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Plot data within a table and use categorial column to "split" them in the graph

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Hello guys,
I have a table.
The size is 795183x35 (in the original data).
The column 3 "RotorNumber" is type categorial.
How can I plot (it doesn´t matter which plot but e.g. quiver) the data of the other rows but by considering the categories so i can have a legend with the different categories?
My first idea was to make a for-loop and to split the table by comparing the categorial data... but for sure there is a much easier way..??
I never worked with categorial data so I don´t know how to handle these... .
Best regards...
and thanks in advance.
  2 Comments
the cyclist
the cyclist on 2 Dec 2022
Edited: the cyclist on 2 Dec 2022
This would be easier to help with if you posted a small sample of the table (e.g. maybe 10 rows, with a few different categories of RotorNumber). You can used the paper clip icon in the INSERT section of the toolbar to upload it here.

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Answers (1)

Seth Furman
Seth Furman on 7 Dec 2022
Group data by RotorNumber using findgroups
load MiniExample.mat
t = sortrows(ExampleTable)
t = 15×35 table
datetime a RotorNumber Runs b c d e f g h i j k datetimeright m n o p q r s t u v w x y z aa bb cc dd ee ff ___________________ ___ __________________________ ____ ______ ___ ______ ___ ______ __ _ ____ _____ _ ___________________ _____ ___ _____ ___ ________ ________ ________ ________ ________ _______ ________ ________ ________ ________ _______ _______ __________ ________ ________ _________ 2022-03-21T15:00:08 100 102A3C02920101000220730650 1 180.99 33 58.59 191 DUO2_1 13 2 135 67.5 1 2022-03-21T15:00:46 30.37 4 19.55 145 151.79 98.574 30.296 2.1185 -57.514 -11.179 -16.014 11.213 121.49 96.456 -41.499 -22.393 0.19959 0.021491 0.27845 -1.003 2022-03-21T15:00:46 100 102A3C02920101000220730650 2 30.37 4 19.55 145 DUO2_1 12 4 22.5 67.5 2 2022-03-21T15:01:12 5.15 353 2.44 107 30.296 2.1185 5.1116 -0.62763 -16.014 11.213 -0.71339 2.3334 25.184 2.7461 -15.301 8.88 0.16872 -0.29626 0.044547 0.20809 2022-03-21T15:01:12 100 102A3C02920101000220730650 3 5.15 353 2.44 107 DUO2_1 2 1 22.5 67.5 2 2022-03-21T15:01:30 0.57 323 2.51 295 5.1116 -0.62763 0.45522 -0.34303 -0.71339 2.3334 1.0608 -2.2748 4.6564 -0.28459 -1.7742 4.6082 0.089056 0.54656 -1.487 -0.97491 2022-03-21T15:03:16 100 102A3C02920101000220730657 1 157.09 26 86.09 169 DUO2_1 12 3 135 67.5 1 2022-03-21T15:03:52 12.75 310 23.81 111 141.19 68.864 8.1955 -9.7671 -84.508 16.427 -8.5327 22.229 133 78.631 -75.976 -5.8018 0.058046 -0.14183 0.10097 1.3532 2022-03-21T15:03:52 100 102A3C02920101000220730657 2 12.75 310 23.81 111 DUO2_1 5 5 22.5 67.5 2 2022-03-21T15:04:18 1.98 192 1.47 331 8.1955 -9.7671 -1.9367 -0.41167 -8.5327 22.229 1.2857 -0.71267 10.132 -9.3554 -9.8184 22.941 -0.23632 0.042148 -0.15068 -0.032061 2022-03-21T15:06:41 100 102A3C02920101000220730664 1 138.97 19 213.92 165 DUO2_1 10 5 135 112.5 1 2022-03-21T15:07:16 32.46 287 35.04 75 131.4 45.244 9.4904 -31.042 -206.63 55.367 9.069 33.846 121.91 76.286 -215.7 21.521 0.072226 -0.68609 -0.04389 0.61131 2022-03-21T15:07:16 100 102A3C02920101000220730664 2 32.46 287 35.04 75 DUO2_1 13 6 22.5 67.5 2 2022-03-21T15:07:44 2.25 202 5.49 26 9.4904 -31.042 -2.0862 -0.84286 9.069 33.846 4.9344 2.4067 11.577 -30.199 4.1346 31.439 -0.21982 0.027153 0.54409 0.071106 2022-03-21T15:07:44 100 102A3C02920101000220730664 3 2.25 202 5.49 26 DUO2_1 1 2 22.5 67.5 3 2022-03-21T15:08:02 2.32 20 0.84 21 -2.0862 -0.84286 2.1801 0.79349 4.9344 2.4067 0.78421 0.30103 -4.2663 -1.6364 4.1502 2.1056 -1.045 -0.94142 0.15893 0.12508 2022-03-21T15:11:33 100 102A3C02920101000220730671 1 97.73 249 132.7 190 DUO2_1 7 3 135 112.5 1 2022-03-21T15:12:03 16 289 57.03 197 -35.023 -91.239 5.2091 -15.128 -130.68 -23.043 -54.538 -16.674 -40.232 -76.111 -76.146 -6.3692 -0.14873 0.16581 0.41733 0.7236 2022-03-21T15:12:03 100 102A3C02920101000220730671 2 16 289 57.03 197 DUO2_1 6 2 22.5 67.5 1 2022-03-21T15:12:28 6.31 314 16.95 201 5.2091 -15.128 4.3833 -4.539 -54.538 -16.674 -15.824 -6.0743 0.8258 -10.589 -38.714 -10.6 0.84147 0.30004 0.29015 0.3643 2022-03-21T15:12:28 100 102A3C02920101000220730671 3 6.31 314 16.95 201 DUO2_1 3 4 22.5 67.5 2 2022-03-21T15:12:53 1.86 201 2.08 354 4.3833 -4.539 -1.7365 -0.66656 -15.824 -6.0743 2.0686 -0.21742 6.1198 -3.8725 -17.893 -5.8569 -0.39615 0.14685 -0.13072 0.035793 2022-03-23T13:14:46 100 102A3C02920101000220730666 1 81.6 44 214.78 166 DUO2_1 6 5 135 112.5 1 2022-03-23T13:15:17 34.25 312 26.34 107 58.698 56.684 22.918 -25.453 -208.4 51.96 -7.7011 25.189 35.78 82.137 -200.7 26.771 0.39043 -0.44903 0.036953 0.48478 2022-03-23T13:15:17 100 102A3C02920101000220730666 2 34.25 312 26.34 107 DUO2_1 14 6 22.5 67.5 2 2022-03-23T13:15:44 1.31 262 5.65 292 22.918 -25.453 -0.18232 -1.2973 -7.7011 25.189 2.1165 -5.2386 23.1 -24.155 -9.8176 30.428 -0.0079553 0.050967 -0.27484 -0.20797 2022-03-23T13:15:44 100 102A3C02920101000220730666 3 1.31 262 5.65 292 DUO2_1 1 2 22.5 67.5 3 2022-03-23T13:16:03 1.16 67 2.23 288 -0.18232 -1.2973 0.45325 1.0678 2.1165 -5.2386 0.68911 -2.1209 -0.63556 -2.365 1.4274 -3.1177 -2.486 -0.82311 0.32558 0.40485 2022-03-23T13:19:19 100 102A3C02920101000220730668 1 116 94 59.36 250 DUO2_1 9 2 135 67.5 1 2022-03-23T13:19:50 17.73 66 25.38 226 -8.0918 115.72 7.2114 16.197 -20.302 -55.78 -17.63 -18.257 -15.303 99.52 -2.6719 -37.523 -0.89121 0.13997 0.86839 0.3273
[groupNums,uniqueRotorNumbers] = findgroups(t.RotorNumber)
groupNums = 15×1
1 1 1 2 2 3 3 3 6 6
uniqueRotorNumbers = 6×1 categorical array
102A3C02920101000220730650 102A3C02920101000220730657 102A3C02920101000220730664 102A3C02920101000220730666 102A3C02920101000220730668 102A3C02920101000220730671
Plot data using splitapply and plot
hold on
splitapply(@plot,t(:,"b"),groupNums)
hold off
legend(string(uniqueRotorNumbers));
title("b vs. Row Number");
ylabel("b");
xlabel("Row Number");
figure
hold on
splitapply(@(x,y)plot(x,y),t(:,["datetime","b"]),groupNums)
hold off
legend(string(uniqueRotorNumbers));
title("b vs. datetime");
ylabel("b");
xlabel("datetime");
Plot data using splitapply and stackedplot support for multiple table inputs
tableCellData2Table = @(varargin){table(varargin{:},VariableNames=t.Properties.VariableNames)};
tCell = splitapply(tableCellData2Table,t,groupNums)
tCell = 6×1 cell array
{3×35 table} {2×35 table} {3×35 table} {3×35 table} {1×35 table} {3×35 table}
variablesToPlot = t.Properties.VariableNames(5:6);
stackedplot(tCell,variablesToPlot,LegendLabels=string(uniqueRotorNumbers))
OR you can set the x-variable with the XVariable parameter.
stackedplot(tCell,variablesToPlot,LegendLabels=string(uniqueRotorNumbers),XVariable="datetime")

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