Overview

Dataset statistics

Number of variables9
Number of observations370
Missing cells740
Missing cells (%)22.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.2 KiB
Average record size in memory75.4 B

Variable types

Numeric1
Text5
Unsupported2
Categorical1

Dataset

Description서울특별시 용산구 제설함 염화칼슘보관의집현황(연번 관리번호 관리번호 도로명 규격 위치-구 위치-도로명 위치-번호 비고)에 대한 데이터를 제공합니다
Author서울특별시 용산구
URLhttps://www.data.go.kr/data/3077859/fileData.do

Alerts

위치-구 has constant value ""Constant
규격 has 370 (100.0%) missing valuesMissing
비고 has 370 (100.0%) missing valuesMissing
연번 has unique valuesUnique
관리번호 has unique valuesUnique
관리번호.1 has unique valuesUnique
규격 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 09:15:24.595964
Analysis finished2023-12-12 09:15:25.284925
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.5
Minimum1
Maximum370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T18:15:25.439744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.45
Q193.25
median185.5
Q3277.75
95-th percentile351.55
Maximum370
Range369
Interquartile range (IQR)184.5

Descriptive statistics

Standard deviation106.95404
Coefficient of variation (CV)0.57657164
Kurtosis-1.2
Mean185.5
Median Absolute Deviation (MAD)92.5
Skewness0
Sum68635
Variance11439.167
MonotonicityStrictly increasing
2023-12-12T18:15:25.664968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
245 1
 
0.3%
254 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
Other values (360) 360
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
370 1
0.3%
369 1
0.3%
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%

관리번호
Text

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:15:26.162973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2220
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique370 ?
Unique (%)100.0%

Sample

1st row용산-001
2nd row용산-002
3rd row용산-003
4th row용산-004
5th row용산-005
ValueCountFrequency (%)
용산-001 1
 
0.3%
용산-278 1
 
0.3%
용산-252 1
 
0.3%
용산-251 1
 
0.3%
용산-250 1
 
0.3%
용산-249 1
 
0.3%
용산-248 1
 
0.3%
용산-247 1
 
0.3%
용산-246 1
 
0.3%
용산-245 1
 
0.3%
Other values (360) 360
97.3%
2023-12-12T18:15:26.757159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 370
16.7%
산 370
16.7%
- 370
16.7%
1 177
8.0%
2 177
8.0%
0 175
7.9%
3 148
 
6.7%
4 77
 
3.5%
5 77
 
3.5%
6 77
 
3.5%
Other values (3) 202
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1110
50.0%
Other Letter 740
33.3%
Dash Punctuation 370
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 177
15.9%
2 177
15.9%
0 175
15.8%
3 148
13.3%
4 77
6.9%
5 77
6.9%
6 77
6.9%
7 68
 
6.1%
8 67
 
6.0%
9 67
 
6.0%
Other Letter
ValueCountFrequency (%)
용 370
50.0%
산 370
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 370
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1480
66.7%
Hangul 740
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 370
25.0%
1 177
12.0%
2 177
12.0%
0 175
11.8%
3 148
 
10.0%
4 77
 
5.2%
5 77
 
5.2%
6 77
 
5.2%
7 68
 
4.6%
8 67
 
4.5%
Hangul
ValueCountFrequency (%)
용 370
50.0%
산 370
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1480
66.7%
Hangul 740
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 370
50.0%
산 370
50.0%
ASCII
ValueCountFrequency (%)
- 370
25.0%
1 177
12.0%
2 177
12.0%
0 175
11.8%
3 148
 
10.0%
4 77
 
5.2%
5 77
 
5.2%
6 77
 
5.2%
7 68
 
4.6%
8 67
 
4.5%

관리번호.1
Text

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:15:27.111457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.6324324
Min length7

Characters and Unicode

Total characters2824
Distinct characters37
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

Unique370 ?
Unique (%)100.0%

Sample

1st row후암동-001
2nd row후암동-002
3rd row후암동-003
4th row후암동-004
5th row후암동-005
ValueCountFrequency (%)
용문동 11
 
2.9%
후암동-001 1
 
0.3%
이태원2동-001 1
 
0.3%
이태원2동-010 1
 
0.3%
이태원2동-009 1
 
0.3%
이태원2동-008 1
 
0.3%
이태원2동-007 1
 
0.3%
이태원2동-006 1
 
0.3%
이태원2동-005 1
 
0.3%
이태원2동-004 1
 
0.3%
Other values (361) 361
94.8%
2023-12-12T18:15:27.643958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 489
17.3%
동 370
13.1%
- 370
13.1%
2 221
 
7.8%
1 192
 
6.8%
원 107
 
3.8%
3 91
 
3.2%
효 90
 
3.2%
4 60
 
2.1%
남 57
 
2.0%
Other values (27) 777
27.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1226
43.4%
Other Letter 1217
43.1%
Dash Punctuation 370
 
13.1%
Space Separator 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 370
30.4%
원 107
 
8.8%
효 90
 
7.4%
남 57
 
4.7%
이 51
 
4.2%
한 51
 
4.2%
태 48
 
3.9%
용 39
 
3.2%
청 37
 
3.0%
파 37
 
3.0%
Other values (15) 330
27.1%
Decimal Number
ValueCountFrequency (%)
0 489
39.9%
2 221
18.0%
1 192
 
15.7%
3 91
 
7.4%
4 60
 
4.9%
5 41
 
3.3%
6 34
 
2.8%
8 33
 
2.7%
7 33
 
2.7%
9 32
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 370
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1607
56.9%
Hangul 1217
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 370
30.4%
원 107
 
8.8%
효 90
 
7.4%
남 57
 
4.7%
이 51
 
4.2%
한 51
 
4.2%
태 48
 
3.9%
용 39
 
3.2%
청 37
 
3.0%
파 37
 
3.0%
Other values (15) 330
27.1%
Common
ValueCountFrequency (%)
0 489
30.4%
- 370
23.0%
2 221
13.8%
1 192
 
11.9%
3 91
 
5.7%
4 60
 
3.7%
5 41
 
2.6%
6 34
 
2.1%
8 33
 
2.1%
7 33
 
2.1%
Other values (2) 43
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1607
56.9%
Hangul 1217
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 489
30.4%
- 370
23.0%
2 221
13.8%
1 192
 
11.9%
3 91
 
5.7%
4 60
 
3.7%
5 41
 
2.6%
6 34
 
2.1%
8 33
 
2.1%
7 33
 
2.1%
Other values (2) 43
 
2.7%
Hangul
ValueCountFrequency (%)
동 370
30.4%
원 107
 
8.8%
효 90
 
7.4%
남 57
 
4.7%
이 51
 
4.2%
한 51
 
4.2%
태 48
 
3.9%
용 39
 
3.2%
청 37
 
3.0%
파 37
 
3.0%
Other values (15) 330
27.1%

도로명
Text

Distinct194
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:15:27.976608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.1513514
Min length3

Characters and Unicode

Total characters2276
Distinct characters71
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)34.1%

Sample

1st row한강대로102길
2nd row한강대로98나길
3rd row소월로2나길
4th row소월로2다길
5th row두텁바위로
ValueCountFrequency (%)
효창원로 23
 
6.2%
서빙고로 19
 
5.1%
청파로 18
 
4.9%
효창원로15길 10
 
2.7%
두텁바위로 6
 
1.6%
우사단로10다길 6
 
1.6%
효창원로69길 5
 
1.3%
만리재로 5
 
1.3%
장문로 5
 
1.3%
원효로19길 4
 
1.1%
Other values (184) 270
72.8%
2023-12-12T18:15:28.492924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 369
 
16.2%
길 268
 
11.8%
원 96
 
4.2%
1 93
 
4.1%
효 81
 
3.6%
4 79
 
3.5%
창 75
 
3.3%
2 71
 
3.1%
5 64
 
2.8%
3 53
 
2.3%
Other values (61) 1027
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1708
75.0%
Decimal Number 563
 
24.7%
Space Separator 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 369
21.6%
길 268
15.7%
원 96
 
5.6%
효 81
 
4.7%
창 75
 
4.4%
사 46
 
2.7%
대 46
 
2.7%
나 43
 
2.5%
서 30
 
1.8%
가 28
 
1.6%
Other values (50) 626
36.7%
Decimal Number
ValueCountFrequency (%)
1 93
16.5%
4 79
14.0%
2 71
12.6%
5 64
11.4%
3 53
9.4%
0 48
8.5%
6 43
7.6%
7 41
7.3%
9 38
6.7%
8 33
 
5.9%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1708
75.0%
Common 568
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 369
21.6%
길 268
15.7%
원 96
 
5.6%
효 81
 
4.7%
창 75
 
4.4%
사 46
 
2.7%
대 46
 
2.7%
나 43
 
2.5%
서 30
 
1.8%
가 28
 
1.6%
Other values (50) 626
36.7%
Common
ValueCountFrequency (%)
1 93
16.4%
4 79
13.9%
2 71
12.5%
5 64
11.3%
3 53
9.3%
0 48
8.5%
6 43
7.6%
7 41
7.2%
9 38
6.7%
8 33
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1708
75.0%
ASCII 568
 
25.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 369
21.6%
길 268
15.7%
원 96
 
5.6%
효 81
 
4.7%
창 75
 
4.4%
사 46
 
2.7%
대 46
 
2.7%
나 43
 
2.5%
서 30
 
1.8%
가 28
 
1.6%
Other values (50) 626
36.7%
ASCII
ValueCountFrequency (%)
1 93
16.4%
4 79
13.9%
2 71
12.5%
5 64
11.3%
3 53
9.3%
0 48
8.5%
6 43
7.6%
7 41
7.2%
9 38
6.7%
8 33
 
5.8%

규격
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing370
Missing (%)100.0%
Memory size3.4 KiB

위치-구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
용산구
370 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구 370
100.0%

Length

2023-12-12T18:15:28.678857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:15:28.800153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구 370
100.0%

위치-도로명
Text

Distinct196
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:15:29.111302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.216216
Min length13

Characters and Unicode

Total characters6000
Distinct characters79
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

Unique117 ?
Unique (%)31.6%

Sample

1st row서울특별시 용산구 한강대로102길
2nd row서울특별시 용산구 한강대로98나길
3rd row서울특별시 용산구 소월로2나길
4th row서울특별시 용산구 소월로2다길
5th row서울특별시 용산구 두텁바위로
ValueCountFrequency (%)
서울특별시 370
33.3%
용산구 370
33.3%
회나무로 21
 
1.9%
효창원로 11
 
1.0%
효창원로15길 10
 
0.9%
우사단로10다길 6
 
0.5%
서빙고로91나길 6
 
0.5%
두텁바위로 6
 
0.5%
녹사평대로 6
 
0.5%
효창원로69길 5
 
0.5%
Other values (188) 300
27.0%
2023-12-12T18:15:29.630724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
745
 
12.4%
서 400
 
6.7%
울 370
 
6.2%
산 370
 
6.2%
용 370
 
6.2%
구 370
 
6.2%
시 370
 
6.2%
별 370
 
6.2%
특 370
 
6.2%
로 369
 
6.2%
Other values (69) 1896
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4705
78.4%
Space Separator 745
 
12.4%
Decimal Number 549
 
9.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 400
 
8.5%
울 370
 
7.9%
산 370
 
7.9%
용 370
 
7.9%
구 370
 
7.9%
시 370
 
7.9%
별 370
 
7.9%
특 370
 
7.9%
로 369
 
7.8%
길 286
 
6.1%
Other values (57) 1060
22.5%
Decimal Number
ValueCountFrequency (%)
1 92
16.8%
4 62
11.3%
5 61
11.1%
2 60
10.9%
7 55
10.0%
9 52
9.5%
0 44
8.0%
6 43
7.8%
3 42
7.7%
8 38
6.9%
Space Separator
ValueCountFrequency (%)
745
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4705
78.4%
Common 1295
 
21.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 400
 
8.5%
울 370
 
7.9%
산 370
 
7.9%
용 370
 
7.9%
구 370
 
7.9%
시 370
 
7.9%
별 370
 
7.9%
특 370
 
7.9%
로 369
 
7.8%
길 286
 
6.1%
Other values (57) 1060
22.5%
Common
ValueCountFrequency (%)
745
57.5%
1 92
 
7.1%
4 62
 
4.8%
5 61
 
4.7%
2 60
 
4.6%
7 55
 
4.2%
9 52
 
4.0%
0 44
 
3.4%
6 43
 
3.3%
3 42
 
3.2%
Other values (2) 39
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4705
78.4%
ASCII 1295
 
21.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
745
57.5%
1 92
 
7.1%
4 62
 
4.8%
5 61
 
4.7%
2 60
 
4.6%
7 55
 
4.2%
9 52
 
4.0%
0 44
 
3.4%
6 43
 
3.3%
3 42
 
3.2%
Other values (2) 39
 
3.0%
Hangul
ValueCountFrequency (%)
서 400
 
8.5%
울 370
 
7.9%
산 370
 
7.9%
용 370
 
7.9%
구 370
 
7.9%
시 370
 
7.9%
별 370
 
7.9%
특 370
 
7.9%
로 369
 
7.8%
길 286
 
6.1%
Other values (57) 1060
22.5%

위치-번호
Text

Distinct118
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:15:30.021029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.0405405
Min length1

Characters and Unicode

Total characters755
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)14.6%

Sample

1st row57
2nd row25
3rd row18
4th row21
5th row177
ValueCountFrequency (%)
7 13
 
3.5%
16 12
 
3.2%
15 11
 
3.0%
31 10
 
2.7%
21 9
 
2.4%
34 9
 
2.4%
22 9
 
2.4%
27 8
 
2.2%
18 8
 
2.2%
38 8
 
2.2%
Other values (108) 273
73.8%
2023-12-12T18:15:30.472670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 145
19.2%
2 116
15.4%
3 107
14.2%
4 66
8.7%
5 64
8.5%
7 63
8.3%
6 55
 
7.3%
8 47
 
6.2%
0 46
 
6.1%
9 35
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 744
98.5%
Dash Punctuation 11
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 145
19.5%
2 116
15.6%
3 107
14.4%
4 66
8.9%
5 64
8.6%
7 63
8.5%
6 55
 
7.4%
8 47
 
6.3%
0 46
 
6.2%
9 35
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 755
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 145
19.2%
2 116
15.4%
3 107
14.2%
4 66
8.7%
5 64
8.5%
7 63
8.3%
6 55
 
7.3%
8 47
 
6.2%
0 46
 
6.1%
9 35
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 145
19.2%
2 116
15.4%
3 107
14.2%
4 66
8.7%
5 64
8.5%
7 63
8.3%
6 55
 
7.3%
8 47
 
6.2%
0 46
 
6.1%
9 35
 
4.6%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing370
Missing (%)100.0%
Memory size3.4 KiB

Interactions

2023-12-12T18:15:24.845575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T18:15:25.004349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:15:25.220543image/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

연번관리번호관리번호.1도로명규격위치-구위치-도로명위치-번호비고
01용산-001후암동-001한강대로102길<NA>용산구서울특별시 용산구 한강대로102길57<NA>
12용산-002후암동-002한강대로98나길<NA>용산구서울특별시 용산구 한강대로98나길25<NA>
23용산-003후암동-003소월로2나길<NA>용산구서울특별시 용산구 소월로2나길18<NA>
34용산-004후암동-004소월로2다길<NA>용산구서울특별시 용산구 소월로2다길21<NA>
45용산-005후암동-005두텁바위로<NA>용산구서울특별시 용산구 두텁바위로177<NA>
56용산-006후암동-006후암로48길<NA>용산구서울특별시 용산구 후암로48길38<NA>
67용산-007후암동-007후암로34길<NA>용산구서울특별시 용산구 후암로34길6<NA>
78용산-008후암동-008후암로34길<NA>용산구서울특별시 용산구 후암로34길31<NA>
89용산-009후암동-009두텁바위로75길<NA>용산구서울특별시 용산구 두텁바위로75길25<NA>
910용산-010후암동-010두텁바위로75길<NA>용산구서울특별시 용산구 두텁바위로75길3<NA>
연번관리번호관리번호.1도로명규격위치-구위치-도로명위치-번호비고
360361용산-361보광동-025장문로45길<NA>용산구서울특별시 용산구 장문로45길76-18<NA>
361362용산-362보광동-026우사단로10길<NA>용산구서울특별시 용산구 우사단로10길150<NA>
362363용산-363보광동-027우사단로10마길<NA>용산구서울특별시 용산구 우사단로10마길22<NA>
363364용산-364보광동-028우사단로10길<NA>용산구서울특별시 용산구 우사단로10길160<NA>
364365용산-365보광동-029장문로45나길<NA>용산구서울특별시 용산구 장문로45나길27<NA>
365366용산-366보광동-030장문로45가길<NA>용산구서울특별시 용산구 장문로45가길33<NA>
366367용산-367보광동-031장문로45가길<NA>용산구서울특별시 용산구 장문로45가길21<NA>
367368용산-368보광동-032보광로5길<NA>용산구서울특별시 용산구 보광로5길37<NA>
368369용산-369보광동-033서빙고로<NA>용산구서울특별시 용산구 서빙고로373<NA>
369370용산-370보광동-034장문로<NA>용산구서울특별시 용산구 장문로95<NA>