I want to rename elements with value 0 to NA which lie within lists of lists. I want to do it for to the first four columns that lie within the lists (VA01.000252, VA01.000306, ...) of my main list (F_10). I have an approach which works for my test data but this approach already takes much time to process. The actual dataset is far bigger and I am worried it will take ages for the command to process. The test data and my approach both can be found below.
This is my data:
$VA01.000252
VA01_F0finEnv VA01_F0final VA01_Jitter VA01_Shimmer VA01_MFCC.0. VA01_MFCC.1. VA01_MFCC.2. VA01_MFCC.3. VA01_MFCC.4. VA01_MFCC.5. VA01_MFCC.6. VA01_MFCC.7. VA01_MFCC.8. VA01_MFCC.9. VA01_MFCC.10.
1 0.00000 0.0000 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
2 0.00000 0.0000 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
3 0.00000 0.0000 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
4 59.81091 0.0000 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
5 112.72920 138.0768 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
6 165.64740 138.0768 0 0.0000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
7 156.10650 0.0000 0 0.0000000 -129.11450 -4.886806e 00 8.293210e-01 -9.716904e-01 1.874519e 00 -3.330100e 00 1.155394e-01 -2.982753e-01 1.236686e 00 2.213515e 00 -1.102626e 00
8 151.33920 126.1790 0 1.0000000 -116.44960 -1.273737e 01 3.589834e-01 -4.425217e 00 9.199393e-01 -6.688267e 00 -1.412614e 00 -5.138365e 00 -1.940008e 00 -7.340010e-01 -1.923529e 00
9 154.11870 162.4571 0 0.7356322 -100.07050 -2.011970e 01 2.068043e-01 -6.162563e 00 -2.650808e-01 -9.938509e 00 -5.045537e 00 -8.725165e 00 -2.300158e 00 -1.821709e-01 -4.456659e 00
10 159.54650 180.1982 1 0.6034483 -85.24709 -2.219019e 01 -1.302721e 00 -6.597542e 00 2.171658e-01 -6.894450e 00 -1.055527e 01 -9.126151e 00 -1.717053e 00 -3.730820e 00 -1.023192e 01
11 167.09320 0.0000 0 0.0000000 -80.85322 -2.203539e 01 8.542528e-01 -3.835218e 00 4.422236e 00 -3.171251e 00 -1.415027e 01 -7.171879e 00 1.465298e 00 -2.147878e 00 -1.295104e 01
12 167.09320 0.0000 0 0.0000000 -81.12218 -2.372173e 01 1.530055e 00 -3.164595e 00 6.954316e 00 -2.101640e 00 -1.380905e 01 -2.736499e 00 2.313805e 00 -4.345511e 00 -1.015212e 01
13 167.09320 0.0000 0 0.0000000 -83.30384 -2.619328e 01 2.223715e 00 -1.346338e 00 6.163294e 00 -2.007305e 00 -1.238243e 01 -5.069185e 00 -1.514774e 00 -5.590108e 00 -4.327339e-01
14 167.09320 0.0000 0 0.0000000 -84.06513 -2.743844e 01 8.034258e-01 -8.133652e-01 3.687939e 00 -2.823765e 00 -8.803297e 00 -1.059612e 00 -2.296476e 00 -8.613113e 00 5.305792e 00
15 167.09320 0.0000 0 0.0000000 -83.64664 -2.706799e 01 1.158314e 00 -5.528085e-01 1.531354e 00 -2.680211e 00 -8.055579e 00 -2.319103e 00 -4.283731e 00 -8.192851e 00 7.707067e 00
16 167.09320 0.0000 0 0.0000000 -83.04565 -2.593493e 01 1.763077e 00 -3.936937e 00 -3.647466e 00 -6.354158e 00 -8.138985e 00 5.811316e-01 -2.851794e 00 -6.887127e 00 6.254632e 00
17 167.09320 0.0000 0 0.0000000 -82.64518 -2.568779e 01 1.347809e 00 -8.193944e 00 -5.826789e 00 -7.205881e 00 -1.052378e 01 1.576325e 00 -1.645603e 00 -3.474594e 00 6.372686e 00
18 167.09320 0.0000 0 0.0000000 -82.07550 -2.690814e 01 -1.296210e 00 -1.040748e 01 -6.379502e 00 -7.877069e 00 -1.063956e 01 -1.252872e 00 -2.972258e 00 -2.370217e 00 5.093191e 00
19 167.09320 0.0000 0 0.0000000 -81.27705 -2.732649e 01 -3.065270e 00 -7.066913e 00 -2.598729e 00 -5.304600e 00 -1.107656e 01 -3.846291e 00 -2.725531e 00 -1.543451e 00 3.412861e 00
20 167.09320 0.0000 0 0.0000000 -80.36498 -2.759527e 01 -3.365986e 00 -2.185576e 00 -8.248324e-01 -4.939477e 00 -9.010359e 00 -8.932830e 00 -4.472707e-01 -8.970172e-01 -4.256793e 00
21 167.09320 0.0000 0 0.0000000 -80.53387 -2.746712e 01 -1.673572e 00 1.303288e 00 1.375768e 00 -3.681439e 00 -1.134807e 01 -1.244722e 01 2.112881e 00 -2.435152e-02 -6.124821e 00
22 167.09320 0.0000 0 0.0000000 -81.29316 -2.871439e 01 -1.314733e 00 -1.031087e 00 -2.735091e 00 -5.713663e 00 -1.199027e 01 -1.460559e 01 -1.527567e 00 1.668803e-01 -6.425414e 00
23 167.09320 0.0000 0 0.0000000 -81.90575 -2.933984e 01 -2.327192e 00 -3.482757e 00 -5.539301e 00 -8.520871e 00 -1.524773e 01 -1.433087e 01 -5.164460e 00 -1.778122e 00 -5.645791e 00
24 167.09320 0.0000 0 0.0000000 -82.04091 -2.911803e 01 -3.437798e 00 -5.882364e 00 -7.277412e 00 -7.221782e 00 -1.225192e 01 -1.117920e 01 -7.191702e 00 -4.617439e 00 -6.148396e 00
25 167.09320 0.0000 0 0.0000000 -82.13178 -2.898966e 01 -4.838960e 00 -5.939596e 00 -4.656537e 00 -5.475117e 00 -8.213964e 00 -8.253125e 00 -5.136382e 00 -3.632409e 00 -5.178719e 00
26 167.09320 0.0000 0 0.0000000 -82.75354 -2.892703e 01 -4.283483e 00 -4.956952e 00 -8.748829e-01 -9.806442e-02 -3.997231e 00 -7.371384e 00 -5.868333e 00 -2.999556e 00 -8.084539e-01
27 167.09320 0.0000 0 0.0000000 -82.74642 -2.865274e 01 -3.706652e 00 -5.547077e 00 -5.480065e-01 -2.597058e 00 -6.388766e 00 -6.570017e 00 -5.618668e 00 -1.574020e 00 4.895750e-01
28 167.09320 0.0000 0 0.0000000 -83.49352 -2.922196e 01 -2.170068e 00 -2.311250e 00 3.320872e 00 -1.060383e 00 -7.007614e 00 -5.806552e 00 -1.797331e 00 -3.936761e 00 -2.398118e 00
29 167.09320 0.0000 0 0.0000000 -83.00410 -2.950762e 01 -2.355202e 00 -3.050338e 00 1.869767e 00 -2.100468e 00 -8.660001e 00 -1.047368e 01 -6.588408e 00 -8.047549e 00 -6.600111e 00
30 167.09320 0.0000 0 0.0000000 -83.05898 -3.081953e 01 -3.816830e 00 -2.152992e 00 4.679519e 00 5.164295e-01 -5.140864e 00 -1.107932e 01 -7.775589e 00 -5.094333e 00 -6.355783e 00
31 167.09320 0.0000 0 0.0000000 -82.02769 -3.005491e 01 -5.036798e 00 -6.075222e 00 3.737306e 00 -1.093793e 00 -8.630654e 00 -1.332389e 01 -1.209293e 01 -3.569095e 00 -5.040240e 00
32 167.09320 0.0000 0 0.0000000 -81.43015 -2.970782e 01 -5.878477e 00 -7.077900e 00 3.712163e 00 -3.901497e 00 -1.111143e 01 -1.353048e 01 -9.729337e 00 -4.175434e-01 -2.635696e 00
33 167.09320 0.0000 0 0.0000000 -80.90739 -2.939053e 01 -6.025192e 00 -9.395978e 00 -1.277639e 00 -9.709239e 00 -1.362978e 01 -1.536083e 01 -1.176102e 01 -8.894852e 00 -7.310049e 00
34 167.09320 0.0000 0 0.0000000 -80.45148 -2.961173e 01 -6.865067e 00 -1.135724e 01 -6.189119e 00 -1.109089e 01 -6.817587e 00 -1.570327e 01 -1.764861e 01 -1.836790e 01 -1.024871e 01
35 167.09320 0.0000 0 0.0000000 -80.31771 -2.975894e 01 -8.124461e 00 -1.445113e 01 -8.836887e 00 -8.614040e 00 1.459559e-01 -9.877742e 00 -1.786876e 01 -1.989631e 01 -1.123060e 01
VA01_MFCC.11. VA01_MFCC.12. VA01_MFCC.13. VA01_MFCC.14. VA01_LPCC.0. VA01_LPCC.1. VA01_LPCC.2. VA01_LPCC.3. VA01_LPCC.4. VA01_LPCC.5. VA01_LPCC.6. VA01_LPCC.7. ID
1 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.000000e 00 0.0000000000 0.000000000 VA01.000252
2 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.000000e 00 0.0000000000 0.000000000 VA01.000252
3 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.000000e 00 0.0000000000 0.000000000 VA01.000252
4 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.000000e 00 0.0000000000 0.000000000 VA01.000252
5 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0007353425 0.0133470400 0.0178267000 0.0236341200 0.0051963800 -1.534662e-02 -0.0123545200 -0.006236935 VA01.000252
6 0.0000000 -2.515524e-05 0.0000000 0.00000000 0.0039662060 0.0191080900 0.0221010400 0.0278217900 -0.0151209800 -4.988735e-02 -0.0621331400 -0.042875290 VA01.000252
7 -2.0578450 -4.526057e-01 2.1649830 1.14272200 0.0082406700 0.0184099100 0.0184085100 0.0133602000 -0.0395623400 -8.628076e-02 -0.1246156000 -0.076643490 VA01.000252
8 -1.1773900 -4.042094e 00 0.6001247 2.02709300 0.0089936970 -0.0018600400 -0.0103975200 -0.0467316300 -0.0761350200 -1.033836e-01 -0.1733676000 -0.094520330 VA01.000252
9 -0.3716143 -3.261007e 00 -2.8978200 1.42560600 -0.0011875660 -0.0181171800 -0.0357011600 -0.0943858200 -0.0780721500 -7.972527e-02 -0.1528078000 -0.058934500 VA01.000252
10 -5.6593810 -6.127711e 00 -9.1781060 -3.30674300 -0.0083277100 -0.0124441300 -0.0290099300 -0.0814918100 -0.0502561700 -4.298887e-02 -0.0858175000 -0.005338144 VA01.000252
11 -13.6049000 -8.965543e 00 -12.4168800 -6.97922100 -0.0075976880 0.0003679216 -0.0165640700 -0.0374678100 -0.0212830000 -1.222754e-02 -0.0205598000 0.020251940 VA01.000252
12 -13.6518400 -1.079708e 01 -8.1353630 -5.36020900 0.0086924730 0.0162289300 0.0083109860 0.0179146200 0.0030251260 3.650904e-04 0.0101194900 0.013467260 VA01.000252
13 -4.2140520 -6.399786e 00 -6.8131010 -3.99737200 0.0206394700 0.0124061600 0.0113651500 0.0281120900 0.0009592533 -7.675886e-05 0.0042102340 -0.010332560 VA01.000252
14 1.7268340 1.019973e 00 -5.8971240 -3.67270800 0.0160420600 -0.0025150540 0.0035499690 0.0217870700 0.0012038830 -6.543517e-04 -0.0064042090 -0.027503590 VA01.000252
15 -0.4274078 -1.942096e-01 -6.9390640 -7.73466900 0.0060903790 -0.0193745400 -0.0085384600 0.0069389700 -0.0046961070 -6.010354e-03 -0.0136247200 -0.039329630 VA01.000252
16 -3.1817960 -2.342408e 00 -4.2083140 -7.25781300 0.0024127930 -0.0237320200 -0.0180253000 -0.0007227779 -0.0012942670 -9.491324e-03 0.0037402510 -0.027839280 VA01.000252
17 -4.1359790 -2.151227e 00 -0.3981749 -5.82635500 0.0061842200 -0.0104811700 -0.0159853200 -0.0094374770 -0.0019166110 -1.936967e-02 0.0120926000 -0.049282360 VA01.000252
18 -5.1128360 -1.868084e 00 1.6251510 -2.92386500 0.0047843750 0.0127103400 -0.0049924250 -0.0127612000 0.0014022110 -1.778158e-02 0.0182165600 -0.060821820 VA01.000252
19 -4.6665450 -6.998692e-01 2.9522980 -0.91227390 -0.0067994530 0.0241639500 -0.0035714270 -0.0227305900 -0.0051709650 -1.781380e-02 -0.0107371700 -0.119747700 VA01.000252
20 -1.4622320 -1.024292e 00 6.0916290 -0.68188170 -0.0131211300 0.0206917000 -0.0007370055 -0.0167987500 0.0027669190 -3.750491e-03 -0.0177633900 -0.085645620 VA01.000252
21 -3.2021130 -1.547664e 00 5.2626800 -3.04651800 -0.0059770220 0.0106918900 0.0029697720 -0.0027474640 0.0168087400 6.712651e-03 -0.0074782970 0.011661980 VA01.000252
22 -5.5350250 -1.421402e 00 6.2528610 -5.16527700 0.0056278920 -0.0006325186 0.0064281520 0.0123923700 0.0251277800 1.237495e-02 0.0093992230 0.084718790 VA01.000252
23 -9.9739800 -4.194067e 00 2.7173540 -7.12243300 0.0191741000 -0.0036595940 0.0118473100 0.0195928100 0.0227896900 1.808438e-02 0.0132741000 0.112429100 VA01.000252
24 -7.4694330 -1.708854e 00 -0.9246085 -5.74657400 0.0205290900 -0.0010454420 0.0029362680 0.0147718700 0.0056231740 9.797978e-03 0.0017608400 0.045768830 VA01.000252
25 -4.6853820 -8.716103e-01 -3.6994880 -5.88591400 0.0133582600 -0.0026394610 -0.0060674670 0.0055232170 -0.0078798890 -4.472899e-03 -0.0002278447 -0.006507802 VA01.000252
26 -3.9408350 1.069726e 00 -0.3268897 -4.82812300 -0.0035384920 0.0003950119 -0.0101032000 -0.0074809790 -0.0234347300 -1.949897e-02 -0.0054683810 -0.056227680 VA01.000252
27 -0.7509457 2.139219e 00 6.6879060 -1.82945600 -0.0210549600 -0.0055490140 -0.0127789600 -0.0154033500 -0.0296738700 -1.992862e-02 -0.0132879900 -0.100097000 VA01.000252
28 -2.8119180 -2.486559e 00 3.3848200 0.40004780 -0.0158421100 0.0014721570 -0.0050028440 -0.0106496000 -0.0236421900 1.363218e-03 -0.0263921100 -0.087092330 VA01.000252
29 -5.0905940 -4.498779e 00 0.3184656 1.59565600 0.0009931505 0.0116114100 -0.0049441880 0.0077095150 -0.0056366920 1.981512e-02 -0.0163032500 -0.016945080 VA01.000252
30 -10.7903100 -8.233760e 00 -6.7355710 -1.88403700 0.0185493100 0.0146813200 -0.0025107030 0.0140376200 0.0120996500 1.894019e-02 -0.0016933080 0.074631690 VA01.000252
31 -10.7472500 -3.507028e 00 -0.1868369 -0.01676401 0.0169766300 0.0082867090 0.0059551180 0.0086740850 0.0118743400 1.064398e-02 0.0108309100 0.123264800 VA01.000252
32 -8.8624510 -4.327910e 00 -1.9420190 0.05665708 0.0087855510 -0.0141147600 0.0164769500 0.0007412076 0.0130740800 -1.723886e-04 0.0235768200 0.111186500 VA01.000252
33 -4.1893760 -4.628457e 00 -1.0422120 2.16047900 0.0096208300 -0.0303383700 0.0185003800 0.0002016187 0.0023077250 2.610683e-05 0.0196681900 0.031342030 VA01.000252
34 -2.5935570 -7.604697e 00 -6.2509840 -1.77888000 0.0159274900 -0.0354746000 0.0100154900 0.0027364130 0.0022544260 9.940148e-04 0.0233995400 -0.016331980 VA01.000252
35 -0.3843622 -8.656120e 00 -8.2879270 -4.46927800 0.0119029500 -0.0372953300 -0.0117585300 -0.0065452820 -0.0074253200 -2.392042e-03 0.0032024020 -0.044989680 VA01.000252
[ reached 'max' / getOption("max.print") -- omitted 5732 rows ]
$VA01.000306
VA01_F0finEnv VA01_F0final VA01_Jitter VA01_Shimmer VA01_MFCC.0. VA01_MFCC.1. VA01_MFCC.2. VA01_MFCC.3. VA01_MFCC.4. VA01_MFCC.5. VA01_MFCC.6. VA01_MFCC.7. VA01_MFCC.8. VA01_MFCC.9. VA01_MFCC.10.
1 0.00000 0.0000 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
2 0.00000 0.0000 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
3 0.00000 0.0000 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
4 66.06307 0.0000 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
5 132.07510 197.8827 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
6 198.10720 198.0143 0.00000000 0.00000000 -132.83340 4.071416e-06 -2.168415e-06 -8.838955e-06 -1.102504e-05 -4.339662e-06 -4.926738e-06 -5.424289e-06 2.328874e-05 -3.056164e-06 3.144405e-06
7 198.26770 198.7493 0.00000000 0.00000000 -132.76600 -1.608481e-01 2.037154e-01 -1.779812e-01 9.700684e-02 1.798067e-03 -7.682262e-02 1.031989e-01 -8.462158e-02 4.960256e-02 -3.486202e-02
8 198.47930 199.3359 0.00000000 0.00000000 -121.87960 -3.967190e 00 -3.192784e 00 -5.713863e 00 1.134993e 00 1.154983e 00 9.564801e-01 -4.689783e 00 -7.461606e 00 -4.408395e 00 -2.726076e 00
9 198.67080 0.0000 0.00000000 0.00000000 -106.01020 -7.278543e 00 -3.143362e 00 -7.678925e 00 1.252466e 00 3.508399e 00 3.603816e 00 -6.568146e 00 -1.219917e 01 -8.938245e 00 -4.760966e 00
10 198.67080 0.0000 0.00000000 0.00000000 -88.07464 -1.064713e 01 -3.466723e 00 -8.576050e 00 -1.456704e-01 3.247663e 00 5.926846e 00 -5.519067e 00 -1.191534e 01 -1.394501e 01 -6.998346e 00
11 198.67080 0.0000 0.00000000 0.00000000 -80.93438 -9.849090e 00 -9.713004e-01 -8.205815e 00 -1.488182e 00 3.519478e 00 6.352642e 00 -6.546592e-01 -1.065193e 01 -1.600990e 01 -1.040968e 01
12 198.67080 0.0000 0.00000000 0.00000000 -79.00248 -9.464789e 00 -1.925519e 00 -1.044870e 01 -3.597581e 00 1.343774e 00 3.038982e 00 -1.895679e 00 -1.008268e 01 -1.576755e 01 -1.100388e 01
13 198.67080 0.0000 0.00000000 0.00000000 -78.68784 -8.090163e 00 -1.151505e 00 -1.209496e 01 -3.559671e 00 6.267379e 00 5.489735e 00 -4.759048e 00 -1.185489e 01 -1.706914e 01 -1.093319e 01
14 198.67080 0.0000 0.00000000 0.00000000 -78.79014 -8.380761e 00 -9.766474e-02 -1.078117e 01 -5.220814e 00 9.307704e 00 8.080084e 00 -4.081142e 00 -1.091573e 01 -1.736321e 01 -7.666967e 00
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[ reached 'max' / getOption("max.print") -- omitted 6444 rows ]
This is my approach:
for (i in 1:length(F_10)){
for (j in 1:4){
for (k in 1:length(F_10[[i]][[j]])){
if ( F_10[[i]][[j]][k] == 0 ){
F_10[[i]][[j]][k] <- NA
}
}
}
}
CodePudding user response：
If I understand it correctly and your inner lists are data frames, you only need one loop:
F_10 <- data.frame(a=0:2, b=c(1, 0, 0), c=0:2, d=0:2, e=0:2)
F_10 <- list(F_10, F_10)
# [[1]]
# a b c d e
# 1 0 1 0 0 0
# 2 1 0 1 1 1
# 3 2 0 2 2 2
#
# [[2]]
# a b c d e
# 1 0 1 0 0 0
# 2 1 0 1 1 1
# 3 2 0 2 2 2
col.i <- 1:4
for (i in seq_along(F_10)) {
F_10[[i]][, col.i][F_10[[i]][, col.i]==0] <- NA
}
# [[1]]
# a b c d e
# 1 NA 1 NA NA 0
# 2 1 NA 1 1 1
# 3 2 NA 2 2 2
#
# [[2]]
# a b c d e
# 1 NA 1 NA NA 0
# 2 1 NA 1 1 1
# 3 2 NA 2 2 2