Para comenzar a trazar los histogramas con ggvis, primero se debe descargar https://github.com/rstudio/ggvis.
installed.packages("ggvis")
## Package LibPath Version Priority Depends Imports LinkingTo Suggests
## Enhances License License_is_FOSS License_restricts_use OS_type Archs
## MD5sum NeedsCompilation Built
Para comenzar a trabajar con ggvis cargamos el paquete
library(ggvis)
## Warning: package 'ggvis' was built under R version 3.4.2
data<-read.table(url("http://s3.amazonaws.com/assets.datacamp.com/blog_assets/chol.txt"), header = TRUE)
str(data)
## 'data.frame': 200 obs. of 7 variables:
## $ AGE : int 20 53 44 37 26 41 39 28 33 39 ...
## $ HEIGHT: int 176 167 170 173 170 165 174 171 180 166 ...
## $ WEIGHT: int 77 56 80 89 71 62 75 68 100 74 ...
## $ CHOL : int 195 250 304 178 206 284 232 152 209 150 ...
## $ SMOKE : Factor w/ 3 levels "nonsmo","pipe",..: 1 3 3 1 3 3 3 2 3 3 ...
## $ BLOOD : Factor w/ 4 levels "a","ab","b","o": 3 4 1 4 4 4 4 1 1 1 ...
## $ MORT : Factor w/ 2 levels "alive","dead": 1 2 2 1 1 1 1 1 1 1 ...
head(data)
## AGE HEIGHT WEIGHT CHOL SMOKE BLOOD MORT
## 1 20 176 77 195 nonsmo b alive
## 2 53 167 56 250 sigare o dead
## 3 44 170 80 304 sigare a dead
## 4 37 173 89 178 nonsmo o alive
## 5 26 170 71 206 sigare o alive
## 6 41 165 62 284 sigare o alive
data %>%
ggvis(~AGE) %>%
layer_histograms()
## Guessing width = 1 # range / 40
data %>%
ggvis(~AGE) %>%
layer_histograms(width = 5, center = 35, fill := "#E74C3C") %>%
add_axis("x", title = "Age")%>%
add_axis("y", title = "Count")