MiniMed Connect sample 1.py

# Categorical string values

In [16]: pandas.Series([e['data']['lastSGTrend'] for e in es]).value_counts()
Out[16]:
NONE           2425
DOWN            238
UP              159
DOWN_DOUBLE      76
UP_DOUBLE        63
dtype: int64

In [17]: pandas.Series([e['data']['sensorState'] for e in es]).value_counts()
Out[17]:
NORMAL         2844
UNKNOWN          65
WEAK_SIGNAL      34
WARM_UP          16
METER_BG          2
dtype: int64

# ^ from another dataset this can also be LOST_SENSOR

In [18]: pandas.Series([e['data']['conduitBatteryStatus'] for e in es]).value_counts()
Out[18]:
FULL      2033
HIGH       808
MEDIUM     120
dtype: int64

In [21]: pandas.Series([e['data']['calibStatus'] for e in es]).value_counts()
Out[21]:
LESS_THAN_NINE_HRS      1139
LESS_THAN_TWELVE_HRS    1060
LESS_THAN_SIX_HRS        541
LESS_THAN_THREE_HRS      138
UNKNOWN                   65
DUENOW                    18
dtype: int64

# Booleans

In [19]: pandas.Series([e['data']['conduitMedicalDeviceInRange'] for e in es]).value_counts()
Out[19]:
True     2863
False      98
dtype: int64

In [20]: pandas.Series([e['data']['conduitSensorInRange'] for e in es]).value_counts()
Out[20]:
True     2829
False     132
dtype: int64

# From my own tests, this remains false even when the device IS suspended.

In [27]: pandas.Series([e['data']['medicalDeviceSuspended'] for e in es]).value_counts()
Out[27]:
False    2961
dtype: int64

# Reservoir level and pump battery level are rounded to the nearest 25%

In [29]: pandas.Series([e['data']['reservoirLevelPercent'] for e in es]).value_counts()
Out[29]:
50     2107
75      764
0        65
25       18
100       7
dtype: int64

In [30]: pandas.Series([e['data']['medicalDeviceBatteryLevelPercent'] for e in es]).value_counts()
Out[30]:
75     2297
100     599
0        65
dtype: int64

# This seems worth doing something about... (digging in their JS suggests "MMOL_L" is the other value)

In [22]: pandas.Series([e['data']['bgUnits'] for e in es]).value_counts()
Out[22]:
MGDL    2961
dtype: int64

# Last alarm. Translations appear in https://gist.github.com/mddub/a95dc120d9d1414a433d
# "101"   : "High SG. CHECK BG",
# "102"   : "Low SG",

In [36]: pandas.Series([e['data']['lastAlarm']['type'] for e in es]).value_counts()
Out[36]:
ALARM    2961
dtype: int64

In [37]: pandas.Series([e['data']['lastAlarm']['code'] for e in es]).value_counts()
Out[37]:
101    1912
102    1049
dtype: int64

# This indicates the user's display preference, but all time strings are in 24 hour format

In [34]: pandas.Series([e['data']['timeFormat'] for e in es]).value_counts()
Out[34]:
HR_24    2961
dtype: int64

In [35]: pandas.Series([e['data']['sMedicalDeviceTime'] for e in es]).value_counts()
Out[35]:
Oct 18, 2015 16:33:00    7
Oct 19, 2015 03:53:00    7
Oct 18, 2015 06:58:00    6
Oct 17, 2015 00:15:40    6
Oct 18, 2015 05:14:01    5
Oct 19, 2015 11:24:45    5
...

# Active insulin... -1 indicates the Connect is not connected

In [57]: pandas.Series([e['data']['activeInsulin']['amount'] for e in es]).value_counts()
Out[57]:
 0.000    956
 0.050    109
 0.025     95
-1.000     65
 0.075     54
 0.475     54
 0.100     50
 0.125     49
 0.275     47
 0.200     47
...

In [55]: pandas.Series([e['data']['conduitSensorInRange'] for e in es if e['data']['activeInsulin']['amount'] == -1]).value_counts()
Out[55]:
False    65
dtype: int64

In [56]: pandas.Series([e['data']['conduitMedicalDeviceInRange'] for e in es if e['data']['activeInsulin']['amount'] == -1]).value_counts()
Out[56]:
False    65
dtype: int64

# Confirming that these are unused (as of 2015-10-19)

In [23]: pandas.Series([e['data']['lastSensorTime'] for e in es]).value_counts()
Out[23]:
0    2961
dtype: int64

In [24]: pandas.Series([e['data']['medicalDeviceTime'] for e in es]).value_counts()
Out[24]:
0    2961
dtype: int64

In [25]: pandas.Series([e['data']['lastConduitTime'] for e in es]).value_counts()
Out[25]:
0    2961
dtype: int64

In [26]: pandas.Series([e['data']['lastSensorTS'] for e in es]).value_counts()
Out[26]:
0    2961
dtype: int64

# Sanity-checking integer values

In [31]: pandas.Series([e['data']['timeToNextCalibHours'] for e in es]).value_counts()
Out[31]:
8     447
7     413
10    375
11    370
9     315
6     279
5     240
4     156
3     145
2     111
0      83
1      27

In [28]: pandas.Series([e['data']['conduitBatteryLevel'] for e in es]).value_counts()
Out[28]:
100    1245
96       63
97       61
92       58
37       57
59       52
0        51
95       47
71       45
...

In [32]: pandas.Series([e['data']['sensorDurationHours'] for e in es]).value_counts()
Out[32]:
53     69
99     66
0      65
42     65
76     64
47     62
100    62
...

In [33]: pandas.Series([e['data']['reservoirAmount'] for e in es]).value_counts()
Out[33]:
78     265
55     247
95     220
94     187
77     139
47     137
80     125
87     125
...

# What's up with these *InRange fields?

In [7]: in_ranges = [' '.join(map(str, [a['conduitInRange'], a['conduitMedicalDeviceInRange'], a['conduitSensorInRange']])) for a in [b['data'] for b in es]]

In [8]: in_ranges[:5]
Out[8]:
['True True True',
 'True True True',
 'True True True',
 'True True True',
 'True True True']

# conduitInRange conduitMedicalDeviceInRange conduitSensorInRange
In [9]: pandas.Series(in_ranges).value_counts()
Out[9]:
True True True       972
True True False       12
True False False      10
False False False      6
dtype: int64

# here's an interesting value of "limits":
# User says they correspond to:
# 12 am 70-200
# 5:30am 70-180
# 2 pm 70-200

{
   "limits" : [
      {
         "kind" : "Limits",
         "index" : 0,
         "version" : 1,
         "highLimit" : 200,
         "lowLimit" : 70
      },
      {
         "lowLimit" : 70,
         "highLimit" : 200,
         "version" : 1,
         "kind" : "Limits",
         "index" : 60
      },
      {
         "index" : 126,
         "kind" : "Limits",
         "highLimit" : 180,
         "version" : 1,
         "lowLimit" : 70
      },
      {
         "index" : 228,
         "kind" : "Limits",
         "lowLimit" : 70,
         "highLimit" : 200,
         "version" : 1
      }
   ]
}