ValueError: endog must be in the unit interval
Question: While using statsmodels, I am getting this weird error: `ValueError: endog
must be in the unit interval.` Can someone give me more information on this
error? Google is not helping.

Code that produced the error:

    
    
    """
    Multiple regression with dummy variables. 
    """
    
    import pandas as pd
    import statsmodels.api as sm
    import pylab as pl
    import numpy as np
    
    df = pd.read_csv('cost_data.csv')
    df.columns = ['Cost', 'R(t)', 'Day of Week']
    dummy_ranks = pd.get_dummies(df['Day of Week'], prefix='days')
    cols_to_keep = ['Cost', 'R(t)']
    data = df[cols_to_keep].join(dummy_ranks.ix[:,'days_2':])
    data['intercept'] = 1.0
    
    print(data)
    
    train_cols = data.columns[1:]
    logit = sm.Logit(data['Cost'], data[train_cols])
    
    result = logit.fit()
    
    print(result.summary())
    

And the traceback:

    
    
    Traceback (most recent call last):
      File "multiple_regression_dummy.py", line 20, in <module>
        logit = sm.Logit(data['Cost'], data[train_cols])
      File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/discrete/discrete_model.py", line 404, in __init__
        raise ValueError("endog must be in the unit interval.")
    ValueError: endog must be in the unit interval.
    


Answer: I got this error when my target column had values larger than 1. Make sure
your target column is between 0 and 1 (as is required for a Logistic
Regression) and try again. For example, if you have target column with values
1-5, make 4 and 5 the positive class and 1,2,3 the negative class. Hope this
helps.

