How to plot only the maximum values of the listed variables in a scatter plot?

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Michael
Michael 2023-10-23
评论： Dyuman Joshi 2023-10-26
Hello,
I am new to coding and managed to get this far. I am trying to clean up this plot a little and help differentiate the y axis variables (Gain,PAE,PLRF_dBm) to only show the maximum values of Gain, PAE, and PLRF_dBm for each frequency. Basically, I would like to plot the maximum values from each variable listed above for each frequency. Any help would be greatly appeciated. I have read everything I could find but nothing works with my level of understanding. Thanks so much!!!
Pswpdata = readtable('csv_file.csv');
scatter(Pswpdata,'Frequency',{'Gain','PAE','PLRF_dBm'},'filled')
legend
title('GT,PAE & Pout (dB)')

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Dyuman Joshi
Dyuman Joshi 2023-10-23
移动：Dyuman Joshi 2023-10-23
Ran in:
Pswpdata = readtable('csv_file.csv')
Pswpdata = 49×26 table
Pavs_dB_set Pavs_set Frequency PinRF PavRF GinRF_real GinRF_imag GLRF_real GLRF_imag PLRF VectorGain_real VectorGain_imag PS1_V_base_2 PS1_I_base_2 PS2_V_col_2 PS2_I_col_2 Responsivity Resp_volt_on Resp_volt_off PinRF_dBm PavRF_dBm PLRF_dBm Gain GainT PAE Eff ___________ ________ _________ ________ ________ __________ __________ _________ _________ ________ _______________ _______________ ____________ ____________ ___________ ___________ ____________ ____________ _____________ _________ _________ ________ ______ ________ ________ ________ 9.5 0.008913 1.8e+11 1.3e-05 3.9e-05 -0.40094 -0.52629 0.14437 -0.19054 4.6e-05 -1.4258 -0.1085 1.484 0.005901 2.1 0.09601 -1000 -1000 -1000 -18.744 -14.092 -13.392 5.3515 0.69946 0.015417 0.021765 10.5 0.01122 1.8e+11 1.7e-05 5e-05 -0.40888 -0.51934 0.14434 -0.19058 5.9e-05 -1.4266 -0.033663 1.485 0.005901 2.1 0.096125 -1000 -1000 -1000 -17.645 -13.014 -12.318 5.3267 0.69602 0.019676 0.027842 11.5 0.014125 1.8e+11 2.5e-05 7.3e-05 -0.41009 -0.51849 0.14429 -0.19058 8.5e-05 -1.4252 0.010566 1.4852 0.005901 2.1 0.09614 -1000 -1000 -1000 -16.015 -11.385 -10.697 5.3174 0.68758 0.028546 0.04043 12.5 0.017783 1.8e+11 6.7e-05 0.000192 -0.41176 -0.51566 0.14432 -0.19055 0.000223 -1.4166 0.039907 1.4846 0.005901 2.1 0.09612 -1000 -1000 -1000 -11.767 -7.1558 -6.5111 5.2558 0.64464 0.074415 0.10602 13.5 0.022387 1.8e+11 0.000196 0.000568 -0.41292 -0.516 0.14431 -0.19056 0.000647 -1.4033 0.061581 1.4851 0.005901 2.1 0.09607 -1000 -1000 -1000 -7.0789 -2.4562 -1.8902 5.1887 0.56608 0.21433 0.3074 14.5 0.028184 1.8e+11 0.001856 0.005365 -0.41434 -0.51396 0.14437 -0.19047 0.005463 -1.3243 0.088082 1.4818 0.005901 2.101 0.095135 -1000 -1000 -1000 2.6853 7.296 7.3744 4.6891 0.078333 1.7291 2.6187 15.5 0.035481 1.8e+11 0.011099 0.032409 -0.40748 -0.52239 0.14443 -0.19034 0.023011 -1.1021 0.13808 1.4568 0.005901 2.1 0.08959 -1000 -1000 -1000 10.453 15.107 13.619 3.1665 -1.4872 6.0549 11.697 9.5 0.008913 1.85e+11 0.000122 0.000331 -0.53329 -0.37641 0.037686 -0.38289 0.000421 -1.4349 0.51454 1.4853 0.005901 2.1 0.09601 -1000 -1000 -1000 -9.13 -4.8044 -3.7526 5.3774 1.0518 0.14225 0.20032 10.5 0.01122 1.85e+11 0.00017 0.000459 -0.53465 -0.37408 0.037699 -0.3829 0.000582 -1.4255 0.52291 1.4849 0.005901 2.101 0.09599 -1000 -1000 -1000 -7.6942 -3.3787 -2.3532 5.3409 1.0255 0.1956 0.27641 11.5 0.014125 1.85e+11 0.000241 0.00065 -0.5361 -0.37299 0.037698 -0.38289 0.000816 -1.4157 0.52855 1.4844 0.005901 2.1 0.095845 -1000 -1000 -1000 -6.1888 -1.8715 -0.88348 5.3054 0.98798 0.27397 0.38848 12.5 0.017783 1.85e+11 0.000352 0.000951 -0.53665 -0.37249 0.037733 -0.38291 0.001178 -1.4034 0.5318 1.4852 0.005901 2.101 0.0958 -1000 -1000 -1000 -4.5357 -0.21837 0.71114 5.2468 0.92951 0.39326 0.56081 13.5 0.022387 1.85e+11 0.000501 0.001353 -0.53655 -0.37193 0.037733 -0.3829 0.001645 -1.3884 0.53124 1.4844 0.005901 2.1 0.09556 -1000 -1000 -1000 -2.9978 1.3137 2.1627 5.1605 0.84901 0.54621 0.78563 14.5 0.028184 1.85e+11 0.001762 0.004729 -0.53784 -0.36807 0.037658 -0.38285 0.005183 -1.3119 0.51455 1.4836 0.0059 2.1 0.094215 -1000 -1000 -1000 2.4603 6.7478 7.1455 4.6852 0.39773 1.6556 2.5085 15.5 0.035481 1.85e+11 0.006721 0.01807 -0.53879 -0.36812 0.037654 -0.38278 0.015149 -1.1251 0.50306 1.4724 0.005901 2.1 0.087825 -1000 -1000 -1000 8.2741 12.57 11.804 3.5298 -0.76575 4.3644 7.8444 9.5 0.008913 1.9e+11 0.001226 0.002191 -0.58416 -0.26438 -0.086695 -0.24705 0.004164 -1.1355 0.92611 1.4841 0.005901 2.101 0.094835 -1000 -1000 -1000 0.88553 3.4057 6.1956 5.3101 2.7899 1.4126 2.0021 10.5 0.01122 1.9e+11 0.001788 0.003189 -0.58409 -0.26327 -0.086711 -0.24704 0.005859 -1.1112 0.91579 1.4837 0.0059 2.1 0.094345 -1000 -1000 -1000 2.5246 5.0369 7.6783 5.1537 2.6413 1.9677 2.8321
%Compute the min and max values by the groups of Frequency Variable
T1 = groupsummary(Pswpdata, 'Frequency', 'max')
T1 = 7×27 table
Frequency GroupCount max_Pavs_dB_set max_Pavs_set max_PinRF max_PavRF max_GinRF_real max_GinRF_imag max_GLRF_real max_GLRF_imag max_PLRF max_VectorGain_real max_VectorGain_imag max_PS1_V_base_2 max_PS1_I_base_2 max_PS2_V_col_2 max_PS2_I_col_2 max_Responsivity max_Resp_volt_on max_Resp_volt_off max_PinRF_dBm max_PavRF_dBm max_PLRF_dBm max_Gain max_GainT max_PAE max_Eff _________ __________ _______________ ____________ _________ _________ ______________ ______________ _____________ _____________ ________ ___________________ ___________________ ________________ ________________ _______________ _______________ ________________ ________________ _________________ _____________ _____________ ____________ ________ _________ _______ _______ 1.8e+11 7 15.5 0.035481 0.011099 0.032409 -0.40094 -0.51396 0.14443 -0.19034 0.023011 -1.1021 0.13808 1.4852 0.005901 2.101 0.09614 -1000 -1000 -1000 10.453 15.107 13.619 5.3515 0.69946 6.0549 11.697 1.85e+11 7 15.5 0.035481 0.006721 0.01807 -0.53329 -0.36807 0.037733 -0.38278 0.015149 -1.1251 0.5318 1.4853 0.005901 2.101 0.09601 -1000 -1000 -1000 8.2741 12.57 11.804 5.3774 1.0518 4.3644 7.8444 1.9e+11 7 15.5 0.035481 0.017723 0.032338 -0.56655 -0.2616 -0.086695 -0.24701 0.029105 -0.72841 0.92611 1.4841 0.005901 2.101 0.094835 -1000 -1000 -1000 12.485 15.097 14.64 5.3101 2.7899 6.5312 16.701 1.95e+11 7 15.5 0.035481 0.006511 0.010521 -0.62389 -0.14678 -0.10821 -0.083342 0.015288 -0.63048 1.2383 1.4846 0.005901 2.1 0.0959 -1000 -1000 -1000 8.1365 10.22 11.844 5.6265 3.5571 4.4744 7.7937 2e+11 7 15.5 0.035481 0.016449 0.029244 -0.64307 -0.000384 0.044276 -0.037411 0.028298 -0.27086 1.3764 1.4846 0.005901 2.1 0.096005 -1000 -1000 -1000 12.161 14.66 14.518 5.6244 3.1645 6.5198 15.571 2.05e+11 7 15.5 0.035481 0.007507 0.012945 -0.59975 0.1692 0.10554 -0.26111 0.018151 0.047854 1.5885 1.4849 0.005901 2.101 0.09555 -1000 -1000 -1000 8.7548 11.121 12.589 5.9261 3.4295 5.7252 9.7636 2.1e+11 7 15.5 0.035481 0.016792 0.020756 -0.49666 0.28749 0.053181 -0.33378 0.029596 0.52755 1.5455 1.4851 0.005901 2.1 0.09551 -1000 -1000 -1000 12.251 13.172 14.712 5.5379 4.5783 7.6077 17.584
T2 = groupsummary(Pswpdata, 'Frequency', 'min')
T2 = 7×27 table
Frequency GroupCount min_Pavs_dB_set min_Pavs_set min_PinRF min_PavRF min_GinRF_real min_GinRF_imag min_GLRF_real min_GLRF_imag min_PLRF min_VectorGain_real min_VectorGain_imag min_PS1_V_base_2 min_PS1_I_base_2 min_PS2_V_col_2 min_PS2_I_col_2 min_Responsivity min_Resp_volt_on min_Resp_volt_off min_PinRF_dBm min_PavRF_dBm min_PLRF_dBm min_Gain min_GainT min_PAE min_Eff _________ __________ _______________ ____________ _________ _________ ______________ ______________ _____________ _____________ ________ ___________________ ___________________ ________________ ________________ _______________ _______________ ________________ ________________ _________________ _____________ _____________ ____________ ________ _________ ________ ________ 1.8e+11 7 9.5 0.008913 1.3e-05 3.9e-05 -0.41434 -0.52629 0.14429 -0.19058 4.6e-05 -1.4266 -0.1085 1.4568 0.005901 2.1 0.08959 -1000 -1000 -1000 -18.744 -14.092 -13.392 3.1665 -1.4872 0.015417 0.021765 1.85e+11 7 9.5 0.008913 0.000122 0.000331 -0.53879 -0.37641 0.037654 -0.38291 0.000421 -1.4349 0.50306 1.4724 0.0059 2.1 0.087825 -1000 -1000 -1000 -9.13 -4.8044 -3.7526 3.5298 -0.76575 0.14225 0.20032 1.9e+11 7 9.5 0.008913 0.001226 0.002191 -0.58416 -0.2962 -0.086888 -0.24708 0.004164 -1.1355 0.71551 1.4243 0.0059 2.099 0.078945 -1000 -1000 -1000 0.88553 3.4057 6.1956 2.1543 -0.45748 1.4126 2.0021 1.95e+11 7 9.5 0.008913 0.000205 0.00033 -0.62484 -0.15382 -0.10848 -0.083585 0.000748 -0.80872 1.0033 1.4661 0.0059 2.1 0.08929 -1000 -1000 -1000 -6.8895 -4.8202 -1.263 3.707 1.6231 0.25838 0.35577 2e+11 7 9.5 0.008913 0.000148 0.000261 -0.64764 -0.032687 0.044143 -0.037638 0.000542 -0.48201 0.96494 1.4256 0.005901 2.1 0.082535 -1000 -1000 -1000 -8.286 -5.8261 -2.6616 2.3561 -0.14288 0.18703 0.25757 2.05e+11 7 9.5 0.008913 0.000462 0.000821 -0.61465 0.1636 0.10536 -0.26121 0.001809 -0.001864 1.2684 1.4714 0.005901 2.1 0.08439 -1000 -1000 -1000 -3.3522 -0.85556 2.5739 3.8341 1.468 0.64305 0.86374 2.1e+11 7 9.5 0.008913 0.000659 0.000822 -0.5073 0.26213 0.052897 -0.3339 0.002358 0.46912 1.067 1.4512 0.0059 2.1 0.07607 -1000 -1000 -1000 -1.8133 -0.85368 3.7246 2.4614 1.5409 0.81157 1.1262
%Find the indices of the variables to be added
names = Pswpdata.Properties.VariableNames;
str = {'Gain','PAE','PLRF_dBm'};
%Adding 1 to the indices as the output by groupsummary() has an extra
%column for groupcounts
idx = find(ismember(names, str)) + 1;
%Plot the corresponding values
scatter(T1,'Frequency',idx,'filled')
hold on
scatter(T2,'Frequency',idx,'filled')
legend('Location', 'Best')
title('GT,PAE & Pout (dB)')

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