How can I align labels in a group of bar charts?

I would like to align the labels for the count and percentage over the columns in a group of bar charts. In some of the charts in the group, not all values are represented. There are three values for sentiments -- positive, neutral, and negative -- but some offices only have one or two of the responses. For the individual charts without a value, the labels don't align. How can I get the columns and labels in alignment.

Here is the data and my code -- really appreciate the support!

data

office  sentiment
1   positive
1   positive
1   neutral
1   neutral
1   positive
1   positive
1   positive
1   positive
1   neutral
1   neutral
1   neutral
1   positive
1   positive
1   negative
1   negative
1   positive
1   neutral
1   neutral
1   neutral
1   positive
1   neutral
1   neutral
1   negative
1   positive
1   positive
1   neutral
2   positive
2   positive
2   neutral
3   positive
3   positive
3   positive
3   positive
4   positive
4   negative
4   neutral
5   positive
6   positive
6   positive
6   positive
6   positive
6   neutral
6   positive
6   positive
6   positive
6   positive
7   positive
8   neutral
8   positive
8   positive


df <- [office, sentiment] # a data frame or tibble of the above data set

office_sentiment <- df[ , c("office","sentiment")]
office_sentiment <- office_sentiment %>% group_by(sentiment,office) %>% summarize(count = n()) 
office_sentiment <-  filter(office_sentiment,count >= 1,sentiment != "NA") #%>%
office_sentiment

office_sentiment_percentage <- df[ , c("office","sentiment")]
office_sentiment_percentage <- office_sentiment_percentage %>% group_by(sentiment,office) %>% summarize(count = n()) 
office_sentiment_percentage <-  filter(office_sentiment_percentage,count >= 1,sentiment != "NA") %>%
  mutate(percentage=count/sum(count)*100) 
  office_sentiment_percentage$percentage <- paste0(round(office_sentiment_percentage$percentage,1),"%")

# the function i use for most bar charts
myBarChart_2 <- function(data,var1,var2,count,title,xLabel,yLabel) {
     ggplot(data, aes_string(x=var1, y=count, fill=var2)) +
      ggtitle(title) +
      geom_bar(stat = 'idoffice',width=1,position = position_dodge2(padding=0.1,reverse=FALSE,preserve=c("single"))) +
      scale_color_manual(values=c("#66CCFF","#009999","#FF66CC"),aesthetics = c("colour", "fill")) +
      scale_y_continuous(sec.axis=waiver(),expand = expansion(mult = c(0,0.05))) +
      facet_wrap(var1, strip.position="bottom",scales = "free_x")  +
      xlab(xLabel) +
      ylab(yLabel) +
      theme_set(myBar_theme) +[![enter image description here][1]][1]
      theme(axis.text.x=element_blank())
}

# code for this sample set of charts

myBarChart_2(office_sentiment_percentage,'officeType','sentiment','count',"Sentiment by Office","sentiment","total") +
  (aes(group=factor(sentiment, levels=c('positive','neutral','negative')))) +
  geom_text(aes(label = count),vjust=1.5,position=position_dodge2(width=1),size=2.5) +
  geom_text(aes(label = percentage),vjust=-.3,position=position_dodge2(width=1),size=2.5) +
  guides(fill = guide_legend(reverse = TRUE))

Solution

There are a number of issues with your minimal reproducible example. I strongly recommend using the reprex package and following How to make a minimal reproducible example and How to make a great R reproducible example for future posts.

The answer to your question is, I believe, very straightforward. If you add preserve = "single" to each geom_text() the labels appear to be positioned correctly. I wasn't able to run your example code, so I have stripped out some of the problematic sections to illustrate my answer:

library(tidyverse)

df <- structure(list(office = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
                                1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
                                1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 6L, 6L, 6L, 6L, 
                                6L, 6L, 6L, 6L, 6L, 7L, 8L, 8L, 8L),
                     sentiment = c("positive", 
                                   "positive", "neutral", "neutral", "positive", "positive", "positive", 
                                   "positive", "neutral", "neutral", "neutral", "positive", "positive", 
                                   "negative", "negative", "positive", "neutral", "neutral", "neutral", 
                                   "positive", "neutral", "neutral", "negative", "positive", "positive", 
                                   "neutral", "positive", "positive", "neutral", "positive", "positive", 
                                   "positive", "positive", "positive", "negative", "neutral", "positive", 
                                   "positive", "positive", "positive", "positive", "neutral", "positive", 
                                   "positive", "positive", "positive", "positive", "neutral", "positive", 
                                   "positive")), class = "data.frame", row.names = c(NA, -50L))

office_sentiment <- df[ , c("office","sentiment")]
office_sentiment <- office_sentiment %>% group_by(sentiment,office) %>% summarize(Count = n()) 
#> `summarise()` has grouped output by 'sentiment'. You can override using the `.groups` argument.
office_sentiment <-  filter(office_sentiment, Count >= 1,sentiment != "NA") #%>%
office_sentiment
#> # A tibble: 15 × 3
#> # Groups:   sentiment [3]
#>    sentiment office Count
#>    <chr>      <int> <int>
#>  1 negative       1     3
#>  2 negative       4     1
#>  3 neutral        1    11
#>  4 neutral        2     1
#>  5 neutral        4     1
#>  6 neutral        6     1
#>  7 neutral        8     1
#>  8 positive       1    12
#>  9 positive       2     2
#> 10 positive       3     4
#> 11 positive       4     1
#> 12 positive       5     1
#> 13 positive       6     8
#> 14 positive       7     1
#> 15 positive       8     2

office_sentiment_percentage <- df[ , c("office","sentiment")]
office_sentiment_percentage <- office_sentiment_percentage %>% group_by(sentiment,office) %>% summarize(Count = n()) 
#> `summarise()` has grouped output by 'sentiment'. You can override using the `.groups` argument.
office_sentiment_percentage <-  filter(office_sentiment_percentage, Count >= 1,sentiment != "NA") %>%
  mutate(percentage=Count/sum(Count)*100) 
office_sentiment_percentage$percentage <- paste0(round(office_sentiment_percentage$percentage,1),"%")


ggplot(office_sentiment_percentage,
       aes(x = office, y = Count, fill = sentiment)) +
  ggtitle("Sentiment by Office") +
  geom_col(width = 1,
           position = position_dodge2(
             padding = 0.1,
             reverse = FALSE,
             preserve = c("single")
           )) +
  scale_color_manual(
    values = c("#66CCFF", "#009999", "#FF66CC"),
    aesthetics = c("colour", "fill")
  ) +
  scale_y_continuous(sec.axis = waiver(), expand = expansion(mult = c(0, 0.05))) +
  facet_wrap(~office, strip.position = "bottom", scales = "free_x")  +
  xlab("sentiment") +
  ylab("total count") +
  theme(axis.text.x = element_blank()) +
  geom_text(
    aes(label = Count),
    vjust = 1.5,
    position = position_dodge2(width = 1, preserve = "single"),
    size = 2.5
  ) +
  geom_text(
    aes(label = percentage),
    vjust = -.3,
    position = position_dodge2(width = 1, preserve = "single"),
    size = 2.5
  ) +
  guides(fill = guide_legend(reverse = TRUE))

^{Created on 2022-01-14 by the reprex package (v2.0.1)}

Does this solve your problem?