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94 lines
3.5 KiB
Python
94 lines
3.5 KiB
Python
import pandas as pd
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from data_pipeline.etl.base import ExtractTransformLoad
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from data_pipeline.score import field_names
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from data_pipeline.utils import get_module_logger
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logger = get_module_logger(__name__)
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class EJSCREENETL(ExtractTransformLoad):
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"""Load EJSCREEN data.
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Data dictionary:
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https://gaftp.epa.gov/EJSCREEN/2019/2019_EJSCREEN_columns_explained.csv
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"""
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def __init__(self):
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self.EJSCREEN_FTP_URL = "https://edap-arcgiscloud-data-commons.s3.amazonaws.com/EJSCREEN2020/EJSCREEN_Tract_2020_USPR.csv.zip"
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self.EJSCREEN_CSV = self.TMP_PATH / "EJSCREEN_Tract_2020_USPR.csv"
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self.CSV_PATH = self.DATA_PATH / "dataset" / "ejscreen_2019"
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self.df: pd.DataFrame
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self.COLUMNS_TO_KEEP = [
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self.GEOID_TRACT_FIELD_NAME,
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field_names.TOTAL_POP_FIELD,
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# pylint: disable=duplicate-code
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field_names.AIR_TOXICS_CANCER_RISK_FIELD,
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field_names.RESPIRATORY_HAZARD_FIELD,
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field_names.DIESEL_FIELD,
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field_names.PM25_FIELD,
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field_names.OZONE_FIELD,
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field_names.TRAFFIC_FIELD,
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field_names.RMP_FIELD,
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field_names.TSDF_FIELD,
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field_names.NPL_FIELD,
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field_names.WASTEWATER_FIELD,
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field_names.HOUSEHOLDS_LINGUISTIC_ISO_FIELD,
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field_names.POVERTY_FIELD,
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field_names.OVER_64_FIELD,
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field_names.UNDER_5_FIELD,
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field_names.LEAD_PAINT_FIELD,
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]
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def extract(self) -> None:
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logger.info("Downloading EJScreen Data")
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super().extract(
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self.EJSCREEN_FTP_URL,
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self.TMP_PATH,
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verify=False, # EPA EJScreen end point has certificate issues often
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)
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def transform(self) -> None:
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logger.info("Transforming EJScreen Data")
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self.df = pd.read_csv(
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self.EJSCREEN_CSV,
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dtype={"ID": "string"},
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# EJSCREEN writes the word "None" for NA data.
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na_values=["None"],
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low_memory=False,
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)
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# rename ID to Tract ID
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self.df.rename(
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columns={
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"ID": self.GEOID_TRACT_FIELD_NAME,
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# Note: it is currently unorthodox to use `field_names` in an ETL class,
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# but I think that's the direction we'd like to move all ETL classes. - LMB
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"ACSTOTPOP": field_names.TOTAL_POP_FIELD,
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"CANCER": field_names.AIR_TOXICS_CANCER_RISK_FIELD,
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"RESP": field_names.RESPIRATORY_HAZARD_FIELD,
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"DSLPM": field_names.DIESEL_FIELD,
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"PM25": field_names.PM25_FIELD,
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"OZONE": field_names.OZONE_FIELD,
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"PTRAF": field_names.TRAFFIC_FIELD,
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"PRMP": field_names.RMP_FIELD,
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"PTSDF": field_names.TSDF_FIELD,
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"PNPL": field_names.NPL_FIELD,
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"PWDIS": field_names.WASTEWATER_FIELD,
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"LINGISOPCT": field_names.HOUSEHOLDS_LINGUISTIC_ISO_FIELD,
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"LOWINCPCT": field_names.POVERTY_FIELD,
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"OVER64PCT": field_names.OVER_64_FIELD,
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"UNDER5PCT": field_names.UNDER_5_FIELD,
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"PRE1960PCT": field_names.LEAD_PAINT_FIELD,
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},
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inplace=True,
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)
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def load(self) -> None:
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logger.info("Saving EJScreen CSV")
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# write nationwide csv
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self.CSV_PATH.mkdir(parents=True, exist_ok=True)
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self.df[self.COLUMNS_TO_KEEP].to_csv(
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self.CSV_PATH / "usa.csv", index=False
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)
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