Elizabeth Bolin's repositories
Amazon_Vine_Analysis
Use PySpark to perform the ETL process to extract the dataset, transform the data, connect to an AWS RDS instance, and load the transformed data into pgAdmin. Next, use PySpark, Pandas, or SQL to determine if there is any bias toward favorable reviews from Vine members in the dataset.
Belly_Button_Biodiversity
A dashboard built with JavaScript, HTML, and data from a JSON file
Bolin_Yelp
My personal repo for Yelp exploratory analysis
Crowdfunding-ETL
Extract, Transform and Load data using Python, Pandas, pgAdmin and jupyter notebook
Election_Analysis
Building a scalable election audit process using Python
Pewlett-Hackard-Analysis
Using SQL to query employee data to forecast retirements and employment needs
World_Weather_Analysis
Conduct world weather analysis using APIs and build custom maps for travel industry
EBolinVA
Config files for my GitHub profile.
Green_Stocks_Analysis
Refactor script for stock analysis using Excel VBA
Kickstarter_Analysis
Performing analysis on Kickstarter data to uncover trends
Mapping_Earthquakes
Show the differences between the magnitudes of earthquakes all over the world for the last seven days using GeoJSON earthquake data from the USGS website
markdown-cheatsheet
Markdown Cheatsheet for Github Readme.md
MechaCar_Statistical_Analysis
Statistical review of production data for auto manufacturing team's prototype vehicles.
Netflix_Analysis
Data clean-up, building tables, creating queries
NYC_Bikeshare
Visualize NYC Bikeshare usage data using Tableau.
PyBer_Analysis
Use descriptive statistics to analyze and visualize ride-sharing data with Python, Pandas and the Matplotlib library
School_Data_Analysis
Collecting, cleaning, and summarizing school data using Python and jupyter notebook
Surfs_Up
Business Analysis for hypothetical surf & shake shack, analyzing weather using SQLite, SQLAlchemy, and Flask database structures and querying methods. Python code is written and executed in a Jupyter notebook and graphs are created using Python.
UFOs
Build a table using data stored in a JavaScript array, create filters to make this table fully dynamic, reacting to user input, and then place the table into an HTML file for easy viewing. Customize a webpage using Bootstrap, and equip the table with several fully functional filters that will allow users to interact with visualizations.