gpx_csv_convert.py

import calendar
import dateutil.parser
import pandas as pd

from xml.dom import minidom

def iso_to_epoch(iso_time):
    return calendar.timegm(dateutil.parser.parse(iso_time).timetuple())

class Converter:

    def __init__(self, string, name):

        if name[-4:] != '.csv':
            name = name + '.csv'

        # parse an xml file by name
        mydoc = minidom.parseString(string)

        trkpt = mydoc.getElementsByTagName('trkpt')
        time = mydoc.getElementsByTagName('time')
        ele = mydoc.getElementsByTagName('ele')
        hr = mydoc.getElementsByTagName('gpxtpx:hr')
        cad = mydoc.getElementsByTagName('gpxtpx:cad')
        temp = mydoc.getElementsByTagName('gpxtpx:atemp')
        
        #hr = mydoc.getElementsByTagName('ns3:hr')
        #cad = mydoc.getElementsByTagName('ns3:cad')

        lats = []
        longs = []
        times = []
        eles = []
        hrs = []
        dates = []
        parsed_times = []
        cads = []
        temps = []

        for elem in trkpt:
            lats.append(elem.attributes['lat'].value)
            longs.append(elem.attributes['lon'].value)

        for elem in time:
            times.append(elem.firstChild.data)

        for elem in hr:
            hrs.append(elem.firstChild.data)

        base_time = iso_to_epoch(times[0])

        time_differences = []

        for item in times:
            time_differences.append(iso_to_epoch(item) - base_time)
            date_obj = (dateutil.parser.parse(item))
            dates.append(str(date_obj.year) + "-" + str(date_obj.month) + "-" + str(date_obj.day))
            parsed_times.append(str(date_obj.hour) + ":" + str(date_obj.minute) + ":" + str(date_obj.second))

        for elem in ele:
            eles.append(elem.firstChild.data)

        for elem in cad:
            cads.append(elem.firstChild.data)
   
        for elem in temp:
            temps.append(elem.firstChild.data)
        
        
        hrs.append(0)

        data = {'date': pd.Series(dates),
                'time': pd.Series(parsed_times),
                'latitude': pd.Series(lats),
                'longitude': pd.Series(longs),
                'elevation': pd.Series(eles),
                'heart_rate': pd.Series(hrs),
                'cadence': pd.Series(cads),
                'temperature': pd.Series(temps)}

        #print(len(dates), len(parsed_times), len(lats), len(longs), len(eles), len(hrs), len(cads), len(temps))

        df = pd.DataFrame(data=data)

        df = df[['date', 'time', 'latitude', 'longitude', 'elevation', 'heart_rate', 'cadence', 'temperature']]

        df.to_csv(name, encoding='utf-8', index=False)