drop_labels() about sjmisc HOT 10 CLOSED

I have posted an "example workflow" in my blog, maybe this is helpful, too:
https://strengejacke.wordpress.com/2016/12/22/exploring-the-european-social-survey-ess-pipe-friendly-workflow-with-sjmisc-part-2-rstats-tidyverse/

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I think it is useful to know that if you have defined categories, to see if these have counts or not. Especially if you're not yet familiar with the data, you can see what information is missing, which might be of interest.

Typically, you should call drop_labels() directly after loading the data, if you really don't need the labels:

d <- read_stata('GLES_Vorwahlquerschnitt_ZA5700_v1-0-0.dta')
vars <- select(d, q41, q119a, q192, q11ba) %>% drop_labels()
sjt.xtab(vars$q41, vars$q11ba)

I'm just curious why haven does not tag values as NA - don't these variables have any defined missings in the original Stata file?

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Nope they don't. They are just regular (most of the time negative) numbers.

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It looks like you're using public data - I bet there's an SPSS-file you could use.

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As I am also dealing with this kind of question at the moment: I was wondering if one could directly manipulate the labels by using attributes()? In my case I would like to keep or drop some of them and change others.

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You can use set_labels() with named vectors, or directly attr(x, "labels") <- ....

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Given this case:

> get_labels(dt_imp_org[[9]])
[1] "homme"     "femme"     "pas d'indication"
> attr(dt_imp_org[[9]], "labels")
    homme    femme    pas d'indication 
        1        2                   7 

How can I remove "pas d'indication" but keep the other labels by using set_labels() ?

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You can use remove_labels() to remove specific labels, or set only those labels you like with

set_labels(dt_imp_org[[9]]) <- c(`homme` = 1, `femme` = 2)

Following online-vignette might be interesting for you as well: http://strengejacke.de/sjPlot/sjmisc/

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Btw, @pascaltanner you can also print values in get_labels():

get_labels(dt_imp_org[[9]], include.values = "n")
get_labels(dt_imp_org[[9]], include.values = "p")

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Thank you.

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