Extract a column from cell array containing arrays

Hi everyone,

I'm stuck with this problem: I have a cell array 400x30 and every cell contains an array 1x3. I want to extract the first element of each array of the first column. I want to plot them, so I guess I need to put them in a separate array.

I searched similar questions in the forum, but, even if I "mixed" the answers, I couldn't solve my problem.

Could someone help me?

Thank you in advance :)

Chiara

Answer 1

[Voss]

% 400x30 cell of 1x3 random vectors:
C = reshape(num2cell(rand(400*30,3),2),400,[])

C = 400×30 cell array
    {[0.4837 0.5479 0.9608]}    {[0.8740 0.3447 0.0894]}    {[0.1324 0.1130 0.9205]}    {[0.6612 0.6216 0.5873]}    {[0.4619 0.8044 0.3733]}    {[0.7118 0.5678 0.3860]}    {[0.2325 0.9970 0.5401]}    {[0.0200 0.3322 0.0542]}    {[0.4560 0.2895 0.6130]}    {[0.1519 0.4753 0.5754]}    {[0.8171 0.4048 0.4573]}    {[0.7354 0.5425 0.5611]}    {[0.3328 0.0975 0.9783]}    {[0.8574 0.3883 0.5081]}    {[0.8225 0.3406 0.8372]}    {[0.7205 0.7736 0.3347]}    {[0.0384 0.6472 0.9744]}    {[0.9788 0.7953 0.0246]}    {[0.9149 0.5762 0.6241]}    {[0.2323 0.3532 0.7466]}    {[0.2986 0.4747 0.5098]}    {[0.8800 0.5503 0.5935]}    {[0.0667 0.2037 0.2614]}    {[0.6787 0.1557 0.9346]}    {[0.1189 0.9244 0.7989]}    {[0.1945 0.9929 0.5621]}    {[0.7551 0.7505 0.1591]}    {[0.6601 0.0280 0.2409]}    {[0.0305 0.0797 0.5151]}    {[0.2559 0.6368 0.8397]}
    {[0.8256 0.7417 0.3556]}    {[0.4592 0.0586 0.1227]}    {[0.7049 0.5271 0.5945]}    {[0.4509 0.5334 0.6379]}    {[0.0687 0.2351 0.7441]}    {[0.7839 0.9819 0.1167]}    {[0.7122 0.3132 0.5442]}    {[0.7732 0.0697 0.0487]}    {[0.5106 0.4487 0.6065]}    {[0.3814 0.9769 0.0647]}    {[0.8269 0.7156 0.0518]}    {[0.4651 0.3978 0.6046]}    {[0.7178 0.0011 0.7014]}    {[0.0601 0.9732 0.8102]}    {[0.1606 0.5377 0.2816]}    {[0.8022 0.8079 0.0159]}    {[0.3695 0.1328 0.1443]}    {[0.4676 0.0508 0.5727]}    {[0.5443 0.7566 0.8503]}    {[0.0107 0.5040 0.8610]}    {[0.4242 0.9383 0.1115]}    {[0.0932 0.0828 0.9369]}    {[0.2591 0.1187 0.6178]}    {[0.0037 0.5793 0.0924]}    {[0.4344 0.0524 0.6553]}    {[0.8503 0.4326 0.8567]}    {[0.6300 0.1720 0.8717]}    {[0.7369 0.1118 0.2215]}    {[0.9386 0.2284 0.8319]}    {[0.8376 0.6891 0.6920]}
    {[0.5549 0.6056 0.4723]}    {[0.4091 0.4082 0.9107]}    {[0.0982 0.4066 0.0968]}    {[0.7266 0.5788 0.4095]}    {[0.8680 0.5753 0.0486]}    {[0.0748 0.2115 0.6639]}    {[0.5388 0.4559 0.9605]}    {[0.3071 0.2882 0.3278]}    {[0.8893 0.0140 0.7049]}    {[0.1695 0.8868 0.8048]}    {[0.3605 0.4364 0.7673]}    {[0.6311 0.6105 0.9153]}    {[0.7511 0.5228 0.6202]}    {[0.4553 0.1675 0.4947]}    {[0.8662 0.7652 0.1532]}    {[0.1720 0.3699 0.1499]}    {[0.4470 0.2022 0.3646]}    {[0.7851 0.9267 0.5186]}    {[0.4080 0.6358 0.0468]}    {[0.4649 0.4538 0.6045]}    {[0.6417 0.5620 0.1627]}    {[0.4702 0.0695 0.8553]}    {[0.9411 0.2386 0.1096]}    {[0.0912 0.7837 0.3938]}    {[0.5545 0.5201 0.4134]}    {[0.3380 0.2118 0.4203]}    {[0.1652 0.6318 0.0331]}    {[0.2722 0.3190 0.6849]}    {[0.5397 0.6789 0.1104]}    {[0.5722 0.9089 0.5851]}
    {[0.0788 0.8490 0.9890]}    {[0.3883 0.8900 0.7185]}    {[0.3312 0.8645 0.0857]}    {[0.6314 0.8286 0.2238]}    {[0.8679 0.7740 0.7044]}    {[0.9967 0.1816 0.0508]}    {[0.9261 0.5401 0.9620]}    {[0.5456 0.8579 0.8158]}    {[0.1639 0.0836 0.0100]}    {[0.2139 0.8480 0.6319]}    {[0.0530 0.5922 0.0564]}    {[0.5565 0.2253 0.8306]}    {[0.3360 0.5843 0.8877]}    {[0.5524 0.4638 0.4107]}    {[0.8465 0.6650 0.6172]}    {[0.7286 0.2835 0.5075]}    {[0.4273 0.1658 0.6900]}    {[0.2620 0.5132 0.7666]}    {[0.8590 0.8026 0.6721]}    {[0.4911 0.7929 0.8805]}    {[0.9668 0.7417 0.9387]}    {[0.1840 0.0479 0.3634]}    {[0.5850 0.8498 0.9513]}    {[0.1206 0.1088 0.8556]}    {[0.5714 0.3601 0.5031]}    {[0.6423 0.1588 0.3492]}    {[0.9187 0.9525 0.3367]}    {[0.4693 0.2796 0.9464]}    {[0.9607 0.3978 0.2565]}    {[0.3223 0.1618 0.9614]}
    {[0.4740 0.6440 0.9835]}    {[0.7031 0.3909 0.4786]}    {[0.0956 0.4327 0.5267]}    {[0.7025 0.5465 0.4054]}    {[0.2697 0.8395 0.5352]}    {[0.6983 0.6648 0.6360]}    {[0.4640 0.0288 0.7687]}    {[0.7186 0.2388 0.5413]}    {[0.9529 0.4493 0.3741]}    {[0.1031 0.9649 0.9418]}    {[0.9618 0.5125 0.1941]}    {[0.5651 0.4094 0.4267]}    {[0.0930 0.6638 0.8684]}    {[0.8350 0.1093 0.0787]}    {[0.2929 0.1909 0.5675]}    {[0.0082 0.5910 0.5860]}    {[0.8387 0.8104 0.6301]}    {[0.2495 0.0242 0.8045]}    {[0.7764 0.6953 0.5042]}    {[0.0752 0.5737 0.8014]}    {[0.3261 0.5973 0.3594]}    {[0.6248 0.5492 0.5841]}    {[0.9437 0.9742 0.8127]}    {[0.5454 0.4878 0.5969]}    {[0.9168 0.5589 0.8724]}    {[0.2736 0.4871 0.7337]}    {[0.4397 0.7899 0.6821]}    {[0.7255 0.9487 0.0774]}    {[0.8021 0.7963 0.4184]}    {[0.4656 0.1897 0.0508]}
    {[0.5338 0.0416 0.0283]}    {[0.7526 0.9254 0.7262]}    {[0.5498 0.1496 0.3798]}    {[0.4832 0.4456 0.3445]}    {[0.8979 0.8813 0.9888]}    {[0.8777 0.6003 0.7246]}    {[0.0600 0.6236 0.8887]}    {[0.7067 0.4441 0.4416]}    {[0.0356 0.0168 0.3908]}    {[0.8490 0.4467 0.6501]}    {[0.9712 0.0299 0.8119]}    {[0.0492 0.6419 0.4851]}    {[0.2202 0.6323 0.1903]}    {[0.3548 0.7279 0.4414]}    {[0.0882 0.1935 0.3455]}    {[0.4211 0.9720 0.7946]}    {[0.2338 0.9278 0.5619]}    {[0.2085 0.1994 0.2749]}    {[0.4386 0.9431 0.3582]}    {[0.6316 0.2090 0.2844]}    {[0.9799 0.0388 0.3862]}    {[0.9853 0.1409 0.7635]}    {[0.5281 0.1044 0.7337]}    {[0.2062 0.0378 0.7371]}    {[0.5461 0.0990 0.5748]}    {[0.3105 0.7954 0.0301]}    {[0.2766 0.7251 0.3443]}    {[0.3531 0.1930 0.8259]}    {[0.6678 0.8389 0.0738]}    {[0.9592 0.6472 0.1813]}
    {[0.6690 0.8798 0.8903]}    {[0.4193 0.0258 0.6367]}    {[0.5614 0.2985 0.4244]}    {[0.0265 0.6818 0.0335]}    {[0.2019 0.3967 0.6564]}    {[0.6552 0.0672 0.7762]}    {[0.3658 0.7051 0.1965]}    {[0.4005 0.3529 0.2174]}    {[0.7309 0.0466 0.8950]}    {[0.8173 0.5911 0.2147]}    {[0.8237 0.1622 0.6896]}    {[0.1971 0.3567 0.4296]}    {[0.4563 0.1769 0.4636]}    {[0.3923 0.9724 0.2320]}    {[0.4221 0.5069 0.8784]}    {[0.4862 0.5784 0.2201]}    {[0.6172 0.3137 0.8019]}    {[0.5014 0.5803 0.2544]}    {[0.1152 0.9983 0.8778]}    {[0.8745 0.2788 0.4817]}    {[0.2982 0.4889 0.7505]}    {[0.1953 0.5256 0.4659]}    {[0.8233 0.2660 0.2332]}    {[0.2180 0.2077 0.1297]}    {[0.5983 0.2302 0.1526]}    {[0.2572 0.5000 0.5916]}    {[0.0465 0.7738 0.9477]}    {[0.8519 0.2656 0.0131]}    {[0.1423 0.5800 0.4158]}    {[0.4876 0.5546 0.3007]}
    {[0.8101 0.0701 0.7111]}    {[0.7243 0.9519 0.6616]}    {[0.5799 0.4368 0.1521]}    {[0.4406 0.8420 0.4003]}    {[0.4264 0.4425 0.3172]}    {[0.0973 0.0075 0.7492]}    {[0.6620 0.6270 0.3439]}    {[0.4242 0.2267 0.5790]}    {[0.9587 0.3707 0.5244]}    {[0.7218 0.0968 0.5104]}    {[0.3534 0.4064 0.8220]}    {[0.2709 0.3663 0.2996]}    {[0.1132 0.7857 0.7159]}    {[0.7253 0.1151 0.8383]}    {[0.2636 0.4311 0.5587]}    {[0.1935 0.2722 0.9825]}    {[0.2115 0.9707 0.8707]}    {[0.2095 0.0252 0.3365]}    {[0.0884 0.3246 0.5988]}    {[0.3745 0.0970 0.8368]}    {[0.8799 0.6103 0.4158]}    {[0.1194 0.3970 0.6666]}    {[0.6464 0.2854 0.5060]}    {[0.5217 0.1256 0.2598]}    {[0.4975 0.4014 0.3960]}    {[0.0436 0.2074 0.7811]}    {[0.0452 0.2247 0.0204]}    {[0.4353 0.2068 0.1280]}    {[0.4962 0.1291 0.7826]}    {[0.0980 0.4691 0.1509]}
    {[0.3931 0.2147 0.1128]}    {[0.7120 0.4916 0.6489]}    {[0.9851 0.3103 0.6628]}    {[0.0779 0.7665 0.8331]}    {[0.6079 0.9996 0.9521]}    {[0.7469 0.4178 0.3185]}    {[0.6458 0.2222 0.3456]}    {[0.0630 0.1153 0.8999]}    {[0.0923 0.5957 0.4600]}    {[0.1773 0.2163 0.0341]}    {[0.1143 0.8725 0.5213]}    {[0.3538 0.3945 0.0099]}    {[0.9882 0.3244 0.9005]}    {[0.1814 0.5831 0.6543]}    {[0.3046 0.3577 0.9629]}    {[0.0837 0.1988 0.2158]}    {[0.6012 0.6122 0.8180]}    {[0.2084 0.6530 0.1329]}    {[0.4567 0.7998 0.6229]}    {[0.5604 0.9585 0.7885]}    {[0.1455 0.1571 0.7825]}    {[0.8098 0.1124 0.6113]}    {[0.4093 0.5224 0.8824]}    {[0.8472 0.7005 0.4896]}    {[0.3292 0.3714 0.2693]}    {[0.3222 0.8306 0.9240]}    {[0.9638 0.9011 0.9955]}    {[0.3620 0.4603 0.0667]}    {[0.9914 0.7352 0.9483]}    {[0.4044 0.2173 0.2306]}
    {[0.8212 0.9734 0.8406]}    {[0.6847 0.9813 0.7140]}    {[0.6415 0.5442 0.4869]}    {[0.6561 0.1982 0.6754]}    {[0.4268 0.6907 0.4854]}    {[0.9211 0.0253 0.3084]}    {[0.8204 0.7730 0.9064]}    {[0.7044 0.4361 0.4741]}    {[0.1864 0.4088 0.3198]}    {[0.8216 0.6609 0.6419]}    {[0.8203 0.6612 0.3059]}    {[0.4255 0.9754 0.7308]}    {[0.4428 0.8753 0.0076]}    {[0.7608 0.6652 0.1454]}    {[0.8108 0.9637 0.3491]}    {[0.7484 0.9944 0.6001]}    {[0.9059 0.3448 0.8140]}    {[0.0598 0.5770 0.5844]}    {[0.5630 0.8726 0.5904]}    {[0.3571 0.1817 0.9957]}    {[0.3091 0.8961 0.1120]}    {[0.5101 0.0435 0.9886]}    {[0.9889 0.6029 0.3432]}    {[0.1225 0.9766 0.0210]}    {[0.3239 0.5744 0.5497]}    {[0.0960 0.1308 0.9475]}    {[0.2005 0.2901 0.9302]}    {[0.0221 0.7462 0.7434]}    {[0.4858 0.1259 0.0204]}    {[0.9786 0.9287 0.2042]}
    {[0.1986 0.3884 0.4858]}    {[0.4537 0.5463 0.2020]}    {[0.8516 0.6805 0.1092]}    {[0.9572 0.4085 0.3926]}    {[0.7015 0.5496 0.8890]}    {[0.6601 0.0059 0.3466]}    {[0.1305 0.6630 0.1181]}    {[0.8895 0.0456 0.6786]}    {[0.7027 0.2057 0.9645]}    {[0.3474 0.2080 0.3558]}    {[0.0131 0.6426 0.3651]}    {[0.8334 0.9675 0.2596]}    {[0.4112 0.6319 0.1716]}    {[0.0038 0.8288 0.7512]}    {[0.3765 0.3935 0.1513]}    {[0.2513 0.2035 0.8882]}    {[0.7309 0.4445 0.0941]}    {[0.1130 0.9256 0.7420]}    {[0.6368 0.4931 0.2441]}    {[0.8460 0.2288 0.7460]}    {[0.2058 0.5896 0.8834]}    {[0.8899 0.3923 0.8843]}    {[0.2560 0.6733 0.8569]}    {[0.0671 0.7443 0.0739]}    {[0.8395 0.8269 0.9167]}    {[0.5567 0.2281 0.8641]}    {[0.7965 0.8122 0.7714]}    {[0.2042 0.3360 0.6522]}    {[0.5757 0.7484 0.9566]}    {[0.3920 0.9251 0.4901]}
    {[0.5529 0.5231 0.0089]}    {[0.7994 0.3670 0.3805]}    {[0.9418 0.0345 0.1675]}    {[0.5233 0.4372 0.0052]}    {[0.9316 0.3693 0.9184]}    {[0.8014 0.8803 0.7272]}    {[0.0718 0.0970 0.5921]}    {[0.9470 0.4953 0.9295]}    {[0.0674 0.0263 0.9055]}    {[0.4809 0.4394 0.0436]}    {[0.2569 0.5318 0.9830]}    {[0.0121 0.1660 0.5878]}    {[0.6232 0.8621 0.5788]}    {[0.5535 0.5102 0.9460]}    {[0.2813 0.5256 0.5672]}    {[0.2838 0.2537 0.7169]}    {[0.9680 0.3056 0.9790]}    {[0.2860 0.2832 0.5920]}    {[0.3797 0.2000 0.4297]}    {[0.3824 0.7988 0.0196]}    {[0.5667 0.4902 0.4913]}    {[0.3077 0.6865 0.4992]}    {[0.0929 0.4744 0.6410]}    {[0.4974 0.5873 0.6082]}    {[0.3050 0.8002 0.4510]}    {[0.4656 0.4765 0.9013]}    {[0.6435 0.0826 0.5162]}    {[0.2834 0.2166 0.2668]}    {[0.5962 0.2145 0.2874]}    {[0.8063 0.7309 0.7852]}
    {[0.2528 0.9893 0.5299]}    {[0.5508 0.1951 0.3311]}    {[0.3670 0.9143 0.1113]}    {[0.2537 0.6860 0.0323]}    {[0.3383 0.9572 0.7438]}    {[0.4558 0.7856 0.1936]}    {[0.9615 0.3546 0.5148]}    {[0.8848 0.2885 0.2265]}    {[0.1947 0.5325 0.8871]}    {[0.0237 0.1796 0.3493]}    {[0.6263 0.1123 0.9287]}    {[0.3426 0.3882 0.1770]}    {[0.9710 0.8175 0.4111]}    {[0.4685 0.4824 0.6810]}    {[0.6004 0.0326 0.1220]}    {[0.7025 0.4850 0.8902]}    {[0.2984 0.8840 0.8529]}    {[0.7517 0.1536 0.8892]}    {[0.6687 0.3569 0.9948]}    {[0.0887 0.5132 0.3273]}    {[0.5850 0.8437 0.2936]}    {[0.8004 0.4721 0.3655]}    {[0.2698 0.4545 0.3635]}    {[0.1249 0.1287 0.8256]}    {[0.7919 0.0864 0.9448]}    {[0.5224 0.9139 0.7971]}    {[0.8930 0.9211 0.4165]}    {[0.2960 0.8731 0.0686]}    {[0.5109 0.1940 0.9486]}    {[0.2114 0.7756 0.2927]}
    {[0.9292 0.7464 0.9849]}    {[0.7373 0.3576 0.0823]}    {[0.8953 0.1333 0.8866]}    {[0.2273 0.7162 0.6679]}    {[0.3011 0.9334 0.8106]}    {[0.9188 0.1131 0.0673]}    {[0.6429 0.4821 0.5120]}    {[0.2072 0.3749 0.5819]}    {[0.3450 0.3783 0.9527]}    {[0.0296 0.6055 0.7094]}    {[0.1990 0.4302 0.1943]}    {[0.1467 0.4498 0.2049]}    {[0.5036 0.0508 0.9752]}    {[0.1671 0.4104 0.5694]}    {[0.5888 0.4415 0.7965]}    {[0.6223 0.5846 0.5447]}    {[0.8236 0.4885 0.1215]}    {[0.9703 0.3887 0.0183]}    {[0.8649 0.9943 0.0015]}    {[0.2415 0.3358 0.7310]}    {[0.3409 0.7371 0.4723]}    {[0.9866 0.2764 0.7661]}    {[0.2456 0.9752 0.8331]}    {[0.3264 0.6088 0.9664]}    {[0.5120 0.0158 0.2393]}    {[0.9590 0.4794 0.4923]}    {[0.1408 0.9563 0.1251]}    {[0.7101 0.2474 0.4939]}    {[0.8497 0.3606 0.3267]}    {[0.3959 0.0756 0.6827]}
    {[0.8262 0.6918 0.5471]}    {[0.8755 0.3083 0.4668]}    {[0.2692 0.9491 0.9485]}    {[0.7312 0.0940 0.7889]}    {[0.6232 0.9140 0.2606]}    {[0.0974 0.1642 0.1264]}    {[0.8204 0.4193 0.3712]}    {[0.8510 0.2695 0.2089]}    {[0.9329 0.4857 0.7534]}    {[0.5284 0.4826 0.3174]}    {[0.8365 0.0226 0.9623]}    {[0.0121 0.9591 0.2520]}    {[0.4461 0.2421 0.1642]}    {[0.2766 0.1248 0.5843]}    {[0.1882 0.5491 0.3692]}    {[0.1296 0.0749 0.2469]}    {[0.5580 0.4763 0.2130]}    {[0.0448 0.5313 0.5185]}    {[0.2583 0.5596 0.3773]}    {[0.6429 0.8037 0.0475]}    {[0.2039 0.0803 0.7987]}    {[0.6727 0.4732 0.9227]}    {[0.4730 0.8781 0.2739]}    {[0.5806 0.6633 0.4859]}    {[0.2127 0.0358 0.1055]}    {[0.8714 0.5096 0.3305]}    {[0.4656 0.2529 0.8804]}    {[0.1039 0.9658 0.0965]}    {[0.2534 0.6915 0.5815]}    {[0.8169 0.1143 0.7607]}
    {[0.3358 0.3659 0.0847]}    {[0.8248 0.0630 0.7478]}    {[0.0859 0.4268 0.5120]}    {[0.2942 0.6225 0.1769]}    {[0.6562 0.2325 0.7635]}    {[0.7559 0.9618 0.9766]}    {[0.9743 0.5746 0.1363]}    {[0.3268 0.0317 0.5223]}    {[0.9183 0.0887 0.9893]}    {[0.5820 0.0884 0.4620]}    {[0.2774 0.3369 0.7259]}    {[0.7810 0.0557 0.5424]}    {[0.6290 0.7688 0.2438]}    {[0.6322 0.8649 0.3898]}    {[0.2204 0.8559 0.2658]}    {[0.5622 0.2340 0.7919]}    {[0.6474 0.1660 0.1564]}    {[0.8515 0.9651 0.3565]}    {[0.3523 0.2730 0.5026]}    {[0.4541 0.6099 0.8491]}    {[0.0574 0.2221 0.4081]}    {[0.5365 0.6588 0.2323]}    {[0.7945 0.0529 0.7380]}    {[0.0260 0.8984 0.7425]}    {[0.9261 0.9174 0.9308]}    {[0.7356 0.2066 0.1395]}    {[0.1735 0.2151 0.2176]}    {[0.4628 0.7948 0.6768]}    {[0.1423 0.1103 0.3072]}    {[0.8532 0.4817 0.1074]}

% first element of the vector in each cell of C:
result = cellfun(@(x)x(1),C)

result = 400×30

0.4837 0.8740 0.1324 0.6612 0.4619 0.7118 0.2325 0.0200 0.4560 0.1519 0.8171 0.7354 0.3328 0.8574 0.8225 0.7205 0.0384 0.9788 0.9149 0.2323 0.2986 0.8800 0.0667 0.6787 0.1189 0.1945 0.7551 0.6601 0.0305 0.2559 0.8256 0.4592 0.7049 0.4509 0.0687 0.7839 0.7122 0.7732 0.5106 0.3814 0.8269 0.4651 0.7178 0.0601 0.1606 0.8022 0.3695 0.4676 0.5443 0.0107 0.4242 0.0932 0.2591 0.0037 0.4344 0.8503 0.6300 0.7369 0.9386 0.8376 0.5549 0.4091 0.0982 0.7266 0.8680 0.0748 0.5388 0.3071 0.8893 0.1695 0.3605 0.6311 0.7511 0.4553 0.8662 0.1720 0.4470 0.7851 0.4080 0.4649 0.6417 0.4702 0.9411 0.0912 0.5545 0.3380 0.1652 0.2722 0.5397 0.5722 0.0788 0.3883 0.3312 0.6314 0.8679 0.9967 0.9261 0.5456 0.1639 0.2139 0.0530 0.5565 0.3360 0.5524 0.8465 0.7286 0.4273 0.2620 0.8590 0.4911 0.9668 0.1840 0.5850 0.1206 0.5714 0.6423 0.9187 0.4693 0.9607 0.3223 0.4740 0.7031 0.0956 0.7025 0.2697 0.6983 0.4640 0.7186 0.9529 0.1031 0.9618 0.5651 0.0930 0.8350 0.2929 0.0082 0.8387 0.2495 0.7764 0.0752 0.3261 0.6248 0.9437 0.5454 0.9168 0.2736 0.4397 0.7255 0.8021 0.4656 0.5338 0.7526 0.5498 0.4832 0.8979 0.8777 0.0600 0.7067 0.0356 0.8490 0.9712 0.0492 0.2202 0.3548 0.0882 0.4211 0.2338 0.2085 0.4386 0.6316 0.9799 0.9853 0.5281 0.2062 0.5461 0.3105 0.2766 0.3531 0.6678 0.9592 0.6690 0.4193 0.5614 0.0265 0.2019 0.6552 0.3658 0.4005 0.7309 0.8173 0.8237 0.1971 0.4563 0.3923 0.4221 0.4862 0.6172 0.5014 0.1152 0.8745 0.2982 0.1953 0.8233 0.2180 0.5983 0.2572 0.0465 0.8519 0.1423 0.4876 0.8101 0.7243 0.5799 0.4406 0.4264 0.0973 0.6620 0.4242 0.9587 0.7218 0.3534 0.2709 0.1132 0.7253 0.2636 0.1935 0.2115 0.2095 0.0884 0.3745 0.8799 0.1194 0.6464 0.5217 0.4975 0.0436 0.0452 0.4353 0.4962 0.0980 0.3931 0.7120 0.9851 0.0779 0.6079 0.7469 0.6458 0.0630 0.0923 0.1773 0.1143 0.3538 0.9882 0.1814 0.3046 0.0837 0.6012 0.2084 0.4567 0.5604 0.1455 0.8098 0.4093 0.8472 0.3292 0.3222 0.9638 0.3620 0.9914 0.4044 0.8212 0.6847 0.6415 0.6561 0.4268 0.9211 0.8204 0.7044 0.1864 0.8216 0.8203 0.4255 0.4428 0.7608 0.8108 0.7484 0.9059 0.0598 0.5630 0.3571 0.3091 0.5101 0.9889 0.1225 0.3239 0.0960 0.2005 0.0221 0.4858 0.9786

% or, first element of the vector in each cell of the first column of C:
result = cellfun(@(x)x(1),C(:,1))

result = 400×1

0.4837 0.8256 0.5549 0.0788 0.4740 0.5338 0.6690 0.8101 0.3931 0.8212

[Chiara Gigoli]

Hi Voss,

Thank you for your answer! I did the same thing, but in this way I obtain the first element of ALL columns... But if I want only the first element of the first column?

Sorry for the stupid question, thank you in advance

Chiara

[Voss]

I have edited my answer to show that scenario as well (use C(:,1) instead of C in the call to cellfun).

[Chiara Gigoli]

I already tried, but this error appears:

"Index exceeds the number of array elements. Index must not exceed 0.

Error in @(x)x(1)"

Could it be because I have some blank cells?

I saw a topic in which they say to use this structure to replace blank cells with zeros:

idx = ~cellfun('isempty',C);
result = zeros(size(C))

[Voss]

"Could it be because I have some blank cells?"

Yes, exactly.

You can replace the blank cells with [0 0 0] like this:

C(cellfun(@isempty,C)) = {[0 0 0]};

Or maybe it's better to use a 1x3 array of NaNs instead of zeros (in particular this is better if your data may contain [0 0 0] but will never contain [NaN NaN NaN]):

C(cellfun(@isempty,C)) = {NaN(1,3)};

Or since you just need the first element of the array in each cell, replace blank cells with a single NaN:

C(cellfun(@isempty,C)) = {NaN};

[Chiara Gigoli]

Thank you very much to be so kind and patient.

This solved my question.

[Voss]

You're welcome! I'm glad it's working now!