R Notebook
Laura E. Vega Fdz Practica 2
2/5/2020
Librerias necesarias
library(readr)
library(dplyr)
library(fdth)Cargar datos
datos<-read.csv("../Datos/starwars.csv", fileEncoding = "UTF-8", header = TRUE)Revisar los datos cargados
str(datos)## 'data.frame': 87 obs. of 11 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ name : Factor w/ 87 levels "Ackbar","Adi Gallia",..: 46 15 62 21 44 54 10 64 12 53 ...
## $ height : int 172 167 96 202 150 178 165 97 183 182 ...
## $ mass : num 77 75 32 136 49 120 75 32 84 77 ...
## $ hair_color: Factor w/ 12 levels "auburn","auburn, grey",..: 5 NA NA 10 7 8 7 NA 4 3 ...
## $ skin_color: Factor w/ 31 levels "blue","blue, grey",..: 7 9 29 28 17 17 17 30 17 7 ...
## $ eye_color : Factor w/ 15 levels "black","blue",..: 2 15 11 15 4 2 2 11 4 3 ...
## $ birth_year: num 19 112 33 41.9 19 52 47 NA 24 57 ...
## $ gender : Factor w/ 4 levels "female","hermaphrodite",..: 3 NA NA 3 1 3 1 NA 3 3 ...
## $ homeworld : Factor w/ 48 levels "Alderaan","Aleen Minor",..: 40 40 28 40 1 40 40 40 40 38 ...
## $ species : Factor w/ 37 levels "Aleena","Besalisk",..: 11 6 6 11 11 11 11 6 11 11 ...summary(datos)## X name height mass
## Min. : 1.0 Ackbar : 1 Min. : 66.0 Min. : 15.00
## 1st Qu.:22.5 Adi Gallia : 1 1st Qu.:167.0 1st Qu.: 55.60
## Median :44.0 Anakin Skywalker : 1 Median :180.0 Median : 79.00
## Mean :44.0 Arvel Crynyd : 1 Mean :174.4 Mean : 97.31
## 3rd Qu.:65.5 Ayla Secura : 1 3rd Qu.:191.0 3rd Qu.: 84.50
## Max. :87.0 Bail Prestor Organa: 1 Max. :264.0 Max. :1358.00
## (Other) :81 NA's :6 NA's :28
## hair_color skin_color eye_color birth_year gender
## none :37 fair :17 brown :21 Min. : 8.00 female :19
## brown :18 light :11 blue :19 1st Qu.: 35.00 hermaphrodite: 1
## black :13 dark : 6 yellow :11 Median : 52.00 male :62
## white : 4 green : 6 black :10 Mean : 87.57 none : 2
## blond : 3 grey : 6 orange : 8 3rd Qu.: 72.00 NA's : 3
## (Other): 7 pale : 5 red : 5 Max. :896.00
## NA's : 5 (Other):36 (Other):13 NA's :44
## homeworld species
## Naboo :11 Human :35
## Tatooine :10 Droid : 5
## Alderaan : 3 Gungan : 3
## Coruscant: 3 Kaminoan: 2
## Kamino : 3 Mirialan: 2
## (Other) :47 (Other) :35
## NA's :10 NA's : 5Generar tabla de Distribucion de Frecuencia para gender, variable categorica, y su grafica
tabla.frec<-fdt_cat(x=datos$gender)
tabla.frec<-as.data.frame(tabla.frec)
tabla.frecbarplot(height = tabla.frec$f, names.arg = tabla.frec$Category)
Generar tabla de Distribucion de Frecuencia para homeworld, variable categorica, y su grafica
tabla.frec2<-fdt_cat(x=datos$homeworld)
tabla.frec2<-as.data.frame(tabla.frec2)
tabla.frec2barplot(height = tabla.frec2$f, names.arg = tabla.frec2$Category)
Generar tabla de Distribucion de Frecuencia para species, variable categorica, y su grafica
tabla.frec3<-fdt_cat(x=datos$species)
tabla.frec3<-as.data.frame(tabla.frec3)
tabla.frec3barplot(height = tabla.frec3$f, names.arg = tabla.frec3$Category)
Generar tabla de Distribucion de Frecuencia para height estatura y su grafica
tabla.frec4<-fdt(x=datos$height)
tabla.frec4## Class limits f rf rf(%) cf cf(%)
## [65.34,90.5025) 3 0.04 3.70 3 3.70
## [90.5025,115.665) 5 0.06 6.17 8 9.88
## [115.665,140.827) 2 0.02 2.47 10 12.35
## [140.827,165.99) 9 0.11 11.11 19 23.46
## [165.99,191.152) 43 0.53 53.09 62 76.54
## [191.152,216.315) 14 0.17 17.28 76 93.83
## [216.315,241.477) 4 0.05 4.94 80 98.77
## [241.477,266.64) 1 0.01 1.23 81 100.00barplot(height = tabla.frec4$table$f, names.arg = tabla.frec4$table$`Class limits`)
Generar tabla de Distribucion de Frecuencia para mass peso y su grafica
tabla.frec5<-fdt(x=datos$mass)
tabla.frec5## Class limits f rf rf(%) cf cf(%)
## [14.85,208.6686) 58 0.98 98.31 58 98.31
## [208.6686,402.4871) 0 0.00 0.00 58 98.31
## [402.4871,596.3057) 0 0.00 0.00 58 98.31
## [596.3057,790.1243) 0 0.00 0.00 58 98.31
## [790.1243,983.9429) 0 0.00 0.00 58 98.31
## [983.9429,1177.761) 0 0.00 0.00 58 98.31
## [1177.761,1371.58) 1 0.02 1.69 59 100.00barplot(height = tabla.frec5$table$f, names.arg = tabla.frec5$table$`Class limits`)