import pandas as pd

uri = "https://gist.githubusercontent.com/guilhermesilveira/2d2efa37d66b6c84a722ea627a897ced/raw/10968b997d885cbded1c92938c7a9912ba41c615/tracking.csv"
dados = pd.read_csv(uri)

mapa = {
    "home" : "principal",
    "how_it_works" : "como_funciona",
    "contact" : "contato",
    "bought" : "comprou"
}

dados =  dados.rename(columns = mapa)

x = dados[["principal", "como_funciona", "contato"]]
y = [["comprou"]]

treino_x = x[:75]
treino_y = y[:75]
teste_x = x[75:]
teste_y = y[75:]


print("Treinaremos com %d elementos e testaremos com %d elementos" % (len(treino_x), len(teste_x)))

teste_y.shape

AttributeError                            Traceback (most recent call last)
<ipython-input-15-d90e376a4499> in <module>()
----> 1 teste_y.shape

AttributeError: 'list' object has no attribute 'shape'

from sklearn.svm import LinearSVC

modelo = LinearSVC()
modelo.fit(treino_x, treino_y)

/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py:760: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
  y = column_or_1d(y, warn=True)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-12-359cb4b569f7> in <module>()
      2 
      3 modelo = LinearSVC()
----> 4 modelo.fit(treino_x, treino_y)

2 frames
/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py in check_consistent_length(*arrays)
    210     if len(uniques) > 1:
    211         raise ValueError("Found input variables with inconsistent numbers of"
--> 212                          " samples: %r" % [int(l) for l in lengths])
    213 
    214 

ValueError: Found input variables with inconsistent numbers of samples: [75, 1]

O código apresentou estes dois erros e não se como resolver...