Pushing the docs to dev/ for branch: master, commit 36abde7eed70e809859f91342bce2d8db9e5046a

Author: sklearn-ci

dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -133,7 +133,6 @@
 
 from sklearn.experimental import enable_hist_gradient_boosting  # noqa
 from sklearn.ensemble import HistGradientBoostingClassifier
-import numpy as np
 
 X = np.array([0, 1, 2, np.nan]).reshape(-1, 1)
 y = [0, 0, 1, 1]
@@ -189,7 +188,6 @@
 #
 # Read more in the :ref:`User Guide <knnimpute>`.
 
-import numpy as np
 from sklearn.impute import KNNImputer
 
 X = [[1, 2, np.nan], [3, 4, 3], [np.nan, 6, 5], [8, 8, 7]]

dev/_downloads/50040ae12dd16e7d2e79135d7793c17e/plot_release_highlights_0_22_0.py

@@ -87,7 +87,7 @@
       },
       "outputs": [],
       "source": [
-        "from sklearn.experimental import enable_hist_gradient_boosting  # noqa\nfrom sklearn.ensemble import HistGradientBoostingClassifier\nimport numpy as np\n\nX = np.array([0, 1, 2, np.nan]).reshape(-1, 1)\ny = [0, 0, 1, 1]\n\ngbdt = HistGradientBoostingClassifier(min_samples_leaf=1).fit(X, y)\nprint(gbdt.predict(X))"
+        "from sklearn.experimental import enable_hist_gradient_boosting  # noqa\nfrom sklearn.ensemble import HistGradientBoostingClassifier\n\nX = np.array([0, 1, 2, np.nan]).reshape(-1, 1)\ny = [0, 0, 1, 1]\n\ngbdt = HistGradientBoostingClassifier(min_samples_leaf=1).fit(X, y)\nprint(gbdt.predict(X))"
       ]
     },
     {
@@ -123,7 +123,7 @@
       },
       "outputs": [],
       "source": [
-        "import numpy as np\nfrom sklearn.impute import KNNImputer\n\nX = [[1, 2, np.nan], [3, 4, 3], [np.nan, 6, 5], [8, 8, 7]]\nimputer = KNNImputer(n_neighbors=2)\nprint(imputer.fit_transform(X))"
+        "from sklearn.impute import KNNImputer\n\nX = [[1, 2, np.nan], [3, 4, 3], [np.nan, 6, 5], [8, 8, 7]]\nimputer = KNNImputer(n_neighbors=2)\nprint(imputer.fit_transform(X))"
       ]
     },
     {