cumulative haversion on lat lon of previous row

cumulative_pandas_haversine.py

from datetime import datetime
import time

def as_epoch(row):
    dt = datetime.strptime(row['gps_timestamp'], '%Y-%m-%d %H:%M:%S%z')
    return int(time.mktime(dt.timetuple()))

df['epoch'] = df.apply (lambda row: as_epoch(row), axis=1)
df = df.drop('gps_timestamp', axis=1)
df = df.sort_values('epoch')

from haversine import haversine, Unit

def haversine_dist(row):
    index = df.index.get_loc(row.name)
    if index == 0:
        return 0
    prev_row = df.iloc[index - 1]
    return haversine((row['latitude'], row['longitude']), (prev_row['latitude'], prev_row['longitude']))


df['haversine'] = df.apply (haversine_dist, axis=1)