Combined line plot for proportions

[Nile]

Hi,
I am trying to make a line plot that shows the overall proportion of srh scores >1, and that for male and female sex separately as well. So, there will be three lines for each year point, overall, male, and female. I could make the plot for overall and for the two sexes, but I am not being able to combine them in the same plot.
I'd greatly appreciate if you could give me an idea about it. Below are the data and the codes:

ff %>% select(srh, year, sex)%>% filter(!is.na(srh)) %>% 
    filter(!is.na(sex)) %>% 
    group_by(year) %>%   # Group by year only
    summarize(prop_srh = sum(srh > 1, na.rm = TRUE) / n()) %>% 
    ggplot(aes(x = year, y = (prop_srh * 100)/100)) +
    geom_line(color = "black") 

   srh year sex
1    3 2017   2
2    2 2018   2
3    2 2018   2
4    3 2018   1
5    1 2017   2
6    3 2019   1
7    2 2022   1
8    2 2018   2
9    2 2018   1
10   3 2017   2
11   2 2018   1
12   3 2018   2
13   3 2020   2
14   3 2018   2
15   2 2020   2

[williaml]

Is this what you're after? I have created a sample dataset.

library(tidyverse)

# sample data
ff <- tibble(srh = sample(1:3, 15, replace = TRUE),
             year = sample(2017:2020, 15, replace = TRUE),
             sex = sample(1:2, 15, replace = TRUE)) %>% 
  mutate(sex = factor(sex))

ff %>% 
  select(srh, year, sex) %>% 
  filter(!is.na(srh),
         !is.na(sex)) %>% 
  group_by(year, sex) %>%   
  summarise(prop_srh = sum(srh > 1, na.rm = TRUE) / n()) %>% 
  ggplot(aes(x = year, y = (prop_srh * 100)/100, colour = sex)) +
  geom_line() 

Next time, please provide a reproducible example, e.g. for ff .

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[Nile]

Hi williaml,

Thanks so much for the detailed response. The chart is almost ok, I just want to add another line for the overall/combined trend of srh to understand who is better off between men and women. Please let know if you have any ideas about this.

Thanks!

[williaml]

How about something like this?

library(tidyverse)

# sample data
ff <- tibble(srh = sample(1:3, 15, replace = TRUE),
             year = sample(2017:2020, 15, replace = TRUE),
             sex = sample(1:2, 15, replace = TRUE)) %>% 
  mutate(sex = factor(sex)) %>%
  # assuming that there are more columns in your original data and that there are NAs
  select(srh, year, sex) %>% 
  filter(!is.na(srh),
         !is.na(sex)) 

# by sex
ff1 <- ff %>% 
  group_by(year, sex) %>%   
  summarise(prop_srh = sum(srh > 1, na.rm = TRUE) / n())

# total
ff2 <- ff %>% 
  group_by(year) %>%   
  summarise(prop_srh = sum(srh > 1, na.rm = TRUE) / n()) %>% 
  mutate(sex = "Total")

# combined
ff3 <- bind_rows(ff1, ff2)

# the graph
ggplot(ff3, aes(x = year, y = (prop_srh * 100)/100, colour = sex)) +
  geom_line()