so ive been trying to analyse my non parametric data for a while however I cant seem to get it to work - basically I've been trying to run a post hoc to a kruskal wallis test. however I don't know whats wrong whether its my data layout of my inputs

Stat.testFvFm0N1 <- FvFm0N %>%

- wilcox.test(D0 ~ D1, paired = TRUE) %>% add_significance()

Error in wilcox.test.default(., D0 ~ D1, paired = TRUE) :

'x' must be numeric

Stat.testFvFm0H1 <- FvFm0H %>% wilcox.test(D0 ~ D1, paired = TRUE) %>% add_significance()

Error in wilcox.test.default(., D0 ~ D1, paired = TRUE) :

'x' must be numeric

Stat.testFvFm0H1 <- FvFm0H %>% wilcox.test(FvFm ~ D0*D1, paired = TRUE) %>% add_significance()

Error in wilcox.test.default(., FvFm ~ D0 * D1, paired = TRUE) :

'x' must be numeric

Stat.testFvFm0H1 <- FvFm0H %>% wilcox.test(FvFm ~ Day, paired = TRUE) %>% add_significance()

Error in wilcox.test.default(., FvFm ~ Day, paired = TRUE) :

'x' must be numeric

Stat.testFvFm0H1 <- FvFm0H %>% group_by(Day) %>% wilcox.test(FvFm ~ Day, paired = TRUE) %>% add_significance()

Error: Must group by variables found in`.data`

.

- Column
`Day`

is not found.

Run`rlang::last_error()`

to see where the error occurred.

Stat.testFvFm0H1 <- FvFm0H %>% group_by("Day") %>% wilcox.test(FvFm ~ Day, paired = TRUE) %>% add_significance()

Error in wilcox.test.default(., FvFm ~ Day, paired = TRUE) :

'x' must be numeric

I've split my data up into different conditions for the exact same IPAM parameter to do a paired test between the days, however I don't know whats going on because my data points are numeric except there are more then two data sets in the table but can't seem to focus in on two at a time - I just don't want to have to keep importing data sets with less data in

D0 D1 D2 D3 D4 D5 D6 D7

1 0.163457469 0.187385368 0.136679322 0.10488145 0.110073797 0.095678447 0.094178232 0.106127771

2 0.142494136 0.181154612 0.143094261 0.105833764 0.104921535 0.097943358 0.087377843 0.104797048

3 0.131960693 0.175194359 0.149937526 0.114355231 0.095977698 0.083587252 0.088176672 0.105426727

this is how my data is laid out originally or I've tried to make the data long and that hasn't worked either