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Y_hat data[f"{yname}_hat"] = _first_u - # intercept needs to be dropped by hand due to the presence of fixed effects in the first stage # noqa: W505 + # intercept needs to be dropped by hand due to the presence of fixed effects in the first stage fit2 = cast( Feols, feols( @@ -302,7 +302,7 @@ def _did2s_vcov( else: weights_array = np.sqrt(data[weights].to_numpy()) - # some formula parsing to get the correct formula for the first and second stage model matrix # noqa: W505 + # some formula parsing to get the correct formula for the first and second stage model matrix first_stage_x, first_stage_fe = first_stage.split("|") first_stage_fe_list = [f"C({i})" for i in first_stage_fe.split("+")] first_stage_fe_fml = "+".join(first_stage_fe_list) diff --git a/pyfixest/estimation/FixestMulti_.py b/pyfixest/estimation/FixestMulti_.py index cca07b41..d99d6e4f 100644 --- a/pyfixest/estimation/FixestMulti_.py +++ b/pyfixest/estimation/FixestMulti_.py @@ -361,7 +361,7 @@ def _estimate_all_models( FIT.wls_transform() FIT.get_fit() - # if X is empty: no inference (empty X only as shorthand for demeaning) # noqa: W505 + # if X is empty: no inference (empty X only as shorthand for demeaning) if not FIT._X_is_empty: # inference vcov_type = _get_vcov_type(vcov, fval) diff --git a/pyfixest/estimation/FormulaParser.py b/pyfixest/estimation/FormulaParser.py index 76394df3..4093e50a 100644 --- a/pyfixest/estimation/FormulaParser.py +++ b/pyfixest/estimation/FormulaParser.py @@ -746,7 +746,7 @@ def _dict_to_list_of_formulas(unpacked: dict[str, list[str]]) -> list[str]: else: variable_fml = [res["variable"][i] for i in range(len(res["variable"]))] if variable_type in ["sw0", "csw0"]: - variable_fml = ["0"] + variable_fml + variable_fml = ["0", *variable_fml] fml_list = [] if variable_fml: diff --git a/pyfixest/estimation/feols_.py b/pyfixest/estimation/feols_.py index 7b35fdbc..932f0f60 100644 --- a/pyfixest/estimation/feols_.py +++ b/pyfixest/estimation/feols_.py @@ -738,7 +738,7 @@ def _vcov_crv3_fast(self, clustid, cluster_col): tXX = np.transpose(_X) @ _X tXy = np.transpose(_X) @ _Y - # compute leave-one-out regression coefficients (aka clusterjacks') # noqa: W505 + # compute leave-one-out regression coefficients (aka clusterjacks') for ixg, g in enumerate(clustid): Xg = _X[np.equal(g, cluster_col)] Yg = _Y[np.equal(g, cluster_col)] @@ -2420,14 +2420,14 @@ def _check_vcov_input(vcov: Union[str, dict[str, str]], data: pd.DataFrame): """ assert isinstance(vcov, (dict, str, list)), "vcov must be a dict, string or list" if isinstance(vcov, dict): - assert list(vcov.keys())[0] in [ + assert next(iter(vcov.keys())) in [ "CRV1", "CRV3", ], "vcov dict key must be CRV1 or CRV3" assert isinstance( - list(vcov.values())[0], str + next(iter(vcov.values())), str ), "vcov dict value must be a string" - deparse_vcov = list(vcov.values())[0].split("+") + deparse_vcov = next(iter(vcov.values())).split("+") assert len(deparse_vcov) <= 2, "not more than twoway clustering is supported" if isinstance(vcov, list): @@ -2471,8 +2471,8 @@ def _deparse_vcov_input(vcov: Union[str, dict[str, str]], has_fixef: bool, is_iv The name of the cluster variable. """ if isinstance(vcov, dict): - vcov_type_detail = list(vcov.keys())[0] - deparse_vcov = list(vcov.values())[0].split("+") + vcov_type_detail = next(iter(vcov.keys())) + deparse_vcov = next(iter(vcov.values())).split("+") if isinstance(deparse_vcov, str): deparse_vcov = [deparse_vcov] deparse_vcov = [x.replace(" ", "") for x in deparse_vcov] diff --git a/pyfixest/estimation/feols_compressed_.py b/pyfixest/estimation/feols_compressed_.py index a4bac1ef..2eb01689 100644 --- a/pyfixest/estimation/feols_compressed_.py +++ b/pyfixest/estimation/feols_compressed_.py @@ -164,7 +164,7 @@ def prepare_model_matrix(self): + [col for col in data_long_mundlak.columns if col != "Intercept"] ) - self._coefnames = ["Intercept"] + covars_updated + self._coefnames = ["Intercept", *covars_updated] self._fe = None else: diff --git a/pyfixest/estimation/fepois_.py b/pyfixest/estimation/fepois_.py index b3591fb9..424b18a1 100644 --- a/pyfixest/estimation/fepois_.py +++ b/pyfixest/estimation/fepois_.py @@ -459,7 +459,7 @@ def _check_for_separation( if separation_na: warnings.warn( - f"{str(len(separation_na))} observations removed because of separation." + f"{len(separation_na)!s} observations removed because of separation." ) return list(separation_na) diff --git a/pyfixest/report/summarize.py b/pyfixest/report/summarize.py index 569110b2..933b3f87 100644 --- a/pyfixest/report/summarize.py +++ b/pyfixest/report/summarize.py @@ -117,7 +117,7 @@ def etable( pandas.DataFrame A styled DataFrame with the coefficients and standard errors of the models. When output is "tex", the LaTeX code is returned as a string. - """ # noqa: D301 + """ if signif_code is None: signif_code = [0.001, 0.01, 0.05] assert ( @@ -689,7 +689,8 @@ def _parse_coef_fmt(coef_fmt: str, custom_stats: dict): r"\[", r"\]", ",", - ] + custom_elements + *custom_elements, + ] allowed_elements.sort(key=len, reverse=True) coef_fmt_elements = re.findall("|".join(allowed_elements), coef_fmt) @@ -1249,7 +1250,7 @@ def mean_newline_std(x): # Calculate the desired statistics if (byrow is not None) and (bycol is not None): - bylist = [byrow] + bycol + bylist = [byrow, *bycol] res = df.groupby(bylist).agg(agg_funcs) if (byrow is None) and (bycol is None): res = df.agg(agg_funcs) @@ -1342,7 +1343,7 @@ def mean_newline_std(x): # Finally we want to have the objects first and then the statistics if not isinstance(res.columns, pd.MultiIndex): res.columns = pd.MultiIndex.from_tuples(res.columns) - res.columns = res.columns.reorder_levels(bycol + ["Statistics"]) + res.columns = res.columns.reorder_levels([*bycol, "Statistics"]) # And sort it properly by the variables # (we want to preserve the order of the lowest level for the stats) levels_to_sort = list(range(res.columns.nlevels - 1)) diff --git a/pyproject.toml b/pyproject.toml index bbe73556..133072fb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -135,6 +135,7 @@ select = [ "D", # flake8-docstrings "UP", # pyupgrade "SIM", # flake8-simplify + "RUF", # ruff, "TRY", # tryceratops ] diff --git a/tests/test_did.py b/tests/test_did.py index 890107d3..942e6b4f 100644 --- a/tests/test_did.py +++ b/tests/test_did.py @@ -176,7 +176,7 @@ def test_errors(data): rng = np.random.default_rng(12) data["treat2"] = rng.choice([0, 1, 2], size=len(data)) with pytest.raises(ValueError): - fit = did2s_pyfixest( # noqa: F841 + fit = did2s_pyfixest( data, yname="dep_var", first_stage="~ X | state + year", diff --git a/tests/test_poisson.py b/tests/test_poisson.py index 3c00f5ce..907b4e58 100644 --- a/tests/test_poisson.py +++ b/tests/test_poisson.py @@ -35,7 +35,7 @@ def test_separation(): with pytest.warns( UserWarning, match="2 observations removed because of separation." ): - fepois("Y ~ X | fe1", data=example1, vcov="hetero", separation_check=["fe"]) # noqa: F841 + fepois("Y ~ X | fe1", data=example1, vcov="hetero", separation_check=["fe"]) if False: # this example is taken from ppmlhdfe's primer on separation https://github.com/sergiocorreia/ppmlhdfe/blob/master/guides/separation_primer.md @@ -52,7 +52,7 @@ def test_separation(): with pytest.warns( UserWarning, match="2 observations removed because of separation." ): - fepois("Y ~ X1 + X2", data=example2, vcov="hetero", separation_check=["ir"]) # noqa: F841 + fepois("Y ~ X1 + X2", data=example2, vcov="hetero", separation_check=["ir"]) # ppmlhdfe test data sets (check readme in data/ppmlhdfe_separation_examples) path = os.path.dirname(os.path.abspath(__file__)) diff --git a/tests/test_predict_resid_fixef.py b/tests/test_predict_resid_fixef.py index 7762a886..18aa711f 100644 --- a/tests/test_predict_resid_fixef.py +++ b/tests/test_predict_resid_fixef.py @@ -149,7 +149,7 @@ def test_vs_fixest(data, fml): raise ValueError("Predictions for OLS are not of the same length.") # test predict for Poisson - # if not np.allclose(fepois_mod.predict(data = data2), stats.predict(r_fixest_pois, newdata = data2)): # noqa: W505 + # if not np.allclose(fepois_mod.predict(data = data2), stats.predict(r_fixest_pois, newdata = data2)): # raise ValueError("Predictions for Poisson are not equal") # test resid for OLS diff --git a/tests/test_ses.py b/tests/test_ses.py index 0273d749..4c7abd9a 100644 --- a/tests/test_ses.py +++ b/tests/test_ses.py @@ -205,7 +205,7 @@ def test_CRV3_fixef(N, seed, beta_type, error_type): @pytest.mark.slow def run_crv3_poisson(): data = get_data(N=1000, seed=1234, beta_type="1", error_type="1", model="Fepois") - fit = fepois( # noqa: F841 + fit = fepois( fml="Y~X1 + C(f2)", data=data, vcov={"CRV3": "f1"}, diff --git a/tests/test_vs_fixest.py b/tests/test_vs_fixest.py index 30630db5..70be2a25 100644 --- a/tests/test_vs_fixest.py +++ b/tests/test_vs_fixest.py @@ -50,14 +50,14 @@ ("Y ~ X1 + i(f1, ref = 1) | f2 + f3"), ("Y ~ X1 + i(f1) + i(f2)"), ("Y ~ X1 + i(f1, ref = 1) + i(f2, ref = 2)"), - # ("Y ~ X1 + C(f1):C(fe2)"), # currently does not work as C():C() translation not implemented # noqa: W505 - # ("Y ~ X1 + C(f1):C(fe2) | f3"), # currently does not work as C():C() translation not implemented # noqa: W505 + # ("Y ~ X1 + C(f1):C(fe2)"), # currently does not work as C():C() translation not implemented + # ("Y ~ X1 + C(f1):C(fe2) | f3"), # currently does not work as C():C() translation not implemented ("Y ~ X1 + X2:f1"), ("Y ~ X1 + X2:f1 | f3"), ("Y ~ X1 + X2:f1 | f3 + f1"), - # ("log(Y) ~ X1:X2 | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) # noqa: W505 - # ("log(Y) ~ log(X1):X2 | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) # noqa: W505 - # ("Y ~ X2 + exp(X1) | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) # noqa: W505 + # ("log(Y) ~ X1:X2 | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) + # ("log(Y) ~ log(X1):X2 | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) + # ("Y ~ X2 + exp(X1) | f3 + f1"), # currently, causes big problems for Fepois (takes a long time) ("Y ~ X1 + i(f1,X2)"), ("Y ~ X1 + i(f1,X2) + i(f2, X2)"), ("Y ~ X1 + i(f1,X2, ref =1) + i(f2)"), @@ -69,14 +69,14 @@ ("Y ~ X1 + i(f2,X2, ref=2.0)"), ("Y ~ X1 + i(f1,X2, ref=3.0) | f2"), ("Y ~ X1 + i(f1,X2, ref=4.0) | f2 + f3"), - # ("Y ~ C(f1):X2"), # currently does not work as C():X translation not implemented # noqa: W505 + # ("Y ~ C(f1):X2"), # currently does not work as C():X translation not implemented # ("Y ~ C(f1):C(f2)"), # currently does not work ("Y ~ X1 + I(X2 ** 2)"), ("Y ~ X1 + I(X1 ** 2) + I(X2**4)"), ("Y ~ X1*X2"), ("Y ~ X1*X2 | f1+f2"), - # ("Y ~ X1/X2"), # currently does not work as X1/X2 translation not implemented # noqa: W505 - # ("Y ~ X1/X2 | f1+f2"), # currently does not work as X1/X2 translation not implemented # noqa: W505 + # ("Y ~ X1/X2"), # currently does not work as X1/X2 translation not implemented + # ("Y ~ X1/X2 | f1+f2"), # currently does not work as X1/X2 translation not implemented ("Y ~ X1 + poly(X2, 2) | f1"), ] @@ -470,10 +470,10 @@ def test_single_fit_fepois( check_absolute_diff(py_deviance, r_deviance, 1e-08, "py_deviance != r_deviance") if not mod._has_fixef: - py_predict_response = mod.predict(type="response") # noqa: F841 - py_predict_link = mod.predict(type="link") # noqa: F841 - r_predict_response = stats.predict(r_fixest, type="response") # noqa: F841 - r_predict_link = stats.predict(r_fixest, type="link") # noqa: F841 + py_predict_response = mod.predict(type="response") + py_predict_link = mod.predict(type="link") + r_predict_response = stats.predict(r_fixest, type="response") + r_predict_link = stats.predict(r_fixest, type="link") check_absolute_diff( py_predict_response[0:5], r_predict_response[0:5],