获取切片：“(TypeError( None，None，None)，0)”是无效的键

Question

尝试绘制k-NN分类器的决策边界，但无法获得TypeError: '(slice(None, None, None), 0)' is an invalid key

h = .01  # step size in the mesh

# Create color maps
cmap_light = ListedColormap(['#FFAAAA', '#AAFFAA', '#AAAAFF','#AFAFAF'])
cmap_bold  = ListedColormap(['#FF0000', '#00FF00', '#0000FF','#AFAFAF'])

for weights in ['uniform', 'distance']:
    # we create an instance of Neighbours Classifier and fit the data.
    clf = KNeighborsClassifier(n_neighbors=6, weights=weights)
    clf.fit(X_train, y_train)

    # Plot the decision boundary. For that, we will assign a color to each
    # point in the mesh [x_min, x_max]x[y_min, y_max].
    x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
    y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
    xx, yy = np.meshgrid(np.arange(x_min, x_max, h),
                         np.arange(y_min, y_max, h))
    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])

    # Put the result into a color plot
    Z = Z.reshape(xx.shape)
    plt.figure()
    plt.pcolormesh(xx, yy, Z, cmap=cmap_light)

    # Plot also the training points
    plt.scatter(X[:, 0], X[:, 1], c=y, cmap=cmap_bold)
    plt.xlim(xx.min(), xx.max())
    plt.ylim(yy.min(), yy.max())
    plt.title("4-Class classification (k = %i, weights = '%s')"
              % (n_neighbors, weights))

plt.show()

我在运行时得到了这个，不太确定这意味着什么我不认为clf.fit有问题，但我不确定

  TypeError                                 Traceback (most recent call last)
<ipython-input-394-bef9b05b1940> in <module>
     12         # Plot the decision boundary. For that, we will assign a color to each
     13         # point in the mesh [x_min, x_max]x[y_min, y_max].
---> 14         x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
     15         y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
     16         xx, yy = np.meshgrid(np.arange(x_min, x_max, h),

~\Miniconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2925             if self.columns.nlevels > 1:
   2926                 return self._getitem_multilevel(key)
-> 2927             indexer = self.columns.get_loc(key)
   2928             if is_integer(indexer):
   2929                 indexer = [indexer]

~\Miniconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2654                                  'backfill or nearest lookups')
   2655             try:
-> 2656                 return self._engine.get_loc(key)
   2657             except KeyError:
   2658                 return self._engine.get_loc(self._maybe_cast_indexer(key))

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

TypeError: '(slice(None, None, None), 0)' is an invalid key

Answer 1

由于您尝试以数组的形式直接访问，因此会遇到这个问题。试试这个：

from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values = np.nan, strategy = 'mean',verbose=0)
imputer = imputer.fit(X.iloc[:, 1:3])
X.iloc[:, 1:3] = imputer.transform(X.iloc[:, 1:3])

使用iloc/loc可以解决此问题。

Answer 2

您需要使用iloc/loc来访问df。尝试将iloc添加到X，以便X.iloc[:, 0]

Answer 3

我遇到了以下相同的问题

X = dataset.iloc[:,:-1]

然后我添加了.values属性，之后它就可以正常工作了

X = dataset.iloc[:,:-1].values