Objective: Find a dataset containing at least $200$ observations and $10$ variables. Analyze the dataset and provide a detailed explanation of the variables.

Instructions:

Data Collection: Search for a dataset from reputable sources such as government databases $($e$.$g$.,$ U$.$S$.$ Census Bureau, World Bank$),$ academic repositories $($e$.$g$.,$ UCI Machine Learning Repository, Kaggle$),$ or data journalism platforms $($e$.$g$.,$ Data.gov, FiveThirtyEight$).$

Dataset Requirements: Ensure that the dataset meets the following criteria:

Contains a minimum of $200$ observations $($rows$).$

Includes at least $10$ variables $($columns$)$ providing different types of information.

Preferably in a format compatible with common data analysis tools like CSV$,$ Excel, or JSON.

Insert into R and create the code to analyze the information

Data Exploration and Explanation: Once you have selected a suitable dataset, thoroughly explore its variables and their meanings. Provide a detailed explanation for each variable, including:

Variable name and description.

Data type $($e$.$g$.,$ numerical, categorical, ordinal$).$

Potential range or categories.

Any transformations or preprocessing needed for analysis.

Significance or relevance of the variable to the dataset's overall theme or research question.

Presentation: Compile your findings into a report Include visualizations $($e$.$g$.,$ histograms, bar charts$)$ where appropriate to illustrate the characteristics of the variables.

Submission: Submit your report along with the dataset source and any code used for analysis

Note: Ensure that you properly cite the source of the dataset and any other references used in your analysis.