将 Pandas、Numpy 和 Tensorflow 中的 2-D 变量转换为 1-D 变量

Question

我正在使用tensorflow2.1设计一个股票预测程序。我的变量在我的程序结束时应该是一个二维变量，但只是一个一维。返回的错误是：predictions

Traceback (most recent call last):

  File "/Users/owner/Desktop/algo/predict.py", line 120, in <module>

    valid['Predictions'] = predictions

  File "/usr/local/lib/python3.7/site-packages/pandas/core/frame.py", line 3487, in __setitem__

    self._set_item(key, value)

  File "/usr/local/lib/python3.7/site-packages/pandas/core/frame.py", line 3563, in _set_item

    self._ensure_valid_index(value)

  File "/usr/local/lib/python3.7/site-packages/pandas/core/frame.py", line 3540, in _ensure_valid_index

    value = Series(value)

  File "/usr/local/lib/python3.7/site-packages/pandas/core/series.py", line 314, in __init__

    data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)

  File "/usr/local/lib/python3.7/site-packages/pandas/core/internals/construction.py", line 729, in sanitize_array

    raise Exception("Data must be 1-dimensional")

Exception: Data must be 1-dimensional

这个错误是由于Pandas，Numpy还是Tensorflow造成的？可以做些什么来满足这个错误陈述？我一直在GitHub上寻求帮助，但他们将我重定向到Stackoverflow。

Answer 1

更改为 。错误应该消失。valid['Predictions'] = predictionsvalid['Predictions'] = np.squeeze(predictions)

Answer 2

您的预测是列表的列表。print(predictions)结果[[1597.7726]]您可以使用numpy的挤压方法...print(predictions.shape)predictions = np.squeeze(predictions)...或使用简单的解决方法...print(predictions.shape)predictions = predictions[0]...以解决错误。