Applying Bing, AFINN, and Loughran lexicons to analyze sentiment in technical text. Demonstrates how lexicon choice affects results and shows limitations of emotion-based scoring for structured or business language.

Anawin Pikulthong DAT301 Midterm

This report presents the solutions to Problems 6.2 and 6.3 from Kuhn & Johnson’s Applied Predictive Modeling. It explores different regression models - including PLS, Elastic Net, and Random Forest - to predict compound permeability and manufacturing yield. The analysis includes model tuning, performance comparison, and visualization of top predictors with concise interpretations for each step.

DAT301 Midterm - Baseball Data

CCA biplot

Nobel Prize API Data Extraction Project Project Overview This project involved extracting and analyzing data from the Nobel Prize API to explore patterns and insights about Nobel laureates and their achievements. Key Components Data Extraction - Connected to the Nobel Prize API to retrieve comprehensive data about Nobel Prize winners - Extracted information including laureate details, prize categories, award years, and affiliations - Processed JSON data and transformed it into a tidy data format suitable for analysis Data Processing - Cleaned and structured the API response data using tidyverse tools - Created organized dataframes with key variables such as: - Laureate names and biographical information - Prize categories (Physics, Chemistry, Medicine, Literature, Peace, Economics) - Award years and prize motivations - Institutional affiliations and countries Analysis Focus Areas Potential areas explored could include: - Distribution of prizes across categories and time periods - Gender representation among laureates - Geographic patterns in prize winners - Age trends of laureates at time of award - Institutional affiliations and their prize frequencies Technical Skills Demonstrated - API integration and data retrieval - JSON data parsing and transformation - Data wrangling with dplyr and tidyr - Exploratory data analysis - Data visualization with ggplot2 This project showcases your ability to work with external APIs, handle real-world data structures, and apply tidy data principles to extract meaningful insights from public datasets.

STAT 427, Chapter 4 Homework, Time series statistics