The FulcraAPI class
The main class for making Fulcra API functions.
This contains functions for authorizing a token, authenticating HTTP requests, making calls, and loading data.
apple_location_updates(start_time, end_time, fulcra_userid=None)
Retrieve the raw Apple location update samples during the specified period of time.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which contains the data from a location update. |
Examples:
To retrieve all location updates within a specific hour:
>>> updates = fulcra.apple_location_updates(
... start_time="2023-09-24T20:00:00Z",
... end_time="2023-09-24T21:10:00Z"
... )
To see the details of the first update:
>>> updates[0]
{'speed': -1, 'horizontal_accuracy_meters': 35, 'longitude_degrees':
-117.15661336566698, 'source_is_simulated_by_software': False,
'source_is_produced_by_accessory': False, 'latitude_degrees':
32.706505158026005, 'vertical_accuracy_meters': 3.0130748748779297,
'course_heading_accuracy_degrees': -1, 'course_heading_degrees': -1,
'ellipsoidal_altitude_meters': -6.280021667480469, 'floor': 0,
'speed_accuracy_meters': -1, 'altitude_meters': 29.17388153076172, 'uuid':
'e80feacc-54e9-414f-86cb-8d6ebd85ea41', 'timestamp':
'2023-09-24T20:39:28.056+00:00'}
apple_location_visits(start_time, end_time, fulcra_userid=None)
Retrieve the raw Apple location visit samples during the specified period of time.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which contains the data from a location visit. |
Examples:
To retrieve all location updates within a specific hour:
>>> visits = fulcra.apple_location_visits(
... start_time="2023-09-24T20:00:00Z",
... end_time="2023-09-24T21:10:00Z"
... )
To see the details of the first update:
>>> visits[0]
{'longitude_degrees': -117.1224047932943, 'latitude_degrees':
32.75812770726706, 'arrival_date': '0001-01-01T00:00:00+00:00',
'departure_date': '2023-09-25T01:42:16.998+00:00',
'horizontal_accuracy_meters': 32.93262639589646, 'uuid':
'935971dd-0822-49ef-a74f-b09a24d68c3a'}
apple_workouts(start_time, end_time, fulcra_userid=None)
Retrieve the list of Apple workouts that occurred (at least partially) during the specified time range.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which contains the data from a workout. |
Examples:
To retrieve all workouts during a time period:
>>> workouts = fulcra.apple_workouts(
... start_time = "2023-09-21 07:00:00.000Z",
... end_time = "2023-09-22 07:00:00.000Z"
... )
To inspect the details of a workout:
>>> workouts[0]
{'start_date': '2023-09-21T19:18:31.733000Z', 'end_date':
'2023-09-21T19:49:08.773000Z', 'has_undetermined_duration': False,
'apple_workout_id': '480b25fe-b229-41b9-bf13-7ccf5e2092ec', 'duration':
1837.0397539138794, 'extras': {'HKTimeZone': 'America/Los_Angeles',
'HKAverageMETs': '4.37848 kcal/hr·kg' ... }
authorize()
Request a device token, then prompt the user to authorize it.
This uses the Device Authorization workflow, which requires the user to visit a link and confirm that the code shown on the screen matches.
This function will attempt to open the link in a new browwser tab (using
webbrowser module); it will also be either print()ed out (or display()ed
out if run inside Jupyter).
The function will wait until the user visits the page and authentiactes, or until a specified time has passed.
Raises an exception on failure.
Examples:
fulcra.authorize() Use your browser to log in to Fulcra. If the tab does not open automatically, visit this URL to authenticate: https://fulcra.us.auth0.com/activate?user_code=SJZC-GRBW
When the authorization succeeds, the following will be displayed:
Authorization succeeded.
calendar_events(start_time, end_time, calendar_ids=None, fulcra_userid=None)
Retrieve the list of calendar events that occur (at least partially) during the specified time range.
To request events from another user's store, pass their user
ID as the fulcra_userid parameter.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
calendar_ids |
Optional[List[str]]
|
If included, the query results are limited to events that are on the specified calendars. |
None
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which contains the data from a calendar event. |
Examples:
To retrieve all calendar events that span a given range of time:
>>> cal_events = fulcra.calendar_events(
... start_time = "2023-09-24 07:00:00.000Z",
... end_time = "2023-09-25 07:00:00.000Z",
... calendar_ids=["01fb4138-db27-4792-867d-5cfbdc720165"]
... )
To inspect the details of an event:
>>> cal_events[0]
{'calendar_event_id': 'c409a249-24cd-4c19-b763-3683cc21b9f8',
'calendar_id': '01fb4138-db27-4792-867d-5cfbdc720165', 'start_date':
'2023-09-24T20:10:00Z', 'end_date': '2023-09-24T21:10:00Z',
'allow_new_time_proposals': None, 'alarms':
['19b7692e-7434-44be-a5ba-c8dfa338deb6'], 'availability': 'free',
'calendar_item_external_identifier':
'7kukuqrfedlm2f9tfbe684r6cqpk9mrk0aqdeoan7jdbr93e7963lagn9uq6pdsbac40',
'calendar_item_identifier': '22153B27-4BEE-480C-9627-F2EABC698103',
'event_identifier':
'EC9D6240-04A7-4869-9D2E-1A7648EA7732:7kukuqrfedlm2f9tfbe684r6cqpk9mrk0aqdeoan7jdbr93e7963lagn9uq6pdsbac40',
'creation_date': '2023-09-16T23:27:22Z', 'has_alarms': True,
'has_attendees': True, 'has_notes': True, 'has_recurrence_rules':
False, 'is_all_day': False, 'is_detached': False, 'last_modified_date':
'2023-09-16T23:27:26Z', 'location': 'PETCO Park', 'notes':
'This event was created from an email you received in Gmail.',
'occurrence_date': '2023-09-24T20:10:00Z', 'organizer':
'22381502-0af3-487a-820c-e22aa4cae201', 'recurrence_rules': None,
'status': 'confirmed', 'geolocation': None, 'time_zone':
'America/Los_Angeles (fixed)', 'title':
'St. Louis Cardinals at San Diego Padres', 'url': None,
'extras': {}, 'participants': [{'is_current_user': True,
'participant_role': 'required', 'participant_type': 'person',
'participant_status': 'accepted', 'url': 'mailto:cstone@gmail.com',
'contact_id': '00900185-b290-4f1c-860d-e4433024a943',
'name': 'cstone@gmail.com'}]}
calendars(fulcra_userid=None)
Retrieve the list of calendars available in your data store.
To request the calendars from another user's store, pass their user
ID as the fulcra_userid parameter.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which represents a calendar. |
Examples:
To retrieve all calendars from your data store:
>>> calendars = fulcra.calendars()
>>>
To inspect the details of a calendar:
>>> calendars[0]
{'calendar_id': '02b761da-46d0-4074-a9c8-406fd0de3adf', 'calendar_name':
'Birthdays', 'calendar_color':
'[0.5098039507865906,0.5843137502670288,0.686274528503418,1.0]',
'calendar_source_id': '03da9f61-7b58-4021-8f40-a93548258faf',
'calendar_source_name': 'Other', 'fulcra_source': 'apple_calendar'}
custom_input_events(start_time, end_time, source=None, fulcra_userid=None)
Retrieves events from Fulcra custom inputs, along with any metadata, for the requested time ranges.
Requires a valid access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
source |
Optional[str]
|
When specified, the full name of the source to query records from |
None
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of events; each event is represnted by a dict. |
fulcra_api(access_token, url_path)
Make a call to the given url path (e.g. /v0/data/time_series_grouped?...)
with the specified access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
access_token |
str
|
The access token to authenticate the request with |
required |
url_path |
str
|
The path of the URL to use (e.g. |
required |
Returns:
| Type | Description |
|---|---|
bytes
|
The raw response data (as bytes). Raises an exception on failure. |
get_fulcra_userid()
Retrieve the currently authorized Fulcra UserID.
Returns:
| Type | Description |
|---|---|
str
|
the Fulcra UserID of the currently-authorized user. |
get_shared_datasets()
Retrieves datasets that have been shared with the currently authenticated user
Examples:
>>> datasets = fulcra_client.get_shared_datasets()
>>> datasets[0]
{'permission_id': 'cf362f80-ef41-4c08-b5e3-b18bd3d1524b', 'created_at': '2024-08-21T17:52:10.658596Z', 'time_start': None, 'time_end': None, 'fulcra_userid': 'a24a9667-c2c6-4bbf-9a0f-4Bej0afcb521', 'fulcra_user_name': 'John Doe', 'fulcra_user_picture': 'https://lh3.googleusercontent.com/a/ACg8ocL-ggGYjOFq23Dfbf5GohDXbk01AoGmL0gCSbooVBXDgWeTLJk=s47-d', 'datashare_name': 'Provisioned for data analysis'}
location_at_time(time, window_size=14400, include_after=False, reverse_geocode=False, fulcra_userid=None)
Gets the user's location at the specified time. If no sample is
available for the exact time, searches for the closest sample up to
window_size seconds back. If include_after is true, then also
searches window_size seconds forward.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
time |
Union[str, datetime]
|
The point in time to get the user's location for. |
required |
window_size |
int
|
The size (in seconds) to look back (and optionally forward) for samples |
14400
|
include_after |
bool
|
When true, a sample that occurs after the requested time may be returned if it is the closest one. |
False
|
reverse_geocode |
bool
|
When true, Fulcra will attempt to reverse geocode the location and include the details in the results. |
False
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts; the first dict is the best location sample. |
Examples:
location = fulcra.location_at_time( ... time = "2024-01-24 00:00:00-08:00", ... )
location [{'speed': 0, 'horizontal_accuracy_meters': 4.848857421534995, 'longitude_degrees': -117.15709954484828, 'latitude_degrees': 32.707083bb994486, 'vertical_accuracy_meters': 3.2114044806616686, 'course_heading_accuracy_degrees': 180, 'course_heading_degrees': 87.05299950647989, 'ellipsoidal_altitude_meters': 32.700060645118356, 'floor': 0, 'speed_accuracy_meters': 0.9654413396512306, 'altitude_meters': 6.15396384336054, 'uuid': '59b2d63b-9b0b-436f-a66f-01129e1b33dd', 'timestamp': '2024-01-24T00:01:45.941+00:00', 'location_source': 'apple_location_update'}]
location_time_series(start_time, end_time, change_meters=None, sample_rate=900, look_back=14400, reverse_geocode=False, fulcra_userid=None)
Retrieve a time series of locations that the user was at. This uses the most precise underlying data sources available at the given time.
Requires a valid access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
change_meters |
Optional[float]
|
when specified, subsequent samples that are fewer than this many meters away will not be included. |
None
|
sample_rate |
int
|
The length (in seconds) of each sample |
900
|
look_back |
int
|
The maximum number of seconds in the past to look back to find a value for a sample. |
14400
|
reverse_geocode |
bool
|
When true, Fulcra will attempt to reverse geocode the locations and include the details in the results. |
False
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of samples; each sample represents a location sample. |
Examples:
>>> locations = fulcra.location_time_series(
... start_time = "2024-06-06T19:00:00-07:00",
... end_time = "2024-06-06T20:00:00-07:00",
... reverse_geocode = True
... )
>>> print(pd.DataFrame(locations))
slice_time lat long time distance_change_m address location_details
0 2024-06-07T02:00:00+00:00 32.706814 -117.156455 2024-06-07T01:50:10.92+00:00 NaN Petco Park, 100 Park Boulevard, San Diego, CA ... {'annotations': {'DMS': {'lat': '32° 42' 25.87...
1 2024-06-07T02:15:00+00:00 32.706722 -117.156576 2024-06-07T02:03:56.903+00:00 15.281598 Petco Park, 100 Park Boulevard, San Diego, CA ... {'annotations': {'DMS': {'lat': '32° 42' 25.87...
2 2024-06-07T02:30:00+00:00 32.706699 -117.156583 2024-06-07T02:22:07.571+00:00 2.588992 Petco Park, 100 Park Boulevard, San Diego, CA ... {'annotations': {'DMS': {'lat': '32° 42' 25.87...
3 2024-06-07T02:45:00+00:00 32.706699 -117.156583 2024-06-07T02:22:07.571+00:00 0.000000 Petco Park, 100 Park Boulevard, San Diego, CA ... {'annotations': {'DMS': {'lat': '32° 42' 25.87...
metric_samples(start_time, end_time, metric, fulcra_userid=None)
Retrieve the raw samples related to the given metric that occurred for the user during the specified period of time.
In cases where samples cover ranges and not points in time, a sample will be returned if any part of its range intersects with the requested range.
As an example, if you have start_date as 14:00 and end_date at 15:00,
and there is a sample that covers 13:30-14:30, it will be included.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
metric |
str
|
The name of the metric to retrieve samples for. |
required |
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Examples:
>>> samples = fulcra.metric_samples(
... start_time="2023-08-09 07:00:00.000Z",
... end_time="2023-08-10 07:00:00.000Z",
... metric="StepCount"
... )
To inspect the first sample:
>>> samples[0]
{'start_date': '2023-08-10T06:05:10.726+00:00', 'end_date':
'2023-08-10T06:05:13.285+00:00', 'extras': None,
'has_undetermined_duration': False, 'unit': 'count', 'count': 1,
'uuid': '74983a94-8816-4b95-bbbd-d4108149261a', 'value': 8,
'source_properties': {'name': 'b c’s iPhone', 'version': '16.6',
'productType': 'iPhone12,8', 'operatingSystemVersion': [16, 6, 0],
'sourceBundleIdentifier':
'com.apple.health.F8872676-6D45-4981-8E14-C009D0AE5F27'},
'device_properties': {'name': 'iPhone', 'model':
'iPhone', 'manufacturer': 'Apple Inc.',
'hardwareVersion': 'iPhone12,8',
'softwareVersion': '16.6'}}
metric_time_series(start_time, end_time, metric, sample_rate=60, replace_nulls=False, fulcra_userid=None, calculations=None)
Retrieve time-series data from a single Fulcra metric, covering the
time starting at start_time (inclusive) until end_time
(exclusive).
If specified, the sample_rate parameter defines the number of
seconds per sample. This value can be smaller than 1. The default
value is 60 (one sample per minute).
Requires a valid access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
metric |
str
|
The name of the time-series metric to retrieve |
required |
sample_rate |
float
|
The length (in seconds) of each sample |
60
|
replace_nulls |
Optional[bool]
|
When true, replace all NA/null/None values with 0 |
False
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
calculations |
Optional[list[str]]
|
When present, specifies additional calculations to perform for each time slice. The current values are:
- |
None
|
Returns:
| Type | Description |
|---|---|
DataFrame
|
a pandas DataFrame containing the data. For time ranges where data is
missing, the values will be |
Examples:
To retrieve a dataframe containing the StepCount metric:
>>> df = fulcra.metric_time_series(
... start_time = "2024-01-24 00:00:00-08:00",
... end_time = "2024-01-25 00:00:00-08:00",
... sample_rate = 1,
... metric = "StepCount"
... )
The index of the DataFrame will be the time:
df.index DatetimeIndex(['2024-01-24 08:00:00+00:00', '2024-01-24 08:00:01+00:00', '2024-01-24 08:00:02+00:00', '2024-01-24 08:00:03+00:00', '2024-01-24 08:00:04+00:00', '2024-01-24 08:00:05+00:00', '2024-01-24 08:00:06+00:00', '2024-01-24 08:00:07+00:00', '2024-01-24 08:00:08+00:00', '2024-01-24 08:00:09+00:00', ... '2024-01-25 07:59:50+00:00', '2024-01-25 07:59:51+00:00', '2024-01-25 07:59:52+00:00', '2024-01-25 07:59:53+00:00', '2024-01-25 07:59:54+00:00', '2024-01-25 07:59:55+00:00', '2024-01-25 07:59:56+00:00', '2024-01-25 07:59:57+00:00', '2024-01-25 07:59:58+00:00', '2024-01-25 07:59:59+00:00'], dtype='datetime64[us, UTC]', name='time', length=86400, freq=None)
The non-index column(s) in the dataframe will be related to the metric.
df.columns Index(['step_count'], dtype='object')
metrics_catalog()
Gets the list of time-series metrics that are available for this user.
These metrics can be passed to the `metric_time_series` and
`time_series_grouped` functions.
Returns:
The metrics, including descriptions.
Examples:
>>> metrics = fulcra_client.metrics_catalog()
>>> metrics[0]
{'name': 'AFibBurden', 'description': "A discrete measure of the percentage of time that the user's heart shows signs
of atrial fibrillation (AFib) during a given monitoring period.", 'unit': 'percent', 'is_time_series': True, 'metric_kind': 'discrete', 'value_column': 'afib_burden'} >>> metrics[1] {'name': 'ActiveCaloriesBurned', 'description': 'A cumulative measure of the amount of active energy the user has burned.', 'unit': 'cal', 'is_time_series': True, 'metric_kind': 'cumulative', 'value_column': 'active_calories_burned'}
simple_events(start_time, end_time, categories=None, fulcra_userid=None)
Retrieve the events that occurred during the specified period of time, optionally filtering by categories.
If included, the categories parameter only includes events from the specified
categories.
Requires an authorized access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
categories |
Optional[List[str]]
|
When present, the categories to filter on. Only events matching these categories will be returned. |
None
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
List[Dict]
|
A list of dicts, each of which represents an event. |
Examples:
To retrieve the stored events during a given range:
>>> simple_events = fulcra.simple_events(
... start_time="2022-05-01 04:00:00.000Z",
... end_time="2023-08-03 04:00:00.000Z"
... )
To get the details of an event:
>>> simple_events[0]
{'event_body': 'relieved', 'category': 'mood', 'event_id':
'12680011-6668-4c8e-b4cd-3ca429445ac0', 'timestamp':
'2022-09-21T05:51:22Z'}
time_series_grouped(start_time, end_time, metrics, sample_rate=60, replace_nulls=False, fulcra_userid=None)
Retrieve a time-series data frame containing the specified set of
Fulcra metrics from start_time (inclusive) until end_time (exclusive).
If specified, the sample_rate parameter defines the number of
seconds per sample. This value can be smaller than 1. The default
value is 60 (one sample per minute).
Requires a valid access token.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
start_time |
Union[str, datetime]
|
The start of the time range (inclusive), as an ISO 8601 string or |
required |
end_time |
Union[str, datetime]
|
The end of the range (exclusive), as an ISO 8601 string or |
required |
metrics |
List[str]
|
The names of the time-series metrics to include in the result |
required |
sample_rate |
float
|
The length (in seconds) of each sample |
60
|
replace_nulls |
Optional[bool]
|
When true, replace all NA/null/None values with 0 |
False
|
fulcra_userid |
Optional[str]
|
When present, specifies the Fulcra user ID to request data for. |
None
|
Returns:
| Type | Description |
|---|---|
|
a pandas DataFrame containing the data. For time ranges where data is
missing, the values will be |
Examples:
To retrieve a dataframe containing four different metrics
(DistanceTraveledOnFoot, AppleWatchExerciseTime,
ActiveCaloriesBurned, and BasalCaloriesBurned):
>>> df = fulcra.time_series_grouped(
... start_time = "2023-07-01 04:00:00.000Z",
... end_time = "2023-07-10 04:00:00.000Z",
... metrics=["DistanceTraveledOnFoot",
... "AppleWatchExerciseTime",
... "ActiveCaloriesBurned",
... "BasalCaloriesBurned"
... ]
... )
The index of the DataFrame will be the time:
>>> df.index
DatetimeIndex(['2023-07-01 04:00:00+00:00',
'2023-07-01 04:01:00+00:00',
'2023-07-01 04:02:00+00:00',
'2023-07-01 04:03:00+00:00',
'2023-07-01 04:04:00+00:00',
'2023-07-01 04:05:00+00:00',
'2023-07-01 04:06:00+00:00',
'2023-07-01 04:07:00+00:00',
'2023-07-01 04:08:00+00:00',
'2023-07-01 04:09:00+00:00',
...
'2023-07-10 03:50:00+00:00',
'2023-07-10 03:51:00+00:00',
'2023-07-10 03:52:00+00:00',
'2023-07-10 03:53:00+00:00',
'2023-07-10 03:54:00+00:00',
'2023-07-10 03:55:00+00:00',
'2023-07-10 03:56:00+00:00',
'2023-07-10 03:57:00+00:00',
'2023-07-10 03:58:00+00:00',
'2023-07-10 03:59:00+00:00'],
dtype='datetime64[ns, UTC]', name='time', length=12960,
freq=None)
Each metric requested will add at least one column to the dataframe:
>>> df.columns
Index(['distance_on_foot', 'apple_watch_exercise_time',
'active_calories_burned', 'basal_calories_burned'],
dtype='object')