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@ -231,8 +231,8 @@ def overwrite_impacts(df_observed_impacts, df_raw_features):
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df_observed_impacts.update(df_overwritten_impacts)
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df_observed_impacts.update(df_overwritten_impacts)
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# Replace 'none' with nan
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# Replace 'none' with nan
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df_overwritten_impacts.loc[
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df_observed_impacts.loc[
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df_overwritten_impacts.storm_regime == "unknown", "storm_regime"
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df_observed_impacts.storm_regime == "unknown", "storm_regime"
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] = np.nan
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] = np.nan
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return df_observed_impacts
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return df_observed_impacts
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@ -343,8 +343,8 @@ def create_observed_impacts(
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ele=0,
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ele=0,
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col_name="width_msl_poststorm",
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col_name="width_msl_poststorm",
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)
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)
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df_width_msl_change_m = (df_width_msl_poststorm - df_width_msl_prestorm).rename('df_width_msl_change_m')
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df_width_msl_change_m = (df_width_msl_poststorm - df_width_msl_prestorm).rename('width_msl_change_m')
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df_width_msl_change_pct = (df_width_msl_change_m / df_width_msl_prestorm * 100).rename('df_width_msl_change_pct')
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df_width_msl_change_pct = (df_width_msl_change_m / df_width_msl_prestorm * 100).rename('width_msl_change_pct')
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# Join beach width change onto observed impacts dataframe
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# Join beach width change onto observed impacts dataframe
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df_observed_impacts = pd.concat(
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df_observed_impacts = pd.concat(
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