pacman::p_load(rio, dplyr, lubridate, readxl, stringr, table1)
suicidio <- read_excel("C:/Users/User/Downloads/YDRAY-2024_356_Reporte.xlsx") ## Warning: Expecting numeric in BT1133 / R1133C72: got 'INSTITUCIONA'require(table1)
table1(~sexo_+edad_+estrato_+estado_civ, data=suicidio)| Overall (N=1325) |
|
|---|---|
| sexo_ | |
| F | 858 (64.8%) |
| M | 467 (35.2%) |
| edad_ | |
| Mean (SD) | 25.8 (12.6) |
| Median [Min, Max] | 22.0 [8.00, 90.0] |
| estrato_ | |
| Mean (SD) | 2.19 (0.997) |
| Median [Min, Max] | 2.00 [1.00, 6.00] |
| Missing | 57 (4.3%) |
| estado_civ | |
| Mean (SD) | 1.51 (0.940) |
| Median [Min, Max] | 1.00 [1.00, 5.00] |
# voy a ajustar la variable estrato y la variable estado civil por q las esta tomando como número
suicidio$estrato_=as.factor(suicidio$estrato_)
#ajusto la variable estado civil
suicidio$estado_civ=factor(suicidio$estado_civ, levels = c(1, 2, 3, 4, 5), labels = c("soltero", "casado", "unión libre", "viudo", "divorciado"))
#Ajustar escolaridad
suicidio$escolarid2 = factor(suicidio$escolarid, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14), labels = c("preescolar","jardin", "primaria", "secundaria", "técnica", "tecnólogo", "profesional","profesional2", "especialista", "magister", "PhD", "ninguno", "otro", "sin información"))
require(table1)
table1(~sexo_+edad_+estrato_+estado_civ+escolarid2, data=suicidio)| Overall (N=1325) |
|
|---|---|
| sexo_ | |
| F | 858 (64.8%) |
| M | 467 (35.2%) |
| edad_ | |
| Mean (SD) | 25.8 (12.6) |
| Median [Min, Max] | 22.0 [8.00, 90.0] |
| estrato_ | |
| 1 | 282 (21.3%) |
| 2 | 636 (48.0%) |
| 3 | 240 (18.1%) |
| 4 | 61 (4.6%) |
| 5 | 35 (2.6%) |
| 6 | 14 (1.1%) |
| Missing | 57 (4.3%) |
| estado_civ | |
| soltero | 978 (73.8%) |
| casado | 84 (6.3%) |
| unión libre | 224 (16.9%) |
| viudo | 13 (1.0%) |
| divorciado | 26 (2.0%) |
| escolarid2 | |
| preescolar | 14 (1.1%) |
| jardin | 278 (21.0%) |
| primaria | 653 (49.3%) |
| secundaria | 0 (0%) |
| técnica | 70 (5.3%) |
| tecnólogo | 0 (0%) |
| profesional | 64 (4.8%) |
| profesional2 | 38 (2.9%) |
| especialista | 85 (6.4%) |
| magister | 6 (0.5%) |
| PhD | 2 (0.2%) |
| ninguno | 2 (0.2%) |
| otro | 8 (0.6%) |
| sin información | 105 (7.9%) |
##A continuación se realizará una exploración de los casos reportados diariamente
require (ggplot2)## Cargando paquete requerido: ggplot2suicidio$fecha= as.Date(suicidio$fec_not, format = "%d/%m/%y")
fig1= ggplot(suicidio, aes(x=fecha))+geom_bar(fill="blue")+ theme_classic()
require(plotly)## Cargando paquete requerido: plotly##
## Adjuntando el paquete: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:rio':
##
## export## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutggplotly(fig1)