here is a snippet of data where I would like to drop all rows that have zeros across them, and keep the rest of the rows while maintaining the row names (1,2,3, ...10). The idea here is that a row of zeros is an indication that the row must be dropped. There will never be the case where there is a row(of n columns) with less than 5 zeros in this case(n zeros

I am unsure how to manipulate the data frame to drop rows whiles keeping row names.

Peter

the data (imagine separated by tabs):

      SEKH0001  SEKH0002 SEKH0003 SEKH0004 SEKH0005
 [1,] 256.1139  256.1139 256.1139 256.1139 256.1139
 [2,] 283.0741  695.1000 614.5117 453.0342 500.1436
 [3,] 257.3578  305.0818 257.3578 257.3578 257.3578
 [4,]   0.0000    0.0000   0.0000   0.0000   0.0000
 [5,]   0.0000    0.0000   0.0000   0.0000   0.0000
 [6,]   0.0000    0.0000   0.0000   0.0000   0.0000
 [7,]   0.0000    0.0000   0.0000   0.0000   0.0000
 [8,] 257.0000  257.0000 257.0000 257.0000 257.0000
 [9,] 305.7857 2450.0417 335.5428 305.7857 584.2485
[10,]   0.0000    0.0000   0.0000   0.0000   0.0000

what I want it to look like:

      SEKH0001  SEKH0002 SEKH0003 SEKH0004 SEKH0005
 [1,] 256.1139  256.1139 256.1139 256.1139 256.1139
 [2,] 283.0741  695.1000 614.5117 453.0342 500.1436
 [3,] 257.3578  305.0818 257.3578 257.3578 257.3578
 [8,] 257.0000  257.0000 257.0000 257.0000 257.0000
 [9,] 305.7857 2450.0417 335.5428 305.7857 584.2485

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