I've asked this question previously with no luck, so here goes again:
My dataframe:
data.type <- c("DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","DNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA","RNA")
hour <- c(1,1,1,2,2,2,24,24,24,48,48,48,96,96,96,168,168,168,672,672,672,1,1,1,2,2,2,24,24,24,48,48,48,96,96,96,168,168,168,672,672,672)
zotu.count <- c(11,14,16,7,16,15,5,14,13,6,5,17,7,7,12,3,4,5,3,5,4,2,3,2,1,6,2,1,1,1,1,0,0,1,1,4,1,1,1,6,7,6)
id <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42)
I am trying to do a shapiro test to test for normality of my data using the following code and am being given the following error:
dataset %>% group_by(data.type, hour) %>% shapiro_test(zotu.count)
Error: Problem with `mutate()` column `data`.
ℹ `data = map(.data$data, .f, ...)`.
x Problem with `mutate()` column `data`.
ℹ `data = map(.data$data, .f, ...)`.
x all 'x' values are identical
This is very strange as it has worked before on another dataset with the same data structure but I have no idea why I'm getting this error now. I am very frustrated as I have scoured the internet for answers and have nothing. Anybody who might be able to help would be a godsend!
Thank you!
We could use an if/else condition for this - checking where there are more than one unique values in 'zotu.count' and apply the shapiro_test
library(rstatix)
library(dplyr)
library(tidyr)
dataset %>%
group_by(data.type, hour) %>%
summarise(out = if(n_distinct(zotu.count) == 1) list(NA)
else list(shapiro_test(zotu.count)), .groups = 'drop') %>%
unnest(out)
-output
# A tibble: 14 × 5
data.type hour variable statistic p.value
<chr> <dbl> <chr> <dbl> <dbl>
1 DNA 1 zotu.count 0.987 0.780
2 DNA 2 zotu.count 0.832 0.194
3 DNA 24 zotu.count 0.832 0.194
4 DNA 48 zotu.count 0.812 0.144
5 DNA 96 zotu.count 0.75 0
6 DNA 168 zotu.count 1 1.00
7 DNA 672 zotu.count 1 1.00
8 RNA 1 zotu.count 0.75 0
9 RNA 2 zotu.count 0.893 0.363
10 RNA 24 <NA> NA NA
11 RNA 48 zotu.count 0.75 0
12 RNA 96 zotu.count 0.75 0
13 RNA 168 <NA> NA NA
14 RNA 672 zotu.count 0.75 0
We may also filter out those groups that have only a single unique value
dataset %>%
group_by(data.type, hour) %>%
filter(n_distinct(zotu.count) > 1) %>%
shapiro_test(zotu.count)
# A tibble: 12 × 5
data.type hour variable statistic p
<chr> <dbl> <chr> <dbl> <dbl>
1 DNA 1 zotu.count 0.987 0.780
2 DNA 2 zotu.count 0.832 0.194
3 DNA 24 zotu.count 0.832 0.194
4 DNA 48 zotu.count 0.812 0.144
5 DNA 96 zotu.count 0.75 0
6 DNA 168 zotu.count 1 1.00
7 DNA 672 zotu.count 1 1.00
8 RNA 1 zotu.count 0.75 0
9 RNA 2 zotu.count 0.893 0.363
10 RNA 48 zotu.count 0.75 0
11 RNA 96 zotu.count 0.75 0
12 RNA 672 zotu.count 0.75 0