when I use pandas statsmodels,i get an assertionerror

Question

i'm trying the example of ordinary least squares the codes are in the following.

import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf
dat = sm.datasets.get_rdataset("Guerry", "HistData").data
results = smf.ols('Lottery ~ Literacy + np.log(Pop1831)', data=dat).fit()
print(results.summary())

but i get this error in the following, the source of the example is in the website http://www.statsmodels.org/stable/index.html my statsmodels version is 0.9, i just remove np as the first firend said, but i still get the same error, so it doesn't work, that's all i can try, please help me..... the error is too long, so i need to cut it into some pieces

the first piece is folling:

AssertionError                            Traceback (most recent call last)
<ipython-input-6-1d91087b5e15> in <module>()
      3 import statsmodels.formula.api as smf
      4 dat = sm.datasets.get_rdataset("Guerry", "HistData").data
----> 5 results = smf.ols('Lottery ~ Literacy + log(Pop1831)', data=dat).fit()
      6 print(results.summary())

~\Anaconda3\lib\site-packages\statsmodels\base\model.py in from_formula(cls, formula, data, subset, drop_cols, *args, **kwargs)
    153 
    154         tmp = handle_formula_data(data, None, formula, depth=eval_env,
--> 155                                   missing=missing)
    156         ((endog, exog), missing_idx, design_info) = tmp
    157 

~\Anaconda3\lib\site-packages\statsmodels\formula\formulatools.py in handle_formula_data(Y, X, formula, depth, missing)
     63         if data_util._is_using_pandas(Y, None):
     64             result = dmatrices(formula, Y, depth, return_type='dataframe',
---> 65                                NA_action=na_action)
     66         else:
     67             result = dmatrices(formula, Y, depth, return_type='dataframe',

the second piece is following:

~\Anaconda3\lib\site-packages\patsy\highlevel.py in dmatrices(formula_like, data, eval_env, NA_action, return_type)
    308     eval_env = EvalEnvironment.capture(eval_env, reference=1)
    309     (lhs, rhs) = _do_highlevel_design(formula_like, data, eval_env,
--> 310                                       NA_action, return_type)
    311     if lhs.shape[1] == 0:
    312         raise PatsyError("model is missing required outcome variables")

~\Anaconda3\lib\site-packages\patsy\highlevel.py in _do_highlevel_design(formula_like, data, eval_env, NA_action, return_type)
    163         return iter([data])
    164     design_infos = _try_incr_builders(formula_like, data_iter_maker, eval_env,
--> 165                                       NA_action)
    166     if design_infos is not None:
    167         return build_design_matrices(design_infos, data,

~\Anaconda3\lib\site-packages\patsy\highlevel.py in _try_incr_builders(formula_like, data_iter_maker, eval_env, NA_action)
     60                 "ascii-only, or else upgrade to Python 3.")
     61     if isinstance(formula_like, str):
---> 62         formula_like = ModelDesc.from_formula(formula_like)
     63         # fallthrough
     64     if isinstance(formula_like, ModelDesc):

the third piece is in the following:

~\Anaconda3\lib\site-packages\patsy\desc.py in from_formula(cls, tree_or_string)
    162             tree = tree_or_string
    163         else:
--> 164             tree = parse_formula(tree_or_string)
    165         value = Evaluator().eval(tree, require_evalexpr=False)
    166         assert isinstance(value, cls)

~\Anaconda3\lib\site-packages\patsy\parse_formula.py in parse_formula(code, extra_operators)
    146     tree = infix_parse(_tokenize_formula(code, operator_strings),
    147                        operators,
--> 148                        _atomic_token_types)
    149     if not isinstance(tree, ParseNode) or tree.type != "~":
    150         tree = ParseNode("~", None, [tree], tree.origin)

~\Anaconda3\lib\site-packages\patsy\infix_parser.py in infix_parse(tokens, operators, atomic_types, trace)
    208 
    209     want_noun = True
--> 210     for token in token_source:
    211         if c.trace:
    212             print("Reading next token (want_noun=%r)" % (want_noun,))  

the fourth piece is in the following:

~\Anaconda3\lib\site-packages\patsy\parse_formula.py in _tokenize_formula(code, operator_strings)
     92         else:
     93             it.push_back((pytype, token_string, origin))
---> 94             yield _read_python_expr(it, end_tokens)
     95 
     96 def test__tokenize_formula():

~\Anaconda3\lib\site-packages\patsy\parse_formula.py in _read_python_expr(it, end_tokens)
     42     origins = []
     43     bracket_level = 0
---> 44     for pytype, token_string, origin in it:
     45         assert bracket_level >= 0
     46         if bracket_level == 0 and token_string in end_tokens:

~\Anaconda3\lib\site-packages\patsy\util.py in next(self)
    330         else:
    331             # May raise StopIteration
--> 332             return six.advance_iterator(self._it)
    333     __next__ = next

the fifth piece is in the following:

~\Anaconda3\lib\site-packages\patsy\tokens.py in python_tokenize(code)
     33                 break
     34             origin = Origin(code, start, end)
---> 35             assert pytype not in (tokenize.NL, tokenize.NEWLINE)
     36             if pytype == tokenize.ERRORTOKEN:
     37                 raise PatsyError("error tokenizing input "

AssertionError: 

Answer 1

There was a bug within patsy, the formula parser used by statsmodels. I had the same issue, and upgrading to patsy 0.5.1 solved it. See: https://github.com/statsmodels/statsmodels/issues/5343