title: ValueError: x and y must be the same size
body: <pre><code>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()
  </code></pre>
  
  <p>I need a help understanding the error in while executing the above code. Below is the error:</p>
  
  <blockquote>
    <p>"raise ValueError("x and y must be the same size")"</p>
  </blockquote>
  
  <p>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.</p>