Dataset Overview
Europass Survey
June - September 2019
Description
- Name: skills_aggregate
- Number of observations: 1,298,207
- Number of features: 16
- Description: This dataset describes aggregate skill-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 | |
|---|---|---|---|---|---|---|
| skill_type | Skill Category | Broad category of a classified skill response. | ● |
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| skill_value | Skill Title | ESCO classification for skill free-text or drop down response. | ● | ● |
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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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| latest_job_esco | Latest Job ESCO | ESCO classification for latest job declared. | ● | ● |
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| latest_job_isco | Latest Job ISCO 3 | ISCO level 3 classification for latest job declared. | ● | ● |
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| is_employed | Employment Status | Estimation of employment status based on recruitment and termination year. | ● |
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| total_work_years | Total Work Years | Sum of all work years. | ● |
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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
skill_type
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 10 |
| * No missing values permitted. |
skill_value
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 8066 |
| * No missing values permitted. |
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* | 51073 ( 3.93% ) |
| Number of unique values | 183 |
| * SkillsPassport…Country.Code missing. |
birth_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 488516 ( 37.63% ) |
| Number of unique values | 84 |
| * SkillsPassport…Birthdate.Year missing. |
gender
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 575778 ( 44.35% ) |
| Number of unique values | 3 |
| * SkillsPassport…Gender.Code missing. |
nationality
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 618576 ( 47.65% ) |
| Number of unique values | 168 |
| * SkillsPassport…Nationality.Code missing. |
mother_tongue
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 137078 ( 10.56% ) |
| Number of unique values | 63 |
| * Skills.Linguistic.MotherTongue.Description missing. |
headline_job
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 799755 ( 61.60% ) |
| Number of unique values | 4 |
| * SkillsPassport…Headline.Type.Code missing. |
headline_isco
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 874841 ( 67.39% ) |
| Number of unique values | 126 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
latest_job_esco
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 179741 ( 13.85% ) |
| Number of unique values | 2859 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
latest_job_isco
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 179741 ( 13.85% ) |
| Number of unique values | 126 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
is_employed
| Feature | Result |
|---|---|
| Variable type | logical |
| Number of missing values* | 57792 ( 4.45% ) |
| Number of unique values | 3 |
|
* No work experience entries filled, or both WorkExperien ce.Period.From.Year and WorkExperience.Period.To.Year m issing. |
total_work_years
| Feature | Result |
|---|---|
| Variable type | numeric |
| Number of missing values* | 85702 ( 6.60% ) |
| Number of unique values | 173 |
| Min. | 1 |
| 1st Qu. | 4 |
| Median | 7 |
| Mean | 10.44 |
| 3rd Qu. | 14 |
| Max. | 312 |
| NA’s | 85702 |
|
* No work experience entries filled, or both WorkExperien ce.Period.From.Year and WorkExperience.Period.To.Year m issing. |
eqf_highest
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 353536 ( 27.23% ) |
| Number of unique values | 9 |
|
* 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 | 128 |
| Min. | 1 |
| 1st Qu. | 1 |
| Median | 1 |
| Mean | 1.06 |
| 3rd Qu. | 1 |
| Max. | 601 |
| * No missing values permitted. |
