clear,clc
T = readtable('gridstability.csv')
T = 10000×14 table
tau1 tau2 tau3 tau4 p1 p2 p3 p4 g1 g2 g3 g4 stab stabf
_______ ______ _______ _______ ______ ________ ________ ________ _______ _______ _______ _______ __________ ____________
2.9591 3.0799 8.381 9.7808 3.7631 -0.7826 -1.2574 -1.7231 0.65046 0.85958 0.88744 0.95803 0.055347 {'unstable'}
9.3041 4.9025 3.0475 1.3694 5.0678 -1.9401 -1.8727 -1.255 0.41344 0.86241 0.56214 0.78176 -0.0059575 {'stable' }
8.9717 8.8484 3.0465 1.2145 3.4052 -1.2075 -1.2772 -0.92049 0.16304 0.76669 0.83944 0.10985 0.0034709 {'unstable'}
0.71641 7.6696 4.4866 2.3406 3.9638 -1.0275 -1.9389 -0.99737 0.44621 0.97674 0.92938 0.36272 0.028871 {'unstable'}
3.1341 7.6088 4.9438 9.8576 3.5258 -1.1255 -1.846 -0.55431 0.79711 0.45545 0.65695 0.82092 0.04986 {'unstable'}
6.9992 9.1092 3.7841 4.2678 4.4297 -1.8571 -0.6704 -1.9021 0.26179 0.07793 0.54288 0.46993 -0.017385 {'stable' }
6.7102 3.7652 6.9293 8.8186 2.3974 -0.61459 -1.2088 -0.574 0.17789 0.39798 0.40205 0.37663 0.0059536 {'unstable'}
6.9535 1.3791 5.7194 7.8703 3.2245 -0.749 -1.1865 -1.289 0.37138 0.6332 0.73274 0.38054 0.016634 {'unstable'}
4.6899 4.0077 1.4786 3.7338 4.0413 -1.4103 -1.2382 -1.3928 0.26971 0.25036 0.16494 0.48244 -0.038677 {'stable' }
9.8415 1.4138 9.7699 7.6416 4.7276 -1.9914 -0.85764 -1.8786 0.37636 0.54442 0.79204 0.11626 0.012383 {'unstable'}
5.9301 6.7309 6.2451 0.53329 2.3271 -0.7025 -1.1169 -0.50767 0.23982 0.56311 0.16446 0.7537 -0.028411 {'stable' }
5.3813 8.0145 8.0952 6.7692 5.5076 -1.9727 -1.8493 -1.6855 0.35997 0.17357 0.34914 0.62886 0.02813 {'unstable'}
1.6168 2.9392 0.81979 4.1918 3.7523 -1.4849 -1.2806 -0.98682 0.8997 0.86655 0.30392 0.07761 -0.048617 {'stable' }
8.5516 8.315 2.55 9.9268 4.8917 -1.8086 -1.1671 -1.916 0.6124 0.28098 0.35434 0.47219 0.027756 {'unstable'}
1.1321 2.9203 8.9511 7.2486 5.0337 -1.8461 -1.3628 -1.8248 0.35229 0.52417 0.599 0.67439 0.01488 {'unstable'}
7.0214 4.3743 4.7759 8.8384 3.3359 -0.96239 -1.4076 -0.96584 0.7111 0.62536 0.46833 0.89514 0.072508 {'unstable'}
If you are ok with T.stabf being populated by true/false values, you can use.
T.stabf = strcmp(T.stabf,{'stable'});
T
T = 10000×14 table
tau1 tau2 tau3 tau4 p1 p2 p3 p4 g1 g2 g3 g4 stab stabf
_______ ______ _______ _______ ______ ________ ________ ________ _______ _______ _______ _______ __________ _____
2.9591 3.0799 8.381 9.7808 3.7631 -0.7826 -1.2574 -1.7231 0.65046 0.85958 0.88744 0.95803 0.055347 false
9.3041 4.9025 3.0475 1.3694 5.0678 -1.9401 -1.8727 -1.255 0.41344 0.86241 0.56214 0.78176 -0.0059575 true
8.9717 8.8484 3.0465 1.2145 3.4052 -1.2075 -1.2772 -0.92049 0.16304 0.76669 0.83944 0.10985 0.0034709 false
0.71641 7.6696 4.4866 2.3406 3.9638 -1.0275 -1.9389 -0.99737 0.44621 0.97674 0.92938 0.36272 0.028871 false
3.1341 7.6088 4.9438 9.8576 3.5258 -1.1255 -1.846 -0.55431 0.79711 0.45545 0.65695 0.82092 0.04986 false
6.9992 9.1092 3.7841 4.2678 4.4297 -1.8571 -0.6704 -1.9021 0.26179 0.07793 0.54288 0.46993 -0.017385 true
6.7102 3.7652 6.9293 8.8186 2.3974 -0.61459 -1.2088 -0.574 0.17789 0.39798 0.40205 0.37663 0.0059536 false
6.9535 1.3791 5.7194 7.8703 3.2245 -0.749 -1.1865 -1.289 0.37138 0.6332 0.73274 0.38054 0.016634 false
4.6899 4.0077 1.4786 3.7338 4.0413 -1.4103 -1.2382 -1.3928 0.26971 0.25036 0.16494 0.48244 -0.038677 true
9.8415 1.4138 9.7699 7.6416 4.7276 -1.9914 -0.85764 -1.8786 0.37636 0.54442 0.79204 0.11626 0.012383 false
5.9301 6.7309 6.2451 0.53329 2.3271 -0.7025 -1.1169 -0.50767 0.23982 0.56311 0.16446 0.7537 -0.028411 true
5.3813 8.0145 8.0952 6.7692 5.5076 -1.9727 -1.8493 -1.6855 0.35997 0.17357 0.34914 0.62886 0.02813 false
1.6168 2.9392 0.81979 4.1918 3.7523 -1.4849 -1.2806 -0.98682 0.8997 0.86655 0.30392 0.07761 -0.048617 true
8.5516 8.315 2.55 9.9268 4.8917 -1.8086 -1.1671 -1.916 0.6124 0.28098 0.35434 0.47219 0.027756 false
1.1321 2.9203 8.9511 7.2486 5.0337 -1.8461 -1.3628 -1.8248 0.35229 0.52417 0.599 0.67439 0.01488 false
7.0214 4.3743 4.7759 8.8384 3.3359 -0.96239 -1.4076 -0.96584 0.7111 0.62536 0.46833 0.89514 0.072508 false
However, if you want 0s and 1s strictly, you can use
clear,clc
T = readtable('gridstability.csv')
T = 10000×14 table
tau1 tau2 tau3 tau4 p1 p2 p3 p4 g1 g2 g3 g4 stab stabf
_______ ______ _______ _______ ______ ________ ________ ________ _______ _______ _______ _______ __________ ____________
2.9591 3.0799 8.381 9.7808 3.7631 -0.7826 -1.2574 -1.7231 0.65046 0.85958 0.88744 0.95803 0.055347 {'unstable'}
9.3041 4.9025 3.0475 1.3694 5.0678 -1.9401 -1.8727 -1.255 0.41344 0.86241 0.56214 0.78176 -0.0059575 {'stable' }
8.9717 8.8484 3.0465 1.2145 3.4052 -1.2075 -1.2772 -0.92049 0.16304 0.76669 0.83944 0.10985 0.0034709 {'unstable'}
0.71641 7.6696 4.4866 2.3406 3.9638 -1.0275 -1.9389 -0.99737 0.44621 0.97674 0.92938 0.36272 0.028871 {'unstable'}
3.1341 7.6088 4.9438 9.8576 3.5258 -1.1255 -1.846 -0.55431 0.79711 0.45545 0.65695 0.82092 0.04986 {'unstable'}
6.9992 9.1092 3.7841 4.2678 4.4297 -1.8571 -0.6704 -1.9021 0.26179 0.07793 0.54288 0.46993 -0.017385 {'stable' }
6.7102 3.7652 6.9293 8.8186 2.3974 -0.61459 -1.2088 -0.574 0.17789 0.39798 0.40205 0.37663 0.0059536 {'unstable'}
6.9535 1.3791 5.7194 7.8703 3.2245 -0.749 -1.1865 -1.289 0.37138 0.6332 0.73274 0.38054 0.016634 {'unstable'}
4.6899 4.0077 1.4786 3.7338 4.0413 -1.4103 -1.2382 -1.3928 0.26971 0.25036 0.16494 0.48244 -0.038677 {'stable' }
9.8415 1.4138 9.7699 7.6416 4.7276 -1.9914 -0.85764 -1.8786 0.37636 0.54442 0.79204 0.11626 0.012383 {'unstable'}
5.9301 6.7309 6.2451 0.53329 2.3271 -0.7025 -1.1169 -0.50767 0.23982 0.56311 0.16446 0.7537 -0.028411 {'stable' }
5.3813 8.0145 8.0952 6.7692 5.5076 -1.9727 -1.8493 -1.6855 0.35997 0.17357 0.34914 0.62886 0.02813 {'unstable'}
1.6168 2.9392 0.81979 4.1918 3.7523 -1.4849 -1.2806 -0.98682 0.8997 0.86655 0.30392 0.07761 -0.048617 {'stable' }
8.5516 8.315 2.55 9.9268 4.8917 -1.8086 -1.1671 -1.916 0.6124 0.28098 0.35434 0.47219 0.027756 {'unstable'}
1.1321 2.9203 8.9511 7.2486 5.0337 -1.8461 -1.3628 -1.8248 0.35229 0.52417 0.599 0.67439 0.01488 {'unstable'}
7.0214 4.3743 4.7759 8.8384 3.3359 -0.96239 -1.4076 -0.96584 0.7111 0.62536 0.46833 0.89514 0.072508 {'unstable'}
T.stabf = double(strcmp(T.stabf,{'stable'}));
T
T = 10000×14 table
tau1 tau2 tau3 tau4 p1 p2 p3 p4 g1 g2 g3 g4 stab stabf
_______ ______ _______ _______ ______ ________ ________ ________ _______ _______ _______ _______ __________ _____
2.9591 3.0799 8.381 9.7808 3.7631 -0.7826 -1.2574 -1.7231 0.65046 0.85958 0.88744 0.95803 0.055347 0
9.3041 4.9025 3.0475 1.3694 5.0678 -1.9401 -1.8727 -1.255 0.41344 0.86241 0.56214 0.78176 -0.0059575 1
8.9717 8.8484 3.0465 1.2145 3.4052 -1.2075 -1.2772 -0.92049 0.16304 0.76669 0.83944 0.10985 0.0034709 0
0.71641 7.6696 4.4866 2.3406 3.9638 -1.0275 -1.9389 -0.99737 0.44621 0.97674 0.92938 0.36272 0.028871 0
3.1341 7.6088 4.9438 9.8576 3.5258 -1.1255 -1.846 -0.55431 0.79711 0.45545 0.65695 0.82092 0.04986 0
6.9992 9.1092 3.7841 4.2678 4.4297 -1.8571 -0.6704 -1.9021 0.26179 0.07793 0.54288 0.46993 -0.017385 1
6.7102 3.7652 6.9293 8.8186 2.3974 -0.61459 -1.2088 -0.574 0.17789 0.39798 0.40205 0.37663 0.0059536 0
6.9535 1.3791 5.7194 7.8703 3.2245 -0.749 -1.1865 -1.289 0.37138 0.6332 0.73274 0.38054 0.016634 0
4.6899 4.0077 1.4786 3.7338 4.0413 -1.4103 -1.2382 -1.3928 0.26971 0.25036 0.16494 0.48244 -0.038677 1
9.8415 1.4138 9.7699 7.6416 4.7276 -1.9914 -0.85764 -1.8786 0.37636 0.54442 0.79204 0.11626 0.012383 0
5.9301 6.7309 6.2451 0.53329 2.3271 -0.7025 -1.1169 -0.50767 0.23982 0.56311 0.16446 0.7537 -0.028411 1
5.3813 8.0145 8.0952 6.7692 5.5076 -1.9727 -1.8493 -1.6855 0.35997 0.17357 0.34914 0.62886 0.02813 0
1.6168 2.9392 0.81979 4.1918 3.7523 -1.4849 -1.2806 -0.98682 0.8997 0.86655 0.30392 0.07761 -0.048617 1
8.5516 8.315 2.55 9.9268 4.8917 -1.8086 -1.1671 -1.916 0.6124 0.28098 0.35434 0.47219 0.027756 0
1.1321 2.9203 8.9511 7.2486 5.0337 -1.8461 -1.3628 -1.8248 0.35229 0.52417 0.599 0.67439 0.01488 0
7.0214 4.3743 4.7759 8.8384 3.3359 -0.96239 -1.4076 -0.96584 0.7111 0.62536 0.46833 0.89514 0.072508 0
The code above outputs a logical 1 (true) if the row is 'stable' and a logical 0 (false) is the row is 'unstable'.
For the opposite result, just insert a ~ before the strcmp command.
