Importamos la data
library(rio)
## Warning: package 'rio' was built under R version 4.2.2
admit = "https://raw.githubusercontent.com/aishamartinez03/Estad-stica-/main/dataAdmit%20-%20dataAdmit.csv"
admit =import(admit)
str(admit)
## 'data.frame': 400 obs. of 4 variables:
## $ admitido : chr "no" "si" "si" "si" ...
## $ gre : int 380 660 800 640 520 760 560 400 540 700 ...
## $ gpa : num 3.61 3.67 4 3.19 2.93 3 2.98 3.08 3.39 3.92 ...
## $ prestigio: chr "Bajo" "Bajo" "MuyAlto" "MuyBajo" ...
library(rio)
mort = "https://raw.githubusercontent.com/aishamartinez03/Estad-stica-/main/mortalidad%20-%20datos.csv"
mort =import(mort)
str(mort)
## 'data.frame': 26574 obs. of 7 variables:
## $ sex : chr "male" "male" "male" "male" ...
## $ padreSector : chr "Agricultura" "Agricultura" "NoFijo" "Agricultura" ...
## $ fechaNacimiento: IDate, format: "1853-05-23" "1853-07-19" ...
## $ edadDejaEstudio: num 15 15 15 15 0.559 0.315 15 15 15 15 ...
## $ muere : int 0 0 0 0 1 1 0 0 0 0 ...
## $ naceFueraMatri : chr "no" "no" "no" "no" ...
## $ madreEdad : num 35 30.6 29.3 41.2 42.1 ...
library(rio)
data2022 = "https://raw.githubusercontent.com/aishamartinez03/Estad-stica-/main/data2022.csv"
data2022 =import(data2022)
str(data2022)
## 'data.frame': 228 obs. of 5 variables:
## $ Country : chr "Burundi" "Central African Republic" "Republic of the Congo" "Kenya" ...
## $ Food Risk Score : int 5 5 5 5 5 5 5 5 5 5 ...
## $ Natural Disasters Score : int 5 5 5 5 5 5 5 5 5 5 ...
## $ Rapid Population Growth Score: int 5 5 5 5 5 5 5 5 5 5 ...
## $ Water Risk Score : int 5 5 5 5 5 5 5 5 5 5 ...