Create new variable from an existing variable but deleting some outliers

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Alejandra Uguet de Resayre
评论： Walter Roberson 2022-3-7
Hello!
I'm working with a NetCDF file and I have values of T,S,density,depth, chlorophyll and oxygen measured in time.
I plotted a vertical profile of oxygen with depth and I saw there were some outliers that need to be removed. So, I would like to create a new variable (oxycor) from the original oxygen variable but without those values. I would like to remove those values right in the corner with concentration of oxygen equal to zero.
I tried this and then plotting with 'glider.oxycor' but it says vectors must be the same length.
oxycorrection2=find(glider.oxy>150);
glider.oxycor=glider.oxy(oxycorrection2);
What am I doing wrong?
Thank you!!
  2 个评论
Walter Roberson
Walter Roberson 2022-3-5
Is glider a struct() or is it a table()
If it is a table, then you are trying to have the glider.oxy column be full length but the glider.oxycor column be shorter.
Alejandra Uguet de Resayre
Alejandra Uguet de Resayre 2022-3-5
Yes it is a table.
I thought about making those values NaN, but I don't want to modify the raw variable, just create a new one without them.
What could I do?

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采纳的回答

Walter Roberson
Walter Roberson 2022-3-5
mask = glider.oxy>150;
glider_subset = glider(mask,:);

更多回答（1 个）

Steven Lord
Steven Lord 2022-3-5
Ran in:
Remove all rows in the table that have an outlier value for the oxy variable. Here's a similar example using the sample patients data.
load patients
P = table(LastName, Age, Height, Weight);
P2 = P; % Make a backup copy before outlier removal
fprintf("P has %d rows before outlier removal\n", height(P))
P has 100 rows before outlier removal
head(P)
ans = 8×4 table
LastName Age Height Weight ____________ ___ ______ ______ {'Smith' } 38 71 176 {'Johnson' } 43 69 163 {'Williams'} 38 64 131 {'Jones' } 40 67 133 {'Brown' } 49 64 119 {'Davis' } 46 68 142 {'Miller' } 33 64 142 {'Wilson' } 40 68 180
Let's say outliers are patients that are younger than 40.
tooYoung = P.Age < 40;
P(tooYoung, :) = [];
fprintf("P has %d rows after outlier removal\n", height(P))
P has 44 rows after outlier removal
head(P)
ans = 8×4 table
LastName Age Height Weight ____________ ___ ______ ______ {'Johnson' } 43 69 163 {'Jones' } 40 67 133 {'Brown' } 49 64 119 {'Davis' } 46 68 142 {'Wilson' } 40 68 180 {'Anderson'} 45 68 128 {'Thomas' } 42 66 137 {'Martin' } 48 71 181
Note that several patients younger than 40 appeared in the table before outliers were removed, but afterwards the first patient in the resulting table was Johnson at 43 years old.
Now if you wanted to keep the data but not plot it, you could do that either by just using logical indexing or, if you want to compute with it more often, adding that as a new variable to the table.
P2.tooYoung = tooYoung;
head(P2)
ans = 8×5 table
LastName Age Height Weight tooYoung ____________ ___ ______ ______ ________ {'Smith' } 38 71 176 true {'Johnson' } 43 69 163 false {'Williams'} 38 64 131 true {'Jones' } 40 67 133 false {'Brown' } 49 64 119 false {'Davis' } 46 68 142 false {'Miller' } 33 64 142 true {'Wilson' } 40 68 180 false
plot(P2{tooYoung, "Height"}, P2{tooYoung, "Weight"}, 'o'); % or
figure
scatter(P2{P2.tooYoung, "Height"}, P2{P2.tooYoung, "Weight"})

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