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

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