CODEWITHSUNDEEP
rggplot2
nelakell
nelakell

Reputation: 189

combine bar and scatterplot in ggplot

I have data with a topic, if customers talk about it positive, negative or neutral and the topics impact and difference from the average.

data <- data.frame(topic = c("a", "b", "c", "d"), impact = runif(4, min = -2, max = 2), 
               difference = runif(4, min = -30, max = 30),n = round(runif(4, min = 1, max = 100)), 
               share_positive = c(0.04, 0.9, 0.3, 0.37), share_neutral = c(0.7, 0.06, 0.48, 0.4), 
               share_negative = c(0.26, 0.04, 0.22, 0.23))

I put it in a simple scatterplot:

ggplot(data = data, aes(x = difference, y = impact, size = n, label = topic)) +
  geom_point() +
  geom_text(size = 4, vjust = -1, colour = "black")

Then I added colour to distinct between positive and less positive topics:

ggplot(data = data, aes(x = difference, y = impact, size = n, label = topic, colour = share_positive)) +
  geom_point() +
  scale_color_continuous(low = "grey", high = "green", guide = FALSE) +
  geom_text(size = 4, vjust = -1, colour = "black")

Instead of the colouring, it would be nice to have bars which indicate the share of negative, neutral and positive feedback in this topic. My idea is something like this (example for b and d):

enter image description here

Unfortunately, I have absolutely no idea, how I can combine this and if it's even possible. Googeling doesn't help either. Can you help me?

Upvotes: 3

Views: 383

Answers (1)

bouncyball
bouncyball

Reputation: 10761

Here's a way to do it, but it's sort of "hacky". We use the difference column and the share_* columns to manually define where xmin and xmax should be when we call geom_rect. To make sure we actually get a bar, we add a little fudge factor (0.1) to ymax

library(tidyverse)
theme_set(theme_bw())

data %>%
    mutate(neg_left = difference - share_negative,
           neutral_right = difference + share_neutral,
           positive_right = neutral_right + share_positive) %>%
    ggplot(., aes(ymin = impact, ymax = impact + .1))+
    geom_text(aes(x = difference, y = impact, label = topic), vjust = 1)+
    geom_rect(aes(xmin = neg_left, xmax = difference), fill = 'red', colour = 'black')+
    geom_rect(aes(xmin = difference, xmax = neutral_right), fill = 'grey', colour = 'black')+
    geom_rect(aes(xmin = neutral_right, xmax = positive_right), fill = 'green', colour = 'black')

enter image description here

Data (using set.seed for reproducibility)

set.seed(456)
data <- data.frame(topic = c("a", "b", "c", "d"), impact = runif(4, min = -2, max = 2), 
                   difference = runif(4, min = -30, max = 30),n = round(runif(4, min = 1, max = 100)), 
                   share_positive = c(0.04, 0.9, 0.3, 0.37), share_neutral = c(0.7, 0.06, 0.48, 0.4), 
                   share_negative = c(0.26, 0.04, 0.22, 0.23))

Upvotes: 2

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