NumPy的重塑问题

Question

import numpy as np 
import matplotlib.pyplot as plt 
from matplotlib import style 
from sklearn.linear_model import LinearRegression 
from sklearn import preprocessing, cross_validation, svm 


df = pd.read_csv('table.csv') 
print (df.head()) 

df = df[['Price', 'Asset']] 
x = np.array(df.Price) 
y = np.array(df.Asset) 

x_train, x_test, y_train, y_test = cross_validation.train_test_split(
x, y, test_size=0.2) 


x_train = np.pad(x, [(0,0)], mode='constant') 
x_train.reshape((23,1)) 


y_train = np.pad(y, [(0,0)], mode ='constant') 
y_train.reshape((23,1)) 

np.reshape(-1, 1) 

错误：

runfile('C:/Users/HP/Documents/linear.py', wdir='C:/Users/HP/Documents') 
     Price  Asset 
0 87.585859 191 
1 87.839996 232 
2 87.309998 245 
3 88.629997 445 
4 88.379997 393 
C:\Users\HP\Anaconda3\lib\site-packages\sklearn\utils\validation.py:386: 

    DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample. 
    DeprecationWarning) 
Traceback (most recent call last): 

    File "<ipython-input-124-030ffa933525>", line 1, in <module> 
    runfile('C:/Users/HP/Documents/linear.py', wdir='C:/Users/HP/Documents') 

    File "C:\Users\HP\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 714, in runfile 
    execfile(filename, namespace) 

    File "C:\Users\HP\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 89, in execfile 
    exec(compile(f.read(), filename, 'exec'), namespace) 

    File "C:/Users/HP/Documents/linear.py", line 38, in <module> 
    clf.fit(x_train, y_train) 

    File "C:\Users\HP\Anaconda3\lib\site-packages\sklearn\linear_model\base.py", line 427, in fit 
    y_numeric=True, multi_output=True) 

    File "C:\Users\HP\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 520, in check_X_y 
    check_consistent_length(X, y) 

    File "C:\Users\HP\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 176, in check_consistent_length 
    "%s" % str(uniques)) 

ValueError: Found arrays with inconsistent numbers of samples: [ 1 23] 

我的数据框尺寸：23，2

我填补我x_train和y_train为[23.1]因为我得到这个初始误差ValueError异常：发现样本数不一致的阵列：[1 18]。 填充后我的错误消息：ValueError：发现样本数量不一致的数组：[1 23]。

然后我试图重塑它，仍然收到错误信息：ValueError：发现样本数不一致的阵列：[1 23]。

我该如何解决这个问题？

Answer 1

如果你只想重塑从大小(x, 1)数组(1, x)可以使用np.transpose或numpy.ndarray.T功能：

x_train = x_train.T 
y_train = np.transpose(y_train) 

都达到同样的效果。

编辑：这只适用于一维数组。使用重塑更高维数组。

如果您不给我们提供完整的回溯，它显示错误发生在哪一行，我们不能帮助你更详细。