[R] help with a simple function

[arun]

Hi,

rownames(y_raw_mt)=y_raw[,1] ## y_raw not defined.


set.seed(25)
mat1<- matrix(sample(c(NA,1:20),100,replace=TRUE),20,5)

#changed the function to process 'mat1'.  Also, it is better to read the file separately and check ?str(dt.table) before proceeding.
write.table1=function(durty_data){  
 # dt.table=read.table(durty_data, sep = "\t", header=T)#
 # y_raw_mt=as.matrix(dt.table[2:174])####
y_raw_mt<- durty_data  
rownames(y_raw_mt)= paste0("Col",1:nrow(y_raw_mt)) #assigning the raw names to the matrix
  y_raw_mt_t=t(y_raw_mt)####
  y_raw_mt_t_mean=apply(y_raw_mt_t, 2, mean, na.rm=T)###
  means=c(y_raw_mt_t_mean)##
 
  y_raw_mt_t_meanbind=rbind(y_raw_mt_t,means)##
 
 
  t=function(x) {
    x[is.na(x)]  = mean(x, na.rm = T)
    return(x)
  }
 
  write.a.nice.table=apply(y_raw_mt_t_meanbind,2,t)
  return(write.a.nice.table)
}

#Function seemed to work as intended.
 write.table1(mat1)
      Col1 Col2 Col3 Col4 Col5 Col6 Col7 Col8 Col9 Col10 Col11 Col12 Col13
         8 14.0  3.0 18.0  2.0   20 13.0  7.0  1.0     5   6.0     7  20.0
         9  9.0  1.0  3.0  6.0    6  1.0 12.0 11.0     4  17.0     7   4.0
        14  5.0 11.0 15.0 11.0    6 20.0 14.0  1.0    15   2.0    15  17.0
         2  4.0  6.0 14.0 13.0   17  9.0 18.0 13.0     5  18.0     2   1.0
        12  7.0 10.0  1.0 16.0   16  6.0  8.0 16.0    11  10.0     4  12.0
means    9  7.8  6.2 10.2  9.6   13  9.8 11.8  8.4     8  10.6     7  10.8
      Col14 Col15 Col16 Col17 Col18 Col19 Col20
       12.0  14.0     3  11.0  15.0  10.0    15
        2.0  17.0     8  19.0   7.0   3.0     2
       10.0  11.0     2   2.0  11.0   3.0     2
       16.0   4.0     9   2.0  17.0   3.0     3
       13.0  11.5     8  13.0  18.0   4.0     3
means  10.6  11.5     6   9.4  13.6   4.6     5
 rowMeans(mat1,na.rm=TRUE)
# [1]  9.0  7.8  6.2 10.2  9.6 13.0  9.8 11.8  8.4  8.0 10.6  7.0 10.8 10.6 11.5
#[16]  6.0  9.4 13.6  4.6  5.0


A.K.





hi, I am new to are, very new and want to ask what's wrong with this 
function: It is suppose to read a table and return its matrix transposed
 with NA replaced by the average of each column and a row of means at 
the bottom row. The separated parts are returned correctly. Thanks a lot
 for any help. 

Guy 

write.table=function(durty_data){ 
  
  
  dt.table=read.table(durty_data, sep = "\t", header=T)# 
  y_raw_mt=as.matrix(dt.table[2:174])#### 
  rownames(y_raw_mt)=y_raw[,1] #assigning the raw names to the matrix 
  y_raw_mt_t=t(y_raw_mt)#### 
  y_raw_mt_t_mean=apply(y_raw_mt_t, 2, mean, na.rm=T)### 
  means=c(y_raw_mt_t_mean)## 
  
  y_raw_mt_t_meanbind=rbind(y_raw_mt_t,means)## 
  
  
  t=function(x) { 
    x[is.na(x)]  = mean(x, na.rm = T) 
    return(x) 
  } 
  
  write.a.nice.table=apply(y_raw_mt_t_meanbind,2,t) 
  return(write.a.nice.table) 
}