code

import xml.etree.ElementTree as ET
import dateutil.parser as dp
import pandas as pd
from matplotlib import pyplot as plt

filename = 'your_filename'

tree = ET.parse(filename)
root = tree.getroot()
run = root[0][0]

#checking elements inside our tree
for x in root[0][0][1][5]:
    print(x)

NAMESPACES = {
    'ns': 'http://www.garmin.com/xmlschemas/TrainingCenterDatabase/v2',
    'ns2': 'http://www.garmin.com/xmlschemas/UserProfile/v2',
    'ns3': 'http://www.garmin.com/xmlschemas/ActivityExtension/v2',
    'ns4': 'http://www.garmin.com/xmlschemas/ProfileExtension/v1',
    'ns5': 'http://www.garmin.com/xmlschemas/ActivityGoals/v1'
}

#build our data frame with the data we want, you can choose from the available data from your 
#activity and round/change the type of variable if you want to work with less decimals
data_list = []
for lap_number, lap in enumerate(run.findall('ns:Lap', NAMESPACES)):
    for tp in lap.find('ns:Track', NAMESPACES).findall('ns:Trackpoint', NAMESPACES):
        data = {}
        data['Time'] = dp.parse(tp.find('ns:Time', NAMESPACES).text)
        data['Elevation'] = round(float(tp.find('ns:AltitudeMeters', NAMESPACES).text), 4)
        data['Distance'] = round(float(tp.find('ns:DistanceMeters', NAMESPACES).text), 2)
        data['Heart_rate'] = int(tp.find('ns:HeartRateBpm', NAMESPACES)[0].text)
        data['Speed'] = round(float(tp.find('ns:Extensions', NAMESPACES)[0][0].text), 3)
        data['Lap'] = lap_number+1
        data_list.append(data)
df = pd.DataFrame(data_list)

#visualize data frame
print(df)

#plot with the color codes
#(the zones will vary for every person, as it depends on your performance, check the
#last section after the plots to change the limits here)
x = df['Distance']
y = df['Heart_rate']
plt.plot(x,y, color='black', linewidth=0.4)
plt.ylim(min(y), max(y))
plt.xlim(0,max(x))
plt.ylabel('Heart rate (BPM)')
plt.xlabel('Distance (m)')
plt.title('HR coloured by zones')
plt.fill_between(x,y,0, where=(y>=(min(y)))&(y<=123), facecolor='royalblue')
plt.fill_between(x,y,0, where=(y>=124)&(y<=144), facecolor='limegreen')
plt.fill_between(x,y,0, where=(y>=145)&(y<=165), facecolor='yellow')
plt.fill_between(x,y,0, where=(y>=166)&(y<=185), facecolor='orange')
plt.fill_between(x,y,0, where=(y>=186), facecolor='red')
plt.show()

#if you want to add the elevation colormap as well, replace line 47 with:
#plt.scatter(x,y, c=z, cmap='winter_r', linewidth=5)
#and add these lines:
#z = df['Elevation']
#cbar = plt.colorbar()
#cbar.set_label('Elevation (m)', rotation=90)