mexico geofacet

mx_grid.R

library(dplyr)
library(stringr)
library(readr)
library(ggplot2)
library(geofacet)
options(stringsAsFactors = FALSE)

mx_grid <- data.frame(
  code = c(2L, 8L, 26L, 3L, 5L, 10L, 19L, 25L, 28L, 1L, 18L, 24L, 32L, 
           11L, 13L, 14L, 22L, 30L, 6L, 15L, 29L, 9L, 17L, 21L, 31L, 4L, 
           12L, 16L, 20L, 23L, 27L, 7L),
  name = c("Baja California", "Chihuahua", "Sonora", "Baja California Sur", "Coahuila", "Durango", "Nuevo León", "Sinaloa", "Tamaulipas", "Aguascalientes", "Nayarit", "San Luis Potosí", "Zacatecas", "Guanajuato", "Hidalgo", "Jalisco", "Querétaro", "Veracruz", "Colima", "México", "Tlaxcala", "Ciudad de México", "Morelos", "Puebla", "Yucatán", "Campeche", "Guerrero", "Michoacán", "Oaxaca", "Quintana Roo", "Tabasco", "Chiapas"),
  name_official = c("Baja California", "Chihuahua", "Sonora", "Baja California Sur", "Coahuila de Zaragoza", "Durango", "Nuevo León", "Sinaloa", "Tamaulipas", "Aguascalientes", "Nayarit", "San Luis Potosí", "Zacatecas", "Guanajuato", "Hidalgo", "Jalisco", "Querétaro", "Veracruz de Ignacio de la Llave", "Colima", "México", "Tlaxcala", "Ciudad de México", "Morelos", "Puebla", "Yucatán", "Campeche", "Guerrero", "Michoacán de Ocampo", "Oaxaca", "Quintana Roo", "Tabasco", "Chiapas"),
  name_abbr = c("BC", "CHIH", "SON", "BCS", "COAH", "DGO", "NL", "SIN", "TAM", "AGS", "NAY", "SLP", "ZAC", "GTO", "HGO", "JAL", "QRO", "VER", "COL", "MEX", "TLAX", "CDMX", "MOR", "PUE", "YUC", "CAMP", "GRO", "MICH", "OAX", "QROO", "TAB", "CHPS"),
  name_abbr_iso = c("BCN", "CHH", "SON", "BCS", "COA", "DUR", "NLE", "SIN", "TAM", "AGU", "NAY", "SLP", "ZAC", "GUA", "HID", "JAL", "QUE", "VER", "COL", "MEX", "TLA", "CMX", "MOR", "PUE", "YUC", "CAM", "GRO", "MIC", "OAX", "ROO", "TAB", "CHP"),
  name_abbr_official = c("BC", "Chih.", "Son.", "BCS", "Coah.", "Dgo.", "NL", "Sin.", "Tamps.", "Ags.", "Nay.", "SLP", "Zac.", "Gto.", "Hgo.", "Jal.", "Qro.", "Ver.", "Col.", "Mex.", "Tlax.", "CDMX", "Mor.", "Pue.", "Yuc.", "Camp.", "Gro.", "Mich.", "Oax.", "Q. Roo", "Tab.", "Chis."),
  col = c(1, 3, 2, 1, 4, 3, 5, 2, 6, 5, 3, 6, 4, 4, 6, 3, 5, 7, 4, 5, 6, 5, 4, 6, 9, 8, 5, 4, 6, 9, 7, 7),
  row = c(1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 8)
  )
geofacet::grid_preview(mx_grid)

hom <- read_csv("https://data.diegovalle.net/elcrimen/victimas.csv.gz") %>%
  filter(modalidad == "HOMICIDIOS" & tipo == "DOLOSOS") %>%
  mutate(date = as.Date(str_c(date, "-01"), origin="1960-10-01")) %>%
  mutate(rate = count / population * 10^5 * 12) %>%
  mutate(code = as.integer(state_code))

ggplot(hom, aes(date, rate)) +
  geom_line(color = "steelblue") +
  facet_geo(~ code, grid = mx_grid, label = "name") +
  ggtitle("Homicide rate in Mexico (Jan 2014 - May 2017)") +
  ylab("annualized homicide rate") +
  theme_bw()

Hola! Parece que el enlace a la base de datos para replicar esto esta roto (me dice que me vaya a la TAPO)
Saludos!

--Juvenal

Hola, ya debe de funcionar. Nota que estos datos son de la metodología antigua y hay datos mas recientes en https://elcri.men/acerca/

Perfecto, ya funciona bien!
Muchas gracias!