.. _sphx_glr_auto_examples_01_encoding:

Encoding features
=================


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    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to transform a rich dataframe with columns of various types into a numerical matrix on which machine-learning algorithms can be applied. We study the case of predicting wages using the employee salaries dataset.">

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  :doc:`/auto_examples/01_encoding/0010_encodings`

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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, we explore the performance of string and categorical encoders available in skrub.">

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  :doc:`/auto_examples/01_encoding/0020_text_with_string_encoders`

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      <div class="sphx-glr-thumbnail-title">Various string encoders: a sentiment analysis example</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, we illustrate how to better integrate datetime features in machine learning models with the |DatetimeEncoder|.">

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  :doc:`/auto_examples/01_encoding/0030_datetime_encoder`

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      <div class="sphx-glr-thumbnail-title">Handling datetime features with the DatetimeEncoder</div>
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.. toctree::
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   /auto_examples/01_encoding/0010_encodings
   /auto_examples/01_encoding/0020_text_with_string_encoders
   /auto_examples/01_encoding/0030_datetime_encoder