CODEWITHSUNDEEP
rggplot2
cdcarrion
cdcarrion

Reputation: 590

pretty breaks on secondary axis (negative values doesn't show)

I'm trying to do this plot (1st plot) but it doesn't show the negatives percentages on the secondary axis using pretty_breaks() inside scale_y_continuous and sec_axis.

scale_y_continuous(sec.axis=sec_axis(breaks = pretty_breaks(), labels = label_percent()), breaks = pretty_breaks(), labels = label_dollar()).

enter image description here

And I need to show like this.

enter image description here

minimal example

library(dplyr)
library(tidyr)
library(ggplot2)
library(scales)

test = structure(list(Año = c(2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
                              2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2019L, 2019L, 2019L, 
                              2019L, 2019L, 2019L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L
), Vars = c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements", "Oil.GAV.%", 
            "Non-Oil.GAV.%", "Other.GDP.elements.%", "Oil.GAV", "Non-Oil.GAV", 
            "Other.GDP.elements", "Oil.GAV.%", "Non-Oil.GAV.%", "Other.GDP.elements.%", 
            "Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements", "Oil.GAV.%", 
            "Non-Oil.GAV.%", "Other.GDP.elements.%", "Oil.GAV", "Non-Oil.GAV", 
            "Other.GDP.elements", "Oil.GAV.%", "Non-Oil.GAV.%", "Other.GDP.elements.%"
), value = c(5639977, 91442756, 7213129, 0.0987732330025509, 
             0.869107003693333, 0.0321197633041161, 6918891, 93037062, 7606055, 
             0.0913116709595953, 0.875434164471086, 0.0332541645693185, 6519993, 
             94351584, 7236432, 0.0923079337383433, 0.876825035531481, 0.0308670307301762, 
             4951333, 88365192, 5491485, -0.06, -0.35, -0.078)), row.names = c(NA, 
                                                                               -24L), class = c("tbl_df", "tbl", "data.frame"))


scaleFactor_t <- max(test %>% 
                     filter(Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")) %>% 
                     select(value)) / max(test %>% 
                                            filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")) %>% 
                                            select(value))

ggplot() +
  geom_col(data = test %>% 
             filter(Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
           aes(x = Año, y = value , fill = Vars))+
  geom_line(data = test %>% 
              filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
            aes(x = Año, y = value*scaleFactor_t, colour = Vars), size = 1)+
  geom_point(data = test %>% 
               filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
             aes(x = Año, y = value*scaleFactor_t, colour = Vars), size = 2)+
  scale_y_continuous(name="Miles de dólares", 
                     sec.axis=sec_axis(~./scaleFactor_t, name="Kcal per day", breaks =scales::pretty_breaks(), labels = scales::label_percent()), 
                     breaks =scales::pretty_breaks(), labels = scales::label_dollar())

Upvotes: 1

Views: 282

Answers (1)

Quinten
Quinten

Reputation: 41285

You could say the number of breaks like this pretty_breaks(6). Here is a reproducible example:

library(dplyr)
library(tidyr)
library(ggplot2)
library(scales)

test = structure(list(Año = c(2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
                              2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2019L, 2019L, 2019L, 
                              2019L, 2019L, 2019L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L
), Vars = c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements", "Oil.GAV.%", 
            "Non-Oil.GAV.%", "Other.GDP.elements.%", "Oil.GAV", "Non-Oil.GAV", 
            "Other.GDP.elements", "Oil.GAV.%", "Non-Oil.GAV.%", "Other.GDP.elements.%", 
            "Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements", "Oil.GAV.%", 
            "Non-Oil.GAV.%", "Other.GDP.elements.%", "Oil.GAV", "Non-Oil.GAV", 
            "Other.GDP.elements", "Oil.GAV.%", "Non-Oil.GAV.%", "Other.GDP.elements.%"
), value = c(5639977, 91442756, 7213129, 0.0987732330025509, 
             0.869107003693333, 0.0321197633041161, 6918891, 93037062, 7606055, 
             0.0913116709595953, 0.875434164471086, 0.0332541645693185, 6519993, 
             94351584, 7236432, 0.0923079337383433, 0.876825035531481, 0.0308670307301762, 
             4951333, 88365192, 5491485, -0.06, -0.35, -0.078)), row.names = c(NA, 
                                                                               -24L), class = c("tbl_df", "tbl", "data.frame"))


scaleFactor_t <- max(test %>% 
                       filter(Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")) %>% 
                       select(value)) / max(test %>% 
                                              filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")) %>% 
                                              select(value))

ggplot() +
  geom_col(data = test %>% 
             filter(Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
           aes(x = Año, y = value , fill = Vars))+
  geom_line(data = test %>% 
              filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
            aes(x = Año, y = value*scaleFactor_t, colour = Vars), size = 1)+
  geom_point(data = test %>% 
               filter(!Vars %in% c("Oil.GAV", "Non-Oil.GAV", "Other.GDP.elements")),
             aes(x = Año, y = value*scaleFactor_t, colour = Vars), size = 2)+
  scale_y_continuous(name="Miles de dólares", 
                     sec.axis=sec_axis(~./scaleFactor_t, name="Kcal per day", breaks =scales::pretty_breaks(6), labels = scales::label_percent()), 
                     breaks =scales::pretty_breaks(), labels = scales::label_dollar())

Created on 2022-09-11 with reprex v2.0.2

Upvotes: 2

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