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. Drawing commands could render the component images by placement, and then save the final image.Import networkx as nx import matplotlib.pyplot as plt #import numpy as np #import sklearn as skl #plt.figure(figsize=) G = nx. Or, layout could use pre-built images, and specify location, image-name, and orientation.Shape drawing commands could then render the stylized shapes, and save the final image. Layout could specify shapes and colors, e.g. JSON file dictating layout of named button controls.Solution will be to migrate to 100% Python compositing.Also, the Python libraries to extract PSD data have their own issues, following Adobe's out-of-date and wrong specification, plus they are maintained by volunteers who may not have motivation to solve my particular compatibility issues. Everyone involved in the project does not own a license from Adobe and instead uses their own PSD editor. Working with Photoshop PSD files is proving problematic due to compatibility issues.
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