CSV, with and without headers

Headerless CSV on input or output

Sometimes we get CSV files which lack a header. For example (data/headerless.csv):

 cat data/headerless.csv
 John,23,present
 Fred,34,present
 Alice,56,missing
 Carol,45,present

You can use Miller to add a header. The --implicit-csv-header applies positionally indexed labels:

 mlr --csv --implicit-csv-header cat data/headerless.csv
 1,2,3
 John,23,present
 Fred,34,present
 Alice,56,missing
 Carol,45,present

Following that, you can rename the positionally indexed labels to names with meaning for your context. For example:

 mlr --csv --implicit-csv-header label name,age,status data/headerless.csv
 name,age,status
 John,23,present
 Fred,34,present
 Alice,56,missing
 Carol,45,present

Likewise, if you need to produce CSV which is lacking its header, you can pipe Miller’s output to the system command sed 1d, or you can use Miller’s --headerless-csv-output option:

 head -5 data/colored-shapes.dkvp | mlr --ocsv cat
 color,shape,flag,i,u,v,w,x
 yellow,triangle,1,11,0.6321695890307647,0.9887207810889004,0.4364983936735774,5.7981881667050565
 red,square,1,15,0.21966833570651523,0.001257332190235938,0.7927778364718627,2.944117399716207
 red,circle,1,16,0.20901671281497636,0.29005231936593445,0.13810280912907674,5.065034003400998
 red,square,0,48,0.9562743938458542,0.7467203085342884,0.7755423050923582,7.117831369597269
 purple,triangle,0,51,0.4355354501763202,0.8591292672156728,0.8122903963006748,5.753094629505863
 head -5 data/colored-shapes.dkvp | mlr --ocsv --headerless-csv-output cat
 yellow,triangle,1,11,0.6321695890307647,0.9887207810889004,0.4364983936735774,5.7981881667050565
 red,square,1,15,0.21966833570651523,0.001257332190235938,0.7927778364718627,2.944117399716207
 red,circle,1,16,0.20901671281497636,0.29005231936593445,0.13810280912907674,5.065034003400998
 red,square,0,48,0.9562743938458542,0.7467203085342884,0.7755423050923582,7.117831369597269
 purple,triangle,0,51,0.4355354501763202,0.8591292672156728,0.8122903963006748,5.753094629505863

Lastly, often we say “CSV” or “TSV” when we have positionally indexed data in columns which are separated by commas or tabs, respectively. In this case it’s perhaps simpler to just use NIDX format which was designed for this purpose. (See also File formats.) For example:

 mlr --inidx --ifs comma --oxtab cut -f 1,3 data/headerless.csv
 1 John
 3 present

 1 Fred
 3 present

 1 Alice
 3 missing

 1 Carol
 3 present

Headerless CSV with duplicate field values

Miller is (by central design) a mapping from name to value, rather than integer position to value as in most tools in the Unix toolkit such as sort, cut, awk, etc. So given input Yea=1,Yea=2 on the same input line, first Yea=1 is stored, then updated with Yea=2. This is in the input-parser and the value Yea=1 is unavailable to any further processing. The following example line comes from a headerless CSV file and includes 5 times the string (value) 'NA':

 ag '0.9' nas.csv | head -1
 2:-349801.10097848,4537221.43295653,2,1,NA,NA,NA,NA,NA

The repeated 'NA' strings (values) in the same line will be treated as fields (columns) with same name, thus only one is kept in the output.

This can be worked around by telling mlr that there is no header row by using --implicit-csv-header or changing the input format by using nidx like so:

ag '0.9' nas.csv | mlr --n2c --fs "," label xsn,ysn,x,y,t,a,e29,e31,e32 then head

Regularizing ragged CSV

Miller handles compliant CSV: in particular, it’s an error if the number of data fields in a given data line don’t match the number of header lines. But in the event that you have a CSV file in which some lines have less than the full number of fields, you can use Miller to pad them out. The trick is to use NIDX format, for which each line stands on its own without respect to a header line.

 cat data/ragged.csv
 a,b,c
 1,2,3
 4,5
 6,7,8,9
 mlr --from data/ragged.csv --fs comma --nidx put '
   @maxnf = max(@maxnf, NF);
   @nf = NF;
   while(@nf < @maxnf) {
     @nf += 1;
     $[@nf] = ""
   }
 '
 a,b,c
 1,2,3
 4,5
 6,7,8,9

or, more simply,

 mlr --from data/ragged.csv --fs comma --nidx put '
   @maxnf = max(@maxnf, NF);
   while(NF < @maxnf) {
     $[NF+1] = "";
   }
 '
 a,b,c
 1,2,3
 4,5
 6,7,8,9