The goal of project is to predict the consumer complaint category. This is the "Product" variable in the training data set.May use any of the other variables to predict with. We should create a report describing how we built the model, how we used cross validation, what we think the expected out of sample error is, and why we made the choices we did. We will also use the prediction model to predict 20 different test cases. In this project, the consumer complains data from the Consumer Complaint Database (CFPB) https://www.consumerfinance.gov/data-research/consumer-complaints/. would be used. The CFPB is an independent agency of the United States government that promotes transparency and protects consumers by providing information needed to make decisions when choosing financial institutions including banking institutions, lenders, mortgage services, credit unions, securities firms, foreclosure services, and debt collectors. One of the purposes of the agency is to receive and process complaints and questions about consumer financial products and services.

we will create data visualizations using two data sets about fast food restaurants. the overall goal is to explore the nutrition of entree items and the sales of fast food restaurants in 2018. The task is to reconstruct the a set of plots, all of which were constructed using packages in the Tidyverse or packages that integrate with the Tidyverse. The source data is in : https://hubworks.com/blog/statistics-about-americas-biggest-fast-food-chains.html.

There are several forms of health coverage in the United States of America, Each state has its own health policy; Among those that exist are the health care policy directed by the federal government and the insurance company. It is important to have a general idea about the economics of health in the States. It is required to have an idea of health spending, including healthcare and healthcare coverage and spending in all states. The question is. Is There a Relationship Between Health Coverage and Health Spending in the United States? Data will be collected, data will be imported, data will be cleaned, data will be analyzed and data will be visualized, using well-established and commonly used packages, including library (datasets), library (tidyr), library (dplyr), ggplot2, and ggrepel.

Public health and econimic problems are affected by a number of reasons i am now going to analysize how storms and other severe weather events play a part. Storms and severe weather conditions causes fatalities and injuries and substantial property damage. Hence to minimze damages we should analyse the given data. In this project, we analyze the storm database taken from the U.S. National Oceanic and Atmospheric Administration (NOAA). We estimate the fatalities, injuries, property damage, and crop damage for each type of event (e.g., Flood, Typhoon, Tornado, Hail, Hurricane, etc.). Our goal is to determine which event is most harmful to US population (health) and which event has the largest economic consequences. Our analysis on Fatalities and Injuries conclude that Tornado is the most harmful event in respect to the US health (population). On the other hand, based on the Property and Cost damage, we conclude that Flood has the greatest economic consequences to the US. ## Introduction Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This project involves exploring the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage.