Once again, I need your help and I'm looking forward to listen & learn.
I would like to depict the interrelation between several types of birds (t1 - t7). It is observed how frequently they interact with their own type or other types of birds (o1 - o7)
The data (bird.data) looks as follows:
| type | o1 | o2 | o3 | o4 | o5 | o6 | o7 |
|---|---|---|---|---|---|---|---|
| t1 | 77.6 | 3.5 | 1.5 | 9.1 | 3.3 | 1.4 | 3.6 |
| t2 | 10 | 64.4 | 9 | 3.2 | 2.1 | 7.4 | 3.9 |
| t3 | 8.6 | 12.1 | 63.2 | 2.4 | 0.6 | 8.8 | 4.3 |
| t4 | 28.7 | 5.1 | 2.0 | 51.4 | 5.8 | 0.3 | 6.6 |
| t5 | 4.1 | 12.2 | 9.5 | 1.0 | 0.4 | 64.5 | 8.3 |
| t6 | 10.9 | 3.6 | 0.3 | 6.5 | 66.8 | 2.0 | 9.9 |
| t7 | 15.9 | 8.2 | 4.5 | 5.6 | 9.4 | 5.4 | 51.0 |
bird.data <- structure(list(type = c("t1”, “t2", “t3”, “t4”, “t5”, “t6”, “t7”), o1 = c(77.6, 10, 8.6, 28.7, 4.1, 10.9, 15.9), o2 = c(3.5, 64.4, 12.1, 5.1, 12.2, 3.6, 8.2), o3 = c(1.5, 9, 63.2, 2, 9.5, 0.3, 4.5), o4 = c(9.1, 3.2, 2.4, 51.4, 1, 6.5, 5.6), o5 = c(3.3, 2.1, 0.6, 5.8, 0.4, 66.8, 9.4), o6 = c(1.4, 7.4, 8.8, 0.3, 64.5, 2, 5.4), o7 = c(3.6, 3.9, 4.3, 6.6, 8.3, 9.9, 51)), row.names = c(NA, -7L), class = c("tbl_df", "tbl", "data.frame"))
To show this graphically, I want to plot a flipped, stacked bar chart - similar to this one:
(Taken from this post: Add percentage labels to stacked bar chart ggplot2)
Instead of County, I want to depict the different types of birds on the x-axis (type), instead of Plan Types I want to fill the bar with the percentage of interactions between the different types of birds (o1-o7).
My questions now are:
- How do I organize/group columns o1, o2, o3, o4, o5, o6, o7 to be used as fill?
- What is my y?
ggplot()
geom_bar(aes(y = ?, x = type, fill = ?),
data = bird.data,
stat="identity")
coord_flip()
Thanks a lot in advance for any advice! :-)
CodePudding user response：
You could achieve your desired result by converting your data to long format using e.g. tidyr::pivot_longer. Afterwards it's pretty straightforward what should be mapped on fill and y.
Note: Instead of geom_bar(.. stat="identity") I use geom_col(...). Also instead of coord_flip I switched the role of x and y.
library(tidyr)
library(ggplot2)
bird_data_long <- bird.data %>%
pivot_longer(-type, names_to = "name", values_to = "value")
head(bird_data_long)
#> # A tibble: 6 × 3
#> type name value
#> <chr> <chr> <dbl>
#> 1 t1 o1 77.6
#> 2 t1 o2 3.5
#> 3 t1 o3 1.5
#> 4 t1 o4 9.1
#> 5 t1 o5 3.3
#> 6 t1 o6 1.4
ggplot()
geom_col(aes(x = value, y = type, fill = name), data = bird_data_long)
