AustinLWheat_Lab2.Rmd

---
title: "Lab 2 Assignment"
author: "Austin L. Wheat"
date: "9/12/2021"
output: github_document
editor_options: 
  markdown: 
    wrap: sentence
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r setup_package, warning = FALSE, message = FALSE}
library(tidyverse)
library(tidycensus)
library(sf)
library(tmap)
library(viridis)
set.seed(717)
```

## Load data from {tidycensus}

```{r load_variables, cache = TRUE}
vars <- load_variables(2019, "acs5") # Load Census Variables

acs_vars <- c("B15001_050", # Total Female Bachelors
              "B15001_009", # Total Male Bachelors
              "B01001_001") # ACS total Pop estimate

myTracts <- c("42101000402",
              "42101000401",
              "42101013602",
              "42101013402",
              "42101013401",
              "42101013601",
              "42101000300",
              "42101012500",
              "42101013300",
              "42101013500") # Logan Circle, Fairmount, Spring Garden area

acsTractsPHL.2019.sf <- get_acs(geography = "tract", # Load Census Tracts
                                year = 2019, 
                                variables = acs_vars, 
                                geometry = TRUE, 
                                state = "PA", 
                                county = "Philadelphia", 
                                output = "wide") %>% 
  dplyr::select (GEOID, NAME, all_of(paste0(acs_vars, "E"))) %>%
  rename (total_FemaleBach.2019 = B15001_050E,
          total_MaleBach.2019 = B15001_009E,
          total_pop.2019 = B01001_001E) %>%
  mutate(pctFemalebach.2019 = ((total_FemaleBach.2019/total_pop.2019)*100), #Do math, get %'s
         pctMalebach.2019 = ((total_MaleBach.2019/total_pop.2019)*100)) %>% #Do math, get %'s
  mutate(Neighborhood = ifelse(GEOID %in% myTracts,
                               "Logan Circle",
                               "REST OF PHILADELPHIA"))
```

## Transform to WGS84 with {sf}

```
acsTractsPHL.2019.sf_WGS84 <- acsTractsPHL.2019.sf %>% #Transform to WFS84
  st_transform(crs = "EPSG:4326")
```

## Plot with {ggplot2}


```{r ggplot_geom_sf, warning = FALSE, echo = TRUE}

ggplot()+
    geom_sf(data = acsTractsPHL.2019.sf, aes(fill = pctFemalebach.2019),
            color = "transparent")+
    geom_sf(data = acsTractsPHL.2019.sf %>%
                filter(Neighborhood == "Logan Circle") %>%
                st_union(),
            color = "white",
            fill = "transparent") +
  labs(
    title = "% of Females with a Bachelor's Degree",
    subtitle = "Spring Garden Neighborhood Highlighted",
    caption = "Philadelphia, PA") +
  scale_fill_viridis()
```