再保险sample and Aggregate Data in Timetable

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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, provided that each variable has the same number of rows. With theretimefunction, 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.

loadoutdoorsoutdoors(1:5,:)

ans=5×3 timetable时间湿度TemperatureFPressureHg ___________________ ________ ____________ __________ 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.outdoorsis not a regular timetable.

TF = isregular(outdoors)

TF =logical0

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 =3x1 duration00:00:24 01:29:36 01:30:00

再保险sample Timetable with Interpolation

Adjust the data in the timetable with theretimefunction. Specify an hourly time vector. Interpolate the timetable data to the new row times.

TT = retime(outdoors,'hourly','spline'); TT(1:5,:)

ans=5×3 timetable时间湿度TemperatureFPressureHg ___________________ ________ ____________ __________ 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

再保险sample Timetable with Nearest Neighbor Values

Specify an hourly time vector forTT。每一行的TT, copy values from the corresponding row inoutdoorswhose row time is nearest.

TT = retime(outdoors,'hourly','nearest'); TT(1:5,:)

ans=5×3 timetable时间湿度TemperatureFPressureHg ___________________ ________ ____________ __________ 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

Theretimefunction provides aggregation methods, such asmean。Calculate the daily means for the data inoutdoors。

TT = retime(outdoors,'daily','mean'); TT

TT=4×3 timetable时间湿度TemperatureFPressureHg ___________________ ________ ____________ __________ 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

Adjust Timetable Data to Regular Times

Calculate the means over six-hour time intervals. Specify a regular time step using the'regular'input argument and the'TimeStep'name-value pair argument.

TT = retime(outdoors,'regular','mean','TimeStep',hours(6)); TT(1:5,:)

ans=5×3 timetable时间湿度TemperatureFPressureHg ___________________ ________ ____________ __________ 2015-11-15 00:00:00 48.9 51.45 29.61 2015-11-15 06:00:00 48.9 51.45 29.6 2015-11-15 12:00:00 49.025 51.45 29.61 2015-11-15 18:00:00 48.9 51.225 29.607 2015-11-16 00:00:00 48.5 51.4 29.61

As an alternative, you can specify a time vector that has the same six-hour time intervals. 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=5×3 timetable时间湿度TemperatureFPressureHg ____________________ ________ ____________ __________ 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