Tarea de Noviembre
Vanessa Edith Osuna Mariscal
2023-11-17
ME GUSTÓ ESTA TAREA, SALUDOS!
library(janitor)
library(tidyverse)
library(flextable)
library(moments)
setwd("C:/Users/Nabor Osuna/Downloads/PROYECTO FINAL")
df=read.csv("Life expectancy.csv")
table(df$Birth.rate)##
## 10.0 ‰ 10.1 ‰ 10.2 ‰ 10.3 ‰ 10.4 ‰ 10.5 ‰ 10.6 ‰ 10.8 ‰ 10.9 ‰ 11.0 ‰ 11.1 ‰
## 1 2 3 3 2 1 1 1 1 2 1
## 11.4 ‰ 11.5 ‰ 11.6 ‰ 11.8 ‰ 11.9 ‰ 12.0 ‰ 12.1 ‰ 12.9 ‰ 13.1 ‰ 13.2 ‰ 13.4 ‰
## 1 1 1 1 2 1 1 1 1 1 1
## 13.7 ‰ 13.8 ‰ 13.9 ‰ 14.0 ‰ 14.1 ‰ 14.2 ‰ 14.7 ‰ 14.9 ‰ 15.0 ‰ 15.2 ‰ 15.9 ‰
## 1 1 1 1 1 1 1 2 1 1 1
## 16.0 ‰ 16.4 ‰ 16.8 ‰ 17.1 ‰ 17.5 ‰ 17.7 ‰ 17.8 ‰ 18.4 ‰ 19.3 ‰ 19.7 ‰ 19.8 ‰
## 1 2 1 1 2 1 1 2 2 1 1
## 20.1 ‰ 20.4 ‰ 21.1 ‰ 21.4 ‰ 21.5 ‰ 21.8 ‰ 22.0 ‰ 22.6 ‰ 23.5 ‰ 24.9 ‰ 25.9 ‰
## 1 1 1 1 1 2 2 1 2 1 1
## 27.4 ‰ 27.5 ‰ 27.7 ‰ 30.5 ‰ 32.4 ‰ 32.6 ‰ 33.6 ‰ 33.9 ‰ 34.5 ‰ 34.9 ‰ 35.8 ‰
## 1 2 1 2 1 1 1 1 1 1 1
## 36.2 ‰ 37.1 ‰ 38.8 ‰ 42.0 ‰ 43.4 ‰ 43.6 ‰ 45.3 ‰ 5.0 ‰ 5.1 ‰ 5.9 ‰ 6.6 ‰
## 1 1 1 1 1 1 1 1 1 1 1
## 6.8 ‰ 7.1 ‰ 7.3 ‰ 7.5 ‰ 7.7 ‰ 8.0 ‰ 8.3 ‰ 8.5 ‰ 8.6 ‰ 8.8 ‰ 8.9 ‰
## 1 1 1 1 2 1 1 2 1 1 1
## 9.0 ‰ 9.1 ‰ 9.2 ‰ 9.3 ‰ 9.4 ‰ 9.6 ‰ 9.7 ‰ 9.8 ‰
## 2 1 1 1 1 4 1 1La funcion taby se encuentra en la paqueteria janitor
df %>% tabyl(Birth.rate)## Birth.rate n percent
## 10.0 ‰ 1 0.008333333
## 10.1 ‰ 2 0.016666667
## 10.2 ‰ 3 0.025000000
## 10.3 ‰ 3 0.025000000
## 10.4 ‰ 2 0.016666667
## 10.5 ‰ 1 0.008333333
## 10.6 ‰ 1 0.008333333
## 10.8 ‰ 1 0.008333333
## 10.9 ‰ 1 0.008333333
## 11.0 ‰ 2 0.016666667
## 11.1 ‰ 1 0.008333333
## 11.4 ‰ 1 0.008333333
## 11.5 ‰ 1 0.008333333
## 11.6 ‰ 1 0.008333333
## 11.8 ‰ 1 0.008333333
## 11.9 ‰ 2 0.016666667
## 12.0 ‰ 1 0.008333333
## 12.1 ‰ 1 0.008333333
## 12.9 ‰ 1 0.008333333
## 13.1 ‰ 1 0.008333333
## 13.2 ‰ 1 0.008333333
## 13.4 ‰ 1 0.008333333
## 13.7 ‰ 1 0.008333333
## 13.8 ‰ 1 0.008333333
## 13.9 ‰ 1 0.008333333
## 14.0 ‰ 1 0.008333333
## 14.1 ‰ 1 0.008333333
## 14.2 ‰ 1 0.008333333
## 14.7 ‰ 1 0.008333333
## 14.9 ‰ 2 0.016666667
## 15.0 ‰ 1 0.008333333
## 15.2 ‰ 1 0.008333333
## 15.9 ‰ 1 0.008333333
## 16.0 ‰ 1 0.008333333
## 16.4 ‰ 2 0.016666667
## 16.8 ‰ 1 0.008333333
## 17.1 ‰ 1 0.008333333
## 17.5 ‰ 2 0.016666667
## 17.7 ‰ 1 0.008333333
## 17.8 ‰ 1 0.008333333
## 18.4 ‰ 2 0.016666667
## 19.3 ‰ 2 0.016666667
## 19.7 ‰ 1 0.008333333
## 19.8 ‰ 1 0.008333333
## 20.1 ‰ 1 0.008333333
## 20.4 ‰ 1 0.008333333
## 21.1 ‰ 1 0.008333333
## 21.4 ‰ 1 0.008333333
## 21.5 ‰ 1 0.008333333
## 21.8 ‰ 2 0.016666667
## 22.0 ‰ 2 0.016666667
## 22.6 ‰ 1 0.008333333
## 23.5 ‰ 2 0.016666667
## 24.9 ‰ 1 0.008333333
## 25.9 ‰ 1 0.008333333
## 27.4 ‰ 1 0.008333333
## 27.5 ‰ 2 0.016666667
## 27.7 ‰ 1 0.008333333
## 30.5 ‰ 2 0.016666667
## 32.4 ‰ 1 0.008333333
## 32.6 ‰ 1 0.008333333
## 33.6 ‰ 1 0.008333333
## 33.9 ‰ 1 0.008333333
## 34.5 ‰ 1 0.008333333
## 34.9 ‰ 1 0.008333333
## 35.8 ‰ 1 0.008333333
## 36.2 ‰ 1 0.008333333
## 37.1 ‰ 1 0.008333333
## 38.8 ‰ 1 0.008333333
## 42.0 ‰ 1 0.008333333
## 43.4 ‰ 1 0.008333333
## 43.6 ‰ 1 0.008333333
## 45.3 ‰ 1 0.008333333
## 5.0 ‰ 1 0.008333333
## 5.1 ‰ 1 0.008333333
## 5.9 ‰ 1 0.008333333
## 6.6 ‰ 1 0.008333333
## 6.8 ‰ 1 0.008333333
## 7.1 ‰ 1 0.008333333
## 7.3 ‰ 1 0.008333333
## 7.5 ‰ 1 0.008333333
## 7.7 ‰ 2 0.016666667
## 8.0 ‰ 1 0.008333333
## 8.3 ‰ 1 0.008333333
## 8.5 ‰ 2 0.016666667
## 8.6 ‰ 1 0.008333333
## 8.8 ‰ 1 0.008333333
## 8.9 ‰ 1 0.008333333
## 9.0 ‰ 2 0.016666667
## 9.1 ‰ 1 0.008333333
## 9.2 ‰ 1 0.008333333
## 9.3 ‰ 1 0.008333333
## 9.4 ‰ 1 0.008333333
## 9.6 ‰ 4 0.033333333
## 9.7 ‰ 1 0.008333333
## 9.8 ‰ 1 0.008333333versión mejorada
df %>% tabyl(Life.expectancy.females)## Life.expectancy.females n percent
## 53.1 years 1 0.008333333
## 54.3 years 1 0.008333333
## 57.4 years 1 0.008333333
## 59.9 years 1 0.008333333
## 61.5 years 1 0.008333333
## 62.0 years 2 0.016666667
## 62.8 years 1 0.008333333
## 63.9 years 1 0.008333333
## 64.1 years 1 0.008333333
## 64.3 years 1 0.008333333
## 65.0 years 1 0.008333333
## 65.3 years 1 0.008333333
## 66.0 years 1 0.008333333
## 66.1 years 1 0.008333333
## 66.8 years 1 0.008333333
## 67.1 years 1 0.008333333
## 67.9 years 1 0.008333333
## 68.3 years 2 0.016666667
## 68.6 years 1 0.008333333
## 68.9 years 2 0.016666667
## 69.0 years 1 0.008333333
## 69.3 years 1 0.008333333
## 69.5 years 1 0.008333333
## 69.7 years 1 0.008333333
## 70.1 years 1 0.008333333
## 70.4 years 1 0.008333333
## 71.5 years 1 0.008333333
## 72.3 years 1 0.008333333
## 72.4 years 1 0.008333333
## 72.6 years 1 0.008333333
## 72.7 years 1 0.008333333
## 73.3 years 1 0.008333333
## 73.4 years 1 0.008333333
## 74.0 years 1 0.008333333
## 74.3 years 1 0.008333333
## 74.4 years 1 0.008333333
## 74.7 years 1 0.008333333
## 74.8 years 1 0.008333333
## 74.9 years 1 0.008333333
## 75.1 years 2 0.016666667
## 75.2 years 2 0.016666667
## 75.6 years 1 0.008333333
## 75.7 years 2 0.016666667
## 76.0 years 1 0.008333333
## 76.3 years 1 0.008333333
## 76.4 years 3 0.025000000
## 76.7 years 2 0.016666667
## 76.8 years 2 0.016666667
## 76.9 years 1 0.008333333
## 77.0 years 1 0.008333333
## 77.2 years 1 0.008333333
## 77.3 years 1 0.008333333
## 77.4 years 2 0.016666667
## 77.5 years 1 0.008333333
## 78.0 years 2 0.016666667
## 78.2 years 2 0.016666667
## 78.6 years 1 0.008333333
## 78.8 years 1 0.008333333
## 79.0 years 1 0.008333333
## 79.1 years 1 0.008333333
## 79.2 years 1 0.008333333
## 79.3 years 1 0.008333333
## 79.5 years 1 0.008333333
## 79.6 years 2 0.016666667
## 79.7 years 1 0.008333333
## 79.8 years 1 0.008333333
## 80.0 years 1 0.008333333
## 80.6 years 1 0.008333333
## 80.9 years 2 0.016666667
## 81.0 years 1 0.008333333
## 81.2 years 1 0.008333333
## 81.3 years 1 0.008333333
## 81.4 years 1 0.008333333
## 81.5 years 1 0.008333333
## 82.7 years 1 0.008333333
## 82.8 years 1 0.008333333
## 83.0 years 2 0.016666667
## 83.1 years 1 0.008333333
## 83.3 years 1 0.008333333
## 83.4 years 1 0.008333333
## 83.8 years 1 0.008333333
## 84.0 years 1 0.008333333
## 84.1 years 1 0.008333333
## 84.3 years 1 0.008333333
## 84.4 years 1 0.008333333
## 84.5 years 3 0.025000000
## 84.6 years 1 0.008333333
## 84.7 years 3 0.025000000
## 84.9 years 1 0.008333333
## 85.0 years 1 0.008333333
## 85.1 years 1 0.008333333
## 85.4 years 1 0.008333333
## 85.5 years 1 0.008333333
## 85.9 years 2 0.016666667
## 86.2 years 1 0.008333333
## 86.6 years 1 0.008333333
## 87.6 years 1 0.008333333
## 87.9 years 2 0.016666667Mejorando
df %>% tabyl(Life.expectancy.females) %>%
flextable() %>%
fontsize(size=14) %>%
autofit()Life.expectancy.females | n | percent |
|---|---|---|
53.1 years | 1 | 0.008333333 |
54.3 years | 1 | 0.008333333 |
57.4 years | 1 | 0.008333333 |
59.9 years | 1 | 0.008333333 |
61.5 years | 1 | 0.008333333 |
62.0 years | 2 | 0.016666667 |
62.8 years | 1 | 0.008333333 |
63.9 years | 1 | 0.008333333 |
64.1 years | 1 | 0.008333333 |
64.3 years | 1 | 0.008333333 |
65.0 years | 1 | 0.008333333 |
65.3 years | 1 | 0.008333333 |
66.0 years | 1 | 0.008333333 |
66.1 years | 1 | 0.008333333 |
66.8 years | 1 | 0.008333333 |
67.1 years | 1 | 0.008333333 |
67.9 years | 1 | 0.008333333 |
68.3 years | 2 | 0.016666667 |
68.6 years | 1 | 0.008333333 |
68.9 years | 2 | 0.016666667 |
69.0 years | 1 | 0.008333333 |
69.3 years | 1 | 0.008333333 |
69.5 years | 1 | 0.008333333 |
69.7 years | 1 | 0.008333333 |
70.1 years | 1 | 0.008333333 |
70.4 years | 1 | 0.008333333 |
71.5 years | 1 | 0.008333333 |
72.3 years | 1 | 0.008333333 |
72.4 years | 1 | 0.008333333 |
72.6 years | 1 | 0.008333333 |
72.7 years | 1 | 0.008333333 |
73.3 years | 1 | 0.008333333 |
73.4 years | 1 | 0.008333333 |
74.0 years | 1 | 0.008333333 |
74.3 years | 1 | 0.008333333 |
74.4 years | 1 | 0.008333333 |
74.7 years | 1 | 0.008333333 |
74.8 years | 1 | 0.008333333 |
74.9 years | 1 | 0.008333333 |
75.1 years | 2 | 0.016666667 |
75.2 years | 2 | 0.016666667 |
75.6 years | 1 | 0.008333333 |
75.7 years | 2 | 0.016666667 |
76.0 years | 1 | 0.008333333 |
76.3 years | 1 | 0.008333333 |
76.4 years | 3 | 0.025000000 |
76.7 years | 2 | 0.016666667 |
76.8 years | 2 | 0.016666667 |
76.9 years | 1 | 0.008333333 |
77.0 years | 1 | 0.008333333 |
77.2 years | 1 | 0.008333333 |
77.3 years | 1 | 0.008333333 |
77.4 years | 2 | 0.016666667 |
77.5 years | 1 | 0.008333333 |
78.0 years | 2 | 0.016666667 |
78.2 years | 2 | 0.016666667 |
78.6 years | 1 | 0.008333333 |
78.8 years | 1 | 0.008333333 |
79.0 years | 1 | 0.008333333 |
79.1 years | 1 | 0.008333333 |
79.2 years | 1 | 0.008333333 |
79.3 years | 1 | 0.008333333 |
79.5 years | 1 | 0.008333333 |
79.6 years | 2 | 0.016666667 |
79.7 years | 1 | 0.008333333 |
79.8 years | 1 | 0.008333333 |
80.0 years | 1 | 0.008333333 |
80.6 years | 1 | 0.008333333 |
80.9 years | 2 | 0.016666667 |
81.0 years | 1 | 0.008333333 |
81.2 years | 1 | 0.008333333 |
81.3 years | 1 | 0.008333333 |
81.4 years | 1 | 0.008333333 |
81.5 years | 1 | 0.008333333 |
82.7 years | 1 | 0.008333333 |
82.8 years | 1 | 0.008333333 |
83.0 years | 2 | 0.016666667 |
83.1 years | 1 | 0.008333333 |
83.3 years | 1 | 0.008333333 |
83.4 years | 1 | 0.008333333 |
83.8 years | 1 | 0.008333333 |
84.0 years | 1 | 0.008333333 |
84.1 years | 1 | 0.008333333 |
84.3 years | 1 | 0.008333333 |
84.4 years | 1 | 0.008333333 |
84.5 years | 3 | 0.025000000 |
84.6 years | 1 | 0.008333333 |
84.7 years | 3 | 0.025000000 |
84.9 years | 1 | 0.008333333 |
85.0 years | 1 | 0.008333333 |
85.1 years | 1 | 0.008333333 |
85.4 years | 1 | 0.008333333 |
85.5 years | 1 | 0.008333333 |
85.9 years | 2 | 0.016666667 |
86.2 years | 1 | 0.008333333 |
86.6 years | 1 | 0.008333333 |
87.6 years | 1 | 0.008333333 |
87.9 years | 2 | 0.016666667 |
MEJOR AÚN
df %>% tabyl(Life.expectancy.females) %>%
adorn_pct_formatting() %>%
flextable() %>%
fontsize(size=14) %>%
autofit() %>%
theme_box()Life.expectancy.females | n | percent |
|---|---|---|
53.1 years | 1 | 0.8% |
54.3 years | 1 | 0.8% |
57.4 years | 1 | 0.8% |
59.9 years | 1 | 0.8% |
61.5 years | 1 | 0.8% |
62.0 years | 2 | 1.7% |
62.8 years | 1 | 0.8% |
63.9 years | 1 | 0.8% |
64.1 years | 1 | 0.8% |
64.3 years | 1 | 0.8% |
65.0 years | 1 | 0.8% |
65.3 years | 1 | 0.8% |
66.0 years | 1 | 0.8% |
66.1 years | 1 | 0.8% |
66.8 years | 1 | 0.8% |
67.1 years | 1 | 0.8% |
67.9 years | 1 | 0.8% |
68.3 years | 2 | 1.7% |
68.6 years | 1 | 0.8% |
68.9 years | 2 | 1.7% |
69.0 years | 1 | 0.8% |
69.3 years | 1 | 0.8% |
69.5 years | 1 | 0.8% |
69.7 years | 1 | 0.8% |
70.1 years | 1 | 0.8% |
70.4 years | 1 | 0.8% |
71.5 years | 1 | 0.8% |
72.3 years | 1 | 0.8% |
72.4 years | 1 | 0.8% |
72.6 years | 1 | 0.8% |
72.7 years | 1 | 0.8% |
73.3 years | 1 | 0.8% |
73.4 years | 1 | 0.8% |
74.0 years | 1 | 0.8% |
74.3 years | 1 | 0.8% |
74.4 years | 1 | 0.8% |
74.7 years | 1 | 0.8% |
74.8 years | 1 | 0.8% |
74.9 years | 1 | 0.8% |
75.1 years | 2 | 1.7% |
75.2 years | 2 | 1.7% |
75.6 years | 1 | 0.8% |
75.7 years | 2 | 1.7% |
76.0 years | 1 | 0.8% |
76.3 years | 1 | 0.8% |
76.4 years | 3 | 2.5% |
76.7 years | 2 | 1.7% |
76.8 years | 2 | 1.7% |
76.9 years | 1 | 0.8% |
77.0 years | 1 | 0.8% |
77.2 years | 1 | 0.8% |
77.3 years | 1 | 0.8% |
77.4 years | 2 | 1.7% |
77.5 years | 1 | 0.8% |
78.0 years | 2 | 1.7% |
78.2 years | 2 | 1.7% |
78.6 years | 1 | 0.8% |
78.8 years | 1 | 0.8% |
79.0 years | 1 | 0.8% |
79.1 years | 1 | 0.8% |
79.2 years | 1 | 0.8% |
79.3 years | 1 | 0.8% |
79.5 years | 1 | 0.8% |
79.6 years | 2 | 1.7% |
79.7 years | 1 | 0.8% |
79.8 years | 1 | 0.8% |
80.0 years | 1 | 0.8% |
80.6 years | 1 | 0.8% |
80.9 years | 2 | 1.7% |
81.0 years | 1 | 0.8% |
81.2 years | 1 | 0.8% |
81.3 years | 1 | 0.8% |
81.4 years | 1 | 0.8% |
81.5 years | 1 | 0.8% |
82.7 years | 1 | 0.8% |
82.8 years | 1 | 0.8% |
83.0 years | 2 | 1.7% |
83.1 years | 1 | 0.8% |
83.3 years | 1 | 0.8% |
83.4 years | 1 | 0.8% |
83.8 years | 1 | 0.8% |
84.0 years | 1 | 0.8% |
84.1 years | 1 | 0.8% |
84.3 years | 1 | 0.8% |
84.4 years | 1 | 0.8% |
84.5 years | 3 | 2.5% |
84.6 years | 1 | 0.8% |
84.7 years | 3 | 2.5% |
84.9 years | 1 | 0.8% |
85.0 years | 1 | 0.8% |
85.1 years | 1 | 0.8% |
85.4 years | 1 | 0.8% |
85.5 years | 1 | 0.8% |
85.9 years | 2 | 1.7% |
86.2 years | 1 | 0.8% |
86.6 years | 1 | 0.8% |
87.6 years | 1 | 0.8% |
87.9 years | 2 | 1.7% |
Con TOTAL…
df %>% tabyl(Life.expectancy.males) %>%
adorn_totals("row") %>%
adorn_pct_formatting() %>%
flextable() %>%
fontsize(size=14) %>%
autofit() %>%
theme_box()Life.expectancy.males | n | percent |
|---|---|---|
50.8 years | 1 | 0.8% |
52.3 years | 1 | 0.8% |
53.2 years | 1 | 0.8% |
56.2 years | 1 | 0.8% |
57.0 years | 1 | 0.8% |
57.4 years | 1 | 0.8% |
58.5 years | 1 | 0.8% |
58.7 years | 1 | 0.8% |
58.9 years | 2 | 1.7% |
59.0 years | 1 | 0.8% |
59.5 years | 1 | 0.8% |
60.4 years | 2 | 1.7% |
60.6 years | 1 | 0.8% |
60.9 years | 1 | 0.8% |
61.6 years | 1 | 0.8% |
61.9 years | 1 | 0.8% |
62.5 years | 1 | 0.8% |
62.7 years | 1 | 0.8% |
63.8 years | 1 | 0.8% |
64.2 years | 2 | 1.7% |
64.8 years | 1 | 0.8% |
65.2 years | 1 | 0.8% |
65.4 years | 1 | 0.8% |
65.5 years | 1 | 0.8% |
65.6 years | 1 | 0.8% |
65.8 years | 1 | 0.8% |
66.0 years | 1 | 0.8% |
66.1 years | 3 | 2.5% |
66.2 years | 1 | 0.8% |
66.3 years | 2 | 1.7% |
66.5 years | 1 | 0.8% |
66.6 years | 2 | 1.7% |
66.8 years | 2 | 1.7% |
67.2 years | 1 | 0.8% |
67.9 years | 1 | 0.8% |
68.1 years | 1 | 0.8% |
68.2 years | 1 | 0.8% |
68.3 years | 1 | 0.8% |
68.6 years | 1 | 0.8% |
69.1 years | 2 | 1.7% |
69.3 years | 1 | 0.8% |
69.4 years | 2 | 1.7% |
69.6 years | 1 | 0.8% |
69.9 years | 1 | 0.8% |
70.0 years | 1 | 0.8% |
70.3 years | 2 | 1.7% |
70.6 years | 1 | 0.8% |
70.8 years | 2 | 1.7% |
71.0 years | 1 | 0.8% |
71.1 years | 1 | 0.8% |
71.2 years | 2 | 1.7% |
71.7 years | 1 | 0.8% |
71.9 years | 1 | 0.8% |
72.1 years | 1 | 0.8% |
72.2 years | 1 | 0.8% |
72.4 years | 1 | 0.8% |
72.6 years | 1 | 0.8% |
72.7 years | 1 | 0.8% |
72.8 years | 1 | 0.8% |
73.0 years | 1 | 0.8% |
73.1 years | 2 | 1.7% |
73.4 years | 1 | 0.8% |
73.5 years | 1 | 0.8% |
74.1 years | 1 | 0.8% |
74.3 years | 1 | 0.8% |
74.4 years | 1 | 0.8% |
74.5 years | 1 | 0.8% |
74.9 years | 1 | 0.8% |
75.5 years | 1 | 0.8% |
75.6 years | 1 | 0.8% |
75.8 years | 1 | 0.8% |
75.9 years | 1 | 0.8% |
76.5 years | 1 | 0.8% |
77.2 years | 2 | 1.7% |
77.5 years | 1 | 0.8% |
77.8 years | 1 | 0.8% |
78.0 years | 1 | 0.8% |
78.3 years | 1 | 0.8% |
78.5 years | 1 | 0.8% |
78.7 years | 1 | 0.8% |
78.8 years | 1 | 0.8% |
79.1 years | 1 | 0.8% |
79.3 years | 2 | 1.7% |
79.5 years | 1 | 0.8% |
79.6 years | 1 | 0.8% |
79.9 years | 1 | 0.8% |
80.2 years | 1 | 0.8% |
80.3 years | 1 | 0.8% |
80.5 years | 2 | 1.7% |
80.6 years | 3 | 2.5% |
80.7 years | 1 | 0.8% |
81.1 years | 1 | 0.8% |
81.3 years | 2 | 1.7% |
81.4 years | 1 | 0.8% |
81.5 years | 1 | 0.8% |
81.7 years | 1 | 0.8% |
81.8 years | 1 | 0.8% |
81.9 years | 1 | 0.8% |
82.8 years | 1 | 0.8% |
83.2 years | 1 | 0.8% |
Total | 120 | 100.0% |
DE COLORES…….
df %>% tabyl(Life.expectancy.males) %>%
ggplot(aes(x=Life.expectancy.males,y=n,fill=Life.expectancy.males)) +
geom_col() +
labs(x="Edad", y="Frecuencia",title = "ESPERANZA DE VIDA EN HOMBRES") +
geom_text(aes(label=n),vjust=1.5,col="black",fontface="bold")
—> ALGO MÁS <—
df %>% tabyl(Life.expectancy.males) %>%
ggplot(aes(x=Life.expectancy.males,y=n,fill=Life.expectancy.males)) +
geom_col() +
labs(x="Edad", y="Frecuencia",title = "ESPERANZA DE VIDA EN HOMBRES") +
geom_text(aes(label=sprintf("%.2f%%",100*percent)),vjust=1.5,col="black",fontface="bold")
NUMEROS DE LA CAMPANA DE GAUSS JORDAN
n=100000
numeros= rnorm(n=n,mean=20,sd=1)
df1=data.frame(numeros)
df1 %>%
ggplot (aes(x=numeros)) + geom_histogram(color= "purple", fill="lightpink") +
labs(x="Numeros", y= "Frecuencia", title = "Campana de Gauss Experimental")
colors()## [1] "white" "aliceblue" "antiquewhite"
## [4] "antiquewhite1" "antiquewhite2" "antiquewhite3"
## [7] "antiquewhite4" "aquamarine" "aquamarine1"
## [10] "aquamarine2" "aquamarine3" "aquamarine4"
## [13] "azure" "azure1" "azure2"
## [16] "azure3" "azure4" "beige"
## [19] "bisque" "bisque1" "bisque2"
## [22] "bisque3" "bisque4" "black"
## [25] "blanchedalmond" "blue" "blue1"
## [28] "blue2" "blue3" "blue4"
## [31] "blueviolet" "brown" "brown1"
## [34] "brown2" "brown3" "brown4"
## [37] "burlywood" "burlywood1" "burlywood2"
## [40] "burlywood3" "burlywood4" "cadetblue"
## [43] "cadetblue1" "cadetblue2" "cadetblue3"
## [46] "cadetblue4" "chartreuse" "chartreuse1"
## [49] "chartreuse2" "chartreuse3" "chartreuse4"
## [52] "chocolate" "chocolate1" "chocolate2"
## [55] "chocolate3" "chocolate4" "coral"
## [58] "coral1" "coral2" "coral3"
## [61] "coral4" "cornflowerblue" "cornsilk"
## [64] "cornsilk1" "cornsilk2" "cornsilk3"
## [67] "cornsilk4" "cyan" "cyan1"
## [70] "cyan2" "cyan3" "cyan4"
## [73] "darkblue" "darkcyan" "darkgoldenrod"
## [76] "darkgoldenrod1" "darkgoldenrod2" "darkgoldenrod3"
## [79] "darkgoldenrod4" "darkgray" "darkgreen"
## [82] "darkgrey" "darkkhaki" "darkmagenta"
## [85] "darkolivegreen" "darkolivegreen1" "darkolivegreen2"
## [88] "darkolivegreen3" "darkolivegreen4" "darkorange"
## [91] "darkorange1" "darkorange2" "darkorange3"
## [94] "darkorange4" "darkorchid" "darkorchid1"
## [97] "darkorchid2" "darkorchid3" "darkorchid4"
## [100] "darkred" "darksalmon" "darkseagreen"
## [103] "darkseagreen1" "darkseagreen2" "darkseagreen3"
## [106] "darkseagreen4" "darkslateblue" "darkslategray"
## [109] "darkslategray1" "darkslategray2" "darkslategray3"
## [112] "darkslategray4" "darkslategrey" "darkturquoise"
## [115] "darkviolet" "deeppink" "deeppink1"
## [118] "deeppink2" "deeppink3" "deeppink4"
## [121] "deepskyblue" "deepskyblue1" "deepskyblue2"
## [124] "deepskyblue3" "deepskyblue4" "dimgray"
## [127] "dimgrey" "dodgerblue" "dodgerblue1"
## [130] "dodgerblue2" "dodgerblue3" "dodgerblue4"
## [133] "firebrick" "firebrick1" "firebrick2"
## [136] "firebrick3" "firebrick4" "floralwhite"
## [139] "forestgreen" "gainsboro" "ghostwhite"
## [142] "gold" "gold1" "gold2"
## [145] "gold3" "gold4" "goldenrod"
## [148] "goldenrod1" "goldenrod2" "goldenrod3"
## [151] "goldenrod4" "gray" "gray0"
## [154] "gray1" "gray2" "gray3"
## [157] "gray4" "gray5" "gray6"
## [160] "gray7" "gray8" "gray9"
## [163] "gray10" "gray11" "gray12"
## [166] "gray13" "gray14" "gray15"
## [169] "gray16" "gray17" "gray18"
## [172] "gray19" "gray20" "gray21"
## [175] "gray22" "gray23" "gray24"
## [178] "gray25" "gray26" "gray27"
## [181] "gray28" "gray29" "gray30"
## [184] "gray31" "gray32" "gray33"
## [187] "gray34" "gray35" "gray36"
## [190] "gray37" "gray38" "gray39"
## [193] "gray40" "gray41" "gray42"
## [196] "gray43" "gray44" "gray45"
## [199] "gray46" "gray47" "gray48"
## [202] "gray49" "gray50" "gray51"
## [205] "gray52" "gray53" "gray54"
## [208] "gray55" "gray56" "gray57"
## [211] "gray58" "gray59" "gray60"
## [214] "gray61" "gray62" "gray63"
## [217] "gray64" "gray65" "gray66"
## [220] "gray67" "gray68" "gray69"
## [223] "gray70" "gray71" "gray72"
## [226] "gray73" "gray74" "gray75"
## [229] "gray76" "gray77" "gray78"
## [232] "gray79" "gray80" "gray81"
## [235] "gray82" "gray83" "gray84"
## [238] "gray85" "gray86" "gray87"
## [241] "gray88" "gray89" "gray90"
## [244] "gray91" "gray92" "gray93"
## [247] "gray94" "gray95" "gray96"
## [250] "gray97" "gray98" "gray99"
## [253] "gray100" "green" "green1"
## [256] "green2" "green3" "green4"
## [259] "greenyellow" "grey" "grey0"
## [262] "grey1" "grey2" "grey3"
## [265] "grey4" "grey5" "grey6"
## [268] "grey7" "grey8" "grey9"
## [271] "grey10" "grey11" "grey12"
## [274] "grey13" "grey14" "grey15"
## [277] "grey16" "grey17" "grey18"
## [280] "grey19" "grey20" "grey21"
## [283] "grey22" "grey23" "grey24"
## [286] "grey25" "grey26" "grey27"
## [289] "grey28" "grey29" "grey30"
## [292] "grey31" "grey32" "grey33"
## [295] "grey34" "grey35" "grey36"
## [298] "grey37" "grey38" "grey39"
## [301] "grey40" "grey41" "grey42"
## [304] "grey43" "grey44" "grey45"
## [307] "grey46" "grey47" "grey48"
## [310] "grey49" "grey50" "grey51"
## [313] "grey52" "grey53" "grey54"
## [316] "grey55" "grey56" "grey57"
## [319] "grey58" "grey59" "grey60"
## [322] "grey61" "grey62" "grey63"
## [325] "grey64" "grey65" "grey66"
## [328] "grey67" "grey68" "grey69"
## [331] "grey70" "grey71" "grey72"
## [334] "grey73" "grey74" "grey75"
## [337] "grey76" "grey77" "grey78"
## [340] "grey79" "grey80" "grey81"
## [343] "grey82" "grey83" "grey84"
## [346] "grey85" "grey86" "grey87"
## [349] "grey88" "grey89" "grey90"
## [352] "grey91" "grey92" "grey93"
## [355] "grey94" "grey95" "grey96"
## [358] "grey97" "grey98" "grey99"
## [361] "grey100" "honeydew" "honeydew1"
## [364] "honeydew2" "honeydew3" "honeydew4"
## [367] "hotpink" "hotpink1" "hotpink2"
## [370] "hotpink3" "hotpink4" "indianred"
## [373] "indianred1" "indianred2" "indianred3"
## [376] "indianred4" "ivory" "ivory1"
## [379] "ivory2" "ivory3" "ivory4"
## [382] "khaki" "khaki1" "khaki2"
## [385] "khaki3" "khaki4" "lavender"
## [388] "lavenderblush" "lavenderblush1" "lavenderblush2"
## [391] "lavenderblush3" "lavenderblush4" "lawngreen"
## [394] "lemonchiffon" "lemonchiffon1" "lemonchiffon2"
## [397] "lemonchiffon3" "lemonchiffon4" "lightblue"
## [400] "lightblue1" "lightblue2" "lightblue3"
## [403] "lightblue4" "lightcoral" "lightcyan"
## [406] "lightcyan1" "lightcyan2" "lightcyan3"
## [409] "lightcyan4" "lightgoldenrod" "lightgoldenrod1"
## [412] "lightgoldenrod2" "lightgoldenrod3" "lightgoldenrod4"
## [415] "lightgoldenrodyellow" "lightgray" "lightgreen"
## [418] "lightgrey" "lightpink" "lightpink1"
## [421] "lightpink2" "lightpink3" "lightpink4"
## [424] "lightsalmon" "lightsalmon1" "lightsalmon2"
## [427] "lightsalmon3" "lightsalmon4" "lightseagreen"
## [430] "lightskyblue" "lightskyblue1" "lightskyblue2"
## [433] "lightskyblue3" "lightskyblue4" "lightslateblue"
## [436] "lightslategray" "lightslategrey" "lightsteelblue"
## [439] "lightsteelblue1" "lightsteelblue2" "lightsteelblue3"
## [442] "lightsteelblue4" "lightyellow" "lightyellow1"
## [445] "lightyellow2" "lightyellow3" "lightyellow4"
## [448] "limegreen" "linen" "magenta"
## [451] "magenta1" "magenta2" "magenta3"
## [454] "magenta4" "maroon" "maroon1"
## [457] "maroon2" "maroon3" "maroon4"
## [460] "mediumaquamarine" "mediumblue" "mediumorchid"
## [463] "mediumorchid1" "mediumorchid2" "mediumorchid3"
## [466] "mediumorchid4" "mediumpurple" "mediumpurple1"
## [469] "mediumpurple2" "mediumpurple3" "mediumpurple4"
## [472] "mediumseagreen" "mediumslateblue" "mediumspringgreen"
## [475] "mediumturquoise" "mediumvioletred" "midnightblue"
## [478] "mintcream" "mistyrose" "mistyrose1"
## [481] "mistyrose2" "mistyrose3" "mistyrose4"
## [484] "moccasin" "navajowhite" "navajowhite1"
## [487] "navajowhite2" "navajowhite3" "navajowhite4"
## [490] "navy" "navyblue" "oldlace"
## [493] "olivedrab" "olivedrab1" "olivedrab2"
## [496] "olivedrab3" "olivedrab4" "orange"
## [499] "orange1" "orange2" "orange3"
## [502] "orange4" "orangered" "orangered1"
## [505] "orangered2" "orangered3" "orangered4"
## [508] "orchid" "orchid1" "orchid2"
## [511] "orchid3" "orchid4" "palegoldenrod"
## [514] "palegreen" "palegreen1" "palegreen2"
## [517] "palegreen3" "palegreen4" "paleturquoise"
## [520] "paleturquoise1" "paleturquoise2" "paleturquoise3"
## [523] "paleturquoise4" "palevioletred" "palevioletred1"
## [526] "palevioletred2" "palevioletred3" "palevioletred4"
## [529] "papayawhip" "peachpuff" "peachpuff1"
## [532] "peachpuff2" "peachpuff3" "peachpuff4"
## [535] "peru" "pink" "pink1"
## [538] "pink2" "pink3" "pink4"
## [541] "plum" "plum1" "plum2"
## [544] "plum3" "plum4" "powderblue"
## [547] "purple" "purple1" "purple2"
## [550] "purple3" "purple4" "red"
## [553] "red1" "red2" "red3"
## [556] "red4" "rosybrown" "rosybrown1"
## [559] "rosybrown2" "rosybrown3" "rosybrown4"
## [562] "royalblue" "royalblue1" "royalblue2"
## [565] "royalblue3" "royalblue4" "saddlebrown"
## [568] "salmon" "salmon1" "salmon2"
## [571] "salmon3" "salmon4" "sandybrown"
## [574] "seagreen" "seagreen1" "seagreen2"
## [577] "seagreen3" "seagreen4" "seashell"
## [580] "seashell1" "seashell2" "seashell3"
## [583] "seashell4" "sienna" "sienna1"
## [586] "sienna2" "sienna3" "sienna4"
## [589] "skyblue" "skyblue1" "skyblue2"
## [592] "skyblue3" "skyblue4" "slateblue"
## [595] "slateblue1" "slateblue2" "slateblue3"
## [598] "slateblue4" "slategray" "slategray1"
## [601] "slategray2" "slategray3" "slategray4"
## [604] "slategrey" "snow" "snow1"
## [607] "snow2" "snow3" "snow4"
## [610] "springgreen" "springgreen1" "springgreen2"
## [613] "springgreen3" "springgreen4" "steelblue"
## [616] "steelblue1" "steelblue2" "steelblue3"
## [619] "steelblue4" "tan" "tan1"
## [622] "tan2" "tan3" "tan4"
## [625] "thistle" "thistle1" "thistle2"
## [628] "thistle3" "thistle4" "tomato"
## [631] "tomato1" "tomato2" "tomato3"
## [634] "tomato4" "turquoise" "turquoise1"
## [637] "turquoise2" "turquoise3" "turquoise4"
## [640] "violet" "violetred" "violetred1"
## [643] "violetred2" "violetred3" "violetred4"
## [646] "wheat" "wheat1" "wheat2"
## [649] "wheat3" "wheat4" "whitesmoke"
## [652] "yellow" "yellow1" "yellow2"
## [655] "yellow3" "yellow4" "yellowgreen"