j40-cejst-2/data/data-pipeline/data_pipeline/etl/sources/cdc_places/etl.py
2022-09-30 13:43:31 -04:00

82 lines
2.9 KiB
Python

import typing
import pandas as pd
from data_pipeline.etl.base import ExtractTransformLoad
from data_pipeline.etl.base import ValidGeoLevel
from data_pipeline.score import field_names
from data_pipeline.utils import download_file_from_url
from data_pipeline.utils import get_module_logger
logger = get_module_logger(__name__)
class CDCPlacesETL(ExtractTransformLoad):
NAME = "cdc_places"
GEO_LEVEL: ValidGeoLevel = ValidGeoLevel.CENSUS_TRACT
PUERTO_RICO_EXPECTED_IN_DATA = False
CDC_GEOID_FIELD_NAME = "LocationID"
CDC_VALUE_FIELD_NAME = "Data_Value"
CDC_MEASURE_FIELD_NAME = "Measure"
def __init__(self):
self.OUTPUT_PATH = self.DATA_PATH / "dataset" / "cdc_places"
self.CDC_PLACES_URL = "https://chronicdata.cdc.gov/api/views/cwsq-ngmh/rows.csv?accessType=DOWNLOAD"
self.COLUMNS_TO_KEEP: typing.List[str] = [
self.GEOID_TRACT_FIELD_NAME,
field_names.DIABETES_FIELD,
field_names.ASTHMA_FIELD,
field_names.HEART_DISEASE_FIELD,
field_names.CANCER_FIELD,
field_names.HEALTH_INSURANCE_FIELD,
field_names.PHYS_HEALTH_NOT_GOOD_FIELD,
]
self.df: pd.DataFrame
def extract(self) -> None:
logger.info("Starting to download 520MB CDC Places file.")
file_path = download_file_from_url(
file_url=self.CDC_PLACES_URL,
download_file_name=self.get_tmp_path() / "census_tract.csv",
)
self.df = pd.read_csv(
filepath_or_buffer=file_path,
dtype={self.CDC_GEOID_FIELD_NAME: "string"},
low_memory=False,
)
def transform(self) -> None:
logger.info("Starting CDC Places transform")
# Rename GEOID field
self.df.rename(
columns={self.CDC_GEOID_FIELD_NAME: self.GEOID_TRACT_FIELD_NAME},
inplace=True,
errors="raise",
)
# Note: Puerto Rico not included.
self.df = self.df.pivot(
index=self.GEOID_TRACT_FIELD_NAME,
columns=self.CDC_MEASURE_FIELD_NAME,
values=self.CDC_VALUE_FIELD_NAME,
)
# rename columns to be used in score
rename_fields = {
"Current asthma among adults aged >=18 years": field_names.ASTHMA_FIELD,
"Coronary heart disease among adults aged >=18 years": field_names.HEART_DISEASE_FIELD,
"Cancer (excluding skin cancer) among adults aged >=18 years": field_names.CANCER_FIELD,
"Diagnosed diabetes among adults aged >=18 years": field_names.DIABETES_FIELD,
"Physical health not good for >=14 days among adults aged >=18 years": field_names.PHYS_HEALTH_NOT_GOOD_FIELD,
}
self.df.rename(
columns=rename_fields,
inplace=True,
errors="raise",
)
# Make the index (the census tract ID) a column, not the index.
self.output_df = self.df.reset_index()