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add gunicorn and pandas resources
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content/pages/03-data/16-pandas.markdown

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@@ -102,3 +102,8 @@ is a data structures and analysis library.
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* [Analyzing my Spotify Music Library With Jupyter And a Bit of Pandas](https://vsupalov.com/analyze-spotify-music-library-with-jupyter-pandas/)
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shows how to grab all of your user data from the Spotify API then
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analyze it using pandas in [Jupyter Notebook](/jupyter-notebook.html).
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* [Scalable Python Code with Pandas UDFs](https://towardsdatascience.com/scalable-python-code-with-pandas-udfs-a-data-science-application-dd515a628896)
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explains that pandas operations can often be parallelized for better
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performance using the Pandas UDFs feature in PySpark version 2.3
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or greater.

content/pages/05-deployment/23-gunicorn.markdown

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@@ -131,3 +131,7 @@ perform the request handling. Each worker is independent of the controller.
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context on how to choose the number of workers for your execution
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environment.
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* [Configuring Gunicorn for containers](https://pythonspeed.com/articles/gunicorn-in-docker/)
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explains how to avoid excessive slowness in your [Docker](/docker.html)
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containers that run Gunicorn workers, as well as some tips on
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proper logging.

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