Overview

Dataset statistics

Number of variables6
Number of observations167
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory52.8 B

Variable types

Text2
Numeric4

Dataset

Description각 지역별 전파진흥원 국가기술자격검정 시험장 정보 입니다. 더이상 시험장으로 운영하지 않는 곳도 있으며, 매회 변동성이 있습니다. 컬럼 : 시험장명, 필기시험장 수, 실기시험장 수, 필기 가용인원 수, 실기 가용인원 수, 주소(시험장 주소)
URLhttps://www.data.go.kr/data/15076833/fileData.do

Alerts

필기시험장 수 is highly overall correlated with 필기 가용인원 수High correlation
실기시험장 수 is highly overall correlated with 실기 가용인원 수High correlation
필기 가용인원 수 is highly overall correlated with 필기시험장 수High correlation
실기 가용인원 수 is highly overall correlated with 실기시험장 수High correlation
필기시험장 수 has 74 (44.3%) zerosZeros
실기시험장 수 has 53 (31.7%) zerosZeros
필기 가용인원 수 has 74 (44.3%) zerosZeros
실기 가용인원 수 has 54 (32.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:42:29.431959
Analysis finished2023-12-12 04:42:31.855159
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시험장명
Text

Distinct158
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T13:42:32.064761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length10.706587
Min length4

Characters and Unicode

Total characters1788
Distinct characters188
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)89.8%

Sample

1st row(부산2)자체검정장
2nd row(북서울본부)자체검정장
3rd row(사전접수) 필기면제자 대상
4th row(인천지역2)자체검정교육장
5th row(휴면)동도중학교
ValueCountFrequency (%)
한국폴리텍대학 4
 
2.1%
수원공업고등학교 3
 
1.6%
경제통상진흥원 3
 
1.6%
남부대학교(광산구 2
 
1.0%
동남보건대학(수원 2
 
1.0%
금파공업고등학교 2
 
1.0%
제주대학교(교양강의동 2
 
1.0%
서울여자고등학교(마포구 2
 
1.0%
화성직업훈련교도소 2
 
1.0%
대상 2
 
1.0%
Other values (167) 168
87.5%
2023-12-12T13:42:32.626219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 123
 
6.9%
교 107
 
6.0%
( 68
 
3.8%
) 68
 
3.8%
고 59
 
3.3%
등 58
 
3.2%
대 58
 
3.2%
자 43
 
2.4%
업 42
 
2.3%
공 39
 
2.2%
Other values (178) 1123
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1577
88.2%
Open Punctuation 68
 
3.8%
Close Punctuation 68
 
3.8%
Space Separator 26
 
1.5%
Decimal Number 23
 
1.3%
Uppercase Letter 21
 
1.2%
Connector Punctuation 4
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 123
 
7.8%
교 107
 
6.8%
고 59
 
3.7%
등 58
 
3.7%
대 58
 
3.7%
자 43
 
2.7%
업 42
 
2.7%
공 39
 
2.5%
구 38
 
2.4%
주 31
 
2.0%
Other values (161) 979
62.1%
Decimal Number
ValueCountFrequency (%)
1 9
39.1%
0 4
17.4%
2 4
17.4%
5 2
 
8.7%
4 1
 
4.3%
7 1
 
4.3%
8 1
 
4.3%
3 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
T 7
33.3%
C 6
28.6%
B 5
23.8%
I 3
14.3%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1577
88.2%
Common 190
 
10.6%
Latin 21
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 123
 
7.8%
교 107
 
6.8%
고 59
 
3.7%
등 58
 
3.7%
대 58
 
3.7%
자 43
 
2.7%
업 42
 
2.7%
공 39
 
2.5%
구 38
 
2.4%
주 31
 
2.0%
Other values (161) 979
62.1%
Common
ValueCountFrequency (%)
( 68
35.8%
) 68
35.8%
26
 
13.7%
1 9
 
4.7%
0 4
 
2.1%
_ 4
 
2.1%
2 4
 
2.1%
5 2
 
1.1%
- 1
 
0.5%
4 1
 
0.5%
Other values (3) 3
 
1.6%
Latin
ValueCountFrequency (%)
T 7
33.3%
C 6
28.6%
B 5
23.8%
I 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1577
88.2%
ASCII 211
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 123
 
7.8%
교 107
 
6.8%
고 59
 
3.7%
등 58
 
3.7%
대 58
 
3.7%
자 43
 
2.7%
업 42
 
2.7%
공 39
 
2.5%
구 38
 
2.4%
주 31
 
2.0%
Other values (161) 979
62.1%
ASCII
ValueCountFrequency (%)
( 68
32.2%
) 68
32.2%
26
 
12.3%
1 9
 
4.3%
T 7
 
3.3%
C 6
 
2.8%
B 5
 
2.4%
0 4
 
1.9%
_ 4
 
1.9%
2 4
 
1.9%
Other values (7) 10
 
4.7%

필기시험장 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7784431
Minimum0
Maximum42
Zeros74
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T13:42:32.809564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q311
95-th percentile24
Maximum42
Range42
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.5528972
Coefficient of variation (CV)1.4093055
Kurtosis1.250538
Mean6.7784431
Median Absolute Deviation (MAD)1
Skewness1.420011
Sum1132
Variance91.257846
MonotonicityNot monotonic
2023-12-12T13:42:32.977650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 74
44.3%
20 18
 
10.8%
1 13
 
7.8%
5 13
 
7.8%
6 7
 
4.2%
3 7
 
4.2%
15 7
 
4.2%
24 6
 
3.6%
10 6
 
3.6%
2 3
 
1.8%
Other values (12) 13
 
7.8%
ValueCountFrequency (%)
0 74
44.3%
1 13
 
7.8%
2 3
 
1.8%
3 7
 
4.2%
4 1
 
0.6%
5 13
 
7.8%
6 7
 
4.2%
8 1
 
0.6%
10 6
 
3.6%
12 1
 
0.6%
ValueCountFrequency (%)
42 1
 
0.6%
40 1
 
0.6%
35 1
 
0.6%
32 1
 
0.6%
30 1
 
0.6%
27 1
 
0.6%
24 6
 
3.6%
23 2
 
1.2%
21 1
 
0.6%
20 18
10.8%

실기시험장 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6946108
Minimum0
Maximum200
Zeros53
Zeros (%)31.7%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T13:42:33.142278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q310
95-th percentile26.1
Maximum200
Range200
Interquartile range (IQR)10

Descriptive statistics

Standard deviation19.780029
Coefficient of variation (CV)2.2749758
Kurtosis57.108688
Mean8.6946108
Median Absolute Deviation (MAD)3
Skewness6.7141924
Sum1452
Variance391.24955
MonotonicityNot monotonic
2023-12-12T13:42:33.307214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 53
31.7%
10 22
13.2%
1 16
 
9.6%
20 15
 
9.0%
5 15
 
9.0%
3 12
 
7.2%
2 11
 
6.6%
30 4
 
2.4%
24 3
 
1.8%
15 3
 
1.8%
Other values (9) 13
 
7.8%
ValueCountFrequency (%)
0 53
31.7%
1 16
 
9.6%
2 11
 
6.6%
3 12
 
7.2%
4 2
 
1.2%
5 15
 
9.0%
6 3
 
1.8%
10 22
13.2%
15 3
 
1.8%
19 1
 
0.6%
ValueCountFrequency (%)
200 1
 
0.6%
99 2
 
1.2%
32 1
 
0.6%
30 4
 
2.4%
27 1
 
0.6%
24 3
 
1.8%
23 1
 
0.6%
21 1
 
0.6%
20 15
9.0%
19 1
 
0.6%

필기 가용인원 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.90419
Minimum0
Maximum999
Zeros74
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T13:42:33.509662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median39
Q3300
95-th percentile600
Maximum999
Range999
Interquartile range (IQR)300

Descriptive statistics

Standard deviation214.79063
Coefficient of variation (CV)1.3432458
Kurtosis0.87678749
Mean159.90419
Median Absolute Deviation (MAD)39
Skewness1.302632
Sum26704
Variance46135.015
MonotonicityNot monotonic
2023-12-12T13:42:33.683866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 74
44.3%
200 10
 
6.0%
600 9
 
5.4%
300 9
 
5.4%
100 7
 
4.2%
500 6
 
3.6%
400 6
 
3.6%
180 5
 
3.0%
60 4
 
2.4%
250 3
 
1.8%
Other values (24) 34
20.4%
ValueCountFrequency (%)
0 74
44.3%
12 1
 
0.6%
18 2
 
1.2%
20 1
 
0.6%
24 2
 
1.2%
25 1
 
0.6%
30 2
 
1.2%
39 1
 
0.6%
40 2
 
1.2%
50 1
 
0.6%
ValueCountFrequency (%)
999 1
 
0.6%
700 1
 
0.6%
690 1
 
0.6%
675 1
 
0.6%
640 1
 
0.6%
600 9
5.4%
550 1
 
0.6%
500 6
3.6%
460 1
 
0.6%
450 3
 
1.8%

실기 가용인원 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.64072
Minimum0
Maximum999
Zeros54
Zeros (%)32.3%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T13:42:33.844197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50
Q3130
95-th percentile500
Maximum999
Range999
Interquartile range (IQR)130

Descriptive statistics

Standard deviation185.91432
Coefficient of variation (CV)1.4340735
Kurtosis3.079383
Mean129.64072
Median Absolute Deviation (MAD)50
Skewness1.8229148
Sum21650
Variance34564.135
MonotonicityNot monotonic
2023-12-12T13:42:34.018531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 54
32.3%
100 26
15.6%
400 9
 
5.4%
200 9
 
5.4%
30 8
 
4.8%
20 8
 
4.8%
500 7
 
4.2%
80 6
 
3.6%
50 6
 
3.6%
60 5
 
3.0%
Other values (18) 29
17.4%
ValueCountFrequency (%)
0 54
32.3%
12 1
 
0.6%
20 8
 
4.8%
24 2
 
1.2%
25 2
 
1.2%
30 8
 
4.8%
36 1
 
0.6%
40 5
 
3.0%
50 6
 
3.6%
60 5
 
3.0%
ValueCountFrequency (%)
999 1
 
0.6%
675 1
 
0.6%
640 1
 
0.6%
600 4
2.4%
500 7
4.2%
480 1
 
0.6%
460 1
 
0.6%
450 1
 
0.6%
420 1
 
0.6%
400 9
5.4%

주소
Text

Distinct147
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T13:42:34.427459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length25.670659
Min length3

Characters and Unicode

Total characters4287
Distinct characters264
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

Unique137 ?
Unique (%)82.0%

Sample

1st row부산광역시 동구 초량중로 29(초량동)한국방송통신전파진흥원 부산본부
2nd row서울특별시 마포구 성암로 189(상암동)10층 자체검정장
3rd row미등록
4th row인천광역시 남동구 미래로 7(구월동)4층
5th row서울특별시 마포구 백범로 139 (염리동)
ValueCountFrequency (%)
서울특별시 26
 
3.3%
경기도 14
 
1.8%
광주광역시 12
 
1.5%
미등록 11
 
1.4%
제주특별자치도 11
 
1.4%
제주시 11
 
1.4%
강원도 11
 
1.4%
마포구 10
 
1.3%
북구 10
 
1.3%
인천광역시 10
 
1.3%
Other values (427) 661
84.0%
2023-12-12T13:42:35.025181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
 
14.5%
시 145
 
3.4%
동 135
 
3.1%
로 120
 
2.8%
구 117
 
2.7%
1 114
 
2.7%
( 96
 
2.2%
) 96
 
2.2%
2 86
 
2.0%
대 76
 
1.8%
Other values (254) 2679
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2864
66.8%
Space Separator 623
 
14.5%
Decimal Number 547
 
12.8%
Open Punctuation 97
 
2.3%
Close Punctuation 97
 
2.3%
Dash Punctuation 29
 
0.7%
Uppercase Letter 25
 
0.6%
Other Punctuation 4
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 145
 
5.1%
동 135
 
4.7%
로 120
 
4.2%
구 117
 
4.1%
대 76
 
2.7%
주 73
 
2.5%
도 70
 
2.4%
학 68
 
2.4%
서 66
 
2.3%
광 66
 
2.3%
Other values (227) 1928
67.3%
Decimal Number
ValueCountFrequency (%)
1 114
20.8%
2 86
15.7%
5 60
11.0%
3 58
10.6%
6 48
8.8%
4 48
8.8%
9 39
 
7.1%
7 36
 
6.6%
0 31
 
5.7%
8 27
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
I 9
36.0%
T 6
24.0%
V 4
16.0%
C 2
 
8.0%
A 1
 
4.0%
B 1
 
4.0%
W 1
 
4.0%
K 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 96
99.0%
[ 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 96
99.0%
] 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
623
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2864
66.8%
Common 1397
32.6%
Latin 26
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 145
 
5.1%
동 135
 
4.7%
로 120
 
4.2%
구 117
 
4.1%
대 76
 
2.7%
주 73
 
2.5%
도 70
 
2.4%
학 68
 
2.4%
서 66
 
2.3%
광 66
 
2.3%
Other values (227) 1928
67.3%
Common
ValueCountFrequency (%)
623
44.6%
1 114
 
8.2%
( 96
 
6.9%
) 96
 
6.9%
2 86
 
6.2%
5 60
 
4.3%
3 58
 
4.2%
6 48
 
3.4%
4 48
 
3.4%
9 39
 
2.8%
Other values (8) 129
 
9.2%
Latin
ValueCountFrequency (%)
I 9
34.6%
T 6
23.1%
V 4
15.4%
C 2
 
7.7%
Ⅰ 1
 
3.8%
A 1
 
3.8%
B 1
 
3.8%
W 1
 
3.8%
K 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2864
66.8%
ASCII 1422
33.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
43.8%
1 114
 
8.0%
( 96
 
6.8%
) 96
 
6.8%
2 86
 
6.0%
5 60
 
4.2%
3 58
 
4.1%
6 48
 
3.4%
4 48
 
3.4%
9 39
 
2.7%
Other values (16) 154
 
10.8%
Hangul
ValueCountFrequency (%)
시 145
 
5.1%
동 135
 
4.7%
로 120
 
4.2%
구 117
 
4.1%
대 76
 
2.7%
주 73
 
2.5%
도 70
 
2.4%
학 68
 
2.4%
서 66
 
2.3%
광 66
 
2.3%
Other values (227) 1928
67.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

Interactions

2023-12-12T13:42:31.175418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:29.720263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.146626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.713526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:31.277838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:29.797929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.281061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.829096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:31.400772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:29.898952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.436969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.945675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:31.516608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.033324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:30.560860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:42:31.057091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:42:35.156158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
필기시험장 수실기시험장 수필기 가용인원 수실기 가용인원 수
필기시험장 수1.0000.3070.8200.524
실기시험장 수0.3071.0000.2930.857
필기 가용인원 수0.8200.2931.0000.632
실기 가용인원 수0.5240.8570.6321.000
2023-12-12T13:42:35.266944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
필기시험장 수실기시험장 수필기 가용인원 수실기 가용인원 수
필기시험장 수1.0000.1980.9740.205
실기시험장 수0.1981.0000.1850.927
필기 가용인원 수0.9740.1851.0000.216
실기 가용인원 수0.2050.9270.2161.000

Missing values

2023-12-12T13:42:31.654774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:42:31.797041image/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.

Sample

시험장명필기시험장 수실기시험장 수필기 가용인원 수실기 가용인원 수주소
0(부산2)자체검정장01020부산광역시 동구 초량중로 29(초량동)한국방송통신전파진흥원 부산본부
1(북서울본부)자체검정장114040서울특별시 마포구 성암로 189(상암동)10층 자체검정장
2(사전접수) 필기면제자 대상0100500미등록
3(인천지역2)자체검정교육장050100인천광역시 남동구 미래로 7(구월동)4층
4(휴면)동도중학교2406000서울특별시 마포구 백범로 139 (염리동)
5CBT(북서울01) 마포구10390서울특별시 마포구 성암로 189(상암동)10층 (유료주차장 운영)
6CBT(서울01) 송파구10570서울특별시 송파구 중대로 135(가락동)IT벤처타워 서관 2층
7CBT(전남01) 서구10180광주광역시 서구 운천로 219(치평동)4층 디지털시험장, ( 주차공간 없음 )
8CBT(전북01)덕진구10180전라북도 전주시 덕진구 견훤로 279 (인후동1가)2층
9ICT폴리텍대학599300200경기도 광주시 순암로 16-26(역동)ICT 폴리텍대학
시험장명필기시험장 수실기시험장 수필기 가용인원 수실기 가용인원 수주소
157한국폴리텍대학(강릉캠퍼스)05080강원도 강릉시 남산초교길 121 (노암동)폴리텍대학 강릉캠퍼스
158한국폴리텍대학(제주캠퍼스)03030제주 제주시 아라1동산천단통로 125
159한국폴리텍대학교 김제캠퍼스(기술교육과정)03030전라북도 김제시 백학제길 154 (백학동)
160한국폴리텍대학원주캠퍼스01030강원도 원주시 북원로2425 73 한국폴리텍3대학
161한국해양수산연수원(부산)66250110부산 영도구 동삼동1125번지 한국해양수산연수원 영도캠퍼스(교육관)
162해군282전탐감시대0000전북 군산시 옥도면어청도리 해군 2227부대
163해운대공업고등학교2121420420부산광역시 해운대구 해운대로469번길 96(우동)
164화성직업훈련교도소216020경기도 화성시 화성로 741 직업훈련교도소
165화성직업훈련교도소20600미등록
166흥해공업고등학교03080경북 포항시 북구 흥해읍