从字典中提取数据

Question

I have two tab delimited files, file 1 contains identifiers and file 2 has values related to these identifiers (or say it is a very big dictionary).

file 1

Ronny
Rubby
Suzie
Paul

file 1 has only one column.

file 2

Alistar Barm Cathy Paul Ronny Rubby Suzie Tom Uma Vai Zai
12      13    14   12     11   11   12    23 30  0.34 0.65
1       4     56   23     12   8.9  5.1   1  4    25  3

n number of rows are present in file 2.

what I want, if the identifiers of file 1 are present in file 2, I should have all the values related to it in an another tab delimited file.

Something like this:

Paul Ronny Rubby Suzie
12     11   11   12
23     12   8.9  5.1

Thank you in advance.

Answer 1

NOTE

your example output is NOT correct, since there you have "Ruby" but in your file1 example you had "Rubby" Ruby =/= Rubby

kent$  awk 'NR==FNR{t[$0]++;next}
{if(FNR==1){
        for(i=1;i<=NF;i++)
                if($i in t){
                        v[i]++;
                        printf $i"\t";
                }
        print "";
        }else{
        for(x in v)
                printf $x"\t"
        print "";
}

}' file1 file2

output

Paul    Ronny   Suzie
12      11      12
23      12      5.1

Answer 2

$ awk 'FILENAME~1{a[$0];next};FNR==1{for(i=1;i<=NF;i++)if($i in a)b[i]};{for(j in b)printf("%s\t",$j);print ""}' file{1,2}.txt
Paul    Ronny   Suzie
12      11      12
23      12      5.1

break into multi lines && add whitespace

$ awk '
> FILENAME~1 { a[$0]; next }
> FNR==1 { for(i=1; i<=NF; i++) if($i in a) b[i] }
> { for(j in b) printf("%s\t",$j); print ""}
> ' file{1,2}.txt

Paul    Ronny   Suzie
12      11      12
23      12      5.1

Answer 3

You can use only bash to do it:

FIELDS=`head -1 f2.txt | tr "\t" "\n" | nl -ba | grep -f f1.txt | cut -f1 | tr -d " " | tr "\n" ","`; FIELDS=${FIELDS/%,/}
cut -f$FIELDS f2.txt 
Paul    Ronny   Ruby    Suzie
12  11  11  12
23  12  8.9 5.1

Answer 4

An example in Python that does the work in stream (ie: don't need to load the full file before starting the output):

# read keys
with open('file1', 'r') as fd:
    keys = fd.read().splitlines()

# output keys
print '\t'.join(keys)

# read data file, with header line and content
with open('file2', 'r') as fd:
    headers = fd.readline().split()
    while True:
        line = fd.readline().split()
        if len(line) == 0:
            break
        print '\t'.join([line[headers.index(x)] for x in keys if x in headers])

Output:

$ python test.py 
Ronny   Ruby    Suzie   Paul
11      11      12      12
12      8.9     5.1     23

Answer 5

Perl solution:

#!/usr/bin/perl
use warnings;
use strict;

open my $KEYS, '<', 'file1' or die $!;
my @keys = <$KEYS>;
close $KEYS;
chomp @keys;
my %is_key;
undef @is_key{@keys};

open my $TAB, '<', 'file2' or die $!;
$_ = <$TAB>;
my ($i, @columns);
for (split) {
    push @columns, $i if exists $is_key{$_};
    $i++;
}
do {{
    my @values = split;
    print join("\t", @values[@columns]), "\n";
}} while <$TAB>;

Answer 6

Something like this could probably work, depending on what you want.

use strict;
use warnings;

my %names;
open ( my $nh, '<', $name_file_path ) or die "Could not open '$name_file_path'!";
while ( <$nh> ) { 
    m/^\s*(.*?\S)\s*$/ and $names{ $1 } = 1; 
}
close $nh;

my $coln = -1;
open ( my $dh, '<', $data_file_path ) or die "Could not open '$data_file_path'!";

my ( @name_list, @col_list )
my @names = split /\t/, <$dh>;
foreach my $name ( 0..$#names ) {
    next unless exists $names{ $names[ $name ] };
    push @name_list, $name;
    push @col_list, $coln;
}
local $" = "\t";
print "@name_list\n";
print "@{[ split /\t/ ]}[ @col_list ]\n"  while <$dh>;
close $dh;

Answer 7

This might work for you:

 sed '1{s/\t/\n/gp};d' file2 |
 nl |
 grep -f file1 |
 cut -f1 |
 paste -sd, |
 sed 's/ //g;s,.*,cut -f& /tmp/b,' |
 sh

Explanation:

1. Pivot the column names
2. Number the column names
3. Match the column names against the input file.
4. Ditch the column names retaining the column numbers.
5. Pivot the column numbers separating by , 's.
6. Build a cut command from the comma separated column number list.
7. Run the cut command against the data file.