Python + Jupyter Projects
Middle School Big Data Analysis Project
•Determined if features of middle schools predict selective high school admissions using multiple linear regression
•Reduced dimensions using sklearn to perform Principle Component Analysis on variables that had a moderate to strong correlation.
•Before every PCA, the data were standardized using z-scores, the eigenvalues and loadings of the principal complements were found and graphed.
•Used the t-test to determine whether being in a charter school or not impacts number of admissions to HSPHS.
CSV Reader
• Created a module for reading in csvs and filtering rows based on column values using OOP
• Built table and labelled list classes
• Labelled List functions implemented: getitem(), str(), iter(), eq(), ne(), gt(), lt(), and map()
• Table functions implemented: getitem(), str(), head() and tail(), shape()
• Finally created read_csv() function, which works in a similar fashion to that in the pandas module.
• Performed analysis on occupations data (csv file) using module