.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "checks_gallery/tabular/data_integrity/plot_mixed_nulls.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_checks_gallery_tabular_data_integrity_plot_mixed_nulls.py: Mixed Nulls *********** .. GENERATED FROM PYTHON SOURCE LINES 8-13 .. code-block:: default import pandas as pd from deepchecks.tabular.checks import MixedNulls .. GENERATED FROM PYTHON SOURCE LINES 14-19 .. code-block:: default data = {'col1': ['sog', '1', 'cat', None, None]} dataframe = pd.DataFrame(data=data) MixedNulls().run(dataframe) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none /home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:886: UserWarning: Received a "pandas.DataFrame" instance. It is recommended to pass a "deepchecks.tabular.Dataset" instance by doing "Dataset(dataframe)" /home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:581: UserWarning: It is recommended to initialize Dataset with categorical features by doing "Dataset(df, cat_features=categorical_list)". No categorical features were passed, therefore heuristically inferring categorical features in the data. 0 categorical features were inferred .. raw:: html
Mixed Nulls


.. GENERATED FROM PYTHON SOURCE LINES 20-24 .. code-block:: default data = {'col1': ['nan', None, 'null', 'Nan', '1', 'cat'], 'col2':['', '', 'None', 'a', 'b', 'c'], 'col3': [1,2,3,4,5,6]} dataframe = pd.DataFrame(data=data) MixedNulls().run(dataframe) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none /home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:886: UserWarning: Received a "pandas.DataFrame" instance. It is recommended to pass a "deepchecks.tabular.Dataset" instance by doing "Dataset(dataframe)" /home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:581: UserWarning: It is recommended to initialize Dataset with categorical features by doing "Dataset(df, cat_features=categorical_list)". No categorical features were passed, therefore heuristically inferring categorical features in the data. 0 categorical features were inferred .. raw:: html
Mixed Nulls


.. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.121 seconds) .. _sphx_glr_download_checks_gallery_tabular_data_integrity_plot_mixed_nulls.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_mixed_nulls.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_mixed_nulls.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_