How can I correctly position the geom_text labels to these geom_col data?

MusTheDataGuy Source

I am unable to get the labels to fit properly over each dodged bar in this chart:

enter image description here

I feel that I am almost there, but can't quite figure out how to get the labels perfectly positioned over each respective dodged bar.

Code:

ggplot() +
  geom_col(data = leads_over_chats, aes(x = date, y = count, fill = type),
           colour = "black",
           position = "dodge") +
  labs(title = "Leads Over Chats\n(May 2018)",
       x = "Type",
       y = "Count") +
  geom_text(data = leads_over_chats, aes(x = date, y = count, label = count),
            hjust = -1.5,
            vjust = -0.5,
            size = 4,
            angle = 90,
            position=position_dodge(width = 2.25),
            colour = "black")

I am trying to replicate this (from Kibana):

enter image description here

Reproducible data frame

structure(list(type = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 1L, 1L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("aborted-live-lead", 
"conversation-claimed", "conversation-created", "lead-created"
), class = "factor"), date = structure(c(1525129200, 1525215600, 
1525302000, 1525388400, 1525474800, 1525561200, 1525647600, 1525734000, 
1525820400, 1525906800, 1525993200, 1526079600, 1526166000, 1526252400, 
1526338800, 1526425200, 1526511600, 1526598000, 1526684400, 1526770800, 
1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 1527289200, 
1527375600, 1527462000, 1527548400, 1527634800, 1527721200, 1526166000, 
1526252400, 1526338800, 1526425200, 1526598000, 1526684400, 1526770800, 
1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 1527289200, 
1527375600, 1527462000, 1527548400, 1527634800, 1527721200, 1526252400, 
1526338800, 1526425200, 1526511600, 1526598000, 1526684400, 1526770800, 
1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 1527289200, 
1527375600, 1527462000, 1527548400, 1527634800, 1527721200, 1526252400, 
1526338800, 1526425200, 1526511600, 1526598000, 1526684400, 1526770800, 
1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 1527289200, 
1527375600, 1527462000, 1527548400, 1527634800, 1527721200, 1525129200, 
1525215600, 1525302000, 1525388400, 1525474800, 1525561200, 1525647600, 
1525734000, 1525820400, 1525906800, 1525993200, 1526079600, 1526166000, 
1526252400, 1526338800, 1526425200, 1526511600, 1526598000, 1526684400, 
1526770800, 1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 
1527289200, 1527375600, 1527462000, 1527548400, 1527634800, 1527721200, 
1526166000, 1526252400, 1526338800, 1526425200, 1526511600, 1526598000, 
1526684400, 1526770800, 1526857200, 1526943600, 1527030000, 1527116400, 
1527202800, 1527289200, 1527375600, 1527462000, 1527548400, 1527634800, 
1527721200, 1526252400, 1526338800, 1526425200, 1526511600, 1526598000, 
1526684400, 1526770800, 1526857200, 1526943600, 1527030000, 1527116400, 
1527202800, 1527289200, 1527375600, 1527462000, 1527548400, 1527634800, 
1527721200, 1526252400, 1526338800, 1526425200, 1526511600, 1526598000, 
1526684400, 1526770800, 1526857200, 1526943600, 1527030000, 1527116400, 
1527202800, 1527289200, 1527375600, 1527462000, 1527548400, 1527634800, 
1527721200, 1525129200, 1525215600, 1525302000, 1525388400, 1525474800, 
1525561200, 1525647600, 1525734000, 1525820400, 1525906800, 1525993200, 
1526079600, 1526166000, 1526252400, 1526338800, 1526425200, 1526511600, 
1526598000, 1526684400, 1526770800, 1526857200, 1526943600, 1527030000, 
1527116400, 1527202800, 1527289200, 1527375600, 1527462000, 1527548400, 
1527634800, 1527721200, 1525129200, 1525215600, 1525302000, 1525388400, 
1525474800, 1525561200, 1525647600, 1525820400, 1525906800, 1526079600, 
1526166000, 1526252400, 1526338800, 1526425200, 1526511600, 1526598000, 
1526684400, 1526857200, 1526943600, 1527030000, 1527116400, 1527289200, 
1527462000, 1527548400, 1527634800, 1526252400, 1526338800, 1526425200, 
1526511600, 1526598000, 1526684400, 1526857200, 1526943600, 1527030000, 
1527116400, 1527202800, 1527289200, 1527462000, 1527548400, 1527634800, 
1525129200, 1525215600, 1525302000, 1525388400, 1525734000, 1525820400, 
1525906800, 1525993200, 1526252400, 1526425200, 1526511600, 1526598000, 
1526684400, 1526857200, 1527030000, 1527116400, 1527202800, 1527289200, 
1527548400, 1527721200, 1525129200, 1525215600, 1525302000, 1525388400, 
1525474800, 1525647600, 1525820400, 1525906800, 1525993200, 1526079600, 
1526252400, 1526857200, 1526943600, 1527030000, 1527116400, 1527202800, 
1527462000, 1527548400, 1527634800, 1527721200, 1526857200, 1526943600, 
1527030000, 1527116400, 1527202800, 1527462000, 1527548400, 1527634800, 
1527721200, 1526252400, 1526684400, 1526857200, 1526943600, 1527030000, 
1527202800, 1527462000, 1527548400, 1526252400, 1526857200, 1526943600, 
1527030000, 1527548400, 1525215600, 1525302000, 1525388400, 1525474800, 
1525647600, 1525820400, 1525993200, 1526079600, 1526252400, 1526338800, 
1526511600, 1526598000, 1526684400, 1526770800, 1526857200, 1526943600, 
1527030000, 1527116400, 1527289200, 1527462000, 1527634800, 1527721200, 
1526425200, 1526857200, 1526943600, 1527202800, 1526425200, 1527202800, 
1526425200, 1526943600, 1527202800, 1526857200, 1527202800, 1526338800, 
1526425200, 1526943600, 1527116400, 1527289200, 1527721200, 1525734000, 
1526338800, 1526425200, 1526943600, 1527116400, 1527202800, 1527289200, 
1527202800, 1525302000, 1525388400, 1525734000, 1525820400, 1525993200, 
1526511600, 1526857200, 1526943600, 1527116400, 1527462000, 1527548400, 
1525129200, 1525215600, 1525561200, 1525734000, 1525906800, 1526079600, 
1526252400, 1526857200, 1526943600, 1527375600, 1525302000, 1525474800, 
1525993200, 1526425200, 1527030000, 1525215600, 1525734000, 1526425200, 
1526857200, 1527548400, 1525734000, 1526943600, 1525906800, 1526943600, 
1526252400, 1526338800, 1525215600, 1525820400, 1526252400, 1527202800, 
1525215600, 1526338800, 1526511600, 1526857200, 1525129200, 1527116400
), class = c("POSIXct", "POSIXt"), tzone = ""), count = c(76L, 
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93L, 108L, 137L, 112L, 107L, 15L, 89L, 68L, 85L, 34L, 45L, 44L, 
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-398L))
rpositiongeom-textgeom-col

Answers

answered 2 months ago JasonAizkalns #1

First, you're going to want to summarize your data at the type + date grouping. You currently have multiple count records for each date. Then, I would probably recommend a line chart over a dodged bar for this type of visual:

library(tidyverse)

df <- leads_over_chats

df %>%
  mutate(date = as.Date(date)) %>%
  group_by(type, date) %>%
  summarise(total_count = sum(count)) %>%
  ggplot(., aes(date, total_count, color = type)) +
  geom_line()

enter image description here

If you really want a dodged bar chart, you'll want to first convert type to a factor and then leverage tidyr::complete so that all the bars stay the same width:

df %>%
  mutate(date = as.Date(date),
         type = as.factor(type)) %>%
  group_by(type, date) %>%
  complete(type, date) %>%
  summarise(total_count = sum(count)) %>%
  ggplot(., aes(date, total_count, fill = type)) +
  geom_col(position = position_dodge())

enter image description here

Given your comment, you may also want to consider leveraging patchwork with a "sum" chart and then the breakout. Something like:

library(patchwork)

df_grouped_and_summed <-
  df %>%
  mutate(date = as.Date(date),
         type = as.factor(type)) %>%
  group_by(type, date) %>%
  complete(type, date) %>%
  summarise(total_count = sum(count))

p_created <- 
  ggplot(df_grouped_and_summed, aes(date, total_count)) +
  geom_col() +
  labs(x = "", y = "")

p_splits <-
  ggplot(df_grouped_and_summed %>% filter(type != "conversation-created"),
         aes(date, total_count, fill = type)) +
  geom_col() +
  facet_wrap(~ type, ncol = 1) +
  labs(x = "", y = "") +
  guides(fill = FALSE)

p_created + p_splits

enter image description here

Finally, if it's just a breakout, then you could also use a stacked bar -- however, you'll notice (at least in the data provided) that the sum of the parts does not equal the total:

df_grouped_and_summed %>%
  filter(type != "conversation-created") %>%
  ggplot(., aes(date, total_count, fill = type)) +
  geom_col()

enter image description here

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