.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/plot/plot_diamonds.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_plot_diamonds.py: Diamonds Dataset Visualization ========================================== Regression on the classical diamond dataset. .. GENERATED FROM PYTHON SOURCE LINES 6-15 .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/plot/images/sphx_glr_plot_diamonds_001.png :alt: Target distribution :srcset: /auto_examples/plot/images/sphx_glr_plot_diamonds_001.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/plot/images/sphx_glr_plot_diamonds_002.png :alt: Continuous Feature vs Target, F=9.63E-01, F=1.72E-01, F=1.00E-02 :srcset: /auto_examples/plot/images/sphx_glr_plot_diamonds_002.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/plot/images/sphx_glr_plot_diamonds_003.png :alt: Categorical Feature vs Target, F=3.61E-01, F=2.83E-01, F=1.04E-01 :srcset: /auto_examples/plot/images/sphx_glr_plot_diamonds_003.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out .. code-block:: none /home/circleci/project/~/miniconda/envs/testenv/lib/python3.11/site-packages/sklearn/datasets/_openml.py:322: UserWarning: Multiple active versions of the dataset matching the name diamonds exist. Versions may be fundamentally different, returning version 1. Available versions: - version 1, status: active url: https://www.openml.org/search?type=data&id=42225 - version 2, status: active url: https://www.openml.org/search?type=data&id=43998 warn(warning_msg) Target looks like regression /home/circleci/project/dabl/plot/supervised.py:107: UserWarning: Not plotting highly correlated (0.9961166041570525) feature carat. Set prune_correlations_threshold=0 to keep. warn(f"Not plotting highly correlated ({corr.max()})" /home/circleci/project/dabl/plot/supervised.py:107: UserWarning: Not plotting highly correlated (0.9978949275849379) feature y. Set prune_correlations_threshold=0 to keep. warn(f"Not plotting highly correlated ({corr.max()})" /home/circleci/project/dabl/plot/supervised.py:107: UserWarning: Not plotting highly correlated (0.9873553172140505) feature z. Set prune_correlations_threshold=0 to keep. warn(f"Not plotting highly correlated ({corr.max()})" /home/circleci/project/dabl/plot/supervised.py:214: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. medians = X_new.groupby(col)[target_col].median() /home/circleci/project/~/miniconda/envs/testenv/lib/python3.11/site-packages/seaborn/categorical.py:641: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. grouped_vals = vals.groupby(grouper) /home/circleci/project/dabl/plot/supervised.py:214: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. medians = X_new.groupby(col)[target_col].median() /home/circleci/project/~/miniconda/envs/testenv/lib/python3.11/site-packages/seaborn/categorical.py:641: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. grouped_vals = vals.groupby(grouper) /home/circleci/project/dabl/plot/supervised.py:214: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. medians = X_new.groupby(col)[target_col].median() /home/circleci/project/~/miniconda/envs/testenv/lib/python3.11/site-packages/seaborn/categorical.py:641: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. grouped_vals = vals.groupby(grouper) | .. code-block:: Python # sphinx_gallery_thumbnail_number = 2 import matplotlib.pyplot as plt from sklearn.datasets import fetch_openml from dabl import plot X, y = fetch_openml('diamonds', as_frame=True, return_X_y=True) plot(X, y) plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 13.201 seconds) .. _sphx_glr_download_auto_examples_plot_plot_diamonds.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_diamonds.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_diamonds.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_