added city list and populations

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+
+#exclude API keys
+api_keys/*
+

api_keys/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

cities.csv

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+City,Type,State,Country
+Madison,city,WI,United States
+Bellingham,city,WA,United States
+Portland,city,OR,United States
+Port Angeles,city,WA,United States
+Boston,city,MA,United States
+Boise City,city,ID,United States

city-compare.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX

city_compare.Rmd

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+---
+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))
+
+```