You’re encouraged to experiment with these tools, exploring beyond the basics to discover how they might enhance your academic, collaborative, and research projects. HTML code that integrates LaTeX for Mathematical NotationĪction: Specifically this in double-quotes: “Here’s an inline equation: \(E=mc^2\)”.Īfter completing these exercises, you should have a foundational understanding of how Markdown, LaTeX, and HTML can be used together to create rich, well-documented, and interactive content. Task: While still in your hw1 GitHub repo, ask ChatGPT or any other GPT to give you. Objective: Learn to incorporate LaTeX within Markdown files for displaying mathematical equations and symbols. 3.4.3 Integrating LaTeX for Mathematical Notation # Internal Link Example: (./hw1.do)Īfter completing these exercises, you should have a foundational understanding of how Markdown, LaTeX, and HTML can be used together to create rich, well-documented, and interactive content. your hw1.do raw URL).Īction: Use Markdown to link to another section within your book and to an external website. Task: While still in your hw1 GitHub repo, add internal links to other sections and external links to resources (e.g. Objective: Design navigable documents with internal and external links. **Widely supported:** Used on platforms like GitHub and Jupyter.ģ.4.2 Linking Sections and External Resources # **Easy to write and read:** Ideal for documentation and notes. Markdown is a lightweight markup language with plain-text formatting syntax. Task: Add a new section in your hw3 repo titled “Introduction to Markdown.”Īction: Create a new Markdown file ( index.md) and write a brief introduction to Markdown.Ĭode: Use the following Markdown elements: headers, lists, emphasis (bold and italic), and links. Objective: Familiarize yourself with Markdown syntax to create well-documented sections in your Markdown files. 3.4 Lab # 3.4.1 Basic Markdown for Documentation # They offer a powerful tool for engagement and flexibility but come with considerations for workflow integration and user expertise. In sum, while the use of _request() and similar interactive commands opens up new avenues for customized data analysis, it’s essential to consider the context of their use carefully. Novice Users: Those unfamiliar with Stata’s syntax or the specific requirements of the script may find the _request() prompts challenging, potentially leading to errors or confusion. It empowers users to tailor the analysis to their specific context, enhancing both the relevance and accuracy of the output.įlexibility and Customization: Users can tailor analyses to their specific datasets and preferences, making the script versatile across different projects.Įnhanced User Experience: By engaging users through input requests, the analysis becomes a collaborative process rather than a static execution of code.Īutomated Processing: In scenarios requiring batch processing or automation, pausing for user input disrupts the workflow and efficiency. This approach, particularly the use of _request(), is a paradigm shift towards more interactive and responsive statistical programming. When formatting the value of a macro, using the : di syntax 3.3 Pompt-based programming # Use the = when defining a macro using arithmetic proceedures. get_node_attributes ( G, 'pos' ), with_labels = True, font_weight = 'bold', node_size = 4500, node_color = "lightblue", linewidths = 3 ) ax = plt. add_node ( "results", pos = ( 0, 0 )) G. Import networkx as nx import matplotlib.pyplot as plt #import numpy as np #import sklearn as skl #plt.figure(figsize=) G = nx.
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