39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
import json
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import pandas as pd
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from datetime import datetime
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STEPS_COLUMNS = ("device_id", "steps", "local_date_time", "timestamp")
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def parseStepsData(steps_data):
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if steps_data.empty:
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return pd.DataFrame(columns=STEPS_COLUMNS)
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device_id = steps_data["device_id"].iloc[0]
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records = []
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# Parse JSON into individual records
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for record in steps_data.json_fitbit_column:
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record = json.loads(record) # Parse text into JSON
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if "activities-steps" in record.keys():
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curr_date = datetime.strptime(record["activities-steps"][0]["dateTime"], "%Y-%m-%d")
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row_summary = (device_id,
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record["activities-steps"][0]["value"],
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curr_date,
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0)
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records.append(row_summary)
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parsed_data = pd.DataFrame(data=records, columns=STEPS_COLUMNS)
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return parsed_data
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def main(json_raw, stream_parameters):
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parsed_data = parseStepsData(json_raw)
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parsed_data["timestamp"] = 0 # this column is added at readable_datetime.R because we neeed to take into account multiple timezones
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if pd.api.types.is_datetime64_any_dtype( parsed_data['local_date_time']):
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parsed_data['local_date_time'] = parsed_data['local_date_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
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return(parsed_data)
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