String Mismatch Comparison

.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "tabular/auto_checks/train_test_validation/plot_string_mismatch_comparison.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_tabular_auto_checks_train_test_validation_plot_string_mismatch_comparison.py: .. _tabular__string_mismatch_comparison: String Mismatch Comparison ************************** This page provides an overview for using and understanding the "String Mismatch Comparison" check. **Structure:** * `What is the purpose of the check? <#what-is-the-purpose-of-the-check>`__ * `Run check <#run-the-check>`__ * `Define a condition <#define-a-condition>`__ What is the purpose of the check? ================================= The check compares the same categorical column within train and test and checks whether there are variants of similar strings that exists only in test and not in train. Finding those mismatches is helpful to prevent errors when inferring on the test data. For example, in train data we have category 'New York', and in our test data we have 'new york'. We would like to be acknowledged that the test data contain a new variant of the train data, so we can address the problem. How String Mismatch Defined? ---------------------------- To recognize string mismatch, we transform each string to it's base form. The base form is the string with only its alphanumeric characters in lowercase. (For example "Cat-9?!" base form is "cat9"). If two strings have the same base form, they are considered to be the same. .. GENERATED FROM PYTHON SOURCE LINES 31-34 .. code-block:: default import pandas as pd .. GENERATED FROM PYTHON SOURCE LINES 35-37 Run the Check ============= .. GENERATED FROM PYTHON SOURCE LINES 37-46 .. code-block:: default from deepchecks.tabular.checks import StringMismatchComparison data = {'col1': ['Deep', 'deep', 'deep!!!', 'earth', 'foo', 'bar', 'foo?']} compared_data = {'col1': ['Deep', 'deep', '$deeP$', 'earth', 'foo', 'bar', 'foo?', '?deep']} check = StringMismatchComparison() result = check.run(pd.DataFrame(data=data), pd.DataFrame(data=compared_data)) result .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 47-49 Define a Condition ================== .. GENERATED FROM PYTHON SOURCE LINES 49-53 .. code-block:: default check = StringMismatchComparison().add_condition_no_new_variants() result = check.run(pd.DataFrame(data=data), pd.DataFrame(data=compared_data)) result.show(show_additional_outputs=False) .. raw:: html

String Mismatch Comparison

.. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.056 seconds) .. _sphx_glr_download_tabular_auto_checks_train_test_validation_plot_string_mismatch_comparison.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_string_mismatch_comparison.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_string_mismatch_comparison.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_