how to read a table and multiply its elements with eachother and store it in another table

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i have a table of dimension 152*3, I want to multiply all the elments in row 1 ie: row (1,1)*(1,2)*(1,3) and store its value in another table.
this should be done for each rows untill the last and each values should be stored and viewed in another table

Respuestas (2)

Davide Masiello
Davide Masiello el 6 de Abr. de 2022
Example
%% Creating an example table
T = array2table(rand(152,3));
T.Properties.VariableNames = {'A','B','C'};
disp(T)
A B C ________ _________ _________ 0.42378 0.13393 0.22799 0.082036 0.41103 0.47176 0.75376 0.92698 0.35121 0.76344 0.59448 0.15683 0.6067 0.82957 0.65986 0.13342 0.45348 0.40703 0.6811 0.064675 0.4763 0.39749 0.42151 0.49343 0.25655 0.85027 0.75015 0.2818 0.17302 0.22054 0.43358 0.30905 0.094299 0.067233 0.42883 0.31584 0.59127 0.47814 0.64779 0.21798 0.21966 0.81706 0.24648 0.16125 0.71757 0.47834 0.8578 0.90381 0.33964 0.32478 0.6592 0.58716 0.72589 0.63555 0.2079 0.94555 0.11394 0.23356 0.47505 0.62317 0.38324 0.63074 0.96923 0.029543 0.50752 0.66974 0.47596 0.68114 0.10123 0.51391 0.64901 0.5895 0.62073 0.12588 0.42946 0.14064 0.8107 0.55923 0.55861 0.20972 0.026246 0.88244 0.85151 0.67231 0.24386 0.0091537 0.81313 0.24565 0.40811 0.17537 0.82064 0.70851 0.028089 0.13386 0.50029 0.7247 0.023885 0.67824 0.11584 0.049607 0.67578 0.90859 0.67972 0.53723 0.87945 0.70288 0.24487 0.54332 0.10835 0.11454 0.03875 0.586 0.8897 0.48103 0.19033 0.28499 0.43309 0.16974 0.84623 0.8983 0.25022 0.38247 0.49594 0.14369 0.81799 0.49193 0.017027 0.25476 0.9341 0.69411 0.73299 0.91914 0.63633 0.47565 0.94537 0.26791 0.21803 0.67819 0.59145 0.45666 0.23451 0.89969 0.23141 0.91394 0.30595 0.79774 0.54422 0.82913 0.20912 0.3579 0.56273 0.080806 0.60201 0.56198 0.2252 0.013156 0.98202 0.21236 0.67949 0.30891 0.78289 0.93988 0.92229 0.92271 0.84322 0.96672 0.47785 0.45762 0.84022 0.10221 0.68097 0.030949 0.76589 0.77341 0.85085 0.49493 0.91834 0.67863 0.26774 0.45319 0.91824 0.38266 0.58674 0.11981 0.34745 0.3926 0.45039 0.2838 0.065324 0.77591 0.67981 0.37745 0.96183 0.76159 0.98151 0.093357 0.079286 0.80662 0.010607 0.79386 0.62656 0.85305 0.74432 0.57746 0.28166 0.29303 0.31683 0.06148 0.55658 0.52646 0.20803 0.39411 0.26235 0.37679 0.16947 0.16664 0.40762 0.69195 0.94204 0.86755 0.62125 0.15093 0.6197 0.84974 0.67479 0.15956 0.1419 0.069695 0.94574 0.14687 0.3861 0.010654 0.41531 0.95663 0.090716 0.01221 0.38156 0.38419 0.40451 0.96042 0.034027 0.36074 0.36304 0.7896 0.31645 0.44171 0.95109 0.036508 0.011216 0.68574 0.89948 0.24477 0.81051 0.44184 0.06977 0.21326 0.98712 0.89869 0.47508 0.66351 0.025417 0.50793 0.35838 0.21829 0.63055 0.80763 0.81413 0.91354 0.96246 0.28164 0.81592 0.48461 0.45038 0.72469 0.94251 0.36319 0.89172 0.096547 0.72459 0.46539 0.33833 0.85381 0.25951 0.21369 0.10845 0.74297 0.96254 0.48982 0.12529 0.88964 0.55652 0.45328 0.59957 0.49526 0.25019 0.37341 0.85707 0.80745 0.56399 0.17451 0.57691 0.72659 0.40315 0.68526 0.70135 0.69743 0.71913 0.94173 0.8324 0.57787 0.26485 0.12257 0.11568 0.28255 0.86964 0.50212 0.37506 0.0041642 0.67394 0.2847 0.67101 0.81317 0.12404 0.33385 0.5364 0.74537 0.60136 0.11061 0.72833 0.46459 0.10321 0.43555 0.90648 0.93456 0.82242 0.51391 0.65652 0.030484 0.69796 0.80008 0.633 0.13769 0.027733 0.32003 0.96669 0.48346 0.80731 0.47872 0.42179 0.12564 0.92077 0.69997 0.43716 0.06826 0.62567 0.78622 0.58397 0.55886 0.9579 0.91042 0.23519 0.15555 0.014037 0.97677 0.57281 0.83796 0.84611 0.68231 0.99345 0.2854 0.67092 0.68178 0.28414 0.15534 0.52458 0.67874 0.4807 0.87333 0.47587 0.044565 0.7615 0.15419 0.46918 0.54308 0.49933 0.91122 0.31492 0.44477 0.34637 0.26137 0.19595 0.69232 0.92582 0.58582 0.12117 0.39024 0.71311 0.65721 0.85462 0.09565 0.61922 0.51532 0.96703 0.22528 0.19192 0.21275 0.029376 0.2551 0.031148 0.75886 0.52969 0.82803 0.65453 0.21013 0.70479 0.11133 0.89817 0.029264 0.18215 0.0044201 0.81203 0.059566 0.23815 0.52536 0.81921 0.47153 0.73952 0.93181 0.079821 0.52958 0.96271 0.5986 0.95124 0.86234 0.71223 0.81267 0.57192 0.77478 0.17716 0.61609 0.028296 0.040548 0.41582 0.72524 0.24942 0.58864 0.59282 0.44106 0.32027 0.59054 0.44587 0.019645 0.87156 0.14007 0.56612 0.91016
%% New table with product
T_prod = array2table(prod(T{:,:},2));
T_prod.Properties.VariableNames = {'product'};
disp(T_prod)
product __________ 0.01294 0.015907 0.2454 0.071177 0.33211 0.024626 0.020981 0.082671 0.16364 0.010752 0.012636 0.009106 0.18314 0.039121 0.02852 0.37086 0.072715 0.27088 0.022398 0.069143 0.23429 0.010042 0.032819 0.19662 0.033556 0.063763 0.0030748 0.50518 0.0018151 0.017581 0.016332 0.048534 0.0018765 0.030459 0.32114 0.093513 0.0004809 0.25079 0.023492 0.12903 0.047463 0.057822 0.0040519 0.46764 0.28614 0.039614 0.06334 0.19028 0.13283 0.062056 0.027375 0.001665 0.1417 0.2273 0.71759 0.2114 0.058478 0.018333 0.38672 0.082344 0.20617 0.016344 0.0083496 0.1991 0.71898 0.0059705 0.0052759 0.36666 0.026149 0.018014 0.021509 0.01064 0.26571 0.081347 0.35534 0.0015781 0.053631 0.0042328 0.00042264 0.14926 0.0044563 0.11037 0.00038943 0.15097 0.024986 0.18919 0.008012 0.039736 0.4146 0.24763 0.17808 0.24807 0.062382 0.13444 0.0060139 0.35029 0.062029 0.1346 0.080069 0.079471 0.16899 0.33519 0.56372 0.018759 0.028423 0.00078423 0.12875 0.033675 0.24044 0.037429 0.04075 0.39499 0.013969 0.069735 0.0085799 0.18685 0.048794 0.020887 0.28726 0.48737 0.00051353 0.46884 0.57352 0.13055 0.023154 0.28494 0.016149 0.039289 0.14329 0.040264 0.1256 0.027701 0.40053 0.030522 0.041811 0.0015943 0.01252 0.11389 0.070475 2.3562e-05 0.011519 0.20294 0.055004 0.30519 0.58424 0.36011 0.0030884 0.012228 0.087039 0.083421 0.0076343 0.072172

Stephen23
Stephen23 el 6 de Abr. de 2022
Editada: Stephen23 el 6 de Abr. de 2022
If all you need are numeric operations across all columns then storing the data in one numeric matrix would make your task much easier and more efficient. But if you must use a table:
T = array2table(rand(152,3), 'VariableNames',{'A','B','C'})
T = 152×3 table
A B C ________ _________ ________ 0.54535 0.98312 0.43502 0.58908 0.0013448 0.016707 0.21073 0.047291 0.45771 0.88526 0.26006 0.45427 0.23476 0.82321 0.67366 0.85761 0.96404 0.5221 0.41686 0.18252 0.96219 0.334 0.84439 0.44205 0.4472 0.78245 0.59439 0.034742 0.69014 0.75689 0.56919 0.90472 0.40937 0.97928 0.78709 0.84837 0.63946 0.40587 0.32266 0.96012 0.37461 0.27548 0.86979 0.64672 0.70659 0.73997 0.85677 0.45199
F = @(varargin)prod([varargin{:}]);
Z = rowfun(F,T)
Z = 152×1 table
Var1 __________ 0.23323 1.3235e-05 0.0045614 0.10458 0.13019 0.43166 0.073207 0.12467 0.20798 0.018148 0.21081 0.65391 0.083741 0.099082 0.39747 0.28656

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