21 lines
969 B
Python
21 lines
969 B
Python
import pandas as pd
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cleaned_sensor_features = pd.read_csv(snakemake.input["cleaned_sensor_features"])
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column_names = cleaned_sensor_features.columns
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esm_names_index = column_names.str.startswith("phone_esm_straw")
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# Find all columns coming from phone_esm, since these are not features for our purposes and we will drop them.
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esm_names = column_names[esm_names_index]
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target_variable_name = esm_names.str.contains(snakemake.params["target_variable"])
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if all(~target_variable_name):
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raise ValueError("The requested target (", snakemake.params["target_variable"], ")cannot be found in the dataset.",
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"Please check the names of phone_esm_ columns in all_sensor_features_cleaned_rapids.csv")
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esm_names = esm_names[~target_variable_name]
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# We will only keep one column related to phone_esm and that will be our target variable.
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model_input = cleaned_sensor_features.drop(esm_names, axis=1)
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model_input.to_csv(snakemake.output[0], index=False)
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