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    Asura Enkhbayar
    @Bubblbu
    ghsd
    Ghada
    @hackora
    salut
    Andreas Pizsa
    @AndreasPizsa
    paste it here ^^
    joaopalotti
    @joaopalotti
    hi!
    @all hey
    Apostolos
    @apas
    @hermes11
    Asura Enkhbayar
    @Bubblbu
    Asura Enkhbayar
    @Bubblbu
    for idx, recipe in enumerate(final_recipes):
    for ingredient in recipe['ingredients']:
    ings = [1 if ingredient['name'] == list_element else 0 for list_element in ingredient_list]
    row = [recipe['name'], recipe['rating']]
    row.extend(ings)
    df.loc[idx] = row

    columns = [u'Name', u'Rating']
    columns.extend(ingredient_list)

    df = pd.DataFrame(columns = columns)

    Apostolos
    @apas
    6250fd4e4353f701061f6d5bcdabb179
    56b3dee75b03d8c63b8adbd1a1e5bc29
    117c6b90f9fdc0edafd53810d6b578a8
    a4b8f017c7b74967468760e626c10f14
    Apostolos
    @apas
    Apostolos
    @apas
    dvxXQdV01863Bu3w573HoXq5LZKWl56D
    Ghada
    @hackora
    @joaopalotti dvx310tYY7xiDRirvoMoSD6h7Gr2mRt2
    joaopalotti
    @joaopalotti
    Thanks guy!
    Ghada
    @hackora
    you're welcome
    joaopalotti
    @joaopalotti
    I will be late =(
    Apostolos
    @apas
    @AndreasPizsa http://flowtype.org
    Ghada
    @hackora
    i'll be there in 30 min
    Andreas Pizsa
    @AndreasPizsa
    @hermes11 :+1: see you in a bit!
    Asura Enkhbayar
    @Bubblbu
    Ghada
    @hackora
    @AndreasPizsa 'g': (1.),
    'gram': (1.),
    'kg': (1000.),
    'kilo': (1000.),
    'kilogram': (1000.),
    'lb': (453.592.),
    'pound': (453.592.),
    'ounce': (28.349.),
    'oz': (28.349.),
    'grain': (0.064.),
    'gr': (0.064.),
    'cup' : (150.),
    'tablespoon': (12.),
    'teaspoon': (3.)
    green instead of black maybe
    joaopalotti
    @joaopalotti
    def norm(s):
    if not s:
    return ""
    s = re.sub('[\W_]+', ' ', s)
    s = re.sub("\d+", '', s)
    s = re.sub(' +',' ', s)
    return s.lower()
    joaopalotti
    @joaopalotti
    cols = set(data.columns.values)
    cols = np.array( list(cols - set(['Name', 'Rating', 'Health'])) )
    Asura Enkhbayar
    @Bubblbu
    from sklearn.externals import joblib
    model_clone = joblib.load('my_model.pkl')
    Andreas Pizsa
    @AndreasPizsa
    congrats guys!!1!
    Apostolos
    @apas
    it was epic :)