GYY <- ggplot(GY, aes(x=Fecha, y=Activos)) + 
       geom_line(size=1, colour="darkblue")+theme_economist()+ 
theme(legend.position  = 'none',
      legend.direction = 'horizontal',
      legend.title     = element_blank()) + ylab('En millones USD')

GYY <- GYY + scale_x_date(date_labels = '%Y%-%b',
                          breaks = as.Date(c('2022-03-01',
                                             '2022-06-01',
                                             '2022-09-01',
                                             '2022-12-01',
                                             '2023-03-01',
                                             '2023-06-01',
                                             '2023-09-01',
                                             '2023-12-01')))

fig <- ggplotly(GYY)
fig

#https://plotly.com/ggplot2/line-charts/
#https://www.musgraveanalytics.com/blog/2018/8/24/how-to-make-ggplot2-charts-interactive-with-plotly

data_II <- melt(data_A, id="Fecha", value.name = "Exportaciones", variable.name = "Países")  

p <- ggplot(data=data_II,
           aes(x=Fecha, y=Exportaciones, colour=Países)) +
     geom_line()+scale_color_manual(values = c("#0b5394", "firebrick4"))+
     theme(legend.position  = 'bottom',
           legend.title     = element_blank(),
           axis.line        = element_line(size=1, colour = "black"),
           panel.grid.minor = element_blank(),
           panel.border     = element_blank(), 
           panel.background = element_blank(),
           text             = element_text(family="mono"),
           axis.text.x      = element_text(colour="black", size = 14),
           axis.text.y      = element_text(colour="black", size = 14),
           axis.title       = element_text(size = 15))+
    scale_y_continuous(labels=dollar_format(prefix="$",suffix=" M"))

ggplotly(p)

pa <- ggplot(data=data_II,
           aes(x=Fecha, y=Exportaciones)) +
      geom_line(colour="#f4975f")+theme_stata() +ggtitle("Asiáticos")
pa <- pa + facet_wrap(~Países, scales = "free_y")


fig <- ggplotly(pa)
fig

hchart(Mundial, type = "line", hcaes(x = Fecha, y = Importaciones, group = Países))

# https://jkunst.com/blog/posts/2020-05-22-30diasdegraficos-parte-2/
#http://jkunst.com/LatinR-2019-Highcharter-taller/slides/#6
#http://jkunst.com/LatinR-2019-Highcharter-taller/slides/#3

Tipo_colores <- c("#203764", "#548235")
Tipo_linea   <- c("Solid", "ShortDashDotDot")

H1 <-  hchart(Mundial, type = "line", hcaes(x = Fecha, y = Importaciones, group = Países),
              color = Tipo_colores,dashStyle = Tipo_linea)%>%
       hc_title(text = "Importaciones Ecuador vs Italia") 

H1

# https://jkunst.com/blog/posts/2020-05-22-30diasdegraficos-parte-2/
#http://jkunst.com/LatinR-2019-Highcharter-taller/slides/#6
#http://jkunst.com/LatinR-2019-Highcharter-taller/slides/#3
#https://jkunst.com/blog/posts/2020-05-22-30diasdegraficos-parte-2/

H3 <-  hchart(Mundial, type = "line", hcaes(x = Fecha, y = Importaciones, 
                                            group = Países))%>%
       hc_title(text = "Importaciones Ecuador vs Italia") %>% 
       hc_add_theme(hc_theme_economist())

H3

library(forecast)
library(sweep)
library(timetk)

Mundial_EC <- Mundial %>% dplyr::filter(Países== "Ecuador")
BA_ts <- tk_ts(Mundial_EC, start = 2022, freq = 12, silent = TRUE)

pronosticos <- forecast(auto.arima(BA_ts), h = 6, level = 95)

H4 <- hchart(pronosticos) %>% 
  hc_title(
    text = "Pronóstico Importaciones aplicando libreria forecast"
  ) %>% 
  hc_tooltip(shared = TRUE, valueDecimals = 2)

H4

# First ensure your locale is set to Spanish
#Sys.setlocale("LC_TIME", "es_ES.UTF-8")  # Linux/Mac
Sys.setlocale("LC_TIME", "Spanish")    # Windows

AD <- highchart() %>%
  hc_xAxis(
    categories = format(America$Fecha, "%b-%Y"),  # Format dates directly
    title = list(text = "Fecha"),
    labels = list(style = list(fontSize = "10px"))
  ) %>%
  hc_yAxis(
    title = list(text = "Exportaciones", style = list(fontSize = "12px")),
    gridLineWidth = 0
  ) %>%
  hc_add_series(
    name = "Cobra",
    data = America$Cobra,
    type = "line",
    color = "#1E90FF"
  ) %>%
  hc_add_series(
    name = "Python",
    data = America$Python,
    type = "line",
    color = "#990000"
  ) %>%
  hc_title(text = "Evolución Mensual - 2022-2024") %>%
  hc_tooltip(
    shared = TRUE,
    crosshairs = TRUE,
    pointFormat = "<span style='color:{point.color}'>\u25CF</span> {series.name}: <b>{point.y}</b><br/>"
  ) %>%
  hc_legend(align = "center", verticalAlign = "bottom")

AD

load("D:/Documentos/Estadisticos/R/R_studio/Plotly/File_One.RData")

B1 <- hchart(jjj, type = 'column', hcaes(x = factor(fecha), y = Exportaciones, 
                                         group = Continente),
             dataLabels=list(enabled=TRUE, format='{point.Exportaciones}')) %>%
      hc_xAxis(
          title = list(text = "Fecha")
          )%>%
      hc_add_theme(hc_theme_ft())

B1

B2 <- Blades %>% 
      hchart('column', hcaes(x = 'Años', y = 'Composicion', group = 'CUENTA'),
                             stacking = "normal") %>%
      hc_colors(c('#99C945','#CC61B0','#52BCA3'))

B2

# https://stackoverflow.com/questions/54651243/r-highcharts-multiple-stacked-bar-chart

#https://blogs.sap.com/2019/09/19/top-bottom-analysis-using-r-visualizations-part-2/

#https://www.tmbish.me/lab/highcharter-cookbook/

highchart() %>% 
  hc_chart(type = "column") %>%
  hc_plotOptions(column = list(stacking = "normal"),
                 series = list(boderWidth = 0,
             dataLabels = list(enabled = TRUE))) %>%
  hc_xAxis(categories = Blades_A$Años) %>%
  hc_add_series(name="Inversiones",
                data = Blades_A$Inversiones,
                stack = "Activos")%>% 
  hc_add_series(name="Fondos Disponible",
                data = Blades_A$`Fondos Disponibles`,
                stack = "Activos") %>%
  hc_add_series(name="Cartera de Créditos",
                data = Blades_A$`Cartera de créditos`,
                stack = "Activos")%>%
  hc_yAxis(min=0,max=100)%>%
  hc_add_theme(hc_theme_elementary())

seg1_name = "Masculino"
seg2_name = "Femenino"
color1 = "#830808"
color2 = "#0b467b"

title_caption = "Inscritos en la Facultad de Economía 2022"

highchart() %>% 
  hc_chart(type = "column") %>% 
  hc_title(text = title_caption, 
           margin = 20, align = "center",
           style = list(color = "black", fontWeight = "bold")) %>% 
  hc_plotOptions(column = list(stacking = "normal", 
                 dataLabels = list(enabled = TRUE))) %>%
  hc_legend(align = "left", layout = "vertical", verticalAlign = "top", 
            x=0, y= 250, symbolRadius = 0 ) %>%
  hc_xAxis(categories = df$Departamento, 
           tickLength = 0, lineWidth = 3, lineColor = "black",
           labels = list(style = list(fontSize = "14px", fontWeight = "bold"))) %>%
  hc_yAxis(title = list(text = "Número de inscritos"),
           stackLabels = list(color = "black", fontWeight = "bold", enabled = TRUE)) %>%
  hc_tooltip(enabled = FALSE) %>%
  hc_add_series(name=seg1_name, data = df$Masculino, color = color1) %>%
  hc_add_series(name=seg2_name, data = df$Femenino,  color = color2)

box_stats <- boxplot.stats(ACP$Viaje)$stats

as <- highchart() %>%
  hc_chart(type = "boxplot") %>%
  hc_add_series(
    name = "Mis Datos",
    data = list(box_stats),  # Wrap stats in list
    color = "#0033CC"
  ) %>%
  hc_title(text = "Boxplot simple") %>%
  hc_yAxis(title = list(text = "Valores")) %>%
  hc_xAxis(title = list(text = ""))

as

asl <- highchart() %>%
        hc_chart(type = "boxplot") %>%
        hc_add_series(
          name = "Mis Datos",
          data = list(box_stats),  # Wrap stats in list
          color = "blue",  # Border color
          fillColor = "lightblue",  # Fill color inside the box
          medianColor = "red"  # Median line color
        ) %>%
        hc_plotOptions(
          boxplot = list(
            fillColor = "lightblue",  # Adds color inside the box
            medianColor = "red",  # Changes median line color
            color = "blue"  # Border color of the box
          )
        ) %>%
        hc_title(text = "Boxplot personalizado") %>%
        hc_yAxis(title = list(text = "Valores")) %>%
        hc_xAxis(title = list(text = ""))

asl