Overview

Dataset statistics

Number of variables9
Number of observations160
Missing cells80
Missing cells (%)5.6%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory11.8 KiB
Average record size in memory75.8 B

Variable types

Text2
Categorical5
Numeric2

Dataset

Description관리번호,구분코드(01:전력구,02:통신구),관리기관,관리부서,시설물명,집수정위치,자치구,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21119/S/1/datasetView.do

Alerts

구분코드(01:전력구,02:통신구) has constant value ""Constant
관리기관 has constant value ""Constant
시설물명 has constant value ""Constant
Dataset has 1 (0.6%) duplicate rowsDuplicates
X좌표 is highly overall correlated with 관리부서 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with 관리부서 and 1 other fieldsHigh correlation
관리부서 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
자치구 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
관리번호 has 80 (50.0%) missing valuesMissing

Reproduction

Analysis started2023-12-11 08:17:57.837720
Analysis finished2023-12-11 08:17:59.140593
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

MISSING 

Distinct80
Distinct (%)100.0%
Missing80
Missing (%)50.0%
Memory size1.4 KiB
2023-12-11T17:17:59.423007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters880
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

Unique80 ?
Unique (%)100.0%

Sample

1st row2019_1_0212
2nd row2019_1_0214
3rd row2019_1_0215
4th row2019_1_0216
5th row2019_1_0217
ValueCountFrequency (%)
2019_1_0214 1
 
1.2%
2019_1_0215 1
 
1.2%
2019_1_0286 1
 
1.2%
2019_1_0285 1
 
1.2%
2019_1_0284 1
 
1.2%
2019_1_0283 1
 
1.2%
2019_1_0282 1
 
1.2%
2019_1_0281 1
 
1.2%
2019_1_0280 1
 
1.2%
2019_1_0279 1
 
1.2%
Other values (70) 70
87.5%
2023-12-11T17:18:00.007369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 177
20.1%
1 174
19.8%
2 165
18.8%
_ 160
18.2%
9 96
10.9%
3 25
 
2.8%
6 18
 
2.0%
7 18
 
2.0%
8 17
 
1.9%
4 15
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 720
81.8%
Connector Punctuation 160
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 177
24.6%
1 174
24.2%
2 165
22.9%
9 96
13.3%
3 25
 
3.5%
6 18
 
2.5%
7 18
 
2.5%
8 17
 
2.4%
4 15
 
2.1%
5 15
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_ 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 177
20.1%
1 174
19.8%
2 165
18.8%
_ 160
18.2%
9 96
10.9%
3 25
 
2.8%
6 18
 
2.0%
7 18
 
2.0%
8 17
 
1.9%
4 15
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 177
20.1%
1 174
19.8%
2 165
18.8%
_ 160
18.2%
9 96
10.9%
3 25
 
2.8%
6 18
 
2.0%
7 18
 
2.0%
8 17
 
1.9%
4 15
 
1.7%

구분코드(01:전력구,02:통신구)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
160 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 160
100.0%

Length

2023-12-11T17:18:00.222656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:18:00.339936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 160
100.0%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
㈜KT
160 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row㈜KT
2nd row㈜KT
3rd row㈜KT
4th row㈜KT
5th row㈜KT

Common Values

ValueCountFrequency (%)
㈜KT 160
100.0%

Length

2023-12-11T17:18:00.492242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:18:00.640485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
㈜kt 160
100.0%

관리부서
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
통신구팀
84 
kt 신촌지점
14 
kt 광화문지사(혜화)
12 
kt 성수지점
10 
kt 원효지점
10 
Other values (5)
30 

Length

Max length12
Median length4
Mean length6.1125
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowkt 성수지점
2nd rowkt 성수지점
3rd rowkt 성수지점
4th rowkt 성수지점
5th rowkt 성수지점

Common Values

ValueCountFrequency (%)
통신구팀 84
52.5%
kt 신촌지점 14
 
8.8%
kt 광화문지사(혜화) 12
 
7.5%
kt 성수지점 10
 
6.2%
kt 원효지점 10
 
6.2%
KT구로지사 10
 
6.2%
kt 서대문지사(가좌) 8
 
5.0%
KT동작지사 6
 
3.8%
kt 도봉지점(방학) 4
 
2.5%
kt 서대문지사(홍제) 2
 
1.2%

Length

2023-12-11T17:18:00.795102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:18:01.312571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통신구팀 84
38.2%
kt 60
27.3%
신촌지점 14
 
6.4%
광화문지사(혜화 12
 
5.5%
성수지점 10
 
4.5%
원효지점 10
 
4.5%
kt구로지사 10
 
4.5%
서대문지사(가좌 8
 
3.6%
kt동작지사 6
 
2.7%
도봉지점(방학 4
 
1.8%

시설물명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
통신구
160 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
통신구 160
100.0%

Length

2023-12-11T17:18:01.518576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:18:01.656165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통신구 160
100.0%

집수정위치
Text

Distinct79
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T17:18:01.928253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27.5
Mean length24.275
Min length14

Characters and Unicode

Total characters3884
Distinct characters195
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

Unique0 ?
Unique (%)0.0%

Sample

1st row서울시 성동구 아차산로 13길47 (KT성수지점앞)
2nd row서울시 성동구 아차산로 13길54(신한은행앞)
3rd row서울시 광진구 동일로 190(화양사거리)
4th row서울시 성동구 아차산로 13길47 (KT 성수지점앞)
5th row서울시 성동구 아차산로 13길47 (KT 성수지점앞)
ValueCountFrequency (%)
서울시 76
 
11.8%
집수정 24
 
3.7%
성북구 24
 
3.7%
종로구 18
 
2.8%
앞 16
 
2.5%
동대문구 16
 
2.5%
서대문구 14
 
2.2%
마포구 14
 
2.2%
용산구 10
 
1.6%
성동구 8
 
1.2%
Other values (179) 422
65.7%
2023-12-11T17:18:02.454383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
482
 
12.4%
로 180
 
4.6%
) 160
 
4.1%
( 160
 
4.1%
구 150
 
3.9%
동 140
 
3.6%
1 136
 
3.5%
2 98
 
2.5%
서 94
 
2.4%
4 82
 
2.1%
Other values (185) 2202
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2276
58.6%
Decimal Number 684
 
17.6%
Space Separator 482
 
12.4%
Close Punctuation 160
 
4.1%
Open Punctuation 160
 
4.1%
Dash Punctuation 64
 
1.6%
Other Punctuation 26
 
0.7%
Uppercase Letter 16
 
0.4%
Lowercase Letter 16
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 180
 
7.9%
구 150
 
6.6%
동 140
 
6.2%
서 94
 
4.1%
시 82
 
3.6%
울 76
 
3.3%
문 74
 
3.3%
앞 62
 
2.7%
대 58
 
2.5%
성 48
 
2.1%
Other values (166) 1312
57.6%
Decimal Number
ValueCountFrequency (%)
1 136
19.9%
2 98
14.3%
4 82
12.0%
3 70
10.2%
6 52
 
7.6%
5 52
 
7.6%
8 52
 
7.6%
7 52
 
7.6%
9 48
 
7.0%
0 42
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
K 8
50.0%
T 8
50.0%
Lowercase Letter
ValueCountFrequency (%)
k 8
50.0%
t 8
50.0%
Space Separator
ValueCountFrequency (%)
482
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%
Open Punctuation
ValueCountFrequency (%)
( 160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2276
58.6%
Common 1576
40.6%
Latin 32
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 180
 
7.9%
구 150
 
6.6%
동 140
 
6.2%
서 94
 
4.1%
시 82
 
3.6%
울 76
 
3.3%
문 74
 
3.3%
앞 62
 
2.7%
대 58
 
2.5%
성 48
 
2.1%
Other values (166) 1312
57.6%
Common
ValueCountFrequency (%)
482
30.6%
) 160
 
10.2%
( 160
 
10.2%
1 136
 
8.6%
2 98
 
6.2%
4 82
 
5.2%
3 70
 
4.4%
- 64
 
4.1%
6 52
 
3.3%
5 52
 
3.3%
Other values (5) 220
14.0%
Latin
ValueCountFrequency (%)
K 8
25.0%
T 8
25.0%
k 8
25.0%
t 8
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2276
58.6%
ASCII 1608
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
482
30.0%
) 160
 
10.0%
( 160
 
10.0%
1 136
 
8.5%
2 98
 
6.1%
4 82
 
5.1%
3 70
 
4.4%
- 64
 
4.0%
6 52
 
3.2%
5 52
 
3.2%
Other values (9) 252
15.7%
Hangul
ValueCountFrequency (%)
로 180
 
7.9%
구 150
 
6.6%
동 140
 
6.2%
서 94
 
4.1%
시 82
 
3.6%
울 76
 
3.3%
문 74
 
3.3%
앞 62
 
2.7%
대 58
 
2.5%
성 48
 
2.1%
Other values (166) 1312
57.6%

자치구
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
성북구
26 
종로구
22 
동대문구
18 
마포구
16 
중 구
16 
Other values (11)
62 

Length

Max length4
Median length3
Mean length3.1875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성동구
2nd row성동구
3rd row광진구
4th row성동구
5th row성동구

Common Values

ValueCountFrequency (%)
성북구 26
16.2%
종로구 22
13.8%
동대문구 18
11.2%
마포구 16
10.0%
중 구 16
10.0%
서대문구 12
7.5%
용산구 12
7.5%
성동구 8
 
5.0%
관악구 6
 
3.8%
동작구 6
 
3.8%
Other values (6) 18
11.2%

Length

2023-12-11T17:18:02.668715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성북구 26
14.8%
종로구 22
12.5%
동대문구 18
10.2%
마포구 16
9.1%
중 16
9.1%
구 16
9.1%
서대문구 12
6.8%
용산구 12
6.8%
성동구 8
 
4.5%
관악구 6
 
3.4%
Other values (7) 24
13.6%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199122.47
Minimum189980.94
Maximum206020.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T17:18:02.832549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189980.94
5-th percentile192323.27
Q1195070.81
median200129.94
Q3202612.54
95-th percentile205462.98
Maximum206020.13
Range16039.19
Interquartile range (IQR)7541.7325

Descriptive statistics

Standard deviation4570.9304
Coefficient of variation (CV)0.022955372
Kurtosis-1.1899116
Mean199122.47
Median Absolute Deviation (MAD)3646.62
Skewness-0.23766085
Sum31859596
Variance20893404
MonotonicityNot monotonic
2023-12-11T17:18:03.040616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205462.98 6
 
3.8%
194202.19 6
 
3.8%
200129.94 4
 
2.5%
197444.72 2
 
1.2%
204037.16 2
 
1.2%
204759.19 2
 
1.2%
205462.03 2
 
1.2%
197226.15 2
 
1.2%
197292.76 2
 
1.2%
197523.67 2
 
1.2%
Other values (65) 130
81.2%
ValueCountFrequency (%)
189980.94 2
1.2%
190323.43 2
1.2%
191187.67 2
1.2%
192139.75 2
1.2%
192332.93 2
1.2%
192342.94 2
1.2%
192372.44 2
1.2%
192416.46 2
1.2%
193196.03 2
1.2%
193207.38 2
1.2%
ValueCountFrequency (%)
206020.13 2
 
1.2%
205553.58 2
 
1.2%
205462.98 6
3.8%
205462.03 2
 
1.2%
205348.87 2
 
1.2%
205191.52 2
 
1.2%
205046.18 2
 
1.2%
204990.44 2
 
1.2%
204941.08 2
 
1.2%
204838.12 2
 
1.2%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451896.89
Minimum442231.24
Maximum463026.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T17:18:03.247487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442231.24
5-th percentile442714.82
Q1450643.91
median452277.36
Q3453909.39
95-th percentile456681.37
Maximum463026.04
Range20794.8
Interquartile range (IQR)3265.4775

Descriptive statistics

Standard deviation3919.6045
Coefficient of variation (CV)0.00867367
Kurtosis1.3986717
Mean451896.89
Median Absolute Deviation (MAD)1704.93
Skewness-0.30601527
Sum72303503
Variance15363300
MonotonicityNot monotonic
2023-12-11T17:18:03.414885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449785.41 6
 
3.8%
445781.28 6
 
3.8%
452993.76 4
 
2.5%
452328.8 2
 
1.2%
456114.31 2
 
1.2%
456660.43 2
 
1.2%
455881.72 2
 
1.2%
451169.47 2
 
1.2%
451356.36 2
 
1.2%
451019.48 2
 
1.2%
Other values (65) 130
81.2%
ValueCountFrequency (%)
442231.24 2
 
1.2%
442267.81 2
 
1.2%
442520.96 2
 
1.2%
442531.97 2
 
1.2%
442724.44 2
 
1.2%
445781.28 6
3.8%
447359.32 2
 
1.2%
447431.77 2
 
1.2%
448432.13 2
 
1.2%
448483.27 2
 
1.2%
ValueCountFrequency (%)
463026.04 2
1.2%
462863.13 2
1.2%
458286.03 2
1.2%
457079.21 2
1.2%
456660.43 2
1.2%
456114.31 2
1.2%
455988.1 2
1.2%
455947.88 2
1.2%
455881.72 2
1.2%
455881.02 2
1.2%

Interactions

2023-12-11T17:17:58.577153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:17:58.275501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:17:58.704847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:17:58.443519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:18:03.509468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호관리부서집수정위치자치구X좌표Y좌표
관리번호1.0001.0001.0001.0001.0001.000
관리부서1.0001.0001.0000.9700.9540.918
집수정위치1.0001.0001.0001.0001.0001.000
자치구1.0000.9701.0001.0000.9130.970
X좌표1.0000.9541.0000.9131.0000.732
Y좌표1.0000.9181.0000.9700.7321.000
2023-12-11T17:18:03.634382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리부서자치구
관리부서1.0000.845
자치구0.8451.000
2023-12-11T17:18:03.747513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X좌표Y좌표관리부서자치구
X좌표1.0000.4530.6450.673
Y좌표0.4531.0000.7390.854
관리부서0.6450.7391.0000.845
자치구0.6730.8540.8451.000

Missing values

2023-12-11T17:17:58.878799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:17:59.072392image/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

관리번호구분코드(01:전력구,02:통신구)관리기관관리부서시설물명집수정위치자치구X좌표Y좌표
02019_1_02122㈜KTkt 성수지점통신구서울시 성동구 아차산로 13길47 (KT성수지점앞)성동구205462.98449785.41
12019_1_02142㈜KTkt 성수지점통신구서울시 성동구 아차산로 13길54(신한은행앞)성동구205553.58449796.49
22019_1_02152㈜KTkt 성수지점통신구서울시 광진구 동일로 190(화양사거리)광진구206020.13449917.67
32019_1_02162㈜KTkt 성수지점통신구서울시 성동구 아차산로 13길47 (KT 성수지점앞)성동구205462.98449785.41
42019_1_02172㈜KTkt 성수지점통신구서울시 성동구 아차산로 13길47 (KT 성수지점앞)성동구205462.98449785.41
52019_1_02202㈜KTkt 서대문지사(가좌)통신구서울시 서대문구 응암로121 (kt가좌지사 우측편)서대문구192372.44453800.82
62019_1_02212㈜KTkt 서대문지사(가좌)통신구서울시 서대문구 응암로113 (중소기업은행앞)서대문구192332.93453691.4
72019_1_02222㈜KTkt 서대문지사(가좌)통신구서울시 서대문구 증가로30길 25 (kt가좌지사 후면)서대문구192342.94453836.48
82019_1_02232㈜KTkt 서대문지사(가좌)통신구서울시 서대문구 증가로 261(증산2교 북단 우측)은평구192139.75453814.05
92019_1_02282㈜KTkt 서대문지사(홍제)통신구서울시 서대문구 홍은중앙로 13(홍제초등학교 옆)서대문구195179.81454883.5
관리번호구분코드(01:전력구,02:통신구)관리기관관리부서시설물명집수정위치자치구X좌표Y좌표
150<NA>2㈜KT통신구팀통신구논현로872(신사동610-2), 압구정사거리 집수정강남구202548.67447431.77
151<NA>2㈜KT통신구팀통신구서빙고로4-12(한강3가 49-3), 용산병원 집수정용산구196920.7447359.32
152<NA>2㈜KT통신구팀통신구신촌로297(북아현동126-30), 아현삼거리 집수정마포구196395.79450897.93
153<NA>2㈜KT통신구팀통신구세종대로83(태평로2가344-3), 시청 집수정중 구197923.08451572.19
154<NA>2㈜KT통신구팀통신구을지로54(을지로2가199-78), 중앙국사 분기 집수정중 구198559.1451813.14
155<NA>2㈜KT통신구팀통신구을지로79(을지로2가50), 을지로2가 집수정중 구198813.1451884.17
156<NA>2㈜KT통신구팀통신구다산로248(신당동100-1), 율원파출소 집수정중 구201447.59451723.36
157<NA>2㈜KT통신구팀통신구종로266(종로6가262-1), 청계6가 집수정종로구200647.43452351.7
158<NA>2㈜KT통신구팀통신구낙산성곽길2(창신동697-3), 동대문 집수정종로구200871.1452464.94
159<NA>2㈜KT통신구팀통신구장충단로247(을지로6가18-21), 동대문운동장 집수장동대문구200650.07451918.36

Duplicate rows

Most frequently occurring

관리번호구분코드(01:전력구,02:통신구)관리기관관리부서시설물명집수정위치자치구X좌표Y좌표# duplicates
0<NA>2㈜KTkt 성수지점통신구서울시 성동구 아차산로 13길47 (KT 성수지점앞)성동구205462.98449785.412