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https://issues.apache.org/jira/browse/ARROW-14649?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ian Cook updated ARROW-14649:
-----------------------------
Description:
ARROW-14167 added support for factors in {{{}coalesce(){}}}, but the factors
that are returned will not necessarily retain the factor levels like
{{coalesce()}} does when used on an R data frame.
For example, compare these, noticing the difference in the levels:
{code:r}
# R data frame
tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
mutate(y = coalesce(x, y)) %>%
pull(y)
#> [1] a c
#> Levels: a b c{code}
{code:r}
# Arrow Table
tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
Table$create() %>%
mutate(y = coalesce(x, y)) %>%
pull(y)
#> [1] a c
#> Levels: a c{code}
Similarly, ARROW-13358 and ARROW-14659 added support for factors in
{{if_else()}} but the returned factors will not always retain the levels like
{{if_else()}} does when used on an R data frame.
I'm not sure if it is practical to make Arrow return the factors with the
unused levels included like R does. If so, we should do it.
See the tests in {{test-dplyr-funcs-conditional.R}} that refers to this Jira.
was:
ARROW-14167 added support for factors in {{{}coalesce(){}}}, but the factors
that are returned will not necessarily retain the factor levels like
{{coalesce()}} does when used on an R data frame.
For example, compare these, noticing the difference in the levels:
{code:r}
# R data frame
tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
mutate(y = coalesce(x, y)) %>%
pull(y)
#> [1] a c
#> Levels: a b c{code}
{code:r}
# Arrow Table
tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
Table$create() %>%
mutate(y = coalesce(x, y)) %>%
pull(y)
#> [1] a c
#> Levels: a c{code}
I'm not sure if it is practical to make Arrow return the factors with the
unused levels included like R does. If so, we should do it.
See the test in {{test-dplyr-funcs-conditional.R}} that refers to this Jira.
> [R] Include unused factor levels in coalesce() and if_else() output
> -------------------------------------------------------------------
>
> Key: ARROW-14649
> URL: https://issues.apache.org/jira/browse/ARROW-14649
> Project: Apache Arrow
> Issue Type: Improvement
> Components: R
> Reporter: Ian Cook
> Priority: Minor
>
> ARROW-14167 added support for factors in {{{}coalesce(){}}}, but the factors
> that are returned will not necessarily retain the factor levels like
> {{coalesce()}} does when used on an R data frame.
> For example, compare these, noticing the difference in the levels:
> {code:r}
> # R data frame
> tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
> mutate(y = coalesce(x, y)) %>%
> pull(y)
> #> [1] a c
> #> Levels: a b c{code}
> {code:r}
> # Arrow Table
> tibble(x = factor(c("a", NA_character_)), y = factor(c("b", "c"))) %>%
> Table$create() %>%
> mutate(y = coalesce(x, y)) %>%
> pull(y)
> #> [1] a c
> #> Levels: a c{code}
> Similarly, ARROW-13358 and ARROW-14659 added support for factors in
> {{if_else()}} but the returned factors will not always retain the levels like
> {{if_else()}} does when used on an R data frame.
> I'm not sure if it is practical to make Arrow return the factors with the
> unused levels included like R does. If so, we should do it.
> See the tests in {{test-dplyr-funcs-conditional.R}} that refers to this Jira.
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