1 Introduction
This HTML document is a continuation of descriptive graphics about
violent deaths during the Covid outbreak in 2021. You will find plots of
rates per 100.000 population and number of homicides. in ggplot2 and
Plotly libraries. The source of the data was the “Instituto Nacional de
Medicina Legal y Ciencias Forenses” from Colombia.
2 Load packages and the database
remove(list = ls())
library(tidyverse)
library(googlesheets4)
library(ggplot2)
library(scales)
library(stringr)
library(gridExtra)
library(plotly)
This data was loaded to Google Drive and with the library \(googlesheets4\) it is possible to obtain
those data-frames into the R programming language.
3 Homicides in Colombia
The next barplot shows the total homicides in Colombia:
bar_plot(df_1, total,
titulo = "Number of homicides in Colombia by age \n 2021")
The most affected group were young people between 20 and 29 years old. Also, the next group was located in 30-34. Overall, the homicides were mostly between 20 and 34.
3.1 Homicides by gender in Colombia
grid.arrange(bar_plot(df_1, women,
titulo = "Number of homicides of women by age \n 2021"),
bar_plot(df_1, men,
titulo = "Number of homicides of men by age \n 2021"),
ncol = 2)
More men were killed than women in each age group. However, to make a better comparison it will be necessary calculate rates per 100.000 population.
3.2 Per 100.000 population rates for homicides in Colombia
This interactive barplot has rates per 100000 population. Again, you may notice that suicide rates are higher for men in almost all age groups. Actually, men are overrated in homicides.