Publications by Julian Adames-Ng
CRSP Sample
1. Geometric Transformation of Shapes Using Matrix Multiplication Context: In computer graphics and data visualization, geometric transformations are fundamental. These transformations, such as translation, scaling, rotation, and reflection, can be applied to shapes to manipulate their appearance. Task: Create a simple shape (like a square or tri...
800 sym 1 img
DATA 607 - Final Project
1. Introduction Initial Project Proposal: For my project, I aim to analyze NFL statistics to uncover insights into player performance and game outcomes. The motivation stems from the growing interest in data-driven sports analytics and its impact on player evaluation and fan engagement. I also have had growing interest in NFL data as someone who w...
10626 sym R (52009 sym/89 pcs) 4 img
DATA 607 - Project 4
Introduction It can be useful to be able to classify new “test” documents using already classified “training” documents. A common example is using a corpus of labeled spam and ham (non-spam) e-mails to predict whether or not a new document is spam. For this project, you can start with a spam/ham dataset, then predict the class of new docume...
3708 sym Python (7011 sym/20 pcs)
DATA 607 - Project 2c (Resubmit)
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
3256 sym 4 img
DATA 607 - Project 2b (Resubmit)
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
7085 sym Python (11514 sym/37 pcs) 4 img
DATA 607 - Assignment 6
Introduction This R script shows how to connect to the New York Times Books API to pull in data on the current bestsellers in the “hardcover fiction” category. It sends an HTTP request to the API, retrieves the data in JSON format, and then processes it into a structured R dataframe. This dataframe lets you easily access bestseller details for ...
2179 sym R (45502 sym/12 pcs)
DATA 607 - Assignment 5
Introduction This assignment focuses on utilizing R to create, store, and retrieve data in a variety of file formats. The process reflects a systematic approach to showcasing code and data output. Working with XML and JSON in R I chose the following three books to load into my data-frames. Book 1: Calculus by Ron Larson, Robert Hostetler, and Bru...
2185 sym R (5860 sym/15 pcs)
DATA 607 - Project 2c
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
6634 sym Python (12634 sym/37 pcs) 7 img
DATA 607 - Project 2a
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
7016 sym Python (15167 sym/33 pcs) 7 img
DATA 607 - Project 2b
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
7239 sym Python (33446 sym/41 pcs) 7 img