In kgilds/ACLOlderAmericansProfile: ACL Profle of Older Americans

knitr::opts_chunk$set(echo = TRUE)

library(httr)
library(readxl)
library(dplyr)
library(esquisse)
library(ggplot2)
library(gganimate)
library(ggiraph)

profile_2019 <- ("https://acl.gov/sites/default/files/Aging%20and%20Disability%20in%20America/2019OlderAmericansData.xlsx")

#url_district <- ("http://www.fldoe.org/core/fileparse.php/18534/urlt/DistrictGrades19.xls")



httr::GET(profile_2019, write_disk(profile_2019 <- tempfile(fileext = ".xlsx")))

p_2019 <- readxl::read_xlsx(profile_2019)

excel_sheets(profile_2019)

person_65_p <- read_excel(profile_2019, sheet = 1, skip =2) %>%
  dplyr::rename(population = "People 65+")


names(person_65_p)

esquisse::esquisser(person_65_p)

p <- ggplot(person_65_p) +
  aes(x = Year, y = population) +
  geom_point(
    shape = "diamond open",
    size = 1.5,
    colour = "#FF8C00"
  ) +
  labs(
    title = "Number of Persons 65 & Over 1900-2060",
    subtitle = "Number in Millions",
    caption = "Source: U.S. Census Bureau,
 Population Estimates and Projections"
  ) +

  hrbrthemes::theme_modern_rc()

ggplot(person_65_p) +
  aes(x = Year, y = population) +
  geom_col(
      width = .1
  ) +
  labs(
    title = "Number of Persons 65 & Over 1900-2060",
    subtitle = "Number in Millions",
    caption = "Source: U.S. Census Bureau,
 Population Estimates and Projections"
  ) +
  hrbrthemes::theme_modern_rc()

ggplot(person_65_p) +
  aes(x = Year, y = population) +
  +
  labs(
    title = "Number of Persons 65 & Over 1900-2060",
    subtitle = "Number in Millions",
    caption = "Source: U.S. Census Bureau,
 Population Estimates and Projections"
  ) +
  hrbrthemes::theme_modern_rc()