mirror of
https://github.com/DOI-DO/j40-cejst-2.git
synced 2025-02-24 18:44:20 -08:00
5504528fdf
* Adds flake8, pylint, liccheck, flake8 to dependencies for data-pipeline * Sets up and runs black autoformatting * Adds flake8 to tox linting * Fixes flake8 error F541 f string missing placeholders * Fixes flake8 E501 line too long * Fixes flake8 F401 imported but not used * Adds pylint to tox and disables the following pylint errors: - C0114: module docstrings - R0201: method could have been a function - R0903: too few public methods - C0103: name case styling - W0511: fix me - W1203: f-string interpolation in logging * Adds utils.py to tox.ini linting, runs black on utils.py * Fixes import related pylint errors: C0411 and C0412 * Fixes or ignores remaining pylint errors (for discussion later) * Adds safety and liccheck to tox.ini
103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
import pandas as pd
|
|
import censusdata
|
|
|
|
from etl.base import ExtractTransformLoad
|
|
from etl.sources.census.etl_utils import get_state_fips_codes
|
|
from utils import get_module_logger
|
|
|
|
logger = get_module_logger(__name__)
|
|
|
|
|
|
class CensusACSETL(ExtractTransformLoad):
|
|
def __init__(self):
|
|
self.ACS_YEAR = 2019
|
|
self.OUTPUT_PATH = self.DATA_PATH / "dataset" / f"census_acs_{self.ACS_YEAR}"
|
|
self.UNEMPLOYED_FIELD_NAME = "Unemployed civilians (percent)"
|
|
self.LINGUISTIC_ISOLATION_FIELD_NAME = "Linguistic isolation (percent)"
|
|
self.LINGUISTIC_ISOLATION_TOTAL_FIELD_NAME = "Linguistic isolation (total)"
|
|
self.LINGUISTIC_ISOLATION_FIELDS = [
|
|
"C16002_001E",
|
|
"C16002_004E",
|
|
"C16002_007E",
|
|
"C16002_010E",
|
|
"C16002_013E",
|
|
]
|
|
self.df: pd.DataFrame
|
|
|
|
def _fips_from_censusdata_censusgeo(self, censusgeo: censusdata.censusgeo) -> str:
|
|
"""Create a FIPS code from the proprietary censusgeo index."""
|
|
fips = "".join([value for (key, value) in censusgeo.params()])
|
|
return fips
|
|
|
|
def extract(self) -> None:
|
|
dfs = []
|
|
for fips in get_state_fips_codes(self.DATA_PATH):
|
|
logger.info(f"Downloading data for state/territory with FIPS code {fips}")
|
|
|
|
dfs.append(
|
|
censusdata.download(
|
|
src="acs5",
|
|
year=self.ACS_YEAR,
|
|
geo=censusdata.censusgeo(
|
|
[("state", fips), ("county", "*"), ("block group", "*")]
|
|
),
|
|
var=[
|
|
# Emploment fields
|
|
"B23025_005E",
|
|
"B23025_003E",
|
|
]
|
|
+ self.LINGUISTIC_ISOLATION_FIELDS,
|
|
)
|
|
)
|
|
|
|
self.df = pd.concat(dfs)
|
|
|
|
self.df[self.GEOID_FIELD_NAME] = self.df.index.to_series().apply(
|
|
func=self._fips_from_censusdata_censusgeo
|
|
)
|
|
|
|
def transform(self) -> None:
|
|
logger.info("Starting Census ACS Transform")
|
|
|
|
# Calculate percent unemployment.
|
|
# TODO: remove small-sample data that should be `None` instead of a high-variance fraction.
|
|
self.df[self.UNEMPLOYED_FIELD_NAME] = self.df.B23025_005E / self.df.B23025_003E
|
|
|
|
# Calculate linguistic isolation.
|
|
individual_limited_english_fields = [
|
|
"C16002_004E",
|
|
"C16002_007E",
|
|
"C16002_010E",
|
|
"C16002_013E",
|
|
]
|
|
|
|
self.df[self.LINGUISTIC_ISOLATION_TOTAL_FIELD_NAME] = self.df[
|
|
individual_limited_english_fields
|
|
].sum(axis=1, skipna=True)
|
|
self.df[self.LINGUISTIC_ISOLATION_FIELD_NAME] = (
|
|
self.df[self.LINGUISTIC_ISOLATION_TOTAL_FIELD_NAME].astype(float)
|
|
/ self.df["C16002_001E"]
|
|
)
|
|
|
|
self.df[self.LINGUISTIC_ISOLATION_FIELD_NAME].describe()
|
|
|
|
def load(self) -> None:
|
|
logger.info("Saving Census ACS Data")
|
|
|
|
# mkdir census
|
|
self.OUTPUT_PATH.mkdir(parents=True, exist_ok=True)
|
|
|
|
columns_to_include = [
|
|
self.GEOID_FIELD_NAME,
|
|
self.UNEMPLOYED_FIELD_NAME,
|
|
self.LINGUISTIC_ISOLATION_FIELD_NAME,
|
|
]
|
|
|
|
self.df[columns_to_include].to_csv(
|
|
path_or_buf=self.OUTPUT_PATH / "usa.csv", index=False
|
|
)
|
|
|
|
def validate(self) -> None:
|
|
logger.info("Validating Census ACS Data")
|
|
|
|
pass
|