exploratory-analysis/008-maryland-maps.Rmd at master · mapping-elections/exploratory-analysis · GitHub

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---
title: "Map Maryland Congressional Elections"
output:
  html_notebook: default
  html_document: default
---

```{r, include=FALSE}
library(tidyverse)
library(mappingelections)
library(stringr)
library(forcats)
```

```{r, fig.height=4.5}
county_parties <- meae_maps %>%
  filter(state == "MD") %>%
  left_join(meae_congress_counties_parties, by = "meae_id") %>%
  select(congress, county_ahcb, ends_with("_percentage")) %>%
  gather(party, percentage, -congress, -county_ahcb) %>%
  mutate(party = party %>%
           str_replace("_percentage", "") %>%
           tools::toTitleCase()) %>%
  filter(county_ahcb != "city_annapolis",
         congress != 2) %>%
  mutate(percentage = ifelse(percentage == 0, NA_real_, percentage)) %>%
  mutate(county_ahcb = county_ahcb %>%
           str_replace("mds_", "") %>%
           tools::toTitleCase()) %>%
  mutate(party = fct_collapse(party,
                              Antifederalist = "Antifederalist",
                              Other = c("Chesapeake", "Potomac", "Other"),
                              Federalist = "Federalist",
                              Republican = "Republican"))


ggplot(county_parties, aes(x = congress, y = percentage, color = party)) +
  facet_wrap(~county_ahcb, ncol = 4) +
  geom_line() + geom_point() +
  theme_grey(base_size = 14) +
  theme(legend.position = "bottom") +
  labs(title = "Party competition by county in Maryland",
       subtitle = "Maryland elections to the U.S. House of Representatives, 1st through 19th Congress",
       caption = "Mapping Early American Elections") +
  scale_y_continuous(name = "Vote", labels = scales::percent) +
  scale_x_continuous(name = "Congress", breaks = seq(2, 18, by = 2)) +
  scale_color_discrete(name = "Party")
```

```{r}
district_parties <- meae_maps %>%
  filter(state == "MD") %>%
  left_join(meae_congress_candidate_totals, by = "meae_id") %>%
  group_by(congress, district, party) %>%
  summarize(vote = sum(vote, na.rm = TRUE)) %>%
  group_by(congress, district) %>%
  mutate(total_vote = sum(vote, na.rm = TRUE),
         percentage = vote / total_vote) %>%
  filter(district != "At-large",
         congress > 3)

ggplot(district_parties, aes(x = congress, y = percentage, color = party)) +
  facet_wrap(~district) +
  geom_point() + geom_line() +
  theme_gray(base_size = 14) +
  theme(legend.position = "bottom") +
  labs(title = "Party competition by district in Maryland",
       subtitle = "Maryland elections to the U.S. House of Representatives, 3rd through 19th Congress",
       caption = "Mapping Early American Elections") +
  scale_y_continuous(name = "Vote", labels = scales::percent) +
  scale_x_continuous(name = "Congress", breaks = seq(4, 18, by = 2)) +
  scale_color_discrete(name = "Party")
```

```{r}
meae_maps %>%
  filter(state == "MD") %>%
  left_join(meae_congress_candidate_totals, by = "meae_id") %>%
  filter(winner) %>%
  count(congress, party) %>%
  ggplot(aes(x = congress, y = n, color = party)) +
  geom_line() + geom_point() +
  theme_grey(base_size = 14) +
  labs(title = "Representatives by party in Maryland",
       subtitle = "Maryland elections to the U.S. House of Representatives, 1st through 19th Congress",
       caption = "Mapping Early American Elections") +
  scale_y_continuous(name = "Elected", breaks = 1:8, limits = c(0, 8)) +
  scale_x_continuous(name = "Congress", breaks = seq(2, 18, by = 2)) +
  scale_color_discrete(name = "Party") +
  theme(legend.position = "bottom")


  # scale_color_manual(name = "Party",
  #                    values = c("Federalist" = "green",
  #                               "Republican" = "purple",
  #                               "Anti-Federalist" = "orange"))
```