How can I extract table rows based on the value of a single column
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I am trying to extract data from a table. My table includes air quality data from a number of sensors and I want to compare the results for when a filter was on or off.
The table headings and a line of sample data is shown below.
'Date_Time' , 'PM2.5', 'UV_BC', 'Blue_BC', 'Green_BC', 'Red_BC', 'IR_BC', 'Particle_Count' , 'Particle_Conc', 'Filter_on_off'
09-10-2019 10:50:00 3 538 398.300 364.9 375.5 935.6 155.4708 51.9907 0
The 'Filter_on_off' value ranges from 0 to 1 but is not a logistical value, values of 0.5 and 0.75 are possible (related to fan speed)
How would I isolate data when the filter is off ('Filter_on_off' = 0) and on ('Filter_on_off' >1) for comparison?
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dpb
2019-12-30
编辑:dpb
2019-12-30
Create a variable with the desired categories and populate it by sorting into proper category each value. A histogram would be easy way of assigning bin numbers if the speeds can be anything between 0-1.
OTOH, if they are a finite number of set speeds like those above, then simply categorical(fanspeed) will do it for the categories in unique(fanspeed)(*) You can then either use those values as the category names or assign others like 'OFF', 'SLOW','MEDIUM','HIGH' or whatever you wish.
Again, I can't urge you enough to read the documentation on categorical arrays and look at examples. varfun and/or splitapply are your friends for all these kinds of things...they all just drop in your lap if you set it up to use the facilities TMW provides.
(*) If there aren't all possible categories in the dataset, use the optional inputs to the function to define them.
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