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df_paste preserves factors but drops unseen levels #39

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MilesMcBain opened this issue Mar 18, 2017 · 4 comments · May be fixed by #75
Closed

df_paste preserves factors but drops unseen levels #39

MilesMcBain opened this issue Mar 18, 2017 · 4 comments · May be fixed by #75

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@MilesMcBain
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example:

head(iris) %>% df_paste()
data.frame(
   Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4),
    Sepal.Width = c(3.5, 3, 3.2, 3.1, 3.6, 3.9),
   Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7),
    Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4),
        Species = as.factor(c("setosa", "setosa", "setosa", "setosa", "setosa",
                              "setosa"))
)

Part of me is happy with this since unused factor levels are usually annoying. However this may be unexpected for some people.
@jonocarroll
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If the data is coming from an existing structure then I'd say preserve factor levels. Happy to look into making that happen.

jonocarroll added a commit to jonocarroll/datapasta that referenced this issue Jul 23, 2018
@jonocarroll
⚡ retains factor levels (even if unseen) when pasting an existing object
4ba130d 
closes MilesMcBain#39
@jonocarroll jonocarroll mentioned this issue Jul 23, 2018
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@MilesMcBain
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I'm unsure about merging this. It has never be raised by a user, this was just me making a note of the behaviour.

One of the primary cases when using data from an existing structure is to create a small subset for an example. If you're subsetting a dataframe to become an example, I presume you probably want the factor levels chopped as well, since if those levels were important for the example you would have been sure to include them. I am guessing this change might result in a few people having to manually fudge the factor levels and that is not what I would want.

If you're taking the whole data frame, there is no issue.

@jonocarroll
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All good. I saw it as a 'see how hard it is to do' sort of thing.

One option is to have it activated with an argument, defaulting to dropping levels. I can update if that's something you'd like to try out.

@MilesMcBain
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Leaving factor behaviour as-is for now.

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Retain factor levels (even if unseen) jonocarroll/datapasta
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@jonocarroll @MilesMcBain