
---
title: "SDS192 Mini-Project 3"
date: "Tuesday, November 23rd, 2021"
output:
  pdf_document:
    toc: no
    df_print: paged
---

```{r, message=FALSE, warning=FALSE, echo=FALSE}
# Do not edit this chunk unless you know what you are doing
knitr::opts_chunk$set(
  echo = TRUE, message = FALSE, warning = FALSE, fig.width = 16/2, fig.height = 9/2
)
```

```{r, echo=FALSE}
# Load all packages here
library(tidyverse)
library(sf)
```

## Administrative info:

* Section number: 
* Group number: 
* Group leader name: 
* Group leader academic email: 
* Partner name: 
* Partner academic email: 


```{r, echo=FALSE}
# Load all your data here. Be sure to be in MP3 RStudio Project mode so that R
# knows where to find all data. Here is an example

# Load bike trails shapefile and convert to sf object:
bike_trails <- "biketrails_arc/" %>%
  read_sf()

# Load MA cities from CSV and convert to sf object:
MA_cities_sf <- read_csv("data/ma_cities.csv") %>% 
  st_as_sf(coords = c("lon", "lat"), crs = 4326)
```



# Q1: Peer evaluation Google Form

Fill out the peer evaluation Google Form to receive credit.



# Q2: Introduction

Write no more than 250 words giving the data's context and source here. References should be generated using R Markdown footnotes, as you did in MP2.^[This is an example footnote.]



# Q3: Your map

```{r, echo = FALSE}
# Put code to create your static map here:
ggplot() +
  geom_sf(data = bike_trails, col = "black") +
  geom_sf(data = MA_cities_sf, aes(col = name), size = 2) +
  theme_bw() +
  labs(col = "City")
```


# Additional Analysis

((Optional) If you have any additional analysis you would like to add, add it here. This is optional.
