Column expressions

Reference for table column expressions in Junction Sense queries to select fields from activity, body, sleep, and timeseries resources.

Table Column expression

Your Query Instruction can pull data from Junction summary and timeseries resources through Table Column expressions.

Each Table Column expression can select one column (a field) of the table (the Junction resource). You can use multiple Table Column expressions to select multiple columns in the same query.

Cross-table query instructions are not supported — you cannot mix Table Column expressions from different tables in the same query instruction.

Column expressions for Electrocardiogram, Sleep Cycle, and lab testing biomarkers are planned to be introduced in the future.

Summaries

Table	Python DSL	JSON DSL
Activity daily summary activity	Activity.col("$1")	{ "activity": "$1" }
Body summary body	Body.col("$1")	{ "body": "$1" }
Sleep summary sleep	Sleep.col("$1")	{ "sleep": "$1" }
Readiness scores derived_readiness	DerivedReadiness.col("$1")	{ "derived_readiness": "$1" }
Workout summary workout	Workout.col("$1")	{ "workout": "$1" }
Meal summary meal	Meal.col("$1")	{ "meal": "$1" }
Menstrual cycle menstrual_cycle	MenstrualCycle.col("$1")	{ "menstrual_cycle": "$1" }
Profile profile	Profile.col("$1")	{ "profile": "$1" }

Column Mappings

Map summary resource properties to their Continuous Query column equivalents.

Sleep

Sleep field	Query Column
calendar_date	index
bedtime_start	session_start
bedtime_stop	session_end
type	type
timezone_offset	time_zone
duration	duration_second
total	stage_asleep_second
awake	stage_awake_second
light	stage_light_second
rem	stage_rem_second
deep	stage_deep_second
-	stage_unknown_second
score	score
recovery_readiness_score	recovery_readiness_score
hr_lowest	heart_rate_minimum
hr_average	heart_rate_mean
-	heart_rate_maximum
hr_resting	heart_rate_resting
efficiency	efficiency
latency	latency_second
temperature_delta	skin_temperature_delta
skin_temperature	skin_temperature
hr_dip	heart_rate_dip
average_hrv	hrv_mean_rmssd
-	hrv_mean_sdnn
respiratory_rate	respiratory_rate
state	state
source.slug	source_provider
source.type	source_type
source.device_id	source_device_id
source.app_id	source_app_id

Activity

Activity field	Query Column
calendar_date	index
calories_total	calories_total
calories_active	calories_active
steps	steps
daily_movement	duration_active_second
distance	distance_meter
floors_climbed	floors_climbed
time_zone	time_zone
timezone_offset	time_zone_offset
heart_rate.avg_bpm	heart_rate_mean
heart_rate.min_bpm	heart_rate_minimum
heart_rate.max_bpm	heart_rate_maximum
heart_rate.resting_bpm	heart_rate_resting
heart_rate.avg_walking_bpm	heart_rate_mean_walking
wheelchair_use	wheelchair_use
wheelchair_push	wheelchair_push
-	intensity_sedentary_second
low	intensity_low_second
medium	intensity_medium_second
high	intensity_high_second
source.slug	source_provider
source.type	source_type
source.device_id	source_device_id
source.app_id	source_app_id

Workout

Workout field	Query Column
title	title
timezone_offset	time_zone
average_hr	heart_rate_mean
max_hr	heart_rate_maximum
-	heart_rate_minimum
distance	distance_meter
calendar_date	-
time_start	session_start
time_end	session_end
calories	calories
sport.name	sport_name
sport.slug	sport_slug
hr_zones	heart_rate_zone_1..6
moving_time	duration_active_second
total_elevation_gain	elevation_gain_meter
elev_high	elevation_maximum_meter
elev_low	elevation_minimum_meter
average_speed	speed_mean
max_speed	speed_maximum
average_watts	power_mean
device_watts	power_source
max_watts	power_maximum
weighted_average_watts	power_weighted_mean
steps	steps
map.polyline	map_polyline
map.summary_polyline	map_summary_polyline
provider_id	external_id
source.slug	source_provider
source.type	source_type
source.device_id	source_device_id
source.app_id	source_app_id

Body

Body field	Query Column
calendar_date	-
date (deprecated)	-
-	measured_at
weight	weight_kilogram
fat	fat_mass_percentage
water_percentage	water_percentage
muscle_mass_percentage	muscle_mass_percentage
visceral_fat_index	visceral_fat_index
bone_mass_percentage	bone_mass_percentage
body_mass_index	body_mass_index
lean_body_mass_kilogram	lean_body_mass_kilogram
waist_circumference_centimeter	waist_circumference_centimeter
-	time_zone
source.slug	source_provider
source.type	source_type
source.device_id	source_device_id
source.app_id	source_app_id

Meal

Meal field	Query Column
timestamp	index
name	name
energy.value	calories
macros.carbs	carbohydrate_gram
macros.protein	protein_gram
macros.alcohol	alcohol_gram
macros.water	water_gram
macros.fibre	fibre_gram
macros.sugar	sugar_gram
macros.cholesterol	cholesterol_gram
macros.fats.saturated	saturated_fat_gram
macros.fats.monounsaturated	monounsaturated_fat_gram
macros.fats.polyunsaturated	polyunsaturated_fat_gram
macros.fats.omega3	omega3_fat_gram
macros.fats.omega6	omega6_fat_gram
macros.fats.total	total_fat_gram
micros.minerals.sodium	sodium_milligram
micros.minerals.potassium	potassium_milligram
micros.minerals.calcium	calcium_milligram
micros.minerals.phosphorus	phosphorus_milligram
micros.minerals.magnesium	magnesium_milligram
micros.minerals.iron	iron_milligram
micros.minerals.zinc	zinc_milligram
micros.minerals.fluoride	fluoride_milligram
micros.minerals.chloride	chloride_milligram
micros.vitamins.vitamin_a	vitamin_a_milligram
micros.vitamins.vitamin_b1	vitamin_b1_milligram
micros.vitamins.riboflavin	riboflavin_milligram
micros.vitamins.niacin	niacin_milligram
micros.vitamins.pantothenic_acid	pantothenic_acid_milligram
micros.vitamins.vitamin_b6	vitamin_b6_milligram
micros.vitamins.biotin	biotin_microgram
micros.vitamins.vitamin_b12	vitamin_b12_microgram
micros.vitamins.vitamin_c	vitamin_c_milligram
micros.vitamins.vitamin_d	vitamin_d_microgram
micros.vitamins.vitamin_e	vitamin_e_milligram
micros.vitamins.vitamin_k	vitamin_k_microgram
micros.vitamins.folic_acid	folic_acid_microgram
micros.trace_elements.chromium	chromium_microgram
micros.trace_elements.copper	copper_milligram
micros.trace_elements.iodine	iodine_microgram
micros.trace_elements.manganese	manganese_milligram
micros.trace_elements.molybdenum	molybdenum_microgram
micros.trace_elements.selenium	selenium_microgram
source.slug	source_provider
source.type	source_type
source.app_id	source_app_id
source.device_id	source_device_id

MenstrualCycle

MenstrualCycle field	Query Column	Element type
period_start	period_start	scalar (Date)
period_end	period_end	scalar (Date)
cycle_end	cycle_end	scalar (Date)
is_predicted	is_predicted	scalar (Boolean)
menstrual_flow	menstrual_flow	list of struct {date, flow}
cervical_mucus	cervical_mucus	list of struct {date, quality}
intermenstrual_bleeding	intermenstrual_bleeding	list of struct {date}
contraceptive	contraceptive	list of struct {date, type}
detected_deviations	detected_deviations	list of struct {date, deviation}
ovulation_test	ovulation_test	list of struct {date, test_result}
home_pregnancy_test	home_pregnancy_test	list of struct {date, test_result}
home_progesterone_test	home_progesterone_test	list of struct {date, test_result}
sexual_activity	sexual_activity	list of struct {date, protection_used}
basal_body_temperature	basal_body_temperature	list of struct {date, value}
source.slug	source_provider	scalar
source.type	source_type	scalar
source.device_id	source_device_id	scalar
source.app_id	source_app_id	scalar

List columns cannot be selected directly as a table column — aggregate them with a scalar-output subquery. See List-column aggregation for the full syntax.

Profile

Profile field	Query Column
sex	sex
gender	gender
height	height_centimeter
wheelchair_use	wheelchair_use
birth_date	birth_date
created_at	created_at
updated_at	updated_at
source.slug	source_provider
source.type	source_type
source.app_id	source_app_id
source.device_id	source_device_id

Timeseries

Table	Python DSL	JSON DSL
Timeseries Resource fields	Timeseries.col("$1").field("$2")	{ "timeseries": "$1", "field": "$2" }

Source Column expression

You can use a Source Column expression to refer to Data Source fields common to Junction resources.

Note that some Source Column expressions may not be valid in the implicit query context. For example, source_sport is not a valid Source Column expression in a query that is selecting from the Sleep resource.

If both the Provider and Source Type Source Columns are present in the Group By clause, the implicit Data Prioritization behavior would be disabled.

Column	Python DSL	JSON DSL	Available in
Provider	Source.col("source_provider")	{ "source": "source_provider" }	All Tables
Source Type	Source.col("source_type")	{ "source": "source_type" }	All Tables
Source App ID	Source.col("source_app_id")	{ "source": "source_app_id" }	All summary tables
Workout ID	Source.col("source_workout_id")	{ "source": "source_workout_id" }	Workout Stream timeseries only
Sport	Source.col("source_sport")	{ "source": "source_sport" }	Workout Stream timeseries only

Index Column expression

Each Junction resource has a primary datetime index. Your Query Instruction can reference this datetime index using the special Index Column expression:

Table	Index	Python DSL	JSON DSL
Activity daily summary activity	Calendar date	Activity.index()	{ "index": "activity" }
Body summary body	Measurement datetime	Body.index()	{ "index": "body" }
Sleep summary sleep	Session end datetime	Sleep.index()	{ "index": "sleep" }
Readiness scores derived_readiness	Calendar date	DerivedReadiness.index()	{ "index": "derived_readiness" }
Workout summary workout	Session start datetime	Workout.index()	{ "index": "workout" }
Menstrual cycle menstrual_cycle	Period start date	MenstrualCycle.index()	{ "index": "menstrual_cycle" }
Profile profile	Updated At (UTC) datetime	Profile.index()	{ "index": "profile" }

Group Key Column expression

When your Query Instruction uses the group_by clause, each expression in the group_by clause creates a temporary Group Key Column (group_key.$OFFSET). These temporary columns are then used to facilitate the data grouping and aggregation as specified by your Query Instruction.

You can refer to these columns using the special Group Key Column expression:

Group Key Columns	Python DSL	JSON DSL
All	group_key("*")	{ "group_key": "*" }
The $N-th key	group_key($N)	{ "group_key": $N }