Overview

Dataset statistics

Number of variables16
Number of observations772
Missing cells316
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory98.9 KiB
Average record size in memory131.2 B

Variable types

Text4
Categorical8
Numeric3
DateTime1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-20908/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치위치(층) and 3 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
설치위치(층) is highly imbalanced (75.4%)Imbalance
wifi접속환경 is highly imbalanced (94.8%)Imbalance
도로명주소 has 138 (17.9%) missing valuesMissing
상세주소 has 178 (23.1%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 04:45:11.318168
Analysis finished2024-05-18 04:45:19.269507
Duration7.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-18T13:45:19.899555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.3367876
Min length7

Characters and Unicode

Total characters7208
Distinct characters24
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)100.0%

Sample

1st rowARI00133
2nd rowARI00134
3rd rowARI00135
4th rowARI00136
5th rowARI00137
ValueCountFrequency (%)
ari00133 1
 
0.1%
서울-1051 1
 
0.1%
서울-1082-2 1
 
0.1%
서울-1078 1
 
0.1%
서울-1080 1
 
0.1%
서울-1080-1 1
 
0.1%
서울-1080-2 1
 
0.1%
서울-1081 1
 
0.1%
서울-1081-1 1
 
0.1%
서울-1081-2 1
 
0.1%
Other values (762) 762
98.7%
2024-05-18T13:45:21.252365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 836
 
11.6%
- 768
 
10.7%
2 698
 
9.7%
1 687
 
9.5%
4 452
 
6.3%
5 394
 
5.5%
울 336
 
4.7%
서 336
 
4.7%
3 298
 
4.1%
9 267
 
3.7%
Other values (14) 2136
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4268
59.2%
Uppercase Letter 1268
 
17.6%
Other Letter 904
 
12.5%
Dash Punctuation 768
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 836
19.6%
2 698
16.4%
1 687
16.1%
4 452
10.6%
5 394
9.2%
3 298
 
7.0%
9 267
 
6.3%
6 230
 
5.4%
8 229
 
5.4%
7 177
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 198
15.6%
J 196
15.5%
D 196
15.5%
P 174
13.7%
W 150
11.8%
F 150
11.8%
S 90
7.1%
B 66
 
5.2%
R 24
 
1.9%
I 24
 
1.9%
Other Letter
ValueCountFrequency (%)
울 336
37.2%
서 336
37.2%
차 232
25.7%
Dash Punctuation
ValueCountFrequency (%)
- 768
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5036
69.9%
Latin 1268
 
17.6%
Hangul 904
 
12.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 836
16.6%
- 768
15.3%
2 698
13.9%
1 687
13.6%
4 452
9.0%
5 394
7.8%
3 298
 
5.9%
9 267
 
5.3%
6 230
 
4.6%
8 229
 
4.5%
Latin
ValueCountFrequency (%)
A 198
15.6%
J 196
15.5%
D 196
15.5%
P 174
13.7%
W 150
11.8%
F 150
11.8%
S 90
7.1%
B 66
 
5.2%
R 24
 
1.9%
I 24
 
1.9%
Hangul
ValueCountFrequency (%)
울 336
37.2%
서 336
37.2%
차 232
25.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6304
87.5%
Hangul 904
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 836
13.3%
- 768
12.2%
2 698
11.1%
1 687
10.9%
4 452
 
7.2%
5 394
 
6.2%
3 298
 
4.7%
9 267
 
4.2%
6 230
 
3.6%
8 229
 
3.6%
Other values (11) 1445
22.9%
Hangul
ValueCountFrequency (%)
울 336
37.2%
서 336
37.2%
차 232
25.7%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
동작구
772 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동작구 772
100.0%

Length

2024-05-18T13:45:21.803909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:22.496393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작구 772
100.0%

와이파이명
Text

Distinct237
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-18T13:45:22.852893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length8.015544
Min length3

Characters and Unicode

Total characters6188
Distinct characters259
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

Unique136 ?
Unique (%)17.6%

Sample

1st row남부수도사업소
2nd row남부수도사업소
3rd row남부수도사업소
4th row남부수도사업소
5th row남부수도사업소
ValueCountFrequency (%)
보라매공원 48
 
6.0%
숭실대학교 34
 
4.2%
중앙대학교 34
 
4.2%
사당4동주민센터인근거리 28
 
3.5%
노량진수산시장 24
 
3.0%
대방동노량진공원 19
 
2.4%
시립보라매청소년센터 18
 
2.2%
남부수도사업소 17
 
2.1%
사당역먹자골목 16
 
2.0%
성대전통시장 15
 
1.9%
Other values (237) 551
68.5%
2024-05-18T13:45:23.955745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 226
 
3.7%
원 180
 
2.9%
사 167
 
2.7%
터 149
 
2.4%
공 142
 
2.3%
센 140
 
2.3%
소 138
 
2.2%
대 128
 
2.1%
작 120
 
1.9%
장 115
 
1.9%
Other values (249) 4683
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5868
94.8%
Decimal Number 142
 
2.3%
Connector Punctuation 66
 
1.1%
Space Separator 32
 
0.5%
Uppercase Letter 26
 
0.4%
Other Punctuation 17
 
0.3%
Close Punctuation 16
 
0.3%
Open Punctuation 16
 
0.3%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 226
 
3.9%
원 180
 
3.1%
사 167
 
2.8%
터 149
 
2.5%
공 142
 
2.4%
센 140
 
2.4%
소 138
 
2.4%
대 128
 
2.2%
작 120
 
2.0%
장 115
 
2.0%
Other values (226) 4363
74.4%
Decimal Number
ValueCountFrequency (%)
4 45
31.7%
2 26
18.3%
1 17
 
12.0%
3 17
 
12.0%
5 10
 
7.0%
0 10
 
7.0%
9 6
 
4.2%
6 5
 
3.5%
8 3
 
2.1%
7 3
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 7
26.9%
P 7
26.9%
T 4
15.4%
S 3
11.5%
V 2
 
7.7%
C 2
 
7.7%
H 1
 
3.8%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
. 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5868
94.8%
Common 294
 
4.8%
Latin 26
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 226
 
3.9%
원 180
 
3.1%
사 167
 
2.8%
터 149
 
2.5%
공 142
 
2.4%
센 140
 
2.4%
소 138
 
2.4%
대 128
 
2.2%
작 120
 
2.0%
장 115
 
2.0%
Other values (226) 4363
74.4%
Common
ValueCountFrequency (%)
_ 66
22.4%
4 45
15.3%
32
10.9%
2 26
 
8.8%
1 17
 
5.8%
3 17
 
5.8%
. 17
 
5.8%
) 16
 
5.4%
( 16
 
5.4%
5 10
 
3.4%
Other values (6) 32
10.9%
Latin
ValueCountFrequency (%)
A 7
26.9%
P 7
26.9%
T 4
15.4%
S 3
11.5%
V 2
 
7.7%
C 2
 
7.7%
H 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5868
94.8%
ASCII 320
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 226
 
3.9%
원 180
 
3.1%
사 167
 
2.8%
터 149
 
2.5%
공 142
 
2.4%
센 140
 
2.4%
소 138
 
2.4%
대 128
 
2.2%
작 120
 
2.0%
장 115
 
2.0%
Other values (226) 4363
74.4%
ASCII
ValueCountFrequency (%)
_ 66
20.6%
4 45
14.1%
32
10.0%
2 26
 
8.1%
1 17
 
5.3%
3 17
 
5.3%
. 17
 
5.3%
) 16
 
5.0%
( 16
 
5.0%
5 10
 
3.1%
Other values (13) 58
18.1%

도로명주소
Text

MISSING 

Distinct317
Distinct (%)50.0%
Missing138
Missing (%)17.9%
Memory size6.2 KiB
2024-05-18T13:45:24.497840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length32
Mean length18.919558
Min length4

Characters and Unicode

Total characters11995
Distinct characters198
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)37.2%

Sample

1st row여의대방로10길 97
2nd row여의대방로10길 97
3rd row여의대방로10길 97
4th row여의대방로10길 97
5th row여의대방로10길 97
ValueCountFrequency (%)
동작구 400
 
17.0%
서울특별시 232
 
9.9%
서울시 101
 
4.3%
여의대방로20길 58
 
2.5%
공원(하천 49
 
2.1%
49
 
2.1%
33(보라매3 48
 
2.0%
사당동 45
 
1.9%
71 25
 
1.1%
상도로 20
 
0.9%
Other values (453) 1321
56.3%
2024-05-18T13:45:25.557412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1715
 
14.3%
동 562
 
4.7%
로 506
 
4.2%
2 486
 
4.1%
1 467
 
3.9%
3 458
 
3.8%
작 444
 
3.7%
구 407
 
3.4%
길 403
 
3.4%
서 346
 
2.9%
Other values (188) 6201
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6550
54.6%
Decimal Number 2766
23.1%
Space Separator 1715
 
14.3%
Dash Punctuation 251
 
2.1%
Open Punctuation 229
 
1.9%
Close Punctuation 229
 
1.9%
Uppercase Letter 127
 
1.1%
Other Punctuation 123
 
1.0%
Math Symbol 4
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 562
 
8.6%
로 506
 
7.7%
작 444
 
6.8%
구 407
 
6.2%
길 403
 
6.2%
서 346
 
5.3%
시 343
 
5.2%
울 337
 
5.1%
별 234
 
3.6%
특 232
 
3.5%
Other values (161) 2736
41.8%
Decimal Number
ValueCountFrequency (%)
2 486
17.6%
1 467
16.9%
3 458
16.6%
0 316
11.4%
7 206
7.4%
6 188
 
6.8%
4 184
 
6.7%
9 170
 
6.1%
5 169
 
6.1%
8 122
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
C 48
37.8%
T 24
18.9%
V 24
18.9%
F 20
15.7%
U 3
 
2.4%
L 3
 
2.4%
G 3
 
2.4%
B 2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 62
50.4%
, 61
49.6%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1715
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 251
100.0%
Open Punctuation
ValueCountFrequency (%)
( 229
100.0%
Close Punctuation
ValueCountFrequency (%)
) 229
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6550
54.6%
Common 5318
44.3%
Latin 127
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 562
 
8.6%
로 506
 
7.7%
작 444
 
6.8%
구 407
 
6.2%
길 403
 
6.2%
서 346
 
5.3%
시 343
 
5.2%
울 337
 
5.1%
별 234
 
3.6%
특 232
 
3.5%
Other values (161) 2736
41.8%
Common
ValueCountFrequency (%)
1715
32.2%
2 486
 
9.1%
1 467
 
8.8%
3 458
 
8.6%
0 316
 
5.9%
- 251
 
4.7%
( 229
 
4.3%
) 229
 
4.3%
7 206
 
3.9%
6 188
 
3.5%
Other values (9) 773
14.5%
Latin
ValueCountFrequency (%)
C 48
37.8%
T 24
18.9%
V 24
18.9%
F 20
15.7%
U 3
 
2.4%
L 3
 
2.4%
G 3
 
2.4%
B 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6550
54.6%
ASCII 5445
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1715
31.5%
2 486
 
8.9%
1 467
 
8.6%
3 458
 
8.4%
0 316
 
5.8%
- 251
 
4.6%
( 229
 
4.2%
) 229
 
4.2%
7 206
 
3.8%
6 188
 
3.5%
Other values (17) 900
16.5%
Hangul
ValueCountFrequency (%)
동 562
 
8.6%
로 506
 
7.7%
작 444
 
6.8%
구 407
 
6.2%
길 403
 
6.2%
서 346
 
5.3%
시 343
 
5.2%
울 337
 
5.1%
별 234
 
3.6%
특 232
 
3.5%
Other values (161) 2736
41.8%

상세주소
Text

MISSING 

Distinct407
Distinct (%)68.5%
Missing178
Missing (%)23.1%
Memory size6.2 KiB
2024-05-18T13:45:26.200691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length28
Mean length12.148148
Min length2

Characters and Unicode

Total characters7216
Distinct characters335
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)56.9%

Sample

1st row본관 1F
2nd row본관 1F
3rd row본관 1F
4th row본관 1F
5th row본관 2F
ValueCountFrequency (%)
cctv 115
 
10.3%
함체_1 30
 
2.7%
본관 29
 
2.6%
cctv폴대상단_1 28
 
2.5%
2층 28
 
2.5%
폴대_1 28
 
2.5%
상단_1 25
 
2.2%
1층 21
 
1.9%
cctv폴대 16
 
1.4%
3층 15
 
1.3%
Other values (492) 783
70.0%
2024-05-18T13:45:27.983703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 536
 
7.4%
524
 
7.3%
2 288
 
4.0%
_ 268
 
3.7%
0 250
 
3.5%
( 222
 
3.1%
) 219
 
3.0%
C 211
 
2.9%
- 170
 
2.4%
c 152
 
2.1%
Other values (325) 4376
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3241
44.9%
Decimal Number 1642
22.8%
Uppercase Letter 582
 
8.1%
Space Separator 524
 
7.3%
Lowercase Letter 307
 
4.3%
Connector Punctuation 268
 
3.7%
Open Punctuation 222
 
3.1%
Close Punctuation 219
 
3.0%
Dash Punctuation 170
 
2.4%
Other Punctuation 37
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 108
 
3.3%
대 107
 
3.3%
옥 102
 
3.1%
폴 97
 
3.0%
층 96
 
3.0%
범 88
 
2.7%
관 74
 
2.3%
상 74
 
2.3%
앞 73
 
2.3%
실 73
 
2.3%
Other values (281) 2349
72.5%
Uppercase Letter
ValueCountFrequency (%)
C 211
36.3%
T 107
18.4%
V 105
18.0%
F 97
16.7%
B 17
 
2.9%
P 9
 
1.5%
O 9
 
1.5%
E 6
 
1.0%
I 5
 
0.9%
D 4
 
0.7%
Other values (8) 12
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 536
32.6%
2 288
17.5%
0 250
15.2%
3 143
 
8.7%
4 95
 
5.8%
7 80
 
4.9%
8 67
 
4.1%
9 66
 
4.0%
5 61
 
3.7%
6 56
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
c 152
49.5%
v 75
24.4%
t 74
24.1%
u 2
 
0.7%
f 2
 
0.7%
r 1
 
0.3%
n 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 23
62.2%
/ 7
 
18.9%
. 7
 
18.9%
Space Separator
ValueCountFrequency (%)
524
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3241
44.9%
Common 3086
42.8%
Latin 889
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 108
 
3.3%
대 107
 
3.3%
옥 102
 
3.1%
폴 97
 
3.0%
층 96
 
3.0%
범 88
 
2.7%
관 74
 
2.3%
상 74
 
2.3%
앞 73
 
2.3%
실 73
 
2.3%
Other values (281) 2349
72.5%
Latin
ValueCountFrequency (%)
C 211
23.7%
c 152
17.1%
T 107
12.0%
V 105
11.8%
F 97
10.9%
v 75
 
8.4%
t 74
 
8.3%
B 17
 
1.9%
P 9
 
1.0%
O 9
 
1.0%
Other values (15) 33
 
3.7%
Common
ValueCountFrequency (%)
1 536
17.4%
524
17.0%
2 288
9.3%
_ 268
8.7%
0 250
8.1%
( 222
7.2%
) 219
7.1%
- 170
 
5.5%
3 143
 
4.6%
4 95
 
3.1%
Other values (9) 371
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3975
55.1%
Hangul 3241
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 536
13.5%
524
13.2%
2 288
 
7.2%
_ 268
 
6.7%
0 250
 
6.3%
( 222
 
5.6%
) 219
 
5.5%
C 211
 
5.3%
- 170
 
4.3%
c 152
 
3.8%
Other values (34) 1135
28.6%
Hangul
ValueCountFrequency (%)
방 108
 
3.3%
대 107
 
3.3%
옥 102
 
3.1%
폴 97
 
3.0%
층 96
 
3.0%
범 88
 
2.7%
관 74
 
2.3%
상 74
 
2.3%
앞 73
 
2.3%
실 73
 
2.3%
Other values (281) 2349
72.5%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
672 
-
 
38
2
 
25
1
 
12
3
 
11
Other values (7)
 
14

Length

Max length4
Median length4
Mean length3.6204663
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 672
87.0%
- 38
 
4.9%
2 25
 
3.2%
1 12
 
1.6%
3 11
 
1.4%
6 4
 
0.5%
1층 3
 
0.4%
4 2
 
0.3%
B1 2
 
0.3%
5 1
 
0.1%
Other values (2) 2
 
0.3%

Length

2024-05-18T13:45:28.848799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 672
87.0%
38
 
4.9%
2 25
 
3.2%
1 12
 
1.6%
3 11
 
1.4%
6 4
 
0.5%
1층 3
 
0.4%
4 2
 
0.3%
b1 2
 
0.3%
5 1
 
0.1%
Other values (2) 2
 
0.3%

설치유형
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
1. 주요거리
199 
3. 공원(하천)
148 
6-4. 복지 - 아동청소년
60 
5-1. 버스정류소(국비)
42 
7-3. 공공 - 지역
38 
Other values (14)
285 

Length

Max length21
Median length20
Mean length10.972798
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7-1-3. 공공 - 시산하기관
2nd row7-1-3. 공공 - 시산하기관
3rd row7-1-3. 공공 - 시산하기관
4th row7-1-3. 공공 - 시산하기관
5th row7-1-3. 공공 - 시산하기관

Common Values

ValueCountFrequency (%)
1. 주요거리 199
25.8%
3. 공원(하천) 148
19.2%
6-4. 복지 - 아동청소년 60
 
7.8%
5-1. 버스정류소(국비) 42
 
5.4%
7-3. 공공 - 지역 38
 
4.9%
6-3. 복지 - 장애인 37
 
4.8%
7-1-3. 공공 - 시산하기관 36
 
4.7%
4. 문화관광 33
 
4.3%
6-2. 복지 - 노인 32
 
4.1%
2. 전통시장 32
 
4.1%
Other values (9) 115
14.9%

Length

2024-05-18T13:45:29.507935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
294
 
13.4%
1 199
 
9.1%
주요거리 199
 
9.1%
복지 157
 
7.2%
공원(하천 148
 
6.7%
3 148
 
6.7%
공공 137
 
6.2%
아동청소년 60
 
2.7%
6-4 60
 
2.7%
5-1 42
 
1.9%
Other values (34) 750
34.2%

설치기관
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
디지털뉴딜(LG U+)
336 
자치구
205 
서울시(AP)
165 
버스정류소(국비)
42 
버스정류소(시비)
 
24

Length

Max length12
Median length9
Mean length8.2849741
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울시(AP)
2nd row서울시(AP)
3rd row서울시(AP)
4th row서울시(AP)
5th row서울시(AP)

Common Values

ValueCountFrequency (%)
디지털뉴딜(LG U+) 336
43.5%
자치구 205
26.6%
서울시(AP) 165
21.4%
버스정류소(국비) 42
 
5.4%
버스정류소(시비) 24
 
3.1%

Length

2024-05-18T13:45:30.173788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:30.747002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
디지털뉴딜(lg 336
30.3%
u 336
30.3%
자치구 205
18.5%
서울시(ap 165
14.9%
버스정류소(국비 42
 
3.8%
버스정류소(시비 24
 
2.2%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
공공WiFi
583 
과기부WiFi(핫플레이스)
62 
<NA>
 
43
과기부WiFi
 
42
과기부WiFi(복지시설)
 
42

Length

Max length14
Median length6
Mean length6.9663212
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 583
75.5%
과기부WiFi(핫플레이스) 62
 
8.0%
<NA> 43
 
5.6%
과기부WiFi 42
 
5.4%
과기부WiFi(복지시설) 42
 
5.4%

Length

2024-05-18T13:45:31.366833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:31.911501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 583
75.5%
과기부wifi(핫플레이스 62
 
8.0%
na 43
 
5.6%
과기부wifi 42
 
5.4%
과기부wifi(복지시설 42
 
5.4%

망종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
인터넷망_뉴딜용
336 
임대망
157 
자가망_U무선망
117 
자가망U무선망
114 
자가망_수도사업소망
 
24

Length

Max length10
Median length8
Mean length6.7733161
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷망_뉴딜용 336
43.5%
임대망 157
20.3%
자가망_U무선망 117
 
15.2%
자가망U무선망 114
 
14.8%
자가망_수도사업소망 24
 
3.1%
<NA> 24
 
3.1%

Length

2024-05-18T13:45:32.571172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:33.097822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 336
43.5%
임대망 157
20.3%
자가망_u무선망 117
 
15.2%
자가망u무선망 114
 
14.8%
자가망_수도사업소망 24
 
3.1%
na 24
 
3.1%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021.5259
Minimum2018
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-18T13:45:33.627609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2018
5-th percentile2019
Q12021
median2022
Q32022
95-th percentile2023
Maximum2023
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3017408
Coefficient of variation (CV)0.00064393969
Kurtosis0.037318929
Mean2021.5259
Median Absolute Deviation (MAD)1
Skewness-0.98895164
Sum1560618
Variance1.694529
MonotonicityNot monotonic
2024-05-18T13:45:34.116913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 362
46.9%
2023 157
20.3%
2021 101
 
13.1%
2019 94
 
12.2%
2020 46
 
6.0%
2018 12
 
1.6%
ValueCountFrequency (%)
2018 12
 
1.6%
2019 94
 
12.2%
2020 46
 
6.0%
2021 101
 
13.1%
2022 362
46.9%
2023 157
20.3%
ValueCountFrequency (%)
2023 157
20.3%
2022 362
46.9%
2021 101
 
13.1%
2020 46
 
6.0%
2019 94
 
12.2%
2018 12
 
1.6%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
실외
467 
실내
305 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실외 467
60.5%
실내 305
39.5%

Length

2024-05-18T13:45:34.458396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:34.733739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 467
60.5%
실내 305
39.5%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
765 
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정
 
5
10G 백홀, WIFI6E
 
2

Length

Max length53
Median length4
Mean length4.3432642
Min length4

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> 765
99.1%
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정 5
 
0.6%
10G 백홀, WIFI6E 2
 
0.3%

Length

2024-05-18T13:45:35.130217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:45:35.420973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 765
92.1%
후 10
 
1.2%
6.20~6.24 5
 
0.6%
proxy 5
 
0.6%
서버개발 5
 
0.6%
2~3개 5
 
0.6%
임시적용 5
 
0.6%
6월말 5
 
0.6%
cns링크 5
 
0.6%
전체 5
 
0.6%
Other values (5) 16
 
1.9%

X좌표
Real number (ℝ)

Distinct451
Distinct (%)58.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.498147
Minimum37.47603
Maximum37.515198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-18T13:45:35.787140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.47603
5-th percentile37.480477
Q137.49132
median37.4983
Q337.506653
95-th percentile37.513943
Maximum37.515198
Range0.039168
Interquartile range (IQR)0.015333

Descriptive statistics

Standard deviation0.010481212
Coefficient of variation (CV)0.0002795128
Kurtosis-0.9373196
Mean37.498147
Median Absolute Deviation (MAD)0.00801
Skewness-0.13488073
Sum28948.57
Variance0.00010985581
MonotonicityNot monotonic
2024-05-18T13:45:36.432324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.493233 18
 
2.3%
37.492393 17
 
2.2%
37.50442 14
 
1.8%
37.490253 13
 
1.7%
37.50406 12
 
1.6%
37.50055 11
 
1.4%
37.47704 11
 
1.4%
37.49283 10
 
1.3%
37.4847 9
 
1.2%
37.49929 8
 
1.0%
Other values (441) 649
84.1%
ValueCountFrequency (%)
37.47603 1
 
0.1%
37.47639 3
 
0.4%
37.476784 1
 
0.1%
37.476955 1
 
0.1%
37.476994 1
 
0.1%
37.47704 11
1.4%
37.477238 2
 
0.3%
37.477314 1
 
0.1%
37.477467 1
 
0.1%
37.47756 1
 
0.1%
ValueCountFrequency (%)
37.515198 1
 
0.1%
37.515167 1
 
0.1%
37.515133 1
 
0.1%
37.515095 1
 
0.1%
37.515057 8
1.0%
37.51502 1
 
0.1%
37.514988 1
 
0.1%
37.514965 1
 
0.1%
37.514946 1
 
0.1%
37.514935 1
 
0.1%

Y좌표
Real number (ℝ)

Distinct457
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94495
Minimum126.6479
Maximum126.98341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-18T13:45:37.059861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6479
5-th percentile126.91676
Q1126.92893
median126.94252
Q3126.96132
95-th percentile126.97986
Maximum126.98341
Range0.33551
Interquartile range (IQR)0.03239125

Descriptive statistics

Standard deviation0.023257282
Coefficient of variation (CV)0.00018320761
Kurtosis32.972061
Mean126.94495
Median Absolute Deviation (MAD)0.017045
Skewness-2.5903478
Sum98001.503
Variance0.00054090116
MonotonicityNot monotonic
2024-05-18T13:45:37.632558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.91971 18
 
2.3%
126.915 17
 
2.2%
126.91688 14
 
1.8%
126.941124 14
 
1.8%
126.933266 12
 
1.6%
126.92893 11
 
1.4%
126.97986 11
 
1.4%
126.91695 10
 
1.3%
126.96961 9
 
1.2%
126.94501 7
 
0.9%
Other values (447) 649
84.1%
ValueCountFrequency (%)
126.6479 1
0.1%
126.90356 1
0.1%
126.90445 1
0.1%
126.905304 1
0.1%
126.90777 1
0.1%
126.907845 1
0.1%
126.90859 2
0.3%
126.90878 1
0.1%
126.90973 1
0.1%
126.91008 1
0.1%
ValueCountFrequency (%)
126.98341 1
0.1%
126.982735 1
0.1%
126.98262 1
0.1%
126.98222 1
0.1%
126.982086 1
0.1%
126.98195 1
0.1%
126.98189 1
0.1%
126.98181 1
0.1%
126.98174 1
0.1%
126.98173 1
0.1%

작업일자
Date

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2024-05-18 11:12:52
Maximum2024-05-18 11:13:06
2024-05-18T13:45:38.081715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:38.400788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-18T13:45:16.071039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:13.838439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:14.871771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:16.467249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:14.149423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:15.179900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:16.883312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:14.553337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:45:15.523067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:45:38.686009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
설치위치(층)1.0000.8101.000NaN0.8340.4340.758NaN0.6330.0001.000
설치유형0.8101.0000.9490.8850.8480.8550.9671.0000.7360.5980.864
설치기관1.0000.9491.0000.7040.8200.9420.521NaN0.5300.1620.948
서비스구분NaN0.8850.7041.0000.4480.4860.6160.7820.3360.2710.848
망종류0.8340.8480.8200.4481.0000.9320.349NaN0.6140.4340.955
설치년도0.4340.8550.9420.4860.9321.0000.470NaN0.5100.2470.896
실내외구분0.7580.9670.5210.6160.3490.4701.0000.7820.2130.3660.744
wifi접속환경NaN1.000NaN0.782NaNNaN0.7821.0001.0000.000NaN
X좌표0.6330.7360.5300.3360.6140.5100.2131.0001.0000.5590.478
Y좌표0.0000.5980.1620.2710.4340.2470.3660.0000.5591.0000.585
작업일자1.0000.8640.9480.8480.9550.8960.744NaN0.4780.5851.000
2024-05-18T13:45:39.052074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형wifi접속환경실내외구분망종류서비스구분설치기관
설치위치(층)1.0000.537NaN0.7100.6961.0000.953
설치유형0.5371.0000.8940.9500.6350.7060.822
wifi접속환경NaN0.8941.0000.5541.0000.5541.000
실내외구분0.7100.9500.5541.0000.4250.4260.631
망종류0.6960.6351.0000.4251.0000.3800.786
서비스구분1.0000.7060.5540.4260.3801.0000.640
설치기관0.9530.8221.0000.6310.7860.6401.000
2024-05-18T13:45:39.376277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.0000.1220.1000.3960.6140.6620.4150.6420.5831.000
X좌표0.1221.000-0.1640.3560.3810.2460.2060.2990.1630.447
Y좌표0.100-0.1641.0000.0000.3680.1320.1090.3670.2440.000
설치위치(층)0.3960.3560.0001.0000.5370.9531.0000.6960.7100.000
설치유형0.6140.3810.3680.5371.0000.8220.7060.6350.9500.894
설치기관0.6620.2460.1320.9530.8221.0000.6400.7860.6311.000
서비스구분0.4150.2060.1091.0000.7060.6401.0000.3800.4260.554
망종류0.6420.2990.3670.6960.6350.7860.3801.0000.4251.000
실내외구분0.5830.1630.2440.7100.9500.6310.4260.4251.0000.554
wifi접속환경1.0000.4470.0000.0000.8941.0000.5541.0000.5541.000

Missing values

2024-05-18T13:45:17.502577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:45:18.311078image/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.
2024-05-18T13:45:18.934004image/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

관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
0ARI00133동작구남부수도사업소여의대방로10길 97본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
1ARI00134동작구남부수도사업소여의대방로10길 97본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
2ARI00135동작구남부수도사업소여의대방로10길 97본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
3ARI00136동작구남부수도사업소여의대방로10길 97본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
4ARI00137동작구남부수도사업소여의대방로10길 97본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
5ARI00138동작구남부수도사업소여의대방로10길 97본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
6ARI00139동작구남부수도사업소여의대방로10길 97본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
7ARI00140동작구남부수도사업소여의대방로10길 97본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
8ARI00141동작구남부수도사업소여의대방로10길 97본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
9ARI00142동작구남부수도사업소여의대방로10길 97본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.492393126.9152024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
762서울5차-1066동작구경문고등학교인근거리서울특별시 동작구 동작대로 35가길 9(CCTV) 방범306-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.49065126.981212024-05-18 11:13:06.0
763서울5차-1067동작구경문고등학교인근거리서울특별시 동작구 동작대로 33길 29(CCTV) 방범108-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.48991126.9808042024-05-18 11:13:06.0
764서울5차-1068동작구경문고등학교인근거리서울특별시 동작구 동작대로 33길 7(CCTV) 방범360-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.48949126.981742024-05-18 11:13:06.0
765서울5차-1069동작구신상도초등학교인근거리서울특별시 동작구 양녕로 203(CCTV) 어린이045-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.499218126.9439852024-05-18 11:13:06.0
766서울5차-1070동작구신상도초등학교인근거리서울특별시 동작구 장승배기로 13(CCTV) 어린이82-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.49976126.942922024-05-18 11:13:06.0
767서울5차-1071동작구상도역서울특별시 동작구 상도로 259(CCTV) 주정차038-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.50391126.9471362024-05-18 11:13:06.0
768서울5차-1072동작구신남성초등학교인근거리서울특별시 동작구 사당로2길 64(CCTV) 방범081-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.487785126.964712024-05-18 11:13:06.0
769서울5차-1073동작구신남성초등학교인근거리서울특별시 동작구 사당로 146(CCTV) 어린이안전084-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.488415126.96612024-05-18 11:13:06.0
770서울5차-1074동작구신남성초등학교인근거리서울특별시 동작구 사당로 6길 5(CCTV) 방범082-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.486637126.96762024-05-18 11:13:06.0
771서울5차-1075동작구사당3동주민센터인근거리서울특별시 동작구 사당로 17길 31(CCTV) 방범078-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.484512126.9736252024-05-18 11:13:06.0