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
On Wed, 30-Jun-2004 at 11:57PM -0400, Peter Wilkinson wrote: |> 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 I'm curious to know how you got those row names. I suspect you really have a matrix. If it were a dataframe, it would behave exactly how you are reqesting -- depending on how you got rid of rows 4:7. Try as.data.frame(<whatever.your.data.is.now>) Then deleting the rows will 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 HTH -- Patrick Connolly HortResearch Mt Albert Auckland New Zealand Ph: +64-9 815 4200 x 7188 ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~ I have the world`s largest collection of seashells. I keep it on all the beaches of the world ... Perhaps you`ve seen it. ---Steven Wright ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~
Assuming all the entries are non-negative and non-NA this will do it:
DF[rowSums(DF) > 0,]
Peter Wilkinson <pwilkinson <at> videotron.ca> writes:
:
: 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