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“Intro to Python for Working with Text” workshop series
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<h1>“Intro to Python for Working with Text” workshop series</h1>
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<h2> Contents </h2>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#workshop-overviews">Workshop overviews</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#upcoming-digital-scholarship-workshops">Upcoming Digital Scholarship Workshops</a></li>
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<section class="tex2jax_ignore mathjax_ignore" id="intro-to-python-for-working-with-text-workshop-series">
<h1>“Intro to Python for Working with Text” workshop series<a class="headerlink" href="#intro-to-python-for-working-with-text-workshop-series" title="Permalink to this heading">#</a></h1>
<p>By Filipa Calado, Princeton University</p>
<p><a class="reference external" href="mailto:filipa%40princeton.edu">filipa<span>@</span>princeton<span>.</span>edu</a></p>
<section id="welcome-to-the-series">
<h2>Welcome to the series!<a class="headerlink" href="#welcome-to-the-series" title="Permalink to this heading">#</a></h2>
<p>As one of the most popular, versatile, and beginner-friendly
programming langauges, Python can be used for a variety of tasks from
analyzing data to building websites.</p>
<p>This 5-part workshop series introduces participants to the Python
programming language for working with text. The first workshop begins
with core concepts, like data types, variables, functions, loops, and
conditional statements. The second and third workshops move to data
gathering and processing with web scraping, APIs, and text cleaning
methods. The fourth and fifth workshops explore text analysis with
Natural Language Processing (NLP) and deep learning tools. See a more
detailed description of each workshop below.</p>
<section id="workshop-overviews">
<h3>Workshop overviews<a class="headerlink" href="#workshop-overviews" title="Permalink to this heading">#</a></h3>
<p><strong>Workshop 1: “Introduction to Python Fundamentals”</strong></p>
<ul class="simple">
<li><p>Offers basic
introduction to core concepts in Python programming, grounded in a
critical awareness about data and what happens to data at various
levels of transformation and abstraction.</p></li>
</ul>
<p><strong>Workshop 2: “Python for Web Scraping and APIs”</strong></p>
<ul class="simple">
<li><p>Introduction to
ethics, legality, and programmatic methods for extracting data from
the web. Advances core concepts from introductory session (like loops and
conditional statements) and adds new concepts on object-oriented
programming and working with Python libraries. Participants practice
scraping metadata from current “anti-trans” bills in the USA.</p></li>
<li><p>libraries: <code class="docutils literal notranslate"><span class="pre">requests</span></code>, <code class="docutils literal notranslate"><span class="pre">bs4</span></code>, and <code class="docutils literal notranslate"><span class="pre">pandas</span></code></p></li>
</ul>
<p><strong>Workshop 3: “Python for Text Cleaning”</strong></p>
<ul class="simple">
<li><p>Experiments with approaches for wrangling
text data into formats for analysis, with emphasis on removing unwanted
elements that may skew analysis. While building on skills
for writing loops and conditional statements and working with
external libraries, participants will learn to write functions and
scripts for running customized text cleaning processes.</p></li>
<li><p>libraries: <code class="docutils literal notranslate"><span class="pre">pandas</span></code>, <code class="docutils literal notranslate"><span class="pre">spacy</span></code></p></li>
</ul>
<p><strong>Workshop 4: “Python for Text Analysis”</strong></p>
<ul class="simple">
<li><p>Explores methods for finding and analyzing textual patterns through popular tasks in Natural
Language Processing. Participants practice writing code to annotate
and extract text according to specific features from current
“anti-trans” bills in the USA.</p></li>
<li><p>libraries: <code class="docutils literal notranslate"><span class="pre">spaCy</span></code></p></li>
</ul>
<p>*<strong>Workshop 5: “Python for Text Generation (with Machine Learning)”</strong></p>
<ul class="simple">
<li><p>With the anti-trans bills data that they prepared in previous workshops, participants practice fine-tuning a small Text Generation model and learn about how to use Machine Learning for research.</p></li>
<li><p>libraries: <code class="docutils literal notranslate"><span class="pre">transformers</span></code></p></li>
</ul>
</section>
</section>
<section id="upcoming-digital-scholarship-workshops">
<h2>Upcoming Digital Scholarship Workshops<a class="headerlink" href="#upcoming-digital-scholarship-workshops" title="Permalink to this heading">#</a></h2>
<p>See more workshop offerings (including on Python) at the <a class="reference external" href="https://libcal.princeton.edu/calendar/">Princeton University library</a>. We have upcoming workshops on working with data, digital publishing, and more.</p>
<p>Want to talk Python or another digital project or tool? Sign up for a <a class="reference external" href="https://bit.ly/ds-consults">consultation with Digital Scholarship</a> at Princeton.</p>
<p>For other workshops and reference materials on computational methods at Princeton University, check out <a class="reference external" href="https://researchcomputing.princeton.edu/">Research Computing</a>.</p>
</section>
<section id="sources">
<h2>Sources<a class="headerlink" href="#sources" title="Permalink to this heading">#</a></h2>
<p>This curriculum is inspired by the <a class="reference external" href="https://gcdi.commons.gc.cuny.edu/">Graduate Center Digital
Initiatives</a> Digital Humanities
Research Institute <a class="reference external" href="https://github.com/DHRI-Curriculum/python">Python workshop</a>.</p>
<p>The opening challenge takes text from the <a class="reference external" href="https://www.manifestno.com/">Feminist Data Manifest-No</a> by M. Cifor, P. Garcia, et al.</p>
<p>For more instruction with Python, please see these books:</p>
<ul class="simple">
<li><p>WJB Mattingly’s <a class="reference external" href="https://python-textbook.pythonhumanities.com/intro.html">Introduction to Python for
Humanists</a></p></li>
<li><p>Melanie Walsh’s <a class="reference external" href="https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html">Introduction to Cultural Analytics &
Python</a></p></li>
</ul>
<p><a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</p>
</section>
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