Overview

Dataset statistics

Number of variables11
Number of observations493
Missing cells1481
Missing cells (%)27.3%
Duplicate rows73
Duplicate rows (%)14.8%
Total size in memory43.9 KiB
Average record size in memory91.3 B

Variable types

Text3
Categorical5
Unsupported3

Dataset

Description우리나라 공역에 대한 정보로 공역의 유형과 공역 명칭, 공역 상하한 참조기준과 단위, 공역등급 등에 대한 내용을 수록한 정보입니다.
Author국토교통부 항공교통본부
URLhttps://www.data.go.kr/data/15122905/fileData.do

Alerts

Dataset has 73 (14.8%) duplicate rowsDuplicates
하위고도한계단위 is highly overall correlated with 공역구성연산 and 1 other fieldsHigh correlation
공역구성연산 is highly overall correlated with 공역유형 and 3 other fieldsHigh correlation
하위고도한계 is highly overall correlated with 공역유형 and 3 other fieldsHigh correlation
상위고도한계단위 is highly overall correlated with 공역유형 and 2 other fieldsHigh correlation
공역유형 is highly overall correlated with 공역구성연산 and 2 other fieldsHigh correlation
공역구성연산 is highly imbalanced (73.7%)Imbalance
공역클래스상위고도 has 493 (100.0%) missing valuesMissing
공역클래스하위고도 has 493 (100.0%) missing valuesMissing
공역클래스 has 493 (100.0%) missing valuesMissing
공역클래스상위고도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공역클래스하위고도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공역클래스 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 11:45:35.342871
Analysis finished2023-12-12 11:45:36.189059
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식별자
Text

Distinct335
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T20:45:36.498539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length14
Mean length5.5760649
Min length2

Characters and Unicode

Total characters2749
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)50.3%

Sample

1st rowGWANGAN BRIDGE
2nd rowD13
3rd rowD14
4th rowD15
5th rowD16
ValueCountFrequency (%)
t 78
 
10.9%
moa 64
 
8.9%
ua 32
 
4.5%
ctr 19
 
2.6%
east-sea 16
 
2.2%
cata 9
 
1.3%
jochiwon 8
 
1.1%
chuncheon 8
 
1.1%
gapyeong 8
 
1.1%
yongin 8
 
1.1%
Other values (283) 467
65.1%
2023-12-12T20:45:37.004354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 242
 
8.8%
224
 
8.1%
1 191
 
6.9%
R 166
 
6.0%
O 161
 
5.9%
T 154
 
5.6%
E 134
 
4.9%
N 120
 
4.4%
2 111
 
4.0%
3 99
 
3.6%
Other values (40) 1147
41.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1678
61.0%
Decimal Number 751
27.3%
Space Separator 224
 
8.1%
Lowercase Letter 56
 
2.0%
Connector Punctuation 24
 
0.9%
Dash Punctuation 16
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 242
14.4%
R 166
9.9%
O 161
9.6%
T 154
 
9.2%
E 134
 
8.0%
N 120
 
7.2%
C 85
 
5.1%
G 81
 
4.8%
M 81
 
4.8%
S 66
 
3.9%
Other values (13) 388
23.1%
Lowercase Letter
ValueCountFrequency (%)
n 9
16.1%
u 7
12.5%
e 7
12.5%
a 7
12.5%
o 6
10.7%
h 4
7.1%
j 3
 
5.4%
g 3
 
5.4%
s 3
 
5.4%
c 2
 
3.6%
Other values (4) 5
8.9%
Decimal Number
ValueCountFrequency (%)
1 191
25.4%
2 111
14.8%
3 99
13.2%
0 67
 
8.9%
5 55
 
7.3%
4 54
 
7.2%
7 50
 
6.7%
8 48
 
6.4%
9 46
 
6.1%
6 30
 
4.0%
Space Separator
ValueCountFrequency (%)
224
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1734
63.1%
Common 1015
36.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 242
14.0%
R 166
 
9.6%
O 161
 
9.3%
T 154
 
8.9%
E 134
 
7.7%
N 120
 
6.9%
C 85
 
4.9%
G 81
 
4.7%
M 81
 
4.7%
S 66
 
3.8%
Other values (27) 444
25.6%
Common
ValueCountFrequency (%)
224
22.1%
1 191
18.8%
2 111
10.9%
3 99
9.8%
0 67
 
6.6%
5 55
 
5.4%
4 54
 
5.3%
7 50
 
4.9%
8 48
 
4.7%
9 46
 
4.5%
Other values (3) 70
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2749
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 242
 
8.8%
224
 
8.1%
1 191
 
6.9%
R 166
 
6.0%
O 161
 
5.9%
T 154
 
5.6%
E 134
 
4.9%
N 120
 
4.4%
2 111
 
4.0%
3 99
 
3.6%
Other values (40) 1147
41.7%

공역유형
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
R
114 
TMA
78 
MOA
76 
ATZ
61 
CTA
42 
Other values (9)
122 

Length

Max length5
Median length3
Mean length2.3306288
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st rowOTHER
2nd rowD
3rd rowD
4th rowD
5th rowD

Common Values

ValueCountFrequency (%)
R 114
23.1%
TMA 78
15.8%
MOA 76
15.4%
ATZ 61
12.4%
CTA 42
 
8.5%
D 37
 
7.5%
UFA 32
 
6.5%
CTR 19
 
3.9%
P 11
 
2.2%
A 10
 
2.0%
Other values (4) 13
 
2.6%

Length

2023-12-12T20:45:37.156083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r 114
23.1%
tma 78
15.8%
moa 76
15.4%
atz 61
12.4%
cta 42
 
8.5%
d 37
 
7.5%
ufa 32
 
6.5%
ctr 19
 
3.9%
p 11
 
2.2%
a 10
 
2.0%
Other values (4) 13
 
2.6%

공역명
Text

Distinct336
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T20:45:37.535523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length11.184584
Min length3

Characters and Unicode

Total characters5514
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)50.7%

Sample

1st rowGWANGAN BRIDGE
2nd rowRK D13 SEONGHWAN
3rd rowRK D14 JAECHEON
4th rowRK D15 JEONUI
5th rowRK D16 JANGDONG
ValueCountFrequency (%)
rk 165
 
14.0%
t 77
 
6.6%
moa 64
 
5.4%
atz 61
 
5.2%
sector 42
 
3.6%
ctr 19
 
1.6%
east-sea 16
 
1.4%
kcg 14
 
1.2%
jochiwon 10
 
0.9%
area 10
 
0.9%
Other values (425) 697
59.3%
2023-12-12T20:45:38.027601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
682
 
12.4%
A 425
 
7.7%
O 412
 
7.5%
R 380
 
6.9%
N 350
 
6.3%
E 331
 
6.0%
T 264
 
4.8%
G 234
 
4.2%
K 217
 
3.9%
C 189
 
3.4%
Other values (41) 2030
36.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4025
73.0%
Decimal Number 693
 
12.6%
Space Separator 682
 
12.4%
Dash Punctuation 56
 
1.0%
Lowercase Letter 56
 
1.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 425
10.6%
O 412
 
10.2%
R 380
 
9.4%
N 350
 
8.7%
E 331
 
8.2%
T 264
 
6.6%
G 234
 
5.8%
K 217
 
5.4%
C 189
 
4.7%
S 181
 
4.5%
Other values (13) 1042
25.9%
Lowercase Letter
ValueCountFrequency (%)
n 9
16.1%
e 7
12.5%
u 7
12.5%
a 7
12.5%
o 6
10.7%
h 4
7.1%
g 3
 
5.4%
j 3
 
5.4%
s 3
 
5.4%
l 2
 
3.6%
Other values (4) 5
8.9%
Decimal Number
ValueCountFrequency (%)
1 186
26.8%
2 98
14.1%
3 85
12.3%
0 62
 
8.9%
5 52
 
7.5%
4 49
 
7.1%
7 47
 
6.8%
8 45
 
6.5%
9 42
 
6.1%
6 27
 
3.9%
Space Separator
ValueCountFrequency (%)
682
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4081
74.0%
Common 1433
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 425
 
10.4%
O 412
 
10.1%
R 380
 
9.3%
N 350
 
8.6%
E 331
 
8.1%
T 264
 
6.5%
G 234
 
5.7%
K 217
 
5.3%
C 189
 
4.6%
S 181
 
4.4%
Other values (27) 1098
26.9%
Common
ValueCountFrequency (%)
682
47.6%
1 186
 
13.0%
2 98
 
6.8%
3 85
 
5.9%
0 62
 
4.3%
- 56
 
3.9%
5 52
 
3.6%
4 49
 
3.4%
7 47
 
3.3%
8 45
 
3.1%
Other values (4) 71
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
682
 
12.4%
A 425
 
7.7%
O 412
 
7.5%
R 380
 
6.9%
N 350
 
6.3%
E 331
 
6.0%
T 264
 
4.8%
G 234
 
4.2%
K 217
 
3.9%
C 189
 
3.4%
Other values (41) 2030
36.8%

공역구성연산
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
BASE
471 
<NA>
 
22

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BASE 471
95.5%
<NA> 22
 
4.5%

Length

2023-12-12T20:45:38.189719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:45:38.341307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
base 471
95.5%
na 22
 
4.5%

상위고도한계
Text

Distinct60
Distinct (%)12.2%
Missing2
Missing (%)0.4%
Memory size4.0 KiB
2023-12-12T20:45:38.532495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.7535642
Min length3

Characters and Unicode

Total characters1843
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.0%

Sample

1st row4000
2nd row3000
3rd row3000
4th row3000
5th row2000
ValueCountFrequency (%)
500 122
20.9%
1 59
 
10.1%
600 45
 
7.7%
400 42
 
7.2%
3000 32
 
5.5%
5000 22
 
3.8%
unl 18
 
3.1%
300 16
 
2.7%
225 15
 
2.6%
9000 12
 
2.1%
Other values (50) 201
34.4%
2023-12-12T20:45:38.938974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 962
52.2%
5 232
 
12.6%
1 144
 
7.8%
93
 
5.0%
4 75
 
4.1%
6 68
 
3.7%
3 68
 
3.7%
2 64
 
3.5%
9 29
 
1.6%
7 28
 
1.5%
Other values (10) 80
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1689
91.6%
Space Separator 93
 
5.0%
Uppercase Letter 60
 
3.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 962
57.0%
5 232
 
13.7%
1 144
 
8.5%
4 75
 
4.4%
6 68
 
4.0%
3 68
 
4.0%
2 64
 
3.8%
9 29
 
1.7%
7 28
 
1.7%
8 19
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 19
31.7%
L 18
30.0%
U 18
30.0%
B 1
 
1.7%
O 1
 
1.7%
T 1
 
1.7%
A 1
 
1.7%
M 1
 
1.7%
Space Separator
ValueCountFrequency (%)
93
100.0%
Lowercase Letter
ValueCountFrequency (%)
y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1782
96.7%
Latin 61
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 962
54.0%
5 232
 
13.0%
1 144
 
8.1%
93
 
5.2%
4 75
 
4.2%
6 68
 
3.8%
3 68
 
3.8%
2 64
 
3.6%
9 29
 
1.6%
7 28
 
1.6%
Latin
ValueCountFrequency (%)
N 19
31.1%
L 18
29.5%
U 18
29.5%
B 1
 
1.6%
y 1
 
1.6%
O 1
 
1.6%
T 1
 
1.6%
A 1
 
1.6%
M 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 962
52.2%
5 232
 
12.6%
1 144
 
7.8%
93
 
5.0%
4 75
 
4.1%
6 68
 
3.7%
3 68
 
3.7%
2 64
 
3.5%
9 29
 
1.6%
7 28
 
1.5%
Other values (10) 80
 
4.3%

상위고도한계단위
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
FT
315 
FL
157 
<NA>
 
21

Length

Max length4
Median length2
Mean length2.0851927
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
FT 315
63.9%
FL 157
31.8%
<NA> 21
 
4.3%

Length

2023-12-12T20:45:39.131886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:45:39.272059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ft 315
63.9%
fl 157
31.8%
na 21
 
4.3%

하위고도한계
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
GND
177 
FLOOR
81 
1 000
51 
1000
46 
SFC
26 
Other values (30)
112 

Length

Max length8
Median length6
Mean length3.9371197
Min length1

Unique

Unique13 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
GND 177
35.9%
FLOOR 81
16.4%
1 000 51
 
10.3%
1000 46
 
9.3%
SFC 26
 
5.3%
3000 20
 
4.1%
10000 18
 
3.7%
<NA> 10
 
2.0%
11000 10
 
2.0%
4 500 6
 
1.2%
Other values (25) 48
 
9.7%

Length

2023-12-12T20:45:39.431044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
gnd 177
31.1%
floor 81
14.2%
1 52
 
9.1%
000 52
 
9.1%
1000 46
 
8.1%
500 26
 
4.6%
sfc 26
 
4.6%
3000 20
 
3.5%
10000 18
 
3.2%
na 10
 
1.8%
Other values (26) 62
 
10.9%

하위고도한계단위
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
294 
FT
194 
FL
 
5

Length

Max length4
Median length4
Mean length3.1926978
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 294
59.6%
FT 194
39.4%
FL 5
 
1.0%

Length

2023-12-12T20:45:39.584275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:45:39.728433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 294
59.6%
ft 194
39.4%
fl 5
 
1.0%

공역클래스상위고도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing493
Missing (%)100.0%
Memory size4.5 KiB

공역클래스하위고도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing493
Missing (%)100.0%
Memory size4.5 KiB

공역클래스
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing493
Missing (%)100.0%
Memory size4.5 KiB

Correlations

2023-12-12T20:45:39.803557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공역유형상위고도한계상위고도한계단위하위고도한계하위고도한계단위
공역유형1.0000.9550.6080.8940.000
상위고도한계0.9551.0000.9970.9470.872
상위고도한계단위0.6080.9971.0000.7990.092
하위고도한계0.8940.9470.7991.0001.000
하위고도한계단위0.0000.8720.0921.0001.000
2023-12-12T20:45:39.929736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하위고도한계단위공역구성연산하위고도한계상위고도한계단위공역유형
하위고도한계단위1.0001.0000.9260.0580.000
공역구성연산1.0001.0001.0001.0001.000
하위고도한계0.9261.0001.0000.6810.515
상위고도한계단위0.0581.0000.6811.0000.582
공역유형0.0001.0000.5150.5821.000
2023-12-12T20:45:40.061886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공역유형공역구성연산상위고도한계단위하위고도한계하위고도한계단위
공역유형1.0001.0000.5820.5150.000
공역구성연산1.0001.0001.0001.0001.000
상위고도한계단위0.5821.0001.0000.6810.058
하위고도한계0.5151.0000.6811.0000.926
하위고도한계단위0.0001.0000.0580.9261.000

Missing values

2023-12-12T20:45:35.910233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:45:36.107342image/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

식별자공역유형공역명공역구성연산상위고도한계상위고도한계단위하위고도한계하위고도한계단위공역클래스상위고도공역클래스하위고도공역클래스
0GWANGAN BRIDGEOTHERGWANGAN BRIDGEBASE4000FTGND<NA><NA><NA><NA>
1D13DRK D13 SEONGHWANBASE3000FTGND<NA><NA><NA><NA>
2D14DRK D14 JAECHEONBASE3000FTGND<NA><NA><NA><NA>
3D15DRK D15 JEONUIBASE3000FTGND<NA><NA><NA><NA>
4D16DRK D16 JANGDONGBASE2000FTGND<NA><NA><NA><NA>
5D17DRK D17 IMSILBASE3000FTGND<NA><NA><NA><NA>
6D18DRK D18 HAKSANBASE3000FTGND<NA><NA><NA><NA>
7D19DRK D19 JUDEOKBASE1000FTGND<NA><NA><NA><NA>
8D20DRK D20 GUUIBASE1600FTGND<NA><NA><NA><NA>
9D21DRK D21 JAYANGBASE1700FTGND<NA><NA><NA><NA>
식별자공역유형공역명공역구성연산상위고도한계상위고도한계단위하위고도한계하위고도한계단위공역클래스상위고도공역클래스하위고도공역클래스
483P73CENTER1PP73CENTER1BASEUNL<NA>GND<NA><NA><NA><NA>
484P73CENTER1PP73CENTER1BASEUNL<NA>GND<NA><NA><NA><NA>
485R72RRK R72 YOKJIDOBASEUNL<NA>GND<NA><NA><NA><NA>
486R99RRK R99 GEOJEDOBASE360FLGND<NA><NA><NA><NA>
487P73CENTER2PP73CENTER2<NA><NA><NA><NA><NA><NA><NA><NA>
488CHEONGJU CTRCTRCHEONGJU CTR<NA>5000FTFLOOR<NA><NA><NA><NA>
489CHEONGJU CTRCTRCHEONGJU CTR<NA>5000FTFLOOR<NA><NA><NA><NA>
490A8ARK A8 IEODOBASE140FLGND<NA><NA><NA><NA>
491A9AARK A9A IEODOBASE3000FTGND<NA><NA><NA><NA>
492A9BARK A9B IEODOBASE3000FTGND<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

식별자공역유형공역명공역구성연산상위고도한계상위고도한계단위하위고도한계하위고도한계단위# duplicates
5EAST-SEACTAEAST-SEA SECTORBASE600FL1000FT16
2CHUNCHEONATZCHUNCHEON ATZBASE1 500FTFLOOR<NA>8
6GAPYEONGATZGAPYEONG ATZBASE1 500FTFLOOR<NA>8
16JOCHIWONATZJOCHIWON ATZBASE1 500FTFLOOR<NA>8
71YONGINATZYONGIN ATZBASE1 500FTFLOOR<NA>8
3DEOKSOATZDEOKSO ATZBASE1 000FTFLOOR<NA>4
7GEUMWANGATZGEUMWANG ATZBASE1 500FTFLOOR<NA>4
9GJ_WESTCTAGWANGJU WEST SECTORBASE600FT1000FT4
12HONGCHEONATZHONGCHEON ATZBASE1 500FTFLOOR<NA>4
13HYEONRIATZHYEONRI ATZBASE1 500FTFLOOR<NA>4