How to round percantage in hover text with plotly-r-CodePudding

I have practiced with plotly in R and created a barplot with data from a textbook called stats_test

prada_stats_test_url <- paste0("https://raw.github.com/",
                               "sebastiansauer/", 
                               "Praxis_der_Datenanalyse/", 
                               "master/",
                               "data/stats_test.csv") 

stats_test <- read.csv(prada_stats_test_url)

Here is the code for the barplot:


test <- stats_test %>% 
  drop_na() %>% 
  ggplot()  
  aes(x = interest, fill = bestanden)  
  geom_bar(position = "fill")

test <- ggplotly(test)

When I scroll over the graph it shows me the percentage ratios. I would like to round these to only two decimal places. How could I do that? And maybe add a percantage symbol.

Here is the output from the dataset dput(head(stats_test,20))


structure(list(row_number = 1:20, date_time = c("05.01.2017 13:57:01", 
"05.01.2017 21:07:56", "05.01.2017 23:33:47", "06.01.2017 09:58:05", 
"06.01.2017 14:13:08", "06.01.2017 14:21:18", "06.01.2017 14:25:49", 
"06.01.2017 17:24:53", "07.01.2017 10:11:17", "07.01.2017 18:10:05", 
"08.01.2017 12:56:43", "08.01.2017 19:17:20", "09.01.2017 09:51:37", 
"09.01.2017 12:15:48", "09.01.2017 15:23:15", "09.01.2017 15:52:12", 
"09.01.2017 20:49:48", "09.01.2017 22:57:38", "10.01.2017 17:16:48", 
"10.01.2017 18:33:15"), bestanden = c("ja", "ja", "ja", "nein", 
"ja", "ja", "ja", "nein", "ja", "ja", "ja", "ja", "nein", "ja", 
"ja", "nein", "ja", "ja", "nein", "ja"), study_time = c(5L, 3L, 
5L, 2L, 4L, NA, NA, 2L, 2L, 4L, 1L, 4L, 1L, 4L, NA, 2L, 2L, 3L, 
NA, 3L), self_eval = c(8L, 7L, 10L, 3L, 8L, NA, NA, 5L, 3L, 5L, 
2L, 7L, 2L, 9L, NA, 5L, 5L, 3L, NA, 5L), interest = c(5L, 3L, 
6L, 2L, 6L, NA, NA, 3L, 5L, 5L, 4L, 4L, 2L, 3L, NA, 3L, 3L, 5L, 
NA, 2L), score = c(29L, 29L, 40L, 18L, 34L, 39L, 40L, 24L, 25L, 
33L, 32L, 31L, 22L, 35L, 30L, 24L, 33L, 32L, 22L, 26L)), row.names = c(NA, 
20L), class = "data.frame")

CodePudding user response：

You can calculate the tooltip manually:

library(tidyverse)
library(plotly)
#> 
#> Attaching package: 'plotly'
#> The following object is masked from 'package:ggplot2':
#> 
#>     last_plot
#> The following object is masked from 'package:stats':
#> 
#>     filter
#> The following object is masked from 'package:graphics':
#> 
#>     layout

prada_stats_test_url <- paste0(
  "https://raw.github.com/",
  "sebastiansauer/",
  "Praxis_der_Datenanalyse/",
  "master/",
  "data/stats_test.csv"
)

stats_test <-
  read.csv(prada_stats_test_url) %>%
  drop_na() %>%
  count(interest, bestanden) %>%
  group_by(interest) %>%
  mutate(
    n = n / sum(n),
    tooltip = (round(n * 100, 2)) %>% paste0("%")
  )
stats_test
#> # A tibble: 12 x 4
#> # Groups:   interest [6]
#>    interest bestanden      n tooltip
#>       <int> <chr>      <dbl> <chr>  
#>  1        1 ja        0.8    80%    
#>  2        1 nein      0.2    20%    
#>  3        2 ja        0.851  85.11% 
#>  4        2 nein      0.149  14.89% 
#>  5        3 ja        0.803  80.3%  
#>  6        3 nein      0.197  19.7%  
#>  7        4 ja        0.829  82.93% 
#>  8        4 nein      0.171  17.07% 
#>  9        5 ja        0.911  91.11% 
#> 10        5 nein      0.0889 8.89%  
#> 11        6 ja        0.889  88.89% 
#> 12        6 nein      0.111  11.11%

plt <-
  stats_test %>%
  ggplot()  
  aes(x = interest, y = n, fill = bestanden, tooltip = tooltip)  
  geom_bar(stat = "identity")

ggplotly(plt, tooltip = "tooltip")