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< svg xmlns = "http://www.w3.org/2000/svg" viewBox = "0 0 24 24" > < path d = "M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25z" / > < / svg >
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< h1 id = "fitbitparsed_csv" > < code > fitbitparsed_csv< / code > < a class = "headerlink" href = "#fitbitparsed_csv" title = "Permanent link" > ¶ < / a > < / h1 >
< p > This < a href = "../../datastreams/data-streams-introduction" > data stream< / a > handles Fitbit sensor data downloaded using the < a href = "https://dev.fitbit.com/build/reference/web-api/" > Fitbit Web API< / a > , < strong > parsed< / strong > , and stored in a CSV file. Please note that RAPIDS cannot query the API directly; you need to use other available tools or implement your own. Once you have your parsed sensor data in a CSV file, RAPIDS can process it.< / p >
< div class = "admonition info" >
< p class = "admonition-title" > What is the difference between JSON and plain data streams< / p >
< p > Most people will only need < code > fitbitjson_*< / code > because they downloaded and stored their data directly from Fitbit’ s API. However, if, for some reason, you don’ t have access to that JSON data and instead only have the parsed data (columns and rows), you can use this data stream.< / p >
< / div >
< div class = "admonition warning" >
< p class = "admonition-title" > Warning< / p >
< p > The CSV files have to use < code > ,< / code > as separator, < code > \< / code > as escape character (do not escape < code > "< / code > with < code > ""< / code > ), and wrap any string columns with < code > "< / code > .< / p >
< details class = "example" > < summary > Example of a valid CSV file< / summary > < div class = "highlight" > < pre > < span > < / span > < code > " device_id" ," heartrate" ," heartrate_zone" ," local_date_time" ," timestamp"
" a748ee1a-1d0b-4ae9-9074-279a2b6ba524" ,69," outofrange" ," 2020-04-23 00:00:00" ,0
" a748ee1a-1d0b-4ae9-9074-279a2b6ba524" ,69," outofrange" ," 2020-04-23 00:01:00" ,0
" a748ee1a-1d0b-4ae9-9074-279a2b6ba524" ,67," outofrange" ," 2020-04-23 00:02:00" ,0
" a748ee1a-1d0b-4ae9-9074-279a2b6ba524" ,69," outofrange" ," 2020-04-23 00:03:00" ,0
< / code > < / pre > < / div >
< / details >
< / div >
< h2 id = "container" > Container< a class = "headerlink" href = "#container" title = "Permanent link" > ¶ < / a > < / h2 >
< p > The container should be a CSV file per sensor, each containing all participants’ data.< / p >
< p > The script to connect and download data from this container is at:
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/fitbitparsed_csv/container.R
< / code > < / pre > < / div > < / p >
< h2 id = "format" > Format< a class = "headerlink" href = "#format" title = "Permanent link" > ¶ < / a > < / h2 >
< p > The < code > format.yaml< / code > maps and transforms columns in your raw data stream to the < a href = "../mandatory-fitbit-format" > mandatory columns RAPIDS needs for Fitbit sensors< / a > . This file is at:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/fitbitparsed_mysql/format.yaml
< / code > < / pre > < / div >
< p > If you want to use this stream with your data, modify every sensor in < code > format.yaml< / code > to map all columns except < code > TIMESTAMP< / code > in < code > [RAPIDS_COLUMN_MAPPINGS]< / code > to your raw data column names.< / p >
< p > All columns are mandatory; however, all except < code > device_id< / code > and < code > local_date_time< / code > can be empty if you don’ t have that data. Just have in mind that some features will be empty if some of these columns are empty.< / p >
< details class = "info" > < summary > FITBIT_HEARTRATE_SUMMARY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > HEARTRATE_DAILY_RESTINGHR< / td >
< td > heartrate_daily_restinghr< / td >
< / tr >
< tr >
< td > HEARTRATE_DAILY_CALORIESOUTOFRANGE< / td >
< td > heartrate_daily_caloriesoutofrange< / td >
< / tr >
< tr >
< td > HEARTRATE_DAILY_CALORIESFATBURN< / td >
< td > heartrate_daily_caloriesfatburn< / td >
< / tr >
< tr >
< td > HEARTRATE_DAILY_CALORIESCARDIO< / td >
< td > heartrate_daily_caloriescardio< / td >
< / tr >
< tr >
< td > HEARTRATE_DAILY_CALORIESPEAK< / td >
< td > heartrate_daily_caloriespeak< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< details class = "example" > < summary > Example of the raw data RAPIDS expects for this data stream< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > local_date_time< / th >
< th > heartrate_daily_restinghr< / th >
< th > heartrate_daily_caloriesoutofrange< / th >
< th > heartrate_daily_caloriesfatburn< / th >
< th > heartrate_daily_caloriescardio< / th >
< th > heartrate_daily_caloriespeak< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07< / td >
< td > 72< / td >
< td > 1200.6102< / td >
< td > 760.3020< / td >
< td > 15.2048< / td >
< td > 0< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-08< / td >
< td > 70< / td >
< td > 1100.1120< / td >
< td > 660.0012< / td >
< td > 23.7088< / td >
< td > 0< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-09< / td >
< td > 69< / td >
< td > 750.3615< / td >
< td > 734.1516< / td >
< td > 131.8579< / td >
< td > 0< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
< details class = "info" > < summary > FITBIT_HEARTRATE_INTRADAY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > HEARTRATE< / td >
< td > heartrate< / td >
< / tr >
< tr >
< td > HEARTRATE_ZONE< / td >
< td > heartrate_zone< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< details class = "example" > < summary > Example of the raw data RAPIDS expects for this data stream< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > local_date_time< / th >
< th > heartrate< / th >
< th > heartrate_zone< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:00:00< / td >
< td > 68< / td >
< td > outofrange< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:01:00< / td >
< td > 67< / td >
< td > outofrange< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:02:00< / td >
< td > 67< / td >
< td > outofrange< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
< details class = "info" > < summary > FITBIT_SLEEP_SUMMARY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > LOCAL_START_DATE_TIME< / td >
< td > local_start_date_time< / td >
< / tr >
< tr >
< td > LOCAL_END_DATE_TIME< / td >
< td > local_end_date_time< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > EFFICIENCY< / td >
< td > efficiency< / td >
< / tr >
< tr >
< td > MINUTES_AFTER_WAKEUP< / td >
< td > minutes_after_wakeup< / td >
< / tr >
< tr >
< td > MINUTES_ASLEEP< / td >
< td > minutes_asleep< / td >
< / tr >
< tr >
< td > MINUTES_AWAKE< / td >
< td > minutes_awake< / td >
< / tr >
< tr >
< td > MINUTES_TO_FALL_ASLEEP< / td >
< td > minutes_to_fall_asleep< / td >
< / tr >
< tr >
< td > MINUTES_IN_BED< / td >
< td > minutes_in_bed< / td >
< / tr >
< tr >
< td > IS_MAIN_SLEEP< / td >
< td > is_main_sleep< / td >
< / tr >
< tr >
< td > TYPE< / td >
< td > type< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< p > Fitbit API has two versions for sleep data, v1 and v1.2. We support both but ignore v1’ s < code > count_awake< / code > , < code > duration_awake< / code > , and < code > count_awakenings< / code > , < code > count_restless< / code > , < code > duration_restless< / code > columns.< / p >
< details class = "example" > < summary > Example of the expected raw data< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > local_start_date_time< / th >
< th > local_end_date_time< / th >
< th > efficiency< / th >
< th > minutes_after_wakeup< / th >
< th > minutes_asleep< / th >
< th > minutes_awake< / th >
< th > minutes_to_fall_asleep< / th >
< th > minutes_in_bed< / th >
< th > is_main_sleep< / th >
< th > type< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-10 15:36:30< / td >
< td > 2020-10-10 16:37:00< / td >
< td > 92< / td >
< td > 0< / td >
< td > 55< / td >
< td > 5< / td >
< td > 0< / td >
< td > 60< / td >
< td > 0< / td >
< td > classic< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-10 01:46:30< / td >
< td > 2020-10-10 08:10:00< / td >
< td > 88< / td >
< td > 0< / td >
< td > 318< / td >
< td > 65< / td >
< td > 0< / td >
< td > 383< / td >
< td > 1< / td >
< td > stages< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-11 00:12:30< / td >
< td > 2020-10-11 11:47:00< / td >
< td > 89< / td >
< td > 1< / td >
< td > 562< / td >
< td > 132< / td >
< td > 0< / td >
< td > 694< / td >
< td > 1< / td >
< td > stages< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-12 01:31:00< / td >
< td > 2020-10-12 09:34:30< / td >
< td > 93< / td >
< td > 0< / td >
< td > 415< / td >
< td > 68< / td >
< td > 0< / td >
< td > 483< / td >
< td > 1< / td >
< td > stages< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
< details class = "info" > < summary > FITBIT_SLEEP_INTRADAY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > TYPE_EPISODE_ID< / td >
< td > type_episode_id< / td >
< / tr >
< tr >
< td > DURATION< / td >
< td > duration< / td >
< / tr >
< tr >
< td > IS_MAIN_SLEEP< / td >
< td > is_main_sleep< / td >
< / tr >
< tr >
< td > TYPE< / td >
< td > type< / td >
< / tr >
< tr >
< td > LEVEL< / td >
< td > level< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< p > Fitbit API has two versions for sleep data, v1 and v1.2, we support both.< / p >
< details class = "example" > < summary > Example of the expected raw data< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > type_episode_id< / th >
< th > local_date_time< / th >
< th > duration< / th >
< th > level< / th >
< th > is_main_sleep< / th >
< th > type< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 0< / td >
< td > 2020-10-10 15:36:30< / td >
< td > 60< / td >
< td > restless< / td >
< td > 0< / td >
< td > classic< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 0< / td >
< td > 2020-10-10 15:37:30< / td >
< td > 660< / td >
< td > asleep< / td >
< td > 0< / td >
< td > classic< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 0< / td >
< td > 2020-10-10 15:48:30< / td >
< td > 60< / td >
< td > restless< / td >
< td > 0< / td >
< td > classic< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > … < / td >
< td > … < / td >
< td > … < / td >
< td > … < / td >
< td > … < / td >
< td > … < / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 1< / td >
< td > 2020-10-10 01:46:30< / td >
< td > 420< / td >
< td > light< / td >
< td > 1< / td >
< td > stages< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 1< / td >
< td > 2020-10-10 01:53:30< / td >
< td > 1230< / td >
< td > deep< / td >
< td > 1< / td >
< td > stages< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
< details class = "info" > < summary > FITBIT_STEPS_SUMMARY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > STEPS< / td >
< td > steps< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< details class = "example" > < summary > Example of the expected raw data< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > local_date_time< / th >
< th > steps< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07< / td >
< td > 1775< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-08< / td >
< td > 3201< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-09< / td >
< td > 998< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
< details class = "info" > < summary > FITBIT_STEPS_INTRADAY< / summary > < p > < strong > RAPIDS_COLUMN_MAPPINGS< / strong > < / p >
< table >
< thead >
< tr >
< th > RAPIDS column< / th >
< th > Stream column< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > TIMESTAMP< / td >
< td > FLAG_TO_MUTATE< / td >
< / tr >
< tr >
< td > DEVICE_ID< / td >
< td > device_id< / td >
< / tr >
< tr >
< td > LOCAL_DATE_TIME< / td >
< td > local_date_time< / td >
< / tr >
< tr >
< td > STEPS< / td >
< td > steps< / td >
< / tr >
< / tbody >
< / table >
< p > < strong > MUTATION< / strong > < / p >
< ul >
< li >
< p > < strong > COLUMN_MAPPINGS< / strong > (None)< / p >
< / li >
< li >
< p > < strong > SCRIPTS< / strong > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > src/data/streams/mutations/fitbit/add_zero_timestamp.py
< / code > < / pre > < / div >
< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > < code > add_zero_timestamp< / code > adds an all-zero column called < code > timestamp< / code > that will be filled in later in the pipeline by < code > readable_time.R< / code > converting LOCAL_DATE_TIME to a unix timestamp taking into account single or multiple time zones.< / p >
< details class = "example" > < summary > Example of the expected raw data< / summary > < table >
< thead >
< tr >
< th > device_id< / th >
< th > local_date_time< / th >
< th > steps< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:00:00< / td >
< td > 5< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:01:00< / td >
< td > 3< / td >
< / tr >
< tr >
< td > a748ee1a-1d0b-4ae9-9074-279a2b6ba524< / td >
< td > 2020-10-07 00:02:00< / td >
< td > 0< / td >
< / tr >
< / tbody >
< / table >
< / details >
< / div >
< / details >
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