Description

Name: qualifications_progression_aggregate
Number of observations: 1,658,787
Number of features: 13
Description: This dataset describes aggregate education level progression 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
from_education_field	From Education Field	ISCED FoET classification of a free-text qualification response for initial education field.	●		●
to_education_field	To Education Field	ISCED FoET classification of a free-text qualification response for subsequent education field.	●		●
eqf_granted	EQF Granted	EQF classification of a free-text qualification response.	●		●
institution	Institution	Educational institution.		●	●
institution_country	Institution Country	Country of instutution where qualification was granted.	●
enrollment_year	Enrollment Year	Year of enrollment.	●
graduation_year	Graduation Year	Year of graduation.	●
locale	CV Language	Language used to write CV.	●
country	Country	Country of residence.	●
birth_year	Birth Year	Year of birth.	●
gender	Gender	Female, male or missing value.	●
nationality	Nationality	Nationality.	●
responses	Responses	Number of responses with a particular combination of values for the above variables.		●
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

Feature	Result
Variable type	factor (nominal)
Number of missing values*	0 ( 0.00% )
Number of unique values	116
^* Missing features required for estimation, or unidentifi ed from classification algorithm.

Feature	Result
Variable type	factor (nominal)
Number of missing values*	0 ( 0.00% )
Number of unique values	116
^* Missing features required for estimation, or unidentifi ed from classification algorithm.

Feature	Result
Variable type	character (nominal)
Number of missing values*	775104 ( 46.73% )
Number of unique values	9
^* Missing features required for estimation, or unidentifi ed from classification algorithm.

Feature	Result
Variable type	factor (nominal)
Number of missing values*	80538 ( 4.86% )
Number of unique values	2747
^* Education.Organisation.Name missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	344325 ( 20.76% )
Number of unique values	180
^* Education.Organisation…Country.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	0 ( 0.00% )
Number of unique values	63
^* Education.Period.From.Year missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	309785 ( 18.68% )
Number of unique values	62
^* Education.Period.To.Year missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	0 ( 0.00% )
Number of unique values	29
^* SkillsPassport.Locale missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	73145 ( 4.41% )
Number of unique values	178
^* SkillsPassport…Country.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	582916 ( 35.14% )
Number of unique values	59
^* SkillsPassport…Birthdate.Year missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	733538 ( 44.22% )
Number of unique values	3
^* SkillsPassport…Gender.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	755481 ( 45.54% )
Number of unique values	160
^* SkillsPassport…Nationality.Code missing.