28 lines
1.1 KiB
Python
28 lines
1.1 KiB
Python
import pandas as pd
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import seaborn as sns
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import matplotlib.pyplot as plt
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# path = "/rapids/data/processed/features/all_participants/all_sensor_features.csv" # all features all participants
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# path = "/rapids/data/interim/p03/empatica_accelerometer_features/empatica_accelerometer_python_cr_windows.csv"
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path = "/rapids/data/interim/p031/empatica_electrodermal_activity_features/empatica_electrodermal_activity_python_cr_windows.csv"
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# path = "/rapids/data/interim/p02/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_cr_windows.csv"
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# path = "/rapids/data/interim/p02/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_cr_windows.csv"
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# path = "/rapids/data/interim/p02/empatica_temperature_features/empatica_temperature_python_cr_windows.csv"
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df = pd.read_csv(path)
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print(df)
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is_NaN = df.isnull()
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df = df[df["empatica_electrodermal_activity_cr_numPeaks"]]
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print(df)
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# row_has_NaN = is_NaN. any(axis=1)
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# rows_with_NaN = df[row_has_NaN]
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# print(rows_with_NaN.size)
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# sns.heatmap(df.isna(), cbar=False)
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plt.savefig('eda_windows_p03_window_60_thresh_default.png', bbox_inches='tight')
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