• Check out https://setosa.io/blog/2014/08/03/csv-fingerprints/

$ java edu.rpi.tw.data.csv.util.BinaryTable
usage: BinaryTable <file> [--comment-character char] [--header-line headerLineNumber] [--delimiter delimiter]
                          [--column-stop colNumber]
see https://github.com/timrdf/csv2rdf4lod-automation/wiki/Characterizing-table-completeness

• Column numbers along top,
• Row sparseness pattern indicated with periods (.),
• Pattern occurrence frequency along right,
• completeness indication along bottom
  • | indicates that all cells in this column have values in all rows;
  • _ indicates that come cells in this column are missing values).

The following sample output produced when BinaryTable is applied to geonames US zip codes. One of the things this says is "41,940 rows have values for all cells except for cells 8 and 9. Three rows have values for all cells except for cells 6, 7, 8 and 9.".

bash-3.2$ java edu.rpi.tw.data.csv.util.BinaryTable source/US.txt --header-line 0 --delimiter '\t'
123456789012
.....    ...| 3
.......  .. | 41940
..... .  .. | 1
... .    .. | 4
.......  ...| 147
... ...  .. | 10
.....    .. | 1408
......   .. | 84
... . .  .. | 5
|||_|____||_

• Generating enhancement parameters and FAQ for how to use edu.rpi.tw.data.csv.impl.CSVHeaders
• Script: cr test conversion.sh uses this to gray out columns that are missing values, which helps design the enhancement parameters for geonames.
• Example: White Hosue Visitor Access Records
• Generating enhancement parameters