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hotfix on float cols (#526)
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1 changed files with 13 additions and 10 deletions
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@ -32,7 +32,9 @@ class PostScoreETL(ExtractTransformLoad):
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self.SCORE_CSV_PATH = self.DATA_PATH / "score" / "csv"
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self.DOWNLOADABLE_INFO_PATH = self.DATA_PATH / "score" / "downloadable"
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self.STATE_CSV = self.DATA_PATH / "census" / "csv" / "fips_states_2010.csv"
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self.STATE_CSV = (
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self.DATA_PATH / "census" / "csv" / "fips_states_2010.csv"
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)
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self.FULL_SCORE_CSV = self.SCORE_CSV_PATH / "full" / "usa.csv"
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self.FULL_SCORE_CSV_PLUS_COUNTIES = (
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@ -59,11 +61,11 @@ class PostScoreETL(ExtractTransformLoad):
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self.TILES_SCORE_FLOAT_COLUMNS = [
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"Score E (percentile)",
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"Score E (top 25th percentile)",
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"Poverty (Less than 200% of federal poverty line)",
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"Percent individuals age 25 or over with less than high school degree",
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"Linguistic isolation (percent)",
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"Unemployed civilians (percent)",
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"Housing burden (percent)",
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"Poverty (Less than 200% of federal poverty line) (percentile)",
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"Percent individuals age 25 or over with less than high school degree (percentile)",
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"Linguistic isolation (percent) (percentile)",
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"Unemployed civilians (percent) (percentile)",
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"Housing burden (percent) (percentile)",
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]
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self.TILES_ROUND_NUM_DECIMALS = 2
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@ -203,9 +205,9 @@ class PostScoreETL(ExtractTransformLoad):
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# subsctract data sets
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# this follows the XOR pattern outlined here:
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# https://stackoverflow.com/a/37313953
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removed_df = pd.concat([merged_df, null_cbg_df, null_cbg_df]).drop_duplicates(
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keep=False
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)
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removed_df = pd.concat(
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[merged_df, null_cbg_df, null_cbg_df]
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).drop_duplicates(keep=False)
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# set the score to the new df
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self.score_county_state_merged = removed_df
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@ -222,7 +224,8 @@ class PostScoreETL(ExtractTransformLoad):
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score_tiles = self.score_county_state_merged[self.TILES_SCORE_COLUMNS]
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decimals = pd.Series(
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[self.TILES_ROUND_NUM_DECIMALS] * len(self.TILES_SCORE_FLOAT_COLUMNS),
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[self.TILES_ROUND_NUM_DECIMALS]
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* len(self.TILES_SCORE_FLOAT_COLUMNS),
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index=self.TILES_SCORE_FLOAT_COLUMNS,
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)
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score_tiles = score_tiles.round(decimals)
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