Help on error " ValueError: For numerical factors, num_columns must be an int "

[Robert]

Hi,

When I run the following code, there is an error:

ValueError: For numerical factors, num_columns must be an int 


================
import numpy as np
import pandas as pd
from patsy import dmatrices
from sklearn.linear_model import LogisticRegression

X = [0.5,0.75,1.0,1.25,1.5,1.75,1.75,2.0,2.25,2.5,2.75,3.0,3.25,
3.5,4.0,4.25,4.5,4.75,5.0,5.5]
y = [0,0,0,0,0,0,1,0,1,0,1,0,1,0,1,1,1,1,1,1]

zipped = list(zip(X,y))
df = pd.DataFrame(zipped,columns = ['study_hrs','p_or_f'])

y, X = dmatrices('p_or_f ~ study_hrs', df, return_type="dataframe")
=======================

I have check 'df' is this type:
=============
type(df)
Out[25]: pandas.core.frame.DataFrame
=============

I cannot figure out where the problem is. Can you help me?
Thanks.

Error message:
..........


---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
C:\Users\rj\pyprj\stackoverflow_logisticregression0.py in <module>()
     17 df = pd.DataFrame(zipped,columns = ['study_hrs','p_or_f'])
     18 
---> 19 y, X = dmatrices('p_or_f ~ study_hrs', df, return_type="dataframe")
     20 
     21 y = np.ravel(y)

C:\Users\rj\AppData\Local\Enthought\Canopy\User\lib\site-packages\patsy\highlevel.pyc in dmatrices(formula_like, data, eval_env, NA_action, return_type)
    295     eval_env = EvalEnvironment.capture(eval_env, reference=1)
    296     (lhs, rhs) = _do_highlevel_design(formula_like, data, eval_env,
--> 297                                       NA_action, return_type)
    298     if lhs.shape[1] == 0:
    299         raise PatsyError("model is missing required outcome variables")

C:\Users\rj\AppData\Local\Enthought\Canopy\User\lib\site-packages\patsy\highlevel.pyc in _do_highlevel_design(formula_like, data, eval_env, NA_action, return_type)
    150         return iter([data])
    151     design_infos = _try_incr_builders(formula_like, data_iter_maker, eval_env,
--> 152                                       NA_action)
    153     if design_infos is not None:
    154         return build_design_matrices(design_infos, data,

C:\Users\rj\AppData\Local\Enthought\Canopy\User\lib\site-packages\patsy\highlevel.pyc in _try_incr_builders(formula_like, data_iter_maker, eval_env, NA_action)
     55                                       data_iter_maker,
     56                                       eval_env,
---> 57                                       NA_action)
     58     else:
     59         return None

C:\Users\rj\AppData\Local\Enthought\Canopy\User\lib\site-packages\patsy\build.pyc in design_matrix_builders(termlists, data_iter_maker, eval_env, NA_action)
    704                             factor_states[factor],
    705                             num_columns=num_column_counts[factor],
--> 706                             categories=None)
    707         else:
    708             assert factor in cat_levels_contrasts

C:\Users\rj\AppData\Local\Enthought\Canopy\User\lib\site-packages\patsy\design_info.pyc in __init__(self, factor, type, state, num_columns, categories)
     86         if self.type == "numerical":
     87             if not isinstance(num_columns, int):
---> 88                 raise ValueError("For numerical factors, num_columns "
     89                                  "must be an int")
     90             if categories is not None:

ValueError: For numerical factors, num_columns must be an int