data_frame_demo

data_frame (master): plain_frame 
Loading Data Frame version: 0.1.8
>> df = DataFrame.from_csv('http://archive.ics.uci.edu/ml/machine-learning-databases/forest-fires/forestfires.csv')
=> DataFrame rows: 517 labels: [:x, :y, :month, :day, :ffmc, :dmc, :dc, :isi, :temp, :rh, :wind, :rain, :area]
>> df.month.categories                                                                                             
=> ["apr", "aug", "dec", "feb", "jan", "jul", "jun", "mar", "may", "nov", "oct", "sep"]
>> df.wind.categories                                                                                              
=> [0.4, 0.9, 1.3, 1.8, 2.2, 2.7, 3.1, 3.6, 4, 4.5, 4.9, 5.4, 5.8, 6.3, 6.7, 7.2, 7.6, 8, 8.5, 8.9, 9.4]
>> df.wind.add_category(0) {|e| e <= 5}                                                                            
=> {0=>#<Proc:0x0259cdf4@(irb):4>}
>> df.wind.add_category(1) {|e| e > 5}                                                                             
=> {1=>#<Proc:0x025902ac@(irb):5>}
>> df.wind.categories
=> [0, 1]
>> df.duplicate!(:wind)
=> true
>> df.rename!(:wind_categories, :wind1)
=> :wind_categories
>> df.categorize!(:wind_categories)
=> false
>> df.wind.uniq
=> [6.7, 0.9, 1.3, 4, 1.8, 5.4, 3.1, 2.2, 7.2, 4.5, 4.9, 2.7, 5.8, 3.6, 7.6, 6.3, 8.9, 8.5, 9.4, 0.4, 8]
>> df.wind_categories.uniq
=> [6.7, 0.9, 1.3, 4, 1.8, 5.4, 3.1, 2.2, 7.2, 4.5, 4.9, 2.7, 5.8, 3.6, 7.6, 6.3, 8.9, 8.5, 9.4, 0.4, 8]
>> df.wind.categories
=> [0.4, 0.9, 1.3, 1.8, 2.2, 2.7, 3.1, 3.6, 4, 4.5, 4.9, 5.4, 5.8, 6.3, 6.7, 7.2, 7.6, 8, 8.5, 8.9, 9.4]