oregon_lollipop.Rmd

---
title: "R Notebook"
output: html_notebook
---

```{r}
# setup
library(readr)
library(dplyr)
library(forcats)
library(ggplot2)
library(tibble)
```

```{r}
#load data
url <- "https://gist.githubusercontent.com/dgkeyes/a9b47cfa9a7bd8313e5603d18cf3d444/raw/3de0e4074db23636ebd420af78e90c4009aa10c7/oregon-economic-mobility-data.csv"
raw_data <- read_csv(url, col_names = c("name", "upward_mobile"), skip = 1)
```

```{r}
# clean data
extract_percentage <- function(x) {
    sans_percent <- substr(x, 1, nchar(x) - 1)
    as.numeric(sans_percent)
}

clean_data <- mutate(raw_data, upward_mobile = extract_percentage(upward_mobile))

state_mean <- mean(clean_data$upward_mobile)

county_data <- clean_data %>% 
    mutate(highlow = if_else(upward_mobile > state_mean, "High", "Low"),
           simple_name = stringr::str_extract(string = name, 
                                       pattern = "^[A-Za-z ]+(?= County, OR)"))

state_data <- tibble(name = "Oregon Average", 
                     upward_mobile = state_mean, 
                     highlow = "",
                     simple_name = "Oregon Average")

plot_data <- bind_rows(county_data, state_data) %>%
    arrange(upward_mobile) %>%
    mutate(simple_name = forcats::fct_inorder(simple_name),
           highlow = forcats::fct_inorder(highlow))



```


```{r, fig.height=10, fig.width=5}
# plot

vert_axis <- 7

use_palette <- c("#f5a52f", "#5c5c5c","#2f50f5")

ggplot(plot_data, aes(x = upward_mobile, y = simple_name)) +
    geom_segment(aes(x = vert_axis, xend = upward_mobile, yend = simple_name, color = highlow), size = 1.5) +
    geom_point(aes(color = highlow), size = 4) +
    geom_text(aes(x = upward_mobile + 0.8, y = simple_name, label = scales::percent(upward_mobile/100))) +
    scale_color_manual(values = use_palette) +
    scale_x_continuous(limits = c(vert_axis, 16), expand = expand_scale()) +
    labs(title = "Upward Mobility") + 
    theme_classic() +
    theme(legend.position = "none", 
          axis.title.x = element_blank(), 
          axis.title.y = element_blank(), 
          plot.background = element_rect(fill = "#fffff0"),
          panel.background = element_rect(fill = "#fffff0"),
          axis.text.x = element_blank(), 
          axis.line.x = element_blank(),
          axis.line.y = element_blank(),
          axis.ticks = element_blank(),
          title = element_text(size = 20) )
```

FYI, reader::parse_number() is a standard drop in for your extract_percentage()

Thanks... I actually noted that in your gist. Going to remember that one for the future.