library(tidyverse)
df16 <- read_csv('../Fuentes/tas_part_lad_16_sexo__annio__g_g_activ_limpio.csv')
df05 <- read_csv('../Fuentes/tas_part_lad_sexo__annio__g_g_activ_limpio.csv')
df <- bind_rows(df05,df16)
library(gapminder)
glimpse(gapminder)
library(ggridges)
library(viridis)
ggplot(gapminder, aes(x = lifeExp, y = factor(year), fill = ..x..)) +
geom_density_ridges_gradient()+
scale_y_discrete(expand = c(0.01, 0)) +
scale_fill_viridis(name = "Esperanza de vida", option = "C")+
theme_ridges()+
theme(legend.position = 'bottom')
View(df05)
View(df16)
View(df)
a <- rbind(df05,df16)
a <-
df05 %>% rename(anio2 = anio) %>%
rbind(,df16)
a <-
df05 %>% rename(anio2 = anio) %>%
rbind(.,df16)
a <-
df05 %>%
#rename(anio2 = anio) %>%
rbind(.,df16)
a <-
df05 %>%
select(-anio) %>%
rbind(.,df16)
a <-
df05 %>%
select(sexo,everything()) %>%
rbind(.,df16)
View(a)
a <-
df05 %>%
mutate(sexos = 2) %>%
rbind(.,df16)
