How to convert from ordinal to categorical variable

[rsoto310790]

Dear all,

I am trying to convert an ordinal variable into a categorical one. When running the following code, and print the tibble again:

> diamonds$cut=as.factor(diamonds$cut)

diamonds

# A tibble: 53,940 x 10

    carat   cut    color   clarity  depth table  price    x         y        z
   <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>

The variable type did not change! What am I doing wrong?

[FJCC]

Try using factor() with ordered = FALSE

library(ggplot2)
diamonds
#> # A tibble: 53,940 x 10
#>    carat cut       color clarity depth table price     x     y     z
#>    <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
#>  1 0.23  Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
#>  2 0.21  Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
#>  3 0.23  Good      E     VS1      56.9    65   327  4.05  4.07  2.31
#>  4 0.290 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
#>  5 0.31  Good      J     SI2      63.3    58   335  4.34  4.35  2.75
#>  6 0.24  Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
#>  7 0.24  Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
#>  8 0.26  Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
#>  9 0.22  Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
#> 10 0.23  Very Good H     VS1      59.4    61   338  4     4.05  2.39
#> # ... with 53,930 more rows

diamonds$cut = factor(diamonds$cut, ordered = FALSE)

diamonds
#> # A tibble: 53,940 x 10
#>    carat cut       color clarity depth table price     x     y     z
#>    <dbl> <fct>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
#>  1 0.23  Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
#>  2 0.21  Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
#>  3 0.23  Good      E     VS1      56.9    65   327  4.05  4.07  2.31
#>  4 0.290 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
#>  5 0.31  Good      J     SI2      63.3    58   335  4.34  4.35  2.75
#>  6 0.24  Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
#>  7 0.24  Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
#>  8 0.26  Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
#>  9 0.22  Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
#> 10 0.23  Very Good H     VS1      59.4    61   338  4     4.05  2.39
#> # ... with 53,930 more rows

^{Created on 2019-06-03 by the reprex package (v0.2.1)}