Combine rows to create a new "other" row to reduce data size

There are 100 variables, but the screenshot only shows 22 of them. I want to be able to plot the data into a readable bar graph and with 100 variables I cannot read it well. So, I want to make an "other" row under the brand column that puts all rows into the "other" row that has a total count of less than 5. Is this possible? Or does anyone have another way of plotting 100 categorical variables into a bar plot and being able to read it? I attached a screenshot of the bar plot as well.

The image I attached is what the bar plot looks like will all 100 variables, I cannot read it.

If this is your data

set.seed(42)

df <- data.frame(brand = LETTERS[1:20], Count = sample(10, 20, replace=T))

Using bind_rows to get the modified data set

val <- 5

bind_rows(df %>% filter(Count >= val), 
          df %>% summarize(brand = "other", Count = sum(Count[Count < val])))
   brand Count
1      B     5
2      D     9
3      E    10
4      H    10
5      J     8
6      K     7
7      M     9
8      N     5
9      P    10
10     S     9
11     T     9
12 other    22

Note you can, additionally, rotate your labels to make them more readable, e.g. ... + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

Final plot including ordering of bars, first "other", then ascending by Count

bind_rows(df %>% filter(Count >= val), 
          df %>% summarize(brand = "other", Count = sum(Count[Count < val]))) %>%
  mutate(brand = factor(brand, levels = 
                   c(brand[grep("other", brand)], 
                     brand[grep("other", brand, invert = T)][order(Count)]))) %>%
  ggplot() + 
    geom_col(aes(brand, Count)) + 
    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

I'll demonstrate how to reduce a subset of categoricals into an "other" category for plotting.

library(dplyr)
library(ggplot2)
data("starwars", package="dplyr")
ggplot(starwars, aes(eye_color)) + geom_bar()

count(starwars, eye_color) %>%
  arrange(desc(n))
# # A tibble: 15 × 2
#    eye_color         n
#    <chr>         <int>
#  1 brown            21
#  2 blue             19
#  3 yellow           11
#  4 black            10
#  5 orange            8
#  6 red               5
#  7 hazel             3
#  8 unknown           3
#  9 blue-gray         1
# 10 dark              1
# 11 gold              1
# 12 green, yellow     1
# 13 pink              1
# 14 red, blue         1
# 15 white             1
count(starwars, eye_color) %>%
  mutate(eye2 = if_else(n <= 5, "other", eye_color)) %>%
  left_join(starwars, by="eye_color") %>%
  ggplot(aes(eye2)) +
  geom_bar()

Another option is to use the ifelse to mutate the data, summarize it then plot:

library(tidyverse)
df <- starwars
df$brand <- df$eye_color

df1 <- df %>%
  count(brand, name = 'total_count')%>%
  mutate(brand = ifelse(total_count > 5, brand, "Other"))%>%
  summarise(total_count = sum(total_count), .by = brand)
df1
#> # A tibble: 6 × 2
#>   brand  total_count
#>   <chr>        <int>
#> 1 black           10
#> 2 blue            19
#> 3 Other           18
#> 4 brown           21
#> 5 orange           8
#> 6 yellow          11

  ggplot(df1, aes(brand, total_count)) +
  geom_bar(stat='identity')

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^{Created on 2023-04-16 with reprex v2.0.2}