Project Overview: Reviewing the Titanic and the Estonia Datasets.
The main objective of this project is to examine both the datasets provided for the Titanic and the Estonia,
and determine relevant questions pertinent to these shipwrecks. Exploratory Data Analyses was completed for these datasets and data subsets.
The purpose of this project is to examine trends in this massive dataset of Prosper Loan Data to answer various economic and sociological questions.
An exploratory analysis and an explanatory analysis were both completed for this project.
This TMBd data file, which includes 10,000 movie records, was investigated to gain important insight into questions such as most profitable movies, most profitable directors, etc.
This PowerBI project uses a Netflix dataset with the Overview page containing the following charts: Shows Added By Date, Shows By Rating, Top 10 Genres, and Countries Available. The Single-Title-View page contains specific information to a tv show or movie. The tv show or movie is selected by a drop down selection.
The sales of these classic vehicles and planes are broken down by Sale numbers and Net Profit amounts. Various charts, filters, and bookmarks were used for the dashboard creation.
The dashboard for this bike sales dataset includes: Bike products by quantity, the age group of the categories of the products in a bubble chart with revenue determining the size of the bubble, a map of the world with total profit by country as the determining factor for the size of the bubble on the map, and a barchart where the product categories are broken down by profit and gender. There is also a ProfitCard with Year over Year % change, a Revenue Card, Cost Card, and a Year Parameter selection for the cards.
The dashboard for this electric vehicles dataset includes: Make & Model, Top 10 Counties in Washington State, Map of number of vehicles by postal code in Washington State, Year & Type by Battery or Plug-in Hybrid vehicles, and a Car Make drop down selection.
This SQL project includes data cleaning and performing an Exploratory Data Analysis on employer layoffs data.