README.md
In maelle/eml.tools: Helps Using EML Metadata
Package in construction for using EML (Ecological Metadata Language) in data analysis, currently only one function. For creating a new EML, see the rOpenSci EML package. This package will take advantage from the fact that EML is machine readable to make some analysis steps easier. Any suggestion or contribution is welcome, but please note that this package has a code of conduct.
Translating factors into their meanings
When the EML only has one table
library("eml.tools")
data("animals_eml")
data("animals_data")
animals_data
## animal age size
## 1 A A 50.902957
## 2 A A 48.834863
## 3 A A 51.521256
## 4 A A 50.919211
## 5 A A 50.801015
## 6 A B 80.519204
## 7 A B 80.889112
## 8 A B 79.751250
## 9 A B 80.310155
## 10 A B 79.971646
## 11 B A 10.609813
## 12 B A 9.782217
## 13 B A 9.753498
## 14 B A 10.371456
## 15 B A 10.487272
## 16 B B 20.630848
## 17 B B 19.361207
## 18 B B 18.735406
## 19 B B 19.214350
## 20 B B 21.500681
eml_translate_factors(df = animals_data, eml = animals_eml, keep = FALSE)
## # A tibble: 20 × 3
## size animal age
## <dbl> <chr> <chr>
## 1 50.902957 monstercat juvenile
## 2 48.834863 monstercat juvenile
## 3 51.521256 monstercat juvenile
## 4 50.919211 monstercat juvenile
## 5 50.801015 monstercat juvenile
## 6 80.519204 monstercat adult
## 7 80.889112 monstercat adult
## 8 79.751250 monstercat adult
## 9 80.310155 monstercat adult
## 10 79.971646 monstercat adult
## 11 10.609813 monsterdog juvenile
## 12 9.782217 monsterdog juvenile
## 13 9.753498 monsterdog juvenile
## 14 10.371456 monsterdog juvenile
## 15 10.487272 monsterdog juvenile
## 16 20.630848 monsterdog adult
## 17 19.361207 monsterdog adult
## 18 18.735406 monsterdog adult
## 19 19.214350 monsterdog adult
## 20 21.500681 monsterdog adult
eml_translate_factors(df = animals_data, eml = animals_eml, keep = TRUE)
## # A tibble: 20 × 5
## animal age size animal_meaning age_meaning
## <chr> <chr> <dbl> <chr> <chr>
## 1 A A 50.902957 monstercat juvenile
## 2 A A 48.834863 monstercat juvenile
## 3 A A 51.521256 monstercat juvenile
## 4 A A 50.919211 monstercat juvenile
## 5 A A 50.801015 monstercat juvenile
## 6 A B 80.519204 monstercat adult
## 7 A B 80.889112 monstercat adult
## 8 A B 79.751250 monstercat adult
## 9 A B 80.310155 monstercat adult
## 10 A B 79.971646 monstercat adult
## 11 B A 10.609813 monsterdog juvenile
## 12 B A 9.782217 monsterdog juvenile
## 13 B A 9.753498 monsterdog juvenile
## 14 B A 10.371456 monsterdog juvenile
## 15 B A 10.487272 monsterdog juvenile
## 16 B B 20.630848 monsterdog adult
## 17 B B 19.361207 monsterdog adult
## 18 B B 18.735406 monsterdog adult
## 19 B B 19.214350 monsterdog adult
## 20 B B 21.500681 monsterdog adult
When the EML only has several tables
This is the case if the EML documents a database. In this case, we need to use the entityName of the table for which we want to perform the translation.
library("eml.tools")
data("animals_db_eml")
data("animals_data")
animals_data
## # A tibble: 20 × 3
## animal age size
## <fctr> <fctr> <dbl>
## 1 A A 50.902957
## 2 A A 48.834863
## 3 A A 51.521256
## 4 A A 50.919211
## 5 A A 50.801015
## 6 A B 80.519204
## 7 A B 80.889112
## 8 A B 79.751250
## 9 A B 80.310155
## 10 A B 79.971646
## 11 B A 10.609813
## 12 B A 9.782217
## 13 B A 9.753498
## 14 B A 10.371456
## 15 B A 10.487272
## 16 B B 20.630848
## 17 B B 19.361207
## 18 B B 18.735406
## 19 B B 19.214350
## 20 B B 21.500681
eml_translate_factors(df = animals_data,
eml = animals_db_eml,
which_table = "english_animals",
keep = FALSE)
## # A tibble: 20 × 3
## size animal age
## <dbl> <chr> <chr>
## 1 50.902957 monstercat juvenile
## 2 48.834863 monstercat juvenile
## 3 51.521256 monstercat juvenile
## 4 50.919211 monstercat juvenile
## 5 50.801015 monstercat juvenile
## 6 80.519204 monstercat adult
## 7 80.889112 monstercat adult
## 8 79.751250 monstercat adult
## 9 80.310155 monstercat adult
## 10 79.971646 monstercat adult
## 11 10.609813 monsterdog juvenile
## 12 9.782217 monsterdog juvenile
## 13 9.753498 monsterdog juvenile
## 14 10.371456 monsterdog juvenile
## 15 10.487272 monsterdog juvenile
## 16 20.630848 monsterdog adult
## 17 19.361207 monsterdog adult
## 18 18.735406 monsterdog adult
## 19 19.214350 monsterdog adult
## 20 21.500681 monsterdog adult
eml_translate_factors(df = animals_data,
eml = animals_db_eml,
which_table = "english_animals",
keep = TRUE)
## # A tibble: 20 × 5
## animal age size animal_meaning age_meaning
## <chr> <chr> <dbl> <chr> <chr>
## 1 A A 50.902957 monstercat juvenile
## 2 A A 48.834863 monstercat juvenile
## 3 A A 51.521256 monstercat juvenile
## 4 A A 50.919211 monstercat juvenile
## 5 A A 50.801015 monstercat juvenile
## 6 A B 80.519204 monstercat adult
## 7 A B 80.889112 monstercat adult
## 8 A B 79.751250 monstercat adult
## 9 A B 80.310155 monstercat adult
## 10 A B 79.971646 monstercat adult
## 11 B A 10.609813 monsterdog juvenile
## 12 B A 9.782217 monsterdog juvenile
## 13 B A 9.753498 monsterdog juvenile
## 14 B A 10.371456 monsterdog juvenile
## 15 B A 10.487272 monsterdog juvenile
## 16 B B 20.630848 monsterdog adult
## 17 B B 19.361207 monsterdog adult
## 18 B B 18.735406 monsterdog adult
## 19 B B 19.214350 monsterdog adult
## 20 B B 21.500681 monsterdog adult
maelle/eml.tools documentation built on May 21, 2019, 11:04 a.m.
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Package in construction for using EML (Ecological Metadata Language) in data analysis, currently only one function. For creating a new EML, see the rOpenSci EML package. This package will take advantage from the fact that EML is machine readable to make some analysis steps easier. Any suggestion or contribution is welcome, but please note that this package has a code of conduct.
Translating factors into their meanings
When the EML only has one table
library("eml.tools")
data("animals_eml")
data("animals_data")
animals_data
## animal age size
## 1 A A 50.902957
## 2 A A 48.834863
## 3 A A 51.521256
## 4 A A 50.919211
## 5 A A 50.801015
## 6 A B 80.519204
## 7 A B 80.889112
## 8 A B 79.751250
## 9 A B 80.310155
## 10 A B 79.971646
## 11 B A 10.609813
## 12 B A 9.782217
## 13 B A 9.753498
## 14 B A 10.371456
## 15 B A 10.487272
## 16 B B 20.630848
## 17 B B 19.361207
## 18 B B 18.735406
## 19 B B 19.214350
## 20 B B 21.500681
eml_translate_factors(df = animals_data, eml = animals_eml, keep = FALSE)
## # A tibble: 20 × 3
## size animal age
## <dbl> <chr> <chr>
## 1 50.902957 monstercat juvenile
## 2 48.834863 monstercat juvenile
## 3 51.521256 monstercat juvenile
## 4 50.919211 monstercat juvenile
## 5 50.801015 monstercat juvenile
## 6 80.519204 monstercat adult
## 7 80.889112 monstercat adult
## 8 79.751250 monstercat adult
## 9 80.310155 monstercat adult
## 10 79.971646 monstercat adult
## 11 10.609813 monsterdog juvenile
## 12 9.782217 monsterdog juvenile
## 13 9.753498 monsterdog juvenile
## 14 10.371456 monsterdog juvenile
## 15 10.487272 monsterdog juvenile
## 16 20.630848 monsterdog adult
## 17 19.361207 monsterdog adult
## 18 18.735406 monsterdog adult
## 19 19.214350 monsterdog adult
## 20 21.500681 monsterdog adult
eml_translate_factors(df = animals_data, eml = animals_eml, keep = TRUE)
## # A tibble: 20 × 5
## animal age size animal_meaning age_meaning
## <chr> <chr> <dbl> <chr> <chr>
## 1 A A 50.902957 monstercat juvenile
## 2 A A 48.834863 monstercat juvenile
## 3 A A 51.521256 monstercat juvenile
## 4 A A 50.919211 monstercat juvenile
## 5 A A 50.801015 monstercat juvenile
## 6 A B 80.519204 monstercat adult
## 7 A B 80.889112 monstercat adult
## 8 A B 79.751250 monstercat adult
## 9 A B 80.310155 monstercat adult
## 10 A B 79.971646 monstercat adult
## 11 B A 10.609813 monsterdog juvenile
## 12 B A 9.782217 monsterdog juvenile
## 13 B A 9.753498 monsterdog juvenile
## 14 B A 10.371456 monsterdog juvenile
## 15 B A 10.487272 monsterdog juvenile
## 16 B B 20.630848 monsterdog adult
## 17 B B 19.361207 monsterdog adult
## 18 B B 18.735406 monsterdog adult
## 19 B B 19.214350 monsterdog adult
## 20 B B 21.500681 monsterdog adult
When the EML only has several tables
This is the case if the EML documents a database. In this case, we need to use the entityName of the table for which we want to perform the translation.
library("eml.tools")
data("animals_db_eml")
data("animals_data")
animals_data
## # A tibble: 20 × 3
## animal age size
## <fctr> <fctr> <dbl>
## 1 A A 50.902957
## 2 A A 48.834863
## 3 A A 51.521256
## 4 A A 50.919211
## 5 A A 50.801015
## 6 A B 80.519204
## 7 A B 80.889112
## 8 A B 79.751250
## 9 A B 80.310155
## 10 A B 79.971646
## 11 B A 10.609813
## 12 B A 9.782217
## 13 B A 9.753498
## 14 B A 10.371456
## 15 B A 10.487272
## 16 B B 20.630848
## 17 B B 19.361207
## 18 B B 18.735406
## 19 B B 19.214350
## 20 B B 21.500681
eml_translate_factors(df = animals_data,
eml = animals_db_eml,
which_table = "english_animals",
keep = FALSE)
## # A tibble: 20 × 3
## size animal age
## <dbl> <chr> <chr>
## 1 50.902957 monstercat juvenile
## 2 48.834863 monstercat juvenile
## 3 51.521256 monstercat juvenile
## 4 50.919211 monstercat juvenile
## 5 50.801015 monstercat juvenile
## 6 80.519204 monstercat adult
## 7 80.889112 monstercat adult
## 8 79.751250 monstercat adult
## 9 80.310155 monstercat adult
## 10 79.971646 monstercat adult
## 11 10.609813 monsterdog juvenile
## 12 9.782217 monsterdog juvenile
## 13 9.753498 monsterdog juvenile
## 14 10.371456 monsterdog juvenile
## 15 10.487272 monsterdog juvenile
## 16 20.630848 monsterdog adult
## 17 19.361207 monsterdog adult
## 18 18.735406 monsterdog adult
## 19 19.214350 monsterdog adult
## 20 21.500681 monsterdog adult
eml_translate_factors(df = animals_data,
eml = animals_db_eml,
which_table = "english_animals",
keep = TRUE)
## # A tibble: 20 × 5
## animal age size animal_meaning age_meaning
## <chr> <chr> <dbl> <chr> <chr>
## 1 A A 50.902957 monstercat juvenile
## 2 A A 48.834863 monstercat juvenile
## 3 A A 51.521256 monstercat juvenile
## 4 A A 50.919211 monstercat juvenile
## 5 A A 50.801015 monstercat juvenile
## 6 A B 80.519204 monstercat adult
## 7 A B 80.889112 monstercat adult
## 8 A B 79.751250 monstercat adult
## 9 A B 80.310155 monstercat adult
## 10 A B 79.971646 monstercat adult
## 11 B A 10.609813 monsterdog juvenile
## 12 B A 9.782217 monsterdog juvenile
## 13 B A 9.753498 monsterdog juvenile
## 14 B A 10.371456 monsterdog juvenile
## 15 B A 10.487272 monsterdog juvenile
## 16 B B 20.630848 monsterdog adult
## 17 B B 19.361207 monsterdog adult
## 18 B B 18.735406 monsterdog adult
## 19 B B 19.214350 monsterdog adult
## 20 B B 21.500681 monsterdog adult
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