Overview

Dataset statistics

Number of variables9
Number of observations882
Missing cells892
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.9 KiB
Average record size in memory74.1 B

Variable types

Numeric1
Categorical3
Text4
Unsupported1

Dataset

Description파일 다운로드
Author서울 교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13241/F/1/datasetView.do

Alerts

장비 has constant value ""Constant
연번 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 연번High correlation
비고 has 882 (100.0%) missing valuesMissing
연번 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 04:00:38.142626
Analysis finished2023-12-11 04:00:39.225632
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct882
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean441.5
Minimum1
Maximum882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T13:00:39.308226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.05
Q1221.25
median441.5
Q3661.75
95-th percentile837.95
Maximum882
Range881
Interquartile range (IQR)440.5

Descriptive statistics

Standard deviation254.75577
Coefficient of variation (CV)0.57702325
Kurtosis-1.2
Mean441.5
Median Absolute Deviation (MAD)220.5
Skewness0
Sum389403
Variance64900.5
MonotonicityStrictly increasing
2023-12-11T13:00:39.462466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
594 1
 
0.1%
583 1
 
0.1%
584 1
 
0.1%
585 1
 
0.1%
586 1
 
0.1%
587 1
 
0.1%
588 1
 
0.1%
589 1
 
0.1%
590 1
 
0.1%
Other values (872) 872
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
882 1
0.1%
881 1
0.1%
880 1
0.1%
879 1
0.1%
878 1
0.1%
877 1
0.1%
876 1
0.1%
875 1
0.1%
874 1
0.1%
873 1
0.1%

호선
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
5
150 
2
149 
7
126 
6
113 
3
87 
Other values (9)
257 

Length

Max length5
Median length1
Mean length1.329932
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
5 150
17.0%
2 149
16.9%
7 126
14.3%
6 113
12.8%
3 87
9.9%
4 77
8.7%
8 56
 
6.3%
7(연) 37
 
4.2%
1 36
 
4.1%
5(연) 24
 
2.7%
Other values (4) 27
 
3.1%

Length

2023-12-11T13:00:39.640134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5 150
17.0%
2 149
16.9%
7 126
14.3%
6 113
12.8%
3 87
9.9%
4 77
8.7%
8 56
 
6.3%
7(연 37
 
4.2%
1 36
 
4.1%
5(연 24
 
2.7%
Other values (4) 27
 
3.1%

역명
Text

Distinct265
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2023-12-11T13:00:39.988049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length3.1519274
Min length2

Characters and Unicode

Total characters2780
Distinct characters218
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)1.9%

Sample

1st row서울(1)
2nd row서울(1)
3rd row서울(1)
4th row서울(1)
5th row시청(1)
ValueCountFrequency (%)
삼각지 10
 
1.1%
가락시장 9
 
1.0%
합정 9
 
1.0%
부평구청 9
 
1.0%
동묘앞 9
 
1.0%
잠실 8
 
0.9%
오금 8
 
0.9%
강일 7
 
0.8%
대림 7
 
0.8%
영등포구청 7
 
0.8%
Other values (255) 799
90.6%
2023-12-11T13:00:40.565461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 97
 
3.5%
신 89
 
3.2%
구 87
 
3.1%
동 81
 
2.9%
산 62
 
2.2%
지 54
 
1.9%
청 51
 
1.8%
( 49
 
1.8%
) 49
 
1.8%
원 46
 
1.7%
Other values (208) 2115
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2616
94.1%
Decimal Number 66
 
2.4%
Open Punctuation 49
 
1.8%
Close Punctuation 49
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 97
 
3.7%
신 89
 
3.4%
구 87
 
3.3%
동 81
 
3.1%
산 62
 
2.4%
지 54
 
2.1%
청 51
 
1.9%
원 46
 
1.8%
입 42
 
1.6%
장 40
 
1.5%
Other values (201) 1967
75.2%
Decimal Number
ValueCountFrequency (%)
1 19
28.8%
2 15
22.7%
3 15
22.7%
4 14
21.2%
5 3
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2616
94.1%
Common 164
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 97
 
3.7%
신 89
 
3.4%
구 87
 
3.3%
동 81
 
3.1%
산 62
 
2.4%
지 54
 
2.1%
청 51
 
1.9%
원 46
 
1.8%
입 42
 
1.6%
장 40
 
1.5%
Other values (201) 1967
75.2%
Common
ValueCountFrequency (%)
( 49
29.9%
) 49
29.9%
1 19
 
11.6%
2 15
 
9.1%
3 15
 
9.1%
4 14
 
8.5%
5 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2616
94.1%
ASCII 164
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 97
 
3.7%
신 89
 
3.4%
구 87
 
3.3%
동 81
 
3.1%
산 62
 
2.4%
지 54
 
2.1%
청 51
 
1.9%
원 46
 
1.8%
입 42
 
1.6%
장 40
 
1.5%
Other values (201) 1967
75.2%
ASCII
ValueCountFrequency (%)
( 49
29.9%
) 49
29.9%
1 19
 
11.6%
2 15
 
9.1%
3 15
 
9.1%
4 14
 
8.5%
5 3
 
1.8%

장비
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
E/L
882 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE/L
2nd rowE/L
3rd rowE/L
4th rowE/L
5th rowE/L

Common Values

ValueCountFrequency (%)
E/L 882
100.0%

Length

2023-12-11T13:00:40.713622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:00:40.857742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e/l 882
100.0%

호기
Categorical

Distinct25
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
1
167 
2
155 
3
120 
내부#1
112 
외부#1
104 
Other values (20)
224 

Length

Max length4
Median length1
Mean length2.207483
Min length1

Unique

Unique6 ?
Unique (%)0.7%

Sample

1st row내부#1
2nd row외부#1
3rd row외부#2
4th row외부#3
5th row내부#1

Common Values

ValueCountFrequency (%)
1 167
18.9%
2 155
17.6%
3 120
13.6%
내부#1 112
12.7%
외부#1 104
11.8%
내부#2 76
8.6%
4 54
 
6.1%
외부#2 43
 
4.9%
5 17
 
1.9%
외부#3 6
 
0.7%
Other values (15) 28
 
3.2%

Length

2023-12-11T13:00:40.983891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 167
18.9%
2 155
17.6%
3 120
13.6%
내부#1 112
12.7%
외부#1 104
11.8%
내부#2 76
8.6%
4 54
 
6.1%
외부#2 43
 
4.9%
5 17
 
1.9%
외부#3 6
 
0.7%
Other values (15) 28
 
3.2%

승강기번호
Text

Distinct879
Distinct (%)100.0%
Missing3
Missing (%)0.3%
Memory size7.0 KiB
2023-12-11T13:00:41.396892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.0011377
Min length8

Characters and Unicode

Total characters7033
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique879 ?
Unique (%)100.0%

Sample

1st row0074-205
2nd row0104-656
3rd row0105-867
4th row0073-979
5th row0002-888
ValueCountFrequency (%)
0000-513 1
 
0.1%
0007-065 1
 
0.1%
0041-877 1
 
0.1%
0040-054 1
 
0.1%
0039-042 1
 
0.1%
0039-043 1
 
0.1%
0005-870 1
 
0.1%
0108-823 1
 
0.1%
0102-308 1
 
0.1%
0143-822 1
 
0.1%
Other values (869) 869
98.9%
2023-12-11T13:00:42.048315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2025
28.8%
- 879
12.5%
2 648
 
9.2%
1 602
 
8.6%
9 480
 
6.8%
7 453
 
6.4%
3 422
 
6.0%
8 415
 
5.9%
5 408
 
5.8%
4 378
 
5.4%
Other values (2) 323
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6153
87.5%
Dash Punctuation 879
 
12.5%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2025
32.9%
2 648
 
10.5%
1 602
 
9.8%
9 480
 
7.8%
7 453
 
7.4%
3 422
 
6.9%
8 415
 
6.7%
5 408
 
6.6%
4 378
 
6.1%
6 322
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 879
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7033
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2025
28.8%
- 879
12.5%
2 648
 
9.2%
1 602
 
8.6%
9 480
 
6.8%
7 453
 
6.4%
3 422
 
6.0%
8 415
 
5.9%
5 408
 
5.8%
4 378
 
5.4%
Other values (2) 323
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2025
28.8%
- 879
12.5%
2 648
 
9.2%
1 602
 
8.6%
9 480
 
6.8%
7 453
 
6.4%
3 422
 
6.0%
8 415
 
5.9%
5 408
 
5.8%
4 378
 
5.4%
Other values (2) 323
 
4.6%

운행구간
Text

Distinct89
Distinct (%)10.1%
Missing3
Missing (%)0.3%
Memory size7.0 KiB
2023-12-11T13:00:42.376557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length5
Mean length7.0011377
Min length3

Characters and Unicode

Total characters6154
Distinct characters37
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

Unique33 ?
Unique (%)3.8%

Sample

1st rowB2(승)~B1(대)
2nd rowB1(대)~지상
3rd rowB1(대)~지상
4th rowB1(대)~지상
5th rowB2(승)~B1(대)
ValueCountFrequency (%)
f1-b1 121
13.7%
b2(승)~b1(대 111
12.6%
b1(대)~지상 109
12.3%
b1-b2 91
 
10.3%
b2-b3 86
 
9.7%
f1-b2 41
 
4.6%
b1-b3 29
 
3.3%
f2(대)~f3(승 24
 
2.7%
b3(승)~b2(대 21
 
2.4%
b3-b4 20
 
2.3%
Other values (81) 231
26.1%
2023-12-11T13:00:42.857764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 1271
20.7%
1 806
13.1%
) 562
9.1%
( 561
9.1%
- 511
8.3%
2 483
 
7.8%
~ 387
 
6.3%
대 352
 
5.7%
F 336
 
5.5%
3 225
 
3.7%
Other values (27) 660
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1631
26.5%
Uppercase Letter 1615
26.2%
Other Letter 880
14.3%
Close Punctuation 562
 
9.1%
Open Punctuation 561
 
9.1%
Dash Punctuation 511
 
8.3%
Math Symbol 389
 
6.3%
Space Separator 4
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 352
40.0%
승 203
23.1%
상 154
17.5%
지 151
17.2%
가 3
 
0.3%
연 2
 
0.2%
환 2
 
0.2%
합 2
 
0.2%
실 2
 
0.2%
리 1
 
0.1%
Other values (8) 8
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 806
49.4%
2 483
29.6%
3 225
 
13.8%
4 70
 
4.3%
5 28
 
1.7%
7 8
 
0.5%
6 6
 
0.4%
8 3
 
0.2%
0 2
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 1271
78.7%
F 336
 
20.8%
M 8
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 387
99.5%
⇔ 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 562
100.0%
Open Punctuation
ValueCountFrequency (%)
( 561
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 511
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3659
59.5%
Latin 1615
26.2%
Hangul 880
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 352
40.0%
승 203
23.1%
상 154
17.5%
지 151
17.2%
가 3
 
0.3%
연 2
 
0.2%
환 2
 
0.2%
합 2
 
0.2%
실 2
 
0.2%
리 1
 
0.1%
Other values (8) 8
 
0.9%
Common
ValueCountFrequency (%)
1 806
22.0%
) 562
15.4%
( 561
15.3%
- 511
14.0%
2 483
13.2%
~ 387
10.6%
3 225
 
6.1%
4 70
 
1.9%
5 28
 
0.8%
7 8
 
0.2%
Other values (6) 18
 
0.5%
Latin
ValueCountFrequency (%)
B 1271
78.7%
F 336
 
20.8%
M 8
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5272
85.7%
Hangul 880
 
14.3%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 1271
24.1%
1 806
15.3%
) 562
10.7%
( 561
10.6%
- 511
9.7%
2 483
 
9.2%
~ 387
 
7.3%
F 336
 
6.4%
3 225
 
4.3%
4 70
 
1.3%
Other values (8) 60
 
1.1%
Hangul
ValueCountFrequency (%)
대 352
40.0%
승 203
23.1%
상 154
17.5%
지 151
17.2%
가 3
 
0.3%
연 2
 
0.2%
환 2
 
0.2%
합 2
 
0.2%
실 2
 
0.2%
리 1
 
0.1%
Other values (8) 8
 
0.9%
Arrows
ValueCountFrequency (%)
⇔ 2
100.0%

설치위치
Text

Distinct176
Distinct (%)20.0%
Missing4
Missing (%)0.5%
Memory size7.0 KiB
2023-12-11T13:00:43.165562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length2
Mean length3.9031891
Min length2

Characters and Unicode

Total characters3427
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)11.6%

Sample

1st row섬식(상) 5-1
2nd row2번 출구측
3rd row4번 출구측
4th row3번 출구측
5th row상행 3-2
ValueCountFrequency (%)
내부 299
24.6%
외부 206
17.0%
출구측 117
 
9.6%
상행 41
 
3.4%
하행 41
 
3.4%
1번 33
 
2.7%
외선 33
 
2.7%
내선 33
 
2.7%
3-2 18
 
1.5%
섬식(상 17
 
1.4%
Other values (108) 375
30.9%
2023-12-11T13:00:43.681106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 505
14.7%
337
 
9.8%
내 333
 
9.7%
외 252
 
7.4%
- 213
 
6.2%
구 157
 
4.6%
출 156
 
4.6%
번 154
 
4.5%
측 123
 
3.6%
3 123
 
3.6%
Other values (60) 1074
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2188
63.8%
Decimal Number 587
 
17.1%
Space Separator 337
 
9.8%
Dash Punctuation 213
 
6.2%
Close Punctuation 46
 
1.3%
Open Punctuation 46
 
1.3%
Other Punctuation 6
 
0.2%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 505
23.1%
내 333
15.2%
외 252
11.5%
구 157
 
7.2%
출 156
 
7.1%
번 154
 
7.0%
측 123
 
5.6%
행 86
 
3.9%
상 68
 
3.1%
선 66
 
3.0%
Other values (44) 288
13.2%
Decimal Number
ValueCountFrequency (%)
3 123
21.0%
1 118
20.1%
4 104
17.7%
2 83
14.1%
8 50
8.5%
6 35
 
6.0%
7 28
 
4.8%
5 23
 
3.9%
9 12
 
2.0%
0 11
 
1.9%
Space Separator
ValueCountFrequency (%)
337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2188
63.8%
Common 1239
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 505
23.1%
내 333
15.2%
외 252
11.5%
구 157
 
7.2%
출 156
 
7.1%
번 154
 
7.0%
측 123
 
5.6%
행 86
 
3.9%
상 68
 
3.1%
선 66
 
3.0%
Other values (44) 288
13.2%
Common
ValueCountFrequency (%)
337
27.2%
- 213
17.2%
3 123
 
9.9%
1 118
 
9.5%
4 104
 
8.4%
2 83
 
6.7%
8 50
 
4.0%
) 46
 
3.7%
( 46
 
3.7%
6 35
 
2.8%
Other values (6) 84
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2188
63.8%
ASCII 1239
36.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 505
23.1%
내 333
15.2%
외 252
11.5%
구 157
 
7.2%
출 156
 
7.1%
번 154
 
7.0%
측 123
 
5.6%
행 86
 
3.9%
상 68
 
3.1%
선 66
 
3.0%
Other values (44) 288
13.2%
ASCII
ValueCountFrequency (%)
337
27.2%
- 213
17.2%
3 123
 
9.9%
1 118
 
9.5%
4 104
 
8.4%
2 83
 
6.7%
8 50
 
4.0%
) 46
 
3.7%
( 46
 
3.7%
6 35
 
2.8%
Other values (6) 84
 
6.8%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing882
Missing (%)100.0%
Memory size7.9 KiB

Interactions

2023-12-11T13:00:38.592388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:00:43.809553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선호기운행구간
연번1.0000.9250.6740.819
호선0.9251.0000.7360.961
호기0.6740.7361.0000.944
운행구간0.8190.9610.9441.000
2023-12-11T13:00:43.935605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호기호선
호기1.0000.328
호선0.3281.000
2023-12-11T13:00:44.044725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선호기
연번1.0000.7200.306
호선0.7201.0000.328
호기0.3060.3281.000

Missing values

2023-12-11T13:00:38.722433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:00:38.840207image/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.
2023-12-11T13:00:39.174953image/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

연번호선역명장비호기승강기번호운행구간설치위치비고
011서울(1)E/L내부#10074-205B2(승)~B1(대)섬식(상) 5-1<NA>
121서울(1)E/L외부#10104-656B1(대)~지상2번 출구측<NA>
231서울(1)E/L외부#20105-867B1(대)~지상4번 출구측<NA>
341서울(1)E/L외부#30073-979B1(대)~지상3번 출구측<NA>
451시청(1)E/L내부#10002-888B2(승)~B1(대)상행 3-2<NA>
561시청(1)E/L내부#20002-887B2(승)~B1(대)하행 8-3<NA>
671시청(1)E/L외부#10002-889B1(대)~지상1-2번 출구사이<NA>
781종각E/L내부#10000-506B2(승)~B1(대)상행 6-4<NA>
891종각E/L내부#20000-507B2(승)~B1(대)하행 4-4<NA>
9101종각E/L외부#10000-508B1(대)~지상3번 출구측<NA>
연번호선역명장비호기승강기번호운행구간설치위치비고
8728738단대오거리E/L22116-587B1-B3내부<NA>
8738748단대오거리E/L32116-588F1-B1외부<NA>
8748758신흥E/L12022-969B1-B2내부<NA>
8758768신흥E/L22022-970B1-B2내부<NA>
8768778수진E/L12116-589B1-B2내부<NA>
8778788수진E/L22116-590B1-B2내부<NA>
8788798수진E/L32212-625B1-F1외부<NA>
8798808모란E/L12116-583B1-B3내부<NA>
8808818모란E/L22116-584B2-B3내부<NA>
8818828모란E/L32116-585F1-B1외부<NA>