ValueError：传递的项目数量错误-含义和建议？

Question

我收到错误消息： ValueError: Wrong number of items passed 3, placement implies 1，并且我正在努力找出可能在哪里以及如何开始解决该问题。

我不太了解错误的含义；这使我很难进行故障排除。我还在Jupyter Notebook中包含了触发错误的代码块。

数据很难附加。因此，我不需要任何人尝试为我重新创建此错误。我只是在寻找有关如何解决此错误的反馈。

KeyError                                  Traceback (most recent call last)
C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance)
   1944             try:
-> 1945                 return self._engine.get_loc(key)
   1946             except KeyError:

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12368)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)()

KeyError: 'predictedY'

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\internals.py in set(self, item, value, check)
   3414         try:
-> 3415             loc = self.items.get_loc(item)
   3416         except KeyError:

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance)
   1946             except KeyError:
-> 1947                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   1948

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12368)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)()

KeyError: 'predictedY'

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-95-476dc59cd7fa> in <module>()
     26     return gp, results
     27 
---> 28 gp_dailyElectricity, results_dailyElectricity = predictAll(3, 0.04, trainX_dailyElectricity, trainY_dailyElectricity, testX_dailyElectricity, testY_dailyElectricity, testSet_dailyElectricity, 'Daily Electricity')

<ipython-input-95-476dc59cd7fa> in predictAll(theta, nugget, trainX, trainY, testX, testY, testSet, title)
      8 
      9     results = testSet.copy()
---> 10     results['predictedY'] = predictedY
     11     results['sigma'] = sigma
     12

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\frame.py in __setitem__(self, key, value)
   2355         else:
   2356             # set column
-> 2357             self._set_item(key, value)
   2358 
   2359     def _setitem_slice(self, key, value):

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\frame.py in _set_item(self, key, value)
   2422         self._ensure_valid_index(value)
   2423         value = self._sanitize_column(key, value)
-> 2424         NDFrame._set_item(self, key, value)
   2425 
   2426         # check if we are modifying a copy

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\generic.py in _set_item(self, key, value)
   1462 
   1463     def _set_item(self, key, value):
-> 1464         self._data.set(key, value)
   1465         self._clear_item_cache()
   1466

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\internals.py in set(self, item, value, check)
   3416         except KeyError:
   3417             # This item wasn't present, just insert at end
-> 3418             self.insert(len(self.items), item, value)
   3419             return
   3420

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\internals.py in insert(self, loc, item, value, allow_duplicates)
   3517 
   3518         block = make_block(values=value, ndim=self.ndim,
-> 3519                            placement=slice(loc, loc + 1))
   3520 
   3521         for blkno, count in _fast_count_smallints(self._blknos[loc:]):

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\internals.py in make_block(values, placement, klass, ndim, dtype, fastpath)
   2516                      placement=placement, dtype=dtype)
   2517 
-> 2518     return klass(values, ndim=ndim, fastpath=fastpath, placement=placement)
   2519 
   2520 # TODO: flexible with index=None and/or items=None

C:\Users\brennn1\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\internals.py in __init__(self, values, placement, ndim, fastpath)
     88             raise ValueError('Wrong number of items passed %d, placement '
     89                              'implies %d' % (len(self.values),
---> 90                                              len(self.mgr_locs)))
     91 
     92     @property

ValueError: Wrong number of items passed 3, placement implies 1

我的代码如下：

def predictAll(theta, nugget, trainX, trainY, testX, testY, testSet, title):

    gp = gaussian_process.GaussianProcess(theta0=theta, nugget =nugget)
    gp.fit(trainX, trainY)

    predictedY, MSE = gp.predict(testX, eval_MSE = True)
    sigma = np.sqrt(MSE)

    results = testSet.copy()
    results['predictedY'] = predictedY
    results['sigma'] = sigma

    print ("Train score R2:", gp.score(trainX, trainY))
    print ("Test score R2:", sklearn.metrics.r2_score(testY, predictedY))

    plt.figure(figsize = (9,8))
    plt.scatter(testY, predictedY)
    plt.plot([min(testY), max(testY)], [min(testY), max(testY)], 'r')
    plt.xlim([min(testY), max(testY)])
    plt.ylim([min(testY), max(testY)])
    plt.title('Predicted vs. observed: ' + title)
    plt.xlabel('Observed')
    plt.ylabel('Predicted')
    plt.show()

    return gp, results

gp_dailyElectricity, results_dailyElectricity = predictAll(3, 0.04, trainX_dailyElectricity, trainY_dailyElectricity, testX_dailyElectricity, testY_dailyElectricity, testSet_dailyElectricity, 'Daily Electricity')

Answer 1

通常，该错误ValueError: Wrong number of items passed 3, placement implies 1表明您正在尝试将过多的鸽子放到过少的鸽子洞中。在这种情况下，等式右边的值

results['predictedY'] = predictedY

正在尝试将3个“事物”放入只能容纳一个的容器中。由于左侧是数据框列，并且可以在该（列）维度上接受多个项目，因此您应该看到另一个维度上的项目太多。

在这里，看来您正在使用sklearn进行建模，这是从哪里来的gaussian_process.GaussianProcess()（我想是，但请纠正我，如果这是错误的，请修改问题）。

现在，您在这里生成 y的 预测值：

predictedY, MSE = gp.predict(testX, eval_MSE = True)

但是，正如我们从GaussianProcess的文档中看到的那样，它predict()返回两个项目。第一个是
y ，它 像数组 （强调我的）。这意味着它可以具有多个维度，或者，对于像我这样的头脑笨拙的人而言，它可以具有多个列-
请注意，它可以返回(n_samples, n_targets)，取决于testX（可能是(1000, 3)选择数字）
。因此，您predictedY可能有3列。

如果是这样，当您尝试将带有三个“列”的内容放入单个数据框列时，您将传递3个项目，其中只有1个适合。