Python ValueError：传递的项目数量错误 - 含义和建议？
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ValueError: Wrong number of items passed - Meaning and suggestions?
提问by Gary
I am receiving the error:
ValueError: Wrong number of items passed 3, placement implies 1, and I am struggling to figure out where, and how I may begin addressing the problem.
我收到错误：
ValueError: Wrong number of items passed 3, placement implies 1，我正在努力弄清楚从哪里开始，以及如何开始解决这个问题。
I don't really understand the meaning of the error; which is making it difficult for me to troubleshoot. I have also included the block of code that is triggering the error in my Jupyter Notebook.
我不太明白错误的含义；这让我很难排除故障。我还在我的 Jupyter Notebook 中包含了触发错误的代码块。
The data is tough to attach; so I am not looking for anyone to try and re-create this error for me. I am just looking for some feedback on how I could address this error.
数据很难附加；所以我不是在寻找任何人来尝试为我重新创建这个错误。我只是在寻找有关如何解决此错误的一些反馈。
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
My code is as follows:
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')
回答by Savage Henry
In general, the error ValueError: Wrong number of items passed 3, placement implies 1suggests that you are attempting to put too many pigeons in too few pigeonholes. In this case, the value on the right of the equation
一般而言，该错误ValueError: Wrong number of items passed 3, placement implies 1表明您试图将过多的鸽子放入过少的鸽笼中。在这种情况下，等式右边的值
results['predictedY'] = predictedY
results['predictedY'] = predictedY
is trying to put 3 "things" into a container that allows only one. Because the left side is a dataframe column, and can accept multiple items on that (column) dimension, you should see that there are too many items on another dimension.
试图将 3 个“东西”放入一个只允许一个的容器中。由于左侧是数据框列，并且可以接受该（列）维度上的多个项目，因此您应该看到另一个维度上的项目太多。
Here, it appears you are using sklearn for modeling, which is where gaussian_process.GaussianProcess()is coming from (I'm guessing, but correct me and revise the question if this is wrong).
在这里，您似乎正在使用 sklearn 进行建模，这是从哪里来的gaussian_process.GaussianProcess()（我在猜测，但如果这是错误的，请纠正我并修改问题）。
Now, you generate predicted values for yhere:
现在，您在此处生成y 的预测值：
predictedY, MSE = gp.predict(testX, eval_MSE = True)
predictedY, MSE = gp.predict(testX, eval_MSE = True)
However, as we can see from the documentation for GaussianProcess, predict()returns two items. The first is y, which is array-like(emphasis mine). That means that it can have more than one dimension, or, to be concrete for thick headed people like me, it can have more than one column -- see that it can return (n_samples, n_targets)which, depending on testX, could be (1000, 3)(just to pick numbers). Thus, your predictedYmight have 3 columns.
但是，正如我们从GaussianProcess 的文档中看到的，predict()返回两个项目。第一个是y，它类似于数组（重点是我的）。这意味着它可以有多个维度，或者，对于像我这样头脑清醒的人来说，它可以有不止一列——看到它可以返回(n_samples, n_targets)哪个，取决于testX，可能是(1000, 3)（只是为了选择数字） . 因此，您predictedY可能有 3 列。
If so, when you try to put something with three "columns" into a single dataframe column, you are passing 3 items where only 1 would fit.
如果是这样，当您尝试将具有三个“列”的内容放入单个数据框列时，您将传递 3 个只有 1 个适合的项目。
