# Cargar librerías necesarias
library(ggplot2)
library(readr)
library(dplyr)

## 
## Adjuntando el paquete: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(scales)

## 
## Adjuntando el paquete: 'scales'

## The following object is masked from 'package:readr':
## 
##     col_factor

# Leer el archivo
data <- read_table("Water_Area_TimeSeries_Procs.txt", 
                   col_names = c("Year", "Month", "Day", "Area_ha"))

## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   Year = col_double(),
##   Month = col_character(),
##   Day = col_character(),
##   Area_ha = col_double()
## )

# Crear columna de fecha
data <- data %>%
  mutate(Date = as.Date(paste(Year, Month, Day, sep = "-")))

# Graficar como barras con formato científico
ggplot(data, aes(x = Date, y = Area_ha)) +
  geom_bar(stat = "identity", fill = "steelblue") +
  scale_y_continuous(labels = scientific_format(digits = 3)) +
  labs(
    title = "Evolución temporal del área cubierta por agua",
    x = "Fecha",
    y = expression("Área (ha)")
  ) +
  theme_minimal(base_size = 14)