require 'daru'

df = Daru::DataFrame.new({a: [1,2,3,4,5], b: [10,14,15,17,44]})
df.plot legends: [:a, :b], type: :line do |p,d|
  p.yrange [0,100]
  p.legend true
  d.color "green"
end

require 'daru'
# Calculate statistics of numeric columns
df = Daru::DataFrame.new({
      a: ['foo'  ,  'foo',  'foo',  'foo',  'foo',  'bar',  'bar',  'bar',  'bar'], 
      b: ['one'  ,  'one',  'one',  'two',  'two',  'one',  'one',  'two',  'two'],
      c: ['small','large','large','small','small','large','small','large','small'],
      d: [1,2,2,3,3,4,5,6,7],
      e: [2,4,4,6,6,8,10,12,14],
      f: [10,20,20,30,30,40,50,60,70]
    })
df.mean

# Calculate multiple statistical measures in one shot
df.describe

# Create a multi-indexed DataFrame
tuples = [
  [:a,:one,:bar],
  [:a,:one,:baz],
  [:a,:two,:bar],
  [:a,:two,:baz],
  [:b,:one,:bar],
  [:b,:two,:bar],
  [:b,:two,:baz],
  [:b,:one,:foo],
  [:c,:one,:bar],
  [:c,:one,:baz],
  [:c,:two,:foo],
  [:c,:two,:bar]
]
multi_index = Daru::MultiIndex.new(tuples)

vector_arry1 = [11,12,13,14,11,12,13,14,11,12,13,14]
vector_arry2 = [1,2,3,4,1,2,3,4,1,2,3,4]

order_mi = Daru::MultiIndex.new([
  [:a,:one,:bar],
  [:a,:two,:baz],
  [:b,:two,:foo],
  [:b,:one,:foo]])

df_mi = Daru::DataFrame.new([
  vector_arry1, 
  vector_arry2, 
  vector_arry1, 
  vector_arry2], order: order_mi, index: multi_index)

# Specify complete tuple to choose a single row
df_mi.row[:a, :one,:bar]

# Specify partial tuple to select index hierarchially
df_mi.row[:a]

# See grouped rows with the 'groups' method

df = Daru::DataFrame.new({
  a: %w{foo bar foo bar   foo bar foo foo},
  b: %w{one one two three two two one three},
  c:   [1  ,2  ,3  ,1    ,3  ,6  ,3  ,8],
  d:   [11 ,22 ,33 ,44   ,55 ,66 ,77 ,88]
})
grouped = df.group_by([:a, :b])
grouped.groups

# First group by the columns :a and :b and then calculate mean of the grouped rows.
grouped.mean

grouped.get_group(["foo", "one"])

require 'daru'
sales = Daru::DataFrame.from_csv '/home/sameer/sales-funnel.csv'

sales.pivot_table index: [:manager, :rep]

sales.pivot_table(index: [:manager,:rep], values: :price,vectors: [:product], agg: :sum)

df = Daru::DataFrame.new({
        a: ['ff'  ,  'fwwq',  'efe',  'a',  'efef',  'zzzz',  'efgg',  'q',  'ggf'], 
        b: ['one'  ,  'one',  'one',  'two',  'two',  'one',  'one',  'two',  'two'],
        c: ['small','large','large','small','small','large','small','large','small'],
        d: [-1,2,-2,3,-3,4,-5,6,7],
        e: [2,4,4,6,6,8,10,12,14]
      })
 df.sort([:a,:d], by: {a: lambda {|a,b| a.length <=> b.length }, b: lambda {|a,b| a.abs <=> b.abs }}, ascending: [false, true])