Python“数组的索引太多”
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Python "Too many indices for array"
提问by Farhan Javed
I am reading a file in python using pandas and then saving it in a numpy array. The file has the dimension of 11303402 rows x 10 columns. I need to split the data for cross validation and for that I sliced the data into 11303402 rows x 9 columns of examples and 1 array of 11303402 rows x 1 col of labels. The following is the code:
我正在使用 Pandas 在 python 中读取文件，然后将其保存在一个 numpy 数组中。该文件的尺寸为 11303402 行 x 10 列。我需要拆分数据以进行交叉验证，为此我将数据切成 11303402 行 x 9 列示例和 1 个 11303402 行 x 1 列标签数组。以下是代码：
tdata=pd.read_csv('train.csv')
tdata.columns='Arrival_Time','Creation_Time','x','y','z','User','Model','Device','sensor','gt']
User_Data = np.array(tdata)
features = User_Data[:,0:9]
labels = User_Data[:,9:10]
The error comes in the following code:
错误出现在以下代码中：
classes=np.unique(labels)
idx=labels==classes[0]
Yt=labels[idx]
Xt=features[idx,:]
On the line:
在线上：
Xt=features[idx,:]
it says 'too many indices for array'
它说“数组的索引太多”
The shapes of all 3 data sets are:
所有 3 个数据集的形状是：
print np.shape(tdata) = (11303402, 10)
print np.shape(features) = (11303402, 9)
print np.shape(labels) = (11303402, 1)
If anyone knows the problem, please help.
如果有人知道问题，请帮助。
回答by Keith Prussing
The problem is idxhas shape (11303402,1)because the logical comparison returns an array of the same shape as labels. These two dimensions use all of the indexes in features. The quick work around is
问题是idx有形状，(11303402,1)因为逻辑比较返回一个与 形状相同的数组labels。这两个维度使用 中的所有索引features。快速解决方法是
Xt=features[idx[:,0],:]
