#Punto 1

library(dslabs)
data("murders")
region<-as.data.frame(state.region)
state<-as.data.frame(state.name)
de<-as.data.frame(table(region$state))
de
##            Var1 Freq
## 1     Northeast    9
## 2         South   16
## 3 North Central   12
## 4          West   13
pop<-c(murders$population)
sort(pop)
##  [1]   563626   601723   625741   672591   710231   814180   897934   989415
##  [9]  1052567  1316470  1328361  1360301  1567582  1826341  1852994  2059179
## [17]  2700551  2763885  2853118  2915918  2967297  3046355  3574097  3751351
## [25]  3831074  4339367  4533372  4625364  4779736  5029196  5303925  5686986
## [33]  5773552  5988927  6346105  6392017  6483802  6547629  6724540  8001024
## [41]  8791894  9535483  9883640  9920000 11536504 12702379 12830632 19378102
## [49] 19687653 25145561 37253956
order(pop)
##  [1] 51  9 46 35  2 42  8 27 40 30 20 12 13 28 49 32 29 45 17  4 25 16  7 37 38
## [26] 18 19 41  1  6 24 50 21 26 43  3 15 22 48 47 31 34 23 11 36 39 14 33 10 44
## [51]  5
i<-which.min(pop)
i
## [1] 51
murders$state[i]
## [1] "Wyoming"

#Punto 2

data("movielens")
nrow(movielens)
## [1] 100004
ncol(movielens)
## [1] 7
class(movielens$title)
## [1] "character"
class(movielens$genres)
## [1] "factor"
nlevels(movielens$genres)
## [1] 901