1.Librerías
library(readr)
library(knitr)
library(kableExtra)
library(dplyr)
##
## Adjuntando el paquete: 'dplyr'
## The following object is masked from 'package:kableExtra':
##
## group_rows
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
2.Leer Datos
variables <- read_csv(
"C:/Users/WAN/Downloads/GlobalWeatherRepository.csv"
)
## Rows: 141703 Columns: 41
## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (8): country, location_name, timezone, condition_text, wind_direction,...
## dbl (30): latitude, longitude, last_updated_epoch, temperature_celsius, tem...
## dttm (1): last_updated
## time (2): sunrise, sunset
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
4. Agrupar Datos
DEFRA_agrupada <- cut(
DEFRA,
breaks = c(0, 3, 6, 9, 10),
labels = c(
"Bajo",
"Moderado",
"Alto",
"Muy Alto"
),
include.lowest = TRUE
)
5. Tabla Base
tabla_base <- table(DEFRA_agrupada)
categorias <- names(tabla_base)
6. Frecuencia absoluta
ni <- numeric(length(tabla_base))
for(i in 1:length(tabla_base)){
if(tabla_base[i] >= 0){
ni[i] <- tabla_base[i]
} else {
ni[i] <- 0
}
}
7. Frecuencia Relativa
hi <- numeric(length(ni))
for(i in 1:length(ni)){
hi[i] <- round(
(ni[i] / sum(ni)) * 100,
2
)
}
8. Tabla Final
TDF_DEFRA <- data.frame(
DEFRA = categorias,
ni = ni,
hi = hi
)
9. Fila Total
sumatoria <- data.frame(
DEFRA = "TOTAL",
ni = sum(ni),
hi = 100
)
# Agregar total
TDF_DEFRA_suma <- rbind(
TDF_DEFRA,
sumatoria
)
10. Cambiar Nombres
colnames(TDF_DEFRA_suma) <- c(
"DEFRA",
"ni",
"hi (%)"
)
11. Tabla de Frecuencias Agrupadas
kable(
TDF_DEFRA_suma,
align = "c",
caption = paste(
"Tabla N°2:",
"Distribución de frecuencia",
"del índice AQI según DEFRA"
)
) |>
kable_styling(
full_width = TRUE,
position = "center",
bootstrap_options = c(
"striped",
"hover",
"condensed",
"responsive"
)
) |>
row_spec(
0,
bold = TRUE,
color = "white",
background = "#2C3E50"
) |>
row_spec(
nrow(TDF_DEFRA_suma),
bold = TRUE,
background = "#EAEDED"
) |>
footnote(
general = paste(
"Elaborado por Grupo 2.",
"Fuente: Global Weather Repository.",
"https://www.kaggle.com/datasets/nelgiriyewithana/global-weather-repository"
),
general_title = "Nota: ",
footnote_as_chunk = TRUE,
title_format = c(
"italic",
"bold"
)
)
12.Diagrama de Barras
barplot(
ni,
names.arg = categorias,
col = c(
"green",
"yellow",
"orange",
"red"
),
main = "Gráfica N°1: Índice AQI según DEFRA",
xlab = "Categorías DEFRA",
ylab = "Frecuencia",
ylim = c(0, max(ni) + 100),
las = 1,
cex.names = 0.9
)
mtext(
"Indica la calidad de aire ",
side = 1,
line = 4,
cex = 0.8
)
13. Sector Círcular
etiquetas <- paste0(hi, "%")
colores <- c(
"green",
"yellow",
"orange",
"red"
)
pie(
hi,
labels = etiquetas,
col = colores,
main = "Gráfica N°2: Distribución porcentual AQI DEFRA"
)
legend(
"topright",
legend = categorias,
fill = colores,
title = "Categorías",
cex = 0.8
)
mtext(
"Nota: El 82.68% indica la calidad de aire buena según la escala mostrada",
side = 1,
line = 4,
cex = 0.8
)
