Raku Data::Summarizers

This Raku package has data summarizing functions for different data structures that are coercible to full arrays.

The supported data structures (so far) are:

• 1D Arrays

• 1D Lists

• Positional-of-hashes

• Positional-of-arrays

Usage examples

Setup

Here we load the Raku modules Data::Generators, Data::Reshapers and this module, Data::Summarizers:

use Data::Generators;
use Data::Reshapers;
use Data::Summarizers;

Summarize vectors

Here we generate a numerical vector, place some NaN's or Whatever's in it:

my @vec = [^1001].roll(12);
@vec = @vec.append( [NaN, Whatever, Nil]);
@vec .= pick(@vec.elems);
@vec

Here we summarize the vector generated above:

records-summary(@vec)

Summarize tabular datasets

Here we generate a random tabular dataset with 16 rows and 3 columns and display it:

srand(32);
my $tbl = random-tabular-dataset(16,
                                 <Pet Ref Code>,
                                 generators=>[random-pet-name(4), -> $n { ((^20).rand xx $n).List }, random-string(6)]);
to-pretty-table($tbl)

Remark: The values of the column "Pet" is sampled from a set of four pet names, and the values of the column and "Code" is sampled from a set of 6 strings.

Here we summarize the tabular dataset generated above:

records-summary($tbl)

Summarize collections of tabular datasets

Here is a hash of tabular datasets:

my %group = group-by($tbl, 'Pet');

%group.pairs.map({ say("{$_.key} =>"); say to-pretty-table($_.value) });

Here is the summary of that collection of datasets:

records-summary(%group)

Skim

TBD...

TODO

• User specified NA marker

• Tabular dataset summarization tests

• Skimmer

• Peek-er

References

Functions, repositories

[AAf1] Anton Antonov, RecordsSummary, (2019), Wolfram Function Repository.