Colors assignation in geom_point with conditions

Question

I have the following peace of code:

ggplot(data = afirmaciones[afirmaciones$prueba==x,
                                     ], 
                 aes(x = 1, 
                     y = Afirmacion_d)) +
    geom_point(size = 20, 
               stroke = 5,
               aes(color = porcentaje),
               show.legend = F) + facet_wrap(~agregacion) +
    geom_text(aes(label = porcentaje),
              color = "white",
              size = 8) +
    theme(
      panel.background = element_rect(color = "#575756",
                                      size = 1.1,
                                      linetype = "solid",
                                      fill = "white"),
      panel.grid.major.y = element_line(size = 0.1,
                                        linetype = "dotted",
                                        color = "#575756"),
      axis.title = element_blank(),
      axis.text.x = element_blank(),
      strip.background = element_rect(fill = "white"),
      strip.text = element_text(colour = "#575756",
                                size = 20),
      axis.text.y = element_text(color = "#575756",
                                 size = 22)
    )

Which returns the following plot:

I would like to color each one of the bubbles according to the number of the variable "porcentaje". However I have some specific colors in mind I would like to bubbles to be colored if the variable "porcentaje" falls into a specific interval. The first thing It came to me was to generate a variable "colores" which has the color if the var follows into the variable and then add it using scale_color_manual(values = afirmaciones[afirmaciones$prueba==x, "colores"]) at the end, but it does not work. The conditions for each color are given by:

afirmaciones$colores <- NA
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje < 20,"colores"] <-  "#74ad68"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 20 &
               afirmaciones$porcentaje < 40,"colores"] <-  "#e0e165"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 40 &
               afirmaciones$porcentaje < 70,"colores"] <-  "#de9452"
afirmaciones[afirmaciones$agregacion=="Nacional" |
               afirmaciones$porcentaje > 70,"colores"] <-  "#cb4c43"

afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje < 20,"colores"] <-  "#74ad68"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 20 &
               afirmaciones$porcentaje < 40,"colores"] <-  "#e0e165"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 40 &
               afirmaciones$porcentaje < 70,"colores"] <-  "#de9452"
afirmaciones[afirmaciones$agregacion=="SENA" |
               afirmaciones$porcentaje > 70,"colores"] <-  "#cb4c43"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje<=-5,"colores"] <- "#74ad68"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>-5 &
               afirmaciones$porcentaje<=-0.1,"colores"] <- "#e0e165"

afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>-0.1 &
               afirmaciones$porcentaje<=4.9,"colores"] <- "#de9452"
afirmaciones[afirmaciones$agregacion=="Diferencia" &
               afirmaciones$porcentaje>5,"colores"] <- "#cb4c43"

The resulting plot by doing this is:

But the colors are just wrong assigned in this plot. Does anyone know how I can solve this?

My data can be replicated by:

structure(list(agregacion = structure(c(2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
2L, 1L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L), .Label = c("SENA", "Nacional", "Diferencia"), class = "factor"), 
    Afirmacion_d = structure(c(12L, 12L, 11L, 11L, 10L, 10L, 
    9L, 9L, 8L, 8L, 7L, 7L, 6L, 6L, 12L, 12L, 3L, 3L, 2L, 2L, 
    1L, 1L, 11L, 11L, 10L, 10L, 9L, 9L, 8L, 8L, 7L, 7L, 6L, 6L, 
    5L, 5L, 4L, 4L, 12L, 12L, 11L, 11L, 10L, 10L, 12L, 12L, 11L, 
    11L, 12L, 12L, 11L, 11L, 12L, 12L, 11L, 11L, 10L, 10L, 12L, 
    11L, 10L, 9L, 8L, 7L, 6L, 12L, 3L, 2L, 1L, 11L, 10L, 9L, 
    8L, 7L, 6L, 5L, 4L, 12L, 11L, 10L, 12L, 11L, 12L, 11L, 12L, 
    11L, 10L), .Label = c("Afirmación 12", "Afirmación 11", "Afirmación 10", 
    "Afirmación 9", "Afirmación 8", "Afirmación 7", "Afirmación 6", 
    "Afirmación 5", "Afirmación 4", "Afirmación 3", "Afirmación 2", 
    "Afirmación 1"), class = "factor"), prueba = c("competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "lectura", "lectura", "lectura", "lectura", 
    "lectura", "lectura", "mantenimiento", "mantenimiento", "mantenimiento", 
    "mantenimiento", "promoción", "promoción", "promoción", "promoción", 
    "razonamiento", "razonamiento", "razonamiento", "razonamiento", 
    "razonamiento", "razonamiento", "competencias", "competencias", 
    "competencias", "competencias", "competencias", "competencias", 
    "competencias", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", 
    "ensamblaje", "ensamblaje", "ensamblaje", "ensamblaje", "lectura", 
    "lectura", "lectura", "mantenimiento", "mantenimiento", "promoción", 
    "promoción", "razonamiento", "razonamiento", "razonamiento"
    ), porcentaje = c("51", "53", "51", "52", "61", "62", "57", 
    "58", "47", "49", "55", "56", "48", "49", "61", "61", "49", 
    "50", "47", "48", "60", "60", "64", "65", "50", "50", "55", 
    "55", "61", "62", "41", "42", "38", "39", "36", "36", "50", 
    "50", "53", "54", "43", "43", "53", "54", "54", "55", "49", 
    "50", "50", "51", "45", "44", "48", "49", "63", "64", "57", 
    "57", "2", "1", "1", "1", "2", "1", "1", "0", "1", "1", "0", 
    "1", "0", "0", "1", "1", "1", "0", "0", "1", "0", "1", "1", 
    "1", "1", "-1", "1", "1", "0"), colores = c("#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#e0e165", "#cb4c43", "#e0e165", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#cb4c43", "#de9452", "#cb4c43", 
    "#de9452", "#cb4c43", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", "#de9452", 
    "#de9452", "#de9452", "#de9452", "#e0e165", "#de9452", "#de9452", 
    "#de9452")), row.names = c("56772", "76081", "56752", "76086", 
"56771", "76085", "56781", "76080", "56775", "76083", "56753", 
"76084", "59239", "76082", "59235", "76108", "59236", "76107", 
"56776", "76103", "56754", "76099", "56749", "76104", "59238", 
"76100", "56764", "76106", "59240", "76102", "56763", "76098", 
"56755", "76105", "56760", "76101", "59237", "76097", "56777", 
"76088", "56773", "76089", "56761", "76087", "56750", "76095", 
"56765", "76096", "56779", "76093", "56778", "76094", "56757", 
"76090", "56756", "76091", "56766", "76092", "760811", "760861", 
"760851", "760801", "760831", "760841", "760821", "761081", "761071", 
"761031", "760991", "761041", "761001", "761061", "761021", "760981", 
"761051", "761011", "760971", "760881", "760891", "760871", "760951", 
"760961", "760931", "760941", "760901", "760911", "760921"), class = "data.frame")

Kind regards.

Answer 1

It's a bit hacky, but I think this is what you were looking for (using the case where prueba == "ensamblaje":

pal <- c("#74ad68", "#e0e165", "#de9452", "#cb4c43")
afirmaciones$grp <- dplyr::case_when(
    afirmaciones$porcentaje < 20 ~ "#74ad68",
    afirmaciones$porcentaje > 20 & afirmaciones$porcentaje < 40 ~ "#e0e165",
    afirmaciones$porcentaje > 40 & afirmaciones$porcentaje < 70 ~ "#de9452",
    TRUE ~ "#cb4c43"
)

ggplot(data = afirmaciones[afirmaciones$prueba=="ensamblaje",
                           ], 
       aes(x = 1, 
           y = Afirmacion_d)) +
    geom_point(size = 20, 
               stroke = 5,
               aes(color = grp),
               show.legend = F) + facet_wrap(~agregacion) +
    scale_color_manual(values = pal, limits = pal) +
    geom_text(aes(label = porcentaje),
              color = "white",
              size = 8) +
    theme(
        panel.background = element_rect(color = "#575756",
                                        size = 1.1,
                                        linetype = "solid",
                                        fill = "white"),
        panel.grid.major.y = element_line(size = 0.1,
                                          linetype = "dotted",
                                          color = "#575756"),
        axis.title = element_blank(),
        axis.text.x = element_blank(),
        strip.background = element_rect(fill = "white"),
        strip.text = element_text(colour = "#575756",
                                  size = 20),
        axis.text.y = element_text(color = "#575756",
                                   size = 22)
    )

(the circles will look more like how you want with a more appropriate level of zoom / better plot size)