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

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.

[the cyclist]

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.

[youjarr]

Added a MAT-File with a small example

Answer 1

[Seth Furman]

Group data by RotorNumber using findgroups

https://www.mathworks.com/help/matlab/ref/findgroups.html

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

https://www.mathworks.com/help/matlab/ref/splitapply.html

https://www.mathworks.com/help/matlab/ref/plot.html

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

https://www.mathworks.com/help/matlab/ref/splitapply.html

https://www.mathworks.com/help/matlab/ref/stackedplot.html

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")