cbind usage returns unexpected results

Question

I have a tibble abc and a tibble def.

abc

# A tibble: 4 x 4
# Groups:   Category, Measure [1]
  Category Measure     Date          Value
  <chr>    <chr>       <date>        <dbl>
1 Pickles  Gross Sales 2016-01-03 6518758.
2 Pickles  Gross Sales 2016-01-10 5640691.
3 Pickles  Gross Sales 2016-01-17 5450121.
4 Pickles  Gross Sales 2016-01-24 5726041.

def

# A tibble: 4 x 2
        all       pb
      <dbl>    <dbl>
1 25992010. 4836410.
2 25769111. 4692100.
3 25612548. 4555298.
4 23869990. 4180362.

I want to cbind abc and def to get a tibble with 6 columns.

But when I do cbind(abc,def) I get the below. I am not sure why. Can someone help?

       abc         def      
Category Character,4 Numeric,4
Measure  Character,4 Numeric,4
Date     Numeric,4   Numeric,4
Value    Numeric,4   Numeric,4

score 4 · Answer 1 · edited Feb 26 '20 at 21:45

4

new_tibble <- bind_cols(abc,def)

edited Feb 26 '20 at 21:45

Maurits Evers

49,617
4
47
68

answered Feb 26 '20 at 21:42

HarvProgrammer

41
3

akrun · Accepted Answer · 2020-02-26T21:57:15.563

In the structure, one of them is grouped with group attributes so we if we ungroup or convert to data.frame (as.data.frame - removes the attributes), cbind would work

library(dplyr)
abc %>%
   ungroup %>%
   cbind(def)

It can be reproduced with mtcars

cbind(as_tibble(head(mtcars[1:4], 3)) %>% 
       group_by(cyl), 
       as_tibble(head(mtcars[5:7], 3)))
#     [,1]      [,2]     
#mpg  Numeric,3 Numeric,3
#cyl  Numeric,3 Numeric,3
#disp Numeric,3 Numeric,3
#hp   Numeric,3 Numeric,3

Without group attributes

cbind(as_tibble(head(mtcars[1:4], 3)), as_tibble(head(mtcars[5:7], 3)))
#   mpg cyl disp  hp drat    wt  qsec
#1 21.0   6  160 110 3.90 2.620 16.46
#2 21.0   6  160 110 3.90 2.875 17.02
#3 22.8   4  108  93 3.85 2.320 18.61

Also, by checking the methods for cbind

methods("cbind")
#[1] cbind.data.frame  cbind.grouped_df* cbind.ts*

when there is a grouped_df, it automatically calls the cbind.grouped_df instead of cbind.data.frame. If we explicitly specify cbind.data.frame, it should work

cbind.data.frame(as_tibble(head(mtcars[1:4], 3)) %>% 
       group_by(cyl), 
        as_tibble(head(mtcars[5:7], 3)))
#   mpg cyl disp  hp drat    wt  qsec
#1 21.0   6  160 110 3.90 2.620 16.46
#2 21.0   6  160 110 3.90 2.875 17.02
#3 22.8   4  108  93 3.85 2.320 18.61

NOTE: The OP's question was about the behavior with cbind and this answers the cause of it

Thank you. How did you know it was grouped? Is there any function call to know whether a data frame is grouped? — user17144, Feb 27 '20 at 03:19
@user2371765 it is already showed in your post `# Groups: Category, Measure [1]` — akrun, Feb 27 '20 at 17:32

cbind usage returns unexpected results

2 Answers2