Python ValueError：x 和 y 的大小必须相同
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/41659535/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
ValueError: x and y must be the same size
提问by user3521180
import numpy as np
import pandas as pd
import matplotlib.pyplot as pt
data1 = pd.read_csv('stage1_labels.csv')
X = data1.iloc[:, :-1].values
y = data1.iloc[:, 1].values
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
label_X = LabelEncoder()
X[:,0] = label_X.fit_transform(X[:,0])
encoder = OneHotEncoder(categorical_features = [0])
X = encoder.fit_transform(X).toarray()
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train,y_test = train_test_split(X, y, test_size = 0.4, random_state = 0)
#fitting Simple Regression to training set
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)
#predecting the test set results
y_pred = regressor.predict(X_test)
#Visualization of the training set results
pt.scatter(X_train, y_train, color = 'red')
pt.plot(X_train, regressor.predict(X_train), color = 'green')
pt.title('salary vs yearExp (Training set)')
pt.xlabel('years of experience')
pt.ylabel('salary')
pt.show()
I need a help understanding the error in while executing the above code. Below is the error:
我需要帮助理解执行上述代码时出现的错误。下面是错误：
"raise ValueError("x and y must be the same size")"
"raise ValueError("x 和 y 的大小必须相同")"
I have .csv file with 1398 rows and 2 column. I have taken 40% as y_test set, as it is visible in the above code.
我有 1398 行和 2 列的 .csv 文件。我已经将 40% 作为 y_test 集，因为它在上面的代码中是可见的。
回答by Lukasz Tracewski
Print X_train shape. What do you see? I'd bet X_trainis 2d (matrix with a single column), while y_train1d (vector). In turn you get different sizes.
打印 X_train 形状。你看到了什么？我敢打赌X_train是 2d（单列矩阵），而y_train1d（向量）。反过来，你会得到不同的尺寸。
I think using X_train[:,0]for plotting (which is from where the error originates) should solve the problem
我认为X_train[:,0]用于绘图（这是错误的来源）应该可以解决问题
回答by yogabonito
Slicing with [:, :-1]will give you a 2-dimensionalarray (including all rows and all columns excluding the last column).
切片[:, :-1]将为您提供一个二维数组（包括除最后一列之外的所有行和所有列）。
Slicing with [:, 1]will give you a 1-dimensionalarray (including all rows from the second column). To make this array also 2-dimensional use [:, 1:2]or [:, 1].reshape(-1, 1)or [:, 1][:, None]instead of [:, 1]. This will make xand ycomparable.
切片[:, 1]将为您提供一个一维数组（包括第二列中的所有行）。要使此数组也为二维，请使用[:, 1:2]or[:, 1].reshape(-1, 1)或[:, 1][:, None]代替[:, 1]。这将使x和y具有可比性。
An alternative to making both arrays 2-dimensional is making them both one dimensional. For this one would do [:, 0](instead of [:, :1]) for selecting the first column and [:, 1]for selecting the second column.
使两个数组都为二维的另一种方法是使它们都是一维的。为此，可以[:, 0]（而不是[:, :1]）选择第一列和[:, 1]选择第二列。
回答by PdF
In my case the problem was that the size of test_size was different from the range of the scatter plot. The range should be the same of the test_size (40% in your code) of the total observation. Here you should set the range of your scatter plot as 40% of total observations that you are processing in your model.
就我而言，问题是 test_size 的大小与散点图的范围不同。该范围应与总观察值的 test_size （代码中的 40%）相同。在这里，您应该将散点图的范围设置为您在模型中处理的总观测值的 40%。
