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

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abhijeet joseph
abhijeet joseph il 6 Apr 2022
Modificato: Stephen23 il 6 Apr 2022
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

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Risposte (2)

Davide Masiello
Davide Masiello il 6 Apr 2022
Ran in:
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 il 6 Apr 2022
Modificato: Stephen23 il 6 Apr 2022
Ran in:
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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