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From: Mark Lawrence <breamoreboy@yahoo.co.uk>
Newsgroups: comp.lang.python
Subject: Re: Help on error " ValueError: For numerical factors, num_columns must be an int "
Date: Wed, 16 Dec 2015 11:33:39 +0000
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On 16/12/2015 10:44, Robert wrote:
> 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
>

Slap the ValueError into a search engine and the first hit is 
https://groups.google.com/forum/#!topic/pystatsmodels/KcSzNqDxv-Q

-- 
My fellow Pythonistas, ask not what our language can do for you, ask
what you can do for our language.

Mark Lawrence