Give me a data set to work on my assignment. That satisfies the requirements.

$-$ Visit one of the following sources to download a dataset related to consumer spending:

$-$ U$.$S$.$ Government's Open Data

$-$ Johns Hopkins University Data Guide

$-$ R Datasets Package

$-$ Choose a dataset that includes variables such as date$/$time of purchase, amount spent, category of expenditure, and demographic information of the spender $($if available$).$

$-$ Your dataset must satisfy the following complexity requirements. Your total data size must be at least $1$GB$,$ and across all data $*$being analyzed$*$ must meet one of the two criteria:

Large Observation Criteria: $\backslash (>50,000\backslash )$ observations and $\backslash (>25\backslash )$ features

Large Feature Criteria: $\backslash (>300\backslash )$ observations and $\backslash (>5,000\backslash )$ features

$2.$ Data Preparation:

$-$ Write and test your R code.

$-$ Load the dataset into R and perform necessary data cleaning steps, such as handling missing values, correcting data types, and removing duplicates.

$3.$ Exploratory Data Analysis:

$-$ Generate summary statistics to understand the distribution and central tendencies of key variables.

$-$ Create visualizations such as histograms, box plots, and scatter plots to observe relationships and patterns in the data.

$4.$ Statistical Analysis:

$-$ Implement one of the week $6-10$ topics for your dataset.

$-$ Use linear regression to explore factors that predict the amount spent.

$5.$ Report Writing: $$ Compile your findings into a structured report. $$ Include an introduction to the dataset and the objectives of the analysis. $$ Present the visualizations and discuss the statistical findings. $$ Conclude with actionable business insights based on the analysis. For instance, suggest marketing strategies that could target specific consumer segments identified as high spenders.

Deliverables: $$ R scripts used for analysis. $$ A comprehensive report $(4-6$ pages$)$ detailing the methodology, findings, and business recommendations.