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@@ -9,23 +9,24 @@ The Python track provides tutorials and resources to help and inspire women to e
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💻 Technical Webinars 📲 Coding Resources 💭 Study Group Sessions 🗺️ Supportive Global Network
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**If you're interested in joining the community as a member or volunteer please visit our [website](https://www.womenwhocode.com/python) for more information! Or send us an [email](python@womenwhocode.com).**
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**If you're interested in joining the community as a member or volunteer, please visit our [website](https://www.womenwhocode.com/python) for more information! Or send us an [email](python@womenwhocode.com).**
Expand the section below to find all the resources shared during past and upcoming events. Clicking on a logo will take you to the event code base and/or slides. You will also find a link to the video recording in the event description. All of our events are uploaded to the [Women Who Code Youtube Channel](https://www.youtube.com/channel/UCfMEaBUSABoOsxr7HgSmEdA) 1-3 days following an event. Please reach out with any questions or issues, and join us on Slack for interactive discussions and support.
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Expand the section below to find all the resources shared during past and upcoming events. Clicking on a logo will take you to the event code base and/or slides. You will also find a link to the video recording in the event description. All of our events are uploaded to the [Women Who Code Youtube Channel](https://www.youtube.com/playlist?list=PLVcEZG2JPVhd8nd_UOjOkocVn_5u_YrcD) 1-7 days following an event. Please reach out with any questions or issues, and join us on Slack for interactive discussions and support.
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To add new resources for events follow the [CONTRIBUTING guidelines](ContributingGuidelines.md).
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To add new resources for events, follow the [CONTRIBUTING guidelines](ContributingGuidelines.md).
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<tdcolspan="4"><h3><br><em>Clicking on a logo below will take you to the associated repo -- where you can review, copy or clone the repo's content. Please reach out with any questions or issues, and/or join us on Slack for interactive discussions and support.</em><br><br></h3></td>
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<!-- Introduction to Coding Environments for Python -->
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<tdstyle="border: none;"align="left"width="20%"><ahref="https://github.com/jessicakoubi/wwcode_pyton_ide_series.git"><imgalt="Introduction to Coding Environments for Python"align="left"src="images/intro_to_code_env.png"/> </td>
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<tdcolspan="3"><b>Introduction to Coding Environments for Python</b>
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<br><br>
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Jupyter. Visual Studio Code. PyCharm. Confused about which IDE or code/text editor to use for your next Python project? Want to know the differences between IDE's and code/text editors? Not to worry! We have you covered!
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Join us for an exciting series that will introduce you to some of the popular coding environments used for Python, including: Google Colab, Jupyter notebooks, Visual Studio Code, PyCharm, Vim, Anaconda, and more!
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<br><br>
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<em>- By Poojita Garg, Jessica Koubi and Nayeon Shin</em></td>
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<!-- Introduction to Qt -->
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<tdstyle="border: none;"align="left"width="20%"><ahref="https://github.com/jessicakoubi/talk_introduction_to_qt"><imgalt="Introduction to Qt"align="left"src="images/intro_to_qt.png"/> </td>
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<tdstyle="border: none;"align="left"width="20%"><ahref="https://github.com/jessicakoubi/talk_coding_for_the_movie_industry"><imgalt="May the Pipeline be with you: Coding for the Movie Industry"align="left"src="images/coding_for_the_movie_industry.png"/> </td>
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<tdcolspan="3"><b>May the Pipeline Be with You: Coding for the Movie Industry</b>
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<br><br>
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This talk will introduce you to the role of a Pipeline Technical Director in the VFX/Animation industry. We will go over who works as Pipeline TD, which kind of software development is done in the movie industry, and finally, we will look at some of the tools developed for Avengers: Infinity War.
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This talk will introduce you to the role of a Pipeline Technical Director in the VFX/Animation industry. We will go over who works as Pipeline TD, which kind of software development is done in the movie industry, and finally, we will look at some of the tools developed for Avengers: Infinity War.
Stay tuned every Tuesday on our Instagram, Twitter, and LinkedIn page for a new Trivia Tuesday.
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<em>- By Sara A. Metwalli</em></td>
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<tdstyle="border: none;"align="left"width="20%"><ahref="https://github.com/nuageklow/WWCodePython_BeginnerSeries"><imgalt="Beginner Python Study Group"align="left"src="images/Beginner_Python_Study_Group_GitHub.png"/> </td>
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<tdcolspan="3"><b>Beginner Python Study Group 2020</b>
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<em>- By Jiaqi Liu</em></td>
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<tdstyle="border: none;"align="left"width="20%"><ahref="https://github.com/ShreyaKhurana/wwc/tree/master"><imgalt="NLP Contextual Word Embeddings"align="left"src="images/NLP_logo.jpg"/> </td>
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<tdcolspan="3"><b>NLP Contextual Word Embeddings</b>
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Functions like **lambda** , **filter**, **map**, & **reduce** fully support the Functional Programming style & in this live coding session we'll demonstrate how they can be effectively & efficiently used in our data analysis tasks.
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**Here are some good reads on Functional Programming, to get your started :**
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1.[**Don't be Scared of Functional Programming**](https://www.smashingmagazine.com/2014/07/dont-be-scared-of-functional-programming/)
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<p>In <b>Session I</b> you will be introduced to Apache Spark main concepts & you'll learn how to leverage the DataFrame API to extract data. You will also learn how to connect to different sources, apply schemas when reading data, and handle corrupt records.
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<b>PART I:</b> [](https://colab.research.google.com/drive/1NcSbNMgjMFqEl64qA0fmpRX7IrHuUx3u)
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In <b>session II</b> you will be introduced to some of the most useful transformations - adding new columns, casting column types, renaming columns, etc. You'll also learn how to define User Defined Functions to do your own custom transformations & a get a little introduction to executing your own ad hoc SQL!
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<b>PART II:</b> [](https://colab.research.google.com/drive/1T3bimqE9-OX4gSW4Zfjo3HjI-xPXBdK9)
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In <b>session III</b> you'll analyze the robberies data by doing some aggregations & sorting. You'll learn how to convert Spark DataFrames to Pandas DataFrames. Additionally, you'll explore joins & lookup tables & write final results to CSV files. At the end of this session we'll go over best practices.
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<b>PART III:</b> [](https://colab.research.google.com/drive/1x3HcVAs9HpUMgCGfbRfdq--6IQII0Fn5)
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</p><em>- By Aida Martinez</em>
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