Overview

Dataset statistics

Number of variables5
Number of observations621
Missing cells302
Missing cells (%)9.7%
Duplicate rows23
Duplicate rows (%)3.7%
Total size in memory24.4 KiB
Average record size in memory40.2 B

Variable types

Categorical2
Text3

Dataset

Description보건의료인국가시험에서 사용하는 용어에 대한 해설(용어, 영어표기, 정의)
Author한국보건의료인국가시험원
URLhttps://www.data.go.kr/data/15054625/fileData.do

Alerts

Dataset has 23 (3.7%) duplicate rowsDuplicates
대분류 is highly overall correlated with 중분류High correlation
중분류 is highly overall correlated with 대분류High correlation
정의 has 298 (48.0%) missing valuesMissing

Reproduction

Analysis started2023-12-13 00:42:47.243356
Analysis finished2023-12-13 00:42:47.896219
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
직종별 국가시험 및 과목
235 
교육평가
115 
시험
107 
문항
76 
위원회 등 조직
47 

Length

Max length13
Median length8
Mean length6.9871176
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시험
2nd row시험
3rd row시험
4th row시험
5th row시험

Common Values

ValueCountFrequency (%)
직종별 국가시험 및 과목 235
37.8%
교육평가 115
18.5%
시험 107
17.2%
문항 76
 
12.2%
위원회 등 조직 47
 
7.6%
연구 41
 
6.6%

Length

2023-12-13T09:42:47.952616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:42:48.037383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직종별 235
16.5%
국가시험 235
16.5%
및 235
16.5%
과목 235
16.5%
교육평가 115
8.1%
시험 107
7.5%
문항 76
 
5.4%
위원회 47
 
3.3%
등 47
 
3.3%
조직 47
 
3.3%

중분류
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
조직
272 
연구
41 
측정평가
30 
문항형식
 
22
시험과목
 
21
Other values (27)
235 

Length

Max length6
Median length2
Mean length2.7520129
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row기관
2nd row기관
3rd row기관
4th row번호
5th row번호

Common Values

ValueCountFrequency (%)
조직 272
43.8%
연구 41
 
6.6%
측정평가 30
 
4.8%
문항형식 22
 
3.5%
시험과목 21
 
3.4%
시험진행 18
 
2.9%
인증종류 15
 
2.4%
문항분석 14
 
2.3%
시험결과 13
 
2.1%
문항관리 13
 
2.1%
Other values (22) 162
26.1%

Length

2023-12-13T09:42:48.151551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조직 272
43.8%
연구 41
 
6.6%
측정평가 30
 
4.8%
문항형식 22
 
3.5%
시험과목 21
 
3.4%
시험진행 18
 
2.9%
인증종류 15
 
2.4%
문항분석 14
 
2.3%
문항관리 13
 
2.1%
검사 13
 
2.1%
Other values (22) 162
26.1%

용어
Text

Distinct570
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-13T09:42:48.375946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length5.9565217
Min length1

Characters and Unicode

Total characters3699
Distinct characters306
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)87.8%

Sample

1st row간호조무사 및 의료유사업자에 관한 규칙
2nd row감독관
3rd row감독관 교육
4th row감독관 근무지침
5th row결격기준
ValueCountFrequency (%)
국가시험 35
 
4.2%
문항 29
 
3.4%
실기시험 19
 
2.3%
10
 
1.2%
및 9
 
1.1%
2급 8
 
1.0%
1급 8
 
1.0%
의료관계법규 8
 
1.0%
보건의약관계법규 6
 
0.7%
보건교육사 6
 
0.7%
Other values (562) 703
83.6%
2023-12-13T09:42:48.711189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
 
6.4%
사 124
 
3.4%
시 118
 
3.2%
험 91
 
2.5%
학 85
 
2.3%
의 82
 
2.2%
기 78
 
2.1%
문 72
 
1.9%
항 69
 
1.9%
가 67
 
1.8%
Other values (296) 2675
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3321
89.8%
Space Separator 238
 
6.4%
Other Punctuation 40
 
1.1%
Lowercase Letter 32
 
0.9%
Uppercase Letter 31
 
0.8%
Decimal Number 28
 
0.8%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Letter Number 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 124
 
3.7%
시 118
 
3.6%
험 91
 
2.7%
학 85
 
2.6%
의 82
 
2.5%
기 78
 
2.3%
문 72
 
2.2%
항 69
 
2.1%
가 67
 
2.0%
보 54
 
1.6%
Other values (250) 2481
74.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
12.9%
A 4
12.9%
C 3
9.7%
I 3
9.7%
R 2
 
6.5%
P 2
 
6.5%
T 2
 
6.5%
S 2
 
6.5%
D 1
 
3.2%
U 1
 
3.2%
Other values (7) 7
22.6%
Lowercase Letter
ValueCountFrequency (%)
o 5
15.6%
f 4
12.5%
r 3
9.4%
k 3
9.4%
n 3
9.4%
g 2
 
6.2%
a 2
 
6.2%
e 2
 
6.2%
b 2
 
6.2%
h 1
 
3.1%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
1 11
39.3%
2 10
35.7%
3 4
 
14.3%
0 2
 
7.1%
9 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 23
57.5%
/ 10
25.0%
? 7
 
17.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
238
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3321
89.8%
Common 313
 
8.5%
Latin 65
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 124
 
3.7%
시 118
 
3.6%
험 91
 
2.7%
학 85
 
2.6%
의 82
 
2.5%
기 78
 
2.3%
문 72
 
2.2%
항 69
 
2.1%
가 67
 
2.0%
보 54
 
1.6%
Other values (250) 2481
74.7%
Latin
ValueCountFrequency (%)
o 5
 
7.7%
B 4
 
6.2%
A 4
 
6.2%
f 4
 
6.2%
C 3
 
4.6%
r 3
 
4.6%
k 3
 
4.6%
n 3
 
4.6%
I 3
 
4.6%
g 2
 
3.1%
Other values (24) 31
47.7%
Common
ValueCountFrequency (%)
238
76.0%
, 23
 
7.3%
1 11
 
3.5%
/ 10
 
3.2%
2 10
 
3.2%
? 7
 
2.2%
3 4
 
1.3%
( 3
 
1.0%
) 3
 
1.0%
0 2
 
0.6%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3321
89.8%
ASCII 376
 
10.2%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
63.3%
, 23
 
6.1%
1 11
 
2.9%
/ 10
 
2.7%
2 10
 
2.7%
? 7
 
1.9%
o 5
 
1.3%
B 4
 
1.1%
3 4
 
1.1%
A 4
 
1.1%
Other values (34) 60
 
16.0%
Hangul
ValueCountFrequency (%)
사 124
 
3.7%
시 118
 
3.6%
험 91
 
2.7%
학 85
 
2.6%
의 82
 
2.5%
기 78
 
2.3%
문 72
 
2.2%
항 69
 
2.1%
가 67
 
2.0%
보 54
 
1.6%
Other values (250) 2481
74.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

영어 표기
Text

Distinct565
Distinct (%)91.6%
Missing4
Missing (%)0.6%
Memory size5.0 KiB
2023-12-13T09:42:48.991618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length340
Median length57
Mean length24.682334
Min length3

Characters and Unicode

Total characters15229
Distinct characters70
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique539 ?
Unique (%)87.4%

Sample

1st rowRegulations on Licensed Practical Nurse and Similar Physicians Who Are Not Legally Licensed
2nd rowproctor
3rd rowproctor training
4th rowproctor's manual
5th rowineligibility standard
ValueCountFrequency (%)
of 65
 
3.4%
test 61
 
3.2%
item 53
 
2.8%
44
 
2.3%
examination 44
 
2.3%
medical 43
 
2.2%
health 40
 
2.1%
and 37
 
1.9%
research 30
 
1.6%
licensing 29
 
1.5%
Other values (598) 1473
76.8%
2023-12-13T09:42:49.414592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1533
 
10.1%
i 1393
 
9.1%
1338
 
8.8%
t 1186
 
7.8%
a 1182
 
7.8%
n 1059
 
7.0%
o 856
 
5.6%
r 817
 
5.4%
l 711
 
4.7%
c 697
 
4.6%
Other values (60) 4457
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12677
83.2%
Space Separator 1338
 
8.8%
Uppercase Letter 981
 
6.4%
Other Punctuation 102
 
0.7%
Dash Punctuation 51
 
0.3%
Decimal Number 30
 
0.2%
Close Punctuation 22
 
0.1%
Open Punctuation 22
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1533
12.1%
i 1393
11.0%
t 1186
9.4%
a 1182
9.3%
n 1059
8.4%
o 856
 
6.8%
r 817
 
6.4%
l 711
 
5.6%
c 697
 
5.5%
s 681
 
5.4%
Other values (17) 2562
20.2%
Uppercase Letter
ValueCountFrequency (%)
P 109
11.1%
M 96
9.8%
E 85
 
8.7%
D 80
 
8.2%
T 73
 
7.4%
C 69
 
7.0%
S 65
 
6.6%
L 64
 
6.5%
H 56
 
5.7%
R 55
 
5.6%
Other values (15) 229
23.3%
Other Punctuation
ValueCountFrequency (%)
, 37
36.3%
: 22
21.6%
/ 21
20.6%
& 17
16.7%
' 3
 
2.9%
? 1
 
1.0%
. 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 12
40.0%
1 11
36.7%
3 5
16.7%
5 1
 
3.3%
0 1
 
3.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 3
50.0%
Ⅱ 3
50.0%
Space Separator
ValueCountFrequency (%)
1338
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13663
89.7%
Common 1565
 
10.3%
Greek 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1533
11.2%
i 1393
 
10.2%
t 1186
 
8.7%
a 1182
 
8.7%
n 1059
 
7.8%
o 856
 
6.3%
r 817
 
6.0%
l 711
 
5.2%
c 697
 
5.1%
s 681
 
5.0%
Other values (43) 3548
26.0%
Common
ValueCountFrequency (%)
1338
85.5%
- 51
 
3.3%
, 37
 
2.4%
) 22
 
1.4%
: 22
 
1.4%
( 22
 
1.4%
/ 21
 
1.3%
& 17
 
1.1%
2 12
 
0.8%
1 11
 
0.7%
Other values (6) 12
 
0.8%
Greek
ValueCountFrequency (%)
α 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15222
> 99.9%
Number Forms 6
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1533
 
10.1%
i 1393
 
9.2%
1338
 
8.8%
t 1186
 
7.8%
a 1182
 
7.8%
n 1059
 
7.0%
o 856
 
5.6%
r 817
 
5.4%
l 711
 
4.7%
c 697
 
4.6%
Other values (57) 4450
29.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 3
50.0%
Ⅱ 3
50.0%
None
ValueCountFrequency (%)
α 1
100.0%

정의
Text

MISSING 

Distinct323
Distinct (%)100.0%
Missing298
Missing (%)48.0%
Memory size5.0 KiB
2023-12-13T09:42:49.673421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length351
Median length144
Mean length81.433437
Min length8

Characters and Unicode

Total characters26303
Distinct characters549
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)100.0%

Sample

1st row간호조무사 관련법령
2nd row시험실 내에서 응시자를 확인하고, 문제지와 답안지를 관리하며, 응시자의 부정행위를 감독하도록 위촉한 인력
3rd row감독관이 시험을 감독하면서 숙지해야 하는 행동수칙에 대한 교육
4th row감독관이 반드시 숙지해야하는 행동수칙을 수록한 지침서
5th row응시자가 해당시험에 응시할 수 없는 기준 또는 면허를 받을 수 없는 기준(해당 시험의 근거법령에 명시되어 있음)
ValueCountFrequency (%)
및 52
 
0.9%
수 51
 
0.9%
또는 37
 
0.6%
있는 31
 
0.5%
위하여 31
 
0.5%
하는 29
 
0.5%
대한 28
 
0.5%
문항의 27
 
0.5%
있음 27
 
0.5%
문항 26
 
0.4%
Other values (3229) 5582
94.3%
2023-12-13T09:42:50.073682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5689
 
21.6%
의 596
 
2.3%
하 592
 
2.3%
는 515
 
2.0%
, 484
 
1.8%
을 397
 
1.5%
에 370
 
1.4%
수 344
 
1.3%
문 330
 
1.3%
이 325
 
1.2%
Other values (539) 16661
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18891
71.8%
Space Separator 5689
 
21.6%
Other Punctuation 713
 
2.7%
Lowercase Letter 560
 
2.1%
Decimal Number 119
 
0.5%
Close Punctuation 100
 
0.4%
Open Punctuation 100
 
0.4%
Uppercase Letter 78
 
0.3%
Dash Punctuation 45
 
0.2%
Math Symbol 6
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 596
 
3.2%
하 592
 
3.1%
는 515
 
2.7%
을 397
 
2.1%
에 370
 
2.0%
수 344
 
1.8%
문 330
 
1.7%
이 325
 
1.7%
정 299
 
1.6%
가 296
 
1.6%
Other values (466) 14827
78.5%
Lowercase Letter
ValueCountFrequency (%)
o 60
10.7%
e 51
 
9.1%
a 48
 
8.6%
i 46
 
8.2%
r 43
 
7.7%
n 43
 
7.7%
t 42
 
7.5%
l 36
 
6.4%
c 31
 
5.5%
s 26
 
4.6%
Other values (17) 134
23.9%
Uppercase Letter
ValueCountFrequency (%)
B 13
16.7%
C 11
14.1%
T 11
14.1%
A 7
9.0%
P 5
 
6.4%
R 5
 
6.4%
X 4
 
5.1%
S 4
 
5.1%
O 3
 
3.8%
Z 3
 
3.8%
Other values (8) 12
15.4%
Other Punctuation
ValueCountFrequency (%)
, 484
67.9%
. 151
 
21.2%
: 26
 
3.6%
/ 13
 
1.8%
* 11
 
1.5%
" 10
 
1.4%
' 8
 
1.1%
· 4
 
0.6%
※ 3
 
0.4%
% 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 34
28.6%
5 16
13.4%
0 16
13.4%
9 16
13.4%
6 14
11.8%
2 10
 
8.4%
7 5
 
4.2%
4 5
 
4.2%
3 3
 
2.5%
Math Symbol
ValueCountFrequency (%)
+ 3
50.0%
= 2
33.3%
~ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
5689
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18891
71.8%
Common 6774
 
25.8%
Latin 636
 
2.4%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 596
 
3.2%
하 592
 
3.1%
는 515
 
2.7%
을 397
 
2.1%
에 370
 
2.0%
수 344
 
1.8%
문 330
 
1.7%
이 325
 
1.7%
정 299
 
1.6%
가 296
 
1.6%
Other values (466) 14827
78.5%
Latin
ValueCountFrequency (%)
o 60
 
9.4%
e 51
 
8.0%
a 48
 
7.5%
i 46
 
7.2%
r 43
 
6.8%
n 43
 
6.8%
t 42
 
6.6%
l 36
 
5.7%
c 31
 
4.9%
s 26
 
4.1%
Other values (33) 210
33.0%
Common
ValueCountFrequency (%)
5689
84.0%
, 484
 
7.1%
. 151
 
2.2%
) 100
 
1.5%
( 100
 
1.5%
- 45
 
0.7%
1 34
 
0.5%
: 26
 
0.4%
5 16
 
0.2%
0 16
 
0.2%
Other values (18) 113
 
1.7%
Greek
ValueCountFrequency (%)
α 1
50.0%
β 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18891
71.8%
ASCII 7401
 
28.1%
None 6
 
< 0.1%
Punctuation 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5689
76.9%
, 484
 
6.5%
. 151
 
2.0%
) 100
 
1.4%
( 100
 
1.4%
o 60
 
0.8%
e 51
 
0.7%
a 48
 
0.6%
i 46
 
0.6%
- 45
 
0.6%
Other values (57) 627
 
8.5%
Hangul
ValueCountFrequency (%)
의 596
 
3.2%
하 592
 
3.1%
는 515
 
2.7%
을 397
 
2.1%
에 370
 
2.0%
수 344
 
1.8%
문 330
 
1.7%
이 325
 
1.7%
정 299
 
1.6%
가 296
 
1.6%
Other values (466) 14827
78.5%
None
ValueCountFrequency (%)
· 4
66.7%
α 1
 
16.7%
β 1
 
16.7%
Punctuation
ValueCountFrequency (%)
※ 3
60.0%
“ 1
 
20.0%
” 1
 
20.0%

Correlations

2023-12-13T09:42:50.145178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류
대분류1.0000.981
중분류0.9811.000
2023-12-13T09:42:50.202806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류
대분류1.0000.882
중분류0.8821.000
2023-12-13T09:42:50.264013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류
대분류1.0000.882
중분류0.8821.000

Missing values

2023-12-13T09:42:47.728432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:42:47.796879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-13T09:42:47.860773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

대분류중분류용어영어 표기정의
0시험기관간호조무사 및 의료유사업자에 관한 규칙Regulations on Licensed Practical Nurse and Similar Physicians Who Are Not Legally Licensed간호조무사 관련법령
1시험기관감독관proctor시험실 내에서 응시자를 확인하고, 문제지와 답안지를 관리하며, 응시자의 부정행위를 감독하도록 위촉한 인력
2시험기관감독관 교육proctor training감독관이 시험을 감독하면서 숙지해야 하는 행동수칙에 대한 교육
3시험번호감독관 근무지침proctor's manual감독관이 반드시 숙지해야하는 행동수칙을 수록한 지침서
4시험번호결격기준ineligibility standard응시자가 해당시험에 응시할 수 없는 기준 또는 면허를 받을 수 없는 기준(해당 시험의 근거법령에 명시되어 있음)
5시험번호공개항목<NA>실기 항목 중에서 출제대상 항목을 분류하여 응시자에게 미리 공고한 항목
6시험번호공중위생관리법Public Health Control Act위생사 관련법령
7시험법령과락과목failed subject어떤 과목의 성적이 합격기준에 못미치는 것으로 특정 과목에서 40점 미만인 경우 과락이 됨. 과락과목이 발생하면 총점에 관계없이 불합격으로 처리함.
8시험법령국민건강증진법National Health Promotion Act보건교육사 관련법령
9시험법령국민영양관리법National Nutrition Management Act영양사 관련법령
대분류중분류용어영어 표기정의
611직종별 국가시험 및 과목조직재활행정Rehabilitation Administration<NA>
612직종별 국가시험 및 과목조직재활정책Rehabilitation Policy<NA>
613직종별 국가시험 및 과목조직예비시험Preliminary examination<NA>
614직종별 국가시험 및 과목조직의사 예비시험Preliminary examination for MLE<NA>
615직종별 국가시험 및 과목조직의학의 기초Essential Medicine<NA>
616직종별 국가시험 및 과목조직치과의사 예비시험Preliminary examination for DLE<NA>
617직종별 국가시험 및 과목조직치의학의 기초Essential Dental Science<NA>
618직종별 국가시험 및 과목조직한의사 예비시험Preliminary examination for OMDLE<NA>
619직종별 국가시험 및 과목조직한국어Proficiency in Korean<NA>
620직종별 국가시험 및 과목조직특례시험Exceptionally-Certified Examination<NA>

Duplicate rows

Most frequently occurring

대분류중분류용어영어 표기정의# duplicates
9직종별 국가시험 및 과목조직실기시험Practical Skill(written exam)<NA>9
14직종별 국가시험 및 과목조직의료관계법규Medical Service Legislation<NA>8
4직종별 국가시험 및 과목조직보건의약관계법규Medical Health Legislation<NA>6
5직종별 국가시험 및 과목조직보건프로그램개발 및 평가Health Program Planning and Evaluation<NA>3
15직종별 국가시험 및 과목조직재활사례관리Rehabilitation Case Management<NA>3
16직종별 국가시험 및 과목조직재활상담Rehabilitation Counseling<NA>3
18직종별 국가시험 및 과목조직재활행정Rehabilitation Administration<NA>3
20직종별 국가시험 및 과목조직직무개발과 배치Job Development and Placement<NA>3
21직종별 국가시험 및 과목조직직업재활개론Introduction to Vocational Rehabilitation<NA>3
22직종별 국가시험 및 과목조직직업평가Vocational Evaluation<NA>3