我有这段代码：
def feat_ext_nir(x):
img = loadImage(x['image_name'])
compressed_img = compress_image(16, 16, img[:,:,3])
return compressed_image.ravel()
cloud_feat_nir = cloud_df_samp.apply(feat_ext_nir, axis=1)
cloud_feat_nir.describe()
当我执行时，我收到此错误：
ValueError: Shape of passed values is (2000, 256), indices imply (2000, 5)
应用函数应该返回一个新的数据帧。它从旧数据帧 (cloud_df_samp( 获取的唯一信息是"image_name"列。256 是应该返回的正确列数，但它似乎认为该数字应该与 cloud_df_samp (5( 中的列数相同，我不确定为什么。
谁能告诉我为什么它需要 5 列或我应该采取不同的做法？完整的错误跟踪是：
ValueError: Shape of passed values is (2000, 256), indices imply (2000, 5)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py in
create_block_manager_from_arrays(arrays, names, axes)
4262 blocks = form_blocks(arrays, names, axes)
-> 4263 mgr = BlockManager(blocks, axes)
4264 mgr._consolidate_inplace()
/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py in
__init__(self, blocks, axes, do_integrity_check, fastpath)
2760 if do_integrity_check:
-> 2761 self._verify_integrity()
2762
/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py in
_verify_integrity(self)
2970 if block._verify_integrity and block.shape[1:] !=
mgr_shape[1:]:
-> 2971 construction_error(tot_items, block.shape[1:],
self.axes)
2972 if len(self.items) != tot_items:
/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py in
construction_error(tot_items, block_shape, axes, e)
4232 raise ValueError("Shape of passed values is {0}, indices imply
{1}".format(
-> 4233 passed, implied))
4234
ValueError: Shape of passed values is (2000, 256), indices imply (2000, 5)
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-15-c473d99817c3> in <module>()
4 return compressed_image.ravel()
5
----> 6 cloud_feat_nir = cloud_df_samp.apply(feat_ext_nir, axis=1)
7 cloud_feat_nir.describe()
/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py in apply(self,
func,
axis, broadcast, raw, reduce, args, **kwds)
这是我在
黑暗中拍摄的东西，因为我不确定输入数据的细节，但是这段代码是否如您所愿？
def feat_ext_nir(x):
img = loadImage(x['image_name'])
compressed_img = compress_image(16, 16, img[:,:,3])
return compressed_image.ravel().tolist()
cloud_feat_nir = pd.Series(cloud_df_samp.apply(feat_ext_nir, axis=1))
cloud_feat_nir.describe()