Dataset Overview
Europass Survey
June - September 2019
Description
- Name: education_fields_aggregate
- Number of observations: 1,635,196
- Number of features: 16
- Description: This dataset describes aggregate education field-related statistics based on responses collected in the Europass Survey. The values of some of its features derive directly from the Europass CV creation form fields, while others are a result of data analysis upon the given responses. Certain features are simple statistics, while others are mappings of free text to standardized taxonomies made using fuzzy matching techniques.
- Sources: Europass Survey: June - September 2019
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| Feature | Name | Description | Form1 | Stat2 | Text3 | |
|---|---|---|---|---|---|---|
| education_field | Education Field | ISCED FoET classification of a free-text qualification response. | ● |
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| eqf_granted | EQF Granted | EQF classification of a free-text qualification response. | ● | ● |
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| institution | Institution | Educational institution. | ● | ● |
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| institution_country | Institution Country | Country of instutution where qualification was granted. | ● |
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| enrollment_year | Enrollment Year | Year of enrollment. | ● |
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| graduation_year | Graduation Year | Year of graduation. | ● |
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| locale | CV Language | Language used to write CV. | ● |
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| country | Country | Country of residence. | ● |
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| birth_year | Birth Year | Year of birth. | ● |
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| gender | Gender | Female, male or missing value. | ● |
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| nationality | Nationality | Nationality. | ● |
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| mother_tongue | Mother Tongue | Native language. | ● |
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| headline_job | Headline Job | Job-related type of application. | ● |
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| headline_isco | Headline ISCO 3 | ISCO level 3 classification for job declared in the type of application. | ● | ● |
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| eqf_highest | EQF Highest | Highest qualification reported with respect to EQF level (including ongoing). | ● | ● |
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| responses | Responses | Number of responses with a particular combination of values for the above variables. | ● |
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| 1 Variable derives directly from a Europass CV; | ||||||
| 2 Variable is a statistical transformation of one or more Europass CV variables; | ||||||
| 3 Variable is a result of information retrieval using text mining |
Summary Statistics
education_field
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 267900 ( 16.38% ) |
| Number of unique values | 117 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
eqf_granted
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 703449 ( 43.02% ) |
| Number of unique values | 9 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
institution
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 98481 ( 6.02% ) |
| Number of unique values | 2767 |
| * Education.Organisation.Name missing. |
institution_country
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 334107 ( 20.43% ) |
| Number of unique values | 189 |
| * Education.Organisation…Country.Code missing. |
enrollment_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 134377 ( 8.22% ) |
| Number of unique values | 76 |
| * Education.Period.From.Year missing. |
graduation_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 404438 ( 24.73% ) |
| Number of unique values | 72 |
| * Education.Period.To.Year missing. |
locale
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 29 |
| * SkillsPassport.Locale missing. |
country
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 70487 ( 4.31% ) |
| Number of unique values | 182 |
| * SkillsPassport…Country.Code missing. |
birth_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 598008 ( 36.57% ) |
| Number of unique values | 68 |
| * SkillsPassport…Birthdate.Year missing. |
gender
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 731179 ( 44.72% ) |
| Number of unique values | 3 |
| * SkillsPassport…Gender.Code missing. |
nationality
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 773081 ( 47.28% ) |
| Number of unique values | 170 |
| * SkillsPassport…Nationality.Code missing. |
mother_tongue
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 279859 ( 17.11% ) |
| Number of unique values | 63 |
| * Skills.Linguistic.MotherTongue.Description missing. |
headline_job
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 1028686 ( 62.91% ) |
| Number of unique values | 4 |
| * SkillsPassport…Headline.Type.Code missing. |
headline_isco
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 1117475 ( 68.34% ) |
| Number of unique values | 126 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
eqf_highest
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 468924 ( 28.68% ) |
| Number of unique values | 9 |
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* Missing features required for estimation, or unidentifi ed from classification algorithm. |
responses
| Feature | Result |
|---|---|
| Variable type | integer |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 79 |
| Min. | 1 |
| 1st Qu. | 1 |
| Median | 1 |
| Mean | 1.08 |
| 3rd Qu. | 1 |
| Max. | 155 |
| * No missing values permitted. |
