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

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