Overview

Dataset statistics

Number of variables7
Number of observations2819
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory157.0 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Text4
Categorical2

Dataset

Description역코드,역명,승강기명,운행구간,설치위치,운행상태,승강기 구분
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-15994/S/1/datasetView.do

Alerts

운행상태 is highly imbalanced (54.3%)Imbalance

Reproduction

Analysis started2024-05-11 05:50:25.313171
Analysis finished2024-05-11 05:50:26.595884
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역코드
Real number (ℝ)

Distinct273
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1798.1093
Minimum150
Maximum2828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T14:50:26.738734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile210
Q1338
median2548
Q32713
95-th percentile2813
Maximum2828
Range2678
Interquartile range (IQR)2375

Descriptive statistics

Standard deviation1133.6857
Coefficient of variation (CV)0.63048766
Kurtosis-1.6447365
Mean1798.1093
Median Absolute Deviation (MAD)190
Skewness-0.57237142
Sum5068870
Variance1285243.3
MonotonicityNot monotonic
2024-05-11T14:50:26.971807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2565 32
 
1.1%
2738 31
 
1.1%
2564 29
 
1.0%
423 27
 
1.0%
2736 27
 
1.0%
329 27
 
1.0%
2752 26
 
0.9%
2563 26
 
0.9%
340 25
 
0.9%
2566 24
 
0.9%
Other values (263) 2545
90.3%
ValueCountFrequency (%)
150 10
0.4%
151 6
 
0.2%
152 6
 
0.2%
153 7
 
0.2%
154 3
 
0.1%
155 4
 
0.1%
156 10
0.4%
157 5
 
0.2%
158 7
 
0.2%
159 19
0.7%
ValueCountFrequency (%)
2828 10
0.4%
2827 7
0.2%
2826 3
 
0.1%
2825 2
 
0.1%
2824 9
0.3%
2823 6
 
0.2%
2822 17
0.6%
2821 7
0.2%
2820 12
0.4%
2819 12
0.4%

역명
Text

Distinct273
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
2024-05-11T14:50:27.378050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.2259667
Min length2

Characters and Unicode

Total characters11913
Distinct characters214
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row서울역(1)
2nd row서울역(1)
3rd row서울역(1)
4th row서울역(1)
5th row서울역(1)
ValueCountFrequency (%)
하남시청 32
 
1.1%
총신대입구(7 31
 
1.1%
하남풍산 29
 
1.0%
고속터미널(3 27
 
1.0%
충무로(4 27
 
1.0%
고속터미널(7 27
 
1.0%
미사 26
 
0.9%
온수(7 26
 
0.9%
가락시장(3 25
 
0.9%
하남검단산 24
 
0.9%
Other values (263) 2545
90.3%
2024-05-11T14:50:28.060344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 1141
 
9.6%
) 1141
 
9.6%
대 330
 
2.8%
구 308
 
2.6%
신 256
 
2.1%
산 214
 
1.8%
동 213
 
1.8%
6 206
 
1.7%
7 201
 
1.7%
5 194
 
1.6%
Other values (204) 7709
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8442
70.9%
Decimal Number 1189
 
10.0%
Open Punctuation 1141
 
9.6%
Close Punctuation 1141
 
9.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 330
 
3.9%
구 308
 
3.6%
신 256
 
3.0%
산 214
 
2.5%
동 213
 
2.5%
남 166
 
2.0%
입 164
 
1.9%
청 159
 
1.9%
지 146
 
1.7%
로 135
 
1.6%
Other values (194) 6351
75.2%
Decimal Number
ValueCountFrequency (%)
6 206
17.3%
7 201
16.9%
5 194
16.3%
3 177
14.9%
2 157
13.2%
4 143
12.0%
1 63
 
5.3%
8 48
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 1141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8442
70.9%
Common 3471
29.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 330
 
3.9%
구 308
 
3.6%
신 256
 
3.0%
산 214
 
2.5%
동 213
 
2.5%
남 166
 
2.0%
입 164
 
1.9%
청 159
 
1.9%
지 146
 
1.7%
로 135
 
1.6%
Other values (194) 6351
75.2%
Common
ValueCountFrequency (%)
( 1141
32.9%
) 1141
32.9%
6 206
 
5.9%
7 201
 
5.8%
5 194
 
5.6%
3 177
 
5.1%
2 157
 
4.5%
4 143
 
4.1%
1 63
 
1.8%
8 48
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8442
70.9%
ASCII 3471
29.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 1141
32.9%
) 1141
32.9%
6 206
 
5.9%
7 201
 
5.8%
5 194
 
5.6%
3 177
 
5.1%
2 157
 
4.5%
4 143
 
4.1%
1 63
 
1.8%
8 48
 
1.4%
Hangul
ValueCountFrequency (%)
대 330
 
3.9%
구 308
 
3.6%
신 256
 
3.0%
산 214
 
2.5%
동 213
 
2.5%
남 166
 
2.0%
입 164
 
1.9%
청 159
 
1.9%
지 146
 
1.7%
로 135
 
1.6%
Other values (194) 6351
75.2%

승강기명
Text

Distinct74
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
2024-05-11T14:50:28.379081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.21426
Min length10

Characters and Unicode

Total characters34432
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.9%

Sample

1st row승강기)에스컬레이터 1
2nd row승강기)에스컬레이터 2
3rd row승강기)에스컬레이터 3
4th row승강기)에스컬레이터 4
5th row승강기)에스컬레이터 5
ValueCountFrequency (%)
승강기)에스컬레이터 1852
32.8%
승강기)엘리베이터 840
14.9%
1 442
 
7.8%
2 416
 
7.4%
3 340
 
6.0%
4 271
 
4.8%
5 173
 
3.1%
6 153
 
2.7%
내부#1 114
 
2.0%
7 112
 
2.0%
Other values (40) 925
16.4%
2024-05-11T14:50:28.895210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
승 2819
 
8.2%
기 2819
 
8.2%
) 2819
 
8.2%
2819
 
8.2%
강 2819
 
8.2%
이 2692
 
7.8%
터 2692
 
7.8%
에 1852
 
5.4%
스 1852
 
5.4%
컬 1852
 
5.4%
Other values (27) 9397
27.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25275
73.4%
Decimal Number 3156
 
9.2%
Close Punctuation 2819
 
8.2%
Space Separator 2819
 
8.2%
Other Punctuation 363
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
승 2819
11.2%
기 2819
11.2%
강 2819
11.2%
이 2692
10.7%
터 2692
10.7%
에 1852
7.3%
스 1852
7.3%
컬 1852
7.3%
레 1852
7.3%
리 949
 
3.8%
Other values (14) 3077
12.2%
Decimal Number
ValueCountFrequency (%)
1 1038
32.9%
2 640
20.3%
3 387
 
12.3%
4 305
 
9.7%
5 197
 
6.2%
6 173
 
5.5%
7 126
 
4.0%
8 124
 
3.9%
9 86
 
2.7%
0 80
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 2819
100.0%
Space Separator
ValueCountFrequency (%)
2819
100.0%
Other Punctuation
ValueCountFrequency (%)
# 363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25275
73.4%
Common 9157
 
26.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
승 2819
11.2%
기 2819
11.2%
강 2819
11.2%
이 2692
10.7%
터 2692
10.7%
에 1852
7.3%
스 1852
7.3%
컬 1852
7.3%
레 1852
7.3%
리 949
 
3.8%
Other values (14) 3077
12.2%
Common
ValueCountFrequency (%)
) 2819
30.8%
2819
30.8%
1 1038
 
11.3%
2 640
 
7.0%
3 387
 
4.2%
# 363
 
4.0%
4 305
 
3.3%
5 197
 
2.2%
6 173
 
1.9%
7 126
 
1.4%
Other values (3) 290
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25275
73.4%
ASCII 9157
 
26.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
승 2819
11.2%
기 2819
11.2%
강 2819
11.2%
이 2692
10.7%
터 2692
10.7%
에 1852
7.3%
스 1852
7.3%
컬 1852
7.3%
레 1852
7.3%
리 949
 
3.8%
Other values (14) 3077
12.2%
ASCII
ValueCountFrequency (%)
) 2819
30.8%
2819
30.8%
1 1038
 
11.3%
2 640
 
7.0%
3 387
 
4.2%
# 363
 
4.0%
4 305
 
3.3%
5 197
 
2.2%
6 173
 
1.9%
7 126
 
1.4%
Other values (3) 290
 
3.2%

운행구간
Text

Distinct130
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
2024-05-11T14:50:29.179677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.1418943
Min length4

Characters and Unicode

Total characters14495
Distinct characters24
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)1.5%

Sample

1st rowB2-B1
2nd rowB1-B2
3rd rowB2-B1
4th rowB1-F1
5th rowF1-B1
ValueCountFrequency (%)
f1-b1 305
 
10.8%
b1-f1 300
 
10.6%
b1-1f 292
 
10.4%
b2-b1 289
 
10.2%
b1-b2 202
 
7.2%
b2-b3 189
 
6.7%
b3-b2 157
 
5.6%
b1-bm1 63
 
2.2%
b3-b1 61
 
2.2%
b2-1f 59
 
2.1%
Other values (120) 904
32.0%
2024-05-11T14:50:29.625251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 4059
28.0%
1 3341
23.0%
- 2861
19.7%
F 1542
 
10.6%
2 1279
 
8.8%
3 672
 
4.6%
M 287
 
2.0%
4 230
 
1.6%
5 64
 
0.4%
지 26
 
0.2%
Other values (14) 134
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5888
40.6%
Decimal Number 5597
38.6%
Dash Punctuation 2861
19.7%
Other Letter 147
 
1.0%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 26
17.7%
상 26
17.7%
환 18
12.2%
통 17
11.6%
로 17
11.6%
승 9
 
6.1%
결 8
 
5.4%
연 8
 
5.4%
셔 7
 
4.8%
터 7
 
4.8%
Other values (2) 4
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 3341
59.7%
2 1279
 
22.9%
3 672
 
12.0%
4 230
 
4.1%
5 64
 
1.1%
6 7
 
0.1%
8 4
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 4059
68.9%
F 1542
 
26.2%
M 287
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 2861
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8460
58.4%
Latin 5888
40.6%
Hangul 147
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 26
17.7%
상 26
17.7%
환 18
12.2%
통 17
11.6%
로 17
11.6%
승 9
 
6.1%
결 8
 
5.4%
연 8
 
5.4%
셔 7
 
4.8%
터 7
 
4.8%
Other values (2) 4
 
2.7%
Common
ValueCountFrequency (%)
1 3341
39.5%
- 2861
33.8%
2 1279
 
15.1%
3 672
 
7.9%
4 230
 
2.7%
5 64
 
0.8%
6 7
 
0.1%
8 4
 
< 0.1%
2
 
< 0.1%
Latin
ValueCountFrequency (%)
B 4059
68.9%
F 1542
 
26.2%
M 287
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14348
99.0%
Hangul 147
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 4059
28.3%
1 3341
23.3%
- 2861
19.9%
F 1542
 
10.7%
2 1279
 
8.9%
3 672
 
4.7%
M 287
 
2.0%
4 230
 
1.6%
5 64
 
0.4%
6 7
 
< 0.1%
Other values (2) 6
 
< 0.1%
Hangul
ValueCountFrequency (%)
지 26
17.7%
상 26
17.7%
환 18
12.2%
통 17
11.6%
로 17
11.6%
승 9
 
6.1%
결 8
 
5.4%
연 8
 
5.4%
셔 7
 
4.8%
터 7
 
4.8%
Other values (2) 4
 
2.7%

설치위치
Text

Distinct906
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
2024-05-11T14:50:30.047754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length8.7257893
Min length3

Characters and Unicode

Total characters24598
Distinct characters267
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique590 ?
Unique (%)20.9%

Sample

1st row연결통로(4호선 방면)
2nd row남영 방면2-3
3rd row시청 방면9-3
4th row4번 출입구
5th row4번 출입구
ValueCountFrequency (%)
출입구 1485
24.5%
1번 280
 
4.6%
방면 242
 
4.0%
3번 221
 
3.6%
2번 213
 
3.5%
4번 190
 
3.1%
대합실 167
 
2.8%
5번 114
 
1.9%
6번 98
 
1.6%
방면1-1 87
 
1.4%
Other values (497) 2965
48.9%
2024-05-11T14:50:30.644365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3243
 
13.2%
구 1606
 
6.5%
입 1552
 
6.3%
번 1512
 
6.1%
출 1512
 
6.1%
방 1364
 
5.5%
면 1330
 
5.4%
- 1096
 
4.5%
1 982
 
4.0%
4 794
 
3.2%
Other values (257) 9607
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14667
59.6%
Decimal Number 4279
 
17.4%
Space Separator 3243
 
13.2%
Dash Punctuation 1096
 
4.5%
Open Punctuation 417
 
1.7%
Close Punctuation 417
 
1.7%
Other Punctuation 372
 
1.5%
Uppercase Letter 65
 
0.3%
Math Symbol 42
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1606
 
10.9%
입 1552
 
10.6%
번 1512
 
10.3%
출 1512
 
10.3%
방 1364
 
9.3%
면 1330
 
9.1%
대 473
 
3.2%
실 379
 
2.6%
합 346
 
2.4%
로 293
 
2.0%
Other values (233) 4300
29.3%
Decimal Number
ValueCountFrequency (%)
1 982
22.9%
4 794
18.6%
3 741
17.3%
2 648
15.1%
5 309
 
7.2%
6 266
 
6.2%
8 223
 
5.2%
7 185
 
4.3%
9 75
 
1.8%
0 56
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
B 47
72.3%
E 7
 
10.8%
S 4
 
6.2%
F 3
 
4.6%
L 3
 
4.6%
C 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 361
97.0%
/ 9
 
2.4%
# 2
 
0.5%
Space Separator
ValueCountFrequency (%)
3243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1096
100.0%
Open Punctuation
ValueCountFrequency (%)
( 417
100.0%
Close Punctuation
ValueCountFrequency (%)
) 417
100.0%
Math Symbol
ValueCountFrequency (%)
~ 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14667
59.6%
Common 9866
40.1%
Latin 65
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1606
 
10.9%
입 1552
 
10.6%
번 1512
 
10.3%
출 1512
 
10.3%
방 1364
 
9.3%
면 1330
 
9.1%
대 473
 
3.2%
실 379
 
2.6%
합 346
 
2.4%
로 293
 
2.0%
Other values (233) 4300
29.3%
Common
ValueCountFrequency (%)
3243
32.9%
- 1096
 
11.1%
1 982
 
10.0%
4 794
 
8.0%
3 741
 
7.5%
2 648
 
6.6%
( 417
 
4.2%
) 417
 
4.2%
, 361
 
3.7%
5 309
 
3.1%
Other values (8) 858
 
8.7%
Latin
ValueCountFrequency (%)
B 47
72.3%
E 7
 
10.8%
S 4
 
6.2%
F 3
 
4.6%
L 3
 
4.6%
C 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14667
59.6%
ASCII 9931
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3243
32.7%
- 1096
 
11.0%
1 982
 
9.9%
4 794
 
8.0%
3 741
 
7.5%
2 648
 
6.5%
( 417
 
4.2%
) 417
 
4.2%
, 361
 
3.6%
5 309
 
3.1%
Other values (14) 923
 
9.3%
Hangul
ValueCountFrequency (%)
구 1606
 
10.9%
입 1552
 
10.6%
번 1512
 
10.3%
출 1512
 
10.3%
방 1364
 
9.3%
면 1330
 
9.1%
대 473
 
3.2%
실 379
 
2.6%
합 346
 
2.4%
로 293
 
2.0%
Other values (233) 4300
29.3%

운행상태
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
사용가능
2304 
보수중
498 
공사중
 
17

Length

Max length4
Median length4
Mean length3.8173111
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용가능 2304
81.7%
보수중 498
 
17.7%
공사중 17
 
0.6%

Length

2024-05-11T14:50:30.781458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:30.891216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용가능 2304
81.7%
보수중 498
 
17.7%
공사중 17
 
0.6%

승강기 구분
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.2 KiB
ES
1852 
EV
840 
WL
 
109
MW
 
18

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ES 1852
65.7%
EV 840
29.8%
WL 109
 
3.9%
MW 18
 
0.6%

Length

2024-05-11T14:50:31.029422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:31.209812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
es 1852
65.7%
ev 840
29.8%
wl 109
 
3.9%
mw 18
 
0.6%

Interactions

2024-05-11T14:50:26.115307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:50:31.325038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역코드승강기명운행상태승강기 구분
역코드1.0000.5940.1840.186
승강기명0.5941.0000.1291.000
운행상태0.1840.1291.0000.119
승강기 구분0.1861.0000.1191.000
2024-05-11T14:50:31.478489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승강기 구분운행상태
승강기 구분1.0000.112
운행상태0.1121.000
2024-05-11T14:50:31.602454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역코드운행상태승강기 구분
역코드1.0000.1740.074
운행상태0.1741.0000.112
승강기 구분0.0740.1121.000

Missing values

2024-05-11T14:50:26.315824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:50:26.512773image/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

역코드역명승강기명운행구간설치위치운행상태승강기 구분
0150서울역(1)승강기)에스컬레이터 1B2-B1연결통로(4호선 방면)사용가능ES
1150서울역(1)승강기)에스컬레이터 2B1-B2남영 방면2-3사용가능ES
2150서울역(1)승강기)에스컬레이터 3B2-B1시청 방면9-3사용가능ES
3150서울역(1)승강기)에스컬레이터 4B1-F14번 출입구사용가능ES
4150서울역(1)승강기)에스컬레이터 5F1-B14번 출입구사용가능ES
5150서울역(1)승강기)엘리베이터 내부#1B2-B1시청 방면5-1사용가능EV
6150서울역(1)승강기)엘리베이터 외부#1B1-1F2번 출입구보수중EV
7150서울역(1)승강기)엘리베이터 외부#2B1-1F4번 출입구사용가능EV
8150서울역(1)승강기)엘리베이터 외부#3B1-1F3번 출입구사용가능EV
9150서울역(1)승강기)휠체어리프트 내부1B2-B1C계단측사용가능WL
역코드역명승강기명운행구간설치위치운행상태승강기 구분
28092828남위례승강기)에스컬레이터 1F1-F21번 출입구사용가능ES
28102828남위례승강기)에스컬레이터 2F2-F11번 출입구보수중ES
28112828남위례승강기)에스컬레이터 3F2-F3대합실사용가능ES
28122828남위례승강기)에스컬레이터 4F3-F2대합실보수중ES
28132828남위례승강기)에스컬레이터 5F3-F2산성 방면5-1사용가능ES
28142828남위례승강기)에스컬레이터 6F2-F3산성 방면5-1사용가능ES
28152828남위례승강기)에스컬레이터 7F1-F25번 출입구보수중ES
28162828남위례승강기)엘리베이터 11F-2F대합실(1번 출입구)사용가능EV
28172828남위례승강기)엘리베이터 21F-4F5번 출입구사용가능EV
28182828남위례승강기)엘리베이터 32F-3F산성 방면3-4사용가능EV