Mini Projects:
Overview:
The goal of this project was to build a system that visualises the ever-fluctuating price of copper in the three major copper future exchanges: Shanghai Futures Exchange (SHFE), London Metal Exchange (LME), and CME Group / COMEX Copper (HG) and predict the opening price of copper in the New York-based COMEX.
Data Cleaning:
All three datasets containing historical prices of copper at the three major exchanges were converted into a data frame format and put into a standardized form before further processing by erasing index labels. For clarity purposes, the number of rows and columns for each dataset was obtained as well.
Overview:
The objective of this project was to zoom in on Exploratory Data Analysis in order to identify patterns between data collected on popularity, vote average, and artificially-made clusters.
Exploratory Data Analysis (EDA)
During this mini project, the EDA step was performed as multiple types of plots with varying axes were created using a data set involving movie genres (horror, comedy, etc.), popularity, and generated clusters based on an unknown perimeter. Close analysis of each plot allowed for conclusions to be drawn surrounding the data.
Overview:
The goal of the project was to determine if there was a correlation between income (measured by median income of a specific location, e.g. county/city) and air quality, measured by PM2.5, or particulate matter with a diameter of 2.5 micrometers or less.
Data acquisition
Data acquisition involved collecting data via the United States Census Bureau website, where a request was submitted for median income data for cities across the United States in 2023. Because the second part of the project required using counties as locations for FIPS, the project collected this additional information from the NIH HD Pulse California income data.