Mini Project

Data Visualization Objective:

A task is a series of data visualizations that reveal key trends, patterns, or insights within a dataset of choice. The goal is to use these visualizations to communicate meaningful story that can inform decision-making or provide deeper understanding of the subject matter. Possible datasets can be found within the following websites, but are free to use any other resources:

1. Health CDC WONDER (Wide-ranging Online Data for Epidemiologic Research): Provides health data in downloadable CSV format, covering diseases, health indicators, and mortality. CDC WONDER HealthData.gov: Many health datasets are available for download in CSV format, including topics like Medicare, hospital performance, and healthcare services. HealthData.gov Global Health Observatory (WHO): Datasets on health statistics, like mortality rates and global health indicators, are downloadable in Excel format. WHO Global Health Observatory

2. Environment EPA (Environmental Protection Agency) Open Data: EPA Environmental Datasets NOAA Climate Data Online: Includes weather, climate, and atmospheric datasets in CSV format, suitable for environment-related visualizations. NOAA Climate Data Online Global Forest Watch: Allows downloading of forest cover and conservation data in CSV format, focused on deforestation and environmental monitoring. Global Forest Watch

3. Economics World Bank Open Data: Offers economic and financial datasets on global development indicators, available in both CSV and Excel formats. World Bank Open Data OECD Data: Provides datasets on economic performance, employment, and finance indicators, downloadable in Excel or CSV. OECD Data U.S. Bureau of Economic Analysis (BEA): U.S. economic datasets, including GDP, income, and industry data, are available in CSV and Excel. BEA Data

4. Government Data Data.gov is the U.S. government's open data platform, providing datasets across various sectors, including health, environment, education, finance, transportation, and more. Many datasets are available in CSV and Excel formats, making it a versatile resource for visualizations and analyses across diverse fields. Project Instruction:

1. Introduction: Select a dataset relevant to chosen topic (e.g., health, environment, economics, etc.) and provide data set source. Clearly define the objectives of visualization project. Specify what aspects of the data plan to explore, such as trends over time, comparisons between categories, or geographical distributions.

2. Data Preparation: Describe the methods and tools will use to clean, organize, and prepare the data for visualization. If the dataset is large, explain how you will filter or segment the data to focus on key areas of interest. Outline any data transformation steps, such as combining, grouping, or normalizing data.

3. Visualization Design: Select appropriate visualization types (e.g. bar charts, scatter plots, heat maps, line graphs) based on the nature of the data and the insights you want to convey. Justify your choice of visualization methods, considering how they will effectively communicate the key points of analysis. Pay attention to design elements such as color, scale, and labeling to ensure clarity and readability.

4. Creation of Visualizations: Use chosen software (Excel) to create visualizations. For each visualization, provide a brief description explaining what it shows and why it is relevant to analysis. Highlight any notable trends, correlations, or outliers revealed through visualizations.

5. Analysis and Interpretation: Analyze the visualizations to draw insights and conclusions about the data. Discuss any patterns or trends observed and what they might imply in the context of the chosen topic. Consider the broader implications of findings and how they might inform decision-making or future research.

6. Challenges and Limitations: Reflect on any challenges you encountered during the visualization process, such as data limitations or design constraints. Discuss how these challenges were addressed and any impact they may have had on the final visualizations.

7. Conclusion: Summarize the key insights gained from visualizations. Highlight the significance of findings and any potential applications or actions that could be informed by work. Suggest any areas for further exploration or improvement.

8. Deliverables: Save raw dataset as a separate file for submission. A set of data visualizations that effectively communicate the key findings, including the element that you did from Assignment

10 A written report detailing the process, from data preparation (at least 4 charts plus a slicer) to interpretation of results. A conclusion summarizing the insights and their potential implications. 9. References: Include any sources or tools used for data collection, visualization software, or methodologies 10. Appendix: Screen shots for visualized charts or add these charts in writing.