Removing NAs from ggplot

R code
1

Hello , please I am trying to remove NA from my ggplot, so that I have three plots instead of four. Also is there a way to remove Unknown from gender, so that my fill=gender will take only Male and Female? Thanks in anticipation

#install packages
pacman:: p_load(rio,janitor, here, tidyverse, datapasta, reprex)

# load data ---------------------------------------------------------------
line_clean<-data.frame(
  stringsAsFactors = FALSE,
  report_date = c("2020-09-17","2021-05-18",
                  "2021-01-06","2021-05-30","2020-04-08","2021-03-26",
                  "2021-03-22","2020-12-07","2020-05-22","2020-06-17",
                  "2021-01-22","2020-10-12","2020-11-08","2021-01-26",
                  "2020-08-18","2020-08-01","2021-01-07","2021-02-08",
                  "2020-06-10","2020-12-06","2021-03-27","2020-12-24",
                  "2021-05-06","2021-03-17","2021-02-07","2021-04-01",
                  "2021-01-05","2020-07-18","2020-06-20","2020-04-02",
                  "2020-08-03","2021-01-31","2020-08-16","2020-08-10",
                  "2020-12-04","2020-08-09","2020-12-18","2020-04-29","2020-11-11",
                  "2020-08-21"),
  gender = c("Male","Female","Female",
             "Male","Male","Female","Female","Female","Female",
             "Male","Female","Female","Female","Male","Male","Male",
             "Female","Female","Female","Male","Female","Female",
             "Unknown","Male","Male","Male","Female","Female",
             "Male","Female","Female","Male","Female","Male",
             "Female","Male","Male","Female","Male","Male"),
  case_race = c("BLACK","OTHER","BLACK",
                "BLACK","WHITE","WHITE","BLACK","WHITE",NA,NA,"WHITE",
                "WHITE","BLACK","WHITE","OTHER","BLACK","WHITE",
                "BLACK","BLACK","WHITE","BLACK","WHITE","OTHER",
                "WHITE","WHITE","BLACK",NA,"BLACK","WHITE","BLACK",
                "WHITE","WHITE","WHITE","WHITE",NA,"WHITE","WHITE",
                "BLACK","BLACK","BLACK")
)

clean<-line_clean %>% 
  clean_names() %>% 
  mutate(report_date=ymd(report_date))

clean %>% 
  ggplot(mapping= aes(x=report_date, fill=gender) )+
  geom_histogram()+
  scale_x_date(date_breaks = "3 months", labels = scales::label_date_short())+
  facet_wrap(~case_race)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

[image]

Created on 2024-03-07 with reprex v2.0.2

Session info
1 Like
2

Hello,

I would filter the data prior to plotting it to achieve this, please see below:

# loading packages
library(tidyverse)
library(janitor)
#> 
#> Attaching package: 'janitor'
#> The following objects are masked from 'package:stats':
#> 
#>     chisq.test, fisher.test

# creating fake data
# load data ---------------------------------------------------------------
line_clean <- data.frame(
  stringsAsFactors = FALSE,
  report_date = c(
    "2020-09-17", "2021-05-18",
    "2021-01-06", "2021-05-30", "2020-04-08", "2021-03-26",
    "2021-03-22", "2020-12-07", "2020-05-22", "2020-06-17",
    "2021-01-22", "2020-10-12", "2020-11-08", "2021-01-26",
    "2020-08-18", "2020-08-01", "2021-01-07", "2021-02-08",
    "2020-06-10", "2020-12-06", "2021-03-27", "2020-12-24",
    "2021-05-06", "2021-03-17", "2021-02-07", "2021-04-01",
    "2021-01-05", "2020-07-18", "2020-06-20", "2020-04-02",
    "2020-08-03", "2021-01-31", "2020-08-16", "2020-08-10",
    "2020-12-04", "2020-08-09", "2020-12-18", "2020-04-29", "2020-11-11",
    "2020-08-21"
  ),
  gender = c(
    "Male", "Female", "Female",
    "Male", "Male", "Female", "Female", "Female", "Female",
    "Male", "Female", "Female", "Female", "Male", "Male", "Male",
    "Female", "Female", "Female", "Male", "Female", "Female",
    "Unknown", "Male", "Male", "Male", "Female", "Female",
    "Male", "Female", "Female", "Male", "Female", "Male",
    "Female", "Male", "Male", "Female", "Male", "Male"
  ),
  case_race = c(
    "BLACK", "OTHER", "BLACK",
    "BLACK", "WHITE", "WHITE", "BLACK", "WHITE", NA, NA, "WHITE",
    "WHITE", "BLACK", "WHITE", "OTHER", "BLACK", "WHITE",
    "BLACK", "BLACK", "WHITE", "BLACK", "WHITE", "OTHER",
    "WHITE", "WHITE", "BLACK", NA, "BLACK", "WHITE", "BLACK",
    "WHITE", "WHITE", "WHITE", "WHITE", NA, "WHITE", "WHITE",
    "BLACK", "BLACK", "BLACK"
  )
)

# cleaning data
clean_data <- line_clean |>
    clean_names() |>
    mutate(report_date = ymd(report_date))

# plotting data
clean_data |>
    dplyr::filter(gender != "Unknown", !is.na(case_race)) |>
    ggplot(mapping = aes(x = report_date, fill = gender)) +
    geom_histogram() +
    scale_x_date(date_breaks = "3 months", labels = scales::label_date_short())+
    facet_wrap(~case_race)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Created on 2024-03-07 with reprex v2.1.0

Session info 
sessioninfo::session_info()
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#>  tz       America/Toronto
#>  date     2024-03-07
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#> 
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All the best,

Tim