Description

Name: occupations_aggregate
Number of observations: 1,213,257
Number of features: 13
Description: This dataset describes aggregate job-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
job_esco	Job ESCO	ESCO classification for job.	●		●
job_isco	Job ISCO 3	ISCO level 3 classification for job.	●		●
recruitment_year	Recruitment Year	Year of recruitment.	●
termination_year	Termination Year	Year of termination.	●
preceding_work_years	Preceding Work Years	Total work years until recruitment date of a particular job.		●
eqf_level	EQF Level	Highest education level mapped to EQF at the time of a particular job.	●		●
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.	●
mother_tongue	Mother Tongue	Native language.	●
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	character (nominal)
Number of missing values*	143911 ( 11.86% )
Number of unique values	2934
^* Missing features required for estimation, or unidentifi ed from classification algorithm.

Feature	Result
Variable type	character (nominal)
Number of missing values*	143911 ( 11.86% )
Number of unique values	126
^* Missing features required for estimation, or unidentifi ed from classification algorithm.

Feature	Result
Variable type	character (nominal)
Number of missing values*	21136 ( 1.74% )
Number of unique values	61
^* WorkExperience.Period.From.Year missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	227035 ( 18.71% )
Number of unique values	61
^* Education.Period.To.Year missing.

Feature	Result
Variable type	numeric
Number of missing values*	21136 ( 1.74% )
Number of unique values	217
Min.	0
1st Qu.	1
Median	3
Mean	6.36
3rd Qu.	8
Max.	291
NA’s	21136
^* No other work experience entries filled, or both WorkEx perience.Period.From.Year and WorkExperience.Period.To. Year missing from prior jobs.

Feature	Result
Variable type	character (nominal)
Number of missing values*	230911 ( 19.03% )
Number of unique values	9
^* Missing features required for estimation, or unidentifi ed from classification algorithm, or either of WorkExpe rience.Period.From.Year or Education.Period.To.Year mis sing.

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*	55818 ( 4.60% )
Number of unique values	184
^* SkillsPassport…Country.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	450961 ( 37.17% )
Number of unique values	84
^* SkillsPassport…Birthdate.Year missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	546896 ( 45.08% )
Number of unique values	3
^* SkillsPassport…Gender.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	584753 ( 48.20% )
Number of unique values	169
^* SkillsPassport…Nationality.Code missing.

Feature	Result
Variable type	character (nominal)
Number of missing values*	209509 ( 17.27% )
Number of unique values	63
^* Skills.Linguistic.MotherTongue.Description missing.