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Transpose columns to Rows : Big data

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# 1  
Old 08-09-2010
Transpose columns to Rows : Big data
Hi,
I did read a few posts on the subjects, tried out a few solutions, but did not solve my problem.
https://www.unix.com/302121568-post11.html
https://www.unix.com/shell-programmin...ows-etc-4.html

Please help. Problem very similar to the second link poster, but slighlt different input format. The field separator is space . The actual data matrix is a file with 2000 rows and 600,000 columns.
Input style:
Code:
IID    PAT    MAT    SEX    PHENOTYPE    rs15286_1    rs319_1    rs80300_1    rs40777_1    rs8597_1    rs5136_1    rs60595_1    rs64968_1    rs4405_1    rs1554_1
TD-MIKV    0 0 2 1 1 0 0 1 0 1 0 1 1 0
TD-HA4Q 0 0 2 1 1 0 0 0 0 0 0 0 0 0
TD-H9ZG 0 0 2 2 0 0 0 1 0 0 0 0 0 0
TD-HAQX 0 0 2 1 0 0 0 2 0 0 0 0 0 0
TD-HA5E 0 0 2 2 0 1 1 1 0 0 0 1 1 0
TD-MGFV 0 0 2 2 1 0 0 0 0 NA 0 0 0 1
TD-HB4V 0 0 2 1 0 0 1 0 1 NA 0 1 1 0
TD-MIPE 0 0 2 2 0 0 0 1 0 0 0 0 0 0
TD-MINR 0 0 2 2 0 0 0 0 0 2 0 1 1 0

Output style
Code:
   IID TD-MIKV TD-HA4Q TD-H9ZG TD-HAQX TD-HA5E TD-MGFV TD-HB4V TD-MIPE TD-MINR
PAT 0 0 0 0 0 0 0 0 0
MAT 0 0 0 0 0 0 0 0 0
SEX 2 2 2 2 2 2 2 2 2
PHENOTYPE 1 1 2 1 2 2 1 2 2
rs15286_1 1 1 0 0 0 1 0 0 0
rs319_1 0 0 0 0 1 0 0 0 0
rs80300_1 0 0 0 0 1 0 1 0 0
rs40777_1 1 0 1 2 1 0 0 1 0
rs8597_1 0 0 0 0 0 0 1 0 0
rs5136_1 1 0 0 0 0 NA NA 0 2
rs60595_1 0 0 0 0 0 0 0 0 0
rs64968_1 1 0 0 0 1 0 1 0 1
rs4405_1 1 0 0 0 1 0 1 0 1
rs1554_1 0 0 0 0 0 1 0 0 0

awk or python preferable, since I understand them a teeny weeny bit.
Thanks in advance,
Regards
~GH
# 2  
Old 08-09-2010
A bit ole school... but here's a possible shell solution:

Code:
#!/bin/sh

filein="$1"
fileout="$2"
cols=`head -1 <"$filein" | wc -w`
count=1
while [ $count -le $cols ]; do
        if [ $count = 1 ]; then
                tr -s ' ' ' ' <"$filein" | cut -f$count -d' ' | tr '\012' ' ' >"$fileout"
        else
                tr -s ' ' ' ' <"$filein" | cut -f$count -d' ' | tr '\012' ' ' >>"$fileout"
        fi
        echo "" >>"$fileout"
        count=`expr $count + 1`
done

In some cases, this may actually work better than reading everything into memory and processing... Anyhow... something to consider...
# 3  
Old 08-09-2010
#deleted#
Last edited by kurumi; 08-10-2010 at 10:39 PM..
# 4  
Old 08-10-2010
Code:
awk '{for (i=1; i<=NF; i++) a[i]=a[i](NR!=1?FS:"")$i} END {for (i=1; i in a; i++) print a[i]}' file

# 5  
Old 08-10-2010
Quote:
Originally Posted by alister
Code:
awk '{for (i=1; i<=NF; i++) a[i]=a[i](NR!=1?FS:"")$i} END {for (i=1; i in a; i++) print a[i]}' file

The code will have problem, if some lines don't have same columns.

kurumi's code is still correct in this situation.
# 6  
Old 08-10-2010
Quote:
Originally Posted by rdcwayx
The code will have problem, if some lines don't have same columns.

kurumi's code is still correct in this situation.
Strictly speaking, neither solution correctly handles irregular lengths; properly handling a file with differing row lengths would involve not making any assumptions based on a single row (if row n has more columns than row 1, truncation would occur).

In any case, nothing in the original post implies that rows vary in width. Quite the contrary, the word "matrix" is used, which indicates a rectangular array. Still, it's good that you pointed that out just in case it is a concern.

On a different note, if memory allows, when dealing with a very large dataset, my solution should be much much much faster. Only one instance of awk is needed and the file is only read once. kurumi's will fork-exec 600,000 awk processes and read the file 600,000 times.
# 7  
Old 08-10-2010
Quote:
Originally Posted by alister
On a different note, if memory allows, when dealing with a very large dataset, my solution should be much much much faster. Only one instance of awk is needed and the file is only read once. kurumi's will fork-exec 600,000 awk processes and read the file 600,000 times.
I wrote the code based on what OP has provided, so please don't assume anything else. As for the 600,000 figure i don't know where you got it from. I assume you mean 600,000 lines of records. If that's so, my code will call awk 15 * 600,000 times (for 15 columns of date) i/o, while yours will fill up memory with the whole big file. Because OP has a big file, do you think its advisable to fill everything to memory ? think about it.
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