Graduates in tertiary education, in science, math., computing, engineering, manufacturing, construction, by sex - per 1000 of population aged 20-29 ta_eductrain_parteduc_numbgrad__educ_uoe_grad04

Time format:
Years
Unit:
Rate per 1000 population (comparable)
AL
EU28
UK
MK
HU
LV
MT
PL
RO
TR
CY
BG
HR
LT
LU
NL
EL
RS
AT
BE
CZ
EU27_2020
FR
IS
IT
NO
PT
SK
DK
SI
ES
EE
FI
DE
IE
SE
LI
CH
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
AL
0.3
0.1
EU28
0.8
0.8(d)
0.8
0.8(d)
0.8(d)
0.7(d)
UK
1.4
1.3
1.2
1.1
1.1
1.1
1.1
MK
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
HU
0.4
0.3
0.2
0.3
0.3
0.2
0.2
0.3
0.3
0.2
LV
0.4
0.3
0.2
0.3
0.3
0.3
0.3
0.4
0.4
0.4
MT
0.2
0.1
0.2
0.1
0.1
0.2
0.2
0.2
0.1
0.1
PL
0.3(de)
0.2
0.2
0.3
0.3
0.2
0.3
0.3
0.2
(d)
RO
0.3
0.4
0.2
0.3
0.2
0.2
0.3
0.5
0.5
0.6
TR
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.1
CY
0.3
0.4
0.3
0.3
0.2
0.2
0.3
0.2
0.2
0.2
BG
0.4
0.4
0.4
0.4
0.4
0.5
0.5
0.5
0.5
0.4
HR
0.7
0.5
0.4
0.4
0.4
0.5
0.4
0.6
0.5
0.5
LT
0.6
0.4
0.4
0.4
0.4
0.4
0.3
0.4
0.4
0.4
LU
1.3
0.7
0.4
0.6
0.5
0.7
0.4
0.4
0.2
0.3
NL
0.4
0.5
0.4
0.5
0.4
0.4
(d)
EL
0.5
0.6
0.5
0.5
0.4
0.5
0.5
0.4
0.4
0.3
RS
0.5
0.4
0.5
0.5
0.7
0.7
0.6
0.5
0.3
AT
0.6
0.6
0.6
0.6
0.6
0.6
0.6
0.5
0.6
0.6
BE
0.7
0.7
0.6
0.6
0.6
0.5
0.6
0.6
0.5
0.5
CZ
0.8
0.7
0.6
0.8
0.7
0.7
0.6
0.6
0.6
0.6
EU27_2020
0.7
0.6
0.6
0.6
0.7(d)
0.7
0.7(d)
0.7(d)
0.7(d)
FR
1
0.6
0.6
0.7
0.7(d)
0.9
0.8
0.8
0.8
0.8
IS
0.5
0.7
0.6
0.5
0.3
0.5
0.5
0.5
0.9
0.5
IT
0.7
0.6
0.6(p)
0.6
0.5
0.6(d)
0.7
0.7
0.7
0.7
NO
0.7
0.6
0.7
0.6
0.6
0.6
0.6
0.6
0.7
PT
0.7
0.6
0.6
0.7
0.8
0.8
0.9
0.8
0.8
0.9
SK
0.7
0.7
0.6
0.6
0.6
0.7
0.8
0.8
0.9
0.9
DK
0.8
0.8
0.7
0.8
0.8
0.8
0.9
0.9
0.8
0.8
SI
0.9
0.6
0.7
0.8
0.7
0.6
3.1
1.5
1.5
1.5
ES
0.8
0.7
0.7
0.7
1.4
1.5
1.3
1.1
0.9
0.8
EE
1
0.8
0.8
0.8
0.8
0.9
0.7
0.6
0.5
0.7
FI
0.8
0.6
0.8
0.8
0.9
0.9
1
1
0.9
0.9
DE
0.9
0.9
0.8
0.9
0.9
0.9
0.9
0.9
0.9
0.9
IE
0.9(d)
0.9(d)
0.9(d)
0.9(d)
0.9(d)
0.8
0.9
0.8
1
0.9
SE
0.9
0.8
0.9
0.8
0.8
0.9
0.9
1
0.9
0.9
LI
0
1.3
0.9
0.5
0
0
0
0
0
CH
1.5
1.6
1.5
1.4
1.5
1.3
1.3
1.1
1

Available flags:

b break in time series c confidential
d definition differs, see metadata e estimated
f forecast i see metadata
m imputed n not significant
p provisional r revised
s Eurostat estimate u low reliability
x dropped due to insufficient sample size y unreliable due to small sample size
z not applicable