---
title: "Assignment 8"
subtitle: CRD 150
author: YOUR FULL NAME HERE
date: INSERT DATE HERE
output: 
  html_document:
    theme: cosmo
---


```{r setup, include=FALSE}
# Do not edit this code block/chunk
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message = FALSE)
knitr::opts_knit$set(progress = TRUE, verbose = TRUE)
```

```{r}
#Load in all necessary packages using the function library()
```

  
1. In this question, you will be exploring the spatial distribution of Airbnb listings in the City of Oakland. Airbnb involves renting an entire home, a room or a shared room, typically from a private citizen. The data were downloaded from Airbnb's public use data site. You will be using the shapefile oak_tracts.zip,  which contains Oakland City tracts with their population sizes downloaded from the 2015-2019 American Community Survey, and the csv file oakland_airbnb_dec2020.csv, which contains Airbnb locations in December 2020. The record layout for oakland_airbnb_dec2020.csv can be found here.  You will also be using the file station_info.csv, which contains the addresses of BART station locations in Oakland. The files are located on Canvas (Files - Week 8 - Assignment). Save the files in an appropriate folder. Unzip oak_tracts.zip to extract the shapefiles.

a. Read the file oakland_airbnb_dec2020.csv into R. Create a point dataset of Airbnb listings using their longitudes and latitudes.  

```{r}
#Insert your code here
```

b. Read the file oak_tracts.shp into R. Create a variable that represents the number of Airbnb listings in each neighborhood. 

```{r}
#Insert your code here
```

c. Create a presentation-ready choropleth map of the number of Airbnb listings per 1,000 residents. 

```{r}
#Insert your code here
```

d. Are neighborhoods with a large presence of Airbnb listings near BART stations, which is the Bay Area's main public rapid-transit system? Read the file station_info.csv into R. Geocode the BART stations using their street addresses

```{r}
#Insert your code here
```

e. Map the BART station point locations onto the choropleth map you created in (c). Based on a visual assessment of the map, are neighborhoods with a large presence of Airbnb listings near BART stations? 

```{r}
#Insert your code here
```

2. The purpose of this question is to increase your exposure to the world of open data. In this exercise, you will explore a city's open data portal, answering questions about one of its data sets and examining the data set in R.  Pick one of the following cities and answer the questions that follow.

New York, NY [(link)](https://opendata.cityofnewyork.us/)
San Francisco, CA [(link)](https://datasf.org/opendata/)
Los Angeles, CA [(link)](https://data.lacity.org/)
Chicago, IL [(link)](https://data.cityofchicago.org/)

a. Which city did you choose?

b. Find a dataset that looks interesting to you and can be downloaded and brought into R.  Answer the following questions about this dataset.

* Describe the dataset you selected. What are the variables, the year(s) captured by  the data, and the units of observations? 
* Are you able to manipulate the data online? This includes filtering rows and selecting columns. 
* Are you able to create visualizations online with the data using graphs and charts? If so, what kinds of graphs and charts? 
* Are you able to map the data online? If so, what types of maps? 
* Is the data set accompanied by a codebook with definitions of terms, variables and fields? 
* Bring the data set into R. Create either a single presentation-ready table, chart or graph that we covered in Lab 4 or a single presentation-ready map that we covered in Lab 5 or Lab 8. Explain what your graphic is showing us. You must show your code to get full points for this question.


```{r}
#Insert your code here
```