Method: RedAmber::Group#summarize

Defined in:
lib/red_amber/group.rb

#summarize {|group| ... } ⇒ DataFrame #summarize {|group| ... } ⇒ DataFrame #summarize {|group| ... } ⇒ DataFrame

Summarize Group by aggregation functions from the block.

Overloads:

  • #summarize {|group| ... } ⇒ DataFrame

    Summarize by a function.

    Examples:

    Single function and single variable

    group = penguins.group(:species)
group

# =>
#<RedAmber::Group : 0x000000000000c314>
  species   group_count
  <string>      <uint8>
0 Adelie            152
1 Chinstrap          68
2 Gentoo            124

group.summarize { mean(:bill_length_mm) }

# =>
#<RedAmber::DataFrame : 3 x 2 Vectors, 0x000000000000c364>
  species   mean(bill_length_mm)
  <string>              <double>
0 Adelie                   38.79
1 Chinstrap                48.83
2 Gentoo                    47.5

    Single function only

    group.summarize { mean }

# =>
#<RedAmber::DataFrame : 3 x 6 Vectors, 0x000000000000c350>
  species   mean(bill_length_mm) mean(bill_depth_mm) ... mean(year)
  <string>              <double>            <double> ...   <double>
0 Adelie                   38.79               18.35 ...    2008.01
1 Chinstrap                48.83               18.42 ...    2007.97
2 Gentoo                    47.5               14.98 ...    2008.08

    Yield Parameters:

    • group (Group) —

      passes group object self.

    Yield Returns:

    Returns:

  • #summarize {|group| ... } ⇒ DataFrame

    Summarize by a function.

    Examples:

    Multiple functions

    group.summarize { [min(:bill_length_mm), max(:bill_length_mm)] }

# =>
#<RedAmber::DataFrame : 3 x 3 Vectors, 0x000000000000c378>
  species   min(bill_length_mm) max(bill_length_mm)
  <string>             <double>            <double>
0 Adelie                   32.1                46.0
1 Chinstrap                40.9                58.0
2 Gentoo                   40.9                59.6

    Yield Parameters:

    • group (Group) —

      passes group object self.

    Yield Returns:

    • (Array<DataFrame>) —

      an aggregated DataFrame or an array of aggregated DataFrames.

    Returns:

  • #summarize {|group| ... } ⇒ DataFrame

    Summarize by a function.

    Examples:

    Rename column name by Hash

    group.summarize {
  {
    min_bill_length_mm: min(:bill_length_mm),
    max_bill_length_mm: max(:bill_length_mm),
  }
}

# =>
#<RedAmber::DataFrame : 3 x 3 Vectors, 0x000000000000c378>
  species   min_bill_length_mm max_bill_length_mm
  <string>            <double>           <double>
0 Adelie                  32.1               46.0
1 Chinstrap               40.9               58.0
2 Gentoo                  40.9               59.6

    Yield Parameters:

    • group (Group) —

      passes group object self.

    Yield Returns:

    • (Hash{Symbol, String => DataFrame}) —

      an aggregated DataFrame or an array of aggregated DataFrames. The DataFrame must return only one aggregated column.

    Returns:



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# File 'lib/red_amber/group.rb', line 549

def summarize(*args, &block)
  if block
    agg = instance_eval(&block)
    unless args.empty?
      agg = [agg] if agg.is_a?(DataFrame)
      agg = args.zip(agg).to_h
    end
  else
    agg = args
  end

  case agg
  when DataFrame
    agg
  when Array
    aggregations =
      agg.map do |df|
        v = df.vectors[-1]
        [v.key, v]
      end
    agg[0].assign(aggregations)
  when Hash
    aggregations =
      agg.map do |key, df|
        aggregated_keys = df.keys - @group_keys
        if aggregated_keys.size > 1
          message =
            "accept only one column from the Hash: #{aggregated_keys.join(', ')}"
          raise GroupArgumentError, message
        end

        v = df.vectors[-1]
        [key, v]
      end
    agg.values[-1].drop(-1).assign(aggregations)
  else
    raise GroupArgumentError, "Unknown argument: #{agg}"
  end
end