title: Python multinomial logit with statsmodels module: Change base value of mlogit regression
body: <p>I have a little problem which I am stuck with.
  I am building a multinomial logit model with Python statsmodels and wish to reproduce an example given in a textbook.
  So far so good, but I am struggling with setting a different target value as the base value for the regression. Can somebody help?!</p>
  
  <pre><code>import numpy as np
  import pandas as pd
  import statsmodels.api as sm
  import matplotlib.pyplot as plt
  
  #import data
  df = pd.read_excel('C:/.../diabetes.xlsx')
  
  #split the data in dependent and independent variables
  y = df['CC']
  X = df.drop(['Patient', 'CC'], axis = 1)
  Xc = sm.add_constant(X)
  
  #instantiate and fit multinomial logit
  mlogit = sm.MNLogit(y, Xc)
  fmlogit = mlogit.fit()
  
  print(fmlogit.summary())
  </code></pre>
  
  <p>So the column 'CC' is the target variable and contains enconding for the diabetes status: </p>
  
  <p>CC = 1 -> Overt diabetes, CC = 2 -> Chemical dibetes, CC = 3 -> Normal</p>
  
  <p>Now, per default CC = 1 is the base value, however, I would like CC = 3 to be my base value. Here is my <a href="https://i.stack.imgur.com/b22cu.png" rel="nofollow noreferrer">regression output</a>.</p>
  
  <p>Does anybody know?</p>
  
  <p>Thanks a lot in advance,
  ig</p>