Remove blank categories from a dynamic bar plot

[cerutt]

I've written a function to create a plot with data that changes based on a filter input, below is a simplified reprex:

            library(tidyverse)                                               
               library(plotly)
one<- as.numeric(NA)
two<- 25
three<- 35
four<- 40
five<- 0
dat<- data.frame(one, two, three, four, five)

  get_plot <- function(x, a){
    data<- x[, a]                       
    p<- data %>%  
        pivot_longer(everything(), names_to="variable", values_to="value") %>%
        ggplot(aes(x = reorder(variable, value), y = value, fill = variable, text = paste0(value*100, "%"))) +
        geom_bar(stat = "identity",position = "dodge")+
        theme(axis.title.x=element_blank(),
              axis.text.x=element_blank(),
              axis.ticks.x=element_blank(),
              axis.title.y=element_blank(),
              legend.position = "none")+
              coord_flip()
    ggplotly(p, tooltip = c("text")) %>% config(displaylogo = FALSE,
                                                modeBarButtons = list(list("toImage")))
  }
  
get_plot(dat, a= c(1:5))

Depending on the filter sometimes I end up with a chart with categories that don't have values in them because the filtered data frame I feed the function ends up looking like dat from my reprex. How do I exclude categories from appearing on the plot when the value is 0 or NA?

[Yarnabrina]

Welcome to the community!

I don't see a filter step in your code. So just based on general assumptions, you can use droplevels function.

See this example:

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

iris %>%
    filter(Species != "setosa") %>%
    str()
#> 'data.frame':    100 obs. of  5 variables:
#>  $ Sepal.Length: num  7 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 ...
#>  $ Sepal.Width : num  3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 ...
#>  $ Petal.Length: num  4.7 4.5 4.9 4 4.6 4.5 4.7 3.3 4.6 3.9 ...
#>  $ Petal.Width : num  1.4 1.5 1.5 1.3 1.5 1.3 1.6 1 1.3 1.4 ...
#>  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 2 2 2 2 2 2 2 2 2 2 ...

iris %>%
    filter(Species != "setosa") %>%
    droplevels() %>%
    str()
#> 'data.frame':    100 obs. of  5 variables:
#>  $ Sepal.Length: num  7 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 ...
#>  $ Sepal.Width : num  3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 ...
#>  $ Petal.Length: num  4.7 4.5 4.9 4 4.6 4.5 4.7 3.3 4.6 3.9 ...
#>  $ Petal.Width : num  1.4 1.5 1.5 1.3 1.5 1.3 1.6 1 1.3 1.4 ...
#>  $ Species     : Factor w/ 2 levels "versicolor","virginica": 1 1 1 1 1 1 1 1 1 1 ...

^{Created on 2021-04-01 by the reprex package (v1.0.0)}

Hope this helps.

[cerutt]

Thank you for the welcome. First post! long time reader. I didn't include the filter step to make the reprex more simplified because the whole thing is actually part of a bigger shiny renderPlotly function. The filter happens before the function and gets me the data frame I'm calling "dat" in the reprex. Then if you run the function like I have at the end of the reprex, get_plot(dat, a= c(1:5)) it results in a bar plot with 5 categories but the "one" category and the "five" category are empty. How do output the plot but not show the empty categories? Keeping in mind that I can't just drop category one and five because sometimes, depending on how the data that creates dat are filtered, there are values in those categories.

[cerutt]

update, after thinking about it more this morning and doing more googling and trying things I figure out a solution. I inserted these select statements into the function and it gets me what I wanted!
p<- data %>%
select(where(~!any(is.na(.)))) %>%
select(where(~!any(.== 0))) %>%