diff --git a/statsmodels/genmod/generalized_estimating_equations.py b/statsmodels/genmod/generalized_estimating_equations.py index 2333ab1deec..4e9a789be18 100644 --- a/statsmodels/genmod/generalized_estimating_equations.py +++ b/statsmodels/genmod/generalized_estimating_equations.py @@ -679,23 +679,23 @@ def from_formula(cls, formula, groups, data, subset=None, """ % {'missing_param_doc': base._missing_param_doc} groups_name = "Groups" - if type(groups) == str: + if isinstance(groups, str): groups_name = groups groups = data[groups] - if type(time) == str: + if isinstance(time, str): time = data[time] - if type(offset) == str: + if isinstance(offset, str): offset = data[offset] - if type(exposure) == str: + if isinstance(exposure, str): exposure = data[exposure] dep_data = kwargs.get("dep_data") dep_data_names = None if dep_data is not None: - if type(dep_data) is str: + if isinstance(dep_data, str): dep_data = patsy.dmatrix(dep_data, data, return_type='dataframe') dep_data_names = dep_data.columns.tolist() else: @@ -2320,7 +2320,7 @@ def setup_nominal(self, endog, exog, groups, time, offset): jrow += 1 # exog names - if type(self.exog_orig) == pd.DataFrame: + if isinstance(self.exog_orig, pd.DataFrame): xnames_in = self.exog_orig.columns else: xnames_in = ["x%d" % k for k in range(1, exog.shape[1] + 1)] @@ -2331,7 +2331,7 @@ def setup_nominal(self, endog, exog, groups, time, offset): exog_out = pd.DataFrame(exog_out, columns=xnames) # Preserve endog name if there is one - if type(self.endog_orig) == pd.Series: + if isinstance(self.endog_orig, pd.Series): endog_out = pd.Series(endog_out, name=self.endog_orig.name) return endog_out, exog_out, groups_out, time_out, offset_out