added city list and populations

city_compare.Rmd

@@ -0,0 +1,89 @@
+---
+title: "City Compare"
+output:
+  html_document:
+    toc: true
+    toc_depth: 5
+    toc_float:
+      collapsed: false
+      smooth_scroll: true
+editor_options:
+  chunk_output_type: console
+---
+
+# Input Data & Configuration
+
+## Libraries
+
+```{r libs, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+date()
+rm(list=ls())
+library(tidyverse)
+library(tidycensus)
+
+```
+
+## API keys
+```{r api_keys, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+# load census api key
+census_api_key(key = substr(read_file(file = "api_keys/census_api_key"), 1, 40))
+
+```
+
+## Cities to compare
+
+```{r cities, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+cities <- read_csv(file = "cities.csv")
+cities <- cities %>%
+  mutate(city_name = paste0(City, " ", Type))
+```
+
+# Get data
+
+## Census data
+```{r census, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+populations <- list(NULL)
+for(city in cities$city_name){
+  state <- cities %>% filter(city_name == city) %>% pull(State)
+  populations[[city]] <- get_acs(
+    geography = "place",
+    variables = "B01003_001",
+    state = state,
+    year = 2023
+  ) %>%
+  filter(str_detect(NAME, city))
+}
+
+populations <- bind_rows(populations)
+
+cities <- bind_cols(cities, populations)
+
+ggplot(cities) +
+  geom_col(aes(x = City,
+               y = estimate))
+
+```
+
+## Weather
+```{r weather, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+populations <- list(NULL)
+for(city in cities$city_name){
+  state <- cities %>% filter(city_name == city) %>% pull(State)
+  populations[[city]] <- get_acs(
+    geography = "place",
+    variables = "B01003_001",
+    state = state,
+    year = 2023
+  ) %>%
+  filter(str_detect(NAME, city))
+}
+
+populations <- bind_rows(populations)
+
+cities <- bind_cols(cities, populations)
+
+ggplot(cities) +
+  geom_col(aes(x = City,
+               y = estimate))
+
+```