danl-200-team-project.qmd

---
title: Team Project
subtitle: What You Should Do for the Team Project
author: Byeong-Hak Choe
institute: SUNY Geneseo
date: 2024-04-25
format: 
  html
    # toc: true
    # toc-depth: 2
    # toc-expand: true
    # toc-title: Contents
code-fold: false

execute:
  echo: true
  eval: true
  message: false
  warning: false
  fig-width: 9
  fig-height: 6
---
```{r}
#| include: false
library(tidyverse)
library(skimr)
library(broom)
library(hrbrthemes)

theme_set(theme_ipsum() +
          theme(strip.background =element_rect(fill="lightgray"),
                axis.title.x = element_text(size = rel(1.5) ),
                axis.title.y = element_text(size = rel(1.5) ))
          )

```

<br>

## Team Project

- Publish the webpage of your team's data analysis on **each team member's website**, hosted in GitHub.
  - The due for the project is May 16, 2024, Thursday, 11:59 P.M.
  - Please notify Byeong-Hak Choe if any team member fails to participate in the project by May 8, 2024. You can report this issue by emailing [bchoe@geneseo.edu](mailto:bchoe@geneseo.edu) after May 8, 2024.

<br>

## Project Data
- For the project, a team must choose one of the following data.frames:
  - `beer_markets`
  - `nyc_housing_sales`

### Beer Market Data
```{r}
beer_markets <- read_csv("https://bcdanl.github.io/data/beer_markets_all.csv")
```

```{r}
#| echo: false
#| results: asis

rmarkdown::paged_table(beer_markets)
```

#### Variable Description

- `hh`: an identifier of the household;
- `X_purchase_desc`: details on the purchased item;
- `quantity`: the number of items purchased;
- `brand`: Bud Light, Busch Light, Coors Light, Miller Lite, or Natural Light;
- `dollar_spent`: total dollar value of purchase;
- `beer_floz`: total volume of beer, in fluid ounces;
- `price_per_floz`: price per fl.oz. (i.e., beer spent/beer floz);
- `container`: the type of container;
- `promo`: Whether the item was promoted (coupon or otherwise);
- `market`: Scan-track market (or state if rural);
- `state`: US State
- demographic data, including gender, marital status, household income, class of work, race, education, age, the size of household, and whether or not the household has a microwave or a dishwasher.

<br>

### NYC Housing Sales Data

```{r}
nyc_housing_sales <- read_csv("https://bcdanl.github.io/data/nyc_housing_sales_2006-2023.csv")
```

```{r}
#| echo: false
#| results: asis

rmarkdown::paged_table(nyc_housing_sales)
```


#### Variable Description

- For the description of variables in the `nyc_housing_sales` data.frame, please refer to the following webpage:
  - [https://www.nyc.gov/site/finance/property/glossary-property-sales.page](https://www.nyc.gov/site/finance/property/glossary-property-sales.page)
    - For the variables of building class code, please refer to the following webpage:
      - [https://www.nyc.gov/assets/finance/jump/hlpbldgcode.html](https://www.nyc.gov/assets/finance/jump/hlpbldgcode.html)

<br>

## Key Components in the Project

- Below are the key components in the project. 

  1. **Title**: A clear and concise title that gives an idea of the project topics.
  
  2. **Introduction**:
     - **Background**: Provide context for the research topics, explaining why they are significant or relevant.
     - **Statement of the Problem**: Clearly articulate the specific problem or issue the project will address.
     
  3. **Exploratory Data Analysis**:
     - List the questions your team aims to answer.
     - Address the questions through summary statistics, data visualization, and data transformation.
  
  4. **Significance of the Project**:
     - Explain its implications for real-world applications, business strategies, or public policy.
  
  6. **References**
     - List all sources cited in the project.


<br>

## Rubric for the Project

- Below links to the PDF file of the rubric for the team project:
  - [Link](https://drive.google.com/file/d/1O2pK4vK2bd1ZP8nnlPOwNr1oAeAbuHHQ/view?usp=share_link)