I am able to define breaks for continous y axis, however applying the code for a discrete y axis is not working. I cannot seem to get the right script . I tried the epi handbook
The y axis shows percentages as discrete variables 1-15%, the y axis is plotted with 1% breaks, where I want to have it with 5% breaks.
the graph is geom_point
kim
Hi Kim,
It would help if you could provide a reproducible example (reprex), or even the code you have been using so far, so that we can help diagnose the problem.
All the best,
Tim
the code is
summ_EV_prop_season$Positive ← factor(summ_EV_prop_season$Positive, levels=c(‘1%’, ‘2%’, ‘3%’,‘4%’, ‘5%’, ‘6%’,‘7%’, ‘8%’, ‘9%’,‘10%’, ‘11%’, ‘12%’,‘13%’, ‘14%’, ‘15%’,‘16%’, ‘17%’, ‘18%’,‘19%’))
summ_EV_prop_season %>%
filter(!(sample_month == "nd")) %>%
ggplot(mapping = aes(x = sample_month,
y= Positive))+
geom_point(size = 3, color = "black")+
scale_y_discrete(position = "right") +
labs(title = "Enterovirus testing",
subtitle = "all samples",
x= "years",
y= "positive %")+
theme(axis.text.x=element_text(angle=45, hjust=0.9, color = "red"),
axis.ticks.y = element_line(color = "red"),
axis.title.y = element_text(color = "red"),
axis.line.y = element_line(color = "red"),
axis.text.y = element_text(color = "red"),
axis.ticks.x = element_line(color = "red"),
axis.title.x = element_text(color = "red"),
axis.line.x = element_line(color = "red"),
)+
facet_wrap(~ year)
this is the data for 2015 in the dataframe
Hi Kim,
This is how I would approach the problem, you should be using a continuous scale for numeric variables, such as proportions or percentages.
# loading packages
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(ggplot2)
library(tibble)
# creating fake data
fake_data <- tibble(year = 2015L, sample_month = c(paste(as.character(1L:12L), month.abb, sep = " "), "nd")) |>
rowwise() |>
mutate(
count = rpois(n = 1, lambda = 1000),
positive = rbinom(n = 1, size = count, prob = 0.1) / count
) |>
ungroup()
# plotting data
fake_data |>
ggplot() +
geom_point(aes(x = sample_month, y = positive)) +
scale_x_discrete(limits = c(paste(as.character(1L:12L), month.abb, sep = " "), "nd")) +
scale_y_continuous(breaks = scales::extended_breaks(),
labels = scales::percent_format()) +
labs(x = "\nSample month", y = "Percentage of samples positive\n") +
theme_minimal()
Created on 2024-12-13 with reprex v2.1.1
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All the best,
Tim