Sardarji
2018-09-09 12:39:22 UTC
As i am going through the Panel Data which is in LINEAR-MODEL And i tried
to run the peace of code given in the Introduction i got this error can you
tell me what i have done wrong ??
*https://bashtage.github.io/linearmodels/panel/introduction.html*
<https://bashtage.github.io/linearmodels/panel/introduction.html>
[image: doubt.JPG]
[image: doubt1.JPG]
And further in the end it is given that
Like statsmodels, panel models can be specified using a R-like formula.
This model is identical to the previous. Note the use of the *special*
variable EntityEffect to include the fixed effects.
So i also tried to use this line of code
*mod = PanelOLS.from_formula('lwage ~ 1 + expersq + union + married +
EntityEffect',data)*
And it given me this error And Please Tell me that *EntityEffect* is a
keyword that is already defined if defined than what is the default value
it has.
---------------------------------------------------------------------------NameError Traceback (most recent call last)~\Anaconda3\lib\site-packages\patsy\compat.py in call_and_wrap_exc(msg, origin, f, *args, **kwargs) 35 try:---> 36 return f(*args, **kwargs) 37 except Exception as e:
~\Anaconda3\lib\site-packages\patsy\eval.py in eval(self, expr, source_name, inner_namespace) 165 return eval(code, {}, VarLookupDict([inner_namespace]--> 166 + self._namespaces)) 167
<string> in <module>()
NameError: name 'EntityEffect' is not defined
The above exception was the direct cause of the following exception:
PatsyError Traceback (most recent call last)<ipython-input-34-11e31c3be118> in <module>() 6 dependent = data.lwage 7 exog = sm.add_constant(data[['expersq','married','union']])----> 8 mod = PanelOLS.from_formula('lwage ~ 1 + expersq + union + married + EntityEffect',data) 9 res = mod.fit(cov_type='unadjusted') 10 res
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in from_formula(cls, formula, data, weights, other_effects) 861 entity_effect = parser.entity_effect 862 time_effect = parser.time_effect--> 863 dependent, exog = parser.data 864 mod = cls(dependent, exog, entity_effects=entity_effect, time_effects=time_effect, 865 weights=weights, other_effects=other_effects)
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in data(self) 93 """Returns a tuple containing the dependent, exog, endog and instruments""" 94 self._eval_env += 1---> 95 out = self.dependent, self.exog 96 self._eval_env -= 1 97 return out
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in exog(self) 107 """DataFrame containing the exogenous variables""" 108 out = dmatrix(self._rhs, self._data.dataframe, eval_env=self._eval_env,--> 109 return_type='dataframe', NA_action=self._na_action) 110 return out 111
~\Anaconda3\lib\site-packages\patsy\highlevel.py in dmatrix(formula_like, data, eval_env, NA_action, return_type) 289 eval_env = EvalEnvironment.capture(eval_env, reference=1) 290 (lhs, rhs) = _do_highlevel_design(formula_like, data, eval_env,--> 291 NA_action, return_type) 292 if lhs.shape[1] != 0: 293 raise PatsyError("encountered outcome variables for a model "
~\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) 68 data_iter_maker, 69 eval_env,---> 70 NA_action) 71 else: 72 return None
~\Anaconda3\lib\site-packages\patsy\build.py in design_matrix_builders(termlists, data_iter_maker, eval_env, NA_action) 694 factor_states, 695 data_iter_maker,--> 696 NA_action) 697 # Now we need the factor infos, which encapsulate the knowledge of 698 # how to turn any given factor into a chunk of data:
~\Anaconda3\lib\site-packages\patsy\build.py in _examine_factor_types(factors, factor_states, data_iter_maker, NA_action) 441 for data in data_iter_maker(): 442 for factor in list(examine_needed):--> 443 value = factor.eval(factor_states[factor], data) 444 if factor in cat_sniffers or guess_categorical(value): 445 if factor not in cat_sniffers:
~\Anaconda3\lib\site-packages\patsy\eval.py in eval(self, memorize_state, data) 564 return self._eval(memorize_state["eval_code"], 565 memorize_state,--> 566 data) 567 568 __getstate__ = no_pickling
~\Anaconda3\lib\site-packages\patsy\eval.py in _eval(self, code, memorize_state, data) 549 memorize_state["eval_env"].eval, 550 code,--> 551 inner_namespace=inner_namespace) 552 553 def memorize_chunk(self, state, which_pass, data):
~\Anaconda3\lib\site-packages\patsy\compat.py in call_and_wrap_exc(msg, origin, f, *args, **kwargs) 41 origin) 42 # Use 'exec' to hide this syntax from the Python 2 parser:---> 43 exec("raise new_exc from e") 44 else: 45 # In python 2, we just let the original exception escape -- better
~\Anaconda3\lib\site-packages\patsy\compat.py in <module>()
PatsyError: Error evaluating factor: NameError: name 'EntityEffect' is not defined
expersq + union + married + EntityEffect
^^^^^^^^^^^^
to run the peace of code given in the Introduction i got this error can you
tell me what i have done wrong ??
*https://bashtage.github.io/linearmodels/panel/introduction.html*
<https://bashtage.github.io/linearmodels/panel/introduction.html>
[image: doubt.JPG]
[image: doubt1.JPG]
And further in the end it is given that
Like statsmodels, panel models can be specified using a R-like formula.
This model is identical to the previous. Note the use of the *special*
variable EntityEffect to include the fixed effects.
So i also tried to use this line of code
*mod = PanelOLS.from_formula('lwage ~ 1 + expersq + union + married +
EntityEffect',data)*
And it given me this error And Please Tell me that *EntityEffect* is a
keyword that is already defined if defined than what is the default value
it has.
---------------------------------------------------------------------------NameError Traceback (most recent call last)~\Anaconda3\lib\site-packages\patsy\compat.py in call_and_wrap_exc(msg, origin, f, *args, **kwargs) 35 try:---> 36 return f(*args, **kwargs) 37 except Exception as e:
~\Anaconda3\lib\site-packages\patsy\eval.py in eval(self, expr, source_name, inner_namespace) 165 return eval(code, {}, VarLookupDict([inner_namespace]--> 166 + self._namespaces)) 167
<string> in <module>()
NameError: name 'EntityEffect' is not defined
The above exception was the direct cause of the following exception:
PatsyError Traceback (most recent call last)<ipython-input-34-11e31c3be118> in <module>() 6 dependent = data.lwage 7 exog = sm.add_constant(data[['expersq','married','union']])----> 8 mod = PanelOLS.from_formula('lwage ~ 1 + expersq + union + married + EntityEffect',data) 9 res = mod.fit(cov_type='unadjusted') 10 res
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in from_formula(cls, formula, data, weights, other_effects) 861 entity_effect = parser.entity_effect 862 time_effect = parser.time_effect--> 863 dependent, exog = parser.data 864 mod = cls(dependent, exog, entity_effects=entity_effect, time_effects=time_effect, 865 weights=weights, other_effects=other_effects)
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in data(self) 93 """Returns a tuple containing the dependent, exog, endog and instruments""" 94 self._eval_env += 1---> 95 out = self.dependent, self.exog 96 self._eval_env -= 1 97 return out
~\Anaconda3\lib\site-packages\linearmodels\panel\model.py in exog(self) 107 """DataFrame containing the exogenous variables""" 108 out = dmatrix(self._rhs, self._data.dataframe, eval_env=self._eval_env,--> 109 return_type='dataframe', NA_action=self._na_action) 110 return out 111
~\Anaconda3\lib\site-packages\patsy\highlevel.py in dmatrix(formula_like, data, eval_env, NA_action, return_type) 289 eval_env = EvalEnvironment.capture(eval_env, reference=1) 290 (lhs, rhs) = _do_highlevel_design(formula_like, data, eval_env,--> 291 NA_action, return_type) 292 if lhs.shape[1] != 0: 293 raise PatsyError("encountered outcome variables for a model "
~\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) 68 data_iter_maker, 69 eval_env,---> 70 NA_action) 71 else: 72 return None
~\Anaconda3\lib\site-packages\patsy\build.py in design_matrix_builders(termlists, data_iter_maker, eval_env, NA_action) 694 factor_states, 695 data_iter_maker,--> 696 NA_action) 697 # Now we need the factor infos, which encapsulate the knowledge of 698 # how to turn any given factor into a chunk of data:
~\Anaconda3\lib\site-packages\patsy\build.py in _examine_factor_types(factors, factor_states, data_iter_maker, NA_action) 441 for data in data_iter_maker(): 442 for factor in list(examine_needed):--> 443 value = factor.eval(factor_states[factor], data) 444 if factor in cat_sniffers or guess_categorical(value): 445 if factor not in cat_sniffers:
~\Anaconda3\lib\site-packages\patsy\eval.py in eval(self, memorize_state, data) 564 return self._eval(memorize_state["eval_code"], 565 memorize_state,--> 566 data) 567 568 __getstate__ = no_pickling
~\Anaconda3\lib\site-packages\patsy\eval.py in _eval(self, code, memorize_state, data) 549 memorize_state["eval_env"].eval, 550 code,--> 551 inner_namespace=inner_namespace) 552 553 def memorize_chunk(self, state, which_pass, data):
~\Anaconda3\lib\site-packages\patsy\compat.py in call_and_wrap_exc(msg, origin, f, *args, **kwargs) 41 origin) 42 # Use 'exec' to hide this syntax from the Python 2 parser:---> 43 exec("raise new_exc from e") 44 else: 45 # In python 2, we just let the original exception escape -- better
~\Anaconda3\lib\site-packages\patsy\compat.py in <module>()
PatsyError: Error evaluating factor: NameError: name 'EntityEffect' is not defined
expersq + union + married + EntityEffect
^^^^^^^^^^^^