Overview

Dataset statistics

Number of variables16
Number of observations1206
Missing cells34
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory154.4 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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-20899/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치유형 and 5 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치위치(층) and 6 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 8 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치위치(층) and 6 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 2 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (94.1%)Imbalance
wifi접속환경 is highly imbalanced (89.8%)Imbalance
도로명주소 has 26 (2.2%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-17 23:14:41.866513
Analysis finished2024-05-17 23:14:47.617491
Duration5.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1206
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-05-18T08:14:48.011005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.0704809
Min length7

Characters and Unicode

Total characters9733
Distinct characters19
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

Unique1206 ?
Unique (%)100.0%

Sample

1st rowBS100386
2nd rowBS100387
3rd rowBS100388
4th rowBS100389
5th rowBS100390
ValueCountFrequency (%)
bs100386 1
 
0.1%
wf190460 1
 
0.1%
wf190455 1
 
0.1%
wf190454 1
 
0.1%
wf190453 1
 
0.1%
wf190452 1
 
0.1%
wf190451 1
 
0.1%
wf190450 1
 
0.1%
wf190449 1
 
0.1%
wf190448 1
 
0.1%
Other values (1196) 1196
99.2%
2024-05-18T08:14:49.529387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1945
20.0%
1 1404
14.4%
W 700
 
7.2%
2 654
 
6.7%
3 538
 
5.5%
4 525
 
5.4%
- 471
 
4.8%
N 434
 
4.5%
9 412
 
4.2%
6 363
 
3.7%
Other values (9) 2287
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6736
69.2%
Uppercase Letter 1732
 
17.8%
Other Letter 794
 
8.2%
Dash Punctuation 471
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1945
28.9%
1 1404
20.8%
2 654
 
9.7%
3 538
 
8.0%
4 525
 
7.8%
9 412
 
6.1%
6 363
 
5.4%
5 348
 
5.2%
8 294
 
4.4%
7 253
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
W 700
40.4%
N 434
25.1%
F 266
 
15.4%
S 179
 
10.3%
B 153
 
8.8%
Other Letter
ValueCountFrequency (%)
서 353
44.5%
울 353
44.5%
차 88
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 471
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7207
74.0%
Latin 1732
 
17.8%
Hangul 794
 
8.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1945
27.0%
1 1404
19.5%
2 654
 
9.1%
3 538
 
7.5%
4 525
 
7.3%
- 471
 
6.5%
9 412
 
5.7%
6 363
 
5.0%
5 348
 
4.8%
8 294
 
4.1%
Latin
ValueCountFrequency (%)
W 700
40.4%
N 434
25.1%
F 266
 
15.4%
S 179
 
10.3%
B 153
 
8.8%
Hangul
ValueCountFrequency (%)
서 353
44.5%
울 353
44.5%
차 88
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8939
91.8%
Hangul 794
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1945
21.8%
1 1404
15.7%
W 700
 
7.8%
2 654
 
7.3%
3 538
 
6.0%
4 525
 
5.9%
- 471
 
5.3%
N 434
 
4.9%
9 412
 
4.6%
6 363
 
4.1%
Other values (6) 1493
16.7%
Hangul
ValueCountFrequency (%)
서 353
44.5%
울 353
44.5%
차 88
 
11.1%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
노원구
1206 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노원구 1206
100.0%

Length

2024-05-18T08:14:49.942579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:50.306669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노원구 1206
100.0%

와이파이명
Text

Distinct371
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-05-18T08:14:50.597656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.2280265
Min length3

Characters and Unicode

Total characters9923
Distinct characters300
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

Unique202 ?
Unique (%)16.7%

Sample

1st row버스정류소_경춘선숲길.화랑대역공원
2nd row버스정류소_골마을근린공원
3rd row버스정류소_공릉대동2차아파트
4th row버스정류소_공릉시장
5th row버스정류소_공릉시장
ValueCountFrequency (%)
노원구청 68
 
5.3%
상계종합사회복지관 24
 
1.9%
월계종합사회복지관 24
 
1.9%
노원역 23
 
1.8%
북부종합사회복지관 23
 
1.8%
시립노원청소년센터 23
 
1.8%
북서울미술관 22
 
1.7%
노원1종합사회복지관 22
 
1.7%
경춘선숲길 20
 
1.6%
중계본동 19
 
1.5%
Other values (373) 1019
79.2%
2024-05-18T08:14:51.385240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 478
 
4.8%
계 346
 
3.5%
노 312
 
3.1%
관 293
 
3.0%
지 280
 
2.8%
소 256
 
2.6%
터 250
 
2.5%
센 242
 
2.4%
복 232
 
2.3%
정 225
 
2.3%
Other values (290) 7009
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9427
95.0%
Decimal Number 193
 
1.9%
Connector Punctuation 153
 
1.5%
Space Separator 81
 
0.8%
Uppercase Letter 30
 
0.3%
Other Punctuation 25
 
0.3%
Dash Punctuation 6
 
0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 478
 
5.1%
계 346
 
3.7%
노 312
 
3.3%
관 293
 
3.1%
지 280
 
3.0%
소 256
 
2.7%
터 250
 
2.7%
센 242
 
2.6%
복 232
 
2.5%
정 225
 
2.4%
Other values (266) 6513
69.1%
Decimal Number
ValueCountFrequency (%)
1 74
38.3%
2 36
18.7%
3 21
 
10.9%
4 18
 
9.3%
0 13
 
6.7%
5 12
 
6.2%
9 6
 
3.1%
7 5
 
2.6%
8 5
 
2.6%
6 3
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
I 6
20.0%
N 6
20.0%
V 3
10.0%
K 3
10.0%
S 3
10.0%
A 3
10.0%
T 3
10.0%
M 3
10.0%
Connector Punctuation
ValueCountFrequency (%)
_ 153
100.0%
Space Separator
ValueCountFrequency (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9427
95.0%
Common 466
 
4.7%
Latin 30
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 478
 
5.1%
계 346
 
3.7%
노 312
 
3.3%
관 293
 
3.1%
지 280
 
3.0%
소 256
 
2.7%
터 250
 
2.7%
센 242
 
2.6%
복 232
 
2.5%
정 225
 
2.4%
Other values (266) 6513
69.1%
Common
ValueCountFrequency (%)
_ 153
32.8%
81
17.4%
1 74
15.9%
2 36
 
7.7%
. 25
 
5.4%
3 21
 
4.5%
4 18
 
3.9%
0 13
 
2.8%
5 12
 
2.6%
9 6
 
1.3%
Other values (6) 27
 
5.8%
Latin
ValueCountFrequency (%)
I 6
20.0%
N 6
20.0%
V 3
10.0%
K 3
10.0%
S 3
10.0%
A 3
10.0%
T 3
10.0%
M 3
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9427
95.0%
ASCII 496
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 478
 
5.1%
계 346
 
3.7%
노 312
 
3.3%
관 293
 
3.1%
지 280
 
3.0%
소 256
 
2.7%
터 250
 
2.7%
센 242
 
2.6%
복 232
 
2.5%
정 225
 
2.4%
Other values (266) 6513
69.1%
ASCII
ValueCountFrequency (%)
_ 153
30.8%
81
16.3%
1 74
14.9%
2 36
 
7.3%
. 25
 
5.0%
3 21
 
4.2%
4 18
 
3.6%
0 13
 
2.6%
5 12
 
2.4%
9 6
 
1.2%
Other values (14) 57
 
11.5%

도로명주소
Text

MISSING 

Distinct488
Distinct (%)41.4%
Missing26
Missing (%)2.2%
Memory size9.6 KiB
2024-05-18T08:14:51.879735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length42
Mean length16.563559
Min length3

Characters and Unicode

Total characters19545
Distinct characters217
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

Unique327 ?
Unique (%)27.7%

Sample

1st row공릉2 121-3
2nd row하계동251-8
3rd row공릉동380-4
4th row공릉동567-4
5th row공릉동 568-27
ValueCountFrequency (%)
노원구 773
 
19.1%
서울특별시 712
 
17.6%
노해로 89
 
2.2%
437 72
 
1.8%
노원로 66
 
1.6%
덕릉로 66
 
1.6%
동일로 53
 
1.3%
월계로 52
 
1.3%
상계동 51
 
1.3%
중계동 49
 
1.2%
Other values (653) 2058
50.9%
2024-05-18T08:14:52.738129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2869
 
14.7%
노 1028
 
5.3%
1 948
 
4.9%
원 945
 
4.8%
로 865
 
4.4%
구 799
 
4.1%
서 756
 
3.9%
울 754
 
3.9%
시 737
 
3.8%
2 722
 
3.7%
Other values (207) 9122
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11204
57.3%
Decimal Number 4873
24.9%
Space Separator 2869
 
14.7%
Dash Punctuation 325
 
1.7%
Close Punctuation 104
 
0.5%
Open Punctuation 104
 
0.5%
Other Punctuation 32
 
0.2%
Uppercase Letter 29
 
0.1%
Lowercase Letter 4
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 1028
 
9.2%
원 945
 
8.4%
로 865
 
7.7%
구 799
 
7.1%
서 756
 
6.7%
울 754
 
6.7%
시 737
 
6.6%
별 715
 
6.4%
특 712
 
6.4%
동 522
 
4.7%
Other values (177) 3371
30.1%
Decimal Number
ValueCountFrequency (%)
1 948
19.5%
2 722
14.8%
3 531
10.9%
5 487
10.0%
4 457
9.4%
7 456
9.4%
6 390
8.0%
0 358
 
7.3%
8 284
 
5.8%
9 240
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
F 9
31.0%
B 7
24.1%
T 4
13.8%
K 2
 
6.9%
C 2
 
6.9%
M 1
 
3.4%
D 1
 
3.4%
P 1
 
3.4%
A 1
 
3.4%
V 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
c 2
50.0%
t 1
25.0%
v 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 17
53.1%
. 15
46.9%
Space Separator
ValueCountFrequency (%)
2869
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11204
57.3%
Common 8308
42.5%
Latin 33
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 1028
 
9.2%
원 945
 
8.4%
로 865
 
7.7%
구 799
 
7.1%
서 756
 
6.7%
울 754
 
6.7%
시 737
 
6.6%
별 715
 
6.4%
특 712
 
6.4%
동 522
 
4.7%
Other values (177) 3371
30.1%
Common
ValueCountFrequency (%)
2869
34.5%
1 948
 
11.4%
2 722
 
8.7%
3 531
 
6.4%
5 487
 
5.9%
4 457
 
5.5%
7 456
 
5.5%
6 390
 
4.7%
0 358
 
4.3%
- 325
 
3.9%
Other values (7) 765
 
9.2%
Latin
ValueCountFrequency (%)
F 9
27.3%
B 7
21.2%
T 4
12.1%
c 2
 
6.1%
K 2
 
6.1%
C 2
 
6.1%
t 1
 
3.0%
M 1
 
3.0%
D 1
 
3.0%
v 1
 
3.0%
Other values (3) 3
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11204
57.3%
ASCII 8341
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2869
34.4%
1 948
 
11.4%
2 722
 
8.7%
3 531
 
6.4%
5 487
 
5.8%
4 457
 
5.5%
7 456
 
5.5%
6 390
 
4.7%
0 358
 
4.3%
- 325
 
3.9%
Other values (20) 798
 
9.6%
Hangul
ValueCountFrequency (%)
노 1028
 
9.2%
원 945
 
8.4%
로 865
 
7.7%
구 799
 
7.1%
서 756
 
6.7%
울 754
 
6.7%
시 737
 
6.6%
별 715
 
6.4%
특 712
 
6.4%
동 522
 
4.7%
Other values (177) 3371
30.1%

상세주소
Text

Distinct966
Distinct (%)80.6%
Missing8
Missing (%)0.7%
Memory size9.6 KiB
2024-05-18T08:14:53.202305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length11.732053
Min length1

Characters and Unicode

Total characters14055
Distinct characters350
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique826 ?
Unique (%)68.9%

Sample

1st row11-143
2nd row11-434
3rd row11-165
4th row11-101
5th row11-102
ValueCountFrequency (%)
옥내1 55
 
2.5%
2층 50
 
2.2%
1층 49
 
2.2%
복도 41
 
1.8%
앞 35
 
1.6%
3층 34
 
1.5%
옥내2 34
 
1.5%
상계동 29
 
1.3%
일대 29
 
1.3%
옥내3 28
 
1.3%
Other values (988) 1851
82.8%
2024-05-18T08:14:54.177860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1038
 
7.4%
1 946
 
6.7%
층 492
 
3.5%
2 476
 
3.4%
( 441
 
3.1%
) 441
 
3.1%
3 392
 
2.8%
원 357
 
2.5%
계 288
 
2.0%
옥 271
 
1.9%
Other values (340) 8913
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8370
59.6%
Decimal Number 2987
 
21.3%
Space Separator 1038
 
7.4%
Open Punctuation 441
 
3.1%
Close Punctuation 441
 
3.1%
Uppercase Letter 290
 
2.1%
Dash Punctuation 255
 
1.8%
Other Punctuation 104
 
0.7%
Connector Punctuation 100
 
0.7%
Lowercase Letter 28
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 492
 
5.9%
원 357
 
4.3%
계 288
 
3.4%
옥 271
 
3.2%
관 260
 
3.1%
터 217
 
2.6%
노 212
 
2.5%
동 207
 
2.5%
내 207
 
2.5%
센 202
 
2.4%
Other values (298) 5657
67.6%
Uppercase Letter
ValueCountFrequency (%)
C 111
38.3%
T 67
23.1%
V 55
19.0%
F 26
 
9.0%
K 11
 
3.8%
P 6
 
2.1%
A 3
 
1.0%
B 3
 
1.0%
S 3
 
1.0%
M 1
 
0.3%
Other values (4) 4
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 946
31.7%
2 476
15.9%
3 392
13.1%
4 253
 
8.5%
5 203
 
6.8%
6 177
 
5.9%
0 160
 
5.4%
7 133
 
4.5%
9 127
 
4.3%
8 120
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
c 8
28.6%
b 5
17.9%
t 5
17.9%
v 5
17.9%
d 1
 
3.6%
p 1
 
3.6%
e 1
 
3.6%
l 1
 
3.6%
o 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 68
65.4%
. 35
33.7%
? 1
 
1.0%
Space Separator
ValueCountFrequency (%)
1038
100.0%
Open Punctuation
ValueCountFrequency (%)
( 441
100.0%
Close Punctuation
ValueCountFrequency (%)
) 441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 255
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 100
100.0%
Other Symbol
ValueCountFrequency (%)
▲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8370
59.6%
Common 5367
38.2%
Latin 318
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 492
 
5.9%
원 357
 
4.3%
계 288
 
3.4%
옥 271
 
3.2%
관 260
 
3.1%
터 217
 
2.6%
노 212
 
2.5%
동 207
 
2.5%
내 207
 
2.5%
센 202
 
2.4%
Other values (298) 5657
67.6%
Latin
ValueCountFrequency (%)
C 111
34.9%
T 67
21.1%
V 55
17.3%
F 26
 
8.2%
K 11
 
3.5%
c 8
 
2.5%
P 6
 
1.9%
b 5
 
1.6%
t 5
 
1.6%
v 5
 
1.6%
Other values (13) 19
 
6.0%
Common
ValueCountFrequency (%)
1038
19.3%
1 946
17.6%
2 476
8.9%
( 441
8.2%
) 441
8.2%
3 392
 
7.3%
- 255
 
4.8%
4 253
 
4.7%
5 203
 
3.8%
6 177
 
3.3%
Other values (9) 745
13.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8370
59.6%
ASCII 5684
40.4%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1038
18.3%
1 946
16.6%
2 476
8.4%
( 441
7.8%
) 441
7.8%
3 392
 
6.9%
- 255
 
4.5%
4 253
 
4.5%
5 203
 
3.6%
6 177
 
3.1%
Other values (31) 1062
18.7%
Hangul
ValueCountFrequency (%)
층 492
 
5.9%
원 357
 
4.3%
계 288
 
3.4%
옥 271
 
3.2%
관 260
 
3.1%
터 217
 
2.6%
노 212
 
2.5%
동 207
 
2.5%
내 207
 
2.5%
센 202
 
2.4%
Other values (298) 5657
67.6%
Geometric Shapes
ValueCountFrequency (%)
▲ 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
<NA>
1184 
-
 
17
2층
 
2
02-2116-3966,소장010-3409-0170
 
1
1층
 
1

Length

Max length28
Median length4
Mean length3.9709784
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1184
98.2%
- 17
 
1.4%
2층 2
 
0.2%
02-2116-3966,소장010-3409-0170 1
 
0.1%
1층 1
 
0.1%
4층 1
 
0.1%

Length

2024-05-18T08:14:54.546259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:54.818945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1184
98.2%
17
 
1.4%
2층 2
 
0.2%
02-2116-3966,소장010-3409-0170 1
 
0.1%
1층 1
 
0.1%
4층 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
3. 공원(하천)
212 
4. 문화관광
155 
6-1. 복지 - 사회
149 
5-1. 버스정류소(국비)
127 
1. 주요거리
109 
Other values (15)
454 

Length

Max length21
Median length17
Mean length11.8466
Min length7

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row5-1. 버스정류소(국비)
2nd row5-1. 버스정류소(국비)
3rd row5-1. 버스정류소(국비)
4th row5-1. 버스정류소(국비)
5th row5-1. 버스정류소(국비)

Common Values

ValueCountFrequency (%)
3. 공원(하천) 212
17.6%
4. 문화관광 155
12.9%
6-1. 복지 - 사회 149
12.4%
5-1. 버스정류소(국비) 127
10.5%
1. 주요거리 109
9.0%
7-2-3. 공공 - 동주민센터 72
 
6.0%
7-2-1. 공공 - 구청사 및 별관 68
 
5.6%
6-3. 복지 - 장애인 66
 
5.5%
6-4. 복지 - 아동청소년 64
 
5.3%
7-3. 공공 - 지역 52
 
4.3%
Other values (10) 132
10.9%

Length

2024-05-18T08:14:55.220380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
566
 
15.1%
복지 334
 
8.9%
공공 232
 
6.2%
3 212
 
5.7%
공원(하천 212
 
5.7%
문화관광 155
 
4.1%
4 155
 
4.1%
6-1 149
 
4.0%
사회 149
 
4.0%
5-1 127
 
3.4%
Other values (36) 1445
38.7%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
자치구
434 
서울시(AP)
261 
디지털뉴딜(KT)
243 
버스정류소(국비)
127 
디지털뉴딜(LG U+)
110 
Other values (2)
 
31

Length

Max length12
Median length9
Mean length6.6774461
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row버스정류소(국비)
2nd row버스정류소(국비)
3rd row버스정류소(국비)
4th row버스정류소(국비)
5th row버스정류소(국비)

Common Values

ValueCountFrequency (%)
자치구 434
36.0%
서울시(AP) 261
21.6%
디지털뉴딜(KT) 243
20.1%
버스정류소(국비) 127
 
10.5%
디지털뉴딜(LG U+) 110
 
9.1%
버스정류소(시비) 26
 
2.2%
서울시(공유기) 5
 
0.4%

Length

2024-05-18T08:14:55.578582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:55.891663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 434
33.0%
서울시(ap 261
19.8%
디지털뉴딜(kt 243
18.5%
버스정류소(국비 127
 
9.7%
디지털뉴딜(lg 110
 
8.4%
u 110
 
8.4%
버스정류소(시비 26
 
2.0%
서울시(공유기 5
 
0.4%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
공공WiFi
793 
과기부WiFi(복지시설)
165 
과기부WiFi
127 
과기부WiFi(핫플레이스)
100 
<NA>
 
21

Length

Max length14
Median length6
Mean length7.6915423
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 793
65.8%
과기부WiFi(복지시설) 165
 
13.7%
과기부WiFi 127
 
10.5%
과기부WiFi(핫플레이스) 100
 
8.3%
<NA> 21
 
1.7%

Length

2024-05-18T08:14:56.224588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:56.552874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 793
65.8%
과기부wifi(복지시설 165
 
13.7%
과기부wifi 127
 
10.5%
과기부wifi(핫플레이스 100
 
8.3%
na 21
 
1.7%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
<NA>
460 
인터넷망_뉴딜용
353 
임대망
265 
자가망_U무선망
106 
전용회선_30M
 
22

Length

Max length8
Median length4
Mean length5.3756219
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 460
38.1%
인터넷망_뉴딜용 353
29.3%
임대망 265
22.0%
자가망_U무선망 106
 
8.8%
전용회선_30M 22
 
1.8%

Length

2024-05-18T08:14:57.063949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:57.481971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 460
38.1%
인터넷망_뉴딜용 353
29.3%
임대망 265
22.0%
자가망_u무선망 106
 
8.8%
전용회선_30m 22
 
1.8%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.8035
Minimum2011
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.7 KiB
2024-05-18T08:14:57.821995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2017
Q12019
median2021
Q32022
95-th percentile2023
Maximum2023
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8037364
Coefficient of variation (CV)0.00089258378
Kurtosis2.3190618
Mean2020.8035
Median Absolute Deviation (MAD)1
Skewness-1.2091969
Sum2437089
Variance3.253465
MonotonicityNot monotonic
2024-05-18T08:14:58.152525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2022 404
33.5%
2021 248
20.6%
2019 199
16.5%
2023 154
 
12.8%
2020 81
 
6.7%
2018 53
 
4.4%
2017 49
 
4.1%
2016 12
 
1.0%
2011 3
 
0.2%
2013 2
 
0.2%
ValueCountFrequency (%)
2011 3
 
0.2%
2012 1
 
0.1%
2013 2
 
0.2%
2016 12
 
1.0%
2017 49
 
4.1%
2018 53
 
4.4%
2019 199
16.5%
2020 81
 
6.7%
2021 248
20.6%
2022 404
33.5%
ValueCountFrequency (%)
2023 154
 
12.8%
2022 404
33.5%
2021 248
20.6%
2020 81
 
6.7%
2019 199
16.5%
2018 53
 
4.4%
2017 49
 
4.1%
2016 12
 
1.0%
2013 2
 
0.2%
2012 1
 
0.1%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
실내
701 
실외
505 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실내 701
58.1%
실외 505
41.9%

Length

2024-05-18T08:14:58.522552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:58.892239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 701
58.1%
실외 505
41.9%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
<NA>
1190 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
16

Length

Max length27
Median length4
Mean length4.305141
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> 1190
98.7%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 16
 
1.3%

Length

2024-05-18T08:14:59.508543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:14:59.789468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1190
93.7%
보안접속 16
 
1.3%
임시적용(머큐리 16
 
1.3%
proxy 16
 
1.3%
서버 16
 
1.3%
개발중 16
 
1.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct538
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.645827
Minimum37.614918
Maximum37.68933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.7 KiB
2024-05-18T08:15:00.215696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.614918
5-th percentile37.620461
Q137.63025
median37.644356
Q337.656414
95-th percentile37.679634
Maximum37.68933
Range0.074412
Interquartile range (IQR)0.026164

Descriptive statistics

Standard deviation0.017123413
Coefficient of variation (CV)0.00045485555
Kurtosis-0.69296483
Mean37.645827
Median Absolute Deviation (MAD)0.013138
Skewness0.26902014
Sum45400.867
Variance0.00029321128
MonotonicityNot monotonic
2024-05-18T08:15:00.885925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.654358 66
 
5.5%
37.64064 22
 
1.8%
37.66805 18
 
1.5%
37.62725 18
 
1.5%
37.63025 15
 
1.2%
37.64291 15
 
1.2%
37.679703 15
 
1.2%
37.66109 14
 
1.2%
37.658615 14
 
1.2%
37.64169 13
 
1.1%
Other values (528) 996
82.6%
ValueCountFrequency (%)
37.614918 1
 
0.1%
37.615303 1
 
0.1%
37.615807 1
 
0.1%
37.61647 2
0.2%
37.617744 3
0.2%
37.61777 1
 
0.1%
37.6178 1
 
0.1%
37.617825 1
 
0.1%
37.617912 1
 
0.1%
37.618256 1
 
0.1%
ValueCountFrequency (%)
37.68933 1
0.1%
37.68901 1
0.1%
37.68777 1
0.1%
37.68718 1
0.1%
37.687065 1
0.1%
37.684322 1
0.1%
37.683544 1
0.1%
37.682983 1
0.1%
37.682896 1
0.1%
37.68284 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct523
Distinct (%)43.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06646
Minimum127.04431
Maximum127.11129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.7 KiB
2024-05-18T08:15:01.321351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.04431
5-th percentile127.0524
Q1127.057
median127.06588
Q3127.07389
95-th percentile127.08322
Maximum127.11129
Range0.06698
Interquartile range (IQR)0.01688625

Descriptive statistics

Standard deviation0.010552151
Coefficient of variation (CV)8.3044347 × 10-5
Kurtosis0.15943847
Mean127.06646
Median Absolute Deviation (MAD)0.00843
Skewness0.51161261
Sum153242.15
Variance0.00011134789
MonotonicityNot monotonic
2024-05-18T08:15:01.887292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.05642 65
 
5.4%
127.052414 23
 
1.9%
127.06694 22
 
1.8%
127.06201 21
 
1.7%
127.05283 18
 
1.5%
127.0783 18
 
1.5%
127.0602 15
 
1.2%
127.07353 14
 
1.2%
127.06505 14
 
1.2%
127.054726 12
 
1.0%
Other values (513) 984
81.6%
ValueCountFrequency (%)
127.04431 1
0.1%
127.04442 2
0.2%
127.04472 1
0.1%
127.044785 1
0.1%
127.045 1
0.1%
127.04542 2
0.2%
127.04656 2
0.2%
127.04703 1
0.1%
127.047485 1
0.1%
127.048225 1
0.1%
ValueCountFrequency (%)
127.11129 1
0.1%
127.10844 1
0.1%
127.1083 1
0.1%
127.10628 1
0.1%
127.10548 1
0.1%
127.10327 1
0.1%
127.09854 1
0.1%
127.096275 1
0.1%
127.09618 1
0.1%
127.09504 1
0.1%

작업일자
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-05-17 11:12:56.0
292 
2024-05-17 11:12:57.0
168 
2024-05-17 11:13:03.0
117 
2024-05-17 11:13:00.0
111 
2024-05-17 11:13:02.0
106 
Other values (7)
412 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

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 11:12:56.0 292
24.2%
2024-05-17 11:12:57.0 168
13.9%
2024-05-17 11:13:03.0 117
9.7%
2024-05-17 11:13:00.0 111
 
9.2%
2024-05-17 11:13:02.0 106
 
8.8%
2024-05-17 11:12:59.0 93
 
7.7%
2024-05-17 11:12:52.0 82
 
6.8%
2024-05-17 11:13:04.0 76
 
6.3%
2024-05-17 11:12:58.0 62
 
5.1%
2024-05-17 11:12:53.0 45
 
3.7%
Other values (2) 54
 
4.5%

Length

2024-05-18T08:15:02.388335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-17 1206
50.0%
11:12:56.0 292
 
12.1%
11:12:57.0 168
 
7.0%
11:13:03.0 117
 
4.9%
11:13:00.0 111
 
4.6%
11:13:02.0 106
 
4.4%
11:12:59.0 93
 
3.9%
11:12:52.0 82
 
3.4%
11:13:04.0 76
 
3.2%
11:12:58.0 62
 
2.6%
Other values (3) 99
 
4.1%

Interactions

2024-05-18T08:14:45.328912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:44.087286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:44.708653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:45.510953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:44.344277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:44.925076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:45.701112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:44.528455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:14:45.128743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T08:15:02.641776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.6571.000NaN1.0001.0001.0000.0000.0001.000
설치유형0.6571.0000.9110.9530.8580.7150.9980.7130.6130.865
설치기관1.0000.9111.0000.8670.7050.6960.4650.3530.2870.930
서비스구분NaN0.9530.8671.0000.8800.8280.8290.3660.3230.982
망종류1.0000.8580.7050.8801.0000.8930.6010.3340.4070.914
설치년도1.0000.7150.6960.8280.8931.0000.4300.3320.2640.792
실내외구분1.0000.9980.4650.8290.6010.4301.0000.3890.3680.729
X좌표0.0000.7130.3530.3660.3340.3320.3891.0000.6630.430
Y좌표0.0000.6130.2870.3230.4070.2640.3680.6631.0000.374
작업일자1.0000.8650.9300.9820.9140.7920.7290.4300.3741.000
2024-05-18T08:15:03.070182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)서비스구분설치기관설치유형wifi접속환경망종류실내외구분작업일자
설치위치(층)1.000NaN0.9220.587NaN0.9220.9220.922
서비스구분NaN1.0000.8010.7441.0000.5510.6230.819
설치기관0.9220.8011.0000.6941.0000.6410.4980.804
설치유형0.5870.7440.6941.0001.0000.6800.9570.517
wifi접속환경NaN1.0001.0001.0001.0001.0001.0001.000
망종류0.9220.5510.6410.6801.0001.0000.4140.804
실내외구분0.9220.6230.4980.9571.0000.4141.0000.577
작업일자0.9220.8190.8040.5171.0000.8040.5771.000
2024-05-18T08:15:03.439699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.0000.034-0.0580.9220.3860.4670.4970.7710.3251.0000.484
X좌표0.0341.000-0.2310.0000.3050.1870.2260.2040.2981.0000.196
Y좌표-0.058-0.2311.0000.0000.2380.1490.1980.2540.2821.0000.166
설치위치(층)0.9220.0000.0001.0000.5870.922NaN0.9220.9220.0000.922
설치유형0.3860.3050.2380.5871.0000.6940.7440.6800.9571.0000.517
설치기관0.4670.1870.1490.9220.6941.0000.8010.6410.4981.0000.804
서비스구분0.4970.2260.198NaN0.7440.8011.0000.5510.6231.0000.819
망종류0.7710.2040.2540.9220.6800.6410.5511.0000.4141.0000.804
실내외구분0.3250.2980.2820.9220.9570.4980.6230.4141.0001.0000.577
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.000
작업일자0.4840.1960.1660.9220.5170.8040.8190.8040.5771.0001.000

Missing values

2024-05-18T08:14:46.153308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T08:14:46.959553image/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.
2024-05-18T08:14:47.408111image/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
0BS100386노원구버스정류소_경춘선숲길.화랑대역공원공릉2 121-311-143<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.623535127.090262024-05-17 11:12:52.0
1BS100387노원구버스정류소_골마을근린공원하계동251-811-434<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.638367127.074422024-05-17 11:12:52.0
2BS100388노원구버스정류소_공릉대동2차아파트공릉동380-411-165<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.626896127.070842024-05-17 11:12:52.0
3BS100389노원구버스정류소_공릉시장공릉동567-411-101<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.62274127.074182024-05-17 11:12:52.0
4BS100390노원구버스정류소_공릉시장공릉동 568-2711-102<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.623116127.073622024-05-17 11:12:52.0
5BS100391노원구버스정류소_공릉역1번출구공릉동 375-411-161<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.62658127.0727842024-05-17 11:12:52.0
6BS100392노원구버스정류소_공릉역4번출구공릉동 379-2711-162<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.626358127.072422024-05-17 11:12:52.0
7BS100393노원구버스정류소_광운대학교월계동46611-335<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.619843127.058142024-05-17 11:12:52.0
8BS100394노원구버스정류소_노원고등학교상계동82011-181<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.66132127.0545352024-05-17 11:12:52.0
9BS100395노원구버스정류소_노원문화예술회관.불암초등학교중계동364-511-403<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.650047127.080922024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1196서울5차-0585노원구노원구뇌병변장애인비전센터서울특별시 노원구 한글비석로 432집단활동실1층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.662724127.069512024-05-17 11:13:06.0
1197서울5차-0585-1노원구노원구뇌병변장애인비전센터서울특별시 노원구 한글비석로 432강당4층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.662724127.069512024-05-17 11:13:06.0
1198서울5차-0586노원구노원구장애인주간보호시설서울특별시 노원구 한글비석로 432사무실2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.662724127.069512024-05-17 11:13:06.0
1199서울5차-0586-1노원구노원구장애인주간보호시설서울특별시 노원구 한글비석로 432이야기실2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.662724127.069512024-05-17 11:13:06.0
1200서울5차-0999노원구감나무어린이공원서울특별시 노원구 상계동 741(CCTV) 공원23-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.64923127.058632024-05-17 11:13:06.0
1201서울5차-1000노원구비석골근린공원물놀이장서울특별시 노원구 초안산로5길 74(CCTV) 공원388-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.630436127.0482252024-05-17 11:13:06.0
1202서울5차-1001노원구민들레어린이공원서울특별시 노원구 상계8동 667(CCTV) 공원004-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.662685127.0561142024-05-17 11:13:06.0
1203서울5차-1004노원구사랑어린이공원서울특별시 노원구 상계6,7동765-1(CCTV) 공원025-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.647224127.0600052024-05-17 11:13:06.0
1204서울5차-1005노원구개나리어린이공원서울특별시 노원구 상계9동 627(CCTV) 공원163-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.66921127.0582052024-05-17 11:13:06.0
1205서울5차-1006노원구선녀어린이공원서울특별시 노원구 상계동 767-2(CCTV) 공원271-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.64689127.058632024-05-17 11:13:06.0