Keeping float value decimal places in an awk script-CodePudding

I have this line using awk:

$ awk '{
                 for (i=1;i<=NF;i  ){
                   if ($i 0 != $i)
                     $i = temp[i] 0.00
                   temp[i]=$i 0.00
                }}1'

In short, this converts every word to the last seen number of that column.

THE PROBLEM

The issue is that the decimals place of every value that comes out of $i = temp[i] 0.00 loses its decimals precision.

For example,

-ERROR -1.57 -2.02 
-2.10 2.70 ERROR
-4.70 ERROR -0.52 
-2.20 ERROR -0.02 
-2.20 -1.50 ERROR

Turns into:

0 -1.57 -2.02 
-2.10 2.70 -2.02
-4.70 2.7 -0.52 
-2.20 2.7 -0.02 
-2.20 -1.50 -0.02

2.70 would become 2.7 and so every word that directly follows 2.70 would not be turned into 2.70, but instead into 2.7. How can you force awk to save a float value to a set amount of decimal places?

Obviously, 0.00 didn't help.

CodePudding user response：

Refrain from performing math on the values which in turn disables awk from making decisions on how many digits of accuracy to maintain; instead, just save each value as is (effectively save as a string).

Consider:

$ printf "1 1.1 1.02 1.003 1.0004 1.00005\na b c d e f\n" 
1 1.1 1.02 1.003 1.0004 1.00005
a b c d e f

A few tweaks to OP's current awk code:

$ printf "1 1.1 1.02 1.003 1.0004 1.00005\na b c d e f\n" | awk '
{ for (i=1;i<=NF;i  ){
      if ($i 0 != $i)
         $i = (i in temp ? temp[i] : 0)
      temp[i]=$i
   }
} 1'
1 1.1 1.02 1.003 1.0004 1.00005
1 1.1 1.02 1.003 1.0004 1.00005

Coming back to OP's sample data ...

Adding some more lines to the sample data set:

$ cat sample.dat
-ERROR -1.57 -2.02
-2.10 2.70 ERROR
-4.70 ERROR -0.52
-2.20 ERROR -0.02
-2.20 -1.50 ERROR
-3.333 0.1234 -0.02
ERROR ERROR ERROR
-2.10 2.70 ERROR
-4.70 ERROR -0.52

Running the modified awk code:

awk '
{ for (i=1;i<=NF;i  ){
      if ($i 0 != $i)
         $i = (i in temp ? temp[i] : 0)
      temp[i]=$i
   }
}1' sample.dat

This generates:

0 -1.57 -2.02
-2.10 2.70 -2.02
-4.70 2.70 -0.52
-2.20 2.70 -0.02
-2.20 -1.50 -0.02
-3.333 0.1234 -0.02
-3.333 0.1234 -0.02
-2.10 2.70 -0.02
-4.70 2.70 -0.52

If this doesn't address the issue then we'll need to see more sample data that more accurately reproduces the issue.