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)
maxLoss = 5×1
10
4
×
2.3141
2.3418
0.8767
0.2796
1.6659
Calculate the maximum power loss due to a power outage by cause. To specify that Cause is the
grouping variable, use table indexing. Create a table that contains the maximum power losses and
their causes.
9 Tables
9-52