Analysis and Visualisation of 10 years of depression scale in United States

S - Situation: The project aims to analyze and visualize a Depression Dataset (2005-2018) to identify common trends and factors leading to depression among Americans. T - Task: Clean the data by removing rows with missing information Analyze the necessary attributes for finding trends in depression dataset Visualize and summarize data to understand its properties Create an interactive dashboard to understand how different factors affect depression A - Action: The following actions will be taken to achieve the project objectives: Data cleaning: Rows with missing data will be removed using Python. Data analysis: EDA, statistical analysis, and visualization will be performed using Python. Necessary attributes will be identified and analyzed to find trends and factors leading to depression. Data visualization: Visualization of different factors leading to depression will be created using different Python visualization libraries. Interactive dashboard: An interactive dashboard will be created to understand how each factor affects depression. Different filters and charts will be used in the dashboard to analyze the interdependence of different factors with depression. R - Result: The expected result of the project is a comprehensive analysis and visualization of the depression dataset, highlighting common trends and factors leading to depression among Americans. The interactive dashboard will provide a better understanding of how different factors affect depression and which factors are interdependent with depression. The project will provide insights into depression, which can be helpful for healthcare professionals, policymakers, and researchers.