From cd33f323c824badaec453726a3c3988a45fdffcf Mon Sep 17 00:00:00 2001
From: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com>
Date: Fri, 17 Sep 2021 13:11:23 -0400
Subject: [PATCH] Revised Columns on Download File + PDF (#701)
* Revised Columns on Download File + PDF
* finishing ticket
---
.../data_pipeline/etl/score/constants.py | 29 +-
.../data_pipeline/etl/score/etl_score_post.py | 17 +-
.../files/Draft_Communities_List.pdf | 3493 +++++++++++++++++
3 files changed, 3524 insertions(+), 15 deletions(-)
create mode 100644 data/data-pipeline/data_pipeline/files/Draft_Communities_List.pdf
diff --git a/data/data-pipeline/data_pipeline/etl/score/constants.py b/data/data-pipeline/data_pipeline/etl/score/constants.py
index d12da2fb..b4b429cb 100644
--- a/data/data-pipeline/data_pipeline/etl/score/constants.py
+++ b/data/data-pipeline/data_pipeline/etl/score/constants.py
@@ -6,6 +6,7 @@ from data_pipeline.config import settings
# Base Paths
DATA_PATH = Path(settings.APP_ROOT) / "data"
TMP_PATH = DATA_PATH / "tmp"
+FILES_PATH = Path(settings.APP_ROOT) / "files"
# Remote Paths
CENSUS_COUNTIES_ZIP_URL = "https://www2.census.gov/geo/docs/maps-data/data/gazetteer/Gaz_counties_national.zip"
@@ -42,6 +43,7 @@ DATA_SCORE_TILES_DIR = DATA_SCORE_DIR / "tiles"
SCORE_DOWNLOADABLE_DIR = DATA_SCORE_DIR / "downloadable"
SCORE_DOWNLOADABLE_CSV_FILE_PATH = SCORE_DOWNLOADABLE_DIR / "usa.csv"
SCORE_DOWNLOADABLE_EXCEL_FILE_PATH = SCORE_DOWNLOADABLE_DIR / "usa.xlsx"
+SCORE_DOWNLOADABLE_PDF_FILE_PATH = FILES_PATH / "Draft_Communities_List.pdf"
SCORE_DOWNLOADABLE_ZIP_FILE_PATH = (
SCORE_DOWNLOADABLE_DIR / "Screening_Tool_Data.zip"
)
@@ -77,7 +79,6 @@ TILES_SCORE_COLUMNS = [
"Particulate matter (PM2.5) (percentile)",
"Median household income (% of AMI) (percentile)",
"Percent of individuals < 200% Federal Poverty Line (percentile)",
- "Percent individuals age 25 or over with less than high school degree (percentile)",
]
# columns to round floats to 2 decimals
@@ -113,18 +114,21 @@ TILES_SCORE_FLOAT_COLUMNS = [
TILES_ROUND_NUM_DECIMALS = 2
DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_BASIC = [
+ "Area Median Income (State or metropolitan)",
+ "Percent of individuals < 100% Federal Poverty Line",
"Percent individuals age 25 or over with less than high school degree",
- "Linguistic isolation (percent)",
- "Poverty (Less than 200% of federal poverty line)",
- "Unemployed civilians (percent)",
- "Housing burden (percent)",
- "Respiratory hazard index",
- "Diesel particulate matter",
- "Particulate matter (PM2.5)",
+ "Diagnosed diabetes among adults aged >=18 years",
+ "Current asthma among adults aged >=18 years",
+ "Coronary heart disease among adults aged >=18 years",
+ "Life expectancy (years)",
"Traffic proximity and volume",
- "Proximity to RMP sites",
+ "FEMA Risk Index Expected Annual Loss Score",
+ "Energy burden",
+ "Housing burden (percent)",
"Wastewater discharge",
"Percent pre-1960s housing (lead paint indicator)",
+ "Diesel particulate matter",
+ "Particulate matter (PM2.5)",
"Total population",
]
@@ -132,7 +136,7 @@ DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_BASIC = [
DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_FULL = list(
pd.core.common.flatten(
[
- [p, f"{p} (percentile)", f"{p} (min-max normalized)"]
+ [p, f"{p} (percentile)"]
for p in DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_BASIC
]
)
@@ -143,7 +147,8 @@ DOWNLOADABLE_SCORE_COLUMNS = [
"GEOID10",
"County Name",
"State Name",
- "Score D (percentile)",
- "Score D (top 25th percentile)",
+ "Score G (communities)",
+ "Median household income (% of AMI)",
+ "Median household income (% of state median household income) (percentile)",
*DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_FULL,
]
diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
index 86a4cfcb..5b4375f6 100644
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
@@ -230,14 +230,18 @@ class PostScoreETL(ExtractTransformLoad):
) -> None:
logger.info("Saving Full Score CSV with County Information")
score_csv_path.parent.mkdir(parents=True, exist_ok=True)
- score_county_state_merged.to_csv(score_csv_path, index=False)
+ score_county_state_merged.to_csv(
+ score_csv_path,
+ index=False,
+ encoding="utf-8-sig", # windows compat https://stackoverflow.com/a/43684587
+ )
def _load_tile_csv(
self, score_tiles_df: pd.DataFrame, tile_score_path: Path
) -> None:
logger.info("Saving Tile Score CSV")
tile_score_path.parent.mkdir(parents=True, exist_ok=True)
- score_tiles_df.to_csv(tile_score_path, index=False)
+ score_tiles_df.to_csv(tile_score_path, index=False, encoding="utf-8")
def _load_downloadable_zip(
self, downloadable_df: pd.DataFrame, downloadable_info_path: Path
@@ -248,6 +252,13 @@ class PostScoreETL(ExtractTransformLoad):
csv_path = constants.SCORE_DOWNLOADABLE_CSV_FILE_PATH
excel_path = constants.SCORE_DOWNLOADABLE_EXCEL_FILE_PATH
zip_path = constants.SCORE_DOWNLOADABLE_ZIP_FILE_PATH
+ pdf_path = constants.SCORE_DOWNLOADABLE_PDF_FILE_PATH
+
+ # Rename score column
+ downloadable_df.rename(
+ columns={"Score G (communities)": "Community of focus (v0.1)"},
+ inplace=True,
+ )
logger.info("Writing downloadable csv")
downloadable_df.to_csv(csv_path, index=False)
@@ -256,7 +267,7 @@ class PostScoreETL(ExtractTransformLoad):
downloadable_df.to_excel(excel_path, index=False)
logger.info("Compressing files")
- files_to_compress = [csv_path, excel_path]
+ files_to_compress = [csv_path, excel_path, pdf_path]
with zipfile.ZipFile(zip_path, "w") as zf:
for f in files_to_compress:
zf.write(f, arcname=Path(f).name, compress_type=compression)
diff --git a/data/data-pipeline/data_pipeline/files/Draft_Communities_List.pdf b/data/data-pipeline/data_pipeline/files/Draft_Communities_List.pdf
new file mode 100644
index 00000000..97616851
--- /dev/null
+++ b/data/data-pipeline/data_pipeline/files/Draft_Communities_List.pdf
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