See below for instructions to run your first Jupyter notebook using GitHub Codespaces – no downloads necessary! If you haven’t used GitHub yet, see Get Started in GitHub! Navigate to the Kit Marlowe Project’s Jupyter Notebooks repository. GitHub Repository Link:https://github.com/alex-krtt/kitmarlowe-jupyter/tree/main
Get started in GitHub!
See instructions below to set up an account and to get started using GitHub! Navigate to https://github.com/signup Provide a valid email address that you have access to. Create a strong password adhering to the on-screen requirements Enter your desired username
Alexander Krett – Spring 2024
Spring 2024 Internship – Summary of Project Work Project Background:This project showcases the applications of Python for humanities-based text analysis. Using corpora created from William Shakespeare’s and Christopher Marlowe’s dramatic works, I wrote code to create five platforms for text
Anaconda – Running your first JupyterLab notebook
Now that we have gotten Anaconda installed, we will need to download the Kitmarlowe repository from GitHub so that we can use the code and the accompanying books to run a few analyses. GitHub Repository Link:https://github.com/alex-krtt/kitmarlowe-jupyter/tree/main On macOS, double the
Anaconda – Windows 10/11 Installation Guide
Navigate to https://www.anaconda.com/download and click Download. Double click the downloaded installer. Check the following options:► Create start menu shortcuts (supported packages only).► Register Anaconda3 as my default Python 3.11► Clear the package cache upon completion Installation may take a couple
Anaconda – macOS Installation Guide
Navigate to https://www.anaconda.com/download and click Download. In order to determine which option Download for Mac (Intel) or (M1/M2/M3) a) Click the Apple Logo on the top left corner of the screen. b) Click “About This Mac”. The line that states
Table of Contents for Kit Marlowe Project’s JupyterLab GitHub
Table of Contents Generates list of the most common words, adjectives and verbs for all books. Creates a lexical dispersion plot for all books. Creates a sentiment analysis graph for all books. Compares all Shakespeare to Marlowe corpus books. (Original