publicdata/j40-cejst-2
1
0
Fork 0
mirror of https://github.com/DOI-DO/j40-cejst-2.git synced 2025-07-28 13:51:16 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

added indoor plumbing to score housing burden

Browse source
This commit is contained in:
Emma Nechamkin 2022-08-03 17:44:24 -04:00
commit 15450cf91f
3 changed files with 41 additions and 18 deletions
Download patch file Download diff file Expand all files Collapse all files

6
data/data-pipeline/data_pipeline/etl/score/etl_score.py
View file

@ -366,6 +366,7 @@ class ScoreETL(ExtractTransformLoad):
numeric_columns = [
field_names.HOUSING_BURDEN_FIELD,
field_names.NO_KITCHEN_OR_INDOOR_PLUMBING_FIELD,
field_names.TOTAL_POP_FIELD,
field_names.MEDIAN_INCOME_AS_PERCENT_OF_STATE_FIELD,
field_names.ASTHMA_FIELD,
@ -416,7 +417,6 @@ class ScoreETL(ExtractTransformLoad):
field_names.HEALTHY_FOOD_FIELD,
field_names.IMPENETRABLE_SURFACES_FIELD,
field_names.UST_FIELD,
# We have to pass this boolean here in order to include it in ag value loss percentiles.
field_names.AGRICULTURAL_VALUE_BOOL_FIELD,
field_names.POVERTY_LESS_THAN_200_FPL_IMPUTED_FIELD,
]
@ -473,9 +473,7 @@ class ScoreETL(ExtractTransformLoad):
set(numeric_columns)
), "You have a double-entered column in the numeric columns list"
df_copy[numeric_columns] = df_copy[numeric_columns].apply(
pd.to_numeric
)
df_copy[numeric_columns] = df_copy[numeric_columns].apply(pd.to_numeric)
# Convert all columns to numeric and do math
# Note that we have a few special conditions here, that we handle explicitly.