Dataset Overview
Europass Survey
June - September 2019
Description
- Name: demographics_indicator
- Number of observations: 294,541
- Number of features: 17
- Description: This dataset brings insights on the demographic distribution of the respondents in the Europass Survey. The CVs of over 350K respondents have been collected, analyzed and aggregated. The analysis provides basic demographic information as well as an estimation of their latest job and educational level based on the established international classifications of ISCO and EQF respectively.
- Sources: Europass Survey: June - September 2019
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| Feature | Name | Description | Form1 | Stat2 | Text3 | |
|---|---|---|---|---|---|---|
| locale | CV Language | Language used to write CV. | ● |
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| country | Country | Country of residence. | ● |
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| age_group1 | Broad Age Group | Broad age groups with three categories. | ● |
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| age_group2 | Narrow Age Group | Narrow age groups with five categories. | ● |
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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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| job_applied_for | Job Applied For | ISCO level 3 classification for job declared in the type of application. | ● | ● |
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| latest_job_isco1 | Latest Job ISCO 1 | ISCO level 1 classification for latest job declared. | ● | ● |
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| latest_job_isco2 | Latest Job ISCO 2 | ISCO level 2 classification for latest job declared. | ● | ● |
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| latest_job_isco3 | 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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| num_jobs | Number of Jobs | Number of jobs declared. | ● |
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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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| is_student | Student Status | Estimation of student status based on enrollment and graduation year. | ● |
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| respondents | Respondents | Number of respondents 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
locale
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 29 |
| * SkillsPassport.Locale missing. |
country
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 12825 ( 4.35% ) |
| Number of unique values | 185 |
| * SkillsPassport…Country.Code missing. |
age_group1
| Feature | Result |
|---|---|
| Variable type | ordered (ordinal) |
| Number of missing values* | 112853 ( 38.31% ) |
| Number of unique values | 4 |
|
* SkillsPassport…Birthdate.Year missing, or over 65 yea rs old. |
age_group2
| Feature | Result |
|---|---|
| Variable type | ordered (ordinal) |
| Number of missing values* | 112458 ( 38.18% ) |
| Number of unique values | 6 |
| * SkillsPassport…Birthdate.Year missing. |
gender
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 132972 ( 45.15% ) |
| Number of unique values | 3 |
| * SkillsPassport…Gender.Code missing. |
nationality
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 145338 ( 49.34% ) |
| Number of unique values | 165 |
| * SkillsPassport…Nationality.Code missing. |
mother_tongue
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 59805 ( 20.30% ) |
| Number of unique values | 63 |
| * Skills.Linguistic.MotherTongue.Description missing. |
job_applied_for
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 191940 ( 65.17% ) |
| Number of unique values | 126 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
latest_job_isco1
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 48180 ( 16.36% ) |
| Number of unique values | 11 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
latest_job_isco2
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 48180 ( 16.36% ) |
| Number of unique values | 43 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
latest_job_isco3
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 48180 ( 16.36% ) |
| Number of unique values | 126 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
is_employed
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 16987 ( 5.77% ) |
| Number of unique values | 3 |
|
* No work experience entries filled, or both WorkExperien ce.Period.From.Year and WorkExperience.Period.To.Year m issing. |
num_jobs
| Feature | Result |
|---|---|
| Variable type | ordered (ordinal) |
| Number of missing values* | 16987 ( 5.77% ) |
| Number of unique values | 11 |
| * No work experience entries filled. |
total_work_years
| Feature | Result |
|---|---|
| Variable type | ordered (ordinal) |
| Number of missing values* | 25487 ( 8.65% ) |
| Number of unique values | 6 |
|
* 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 | ordered (ordinal) |
| Number of missing values* | 90313 ( 30.66% ) |
| Number of unique values | 6 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
is_student
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 15670 ( 5.32% ) |
| Number of unique values | 3 |
|
* No education entries filled, or both Education.Period.F rom.Year and Education.Period.To.Year missing. |
respondents
| Feature | Result |
|---|---|
| Variable type | integer |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 111 |
| Min. | 1 |
| 1st Qu. | 1 |
| Median | 1 |
| Mean | 1.2 |
| 3rd Qu. | 1 |
| Max. | 569 |
| * No missing values permitted. |
