import datasets |
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import pandas as pd |
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import json |
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import zipfile |
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from PIL import Image |
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import numpy as np |
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import io |
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import csv |
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import json |
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import os |
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from typing import List |
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import datasets |
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import logging |
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_CITATION = """\ |
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@misc{long_term_care_aggregated_dataset, |
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title = {Long-Term Care Aggregated Dataset}, |
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author = {Kao, Hsuan-Chen (Justin)}, |
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year = {2024}, |
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publisher = {Hugging Face}, |
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url = {https://github.com/justinkao44/STA663_Project_1}, |
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} |
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""" |
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_DESCRIPTION = """\ |
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The Long-Term Care Aggregated Dataset is a collection of insurance data for 'incidence' and 'termination' categories. |
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It is compiled from Long Term Care insurance policies data, providing insights into trends and patterns in insurance claims |
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and terminations. This dataset can be used for actuarial analysis, risk assessment, and to inform insurance product development. |
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""" |
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_HOMEPAGE = "https://github.com/justinkao44/STA663_Project_1" |
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_LICENSE = "Apache-2.0" |
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_URLS = { |
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"train_incidence": "https://github.com/justinkao44/STA663_Project_1/raw/main/train_filtered_incidence_df.zip", |
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"train_termination": "https://github.com/justinkao44/STA663_Project_1/raw/main/train_filtered_termination_df.zip", |
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"validation_incidence": "https://github.com/justinkao44/STA663_Project_1/raw/main/validation_filtered_incidence_df.zip", |
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"validation_termination": "https://github.com/justinkao44/STA663_Project_1/raw/main/validation_filtered_termination_df.zip", |
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} |
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class LongTermCareAggregatedData(datasets.GeneratorBasedBuilder): |
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"""Dataset for insurance 'incidence' and 'termination' data.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="incidence", version=datasets.Version("1.0.0"), description="This part of the dataset includes incidence features"), |
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datasets.BuilderConfig(name="termination", version=datasets.Version("1.0.0"), description="This part of the dataset includes termination features"), |
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] |
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def _info(self): |
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if self.config.name == "incidence": |
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features = datasets.Features({ |
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"Group_Indicator": datasets.Value("string"), |
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"Gender": datasets.Value("string"), |
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"Issue_Age_Bucket": datasets.Value("string"), |
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"Incurred_Age_Bucket": datasets.Value("string"), |
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"Issue_Year_Bucket": datasets.Value("string"), |
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"Policy_Year": datasets.Value("string"), |
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"Marital_Status": datasets.Value("string"), |
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"Premium_Class": datasets.Value("string"), |
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"Underwriting_Type": datasets.Value("string"), |
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"Coverage_Type_Bucket": datasets.Value("string"), |
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"Tax_Qualification_Status": datasets.Value("string"), |
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"Inflation_Rider": datasets.Value("string"), |
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"Rate_Increase_Flag": datasets.Value("string"), |
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"Restoration_of_Benefits": datasets.Value("string"), |
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"NH_Orig_Daily_Ben_Bucket": datasets.Value("string"), |
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"ALF_Orig_Daily_Ben_Bucket": datasets.Value("string"), |
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"HHC_Orig_Daily_Ben_Bucket": datasets.Value("string"), |
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"NH_Ben_Period_Bucket": datasets.Value("string"), |
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"ALF_Ben_Period_Bucket": datasets.Value("string"), |
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"HHC_Ben_Period_Bucket": datasets.Value("string"), |
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"NH_EP_Bucket": datasets.Value("string"), |
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"ALF_EP_Bucket": datasets.Value("string"), |
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"HHC_EP_Bucket": datasets.Value("string"), |
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"Region": datasets.Value("string"), |
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"Active_Exposure": datasets.Value("float64"), |
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"Total_Exposure": datasets.Value("float64"), |
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"Claim_Count": datasets.Value("int32"), |
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"Count_NH": datasets.Value("int32"), |
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"Count_ALF": datasets.Value("int32"), |
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"Count_HHC": datasets.Value("int32"), |
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"Count_Unk": datasets.Value("int32"), |
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}) |
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elif self.config.name == "termination": |
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features = datasets.Features({ |
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"Gender": datasets.Value("string"), |
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"Incurred_Age_Bucket": datasets.Value("string"), |
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"Incurred_Year_Bucket": datasets.Value("string"), |
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"Claim_Type": datasets.Value("string"), |
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"Region": datasets.Value("string"), |
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"Diagnosis_Category": datasets.Value("string"), |
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"Claim_Duration": datasets.Value("string"), |
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"Exposure": datasets.Value("string"), |
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"Deaths": datasets.Value("string"), |
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"Recovery": datasets.Value("string"), |
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"Terminations": datasets.Value("string"), |
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"Benefit_Expiry": datasets.Value("string"), |
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"Others_Terminations": datasets.Value("string"), |
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}) |
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else: |
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raise ValueError(f"BuilderConfig name not recognized: {self.config.name}") |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage="https://www.soa.org/resources/experience-studies/2020/2000-2016-ltc-aggregate-database/", |
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citation="Please cite this dataset as: Society of Actuaries (SOA). (2020). Long Term Care Insurance Aggregate Experience Data, 2000-2016." |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_files = dl_manager.download(_URLS) |
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train_file = downloaded_files[f"train_{self.config.name}"] |
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validation_file = downloaded_files[f"validation_{self.config.name}"] |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_file": train_file, |
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"split": self.config.name, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"data_file": validation_file, |
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"split": self.config.name, |
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}, |
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), |
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] |
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def _generate_examples(self, data_file, split): |
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with zipfile.ZipFile(data_file, 'r') as zip_ref: |
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csv_filename = zip_ref.namelist()[0] |
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with zip_ref.open(csv_filename) as csv_file: |
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dataframe = pd.read_csv(io.TextIOWrapper(csv_file)) |
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feature_columns = self._get_feature_columns_by_config() |
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for idx, row in dataframe.iterrows(): |
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feature_dict = {column: row[column] for column in feature_columns if column in dataframe.columns} |
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yield idx, feature_dict |
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def _get_feature_columns_by_config(self): |
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if self.config.name == "incidence": |
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return [ |
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"Group_Indicator", "Gender", "Issue_Age_Bucket", "Incurred_Age_Bucket", |
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"Issue_Year_Bucket", "Policy_Year", "Marital_Status", "Premium_Class", |
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"Underwriting_Type", "Coverage_Type_Bucket", "Tax_Qualification_Status", |
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"Inflation_Rider", "Rate_Increase_Flag", "Restoration_of_Benefits", |
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"NH_Orig_Daily_Ben_Bucket", "ALF_Orig_Daily_Ben_Bucket", "HHC_Orig_Daily_Ben_Bucket", |
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"NH_Ben_Period_Bucket", "ALF_Ben_Period_Bucket", "HHC_Ben_Period_Bucket", |
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"NH_EP_Bucket", "ALF_EP_Bucket", "HHC_EP_Bucket", "Region", |
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"Active_Exposure", "Total_Exposure", "Claim_Count", "Count_NH", "Count_ALF", "Count_HHC", "Count_Unk", |
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] |
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elif self.config.name == "termination": |
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return [ |
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"Gender", "Incurred_Age_Bucket", "Incurred_Year_Bucket", "Claim_Type", |
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"Region", "Diagnosis_Category", "Claim_Duration", "Exposure", "Deaths", |
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"Recovery", "Terminations", "Benefit_Expiry", "Others_Terminations", |
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] |
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else: |
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raise ValueError(f"Config name not recognized: {self.config.name}") |
