title: python sklearn multiple linear regression display r-squared
body: <p>I calculated my multiple linear regression equation and I want to see the adjusted R-squared. I know that the score function allows me to see r-squared, but it is not adjusted.</p>
  
  <pre><code>import pandas as pd #import the pandas module
  import numpy as np
  df = pd.read_csv ('/Users/jeangelj/Documents/training/linexdata.csv', sep=',')
  df
         AverageNumberofTickets   NumberofEmployees   ValueofContract Industry
     0              1                    51                  25750    Retail
     1              9                    68                  25000    Services
     2             20                    67                  40000    Services
     3              1                   124                  35000    Retail
     4              8                   124                  25000    Manufacturing
     5             30                   134                  50000    Services
     6             20                   157                  48000    Retail
     7              8                   190                  32000    Retail
     8             20                   205                  70000    Retail
     9             50                   230                  75000    Manufacturing
    10             35                   265                  50000    Manufacturing
    11             65                   296                  75000    Services
    12             35                   336                  50000    Manufacturing
    13             60                   359                  75000    Manufacturing
    14             85                   403                  81000    Services
    15             40                   418                  60000    Retail
    16             75                   437                  53000    Services
    17             85                   451                  90000    Services
    18             65                   465                  70000    Retail
    19             95                   491                  100000   Services
  
  from sklearn.linear_model import LinearRegression
  model = LinearRegression()
  X, y = df[['NumberofEmployees','ValueofContract']], df.AverageNumberofTickets
  model.fit(X, y)
  model.score(X, y)
  &gt;&gt;0.87764337132340009
  </code></pre>
  
  <p>I checked it manually and 0.87764 is R-squared; whereas 0.863248 is the adjusted R-squared. </p>