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Examples
===========



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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 numer...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_01_encodings_thumb.png
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  :ref:`sphx_glr_auto_examples_01_encodings.py`

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      <div class="sphx-glr-thumbnail-title">Encoding: from a dataframe to a numerical matrix for machine learning</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="In this notebook, we will explore the output and inner workings of the |GapEncoder|, one of the...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_02_feature_interpretation_with_gapencoder_thumb.png
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  :ref:`sphx_glr_auto_examples_02_feature_interpretation_with_gapencoder.py`

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      <div class="sphx-glr-thumbnail-title">Feature interpretation with the GapEncoder</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 mo...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_03_datetime_encoder_thumb.png
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  :ref:`sphx_glr_auto_examples_03_datetime_encoder.py`

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      <div class="sphx-glr-thumbnail-title">Handling datetime features with the DatetimeEncoder</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Here we show how to combine data from different sources, with a vocabulary not well normalized.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_04_fuzzy_joining_thumb.png
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  :ref:`sphx_glr_auto_examples_04_fuzzy_joining.py`

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      <div class="sphx-glr-thumbnail-title">Fuzzy joining dirty tables with the Joiner</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Real world datasets often come with misspellings, for instance in manually inputted categorical...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_05_deduplication_thumb.png
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  :ref:`sphx_glr_auto_examples_05_deduplication.py`

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      <div class="sphx-glr-thumbnail-title">Deduplicating misspelled categories</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="When the data comprises common entities (cities, companies or famous people), bringing new info...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_06_ken_embeddings_thumb.png
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  :ref:`sphx_glr_auto_examples_06_ken_embeddings.py`

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      <div class="sphx-glr-thumbnail-title">Wikipedia embeddings to enrich the data</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Joining tables may be difficult if one entry on one side does not have an exact match on the ot...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_07_multiple_key_join_thumb.png
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  :ref:`sphx_glr_auto_examples_07_multiple_key_join.py`

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      <div class="sphx-glr-thumbnail-title">Spatial join for flight data: Joining across multiple columns</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="MovieLens is a famous movie dataset used for both explicit and implicit recommender systems. It...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_08_join_aggregation_thumb.png
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  :ref:`sphx_glr_auto_examples_08_join_aggregation.py`

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      <div class="sphx-glr-thumbnail-title">Self-aggregation on MovieLens</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="We illustrate the InterpolationJoiner, which is a type of join where values from the second tab...">

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  .. image:: /auto_examples/images/thumb/sphx_glr_09_interpolation_join_thumb.png
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  :ref:`sphx_glr_auto_examples_09_interpolation_join.py`

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      <div class="sphx-glr-thumbnail-title">Interpolation join: infer missing rows when joining two tables</div>
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.. toctree::
   :hidden:

   /auto_examples/01_encodings
   /auto_examples/02_feature_interpretation_with_gapencoder
   /auto_examples/03_datetime_encoder
   /auto_examples/04_fuzzy_joining
   /auto_examples/05_deduplication
   /auto_examples/06_ken_embeddings
   /auto_examples/07_multiple_key_join
   /auto_examples/08_join_aggregation
   /auto_examples/09_interpolation_join



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