is the following correct to read the timestamp
pd.to_datetime(out['timestamp'],unit='s')
??
Also, while dealing with data-I, can we join on timestamp ? let me explain, so e.g i am getting data for subject = x , on day = 1 , and i want all the data from all three sensors in one pandas dataframe, so here i read the 3 different file (one for each sensor), and joined them on timestamp. Is this approach correct ?
Created by umar khan ukhan.mscs18seecs >is the following correct to read the timestamp
>
>pd.to_datetime(out['timestamp'],unit='s')
The timestamps are unix timestamps, so yes. You can also work with the timestamp directly as a unitless value, since I believe the rest of the dataset includes the unix timestamp of the event.
> Also, while dealing with data-I, can we join on timestamp ? let me explain, so e.g i am getting data for subject = x , on day = 1 , and i want all the data from all three sensors in one pandas dataframe, so here i read the 3 different file (one for each sensor), and joined them on timestamp. Is this approach correct ?
I would recommend not joining on timestamp since the _exact_ timestamp can depend on arbitrary things like the precision of the device. Instead I would filter timestamps based off of an event of interest. For example, if you want data from all three sensors while subject = x was doing the stndg task on day = 1 you can filter the sensor data between `timestamp` >= `timestamp_start` and `timestamp` <= `timestamp_stop`. Of course, you can always do a full (outer) join of the sensor data, but this depends on your processing pipeline being able to handle missing values -- in the case when a timestamp does not appear in all three sensor data files.