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WIP fema updates

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Shelby Switzer 2021-12-02 10:12:54 -05:00
parent 4c04494da9
commit c0466bd74a
1 changed files with 94 additions and 17 deletions
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111
data/data-pipeline/data_pipeline/etl/sources/national_risk_index/etl.py
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@ -99,27 +99,104 @@ class NationalRiskIndexETL(ExtractTransformLoad):
inplace=True, inplace=True,
) )
# Only use disasters linked to climate change
disaster_categories = [
"AVLN", # Avalanche
"CFLD", # Coastal Flooding
"CWAV", # Cold Wave
"DRGT", # Drought
"HAIL", # Hail
"HWAV", # Heat Wave
"HRCN", # Hurricane
"ISTM", # Ice Storm
"LNDS", # Landslide
"RFLD", # Riverine Flooding
"SWND", # Strong Wind
"TRND", # Tornado
"WFIR", # Wildfire
"WNTW", # Winter Weather
]
disaster_population_sum = df_nri[
[str(x) + "_EALP" for x in disaster_categories]
].sum(axis=1)
print("Population sum is")
print(disaster_population_sum)
# Some disaster categories do not have agriculture value column
agri_columns = [str(x) + "_EALA" for x in disaster_categories if str(x) + "_EALA" in list(df_nri.columns)]
disaster_agriculture_sum = df_nri[
agri_columns
].sum(axis=1)
print("Agri sum is")
print(disaster_agriculture_sum)
disaster_building_sum = df_nri[
[str(x) + "_EALB" for x in disaster_categories]
].sum(axis=1)
print("Building sum is")
print(disaster_building_sum)
# # Note: I'm not sure why pylint is so upset with this particular dataframe,
# # but it may be a known bug. https://github.com/PyCQA/pylint/issues/1498
# for category in disaster_categories:
# df_nri[ # pylint: disable=unsupported-assignment-operation
# f"{category} - Population"
# ] = (
# df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EALP"
# ] # Expected Annual Loss - Population
# / df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EXPP"
# ]
# )
# df_nri[ # pylint: disable=unsupported-assignment-operation
# f"{category} - Agriculture"
# ] = (
# df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EALA"
# ] # Expected Annual Loss - Agriculture
# / df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EXPA"
# ]
# )
# df_nri[ # pylint: disable=unsupported-assignment-operation
# f"{category} - Building Value"
# ] = (
# df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EALB"
# ] # Expected Annual Loss - Building Value
# / df_nri[ # pylint: disable=unsubscriptable-object
# f"{category}_EXPB"
# ]
# )
# df_nri[ # pylint: disable=unsupported-assignment-operation
# self.EXPECTED_ANNUAL_LOSS_RATE
# ] = df_nri[ # pylint: disable=unsubscriptable-object
# disaster_categories
# ].sum(
# axis=1
# )
# Population EAL Rate = Eal Valp / Population # Population EAL Rate = Eal Valp / Population
df_nri[self.EXPECTED_POPULATION_LOSS_RATE_FIELD_NAME] = ( #
df_nri[self.EXPECTED_ANNUAL_LOSS_POPULATION_VALUE_INPUT_FIELD_NAME] # disaster_categories = [AEVN, CFLD, ] -> [AEVN - Population, CFLD - Population, ]
/ df_nri[self.POPULATION_INPUT_FIELD_NAME] #
) # df_nri[self.EXPECTED_POPULATION_LOSS_RATE_FIELD_NAME] = df_nri[
# [str(x) + " - Population" for x in disaster_categories]
# ]
# Agriculture EAL Rate = Eal Vala / Agrivalue
df_nri[self.EXPECTED_AGRICULTURE_LOSS_RATE_FIELD_NAME] = (
df_nri[
self.EXPECTED_ANNUAL_LOSS_AGRICULTURAL_VALUE_INPUT_FIELD_NAME
]
/ df_nri[self.AGRICULTURAL_VALUE_INPUT_FIELD_NAME]
)
# divide EAL_VALB (Expected Annual Loss - Building Value) by BUILDVALUE (Building Value ($)). # # Agriculture EAL Rate = Eal Vala / Agrivalue
df_nri[self.EXPECTED_BUILDING_LOSS_RATE_FIELD_NAME] = ( # df_nri[self.EXPECTED_AGRICULTURE_LOSS_RATE_FIELD_NAME] = (
df_nri[self.EXPECTED_ANNUAL_LOSS_BUILDING_VALUE_INPUT_FIELD_NAME]
/ df_nri[self.BUILDING_VALUE_INPUT_FIELD_NAME] # )
)
self.df = df_nri # # divide EAL_VALB (Expected Annual Loss - Building Value) by BUILDVALUE (Building Value ($)).
# df_nri[self.EXPECTED_BUILDING_LOSS_RATE_FIELD_NAME] = (
# )
# self.df = df_nri
def load(self) -> None: def load(self) -> None:
"""Writes the NRI data as a csv to the directory at self.OUTPUT_DIR""" """Writes the NRI data as a csv to the directory at self.OUTPUT_DIR"""