Why 2 outputs of chisq.test are different in R

Question

In following, why are outputs of 2 chisq.test different, when data is really the same:

> df1
  count position
1     1       11
2     6       12
3    12       13
4    23       14
5    27       15
> df2
  count position
1     1       11
2     4       12
3     9       13
4    24       14
5    24       15
> mm = merge(df1, df2,  by='position')
> mm
  position count.x count.y
1       11       1       1
2       12       6       4
3       13      12       9
4       14      23      24
5       15      27      24

First method:

> chisq.test(mm[2:3])

        Pearson's Chi-squared test

data:  mm[2:3]
X-squared = 0.6541, df = 4, p-value = 0.9569

Warning message:
In chisq.test(mm[2:3]) : Chi-squared approximation may be incorrect

Second method:

> chisq.test(df1$count, df2$count)

        Pearson's Chi-squared test

data:  df1$count and df2$count
X-squared = 15, df = 12, p-value = 0.2414

Warning message:
In chisq.test(df1$count, df2$count) :
  Chi-squared approximation may be incorrect
> 

Edit: responding to comment: following look identical:

> mm[2:3]
  count.x count.y
1       1       1
2       6       4
3      12       9
4      23      24
5      27      24
> 

> mm[,2:3]
  count.x count.y
1       1       1
2       6       4
3      12       9
4      23      24
5      27      24

data:

> dput(df1)
structure(list(count = c(1L, 6L, 12L, 23L, 27L), position = 11:15), .Names = c("count", 
"position"), class = "data.frame", row.names = c(NA, -5L))
> dput(df2)
structure(list(count = c(1L, 4L, 9L, 24L, 24L), position = 11:15), .Names = c("count", 
"position"), class = "data.frame", row.names = c(NA, -5L))

Answer 1

see ?chisq : in the first case, mm[2:3] is taken as a contingency table, in the second case, the contingency table is computed.

chisq.test(table(df1$count, df2$count))

        Pearson's Chi-squared test

data:  table(df1$count, df2$count)
X-squared = 15, df = 12, p-value = 0.2414

Warning message:
In chisq.test(table(df1$count, df2$count)) :
  Chi-squared approximation may be incorrect

So, really, you are calculated chisq of this table :

     1 4 9 24
  1  1 0 0  0
  6  0 1 0  0
  12 0 0 1  0
  23 0 0 0  1
  27 0 0 0  1

Answer 2

It is stated in the R documentation of chisq.test that

If x is a matrix with at least two rows and columns, it is taken as a two-dimensional contingency table

Thus, when you type chisq.test(mm[2:3]), your matrix is the contingency table.

In the second case, when yout type chisq.test(df1$count, df2$count), the contengency table is computed (with the function table) from the vectors df1$count and df2$count