This is the code itself. The issue arises when I tabulate the information; the table contains 'Na' values for species that are not found in the sample area. Therefore, I need to find a way to eliminate the rows that have at least one 'Na' value.
Librarys library(knitr) library(readxl) library(ggplot2) library(dplyr) library(tables) library(xml2) library(tinytex) library(latexpdf) library(tidyr)
DAPP0 <- tabular(("Tipo de Bosque" = DataP$Tipo_Bosque)*
("Especie" = Nombre_Cientifico) ~
("DAP" = DAP) *
((Media = mean) +
(DS = sd) +
(Varianza = var) +
(Mínimo = min) +
(Máximo = max) +
(Mediana = median) ),
data = DataP)
html.tabular( DAPPF0,
options = htmloptions( HTMLcaption = "Tabla Dap por Especie",
justification = "c",
pad = TRUE ) )
Thanks for the help
i try using this
DAPPF0 <- DAPP0 %>%
filter(!is.na(DS) & !is.na(Mediana))
DAPPF0 <- datos[complete.cases(datos), ]
DAPPF0 <- na.omit()
dput(DataP): structure(list(Localidad = c("Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Mallin Quetrus", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte", "Valle Norte"), Tipo_Bosque = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Bosque puro", "Krummholz", "Lenga Mixto"), class = "factor"), Parcela = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), Altitud = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 940, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 928, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896, 896), Especie = structure(c(3L, 3L, 4L, 4L, 5L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 10L, 5L, 5L, 5L, 3L, 1L, 1L, 4L, 5L, 8L, 8L, 9L, 5L, 5L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 7L, 8L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 3L, 5L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 3L, 5L, 3L, 5L, 7L, 7L, 7L, 7L, 3L, 3L, 6L, 5L, 5L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 3L, 7L, 7L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 10L, 5L, 9L, 5L, 5L, 3L, 3L, 5L, 5L, 10L, 11L, 5L, 5L, 2L, 5L, 5L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), levels = c("Chaura", "Chilco", "Coigue", "Corcolen", "Lenga", "Luma", "Mañio de hojas punzantes", "Meli", "Michay", "Sauco del diablo", "Zarzaparrilla"), class = "factor"), Nombre_Cientifico = structure(c(7L, 7L, 3L, 3L, 8L, 1L, 1L, 1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 10L, 8L, 8L, 8L, 7L, 6L, 6L, 3L, 8L, 2L, 2L, 4L, 8L, 8L, 2L, 2L, 2L, 2L, 8L, 8L, 8L, 8L, 8L, 9L, 2L, 8L, 8L, 9L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 1L, 1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 8L, 8L, 8L, 8L, 7L, 8L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 8L, 8L, 8L, 7L, 8L, 7L, 8L, 9L, 9L, 9L, 9L, 7L, 7L, 1L, 8L, 8L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 7L, 9L, 9L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 10L, 8L, 4L, 8L, 8L, 7L, 7L, 8L, 8L, 10L, 11L, 8L, 8L, 5L, 8L, 8L, 8L, 8L, 8L, 9L, 8L, 8L, 8L, 8L, 9L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 8L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L), levels = c("Amomyrtus luma", "Amomyrtus meli", "Azara lanceolata", "Berberis darwinii", "Fucsia magallanica", "Gaultheria mucronata", "Nothofagus dombeyi", "Nothofagus pumilio", "Podocarpus nubigenus", "Raukaua laetevirens", "Ribes punctatum"), class = "factor"), DAP = c(16, 13, 5, 5, 8, 7.5, 8, 7, 17.5, 27, 35, 28, 31, 27, 20, 44, 52, 5, 43, 49, 10, 38, 7, 8, 5, 7, 18, 8, 7, 33, 34, 6.5, 5.5, 5, 10, 23, 23, 27, 32, 33, 25, 8, 30, 14.5, 20, 8, 22, 21, 33, 23, 13, 11, 30, 13, 9, 10, 12, 13, 28, 48, 10, 14, 7, 8, 11, 35, 40, 17, 13, 20, 8, 6, 40, 28, 17, 26, 18, 17, 12, 14, 18, 15, 9, 8, 8, 6, 18, 60, 40, 30, 21, 38, 14, 48, 18, 24, 8, 22, 18, 25, 18, 20, 69, 19, 20, 23, 18, 20, 28, 120, 160, 74, 152, 54, 20, 22, 16, 32, 11, 21, 19, 32, 104, 42, 32, 52, 70, 20, 123, 140, 12, 19, 16, 26, 42, 152, 30, 135, 29, 29, 32, 40, 35, 57, 60, 150, 20, 85, 118, 18, 30, 21, 26, 22, 14, 113, 120, 90, 75, 162, 102, 70, 64, 48, 50, 40, 54, 78, 52, 80, 32, 40, 28, 98, 32, 43, 46, 52, 78, 39, 172, 32, 15, 60, 58, 15, 20, 25, 65, 40, 52, 51, 42, 62, 54, 200, 11, 9, 20, 17, 7, 11, 9, 17, 9, 11, 11, 7, 17, 23, 41, 34, 11, 40, 24, 24, 6, 7, 14, 7, 57, 47, 22, 14, 10, 7, 17, 24, 32, 46, 15, 16, 16, 17, 30, 16, 12, 14, 29, 14, 28, 16, 21, 20, 17, 16, 4, 15, 8, 9, 20, 12, 11, 6, 37, 9, 5, 5, 41, 4, 5, 17, 27, 20, 11, 6, 21, 6, 5, 24, 15, 6, 14, 22, 6, 15, 24, 10, 23, 12, 13, 50, 25, 18, 18, 6, 15, 10, 13, 11, 30, 25, 13, 8, 15, 22, 17, 17, 14, 10, 20, 18, 16, 14, 9, 5, 17, 8, 12, 13, 6, 12, 14, 22, 10, 15, 11, 7, 18, 40, 28, 20, 35, 11, 7, 25, 10, 13, 22, 9, 12, 16, 25, 25, 12, 16, 24, 20, 21, 16, 13, 28, 27, 9, 6), Estado_Sociologico = structure(c(2L, 2L, 3L, 3L, 1L, 3L, 3L, 3L, 5L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 2L, 3L, 2L, 2L, 4L, 2L, 3L, 3L, 3L, 5L, 4L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 2L, 2L, 2L, 3L, 5L, 5L, 1L, 1L, 3L, 3L, 3L, 1L, 5L, 2L, 1L, 3L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 5L, 5L, 5L, 5L, 2L, 2L, 1L, 3L, 5L, 3L, 5L, 2L, 5L, 1L, 3L, 5L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 5L, 2L, 3L, 1L, 2L, 5L, 2L, 1L, 2L, 2L, 2L, 3L, 4L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 5L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 3L, 2L, 2L, 5L, 1L, 5L, 2L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 5L, 3L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 5L, 1L, 1L, 2L, 2L, 1L, 2L, 4L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 3L, 3L, 3L, 5L, 2L, 5L, 3L, 3L, 2L, 2L, 1L, 3L, 5L, 1L, 2L, 1L, 5L, 3L, 3L, 5L, 2L, 2L, 3L, 5L, 3L, 3L, 3L, 5L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 2L, 3L, 2L, 3L, 3L, 2L, 5L, 2L, 5L, 3L, 5L, 5L, 2L, 5L, 3L, 5L, 3L, 2L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 5L, 2L, 5L, 3L, 3L, 3L, 2L, 3L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 5L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 5L, 5L, 3L, 3L, 2L, 5L, 5L, 3L, 5L, 2L, 3L, 5L, 2L, 2L, 2L, 3L, 2L, 3L, 5L, 2L, 1L, 1L, 2L, 2L, 3L, 5L, 3L, 5L, 3L, 1L, 5L, 3L, 3L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 5L, 1L, 1L, 5L, 5L), levels = c("Codominante", "Dominante", "Intermedio", "Muerto", "Suprimido"), class = "factor")), row.names = c(NA, -345L), class = c("tbl_df", "tbl", "data.frame"))