Dataset Overview
Europass Survey
June - September 2019
Description
- Name: qualifications_ngrams
- Number of observations: 6,795,279
- Number of features: 10
- Description: This dataset collects statistics derived from free-text analysis on the education-related responses collected in the Europass Survey. It describes the frequency of one and two-word terms with respect to certain given variables.
- Sources: Europass Survey: June - September 2019
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| Feature | Name | Description | Form1 | Stat2 | Text3 | |
|---|---|---|---|---|---|---|
| term | Term | Unigram or bigram of keywords in a free-text response. | ● | ● |
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| eqf_granted | EQF Granted | EQF classification of a free-text qualification response. | ● | ● |
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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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| 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
term
| Feature | Result |
|---|---|
| Variable type | factor (nominal) |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 79516 |
| * No missing values permitted. |
eqf_granted
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 2654084 ( 39.06% ) |
| Number of unique values | 9 |
|
* Missing features required for estimation, or unidentifi ed from classification algorithm. |
institution_country
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 1398208 ( 20.58% ) |
| Number of unique values | 189 |
| * Education.Organisation…Country.Code missing. |
enrollment_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 531491 ( 7.82% ) |
| Number of unique values | 76 |
| * Education.Period.From.Year missing. |
graduation_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 1623268 ( 23.89% ) |
| 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* | 341258 ( 5.02% ) |
| Number of unique values | 182 |
| * SkillsPassport…Country.Code missing. |
birth_year
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 2215112 ( 32.60% ) |
| Number of unique values | 83 |
| * SkillsPassport…Birthdate.Year missing. |
gender
| Feature | Result |
|---|---|
| Variable type | character (nominal) |
| Number of missing values* | 2846659 ( 41.89% ) |
| Number of unique values | 3 |
| * SkillsPassport…Gender.Code missing. |
responses
| Feature | Result |
|---|---|
| Variable type | integer |
| Number of missing values* | 0 ( 0.00% ) |
| Number of unique values | 354 |
| Min. | 1 |
| 1st Qu. | 1 |
| Median | 1 |
| Mean | 1.31 |
| 3rd Qu. | 1 |
| Max. | 894 |
| * No missing values permitted. |
