"setting an array element with a sequence" error could be improved.

This is a bit of a nitpick, but I think this would improve user-friendlyness. Currently np.asarray([[1, 2], [2, 3, 4]], dtype=np.float) yields “setting an array element with a sequence.”

I think it would be more helpful if it yielded something like “Can’t create array from lists. Column length %d of column %d doesn’t match column length %d.”

I imagine the error bubbles up from somewhere deep in the code and makes perfect sense where it is raised. It is just something that comes up a lot, and a more friendly and / or informative message could be helpful. So maybe we could catch it further up and include more information if possible.

[argriffing]

Re-opening in light of https://github.com/numpy/numpy/issues/5303#issuecomment-152354367.

There are a few different but related issues. One issue is explicit vs. implicit dtype=object array creation. The github issue for that is https://github.com/numpy/numpy/issues/5353 (also https://github.com/numpy/numpy/issues/6070, I see). Another issue is the possibility to create ndarrays of objects with conformable shapes without automatically peeking into those objects and trying to figure out what the user wants. That issue is https://github.com/numpy/numpy/issues/5933.

We could keep this issue open, for improving the error message for specific cases like np.asarray([[1, 2], [2, 3, 4]], dtype=np.float). If the error message could be special-cased for np.asarray(a, dtype=b) even for really specific kinds of a and b, this could be useful. For example, maybe a special case could apply when a is a Python list recursively containing more lists and numeric values (and maybe only when the all leaves of the tree defined by the list all share the same depth?) and where b is some simple numeric dtype.

Here are a few more cases that give the same error message, but which may or may not be in the scope of this issue.

>>> np.array([[[1, 2], [3, 4], [5, 6]], [[1], [2], [3]]], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

>>> np.array([[1, 2, 3], 4], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

>>> np.array([(1, 2), (2, 3, 4)], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

[Chokerino]

I have a 3-D numpy array and im getting the same error if i try to change its dataype to float. Also, if i try using the same data without changing anything with sklearn I get the same error while if I use it with keras, I get ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray).. I am trying to do a machine learning task and my current dataset is a numpy array of shape (556,1) and for every sample it have 27 features so (27,1) and each feature has variable length and the same feature might have a different shape for different samples. Any help on how I get fix this?