Merge pull request #146 from scikit-learn-contrib/doc_categorical_patch

plot_tuto_categorical.py has been patched

Author: JulienRoussel77

examples/tutorials/plot_tuto_categorical.py

@@ -22,6 +22,8 @@
 # We get the data and focus on the explanatory variables
 df = data.get_data("Titanic")
 df = df.drop(columns=["Survived"])
+print("Dataset shape:", df.shape)
+df.head()
 
 # %%
 # 2. Mixed type imputation methods
@@ -61,7 +63,7 @@
 imputer_hgb = ImputerRegressor(estimator=pipestimator, handler_nan="none")
 imputer_wrap_hgb = preprocessing.WrapperTransformer(imputer_hgb, bt)
 
-#  %%
+# %%
 # 3. Mixed type model selection
 # ---------------------------------------------------------------
 # Let us now compare these three aproaches by measuring their ability to impute uniformly

setup.py

@@ -33,12 +33,13 @@
     "category_encoders",
     "dcor>=0.6",
     "hyperopt",
-    "numpy>=1.19",
+    "numpy>=1.21",
     "packaging",
     "pandas>=1.3",
     "scikit-learn",
     "scipy",
     "statsmodels>=0.14",
+    "typing-extensions",
 ]
 EXTRAS_REQUIRE = {
     "tests": ["flake8", "mypy", "pandas", "pytest", "pytest-cov", "typed-ast"],
@@ -47,7 +48,6 @@
         "sphinx",
         "sphinx-gallery",
         "sphinx_rtd_theme",
-        "typing_extensions",
     ],
     "pytorch": [
         "torch==2.0.1",