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Resample and Aggregate Data in Timetable
This example shows how to resample and aggregate data in a timetable. A timetable is a type of table that associates a time with each row. A timetable can store column-oriented data variables that have different data types and sizes, so long as each variable has the same number of rows. With the retime function, you can resample timetable data, or aggregate timetable data into time bins you specify.
Import Timetable
Load a timetable containing weather measurements taken from November 15, 2015, to November 19, 2015. The timetable contains humidity, temperature, and pressure readings taken over this time period.
load(fullfile(matlabroot,'examples','matlab','outdoors')); outdoors(1:5,:)
ans =
Time Humidity TemperatureF PressureHg
___________________ ________ ____________ __________
2015-11-15 00:00:24 49 51.3 29.61
2015-11-15 01:30:24 48.9 51.5 29.61
2015-11-15 03:00:24 48.9 51.5 29.61
2015-11-15 04:30:24 48.8 51.5 29.61
2015-11-15 06:00:24 48.7 51.5 29.6
Determine if the timetable is regular. A regular timetable is one in which the differences between all consecutive row times are the same. outdoors is not a regular timetable.
TF = isregular(outdoors)
TF = logical 0
Find the differences in the time steps. They vary between half a minute and an hour and a half.
dt = unique(diff(outdoors.Time))
dt = 3×1 duration array 00:00:24 01:29:36 01:30:00
Resample Timetable with Interpolation
Adjust the data in the timetable with the retime function. Specify an hourly time vector. Interpolate the timetable data to the new row times.
TT = retime(outdoors,'hourly','spline'); TT(1:5,:)
ans =
Time Humidity TemperatureF PressureHg
___________________ ________ ____________ __________
2015-11-15 00:00:00 49.001 51.298 29.61
2015-11-15 01:00:00 48.909 51.467 29.61
2015-11-15 02:00:00 48.902 51.51 29.61
2015-11-15 03:00:00 48.9 51.5 29.61
2015-11-15 04:00:00 48.844 51.498 29.611
Resample Timetable with Nearest Neighbor Values
Specify an hourly time vector for TT. For each row in TT, copy values from the corresponding row in outdoors whose row time is nearest.
TT = retime(outdoors,'hourly','nearest'); TT(1:5,:)
ans =
Time Humidity TemperatureF PressureHg
___________________ ________ ____________ __________
2015-11-15 00:00:00 49 51.3 29.61
2015-11-15 01:00:00 48.9 51.5 29.61
2015-11-15 02:00:00 48.9 51.5 29.61
2015-11-15 03:00:00 48.9 51.5 29.61
2015-11-15 04:00:00 48.8 51.5 29.61
Aggregate Timetable Data and Calculate Daily Mean
The retime function provides aggregation methods, such as mean. Calculate the daily means for the data in outdoors.
TT = retime(outdoors,'daily','mean'); TT
TT =
Time Humidity TemperatureF PressureHg
___________________ ________ ____________ __________
2015-11-15 00:00:00 48.931 51.394 29.607
2015-11-16 00:00:00 47.924 51.571 29.611
2015-11-17 00:00:00 48.45 51.238 29.613
2015-11-18 00:00:00 49.5 50.8 29.61
Aggregate Timetable Data to Different Time Vector
Calculate the means over six-hour time intervals. Specify a time vector to use with the retime function. Specify a format for the time vector to display both date and time when you display the timetable.
tv = datetime(2015,11,15):hours(6):datetime(2015,11,18); tv.Format = 'dd-MMM-yyyy HH:mm:ss'; TT = retime(outdoors,tv,'mean'); TT(1:5,:)
ans =
Time Humidity TemperatureF PressureHg
____________________ ________ ____________ __________
15-Nov-2015 00:00:00 48.9 51.45 29.61
15-Nov-2015 06:00:00 48.9 51.45 29.6
15-Nov-2015 12:00:00 49.025 51.45 29.61
15-Nov-2015 18:00:00 48.9 51.225 29.607
16-Nov-2015 00:00:00 48.5 51.4 29.61
See Also
retime | synchronize | table2timetable | timetable
