传递值的形状是 (30, 569)，索引意味着 (569, 569)

Posted 2023-03-12

【中文标题】传递值的形状是 (30, 569)，索引意味着 (569, 569)

【英文标题】：Shape of passed values is (30, 569), indices imply (569, 569)

【发布时间】：2018-12-02 13:23:18

【问题描述】：

我正在尝试使用来自 sklean 的癌症数据集，它导入得很好，所有的东西看起来都很好，但是当我尝试创建一个数据框时，它在 tracebak 中显示错误“传递值的形状是 (30, 569)，索引暗示(569, 569)"

from sklearn.datasets import load_breast_cancer
cancer=load_breast_cancer()
cancer.keys()
df_feat = pd.DataFrame(cancer['data'],columns=cancer['target'])

ValueError Traceback（最近一次调用最后一次） C:\Users\Bilal Pharmacist\Anaconda3\lib\site- 包\pandas\core\internals.py 在 create_block_manager_from_blocks（块，轴） 4293 块 = [make_block(values=blocks[0], 第4294章 第4295章

C:\Users\Bilal Pharmacist\Anaconda3\lib\site- 
packages\pandas\core\internals.py in 
make_block(values, placement, klass, ndim, dtype, fastpath)
2718 
2719     return klass(values, ndim=ndim, fastpath=fastpath, 
placement=placement)
2720 

C:\Users\Bilal Pharmacist\Anaconda3\lib\site- 
packages\pandas\core\internals.py in 
__init__(self, values, placement, ndim, fastpath)
114                              'implies %d' % (len(self.values),
115                                              len(self.mgr_locs)))
116 

ValueError: Wrong number of items passed 30, placement implies 569

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-16-24a03a5e14d7> in <module>()
1 df_feat = pd.DataFrame(cancer['data'],columns
2                        =cancer['target'])

C:\Users\Bilal Pharmacist\Anaconda3\lib\site-packages\pandas\core\frame.py in 
__init__(self, data, index, columns, dtype, copy)
304             else:
305                 mgr = self._init_ndarray(data, index, columns, 
dtype=dtype,
306                                          copy=copy)
307         elif isinstance(data, (list, types.GeneratorType)):
308             if isinstance(data, types.GeneratorType):

C:\Users\Bilal Pharmacist\Anaconda3\lib\site-packages\pandas\core\frame.py in 
_init_ndarray(self, values, index, columns, dtype, copy)
481             values = maybe_infer_to_datetimelike(values)
482 
483         return create_block_manager_from_blocks([values], [columns, 
index])
484 
485     @property

C:\Users\Bilal Pharmacist\Anaconda3\lib\site- 
packages\pandas\core\internals.py in 
create_block_manager_from_blocks(blocks, axes)
4301         blocks = [getattr(b, 'values', b) for b in blocks]
4302         tot_items = sum(b.shape[0] for b in blocks)
4303         construction_error(tot_items, blocks[0].shape[1:], axes, e)
4304 
4305 

C:\Users\Bilal Pharmacist\Anaconda3\lib\site- 
packages\pandas\core\internals.py in 
construction_error(tot_items, block_shape, axes, e)
4278         raise ValueError("Empty data passed with indices specified.")
4279     raise ValueError("Shape of passed values is 0, indices imply 
1".format(
4280         passed, implied))
4281 
4282 
ValueError: Shape of passed values is (30, 569), indices imply (569, 569)

【参考方案1】：

错误是因为cancer['data'] 的形状是 (569, 30)（即最多可以接受 30 个列名），而 cancer['target'] 的形状是 (569,)（并且您试图将它们设置为列名）。请改用cancer['feature_names'] 作为columns。我猜cancer['target'] 实际上是一个目标变量 (y)，不应该是列名，而是数据框中的列之一。

这应该可行：

import pandas as pd
from sklearn.datasets import load_breast_cancer

cancer = load_breast_cancer()
df_feat = pd.DataFrame(cancer['data'], columns=cancer['feature_names'])
df_feat['target'] = cancer['target']