loop_count: 3

contexts:
  - name: HEAD
    prelude: |
      $LOAD_PATH.unshift(File.expand_path('lib'))
  - name: 0.3.0
    gems:
      red_amber: 0.3.0
  - name: 0.2.2
    gems:
      red_amber: 0.2.2

prelude: |
  require 'red_amber'
  require 'datasets-arrow'

  ds = Datasets::Rdatasets.new('nycflights13', 'flights')
  df = RedAmber::DataFrame.new(ds.to_arrow)
    .assign(:flight) { flight.map(&:to_s) }

  slicer = df[:distance] > 1000
  distance_km = df[:distance] * 1.852

benchmark:
  'G01: sum distance by destination': |
    df.group(:dest).sum(:distance)

  'G02: sum arr_delay by month and day': |
    df.group(:month, :day).sum(:arr_delay)

  'G03: sum arr_delay, mean distance by flight': |
    df.group(:flight) { [sum(:arr_delay), mean(:distance)] }

  'G04: mean air_time, distance by flight': |
    df.group(:flight).mean(:air_time, :distance)

  'G05: sum dep_delay, arr_delay by carrer': |
    df.group(:carrier).sum(:dep_delay, :arr_delay)