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Fill NA with 0 for AR event features

data_cleaning
Meng Li 2021-10-03 11:37:30 -04:00
parent 4a7989c058
commit 871cdbbcd3
1 changed files with 3 additions and 2 deletions
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5
src/features/phone_activity_recognition/rapids/main.py
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@ -1,5 +1,4 @@
import pandas as pd import pandas as pd
import numpy as np
def rapids_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs): def rapids_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
@ -31,11 +30,13 @@ def rapids_features(sensor_data_files, time_segment, provider, filter_data_by_se
if "duration" + column.lower() in features_to_compute: if "duration" + column.lower() in features_to_compute:
filtered_data = ar_episodes[ar_episodes["activity_name"].isin(pd.Series(activity_labels))] filtered_data = ar_episodes[ar_episodes["activity_name"].isin(pd.Series(activity_labels))]
if not filtered_data.empty: if not filtered_data.empty:
ar_features["duration" + column.lower()] = ar_episodes[ar_episodes["activity_name"].isin(pd.Series(activity_labels))].groupby(["local_segment"])["duration"].sum().fillna(0) ar_features["duration" + column.lower()] = ar_episodes[ar_episodes["activity_name"].isin(pd.Series(activity_labels))].groupby(["local_segment"])["duration"].sum()
else: else:
ar_features["duration" + column.lower()] = 0 ar_features["duration" + column.lower()] = 0
ar_features.index.names = ["local_segment"] ar_features.index.names = ["local_segment"]
ar_features = ar_features.reset_index() ar_features = ar_features.reset_index()
ar_features.fillna(value={"count": 0, "countuniqueactivities": 0, "durationstationary": 0, "durationmobile": 0, "durationvehicle": 0}, inplace=True)
return ar_features return ar_features