Slope graph for employment by industry

slope.R

library(xml2)
library(dplyr)
library(tidyr)
library(stringr)
library(ggplot2)

url <- "http://www.bls.gov/opub/ted/2016/employment-by-industry-1910-and-2015.htm"

page <- read_html(url)

df <- page %>% 
  xml_find_all("//table[@id='ted_20160303']") %>% 
  rvest::html_table(trim = TRUE, fill = TRUE) %>% 
  .[[1]]

df[] <- apply(df, 2, str_replace_all, 
              pattern = "\\s{2,}|,|\\([0-9]\\)", replace = "")

names(df) <- c("industry", paste(rep(c(1910, 2015), each = 2), 
                              df[1, -5], sep = "_")) %>% tolower()

df <- df[2:14, ]

df <- df %>% 
  gather(variable, value, -industry) %>% 
  mutate(value = as.numeric(value)) %>% 
  separate(variable, c("year", "variable"), "_") %>% 
  mutate(industry = plyr::revalue(industry, 
         c("Government not elsewhere classified" = "Government (other)")))

df %>%
  filter(variable == "percent of total") %>% 
  ggplot(aes(x = year, y = value, color = industry, group = industry)) +
  geom_point() +
  geom_line() +
  geom_text(aes(label = sprintf("  %s  ", industry)), 
            hjust = "outward", size = 3) +
  scale_y_continuous(breaks = seq(0, 35, 5)) +
  scale_x_discrete(expand = c(1.5, 1.5)) +
  theme_light(11) +
  theme(legend.position = "none", panel.grid = element_blank()) +
  labs(x = NULL, y = NULL, 
       title = bquote(atop(bold(.("Employment by industry, 1910 and 2015")), 
                           scriptstyle(.("Percent of total")))))