Extracts — Footings IDI Model 0.6.0 documentation

Active Lives - Base¶

ActiveLivesBaseExtract¶

Base policy extract for active lives. A unique record is represented by: POLICY_ID + COVERAGE_ID.

Columns

POLICY_IDPandasDtype.String: The policy ID of the policy holder.
COVERAGE_IDPandasDtype.String: The coverage ID of the policy holder.
BIRTH_DTPandasDtype.DateTime: The birth date of the policy holder.
GENDERPandasDtype.String: The gender of the policy holder.
TOBACCO_USAGEPandasDtype.Bool: The tabacco usage of the policy holder.
POLICY_START_DTPandasDtype.DateTime: The date coverage starts for the policy issued.
PREMIUM_PAY_TO_DTPandasDtype.DateTime: The date premium payments end for the policy issued.
POLICY_END_DTPandasDtype.DateTime: The date coverage ends for the policy issued.
ELIMINATION_PERIODPandasDtype.Int: The elimination days before benefits are paid for the policy holder.
GROSS_PREMIUMPandasDtype.Float: The policy gross premium amount.
GROSS_PREMIUM_FREQPandasDtype.String: The frequency of premium payments.
BENEFIT_AMOUNTPandasDtype.Float: The benefit amount for the policy holder.
IDI_OCCUPATION_CLASSPandasDtype.String: The IDI occupation class of the policy holder.
IDI_CONTRACTPandasDtype.String: The IDI contract type of the policy holder.
IDI_BENEFIT_PERIODPandasDtype.String: The IDI benefit period for the policy holder.
IDI_MARKETPandasDtype.String: The IDI market for the policy holder.
COLA_PERCENTPandasDtype.Float: The COLA percent for the policy holder (0 if no COLA provided).

Sample Data¶

import pandas as pd
extract_base = pd.read_csv(
  "./models/extract_models/active-lives-sample-base.csv",
  parse_dates=["BIRTH_DT", "POLICY_START_DT", "PREMIUM_PAY_TO_DT", "POLICY_END_DT"]
)
extract_base

	POLICY_ID	BIRTH_DT	GENDER	TOBACCO_USAGE	COVERAGE_ID	POLICY_START_DT	PREMIUM_PAY_TO_DT	POLICY_END_DT	ELIMINATION_PERIOD	GROSS_PREMIUM	GROSS_PREMIUM_FREQ	BENEFIT_AMOUNT	IDI_OCCUPATION_CLASS	IDI_CONTRACT	IDI_BENEFIT_PERIOD	IDI_MARKET	COLA_PERCENT
0	M1	1978-08-01	F	N	BASE	2018-03-06	2048-07-31	2048-07-31	360	10	MONTH	100	M	AS	TO70	INDV	0.02
1	M1	1978-08-01	F	N	ROP	2018-03-06	2048-07-31	2048-07-31	360	10	MONTH	100	M	AS	TO70	INDV	0.02
2	M2	1967-11-03	M	N	BASE	2018-01-19	2032-11-02	2032-11-02	14	10	MONTH	100	4	AS	18M	INDV	0.00
3	M3	1982-06-17	M	N	BASE	2007-06-19	2047-06-16	2047-06-16	180	10	MONTH	100	M	AS	TO65	INDV	0.03
4	M3	1982-06-17	M	N	ROP	2007-06-19	2047-06-16	2047-06-16	180	10	MONTH	100	M	AS	TO65	INDV	0.03
5	M4	1974-03-08	F	Y	BASE	2009-10-06	2041-03-07	2041-03-07	90	10	MONTH	100	1	AS	TO67	INDV	0.03
6	M4	1974-03-08	F	Y	ROP	2009-10-06	2041-03-07	2041-03-07	90	10	MONTH	100	1	AS	TO67	INDV	0.03
7	M5	1972-12-10	F	Y	BASE	2003-01-29	2037-12-09	2037-12-09	90	10	MONTH	100	2	AO	TO65	INDV	0.03
8	M5	1972-12-10	F	Y	ROP	2003-01-29	2037-12-09	2037-12-09	90	10	MONTH	100	2	AO	TO65	INDV	0.03

Active Lives - ROP Rider¶

ActiveLivesROPRiderExtract¶

Rider policy extract for active lives. A unique record is represented by: POLICY_ID + COVERAGE_ID + RIDER_ATTRIBUTE.

Columns

POLICY_IDPandasDtype.String: The policy ID of the policy holder.
COVERAGE_IDPandasDtype.String: The coverage ID of the policy holder.
RIDER_ATTRIBUTEPandasDtype.String: The rider attribute name.
VALUEPandasDtype.Object: The value of the rider attribute.

Sample Data¶

import pandas as pd
extract_riders = pd.read_csv(
  "./models/extract_models/active-lives-sample-riders-rop.csv",
)
extract_riders

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
<ipython-input-2-a6814d79d345> in <module>
      1 import pandas as pd
----> 2 extract_riders = pd.read_csv(
      3   "./models/extract_models/active-lives-sample-riders-rop.csv",
      4 )
      5 extract_riders

~/work/footings-idi-model/footings-idi-model/.venv/lib/python3.8/site-packages/pandas/io/parsers.py in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)
    686     )
    687 
--> 688     return _read(filepath_or_buffer, kwds)
    689 
    690 

~/work/footings-idi-model/footings-idi-model/.venv/lib/python3.8/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
    452 
    453     # Create the parser.
--> 454     parser = TextFileReader(fp_or_buf, **kwds)
    455 
    456     if chunksize or iterator:

~/work/footings-idi-model/footings-idi-model/.venv/lib/python3.8/site-packages/pandas/io/parsers.py in __init__(self, f, engine, **kwds)
    946             self.options["has_index_names"] = kwds["has_index_names"]
    947 
--> 948         self._make_engine(self.engine)
    949 
    950     def close(self):

~/work/footings-idi-model/footings-idi-model/.venv/lib/python3.8/site-packages/pandas/io/parsers.py in _make_engine(self, engine)
   1178     def _make_engine(self, engine="c"):
   1179         if engine == "c":
-> 1180             self._engine = CParserWrapper(self.f, **self.options)
   1181         else:
   1182             if engine == "python":

~/work/footings-idi-model/footings-idi-model/.venv/lib/python3.8/site-packages/pandas/io/parsers.py in __init__(self, src, **kwds)
   2008         kwds["usecols"] = self.usecols
   2009 
-> 2010         self._reader = parsers.TextReader(src, **kwds)
   2011         self.unnamed_cols = self._reader.unnamed_cols
   2012 

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.__cinit__()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._setup_parser_source()

FileNotFoundError: [Errno 2] No such file or directory: './models/extract_models/active-lives-sample-riders-rop.csv'

Disabled Lives - Base¶

DisabledLivesBaseExtract¶

Base policy extract for disabled lives. A unique record is represented by: POLICY_ID + CLAIM_ID + COVERAGE_ID.

Columns

POLICY_IDPandasDtype.String: The policy ID of the disabled claimant.
CLAIM_IDPandasDtype.String: The claim ID of the disabled claimant.
COVERAGE_IDPandasDtype.String: The coverage ID of the disabled claimant.
BIRTH_DTPandasDtype.DateTime: The birth date of the disabled claimant.
GENDERPandasDtype.String: The gender of the disabled claimant.
TOBACCO_USAGEPandasDtype.Bool: The tabacco usage of the disabled claimant.
INCURRED_DTPandasDtype.DateTime: The date of disablement for the claimant (i.e., the disablement date).
TERMINATION_DTPandasDtype.DateTime: The termination date of the disabled claimant (i.e., the date benefits will stop being paid).
ELIMINATION_PERIODPandasDtype.Int: The elimination days before benefits are paid for the disabled claimant.
BENEFIT_AMOUNTPandasDtype.Float16: The benefit amount for the disabled claimant.
IDI_OCCUPATION_CLASSPandasDtype.String: The IDI occupation class of the disabled claimant.
IDI_CONTRACTPandasDtype.String: The IDI contract type of the disabled claimant.
IDI_BENEFIT_PERIODPandasDtype.String: The IDI benefit period for the disabled claimant.
IDI_MARKETPandasDtype.String: The IDI market for the disabled claimant.
IDI_DIAGNOSIS_GRPPandasDtype.String: The IDI diagnosis group of the disabled claimant.
COLA_PERCENTPandasDtype.Float16: The COLA percent for the disabled claimant (0 if no COLA provided).

Sample Data¶

import pandas as pd
extract_base = pd.read_csv(
  "./models/extract_models/disabled-lives-sample-base.csv",
  parse_dates=["BIRTH_DT", "INCURRED_DT", "TERMINATION_DT"]
)
extract_base

Disabled Lives - Rider¶

DisabledLivesRiderExtract¶

Rider policy extract for disabled lives. A unique record is represented by: POLICY_ID + CLAIM_ID + COVERAGE_ID + RIDER_ATTRIBUTE.

Columns

POLICY_IDPandasDtype.String: The policy ID of the disabled claimant.
CLAIM_IDPandasDtype.String: The claim ID of the disabled claimant.
COVERAGE_IDPandasDtype.String: The coverage ID of the disabled claimant.
RIDER_ATTRIBUTEPandasDtype.String: The rider attribute name.
VALUEPandasDtype.Object: The value of the rider attribute.

Sample Data¶

import pandas as pd
extract_riders = pd.read_csv(
  "./models/extract_models/disabled-lives-sample-riders.csv",
)
extract_riders

Extracts¶

Active Lives - Base¶

Sample Data¶

Active Lives - ROP Rider¶

Sample Data¶

Disabled Lives - Base¶

Sample Data¶

Disabled Lives - Rider¶

Sample Data¶