Google Locations json to csv

google_locations_json_to_csv.py

import json 
import pandas as pd
from pandas.io.json import json_normalize

map_files_dir = '.././Data_Services_Exports/Google Takeout/Location History/'

#load json object
with open(map_files_dir + "Location History.json") as f:
    d = json.load(f)

df_locations = json_normalize(d['locations'])

#Get the date from Timestamp
df_locations['date'] = pd.to_datetime(df_locations['timestampMs'], unit='ms')

#Fix coordinates
df_locations['latitude'] = (df_locations['latitudeE7']/10000000)
df_locations['longitude'] = (df_locations['longitudeE7']/10000000)

#Enrich with day, hour of the day, day of the week, month of the year, quarter, year 
df_locations['day_of_the_year'] = pd.to_datetime(df_locations['date']).dt.strftime('%x')
df_locations['hour_of_day'] = pd.to_datetime(df_locations['date']).dt.strftime('%H:%M')
df_locations['day_of_week'] = df_locations['date'].dt.day_name()
df_locations['weekday'] = ((df_locations['date'].dt.dayofweek) // 5 == 1).astype(float)
df_locations['month_of_year'] = df_locations['date'].dt.month_name()
df_locations['quarter'] = df_locations['date'].dt.quarter
df_locations['year'] = df_locations['date'].dt.year

header = ['date', 'day_of_the_year', 'hour_of_day', 'latitude', 'longitude', 'velocity', 
          'day_of_week', 'weekday', 'month_of_year', 'accuracy', 'quarter', 'year', 'verticalAccuracy']

df_locations.to_csv("/Users/graphext/Desktop/location_history.csv", columns = header, index = False)

df_locations.head(3)