helpTextVerbose
auto helpTextVerbose = 
q"EOS
Synopsis: tsv-summarize [options] file [file...]
tsv-summarize reads tabular data files (tab-separated by default), tracks
field values for each unique key, and runs summarization algorithms. Consider
the file data.tsv:
   make    color   time
   ford    blue    131
   chevy   green   124
   ford    red     128
   bmw     black   118
   bmw     black   126
   ford    blue    122
The min and average times for each make is generated by the command:
   $ tsv-summarize --header --group-by 1 --min 3 --mean 3 data.tsv
This produces:
   make   time_min time_mean
   ford   122      127
   chevy  124      124
   bmw    118      122
Using '--group 1,2' will group by both 'make' and 'color'. Omitting the
'--group-by' entirely summarizes fields for full file.
The program tries to generate useful headers, but custom headers can be
specified. Example (using -g and -H shortcuts for --header and --group-by):
   $ tsv-summarize -H -g 1 --min 3:fastest --mean 3:average data.tsv
Most operators take custom headers in a similarly way, generally following:
  --<operator-name> FIELD[:header]
Operators can be specified multiple times. They can also take multiple
fields (though not when a custom header is specified). Examples:
  --median 2,3,4
  --median 2-5,7-11
The quantile operator requires one or more probabilities after the fields:
  --quantile 2:0.25                // Quantile 1 of field 2
  --quantile 2-4:0.25,0.5,0.75     // Q1, Median, Q3 of fields 2, 3, 4
Summarization operators available are:
  count       range        mad            values
  retain      sum          var            unique-values
  first       mean         stddev         unique-count
  last        median       mode           missing-count
  min         quantile     mode-count     not-missing-count
  max
Numeric values are printed to 12 significant digits by default. This can be
changed using the '--p|float-precision' option. If six or less it sets the
number of significant digits after the decimal point. If greater than six it
sets the total number of significant digits.
Calculations hold onto the minimum data needed while reading data. A few
operations like median keep all data values in memory. These operations will
start to encounter performance issues as available memory becomes scarce. The
size that can be handled effectively is machine dependent, but often quite
large files can be handled.
Operations requiring numeric entries will signal an error and terminate
processing if a non-numeric entry is found.
Missing values are not treated specially by default, this can be changed
using the '--x|exclude-missing' or '--r|replace-missing' option. The former
turns off processing for missing values, the latter uses a replacement value.
Options:
EOS";
  
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