r - Column is NULL when printed as individual field or column, filled when whole data frame is printed -

when create column of counts using dplyr, appears filled correctly, until try use counts column on own. example: create dataframe:

v1 <- c("test", "test", "test", "test", "testing", "testing","me-tested", "re tested", "re testing") v2 <- c("othertest", "anothertest", "testing", "123", "random stuff", "irrelevant", "tested", "re-test", "tests") v3 <- c("type1", "type2", "type1", "type2", "type3", "type2", "type2", "type2", "type1") df <- data.frame(v1, v2, v3) 

then, use dplyr create column of counts:

df$counts <- df %>% group_by(v3) %>% mutate(count = n()) 

this gives expected result:

> df       v1           v2    v3  counts.v1    counts.v2 counts.v3 counts.count 1       test    othertest type1       test    othertest     type1            3 2       test  anothertest type2       test  anothertest     type2            5 3       test      testing type1       test      testing     type1            3 4       test          123 type2       test          123     type2            5 5    testing random stuff type3    testing random stuff     type3            1 6    testing   irrelevant type2    testing   irrelevant     type2            5 7  me-tested       tested type2  me-tested       tested     type2            5 8  re tested      re-test type2  re tested      re-test     type2            5 9 re testing        tests type1 re testing        tests     type1            3 

but, when try use counts.count column in way, result null:

> df$counts.count null 

same result other columns created dplyr. rest of data frame seems normal:

> df$v1 [1] test       test       test       test       testing    testing    me-tested  re tested  re testing levels: me-tested re tested re testing test test test test testing testing 

i totally confused why printing whole df gives me different output printing column of interest. missing here?

if rewind , recreate dataframe , don't assignment print result screen see this:

df %>% group_by(v3) %>% mutate(count = n())  source: local data frame [9 x 4] groups: v3 [3]            v1           v2     v3 count       <fctr>       <fctr> <fctr> <int> 1       test    othertest  type1     3 2       test  anothertest  type2     5 3       test      testing  type1     3 4       test          123  type2     5 5    testing random stuff  type3     1 6    testing   irrelevant  type2     5 7  me-tested       tested  type2     5 8  re tested      re-test  type2     5 9 re testing        tests  type1     3 

if assgnment structure rather confused , think might have gotten more informative error if there had been fewer unique values of v1 or v2:

df$counts <- df %>% group_by(v3) %>% mutate(count = n()) # snipped showed  str(df) #----- 'data.frame':   9 obs. of  4 variables:  $ v1    : factor w/ 9 levels "me-tested","re tested",..: 7 4 6 5 9 8 1 2 3  $ v2    : factor w/ 9 levels "123","anothertest",..: 4 2 8 1 5 3 7 6 9  $ v3    : factor w/ 3 levels "type1","type2",..: 1 2 1 2 3 2 2 2 1  $ counts:classes ‘grouped_df’, ‘tbl_df’, ‘tbl’ , 'data.frame':   9 obs. of  4 variables:   ..$ v1   : factor w/ 9 levels "me-tested","re tested",..: 7 4 6 5 9 8 1 2 3   ..$ v2   : factor w/ 9 levels "123","anothertest",..: 4 2 8 1 5 3 7 6 9   ..$ v3   : factor w/ 3 levels "type1","type2",..: 1 2 1 2 3 2 2 2 1   ..$ count: int  3 5 3 5 1 5 5 5 3   ..- attr(*, "vars")=list of 1   .. ..$ : symbol v3   ..- attr(*, "labels")='data.frame':   3 obs. of  1 variable:   .. ..$ v3: factor w/ 3 levels "type1","type2",..: 1 2 3   .. ..- attr(*, "vars")=list of 1   .. .. ..$ : symbol v3   .. ..- attr(*, "drop")= logi true   ..- attr(*, "indices")=list of 3   .. ..$ : int  0 2 8   .. ..$ : int  1 3 5 6 7   .. ..$ : int 4   ..- attr(*, "drop")= logi true   ..- attr(*, "group_sizes")= int  3 5 1   ..- attr(*, "biggest_group_size")= int 5 

the format seeing how r displays matrix embedded in dataframe. objects of class table (and perhaps tbl?) inherit matrix-class.