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Added grandfathering of v1.0 DACS

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Carlos Felix 2024-12-04 10:00:14 -05:00 • committed by Carlos Felix
commit e0bb33211a
13 changed files with 74271 additions and 15 deletions
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39
data/data-pipeline/data_pipeline/comparator.py
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@ -6,6 +6,7 @@ from pathlib import Path
from data_pipeline.etl.score import constants
from data_pipeline.utils import get_module_logger, download_file_from_url
from data_pipeline.application import log_title, log_info, log_goodbye
from data_pipeline.score import field_names
logger = get_module_logger(__name__)
@ -176,6 +177,7 @@ def compare_score(
production_row_count = len(production_score_df.index)
local_row_count = len(local_score_df.index)
# Tract comparison
_add_text(
f"* The production score has {production_row_count:,} census tracts, and the freshly calculated score has {local_row_count:,}."
)
@ -191,8 +193,11 @@ def compare_score(
"\n"
)
production_total_population = production_score_df["Total population"].sum()
local_total_population = local_score_df["Total population"].sum()
# Population comparison
production_total_population = production_score_df[
field_names.TOTAL_POP_FIELD
].sum()
local_total_population = local_score_df[field_names.TOTAL_POP_FIELD].sum()
_add_text(
f"* The total population in all census tracts in the production score is {production_total_population:,}. "
@ -204,12 +209,9 @@ def compare_score(
else f"The difference is {abs(production_total_population - local_total_population):,}.\n"
)
production_disadvantaged_tracts_df = production_score_df.query(
"`Definition N community, including adjacency index tracts` == True"
)
local_disadvantaged_tracts_df = local_score_df.query(
"`Definition N community, including adjacency index tracts` == True"
)
dacs_query = f"`{field_names.FINAL_SCORE_N_BOOLEAN}` == True"
production_disadvantaged_tracts_df = production_score_df.query(dacs_query)
local_disadvantaged_tracts_df = local_score_df.query(dacs_query)
production_disadvantaged_tracts_set = set(
production_disadvantaged_tracts_df.index.array
@ -219,14 +221,15 @@ def compare_score(
)
production_pct_of_population_represented = (
production_disadvantaged_tracts_df["Total population"].sum()
production_disadvantaged_tracts_df[field_names.TOTAL_POP_FIELD].sum()
/ production_total_population
)
local_pct_of_population_represented = (
local_disadvantaged_tracts_df["Total population"].sum()
local_disadvantaged_tracts_df[field_names.TOTAL_POP_FIELD].sum()
/ local_total_population
)
# DACS comparison
_add_text(
f"* There are {len(production_disadvantaged_tracts_set):,} disadvantaged tracts in the production score representing"
f" {production_pct_of_population_represented:.1%} of the total population, and {len(local_disadvantaged_tracts_set):,}"
@ -252,15 +255,27 @@ def compare_score(
f" generated score (i.e. disadvantaged tracts that were removed by the new score). "
)
if len(removed_tracts) > 0:
_add_text(f"Those tracts are:\n{removed_tracts}\n")
_add_text(f"Those tracts are:\n{removed_tracts}")
_add_text(
f"* There are {len(added_tracts):,} tract(s) marked as disadvantaged in the locally generated score that are not disadvantaged in the"
f"\n* There are {len(added_tracts):,} tract(s) marked as disadvantaged in the locally generated score that are not disadvantaged in the"
f" production score (i.e. disadvantaged tracts that were added by the new score). "
)
if len(added_tracts) > 0:
_add_text(f"Those tracts are:\n{added_tracts}\n")
# Grandfathered tracts from v1.0
grandfathered_tracts = local_score_df.loc[
local_score_df[field_names.GRANDFATHERED_N_COMMUNITIES_V1_0]
].index
if len(grandfathered_tracts) > 0:
_add_text(
f"* This includes {len(grandfathered_tracts)} grandfathered tract(s) from v1.0 scoring. They are:\n"
f"{grandfathered_tracts.to_list()}\n"
)
else:
_add_text("* There are NO grandfathered tracts from v1.0 scoring.\n")
################
# Create a delta
################