25 lines
926 B
Python
25 lines
926 B
Python
import pandas as pd
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from helper import retain_target_column
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sensor_features = pd.read_csv(snakemake.input["cleaned_sensor_features"])
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all_baseline_features = pd.DataFrame()
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for baseline_features_path in snakemake.input["demographic_features"]:
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pid = baseline_features_path.split("/")[3]
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baseline_features = pd.read_csv(baseline_features_path)
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baseline_features = baseline_features.assign(pid=pid)
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all_baseline_features = pd.concat([all_baseline_features, baseline_features], axis=0)
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# merge sensor features and baseline features
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if not sensor_features.empty:
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features = sensor_features.merge(all_baseline_features, on="pid", how="left")
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target_variable_name = snakemake.params["target_variable"]
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model_input = retain_target_column(features, target_variable_name)
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model_input.to_csv(snakemake.output[0], index=False)
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else:
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sensor_features.to_csv(snakemake.output[0], index=False)
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