How to select only that rows from which I have values in all columns?

I have multiple cloumns of specific variables, and there hourly data for many years. I want to select only those data for which I have vlaues in last three columns.

My data is :

YEAR    MONTH   DAY HOUR    PM2.5   PM10    BC  σsp(525)    ssa σap(520)    α   Ntotal  Nuc (<25nm) Ait (25-90nm)   Acc(>90nm)

2006    4   16  9   43  135 1.23            17.26   1.17    4639    28  1901    2710
2006    4   16  10  40  75  1.06            15.29   1.22    3782    31  1302    2449
2006    4   16  11  34  169 0.82            11.79   1.19    3372    74  1087    2211
2006    4   16  12  39  5   1.32            19.91   1.33    4083    127 1060    2896
2006    4   16  13  45  179 1.59            24.41   1.37    6054    1813    1240    3001
2006    4   16  14  41  60  1.50            22.01   1.26    6269    1840    1544    2885
2006    4   16  15  42  129 1.75            26.01   1.28    5868    1096    1475    3297
2006    4   16  16  44  116 1.52            22.10   1.22    4928    848 1308    2772
2006    4   16  17  40  144 1.53            23.93   1.39    5377    460 1558    3359
2006    4   16  18  47  118 1.68            25.50   1.32    4990    327 1686    2977
2006    4   16  19  39  113 1.67            25.28   1.34    5698    228 2196    3274
2006    4   16  20  44  121 1.76            26.36   1.32    5633    137 2039    3458
2006    4   16  21  47  96  1.96            29.74   1.36    6658    75  2282    4301
2006    4   16  22  49  97  1.70            27.93   1.57    7459    55  2558    4847
2006    4   16  23  49  96  1.79            28.84   1.51    6614    49  2187    4378
2006    4   17  0   40  57  1.55    112.2   0.82    23.62   1.35    4800    45  1402    3354
2006    4   17  1   36  61  1.48    106.8   0.83    22.03   1.28    4254    40  1161    3053
2006    4   17  2   36  75  1.18    96.9    0.85    17.65   1.28    3892    39  1054    2798
2006    4   17  3   31  58  1.35    94.0    0.82    20.62   1.34    3466    26  859 2582
2006    4   17  4   47  120 1.41    93.8    0.82    21.17   1.31    3377    21  807 2548
2006    4   17  5   37  42  1.58    95.9    0.80    23.44   1.27    3556    18  881 2657
2006    4   17  6   43  119 1.39    91.4    0.82    20.41   1.25    3492    27  928 2537
2006    4   17  7   34      1.30    89.1    0.82    18.87   1.23    3674    56  1113    2505
2006    4   17  8   36      1.09    94.8    0.85    16.94   1.39    4039    53  1219    2766
2006    4   17  9   36  35  1.05    77.7    0.82    16.34   1.40    3347    53  1074    2220
2006    4   17  10  37  66  0.93    67.9    0.83    14.08   1.33    2909    52  960 1897
2006    4   17  11  45  49  0.94    70.7    0.83    14.07   1.30    3130    36  1076    2018
2006    4   17  12  28  43  0.86    65.5    0.83    12.83   1.29    3040    43  1088    1909
2006    4   17  13  24  50  0.76    57.9    0.84    11.27   1.25    2779    42  1042    1695
2006    4   17  14  28  39  0.72    54.1    0.84    10.43   1.22    2707    53  1093    1561
2006    4   17  15  25  35  0.68    51.5    0.84    9.81    1.18    2606    84  1059    1463
2006    4   17  16  24  47  0.57    47.7    0.86    8.11    1.19    2443    62  1009    1372
2006    4   17  17  25  54  0.86            12.50   1.31    3321    97  1512    1712
2006    4   17  18  40  89  0.53            8.11    1.31                
2006    4   17  19                                          
2006    4   17  20                                          
2006    4   17  21                                          
2006    4   17  22                                          
2006    4   17  23                                          
2006    4   18  0                                           
2006    4   18  1                                           
2006    4   18  2                                           
2006    4   18  3                                           
2006    4   18  4                                           
2006    4   18  5                                           
2006    4   18  6                                           
2006    4   18  7                                           
2006    4   18  8                                           
2006    4   18  9                                           
2006    4   18  10                                          
2006    4   18  11      38  0.43            6.15    1.22    2017    34  919 1064
2006    4   18  12                                          
2006    4   18  13                                          
2006    4   18  14                                          
2006    4   18  15                                          
2006    4   18  16                                          
2006    4   18  17                                          
2006    4   18  18  9   55  0.51            7.56    1.30    2720    64  1200    1456
2006    4   18  19  20  59  0.59            9.03    1.37    2945    59  1335    1552
2006    4   18  20  18  37  0.47            7.00    1.29    2083    36  899 1148
2006    4   18  21  11  19  0.58            7.97    1.10    2376    78  1084    1214
2006    4   18  22  20  26  0.69            9.69    1.19    3119    87  1463    1569
2006    4   18  23                                          
2006    4   19  0                                           
2006    4   19  1                                           
2006    4   19  2                                           
2006    4   19  3                                           
2006    4   19  4                                           
2006    4   19  5                                           
2006    4   19  6                                           
2006    4   19  7                                           
2006    4   19  8                                           
2006    4   19  9                                           
2006    4   19  10      27  0.39    38.3    0.88    5.38    1.12    2668    40  1477    1151
2006    4   19  11      55  0.48    44.2    0.87    6.96    1.19    2861    43  1563    1255
2006    4   19  12      37  0.52    42.3    0.85    7.43    1.19    3354    117 1911    1326
2006    4   19  13      24  0.53    44.0    0.86    7.43    1.16    3702    255 2022    1424
2006    4   19  14      29  0.61    47.4    0.85    8.58    1.15    4506    618 2366    1523
2006    4   19  15      23  0.60            8.57    1.23                
2006    4   19  16                                          
2006    4   19  17                                          
2006    4   19  18  19  24  0.49            7.22    1.29    3679    350 1985    1345
2006    4   19  19  29  46  0.58            8.94    1.41    3934    233 2159    1541
2006    4   19  20  22  26  0.58            8.44    1.25    3546    209 2011    1326

Answer 1

[Harshit Saini]

To select only the rows from which you have values in all columns of your dataset in MATLAB, you can use the "rmmissing" function. Here's an example code:

% load your dataset

load('your_data_file.mat');

% remove any rows that have missing values in any column

valid_data = rmmissing(data, 'MinNumMissing', 1);

In this code, we first load your dataset into a variable called data. We then use the "rmmissing" function to remove any rows that have missing values in any column. The 'MinNumMissing' option is set to 1 to ensure that only rows with at least one missing value are removed.

The "rmmissing" function returns a new dataset called valid_data that contains only the rows where all columns have non-missing values.

Refer to the documentation link below for more detailed examples

https://in.mathworks.com/help/matlab/ref/rmmissing.html

[AMIT SINGH CHANDEL]

thank you