Decision tree with estimated costs and probabilities if META were to choose or not to go with Nuclear power to meet its speculated 4GWt power consumption by 2030

Dataset: Sankey_data.csv Objective: Visualize Company Layoff's across Different departments Companies: Amazon,Twitter, Meta, Microsoft

Dataset Used: MakeupDB.xlsx, Region.xlsx Visuals: Area Plot, Bubble Chart Focus: 1 - Area Plot for Makeup accessory sales by month over 4 years 2 - Bubble chart for Sales of products by region given their market share

Data Set(s): McDonalds.xlsx - Income v/s Average Visits Dow-1.xlsx - Month for multiple years v/s Returns

Pie Chart Representation Variables: Workforce in different Departments, Salary Ranges DataSet: HR_comma_sep

Data Set: HR_comma_sep Visualizing Lastt_evaluation and Satisfaction_level against employees that LEFT or STAYED at the company

Data Set: HR_comma_sep Rate of Satisfaction at an Eval v/s continued employment