MATLAB Programming Fundamentals - MathWorks

Split Table Data Variables and Apply Functions

This example shows how to split power outage data from a table into groups by region

and cause of the power outages. Then it shows how to apply functions to calculate

statistics for each group and collect the results in a table.

Load Power Outage Data

The sample file, outages.csv, contains data representing electric utility outages in the

United States. The file contains six columns: Region, OutageTime, Loss, Customers,

RestorationTime, and Cause. Read outages.csv into a table.

T = readtable('outages.csv');

Convert Region and Cause to categorical arrays, and OutageTime and

RestorationTime to datetime arrays. Display the first five rows.

T.Region = categorical(T.Region);

T.Cause = categorical(T.Cause);

T.OutageTime = datetime(T.OutageTime);

T.RestorationTime = datetime(T.RestorationTime);

T(1:5,:)

ans=5×6 table

Region OutageTime Loss Customers RestorationTime Cause

_________ ________________ ______ __________ ________________ _______________

SouthWest 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 winter storm

SouthEast 2003-01-23 00:49 530.14 2.1204e+05 NaT winter storm

SouthEast 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 winter storm

West 2004-04-06 05:44 434.81 3.4037e+05 2004-04-06 06:10 equipment fault

MidWest 2002-03-16 06:18 186.44 2.1275e+05 2002-03-18 23:23 severe storm

Calculate Maximum Power Loss

Determine the greatest power loss due to a power outage in each region. The

findgroups function returns G, a vector of group numbers created from T.Region. The

splitapply function uses G to split T.Loss into five groups, corresponding to the five

regions. splitapply applies the max function to each group and concatenates the

maximum power losses into a vector.

G = findgroups(T.Region);

maxLoss = splitapply(@max,T.Loss,G)

Split Table Data Variables and Apply Functions