Question

我有以下功能：

$_GET

然而，我收到错误：

def windows(files):
    x = []
    for my_files in files:
        df = pd.DataFrame(columns=['timestamp', 'time skipped', 'x', 'y', 'z', 'label']).set_index('timestamp')
        with open(os.path.join("/Users", "saqibali", "PycharmProjects", "sensorLogProject", "Data", my_files),
              'rU') as my_file:
            for d in sliding_window(sample_difference(my_file), 50, 25):
                df = df.append(d)
        x.append(df[['x', 'y', 'z']].values.tolist())
    return x

def principal_components():
    pca = PCA(n_components=2)
    training_result = pca.fit_transform(windows(training_files))
    testing_result = pca.transform(windows(test_files))
    return training_result, testing_result

追溯是：

ValueError: setting an array element with a sequence.

以下是/System/Library/Frameworks/Python.framework/Versions/2.7/bin/python2.7 /Users/saqibali/PycharmProjects/sensorLogProject/FeatureSelection/FeatureSelection.py Traceback (most recent call last): File "/Users/saqibali/PycharmProjects/sensorLogProject/FeatureSelection/FeatureSelection.py", line 61, in <module> principal_components() File "/Users/saqibali/PycharmProjects/sensorLogProject/FeatureSelection/FeatureSelection.py", line 56, in principal_components training_result = pca.fit_transform(windows(training_files)) File "/Users/saqibali/Library/Python/2.7/lib/python/site-packages/sklearn/decomposition/pca.py", line 324, in fit_transform U, S, V = self._fit(X) File "/Users/saqibali/Library/Python/2.7/lib/python/site-packages/sklearn/decomposition/pca.py", line 346, in _fit copy=self.copy) File "/Users/saqibali/Library/Python/2.7/lib/python/site-packages/sklearn/utils/validation.py", line 382, in check_array array = np.array(array, dtype=dtype, order=order, copy=copy)的例子：

df

根据下面的评论，我在以下函数中使用time skipped x y z \ timestamp 1970-01-01 00:00:01.501514704 0 -0.055908 -0.729034 -0.645294 1970-01-01 00:00:01.501514704 0 -0.046158 -0.709091 -0.650177 1970-01-01 00:00:01.501514704 0 -0.036469 -0.699554 -0.672668 1970-01-01 00:00:01.501514704 0 -0.027908 -0.695740 -0.678070 1970-01-01 00:00:01.501514704 0 -0.027725 -0.678802 -0.697052 1970-01-01 00:00:01.501514704 0 -0.037491 -0.660660 -0.719605：

pd.readcsv()

我希望有一个np数组，每个元素都是来自每个单独文件的数据帧的np数组版本。例如，我有一个文件和一个数据框来表示它。我想将其转换为np数组，并将其作为自己的元素添加到最终的np数组中。然后，我会为每个文件做同样的事情。我怎么能这样做？

如何创建一个以序列为元素的np数组？

0 个答案: