Overview

Dataset statistics

Number of variables16
Number of observations1134
Missing cells41
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory145.2 KiB
Average record size in memory131.1 B

Variable types

Text4
Categorical9
Numeric3

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-20913/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치년도 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 7 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 6 other fieldsHigh correlation
X좌표 is highly overall correlated with Y좌표 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표High correlation
설치위치(층) is highly imbalanced (93.7%)Imbalance
wifi접속환경 is highly imbalanced (91.8%)Imbalance
도로명주소 has 38 (3.4%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 04:54:15.928430
Analysis finished2024-05-18 04:54:23.738626
Duration7.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1134
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-18T13:54:24.355114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.0943563
Min length7

Characters and Unicode

Total characters9179
Distinct characters26
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

Unique1134 ?
Unique (%)100.0%

Sample

1st rowARI00170
2nd rowARI00171
3rd rowARI00172
4th rowARI00173
5th rowARI00174
ValueCountFrequency (%)
ari00170 1
 
0.1%
서울-3059 1
 
0.1%
서울-3065 1
 
0.1%
서울-3064 1
 
0.1%
서울-3063 1
 
0.1%
서울-3062 1
 
0.1%
서울-3072 1
 
0.1%
서울-3060 1
 
0.1%
서울-3058 1
 
0.1%
서울-3067 1
 
0.1%
Other values (1124) 1124
99.1%
2024-05-18T13:54:25.944961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1486
16.2%
1 1087
11.8%
2 721
 
7.9%
- 687
 
7.5%
3 584
 
6.4%
울 579
 
6.3%
서 579
 
6.3%
4 470
 
5.1%
5 402
 
4.4%
6 339
 
3.7%
Other values (16) 2245
24.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5949
64.8%
Other Letter 1374
 
15.0%
Uppercase Letter 1169
 
12.7%
Dash Punctuation 687
 
7.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 276
23.6%
D 274
23.4%
W 176
15.1%
F 173
14.8%
S 118
10.1%
B 80
 
6.8%
R 21
 
1.8%
I 21
 
1.8%
A 21
 
1.8%
H 4
 
0.3%
Other values (2) 5
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 1486
25.0%
1 1087
18.3%
2 721
12.1%
3 584
 
9.8%
4 470
 
7.9%
5 402
 
6.8%
6 339
 
5.7%
9 306
 
5.1%
8 285
 
4.8%
7 269
 
4.5%
Other Letter
ValueCountFrequency (%)
울 579
42.1%
서 579
42.1%
차 216
 
15.7%
Dash Punctuation
ValueCountFrequency (%)
- 687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6636
72.3%
Hangul 1374
 
15.0%
Latin 1169
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 276
23.6%
D 274
23.4%
W 176
15.1%
F 173
14.8%
S 118
10.1%
B 80
 
6.8%
R 21
 
1.8%
I 21
 
1.8%
A 21
 
1.8%
H 4
 
0.3%
Other values (2) 5
 
0.4%
Common
ValueCountFrequency (%)
0 1486
22.4%
1 1087
16.4%
2 721
10.9%
- 687
10.4%
3 584
 
8.8%
4 470
 
7.1%
5 402
 
6.1%
6 339
 
5.1%
9 306
 
4.6%
8 285
 
4.3%
Hangul
ValueCountFrequency (%)
울 579
42.1%
서 579
42.1%
차 216
 
15.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7805
85.0%
Hangul 1374
 
15.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1486
19.0%
1 1087
13.9%
2 721
9.2%
- 687
8.8%
3 584
 
7.5%
4 470
 
6.0%
5 402
 
5.2%
6 339
 
4.3%
9 306
 
3.9%
8 285
 
3.7%
Other values (13) 1438
18.4%
Hangul
ValueCountFrequency (%)
울 579
42.1%
서 579
42.1%
차 216
 
15.7%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
강동구
1134 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강동구 1134
100.0%

Length

2024-05-18T13:54:26.537106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:26.993679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강동구 1134
100.0%

와이파이명
Text

Distinct204
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-18T13:54:27.403977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length8.308642
Min length3

Characters and Unicode

Total characters9422
Distinct characters272
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

Unique74 ?
Unique (%)6.5%

Sample

1st row강동수도사업소
2nd row강동수도사업소
3rd row강동수도사업소
4th row강동수도사업소
5th row강동수도사업소
ValueCountFrequency (%)
강동구청(본청 53
 
4.5%
양재대로일대 53
 
4.5%
강동역및길동상권 38
 
3.2%
동남로명소화거리 35
 
3.0%
천호로데오거리 27
 
2.3%
구천면로 27
 
2.3%
광나루한강공원 26
 
2.2%
강동구청(제2청사 25
 
2.1%
암사종합전통시장 25
 
2.1%
강동구청 25
 
2.1%
Other values (203) 850
71.8%
2024-05-18T13:54:28.443318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 725
 
7.7%
강 497
 
5.3%
구 266
 
2.8%
청 250
 
2.7%
터 224
 
2.4%
소 221
 
2.3%
센 202
 
2.1%
사 192
 
2.0%
지 190
 
2.0%
로 178
 
1.9%
Other values (262) 6477
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8879
94.2%
Decimal Number 167
 
1.8%
Open Punctuation 101
 
1.1%
Close Punctuation 101
 
1.1%
Connector Punctuation 80
 
0.8%
Space Separator 50
 
0.5%
Other Punctuation 26
 
0.3%
Uppercase Letter 12
 
0.1%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 725
 
8.2%
강 497
 
5.6%
구 266
 
3.0%
청 250
 
2.8%
터 224
 
2.5%
소 221
 
2.5%
센 202
 
2.3%
사 192
 
2.2%
지 190
 
2.1%
로 178
 
2.0%
Other values (235) 5934
66.8%
Decimal Number
ValueCountFrequency (%)
2 60
35.9%
1 33
19.8%
3 22
 
13.2%
0 18
 
10.8%
5 17
 
10.2%
6 6
 
3.6%
9 4
 
2.4%
8 4
 
2.4%
7 2
 
1.2%
4 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 4
33.3%
G 2
16.7%
S 2
16.7%
T 2
16.7%
V 2
16.7%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
m 1
16.7%
i 1
16.7%
o 1
16.7%
t 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 24
92.3%
& 1
 
3.8%
; 1
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 80
100.0%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8879
94.2%
Common 525
 
5.6%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 725
 
8.2%
강 497
 
5.6%
구 266
 
3.0%
청 250
 
2.8%
터 224
 
2.5%
소 221
 
2.5%
센 202
 
2.3%
사 192
 
2.2%
지 190
 
2.1%
로 178
 
2.0%
Other values (235) 5934
66.8%
Common
ValueCountFrequency (%)
( 101
19.2%
) 101
19.2%
_ 80
15.2%
2 60
11.4%
50
9.5%
1 33
 
6.3%
. 24
 
4.6%
3 22
 
4.2%
0 18
 
3.4%
5 17
 
3.2%
Other values (7) 19
 
3.6%
Latin
ValueCountFrequency (%)
C 4
22.2%
d 2
11.1%
G 2
11.1%
S 2
11.1%
T 2
11.1%
V 2
11.1%
m 1
 
5.6%
i 1
 
5.6%
o 1
 
5.6%
t 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8879
94.2%
ASCII 543
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 725
 
8.2%
강 497
 
5.6%
구 266
 
3.0%
청 250
 
2.8%
터 224
 
2.5%
소 221
 
2.5%
센 202
 
2.3%
사 192
 
2.2%
지 190
 
2.1%
로 178
 
2.0%
Other values (235) 5934
66.8%
ASCII
ValueCountFrequency (%)
( 101
18.6%
) 101
18.6%
_ 80
14.7%
2 60
11.0%
50
9.2%
1 33
 
6.1%
. 24
 
4.4%
3 22
 
4.1%
0 18
 
3.3%
5 17
 
3.1%
Other values (17) 37
 
6.8%

도로명주소
Text

MISSING 

Distinct430
Distinct (%)39.2%
Missing38
Missing (%)3.4%
Memory size9.0 KiB
2024-05-18T13:54:29.173440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length15.254562
Min length5

Characters and Unicode

Total characters16719
Distinct characters165
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

Unique204 ?
Unique (%)18.6%

Sample

1st row성내로 51
2nd row성내로 51
3rd row성내로 51
4th row성내로 51
5th row성내로 51
ValueCountFrequency (%)
강동구 658
 
18.0%
서울특별시 553
 
15.1%
성내로 168
 
4.6%
25 92
 
2.5%
올림픽로 68
 
1.9%
구천면로 56
 
1.5%
성안로 52
 
1.4%
길동 42
 
1.1%
천호대로 41
 
1.1%
성내동 40
 
1.1%
Other values (537) 1888
51.6%
2024-05-18T13:54:30.826338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2563
 
15.3%
동 1032
 
6.2%
로 857
 
5.1%
구 759
 
4.5%
강 698
 
4.2%
1 657
 
3.9%
2 607
 
3.6%
서 590
 
3.5%
시 588
 
3.5%
울 584
 
3.5%
Other values (155) 7784
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9646
57.7%
Decimal Number 4036
24.1%
Space Separator 2563
 
15.3%
Dash Punctuation 297
 
1.8%
Open Punctuation 61
 
0.4%
Close Punctuation 61
 
0.4%
Other Punctuation 33
 
0.2%
Uppercase Letter 15
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1032
 
10.7%
로 857
 
8.9%
구 759
 
7.9%
강 698
 
7.2%
서 590
 
6.1%
시 588
 
6.1%
울 584
 
6.1%
별 556
 
5.8%
특 553
 
5.7%
길 412
 
4.3%
Other values (129) 3017
31.3%
Decimal Number
ValueCountFrequency (%)
1 657
16.3%
2 607
15.0%
5 569
14.1%
3 453
11.2%
4 365
9.0%
6 330
8.2%
7 296
7.3%
9 281
7.0%
8 267
6.6%
0 211
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
C 4
26.7%
S 2
13.3%
T 2
13.3%
V 2
13.3%
B 1
 
6.7%
J 1
 
6.7%
Y 1
 
6.7%
P 1
 
6.7%
F 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 28
84.8%
. 5
 
15.2%
Space Separator
ValueCountFrequency (%)
2563
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9646
57.7%
Common 7058
42.2%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1032
 
10.7%
로 857
 
8.9%
구 759
 
7.9%
강 698
 
7.2%
서 590
 
6.1%
시 588
 
6.1%
울 584
 
6.1%
별 556
 
5.8%
특 553
 
5.7%
길 412
 
4.3%
Other values (129) 3017
31.3%
Common
ValueCountFrequency (%)
2563
36.3%
1 657
 
9.3%
2 607
 
8.6%
5 569
 
8.1%
3 453
 
6.4%
4 365
 
5.2%
6 330
 
4.7%
- 297
 
4.2%
7 296
 
4.2%
9 281
 
4.0%
Other values (7) 640
 
9.1%
Latin
ValueCountFrequency (%)
C 4
26.7%
S 2
13.3%
T 2
13.3%
V 2
13.3%
B 1
 
6.7%
J 1
 
6.7%
Y 1
 
6.7%
P 1
 
6.7%
F 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9646
57.7%
ASCII 7073
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2563
36.2%
1 657
 
9.3%
2 607
 
8.6%
5 569
 
8.0%
3 453
 
6.4%
4 365
 
5.2%
6 330
 
4.7%
- 297
 
4.2%
7 296
 
4.2%
9 281
 
4.0%
Other values (16) 655
 
9.3%
Hangul
ValueCountFrequency (%)
동 1032
 
10.7%
로 857
 
8.9%
구 759
 
7.9%
강 698
 
7.2%
서 590
 
6.1%
시 588
 
6.1%
울 584
 
6.1%
별 556
 
5.8%
특 553
 
5.7%
길 412
 
4.3%
Other values (129) 3017
31.3%

상세주소
Text

Distinct817
Distinct (%)72.2%
Missing3
Missing (%)0.3%
Memory size9.0 KiB
2024-05-18T13:54:31.748697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length10.783378
Min length2

Characters and Unicode

Total characters12196
Distinct characters407
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique703 ?
Unique (%)62.2%

Sample

1st row본관 B1F
2nd row본관 B1F
3rd row본관 1F
4th row본관 1F
5th row본관 1F
ValueCountFrequency (%)
cctv 66
 
2.9%
앞 58
 
2.5%
1층 56
 
2.4%
양재대로 53
 
2.3%
일대 53
 
2.3%
3층 50
 
2.2%
2층 48
 
2.1%
옥내1 46
 
2.0%
복도 35
 
1.5%
동남로명소화거리 35
 
1.5%
Other values (686) 1806
78.3%
2024-05-18T13:54:33.031972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1176
 
9.6%
1 561
 
4.6%
) 458
 
3.8%
( 457
 
3.7%
2 421
 
3.5%
옥 383
 
3.1%
_ 289
 
2.4%
3 286
 
2.3%
동 282
 
2.3%
외 277
 
2.3%
Other values (397) 7606
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6855
56.2%
Decimal Number 2057
 
16.9%
Space Separator 1176
 
9.6%
Uppercase Letter 547
 
4.5%
Close Punctuation 458
 
3.8%
Open Punctuation 457
 
3.7%
Connector Punctuation 289
 
2.4%
Dash Punctuation 232
 
1.9%
Other Punctuation 54
 
0.4%
Math Symbol 35
 
0.3%
Other values (3) 36
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 383
 
5.6%
동 282
 
4.1%
외 277
 
4.0%
층 275
 
4.0%
로 194
 
2.8%
내 191
 
2.8%
리 146
 
2.1%
지 145
 
2.1%
강 144
 
2.1%
대 143
 
2.1%
Other values (345) 4675
68.2%
Uppercase Letter
ValueCountFrequency (%)
C 182
33.3%
F 112
20.5%
T 89
16.3%
V 88
16.1%
B 17
 
3.1%
P 15
 
2.7%
A 12
 
2.2%
E 8
 
1.5%
O 4
 
0.7%
U 4
 
0.7%
Other values (9) 16
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
c 10
31.2%
t 6
18.8%
v 5
15.6%
e 3
 
9.4%
l 2
 
6.2%
b 1
 
3.1%
o 1
 
3.1%
r 1
 
3.1%
n 1
 
3.1%
s 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
1 561
27.3%
2 421
20.5%
3 286
13.9%
5 196
 
9.5%
4 166
 
8.1%
0 162
 
7.9%
6 92
 
4.5%
7 69
 
3.4%
8 63
 
3.1%
9 41
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 30
55.6%
. 21
38.9%
: 2
 
3.7%
? 1
 
1.9%
Space Separator
ValueCountFrequency (%)
1176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 458
100.0%
Open Punctuation
ValueCountFrequency (%)
( 457
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 232
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6853
56.2%
Common 4762
39.0%
Latin 579
 
4.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 383
 
5.6%
동 282
 
4.1%
외 277
 
4.0%
층 275
 
4.0%
로 194
 
2.8%
내 191
 
2.8%
리 146
 
2.1%
지 145
 
2.1%
강 144
 
2.1%
대 143
 
2.1%
Other values (343) 4673
68.2%
Latin
ValueCountFrequency (%)
C 182
31.4%
F 112
19.3%
T 89
15.4%
V 88
15.2%
B 17
 
2.9%
P 15
 
2.6%
A 12
 
2.1%
c 10
 
1.7%
E 8
 
1.4%
t 6
 
1.0%
Other values (20) 40
 
6.9%
Common
ValueCountFrequency (%)
1176
24.7%
1 561
11.8%
) 458
 
9.6%
( 457
 
9.6%
2 421
 
8.8%
_ 289
 
6.1%
3 286
 
6.0%
- 232
 
4.9%
5 196
 
4.1%
4 166
 
3.5%
Other values (12) 520
10.9%
Han
ValueCountFrequency (%)
舊 1
50.0%
光 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6853
56.2%
ASCII 5340
43.8%
CJK 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1176
22.0%
1 561
10.5%
) 458
 
8.6%
( 457
 
8.6%
2 421
 
7.9%
_ 289
 
5.4%
3 286
 
5.4%
- 232
 
4.3%
5 196
 
3.7%
C 182
 
3.4%
Other values (41) 1082
20.3%
Hangul
ValueCountFrequency (%)
옥 383
 
5.6%
동 282
 
4.1%
외 277
 
4.0%
층 275
 
4.0%
로 194
 
2.8%
내 191
 
2.8%
리 146
 
2.1%
지 145
 
2.1%
강 144
 
2.1%
대 143
 
2.1%
Other values (343) 4673
68.2%
CJK
ValueCountFrequency (%)
舊 1
50.0%
光 1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1114 
-
 
8
1층
 
5
2층
 
4
3층
 
2

Length

Max length4
Median length4
Mean length3.957672
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1114
98.2%
- 8
 
0.7%
1층 5
 
0.4%
2층 4
 
0.4%
3층 2
 
0.2%
4층 1
 
0.1%

Length

2024-05-18T13:54:33.481270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:33.963362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1114
98.2%
8
 
0.7%
1층 5
 
0.4%
2층 4
 
0.4%
3층 2
 
0.2%
4층 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
1. 주요거리
305 
7-2-1. 공공 - 구청사 및 별관
93 
6-4. 복지 - 아동청소년
92 
3. 공원(하천)
84 
7-2-3. 공공 - 동주민센터
75 
Other values (15)
485 

Length

Max length21
Median length17
Mean length11.816578
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 305
26.9%
7-2-1. 공공 - 구청사 및 별관 93
 
8.2%
6-4. 복지 - 아동청소년 92
 
8.1%
3. 공원(하천) 84
 
7.4%
7-2-3. 공공 - 동주민센터 75
 
6.6%
2. 전통시장 72
 
6.3%
4. 문화관광 56
 
4.9%
6-3. 복지 - 장애인 50
 
4.4%
6-2. 복지 - 노인 48
 
4.2%
7-2-2. 공공 - 구의회 및 보건소 45
 
4.0%
Other values (10) 214
18.9%

Length

2024-05-18T13:54:34.391752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
532
 
14.7%
1 305
 
8.5%
주요거리 305
 
8.5%
공공 290
 
8.0%
복지 242
 
6.7%
및 138
 
3.8%
7-2-1 93
 
2.6%
구청사 93
 
2.6%
별관 93
 
2.6%
아동청소년 92
 
2.5%
Other values (35) 1425
39.5%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
디지털뉴딜(KT)
335 
자치구
274 
디지털뉴딜(LG U+)
244 
서울시(AP)
199 
버스정류소(국비)
42 
Other values (2)
40 

Length

Max length12
Median length9
Mean length7.8430335
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(KT) 335
29.5%
자치구 274
24.2%
디지털뉴딜(LG U+) 244
21.5%
서울시(AP) 199
17.5%
버스정류소(국비) 42
 
3.7%
버스정류소(시비) 38
 
3.4%
서울시(LTE) 2
 
0.2%

Length

2024-05-18T13:54:34.831101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:35.221968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
디지털뉴딜(kt 335
24.3%
자치구 274
19.9%
디지털뉴딜(lg 244
17.7%
u 244
17.7%
서울시(ap 199
14.4%
버스정류소(국비 42
 
3.0%
버스정류소(시비 38
 
2.8%
서울시(lte 2
 
0.1%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
공공WiFi
709 
과기부WiFi(핫플레이스)
275 
과기부WiFi(복지시설)
88 
과기부WiFi
 
42
<NA>
 
20

Length

Max length14
Median length6
Mean length8.4850088
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 709
62.5%
과기부WiFi(핫플레이스) 275
 
24.3%
과기부WiFi(복지시설) 88
 
7.8%
과기부WiFi 42
 
3.7%
<NA> 20
 
1.8%

Length

2024-05-18T13:54:35.790387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:36.260192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 709
62.5%
과기부wifi(핫플레이스 275
 
24.3%
과기부wifi(복지시설 88
 
7.8%
과기부wifi 42
 
3.7%
na 20
 
1.8%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
인터넷망_뉴딜용
579 
자가망_U무선망
329 
임대망
167 
<NA>
 
38
자가망_수도사업소망
 
21

Length

Max length10
Median length8
Mean length7.1666667
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 579
51.1%
자가망_U무선망 329
29.0%
임대망 167
 
14.7%
<NA> 38
 
3.4%
자가망_수도사업소망 21
 
1.9%

Length

2024-05-18T13:54:36.805966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:37.249990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 579
51.1%
자가망_u무선망 329
29.0%
임대망 167
 
14.7%
na 38
 
3.4%
자가망_수도사업소망 21
 
1.9%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.821
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-18T13:54:37.777211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12020
median2022
Q32022
95-th percentile2022
Maximum2023
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7078451
Coefficient of variation (CV)0.00084512437
Kurtosis0.19627768
Mean2020.821
Median Absolute Deviation (MAD)0
Skewness-1.2172344
Sum2291611
Variance2.9167348
MonotonicityNot monotonic
2024-05-18T13:54:38.223998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2022 610
53.8%
2020 148
 
13.1%
2021 145
 
12.8%
2017 122
 
10.8%
2019 50
 
4.4%
2018 39
 
3.4%
2023 20
 
1.8%
ValueCountFrequency (%)
2017 122
 
10.8%
2018 39
 
3.4%
2019 50
 
4.4%
2020 148
 
13.1%
2021 145
 
12.8%
2022 610
53.8%
2023 20
 
1.8%
ValueCountFrequency (%)
2023 20
 
1.8%
2022 610
53.8%
2021 145
 
12.8%
2020 148
 
13.1%
2019 50
 
4.4%
2018 39
 
3.4%
2017 122
 
10.8%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
실외
579 
실내
555 

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 579
51.1%
실내 555
48.9%

Length

2024-05-18T13:54:38.933993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:39.715854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 579
51.1%
실내 555
48.9%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
<NA>
1109 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
23
H123
 
1
H124
 
1

Length

Max length27
Median length4
Mean length4.4664903
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1109
97.8%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 23
 
2.0%
H123 1
 
0.1%
H124 1
 
0.1%

Length

2024-05-18T13:54:40.185071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:54:40.482131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1109
90.5%
보안접속 23
 
1.9%
임시적용(머큐리 23
 
1.9%
proxy 23
 
1.9%
서버 23
 
1.9%
개발중 23
 
1.9%
h123 1
 
0.1%
h124 1
 
0.1%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct541
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.541661
Minimum37.521755
Maximum37.56762
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-18T13:54:41.085707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.521755
5-th percentile37.527564
Q137.530617
median37.539135
Q337.550764
95-th percentile37.561022
Maximum37.56762
Range0.045865
Interquartile range (IQR)0.0201475

Descriptive statistics

Standard deviation0.011246112
Coefficient of variation (CV)0.00029956351
Kurtosis-0.94545787
Mean37.541661
Median Absolute Deviation (MAD)0.009178
Skewness0.39137438
Sum42572.243
Variance0.00012647503
MonotonicityNot monotonic
2024-05-18T13:54:41.688990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.530144 44
 
3.9%
37.52989 25
 
2.2%
37.528637 23
 
2.0%
37.529243 22
 
1.9%
37.529 21
 
1.9%
37.55237 20
 
1.8%
37.532207 19
 
1.7%
37.538986 17
 
1.5%
37.54818 16
 
1.4%
37.53162 12
 
1.1%
Other values (531) 915
80.7%
ValueCountFrequency (%)
37.521755 2
0.2%
37.522465 1
0.1%
37.523075 1
0.1%
37.52343 1
0.1%
37.52357 2
0.2%
37.523643 1
0.1%
37.52365 1
0.1%
37.52381 2
0.2%
37.52403 1
0.1%
37.52441 1
0.1%
ValueCountFrequency (%)
37.56762 4
0.4%
37.56669 1
 
0.1%
37.56648 9
0.8%
37.56647 8
0.7%
37.56625 8
0.7%
37.566013 1
 
0.1%
37.565884 1
 
0.1%
37.56504 5
0.4%
37.564693 1
 
0.1%
37.56405 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct529
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.13838
Minimum127.1055
Maximum127.1799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2024-05-18T13:54:42.128905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.1055
5-th percentile127.12292
Q1127.12622
median127.13285
Q3127.14621
95-th percentile127.17245
Maximum127.1799
Range0.0744
Interquartile range (IQR)0.01999875

Descriptive statistics

Standard deviation0.015268447
Coefficient of variation (CV)0.00012009314
Kurtosis-0.024305317
Mean127.13838
Median Absolute Deviation (MAD)0.008547
Skewness0.96808715
Sum144174.92
Variance0.00023312548
MonotonicityNot monotonic
2024-05-18T13:54:42.738236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.12375 42
 
3.7%
127.124306 25
 
2.2%
127.12635 23
 
2.0%
127.1256 22
 
1.9%
127.12603 21
 
1.9%
127.15422 20
 
1.8%
127.12935 19
 
1.7%
127.12445 17
 
1.5%
127.12712 16
 
1.4%
127.12883 12
 
1.1%
Other values (519) 917
80.9%
ValueCountFrequency (%)
127.1055 2
0.2%
127.105545 1
0.1%
127.108116 1
0.1%
127.11715 1
0.1%
127.118614 2
0.2%
127.11912 2
0.2%
127.11939 1
0.1%
127.11952 1
0.1%
127.11953 1
0.1%
127.11955 1
0.1%
ValueCountFrequency (%)
127.1799 1
0.1%
127.17972 1
0.1%
127.17923 1
0.1%
127.17834 1
0.1%
127.17772 1
0.1%
127.17623 1
0.1%
127.17605 1
0.1%
127.17604 1
0.1%
127.17596 1
0.1%
127.17543 1
0.1%

작업일자
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-05-18 11:13:02.0
275 
2024-05-18 11:12:54.0
274 
2024-05-18 11:13:05.0
138 
2024-05-18 11:13:00.0
117 
2024-05-18 11:13:04.0
86 
Other values (10)
244 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-18 11:12:52.0
2nd row2024-05-18 11:12:52.0
3rd row2024-05-18 11:12:52.0
4th row2024-05-18 11:12:52.0
5th row2024-05-18 11:12:52.0

Common Values

ValueCountFrequency (%)
2024-05-18 11:13:02.0 275
24.3%
2024-05-18 11:12:54.0 274
24.2%
2024-05-18 11:13:05.0 138
12.2%
2024-05-18 11:13:00.0 117
10.3%
2024-05-18 11:13:04.0 86
 
7.6%
2024-05-18 11:13:03.0 60
 
5.3%
2024-05-18 11:12:52.0 59
 
5.2%
2024-05-18 11:12:59.0 53
 
4.7%
2024-05-18 11:12:57.0 21
 
1.9%
2024-05-18 11:13:06.0 20
 
1.8%
Other values (5) 31
 
2.7%

Length

2024-05-18T13:54:43.166788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-18 1134
50.0%
11:13:02.0 275
 
12.1%
11:12:54.0 274
 
12.1%
11:13:05.0 138
 
6.1%
11:13:00.0 117
 
5.2%
11:13:04.0 86
 
3.8%
11:13:03.0 60
 
2.6%
11:12:52.0 59
 
2.6%
11:12:59.0 53
 
2.3%
11:12:57.0 21
 
0.9%
Other values (6) 51
 
2.2%

Interactions

2024-05-18T13:54:20.506475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:18.387026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:19.528427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:20.864958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:18.727500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:19.873648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:21.146545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:19.166490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:54:20.159556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:54:43.424790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
설치위치(층)1.0000.544NaNNaNNaNNaN1.000NaN0.0000.691NaN
설치유형0.5441.0000.9420.9640.9340.8670.9980.6360.7930.7750.910
설치기관NaN0.9421.0000.8690.8320.7460.5571.0000.4250.4730.990
서비스구분NaN0.9640.8691.0000.8230.5090.8451.0000.4060.3840.899
망종류NaN0.9340.8320.8231.0000.7990.5791.0000.4870.4290.907
설치년도NaN0.8670.7460.5090.7991.0000.7261.0000.3810.3890.946
실내외구분1.0000.9980.5570.8450.5790.7261.0001.0000.5070.2670.651
wifi접속환경NaN0.6361.0001.0001.0001.0001.0001.0000.6770.0000.930
X좌표0.0000.7930.4250.4060.4870.3810.5070.6771.0000.8200.566
Y좌표0.6910.7750.4730.3840.4290.3890.2670.0000.8201.0000.610
작업일자NaN0.9100.9900.8990.9070.9460.6510.9300.5660.6101.000
2024-05-18T13:54:43.847744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형wifi접속환경작업일자실내외구분망종류서비스구분설치기관
설치위치(층)1.0000.446NaN1.0000.9131.000NaN1.000
설치유형0.4461.0000.6400.5700.9530.8080.7690.773
wifi접속환경NaN0.6401.0000.6740.9780.9780.9780.978
작업일자1.0000.5700.6741.0000.5990.7680.7530.958
실내외구분0.9130.9530.9780.5991.0000.3980.6420.598
망종류1.0000.8080.9780.7680.3981.0000.4680.689
서비스구분NaN0.7690.9780.7530.6420.4681.0000.804
설치기관1.0000.7730.9780.9580.5980.6890.8041.000
2024-05-18T13:54:44.217719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.0000.2440.2081.0000.6820.5660.4560.6990.5980.9780.764
X좌표0.2441.0000.5660.0000.3780.2310.2530.3120.3890.5220.248
Y좌표0.2080.5661.0000.3040.3600.2620.2380.2690.2040.0000.276
설치위치(층)1.0000.0000.3041.0000.4461.0000.0001.0000.9130.0001.000
설치유형0.6820.3780.3600.4461.0000.7730.7690.8080.9530.6400.570
설치기관0.5660.2310.2621.0000.7731.0000.8040.6890.5980.9780.958
서비스구분0.4560.2530.2380.0000.7690.8041.0000.4680.6420.9780.753
망종류0.6990.3120.2691.0000.8080.6890.4681.0000.3980.9780.768
실내외구분0.5980.3890.2040.9130.9530.5980.6420.3981.0000.9780.599
wifi접속환경0.9780.5220.0000.0000.6400.9780.9780.9780.9781.0000.674
작업일자0.7640.2480.2761.0000.5700.9580.7530.7680.5990.6741.000

Missing values

2024-05-18T13:54:21.956967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:54:22.809040image/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.
2024-05-18T13:54:23.406337image/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
0ARI00170강동구강동수도사업소성내로 51본관 B1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
1ARI00171강동구강동수도사업소성내로 51본관 B1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
2ARI00172강동구강동수도사업소성내로 51본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
3ARI00173강동구강동수도사업소성내로 51본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
4ARI00174강동구강동수도사업소성내로 51본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
5ARI00175강동구강동수도사업소성내로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
6ARI00176강동구강동수도사업소성내로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
7ARI00177강동구강동수도사업소성내로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
8ARI00178강동구강동수도사업소성내로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
9ARI00179강동구강동수도사업소성내로 51본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.529127.126032024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1124서울5차-0681-2강동구우성원서울특별시 강동구 고덕로 295-45201호실 앞 복도2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.55769127.158542024-05-18 11:13:06.0
1125서울5차-0682강동구우성원서울특별시 강동구 고덕로 295-45로비3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.55768127.1585542024-05-18 11:13:06.0
1126서울5차-0682-1강동구우성원서울특별시 강동구 고덕로 295-45301호실 복도3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.55768127.1585542024-05-18 11:13:06.0
1127서울5차-0682-2강동구우성원서울특별시 강동구 고덕로 295-45강당 출입구4층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.55768127.1585542024-05-18 11:13:06.0
1128서울5차-0862강동구강동구민회관서울특별시 강동구 상암로 168로비1층7-3. 공공 - 지역디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.545692127.141242024-05-18 11:13:06.0
1129서울5차-0862-1강동구강동구민회관서울특별시 강동구 상암로 168가정실1층7-3. 공공 - 지역디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.545692127.141242024-05-18 11:13:06.0
1130서울5차-0862-2강동구강동구민회관서울특별시 강동구 상암로 168학습실2층7-3. 공공 - 지역디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.545692127.141242024-05-18 11:13:06.0
1131서울5차-1103강동구강동그린웨이가족캠핑장서울특별시 강동구 천호대로 206길 87(CCTV) 31번기둥-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.536144127.153822024-05-18 11:13:06.0
1132서울5차-1106강동구강동그린웨이가족캠핑장서울특별시 강동구 천호대로 206길 87(CCTV) 34번기둥-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.53594127.153482024-05-18 11:13:06.0
1133서울5차-1109강동구강동그린웨이가족캠핑장서울특별시 강동구 천호대로 206길 87(CCTV) 38번가로수폴-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.536064127.152932024-05-18 11:13:06.0