DataAnalysis

develop good data analysis presentation skills

This lab encourages you to analyze data and present your findings in a clear and concise manner. You will be working with a dataset of your choice. You will be required to generate a Jupyter notebook that explores the data and presents your findings. You will be required to submit the Jupyter notebook and a data analysis report. The report should be a PDF file that provides a high-level overview of your analysis.

A data analysis report is a document that summarizes the findings and insights obtained from analyzing a dataset. It provides a comprehensive overview of the analysis process, including the data sources, methodology, and techniques used. The report typically includes visualizations, statistical summaries, and interpretations of the data.

In a data analysis report, it is important to structure the content in a logical and organized manner. This includes providing an introduction to the analysis, explaining the objectives and scope, and describing the data preprocessing steps. The main body of the report should present the analysis results, such as key findings, trends, patterns, and correlations discovered in the data.

Additionally, a data analysis report should include clear and concise explanations of the analysis methods used, including any statistical tests or machine learning algorithms employed. It is also important to provide proper citations and references for any external sources or libraries used in the analysis.

To enhance the readability and understanding of the report, visualizations such as charts, graphs, and tables can be included to illustrate the findings. These visualizations should be properly labeled and accompanied by captions or explanations.

Finally, a data analysis report should conclude with a summary of the key insights and conclusions drawn from the analysis. It may also include recommendations for further analysis or actions based on the findings.

See the PDF in this repository for an example of a data analysis report and how to structure the content. You can use this as a template for your own report.

The Jupyter notebook should contain the code used to analyze the data, as well as any visualizations or tables generated during the analysis. The notebook should be well-documented, with clear explanations of the code and analysis steps. You can use markdown cells to provide additional context and explanations for the code.

The sources for the data sets can be found at: s3://yoda-public-files/DataAssets/DatasetsForDataAnalysis.zip

Process

• Choose a dataset in the zip file provided
• Generate a Jupyter notebook that explores the data and presents your findings
• Write a data analysis report that summarizes the findings and insights obtained from analyzing the dataset
• Submit the Jupyter notebook and a data analysis report
• Commit and push to your GitHub repository

Requirements

• The Jupyter notebook should contain the code used to analyze the data, as well as any visualizations or tables generated during the analysis
• The notebook should be well-documented, with clear explanations of the code and analysis steps
• The data analysis report should be a PDF file that provides a high-level overview of your analysis
• The report should include an introduction, objectives, methodology, analysis results, conclusions, and recommendations
• The report should include visualizations, statistical summaries, and interpretations of the data
• The report should include clear and concise explanations of the analysis methods used