title: sklearn issue: Found arrays with inconsistent numbers of samples when doing regression
body: <p>this question seems to have been asked before, but I can't seem to comment for further clarification on the accepted answer and I couldn't figure out the solution provided.</p>
  
  <p>I am trying to learn how to use sklearn with my own data. I essentially just got the annual % change in GDP for 2 different countries over the past 100 years. I am just trying to learn using a single variable for now. What I am essentially trying to do is use sklearn to predict what the GDP % change for country A will be given the percentage change in country B's GDP.</p>
  
  <p>The problem is that I receive an error saying: </p>
  
  <blockquote>
    <p>ValueError: Found arrays with inconsistent numbers of samples: [  1
    107]</p>
  </blockquote>
  
  <p>Here is my code:</p>
  
  <pre><code>import sklearn.linear_model as lm
  import numpy as np
  import scipy.stats as st
  import matplotlib.pyplot as plt
  import matplotlib.dates as mdates
  
  
  def bytespdate2num(fmt, encoding='utf-8'):#function to convert bytes to string for the dates.
      strconverter = mdates.strpdate2num(fmt)
      def bytesconverter(b):
          s = b.decode(encoding)
          return strconverter(s)
      return bytesconverter
  
  dataCSV = open('combined_data.csv')
  
  comb_data = []
  
  for line in dataCSV:
      comb_data.append(line)
  
  date, chngdpchange, ausgdpchange = np.loadtxt(comb_data, delimiter=',', unpack=True, converters={0: bytespdate2num('%d/%m/%Y')})
  
  
  chntrain = chngdpchange[:-1]
  chntest = chngdpchange[-1:]
  
  austrain = ausgdpchange[:-1]
  austest = ausgdpchange[-1:]
  
  regr = lm.LinearRegression()
  regr.fit(chntrain, austrain)
  
  print('Coefficients: \n', regr.coef_)
  
  print("Residual sum of squares: %.2f"
        % np.mean((regr.predict(chntest) - austest) ** 2))
  
  print('Variance score: %.2f' % regr.score(chntest, austest))
  
  plt.scatter(chntest, austest,  color='black')
  plt.plot(chntest, regr.predict(chntest), color='blue')
  
  plt.xticks(())
  plt.yticks(())
  
  plt.show()
  </code></pre>
  
  <p>What am I doing wrong? I essentially tried to apply the sklearn tutorial (They used some diabetes data set) to my own simple data. My data just contains the date, country A's % change in GDP for that specific year, and country B's % change in GDP for that same year. </p>
  
  <p>I tried the solutions <a href="https://stackoverflow.com/questions/30813044/sklearn-found-arrays-with-inconsistent-numbers-of-samples-when-calling-linearre">here</a> and <a href="https://stackoverflow.com/questions/14476415/reshape-an-array-in-numpy">here (basically trying to find more out about the solution in the first link)</a>, but just receive the exact same error.</p>
  
  <p>Here is the full traceback in case you want to see it:</p>
  
  <pre><code>Traceback (most recent call last):
    File "D:\My Stuff\Dropbox\Python\Python projects\test regression\tester.py", line 34, in &lt;module&gt;
      regr.fit(chntrain, austrain)
    File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\linear_model\base.py", line 376, in fit
      y_numeric=True, multi_output=True)
    File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\utils\validation.py", line 454, in check_X_y
      check_consistent_length(X, y)
    File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\utils\validation.py", line 174, in check_consistent_length
      "%s" % str(uniques))
  ValueError: Found arrays with inconsistent numbers of samples: [  1 107]
  </code></pre>