j40-cejst-2/data/data-pipeline/etl/sources/housing_and_transportation/etl.py
Lucas Merrill Brown 67b39475f7
Analysis by region (#385)
* Adding regional comparisons

* Small ETL fixes
2021-07-26 10:02:25 -05:00

60 lines
2 KiB
Python

import pandas as pd
from etl.base import ExtractTransformLoad
from etl.sources.census.etl_utils import get_state_fips_codes
from utils import get_module_logger, unzip_file_from_url
logger = get_module_logger(__name__)
class HousingTransportationETL(ExtractTransformLoad):
def __init__(self):
self.HOUSING_FTP_URL = (
"https://htaindex.cnt.org/download/download.php?focus=blkgrp&geoid="
)
self.OUTPUT_PATH = (
self.DATA_PATH / "dataset" / "housing_and_transportation_index"
)
self.df: pd.DataFrame
def extract(self) -> None:
# Download each state / territory individually
dfs = []
zip_file_dir = self.TMP_PATH / "housing_and_transportation_index"
for fips in get_state_fips_codes(self.DATA_PATH):
logger.info(
f"Downloading housing data for state/territory with FIPS code {fips}"
)
# Puerto Rico has no data, so skip
if fips == "72":
continue
unzip_file_from_url(
f"{self.HOUSING_FTP_URL}{fips}", self.TMP_PATH, zip_file_dir
)
# New file name:
tmp_csv_file_path = (
zip_file_dir / f"htaindex_data_blkgrps_{fips}.csv"
)
tmp_df = pd.read_csv(filepath_or_buffer=tmp_csv_file_path)
dfs.append(tmp_df)
self.df = pd.concat(dfs)
def transform(self) -> None:
logger.info(f"Transforming Housing and Transportation Data")
# Rename and reformat block group ID
self.df.rename(columns={"blkgrp": self.GEOID_FIELD_NAME}, inplace=True)
self.df[self.GEOID_FIELD_NAME] = self.df[
self.GEOID_FIELD_NAME
].str.replace('"', "")
def load(self) -> None:
logger.info(f"Saving Housing and Transportation Data")
self.OUTPUT_PATH.mkdir(parents=True, exist_ok=True)
self.df.to_csv(path_or_buf=self.OUTPUT_PATH / "usa.csv", index=False)