This project focuses on a exploratory data analysis and visualized data-driven evaluation. Our primary goal is to refine census income distribution data by handling missing value, encoding categorial columns, creation of binary IncomeBracket column, calculating average age per workclass the proportion of individuals earning more than 50K per education level, performing pivoting and basic conditional formatting operations, visualizing income distribution by education and creation of heatmap of correlations between numeric variables.
Data Analytical Principles and Data Visualization Tools used : Python, Jupyter Notebook Pandas, Matplotlib, Seaborn, Microsoft Excel, Pivot Tables.
Outcome of the analysis: Visualized income distribution dataset with accuracy of >80%.