btroia

Time (hours)  Glucose (mg/dL)  Glucose (mmol/L)  Ketones (mmol/L)  GKI   Weight (lbs)
  0             87               4.8                0.2            24.2    168.9
  11.25         97               5.4                0.6             9.0
  23.75         92               5.1                0.6             8.5    165.0
  32.25         90               5.0                1.0             5.0
  45.92         68               3.8                3.2             1.2    164.4
  59.58         70               3.9                3.1             1.3
  72.0          70               3.9                4.7             0.8    162.7
  

btroia

{
  "metrics": {
    "air_temp": {
      "values": [
        82.8,
        82.8,
        82.8,
        82.8,
        82.8,
        82.8,

btroia

{
  "content": {
    "activities": [
      {
        "heart_rate": {
          "max": null,
          "avg": null,
          "min": null
        },
        "start_time": {

btroia

import json
import datetime as dt
from pprint import pprint

# change this to the JSON file you want to analyze
json_data = open('data/basis-data-2014-09-15-sleep.json')

data = json.load(json_data)
json_data.close()

btroia

mongoexport \
--collection sleepexport --type=csv --fields _id,start_time,offset,light_minutes,rem_minutes,deep_minutes,interruption_minutes,unknown_minutes \
--out mysleepdata.csv --db mydb

btroia

db.sleeps.aggregate( [
	{ $unwind : "$content.activities" },
	{ $project : 
		{
		"content.activities.date" : 1 ,
		"content.activities.sleep" : 1,
		"content.activities.start_time" : 1
		}
	},
	{ "$group": { 

btroia

from __future__ import print_function
import pymongo
import glob
import os
import json

# Define mongoDB database and collection to store sleep data
db_name = "mydb"
collection_name = "mysleeps"

btroia

{
  "content": {
    "activities": [
      {
        "heart_rate": {
          "max": null,
          "avg": 47.91773778920309,
          "min": null
        },
        "start_time": {