Nothing
tests/testthat/_snaps/labels.md
In volker: High-Level Functions for Tabulating, Charting and Reporting Survey Data
Labels are retrieved
Code
print(volker::codebook(data), n = Inf)
Output
# A tibble: 94 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 sd_age sd numeric Age <NA> <NA>
3 cg_activities cg character Activitie~ <NA> <NA>
4 adopter adopter factor Innovator~ I try new~ I try new ~
5 adopter adopter factor Innovator~ I try new~ I try new ~
6 adopter adopter factor Innovator~ I wait un~ I wait unt~
7 adopter adopter factor Innovator~ I only us~ I only use~
8 adopter adopter factor Innovator~ [no answe~ [no answer]
9 sd_gender sd factor Gender female female
10 sd_gender sd factor Gender male male
11 sd_gender sd factor Gender diverse diverse
12 sd_gender sd factor Gender [no answe~ [no answer]
13 use_private use numeric Usage: in~ 1 never
14 use_private use numeric Usage: in~ 2 rarely
15 use_private use numeric Usage: in~ 3 several ti~
16 use_private use numeric Usage: in~ 4 several ti~
17 use_private use numeric Usage: in~ 5 almost dai~
18 use_work use numeric Usage: in~ 1 never
19 use_work use numeric Usage: in~ 2 rarely
20 use_work use numeric Usage: in~ 3 several ti~
21 use_work use numeric Usage: in~ 4 several ti~
22 use_work use numeric Usage: in~ 5 almost dai~
23 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
24 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
25 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
26 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
27 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
28 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
29 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
30 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
31 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
32 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
33 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
34 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
35 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
36 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
37 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
38 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
39 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
40 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
41 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
42 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
43 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
44 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
45 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
46 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
47 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
48 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
49 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
50 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
51 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
52 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
53 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
54 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
55 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
56 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
57 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
58 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
59 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
60 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
61 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
62 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
63 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
64 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
65 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
66 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
67 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
68 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
69 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
70 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
71 cg_adoption_social_01 cg numeric Expectati~ 1 strongly d~
72 cg_adoption_social_01 cg numeric Expectati~ 2 disagree
73 cg_adoption_social_01 cg numeric Expectati~ 3 neutral
74 cg_adoption_social_01 cg numeric Expectati~ 4 agree
75 cg_adoption_social_01 cg numeric Expectati~ 5 strongly a~
76 cg_adoption_social_01 cg numeric Expectati~ -9 [no answer]
77 cg_adoption_social_02 cg numeric Expectati~ 1 strongly d~
78 cg_adoption_social_02 cg numeric Expectati~ 2 disagree
79 cg_adoption_social_02 cg numeric Expectati~ 3 neutral
80 cg_adoption_social_02 cg numeric Expectati~ 4 agree
81 cg_adoption_social_02 cg numeric Expectati~ 5 strongly a~
82 cg_adoption_social_02 cg numeric Expectati~ -9 [no answer]
83 cg_adoption_social_03 cg numeric Expectati~ 1 strongly d~
84 cg_adoption_social_03 cg numeric Expectati~ 2 disagree
85 cg_adoption_social_03 cg numeric Expectati~ 3 neutral
86 cg_adoption_social_03 cg numeric Expectati~ 4 agree
87 cg_adoption_social_03 cg numeric Expectati~ 5 strongly a~
88 cg_adoption_social_03 cg numeric Expectati~ -9 [no answer]
89 cg_adoption_social_04 cg numeric Expectati~ 1 strongly d~
90 cg_adoption_social_04 cg numeric Expectati~ 2 disagree
91 cg_adoption_social_04 cg numeric Expectati~ 3 neutral
92 cg_adoption_social_04 cg numeric Expectati~ 4 agree
93 cg_adoption_social_04 cg numeric Expectati~ 5 strongly a~
94 cg_adoption_social_04 cg numeric Expectati~ -9 [no answer]
Missing labels make no trouble
Code
.
Output
# A tibble: 12 x 6
item_name item_group item_class item_label value_label value_name
<chr> <chr> <chr> <chr> <lgl> <lgl>
1 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
2 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
3 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
4 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
5 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
6 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
7 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
8 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
9 cg_adoption_social_01 cg numeric cg_adopti~ NA NA
10 cg_adoption_social_02 cg numeric cg_adopti~ NA NA
11 cg_adoption_social_03 cg numeric cg_adopti~ NA NA
12 cg_adoption_social_04 cg numeric cg_adopti~ NA NA
Store and clear the codebook
Code
data %>% volker::labs_store() %>% volker::labs_clear() %>% codebook() %>% print(
n = Inf)
Output
# A tibble: 26 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 use_private use numeric use_priva~ <NA> <NA>
3 use_work use numeric use_work <NA> <NA>
4 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
5 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
6 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
7 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
8 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
9 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
10 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
11 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
12 cg_adoption_social_01 cg numeric cg_adopti~ <NA> <NA>
13 cg_adoption_social_02 cg numeric cg_adopti~ <NA> <NA>
14 cg_adoption_social_03 cg numeric cg_adopti~ <NA> <NA>
15 cg_adoption_social_04 cg numeric cg_adopti~ <NA> <NA>
16 sd_age sd numeric sd_age <NA> <NA>
17 cg_activities cg character cg_activi~ <NA> <NA>
18 adopter adopter factor adopter I try new~ I try new ~
19 adopter adopter factor adopter I try new~ I try new ~
20 adopter adopter factor adopter I wait un~ I wait unt~
21 adopter adopter factor adopter I only us~ I only use~
22 adopter adopter factor adopter [no answe~ [no answer]
23 sd_gender sd factor sd_gender female female
24 sd_gender sd factor sd_gender male male
25 sd_gender sd factor sd_gender diverse diverse
26 sd_gender sd factor sd_gender [no answe~ [no answer]
Store, clear and restore the codebook
Code
data %>% volker::labs_store() %>% volker::labs_clear() %>% volker::labs_restore() %>%
codebook() %>% print(n = Inf)
Output
# A tibble: 94 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 sd_age sd numeric Age <NA> <NA>
3 cg_activities cg character Activitie~ <NA> <NA>
4 adopter adopter factor Innovator~ I try new~ I try new ~
5 adopter adopter factor Innovator~ I try new~ I try new ~
6 adopter adopter factor Innovator~ I wait un~ I wait unt~
7 adopter adopter factor Innovator~ I only us~ I only use~
8 adopter adopter factor Innovator~ [no answe~ [no answer]
9 sd_gender sd factor Gender female female
10 sd_gender sd factor Gender male male
11 sd_gender sd factor Gender diverse diverse
12 sd_gender sd factor Gender [no answe~ [no answer]
13 use_private use numeric Usage: in~ 1 never
14 use_private use numeric Usage: in~ 2 rarely
15 use_private use numeric Usage: in~ 3 several ti~
16 use_private use numeric Usage: in~ 4 several ti~
17 use_private use numeric Usage: in~ 5 almost dai~
18 use_work use numeric Usage: in~ 1 never
19 use_work use numeric Usage: in~ 2 rarely
20 use_work use numeric Usage: in~ 3 several ti~
21 use_work use numeric Usage: in~ 4 several ti~
22 use_work use numeric Usage: in~ 5 almost dai~
23 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
24 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
25 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
26 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
27 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
28 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
29 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
30 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
31 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
32 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
33 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
34 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
35 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
36 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
37 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
38 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
39 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
40 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
41 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
42 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
43 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
44 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
45 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
46 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
47 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
48 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
49 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
50 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
51 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
52 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
53 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
54 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
55 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
56 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
57 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
58 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
59 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
60 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
61 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
62 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
63 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
64 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
65 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
66 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
67 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
68 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
69 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
70 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
71 cg_adoption_social_01 cg numeric Expectati~ 1 strongly d~
72 cg_adoption_social_01 cg numeric Expectati~ 2 disagree
73 cg_adoption_social_01 cg numeric Expectati~ 3 neutral
74 cg_adoption_social_01 cg numeric Expectati~ 4 agree
75 cg_adoption_social_01 cg numeric Expectati~ 5 strongly a~
76 cg_adoption_social_01 cg numeric Expectati~ -9 [no answer]
77 cg_adoption_social_02 cg numeric Expectati~ 1 strongly d~
78 cg_adoption_social_02 cg numeric Expectati~ 2 disagree
79 cg_adoption_social_02 cg numeric Expectati~ 3 neutral
80 cg_adoption_social_02 cg numeric Expectati~ 4 agree
81 cg_adoption_social_02 cg numeric Expectati~ 5 strongly a~
82 cg_adoption_social_02 cg numeric Expectati~ -9 [no answer]
83 cg_adoption_social_03 cg numeric Expectati~ 1 strongly d~
84 cg_adoption_social_03 cg numeric Expectati~ 2 disagree
85 cg_adoption_social_03 cg numeric Expectati~ 3 neutral
86 cg_adoption_social_03 cg numeric Expectati~ 4 agree
87 cg_adoption_social_03 cg numeric Expectati~ 5 strongly a~
88 cg_adoption_social_03 cg numeric Expectati~ -9 [no answer]
89 cg_adoption_social_04 cg numeric Expectati~ 1 strongly d~
90 cg_adoption_social_04 cg numeric Expectati~ 2 disagree
91 cg_adoption_social_04 cg numeric Expectati~ 3 neutral
92 cg_adoption_social_04 cg numeric Expectati~ 4 agree
93 cg_adoption_social_04 cg numeric Expectati~ 5 strongly a~
94 cg_adoption_social_04 cg numeric Expectati~ -9 [no answer]
Item values are replaced and keep their order
Code
levels(dplyr::pull(volker:::labs_replace(dplyr::select(data, adopter), adopter,
volker::codebook(data, adopter)), adopter))
Output
[1] "I try new offers immediately"
[2] "I try new offers rather quickly"
[3] "I wait until offers establish themselves"
[4] "I only use new offers when I have no other choice"
Code
levels(dplyr::pull(volker:::labs_replace(dplyr::mutate(dplyr::select(data,
adopter), adopter = as.character(adopter)), adopter, volker::codebook(data,
adopter)), adopter))
Output
[1] "I try new offers immediately"
[2] "I try new offers rather quickly"
[3] "I wait until offers establish themselves"
[4] "I only use new offers when I have no other choice"
Item values are kept even if they are not in the codebook
Code
dplyr::arrange(volker:::labs_replace(dplyr::mutate(dplyr::distinct(data, from = use_private),
to = from), to, codes), to)
Output
# A tibble: 5 x 2
from to
<dbl> <fct>
1 1 never
2 2 2
3 3 3
4 4 4
5 5 almost daily
The column title is kept when values are replaced
Code
tab_counts(df, values)
Output
|VALS | n| p|
|:-----|--:|----:|
|1 | 1| 33%|
|2 | 1| 33%|
|3 | 1| 33%|
|total | 3| 100%|
n=3.
A common prefix is removed from labels
Code
get_prefix(dplyr::pull(codebook(dplyr::select(data, starts_with("use"))),
item_label))
Output
[1] "Usage"
Code
trim_prefix(dplyr::pull(codebook(dplyr::select(data, starts_with("use"))),
item_label))
Output
[1] "in private context" "in private context"
[3] "in private context" "in private context"
[5] "in private context" "in professional context"
[7] "in professional context" "in professional context"
[9] "in professional context" "in professional context"
Numeric values are relabeled
Code
data %>% labs_apply(cols = starts_with("cg_adoption_advantage"), values = list(
`1` = "Stimme überhaupt nicht zu", `2` = "Stimme nicht zu", `3` = "Unentschieden",
`4` = "Stimme zu", `5` = "Stimme voll und ganz zu")) %>% tab_counts(
starts_with("cg_adoption_advantage"))
Output
|Expectations | Stimme überhaupt nicht zu| Stimme nicht zu| Unentschieden| Stimme zu| Stimme voll und ganz zu| total|
|:-----------------------------------------------------------|-------------------------:|---------------:|-------------:|---------:|-----------------------:|---------:|
|ChatGPT has clear advantages compared to similar offerings. | 6% (6)| 8% (8)| 34% (34)| 37% (37)| 14% (14)| 100% (99)|
|Using ChatGPT brings financial benefits. | 22% (22)| 21% (21)| 29% (29)| 21% (21)| 6% (6)| 100% (99)|
|Using ChatGPT is advantageous in many tasks. | 6% (6)| 10% (10)| 21% (21)| 45% (45)| 17% (17)| 100% (99)|
|Compared to other systems, using ChatGPT is more fun. | 6% (6)| 4% (4)| 35% (35)| 39% (39)| 15% (15)| 100% (99)|
2 missing case(s) omitted.
Factor values are relabeled
Code
tab_counts(data %>% labs_apply(cols = sd_gender, values = list(female = "Weiblich",
male = "Männlich", diverse = "Divers")), sd_gender)
Output
|Gender | n| p|
|:--------|---:|----:|
|Weiblich | 40| 40%|
|Männlich | 60| 59%|
|Divers | 1| 1%|
|total | 101| 100%|
n=101.
Elliptical numeric values are relabeled
Code
codebook(testdata %>% labs_apply(cols = use_private, values = list(`1` = "never",
`2` = "2", `3` = "3", `4` = "4", `5` = "almost daily")), use_private)
Output
# A tibble: 5 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 use_private use numeric Usage: in private co~ 1 never
2 use_private use numeric Usage: in private co~ 2 2
3 use_private use numeric Usage: in private co~ 3 3
4 use_private use numeric Usage: in private co~ 4 4
5 use_private use numeric Usage: in private co~ 5 almost dai~
Labels are wrapped at whitespace and slashes
"Super\nlong/\nshort\nlabel\\\ns"
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Labels are retrieved
Code
print(volker::codebook(data), n = Inf)
Output
# A tibble: 94 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 sd_age sd numeric Age <NA> <NA>
3 cg_activities cg character Activitie~ <NA> <NA>
4 adopter adopter factor Innovator~ I try new~ I try new ~
5 adopter adopter factor Innovator~ I try new~ I try new ~
6 adopter adopter factor Innovator~ I wait un~ I wait unt~
7 adopter adopter factor Innovator~ I only us~ I only use~
8 adopter adopter factor Innovator~ [no answe~ [no answer]
9 sd_gender sd factor Gender female female
10 sd_gender sd factor Gender male male
11 sd_gender sd factor Gender diverse diverse
12 sd_gender sd factor Gender [no answe~ [no answer]
13 use_private use numeric Usage: in~ 1 never
14 use_private use numeric Usage: in~ 2 rarely
15 use_private use numeric Usage: in~ 3 several ti~
16 use_private use numeric Usage: in~ 4 several ti~
17 use_private use numeric Usage: in~ 5 almost dai~
18 use_work use numeric Usage: in~ 1 never
19 use_work use numeric Usage: in~ 2 rarely
20 use_work use numeric Usage: in~ 3 several ti~
21 use_work use numeric Usage: in~ 4 several ti~
22 use_work use numeric Usage: in~ 5 almost dai~
23 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
24 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
25 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
26 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
27 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
28 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
29 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
30 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
31 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
32 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
33 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
34 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
35 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
36 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
37 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
38 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
39 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
40 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
41 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
42 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
43 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
44 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
45 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
46 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
47 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
48 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
49 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
50 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
51 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
52 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
53 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
54 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
55 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
56 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
57 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
58 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
59 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
60 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
61 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
62 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
63 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
64 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
65 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
66 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
67 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
68 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
69 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
70 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
71 cg_adoption_social_01 cg numeric Expectati~ 1 strongly d~
72 cg_adoption_social_01 cg numeric Expectati~ 2 disagree
73 cg_adoption_social_01 cg numeric Expectati~ 3 neutral
74 cg_adoption_social_01 cg numeric Expectati~ 4 agree
75 cg_adoption_social_01 cg numeric Expectati~ 5 strongly a~
76 cg_adoption_social_01 cg numeric Expectati~ -9 [no answer]
77 cg_adoption_social_02 cg numeric Expectati~ 1 strongly d~
78 cg_adoption_social_02 cg numeric Expectati~ 2 disagree
79 cg_adoption_social_02 cg numeric Expectati~ 3 neutral
80 cg_adoption_social_02 cg numeric Expectati~ 4 agree
81 cg_adoption_social_02 cg numeric Expectati~ 5 strongly a~
82 cg_adoption_social_02 cg numeric Expectati~ -9 [no answer]
83 cg_adoption_social_03 cg numeric Expectati~ 1 strongly d~
84 cg_adoption_social_03 cg numeric Expectati~ 2 disagree
85 cg_adoption_social_03 cg numeric Expectati~ 3 neutral
86 cg_adoption_social_03 cg numeric Expectati~ 4 agree
87 cg_adoption_social_03 cg numeric Expectati~ 5 strongly a~
88 cg_adoption_social_03 cg numeric Expectati~ -9 [no answer]
89 cg_adoption_social_04 cg numeric Expectati~ 1 strongly d~
90 cg_adoption_social_04 cg numeric Expectati~ 2 disagree
91 cg_adoption_social_04 cg numeric Expectati~ 3 neutral
92 cg_adoption_social_04 cg numeric Expectati~ 4 agree
93 cg_adoption_social_04 cg numeric Expectati~ 5 strongly a~
94 cg_adoption_social_04 cg numeric Expectati~ -9 [no answer]
Missing labels make no trouble
Code
.
Output
# A tibble: 12 x 6
item_name item_group item_class item_label value_label value_name
<chr> <chr> <chr> <chr> <lgl> <lgl>
1 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
2 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
3 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
4 cg_adoption_advantag~ cg numeric cg_adopti~ NA NA
5 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
6 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
7 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
8 cg_adoption_fearofus~ cg numeric cg_adopti~ NA NA
9 cg_adoption_social_01 cg numeric cg_adopti~ NA NA
10 cg_adoption_social_02 cg numeric cg_adopti~ NA NA
11 cg_adoption_social_03 cg numeric cg_adopti~ NA NA
12 cg_adoption_social_04 cg numeric cg_adopti~ NA NA
Store and clear the codebook
Code
data %>% volker::labs_store() %>% volker::labs_clear() %>% codebook() %>% print(
n = Inf)
Output
# A tibble: 26 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 use_private use numeric use_priva~ <NA> <NA>
3 use_work use numeric use_work <NA> <NA>
4 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
5 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
6 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
7 cg_adoption_advantag~ cg numeric cg_adopti~ <NA> <NA>
8 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
9 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
10 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
11 cg_adoption_fearofus~ cg numeric cg_adopti~ <NA> <NA>
12 cg_adoption_social_01 cg numeric cg_adopti~ <NA> <NA>
13 cg_adoption_social_02 cg numeric cg_adopti~ <NA> <NA>
14 cg_adoption_social_03 cg numeric cg_adopti~ <NA> <NA>
15 cg_adoption_social_04 cg numeric cg_adopti~ <NA> <NA>
16 sd_age sd numeric sd_age <NA> <NA>
17 cg_activities cg character cg_activi~ <NA> <NA>
18 adopter adopter factor adopter I try new~ I try new ~
19 adopter adopter factor adopter I try new~ I try new ~
20 adopter adopter factor adopter I wait un~ I wait unt~
21 adopter adopter factor adopter I only us~ I only use~
22 adopter adopter factor adopter [no answe~ [no answer]
23 sd_gender sd factor sd_gender female female
24 sd_gender sd factor sd_gender male male
25 sd_gender sd factor sd_gender diverse diverse
26 sd_gender sd factor sd_gender [no answe~ [no answer]
Store, clear and restore the codebook
Code
data %>% volker::labs_store() %>% volker::labs_clear() %>% volker::labs_restore() %>%
codebook() %>% print(n = Inf)
Output
# A tibble: 94 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 case case numeric case <NA> <NA>
2 sd_age sd numeric Age <NA> <NA>
3 cg_activities cg character Activitie~ <NA> <NA>
4 adopter adopter factor Innovator~ I try new~ I try new ~
5 adopter adopter factor Innovator~ I try new~ I try new ~
6 adopter adopter factor Innovator~ I wait un~ I wait unt~
7 adopter adopter factor Innovator~ I only us~ I only use~
8 adopter adopter factor Innovator~ [no answe~ [no answer]
9 sd_gender sd factor Gender female female
10 sd_gender sd factor Gender male male
11 sd_gender sd factor Gender diverse diverse
12 sd_gender sd factor Gender [no answe~ [no answer]
13 use_private use numeric Usage: in~ 1 never
14 use_private use numeric Usage: in~ 2 rarely
15 use_private use numeric Usage: in~ 3 several ti~
16 use_private use numeric Usage: in~ 4 several ti~
17 use_private use numeric Usage: in~ 5 almost dai~
18 use_work use numeric Usage: in~ 1 never
19 use_work use numeric Usage: in~ 2 rarely
20 use_work use numeric Usage: in~ 3 several ti~
21 use_work use numeric Usage: in~ 4 several ti~
22 use_work use numeric Usage: in~ 5 almost dai~
23 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
24 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
25 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
26 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
27 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
28 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
29 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
30 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
31 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
32 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
33 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
34 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
35 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
36 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
37 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
38 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
39 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
40 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
41 cg_adoption_advantag~ cg numeric Expectati~ 1 strongly d~
42 cg_adoption_advantag~ cg numeric Expectati~ 2 disagree
43 cg_adoption_advantag~ cg numeric Expectati~ 3 neutral
44 cg_adoption_advantag~ cg numeric Expectati~ 4 agree
45 cg_adoption_advantag~ cg numeric Expectati~ 5 strongly a~
46 cg_adoption_advantag~ cg numeric Expectati~ -9 [no answer]
47 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
48 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
49 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
50 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
51 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
52 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
53 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
54 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
55 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
56 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
57 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
58 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
59 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
60 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
61 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
62 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
63 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
64 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
65 cg_adoption_fearofus~ cg numeric Expectati~ 1 strongly d~
66 cg_adoption_fearofus~ cg numeric Expectati~ 2 disagree
67 cg_adoption_fearofus~ cg numeric Expectati~ 3 neutral
68 cg_adoption_fearofus~ cg numeric Expectati~ 4 agree
69 cg_adoption_fearofus~ cg numeric Expectati~ 5 strongly a~
70 cg_adoption_fearofus~ cg numeric Expectati~ -9 [no answer]
71 cg_adoption_social_01 cg numeric Expectati~ 1 strongly d~
72 cg_adoption_social_01 cg numeric Expectati~ 2 disagree
73 cg_adoption_social_01 cg numeric Expectati~ 3 neutral
74 cg_adoption_social_01 cg numeric Expectati~ 4 agree
75 cg_adoption_social_01 cg numeric Expectati~ 5 strongly a~
76 cg_adoption_social_01 cg numeric Expectati~ -9 [no answer]
77 cg_adoption_social_02 cg numeric Expectati~ 1 strongly d~
78 cg_adoption_social_02 cg numeric Expectati~ 2 disagree
79 cg_adoption_social_02 cg numeric Expectati~ 3 neutral
80 cg_adoption_social_02 cg numeric Expectati~ 4 agree
81 cg_adoption_social_02 cg numeric Expectati~ 5 strongly a~
82 cg_adoption_social_02 cg numeric Expectati~ -9 [no answer]
83 cg_adoption_social_03 cg numeric Expectati~ 1 strongly d~
84 cg_adoption_social_03 cg numeric Expectati~ 2 disagree
85 cg_adoption_social_03 cg numeric Expectati~ 3 neutral
86 cg_adoption_social_03 cg numeric Expectati~ 4 agree
87 cg_adoption_social_03 cg numeric Expectati~ 5 strongly a~
88 cg_adoption_social_03 cg numeric Expectati~ -9 [no answer]
89 cg_adoption_social_04 cg numeric Expectati~ 1 strongly d~
90 cg_adoption_social_04 cg numeric Expectati~ 2 disagree
91 cg_adoption_social_04 cg numeric Expectati~ 3 neutral
92 cg_adoption_social_04 cg numeric Expectati~ 4 agree
93 cg_adoption_social_04 cg numeric Expectati~ 5 strongly a~
94 cg_adoption_social_04 cg numeric Expectati~ -9 [no answer]
Item values are replaced and keep their order
Code
levels(dplyr::pull(volker:::labs_replace(dplyr::select(data, adopter), adopter,
volker::codebook(data, adopter)), adopter))
Output
[1] "I try new offers immediately"
[2] "I try new offers rather quickly"
[3] "I wait until offers establish themselves"
[4] "I only use new offers when I have no other choice"
Code
levels(dplyr::pull(volker:::labs_replace(dplyr::mutate(dplyr::select(data,
adopter), adopter = as.character(adopter)), adopter, volker::codebook(data,
adopter)), adopter))
Output
[1] "I try new offers immediately"
[2] "I try new offers rather quickly"
[3] "I wait until offers establish themselves"
[4] "I only use new offers when I have no other choice"
Item values are kept even if they are not in the codebook
Code
dplyr::arrange(volker:::labs_replace(dplyr::mutate(dplyr::distinct(data, from = use_private),
to = from), to, codes), to)
Output
# A tibble: 5 x 2
from to
<dbl> <fct>
1 1 never
2 2 2
3 3 3
4 4 4
5 5 almost daily
The column title is kept when values are replaced
Code
tab_counts(df, values)
Output
|VALS | n| p|
|:-----|--:|----:|
|1 | 1| 33%|
|2 | 1| 33%|
|3 | 1| 33%|
|total | 3| 100%|
n=3.
A common prefix is removed from labels
Code
get_prefix(dplyr::pull(codebook(dplyr::select(data, starts_with("use"))),
item_label))
Output
[1] "Usage"
Code
trim_prefix(dplyr::pull(codebook(dplyr::select(data, starts_with("use"))),
item_label))
Output
[1] "in private context" "in private context"
[3] "in private context" "in private context"
[5] "in private context" "in professional context"
[7] "in professional context" "in professional context"
[9] "in professional context" "in professional context"
Numeric values are relabeled
Code
data %>% labs_apply(cols = starts_with("cg_adoption_advantage"), values = list(
`1` = "Stimme überhaupt nicht zu", `2` = "Stimme nicht zu", `3` = "Unentschieden",
`4` = "Stimme zu", `5` = "Stimme voll und ganz zu")) %>% tab_counts(
starts_with("cg_adoption_advantage"))
Output
|Expectations | Stimme überhaupt nicht zu| Stimme nicht zu| Unentschieden| Stimme zu| Stimme voll und ganz zu| total|
|:-----------------------------------------------------------|-------------------------:|---------------:|-------------:|---------:|-----------------------:|---------:|
|ChatGPT has clear advantages compared to similar offerings. | 6% (6)| 8% (8)| 34% (34)| 37% (37)| 14% (14)| 100% (99)|
|Using ChatGPT brings financial benefits. | 22% (22)| 21% (21)| 29% (29)| 21% (21)| 6% (6)| 100% (99)|
|Using ChatGPT is advantageous in many tasks. | 6% (6)| 10% (10)| 21% (21)| 45% (45)| 17% (17)| 100% (99)|
|Compared to other systems, using ChatGPT is more fun. | 6% (6)| 4% (4)| 35% (35)| 39% (39)| 15% (15)| 100% (99)|
2 missing case(s) omitted.
Factor values are relabeled
Code
tab_counts(data %>% labs_apply(cols = sd_gender, values = list(female = "Weiblich",
male = "Männlich", diverse = "Divers")), sd_gender)
Output
|Gender | n| p|
|:--------|---:|----:|
|Weiblich | 40| 40%|
|Männlich | 60| 59%|
|Divers | 1| 1%|
|total | 101| 100%|
n=101.
Elliptical numeric values are relabeled
Code
codebook(testdata %>% labs_apply(cols = use_private, values = list(`1` = "never",
`2` = "2", `3` = "3", `4` = "4", `5` = "almost daily")), use_private)
Output
# A tibble: 5 x 6
item_name item_group item_class item_label value_name value_label
<chr> <chr> <chr> <chr> <chr> <chr>
1 use_private use numeric Usage: in private co~ 1 never
2 use_private use numeric Usage: in private co~ 2 2
3 use_private use numeric Usage: in private co~ 3 3
4 use_private use numeric Usage: in private co~ 4 4
5 use_private use numeric Usage: in private co~ 5 almost dai~
Labels are wrapped at whitespace and slashes
"Super\nlong/\nshort\nlabel\\\ns"
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