Overview

Dataset statistics

Number of variables16
Number of observations1182
Missing cells38
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory151.3 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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-20892/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치기관 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 8 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 7 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (86.0%)Imbalance
서비스구분 is highly imbalanced (55.9%)Imbalance
wifi접속환경 is highly imbalanced (92.4%)Imbalance
도로명주소 has 14 (1.2%) missing valuesMissing
상세주소 has 24 (2.0%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-17 22:41:42.571002
Analysis finished2024-05-17 22:41:52.618593
Duration10.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1182
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-05-18T07:41:53.393059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.0516074
Min length7

Characters and Unicode

Total characters9517
Distinct characters25
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

Unique1182 ?
Unique (%)100.0%

Sample

1st rowARI00073
2nd rowARI00074
3rd rowARI00075
4th rowARI00076
5th rowARI00077
ValueCountFrequency (%)
ari00073 1
 
0.1%
wn003863 1
 
0.1%
wn003879 1
 
0.1%
wn003878 1
 
0.1%
wn003877 1
 
0.1%
wn003876 1
 
0.1%
wn003875 1
 
0.1%
wn003874 1
 
0.1%
wn003873 1
 
0.1%
wn003872 1
 
0.1%
Other values (1172) 1172
99.2%
2024-05-18T07:41:55.152348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2675
28.1%
3 691
 
7.3%
1 677
 
7.1%
2 610
 
6.4%
S 610
 
6.4%
D 544
 
5.7%
4 475
 
5.0%
9 405
 
4.3%
8 385
 
4.0%
W 317
 
3.3%
Other values (15) 2128
22.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6726
70.7%
Uppercase Letter 1917
 
20.1%
Other Letter 561
 
5.9%
Dash Punctuation 313
 
3.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 610
31.8%
D 544
28.4%
W 317
16.5%
N 225
 
11.7%
F 92
 
4.8%
B 52
 
2.7%
R 25
 
1.3%
I 25
 
1.3%
A 25
 
1.3%
G 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 2675
39.8%
3 691
 
10.3%
1 677
 
10.1%
2 610
 
9.1%
4 475
 
7.1%
9 405
 
6.0%
8 385
 
5.7%
5 305
 
4.5%
7 300
 
4.5%
6 203
 
3.0%
Other Letter
ValueCountFrequency (%)
서 243
43.3%
울 243
43.3%
차 75
 
13.4%
Dash Punctuation
ValueCountFrequency (%)
- 313
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7039
74.0%
Latin 1917
 
20.1%
Hangul 561
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2675
38.0%
3 691
 
9.8%
1 677
 
9.6%
2 610
 
8.7%
4 475
 
6.7%
9 405
 
5.8%
8 385
 
5.5%
- 313
 
4.4%
5 305
 
4.3%
7 300
 
4.3%
Latin
ValueCountFrequency (%)
S 610
31.8%
D 544
28.4%
W 317
16.5%
N 225
 
11.7%
F 92
 
4.8%
B 52
 
2.7%
R 25
 
1.3%
I 25
 
1.3%
A 25
 
1.3%
G 1
 
0.1%
Hangul
ValueCountFrequency (%)
서 243
43.3%
울 243
43.3%
차 75
 
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8956
94.1%
Hangul 561
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2675
29.9%
3 691
 
7.7%
1 677
 
7.6%
2 610
 
6.8%
S 610
 
6.8%
D 544
 
6.1%
4 475
 
5.3%
9 405
 
4.5%
8 385
 
4.3%
W 317
 
3.5%
Other values (12) 1567
17.5%
Hangul
ValueCountFrequency (%)
서 243
43.3%
울 243
43.3%
차 75
 
13.4%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
성동구
1182 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 1182
100.0%

Length

2024-05-18T07:41:55.807222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:41:56.248526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성동구 1182
100.0%

와이파이명
Text

Distinct520
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-05-18T07:41:57.167928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length8.3333333
Min length3

Characters and Unicode

Total characters9850
Distinct characters251
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

Unique426 ?
Unique (%)36.0%

Sample

1st row동부수도사업소
2nd row동부수도사업소
3rd row동부수도사업소
4th row동부수도사업소
5th row동부수도사업소
ValueCountFrequency (%)
성동구청 70
 
4.5%
거리 64
 
4.1%
및 52
 
3.3%
성수 39
 
2.5%
성수수제화카페거리 37
 
2.4%
카페 36
 
2.3%
수제화 36
 
2.3%
왕십리 29
 
1.9%
광장 29
 
1.9%
상점가 29
 
1.9%
Other values (541) 1146
73.1%
2024-05-18T07:41:59.105572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 385
 
3.9%
385
 
3.9%
동 366
 
3.7%
_ 365
 
3.7%
성 351
 
3.6%
A 312
 
3.2%
수 248
 
2.5%
0 243
 
2.5%
터 238
 
2.4%
센 225
 
2.3%
Other values (241) 6732
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6821
69.2%
Decimal Number 1123
 
11.4%
Uppercase Letter 933
 
9.5%
Space Separator 385
 
3.9%
Connector Punctuation 365
 
3.7%
Open Punctuation 88
 
0.9%
Close Punctuation 88
 
0.9%
Lowercase Letter 27
 
0.3%
Other Punctuation 12
 
0.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 366
 
5.4%
성 351
 
5.1%
수 248
 
3.6%
터 238
 
3.5%
센 225
 
3.3%
리 200
 
2.9%
가 146
 
2.1%
청 134
 
2.0%
구 131
 
1.9%
장 118
 
1.7%
Other values (202) 4664
68.4%
Lowercase Letter
ValueCountFrequency (%)
u 6
22.2%
e 4
14.8%
s 4
14.8%
k 3
11.1%
o 2
 
7.4%
m 2
 
7.4%
h 2
 
7.4%
i 1
 
3.7%
v 1
 
3.7%
n 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
P 385
41.3%
A 312
33.4%
C 175
18.8%
F 31
 
3.3%
S 11
 
1.2%
D 9
 
1.0%
G 6
 
0.6%
O 2
 
0.2%
W 1
 
0.1%
T 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 243
21.6%
1 184
16.4%
2 164
14.6%
3 104
9.3%
4 92
 
8.2%
6 76
 
6.8%
5 75
 
6.7%
8 74
 
6.6%
7 71
 
6.3%
9 40
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
# 4
33.3%
Space Separator
ValueCountFrequency (%)
385
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 365
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6821
69.2%
Common 2069
 
21.0%
Latin 960
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 366
 
5.4%
성 351
 
5.1%
수 248
 
3.6%
터 238
 
3.5%
센 225
 
3.3%
리 200
 
2.9%
가 146
 
2.1%
청 134
 
2.0%
구 131
 
1.9%
장 118
 
1.7%
Other values (202) 4664
68.4%
Latin
ValueCountFrequency (%)
P 385
40.1%
A 312
32.5%
C 175
18.2%
F 31
 
3.2%
S 11
 
1.1%
D 9
 
0.9%
u 6
 
0.6%
G 6
 
0.6%
e 4
 
0.4%
s 4
 
0.4%
Other values (11) 17
 
1.8%
Common
ValueCountFrequency (%)
385
18.6%
_ 365
17.6%
0 243
11.7%
1 184
8.9%
2 164
7.9%
3 104
 
5.0%
4 92
 
4.4%
( 88
 
4.3%
) 88
 
4.3%
6 76
 
3.7%
Other values (8) 280
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6821
69.2%
ASCII 3029
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 385
12.7%
385
12.7%
_ 365
12.1%
A 312
10.3%
0 243
 
8.0%
1 184
 
6.1%
C 175
 
5.8%
2 164
 
5.4%
3 104
 
3.4%
4 92
 
3.0%
Other values (29) 620
20.5%
Hangul
ValueCountFrequency (%)
동 366
 
5.4%
성 351
 
5.1%
수 248
 
3.6%
터 238
 
3.5%
센 225
 
3.3%
리 200
 
2.9%
가 146
 
2.1%
청 134
 
2.0%
구 131
 
1.9%
장 118
 
1.7%
Other values (202) 4664
68.4%

도로명주소
Text

MISSING 

Distinct616
Distinct (%)52.7%
Missing14
Missing (%)1.2%
Memory size9.4 KiB
2024-05-18T07:42:00.412766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length11.894692
Min length3

Characters and Unicode

Total characters13893
Distinct characters162
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

Unique451 ?
Unique (%)38.6%

Sample

1st row고산자로10길 13
2nd row고산자로10길 13
3rd row고산자로10길 13
4th row고산자로10길 13
5th row고산자로10길 13
ValueCountFrequency (%)
성동구 296
 
9.8%
서울특별시 246
 
8.1%
고산자로 98
 
3.2%
270 73
 
2.4%
청계천로 54
 
1.8%
20 42
 
1.4%
독서당로 35
 
1.2%
왕십리로 34
 
1.1%
뚝섬로 30
 
1.0%
마장로 30
 
1.0%
Other values (669) 2091
69.0%
2024-05-18T07:42:02.172081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1868
 
13.4%
1 867
 
6.2%
로 708
 
5.1%
2 707
 
5.1%
동 627
 
4.5%
길 553
 
4.0%
3 452
 
3.3%
성 437
 
3.1%
0 388
 
2.8%
7 366
 
2.6%
Other values (152) 6920
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7357
53.0%
Decimal Number 4152
29.9%
Space Separator 1868
 
13.4%
Dash Punctuation 332
 
2.4%
Open Punctuation 56
 
0.4%
Close Punctuation 56
 
0.4%
Uppercase Letter 42
 
0.3%
Lowercase Letter 20
 
0.1%
Other Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 708
 
9.6%
동 627
 
8.5%
길 553
 
7.5%
성 437
 
5.9%
서 330
 
4.5%
구 314
 
4.3%
시 281
 
3.8%
울 277
 
3.8%
별 249
 
3.4%
특 246
 
3.3%
Other values (127) 3335
45.3%
Decimal Number
ValueCountFrequency (%)
1 867
20.9%
2 707
17.0%
3 452
10.9%
0 388
9.3%
7 366
8.8%
6 354
8.5%
4 340
 
8.2%
5 303
 
7.3%
8 205
 
4.9%
9 170
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 12
28.6%
P 12
28.6%
F 6
14.3%
G 5
11.9%
H 5
11.9%
B 2
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 10
50.0%
t 5
25.0%
v 5
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
. 3
30.0%
Space Separator
ValueCountFrequency (%)
1868
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 332
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7357
53.0%
Common 6474
46.6%
Latin 62
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 708
 
9.6%
동 627
 
8.5%
길 553
 
7.5%
성 437
 
5.9%
서 330
 
4.5%
구 314
 
4.3%
시 281
 
3.8%
울 277
 
3.8%
별 249
 
3.4%
특 246
 
3.3%
Other values (127) 3335
45.3%
Common
ValueCountFrequency (%)
1868
28.9%
1 867
13.4%
2 707
 
10.9%
3 452
 
7.0%
0 388
 
6.0%
7 366
 
5.7%
6 354
 
5.5%
4 340
 
5.3%
- 332
 
5.1%
5 303
 
4.7%
Other values (6) 497
 
7.7%
Latin
ValueCountFrequency (%)
A 12
19.4%
P 12
19.4%
c 10
16.1%
F 6
9.7%
t 5
8.1%
G 5
8.1%
H 5
8.1%
v 5
8.1%
B 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7357
53.0%
ASCII 6536
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1868
28.6%
1 867
13.3%
2 707
 
10.8%
3 452
 
6.9%
0 388
 
5.9%
7 366
 
5.6%
6 354
 
5.4%
4 340
 
5.2%
- 332
 
5.1%
5 303
 
4.6%
Other values (15) 559
 
8.6%
Hangul
ValueCountFrequency (%)
로 708
 
9.6%
동 627
 
8.5%
길 553
 
7.5%
성 437
 
5.9%
서 330
 
4.5%
구 314
 
4.3%
시 281
 
3.8%
울 277
 
3.8%
별 249
 
3.4%
특 246
 
3.3%
Other values (127) 3335
45.3%

상세주소
Text

MISSING 

Distinct950
Distinct (%)82.0%
Missing24
Missing (%)2.0%
Memory size9.4 KiB
2024-05-18T07:42:03.100580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length11.530225
Min length1

Characters and Unicode

Total characters13352
Distinct characters349
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique838 ?
Unique (%)72.4%

Sample

1st row본관 B1F
2nd row본관 1F
3rd row본관 1F
4th row본관 1F
5th row본관 1F
ValueCountFrequency (%)
성수 44
 
1.6%
수제화 37
 
1.4%
카페거리 37
 
1.4%
옥내1 36
 
1.3%
2층 32
 
1.2%
복도 31
 
1.1%
1층 30
 
1.1%
ap 29
 
1.1%
왕십리광장 28
 
1.0%
및 28
 
1.0%
Other values (1045) 2382
87.8%
2024-05-18T07:42:05.177116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1581
 
11.8%
1 772
 
5.8%
2 516
 
3.9%
동 369
 
2.8%
3 344
 
2.6%
0 290
 
2.2%
성 279
 
2.1%
4 275
 
2.1%
층 253
 
1.9%
로 250
 
1.9%
Other values (339) 8423
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7375
55.2%
Decimal Number 2956
22.1%
Space Separator 1581
 
11.8%
Uppercase Letter 473
 
3.5%
Open Punctuation 250
 
1.9%
Close Punctuation 249
 
1.9%
Dash Punctuation 220
 
1.6%
Connector Punctuation 129
 
1.0%
Lowercase Letter 62
 
0.5%
Other Punctuation 50
 
0.4%
Other values (2) 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 369
 
5.0%
성 279
 
3.8%
층 253
 
3.4%
로 250
 
3.4%
수 214
 
2.9%
길 206
 
2.8%
옥 203
 
2.8%
사 187
 
2.5%
터 169
 
2.3%
장 146
 
2.0%
Other values (292) 5099
69.1%
Uppercase Letter
ValueCountFrequency (%)
P 123
26.0%
F 109
23.0%
A 90
19.0%
C 46
 
9.7%
E 25
 
5.3%
V 19
 
4.0%
B 17
 
3.6%
O 14
 
3.0%
T 10
 
2.1%
S 8
 
1.7%
Other values (4) 12
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
g 18
29.0%
n 12
19.4%
h 7
 
11.3%
u 6
 
9.7%
o 6
 
9.7%
c 5
 
8.1%
t 2
 
3.2%
v 2
 
3.2%
e 1
 
1.6%
p 1
 
1.6%
Other values (2) 2
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 772
26.1%
2 516
17.5%
3 344
11.6%
0 290
 
9.8%
4 275
 
9.3%
5 191
 
6.5%
6 177
 
6.0%
7 155
 
5.2%
8 139
 
4.7%
9 97
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 25
50.0%
/ 13
26.0%
# 7
 
14.0%
. 5
 
10.0%
Space Separator
ValueCountFrequency (%)
1581
100.0%
Open Punctuation
ValueCountFrequency (%)
( 250
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 129
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7375
55.2%
Common 5442
40.8%
Latin 535
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 369
 
5.0%
성 279
 
3.8%
층 253
 
3.4%
로 250
 
3.4%
수 214
 
2.9%
길 206
 
2.8%
옥 203
 
2.8%
사 187
 
2.5%
터 169
 
2.3%
장 146
 
2.0%
Other values (292) 5099
69.1%
Latin
ValueCountFrequency (%)
P 123
23.0%
F 109
20.4%
A 90
16.8%
C 46
 
8.6%
E 25
 
4.7%
V 19
 
3.6%
g 18
 
3.4%
B 17
 
3.2%
O 14
 
2.6%
n 12
 
2.2%
Other values (16) 62
11.6%
Common
ValueCountFrequency (%)
1581
29.1%
1 772
14.2%
2 516
 
9.5%
3 344
 
6.3%
0 290
 
5.3%
4 275
 
5.1%
( 250
 
4.6%
) 249
 
4.6%
- 220
 
4.0%
5 191
 
3.5%
Other values (11) 754
13.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7375
55.2%
ASCII 5977
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1581
26.5%
1 772
12.9%
2 516
 
8.6%
3 344
 
5.8%
0 290
 
4.9%
4 275
 
4.6%
( 250
 
4.2%
) 249
 
4.2%
- 220
 
3.7%
5 191
 
3.2%
Other values (37) 1289
21.6%
Hangul
ValueCountFrequency (%)
동 369
 
5.0%
성 279
 
3.8%
층 253
 
3.4%
로 250
 
3.4%
수 214
 
2.9%
길 206
 
2.8%
옥 203
 
2.8%
사 187
 
2.5%
터 169
 
2.3%
장 146
 
2.0%
Other values (292) 5099
69.1%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
<NA>
1125 
1F
 
26
-
 
15
2F
 
14
5F
 
1

Length

Max length4
Median length4
Mean length3.8908629
Min length1

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> 1125
95.2%
1F 26
 
2.2%
- 15
 
1.3%
2F 14
 
1.2%
5F 1
 
0.1%
3F 1
 
0.1%

Length

2024-05-18T07:42:05.694729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:06.229666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1125
95.2%
1f 26
 
2.2%
15
 
1.3%
2f 14
 
1.2%
5f 1
 
0.1%
3f 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1. 주요거리
444 
3. 공원(하천)
138 
7-2-3. 공공 - 동주민센터
78 
4. 문화관광
75 
7-2-1. 공공 - 구청사 및 별관
73 
Other values (15)
374 

Length

Max length21
Median length20
Mean length10.888325
Min length7

Unique

Unique1 ?
Unique (%)0.1%

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 444
37.6%
3. 공원(하천) 138
 
11.7%
7-2-3. 공공 - 동주민센터 78
 
6.6%
4. 문화관광 75
 
6.3%
7-2-1. 공공 - 구청사 및 별관 73
 
6.2%
6-1. 복지 - 사회 66
 
5.6%
6-2. 복지 - 노인 54
 
4.6%
7-1-3. 공공 - 시산하기관 44
 
3.7%
5-1. 버스정류소(국비) 38
 
3.2%
7-3. 공공 - 지역 34
 
2.9%
Other values (10) 138
 
11.7%

Length

2024-05-18T07:42:06.964473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 444
 
12.9%
주요거리 444
 
12.9%
443
 
12.9%
공공 283
 
8.2%
복지 160
 
4.6%
3 139
 
4.0%
공원(하천 138
 
4.0%
및 97
 
2.8%
동주민센터 78
 
2.3%
7-2-3 78
 
2.3%
Other values (33) 1140
33.1%

설치기관
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
자치구에스넷1차
440 
자치구
314 
디지털뉴딜(KT)
160 
서울시(AP)
126 
디지털뉴딜(LG U+)
83 
Other values (4)
59 

Length

Max length12
Median length9
Mean length7.0253807
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
자치구에스넷1차 440
37.2%
자치구 314
26.6%
디지털뉴딜(KT) 160
 
13.5%
서울시(AP) 126
 
10.7%
디지털뉴딜(LG U+) 83
 
7.0%
버스정류소(국비) 38
 
3.2%
버스정류소(시비) 14
 
1.2%
서울시(공유기) 6
 
0.5%
서울시(LTE) 1
 
0.1%

Length

2024-05-18T07:42:07.535797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:08.064676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구에스넷1차 440
34.8%
자치구 314
24.8%
디지털뉴딜(kt 160
 
12.6%
서울시(ap 126
 
10.0%
디지털뉴딜(lg 83
 
6.6%
u 83
 
6.6%
버스정류소(국비 38
 
3.0%
버스정류소(시비 14
 
1.1%
서울시(공유기 6
 
0.5%
서울시(lte 1
 
0.1%

서비스구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
공공WiFi
961 
과기부WiFi(복지시설)
 
91
과기부WiFi(핫플레이스)
 
77
과기부WiFi
 
38
<NA>
 
15

Length

Max length14
Median length6
Mean length7.0668359
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 961
81.3%
과기부WiFi(복지시설) 91
 
7.7%
과기부WiFi(핫플레이스) 77
 
6.5%
과기부WiFi 38
 
3.2%
<NA> 15
 
1.3%

Length

2024-05-18T07:42:08.696858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:09.238292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 961
81.3%
과기부wifi(복지시설 91
 
7.7%
과기부wifi(핫플레이스 77
 
6.5%
과기부wifi 38
 
3.2%
na 15
 
1.3%

망종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
자가망_U무선망
537 
인터넷망_뉴딜용
243 
인터넷망_기관자체
239 
임대망
124 
자가망_수도사업소망
 
25

Length

Max length10
Median length8
Mean length7.6725888
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 (%)
자가망_U무선망 537
45.4%
인터넷망_뉴딜용 243
20.6%
인터넷망_기관자체 239
20.2%
임대망 124
 
10.5%
자가망_수도사업소망 25
 
2.1%
<NA> 14
 
1.2%

Length

2024-05-18T07:42:09.742954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:10.208369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 537
45.4%
인터넷망_뉴딜용 243
20.6%
인터넷망_기관자체 239
20.2%
임대망 124
 
10.5%
자가망_수도사업소망 25
 
2.1%
na 14
 
1.2%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.0296
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T07:42:10.648862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12020
median2020
Q32021
95-th percentile2022
Maximum2023
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9112315
Coefficient of variation (CV)0.00094614033
Kurtosis1.2787027
Mean2020.0296
Median Absolute Deviation (MAD)1
Skewness-1.1014719
Sum2387675
Variance3.6528058
MonotonicityNot monotonic
2024-05-18T07:42:10.996534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020 516
43.7%
2022 233
19.7%
2019 116
 
9.8%
2021 112
 
9.5%
2015 85
 
7.2%
2023 58
 
4.9%
2017 52
 
4.4%
2018 10
 
0.8%
ValueCountFrequency (%)
2015 85
 
7.2%
2017 52
 
4.4%
2018 10
 
0.8%
2019 116
 
9.8%
2020 516
43.7%
2021 112
 
9.5%
2022 233
19.7%
2023 58
 
4.9%
ValueCountFrequency (%)
2023 58
 
4.9%
2022 233
19.7%
2021 112
 
9.5%
2020 516
43.7%
2019 116
 
9.8%
2018 10
 
0.8%
2017 52
 
4.4%
2015 85
 
7.2%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
실외
668 
실내
514 

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 668
56.5%
실내 514
43.5%

Length

2024-05-18T07:42:11.398332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:11.783388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 668
56.5%
실내 514
43.5%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
<NA>
1171 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
11

Length

Max length27
Median length4
Mean length4.214044
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> 1171
99.1%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 11
 
0.9%

Length

2024-05-18T07:42:12.256365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:12.608035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1171
95.5%
보안접속 11
 
0.9%
임시적용(머큐리 11
 
0.9%
proxy 11
 
0.9%
서버 11
 
0.9%
개발중 11
 
0.9%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct699
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.555042
Minimum37.53439
Maximum37.57191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T07:42:12.993712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.53439
5-th percentile37.540291
Q137.546375
median37.55492
Q337.563457
95-th percentile37.570225
Maximum37.57191
Range0.03752
Interquartile range (IQR)0.017082

Descriptive statistics

Standard deviation0.0097670542
Coefficient of variation (CV)0.00026007304
Kurtosis-1.2377056
Mean37.555042
Median Absolute Deviation (MAD)0.008537
Skewness-0.039694706
Sum44390.06
Variance9.5395347 × 10-5
MonotonicityNot monotonic
2024-05-18T07:42:13.578429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.563457 68
 
5.8%
37.56149 20
 
1.7%
37.570225 20
 
1.7%
37.55928 17
 
1.4%
37.540462 17
 
1.4%
37.548183 16
 
1.4%
37.571846 13
 
1.1%
37.567753 13
 
1.1%
37.545753 12
 
1.0%
37.55492 12
 
1.0%
Other values (689) 974
82.4%
ValueCountFrequency (%)
37.53439 1
0.1%
37.534973 1
0.1%
37.53535 1
0.1%
37.53538 1
0.1%
37.53595 1
0.1%
37.536167 1
0.1%
37.536785 1
0.1%
37.5368 1
0.1%
37.536972 1
0.1%
37.53722 1
0.1%
ValueCountFrequency (%)
37.57191 1
 
0.1%
37.571846 13
1.1%
37.571724 1
 
0.1%
37.571716 6
0.5%
37.571556 1
 
0.1%
37.5713 1
 
0.1%
37.57124 1
 
0.1%
37.571194 1
 
0.1%
37.57114 1
 
0.1%
37.571083 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct684
Distinct (%)57.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03952
Minimum127.00955
Maximum127.07265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T07:42:14.196109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.00955
5-th percentile127.01847
Q1127.03114
median127.03754
Q3127.04904
95-th percentile127.06211
Maximum127.07265
Range0.0631
Interquartile range (IQR)0.0179

Descriptive statistics

Standard deviation0.013145852
Coefficient of variation (CV)0.00010347845
Kurtosis-0.48097556
Mean127.03952
Median Absolute Deviation (MAD)0.009246
Skewness0.043392282
Sum150160.71
Variance0.00017281343
MonotonicityNot monotonic
2024-05-18T07:42:14.815025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.03682 68
 
5.8%
127.03344 22
 
1.9%
127.04533 20
 
1.7%
127.01276 17
 
1.4%
127.03539 17
 
1.4%
127.05335 16
 
1.4%
127.02556 13
 
1.1%
127.034966 13
 
1.1%
127.04052 12
 
1.0%
127.04434 11
 
0.9%
Other values (674) 973
82.3%
ValueCountFrequency (%)
127.00955 1
0.1%
127.00971 1
0.1%
127.0104 1
0.1%
127.01051 1
0.1%
127.01088 1
0.1%
127.011 1
0.1%
127.01119 1
0.1%
127.01121 1
0.1%
127.01203 1
0.1%
127.0126 1
0.1%
ValueCountFrequency (%)
127.07265 1
0.1%
127.071594 1
0.1%
127.07122 1
0.1%
127.07019 1
0.1%
127.07016 1
0.1%
127.07004 1
0.1%
127.06998 1
0.1%
127.06986 1
0.1%
127.06975 1
0.1%
127.06958 2
0.2%

작업일자
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-05-17 11:12:57.0
543 
2024-05-17 11:13:01.0
225 
2024-05-17 11:13:03.0
97 
2024-05-17 11:13:04.0
61 
2024-05-17 11:12:52.0
 
52
Other values (8)
204 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2024-05-17 11:12:52.0
2nd row2024-05-17 11:12:52.0
3rd row2024-05-17 11:12:52.0
4th row2024-05-17 11:12:52.0
5th row2024-05-17 11:12:52.0

Common Values

ValueCountFrequency (%)
2024-05-17 11:12:57.0 543
45.9%
2024-05-17 11:13:01.0 225
19.0%
2024-05-17 11:13:03.0 97
 
8.2%
2024-05-17 11:13:04.0 61
 
5.2%
2024-05-17 11:12:52.0 52
 
4.4%
2024-05-17 11:13:05.0 48
 
4.1%
2024-05-17 11:12:58.0 42
 
3.6%
2024-05-17 11:13:00.0 42
 
3.6%
2024-05-17 11:12:59.0 23
 
1.9%
2024-05-17 11:13:02.0 22
 
1.9%
Other values (3) 27
 
2.3%

Length

2024-05-18T07:42:15.497045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-17 1182
50.0%
11:12:57.0 543
23.0%
11:13:01.0 225
 
9.5%
11:13:03.0 97
 
4.1%
11:13:04.0 61
 
2.6%
11:12:52.0 52
 
2.2%
11:13:05.0 48
 
2.0%
11:12:58.0 42
 
1.8%
11:13:00.0 42
 
1.8%
11:12:59.0 23
 
1.0%
Other values (4) 49
 
2.1%

Interactions

2024-05-18T07:41:48.646449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:45.948818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:47.299101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:49.144286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:46.398464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:47.741313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:49.603565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:46.842531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:41:48.196187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T07:42:15.899328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.6041.000NaN0.7201.0001.0000.5730.7371.000
설치유형0.6041.0000.9460.9550.9080.8830.9990.7480.7010.906
설치기관1.0000.9461.0000.8910.8660.8030.7660.4520.3130.932
서비스구분NaN0.9550.8911.0000.6370.7000.6040.4050.3510.971
망종류0.7200.9080.8660.6371.0000.8320.6200.6060.4630.934
설치년도1.0000.8830.8030.7000.8321.0000.5740.3950.2960.873
실내외구분1.0000.9990.7660.6040.6200.5741.0000.3980.3230.810
X좌표0.5730.7480.4520.4050.6060.3950.3981.0000.7230.590
Y좌표0.7370.7010.3130.3510.4630.2960.3230.7231.0000.484
작업일자1.0000.9060.9320.9710.9340.8730.8100.5900.4841.000
2024-05-18T07:42:16.437353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치기관실내외구분설치위치(층)wifi접속환경작업일자설치유형서비스구분망종류
설치기관1.0000.7820.9721.0000.7650.7690.8050.764
실내외구분0.7821.0000.9721.0000.7800.9730.4170.745
설치위치(층)0.9720.9721.000NaN0.9720.5261.0000.652
wifi접속환경1.0001.000NaN1.0001.0001.0001.0001.000
작업일자0.7650.7800.9721.0001.0000.5980.7770.841
설치유형0.7690.9730.5261.0000.5981.0000.7470.730
서비스구분0.8050.4171.0001.0000.7770.7471.0000.566
망종류0.7640.7450.6521.0000.8410.7300.5661.000
2024-05-18T07:42:16.952576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.0000.002-0.0940.9720.6180.5670.5690.7540.6641.0000.615
X좌표0.0021.000-0.2040.3590.3350.2240.2530.2950.3051.0000.291
Y좌표-0.094-0.2041.0000.3720.2970.1480.2160.2100.2471.0000.223
설치위치(층)0.9720.3590.3721.0000.5260.9721.0000.6520.9720.0000.972
설치유형0.6180.3350.2970.5261.0000.7690.7470.7300.9731.0000.598
설치기관0.5670.2240.1480.9720.7691.0000.8050.7640.7821.0000.765
서비스구분0.5690.2530.2161.0000.7470.8051.0000.5660.4171.0000.777
망종류0.7540.2950.2100.6520.7300.7640.5661.0000.7451.0000.841
실내외구분0.6640.3050.2470.9720.9730.7820.4170.7451.0001.0000.780
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.000
작업일자0.6150.2910.2230.9720.5980.7650.7770.8410.7801.0001.000

Missing values

2024-05-18T07:41:50.614277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:41:51.545431image/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.
2024-05-18T07:41:52.257902image/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
0ARI00073성동구동부수도사업소고산자로10길 13본관 B1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
1ARI00074성동구동부수도사업소고산자로10길 13본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
2ARI00075성동구동부수도사업소고산자로10길 13본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
3ARI00076성동구동부수도사업소고산자로10길 13본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
4ARI00077성동구동부수도사업소고산자로10길 13본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
5ARI00078성동구동부수도사업소고산자로10길 13본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
6ARI00079성동구동부수도사업소고산자로10길 13본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
7ARI00080성동구동부수도사업소고산자로10길 13본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
8ARI00081성동구동부수도사업소고산자로10길 13본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
9ARI00082성동구동부수도사업소고산자로10길 13본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.55928127.035392024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1172서울5차-1183성동구대현산유아숲체험장서울특별시 성동구 행당동 324-334(CCTV) F_0023_GH01-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.55397127.030522024-05-17 11:13:06.0
1173서울5차-1185성동구금남시장서울특별시 성동구 독서당로 303-14뽀빠이치킨 위-2. 전통시장디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.548576127.022922024-05-17 11:13:06.0
1174서울5차-1186성동구금남시장서울특별시 성동구 독서당로 301-9곤지암소머리국밥위-2. 전통시장디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.548534127.022612024-05-17 11:13:06.0
1175서울5차-1187성동구금남시장서울특별시 성동구 독서당로 299-10은성보쌈-2. 전통시장디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.54854127.022442024-05-17 11:13:06.0
1176서울5차-1188성동구금남시장서울특별시 성동구 독서당로 301-53아씨옷수선-2. 전통시장디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.548725127.022212024-05-17 11:13:06.0
1177서울5차-1189성동구금남시장서울특별시 성동구 장터5길 4-27한마음왕족발-2. 전통시장디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.54861127.021692024-05-17 11:13:06.0
1178서울5차-1190성동구스마트쉼터(04107 청계벽산아파트_텐즈힐아파트)서울특별시 성동구 무학로 33(스마트쉼터) 04107-5-2. 버스정류소(국비)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.56913127.026012024-05-17 11:13:06.0
1179서울5차-1191성동구스마트쉼터(04295 황학교_텐즈힐몰)서울특별시 성동구 마장로 137(스마트쉼터) 04295-5-2. 버스정류소(국비)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.567776127.024552024-05-17 11:13:06.0
1180서울5차-1192성동구스마트쉼터(04212 성동세무서앞)서울특별시 성동구 광나루로 290(스마트쉼터) 04212-5-2. 버스정류소(국비)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.548127.062062024-05-17 11:13:06.0
1181서울5차-1193성동구스마트쉼터(04236 뚝섬역8번출구)서울특별시 성동구 아차산로 6(스마트쉼터) 04236-5-2. 버스정류소(국비)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.547726127.045522024-05-17 11:13:06.0