Overview

Dataset statistics

Number of variables16
Number of observations990
Missing cells1009
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory127.7 KiB
Average record size in memory132.1 B

Variable types

Text4
Categorical8
Numeric3
Unsupported1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-20898/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치유형 and 2 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치유형 and 1 other fieldsHigh correlation
X좌표 is highly overall correlated with 설치위치(층)High correlation
Y좌표 is highly overall correlated with 설치위치(층)High correlation
설치기관 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
설치위치(층) is highly imbalanced (66.2%)Imbalance
도로명주소 has 12 (1.2%) missing valuesMissing
wifi접속환경 has 990 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
wifi접속환경 is an unsupported type, check if it needs cleaning or further analysisUnsupported
X좌표 has 24 (2.4%) zerosZeros
Y좌표 has 24 (2.4%) zerosZeros

Reproduction

Analysis started2024-05-18 05:45:51.324483
Analysis finished2024-05-18 05:45:59.541518
Duration8.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2024-05-18T14:46:00.027618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.3030303
Min length7

Characters and Unicode

Total characters8220
Distinct characters27
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

Unique990 ?
Unique (%)100.0%

Sample

1st rowBS100468
2nd rowBS100469
3rd rowBS100470
4th rowBS100471
5th rowBS100472
ValueCountFrequency (%)
bs100468 1
 
0.1%
wf201379 1
 
0.1%
wf201381 1
 
0.1%
wf201382 1
 
0.1%
wf201383 1
 
0.1%
wf201384 1
 
0.1%
wf201385 1
 
0.1%
wf201386 1
 
0.1%
wf201387 1
 
0.1%
wf201388 1
 
0.1%
Other values (980) 980
99.0%
2024-05-18T14:46:01.212249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1927
23.4%
1 970
11.8%
2 608
 
7.4%
B 481
 
5.9%
D 471
 
5.7%
3 457
 
5.6%
4 382
 
4.6%
W 302
 
3.7%
6 296
 
3.6%
- 283
 
3.4%
Other values (17) 2043
24.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5550
67.5%
Uppercase Letter 1916
 
23.3%
Other Letter 471
 
5.7%
Dash Punctuation 283
 
3.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 481
25.1%
D 471
24.6%
W 302
15.8%
F 196
10.2%
N 100
 
5.2%
S 100
 
5.2%
U 90
 
4.7%
G 44
 
2.3%
C 30
 
1.6%
R 30
 
1.6%
Other values (3) 72
 
3.8%
Decimal Number
ValueCountFrequency (%)
0 1927
34.7%
1 970
17.5%
2 608
 
11.0%
3 457
 
8.2%
4 382
 
6.9%
6 296
 
5.3%
7 280
 
5.0%
8 253
 
4.6%
5 200
 
3.6%
9 177
 
3.2%
Other Letter
ValueCountFrequency (%)
울 213
45.2%
서 213
45.2%
차 45
 
9.6%
Dash Punctuation
ValueCountFrequency (%)
- 283
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5833
71.0%
Latin 1916
 
23.3%
Hangul 471
 
5.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 481
25.1%
D 471
24.6%
W 302
15.8%
F 196
10.2%
N 100
 
5.2%
S 100
 
5.2%
U 90
 
4.7%
G 44
 
2.3%
C 30
 
1.6%
R 30
 
1.6%
Other values (3) 72
 
3.8%
Common
ValueCountFrequency (%)
0 1927
33.0%
1 970
16.6%
2 608
 
10.4%
3 457
 
7.8%
4 382
 
6.5%
6 296
 
5.1%
- 283
 
4.9%
7 280
 
4.8%
8 253
 
4.3%
5 200
 
3.4%
Hangul
ValueCountFrequency (%)
울 213
45.2%
서 213
45.2%
차 45
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7749
94.3%
Hangul 471
 
5.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1927
24.9%
1 970
12.5%
2 608
 
7.8%
B 481
 
6.2%
D 471
 
6.1%
3 457
 
5.9%
4 382
 
4.9%
W 302
 
3.9%
6 296
 
3.8%
- 283
 
3.7%
Other values (14) 1572
20.3%
Hangul
ValueCountFrequency (%)
울 213
45.2%
서 213
45.2%
차 45
 
9.6%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
도봉구
990 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도봉구 990
100.0%

Length

2024-05-18T14:46:01.595941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:46:01.862775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도봉구 990
100.0%

와이파이명
Text

Distinct120
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2024-05-18T14:46:02.266470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length5.9717172
Min length3

Characters and Unicode

Total characters5912
Distinct characters145
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)3.1%

Sample

1st row버스정류소_도봉구민회관
2nd row버스정류소_도봉구민회관
3rd row버스정류소_도봉구청
4th row버스정류소_도봉보건소
5th row버스정류소_도봉보건소.북한산아이파크아파트
ValueCountFrequency (%)
도봉구청 91
 
8.9%
도봉2동 58
 
5.7%
창4동 53
 
5.2%
도봉1동 41
 
4.0%
창1동 39
 
3.8%
창5동 39
 
3.8%
쌍문1동 32
 
3.1%
창2동 30
 
2.9%
중랑천 30
 
2.9%
방학3동 30
 
2.9%
Other values (111) 577
56.6%
2024-05-18T14:46:03.352467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 706
 
11.9%
창 329
 
5.6%
도 303
 
5.1%
봉 280
 
4.7%
1 180
 
3.0%
문 177
 
3.0%
2 175
 
3.0%
쌍 172
 
2.9%
터 169
 
2.9%
센 166
 
2.8%
Other values (135) 3255
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4910
83.1%
Decimal Number 651
 
11.0%
Close Punctuation 109
 
1.8%
Open Punctuation 109
 
1.8%
Connector Punctuation 58
 
1.0%
Other Punctuation 45
 
0.8%
Space Separator 30
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 706
 
14.4%
창 329
 
6.7%
도 303
 
6.2%
봉 280
 
5.7%
문 177
 
3.6%
쌍 172
 
3.5%
터 169
 
3.4%
센 166
 
3.4%
방 156
 
3.2%
학 143
 
2.9%
Other values (119) 2309
47.0%
Decimal Number
ValueCountFrequency (%)
1 180
27.6%
2 175
26.9%
3 108
16.6%
4 101
15.5%
5 59
 
9.1%
0 20
 
3.1%
9 2
 
0.3%
7 2
 
0.3%
8 2
 
0.3%
6 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
# 30
66.7%
. 15
33.3%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 58
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4910
83.1%
Common 1002
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 706
 
14.4%
창 329
 
6.7%
도 303
 
6.2%
봉 280
 
5.7%
문 177
 
3.6%
쌍 172
 
3.5%
터 169
 
3.4%
센 166
 
3.4%
방 156
 
3.2%
학 143
 
2.9%
Other values (119) 2309
47.0%
Common
ValueCountFrequency (%)
1 180
18.0%
2 175
17.5%
) 109
10.9%
( 109
10.9%
3 108
10.8%
4 101
10.1%
5 59
 
5.9%
_ 58
 
5.8%
30
 
3.0%
# 30
 
3.0%
Other values (6) 43
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4910
83.1%
ASCII 1002
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 706
 
14.4%
창 329
 
6.7%
도 303
 
6.2%
봉 280
 
5.7%
문 177
 
3.6%
쌍 172
 
3.5%
터 169
 
3.4%
센 166
 
3.4%
방 156
 
3.2%
학 143
 
2.9%
Other values (119) 2309
47.0%
ASCII
ValueCountFrequency (%)
1 180
18.0%
2 175
17.5%
) 109
10.9%
( 109
10.9%
3 108
10.8%
4 101
10.1%
5 59
 
5.9%
_ 58
 
5.8%
30
 
3.0%
# 30
 
3.0%
Other values (6) 43
 
4.3%

도로명주소
Text

MISSING 

Distinct421
Distinct (%)43.0%
Missing12
Missing (%)1.2%
Memory size7.9 KiB
2024-05-18T14:46:04.136348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length33
Mean length19.207566
Min length3

Characters and Unicode

Total characters18785
Distinct characters310
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 (%)33.4%

Sample

1st row도봉로
2nd row도봉로
3rd row방학동 720
4th row도봉로
5th row도봉로
ValueCountFrequency (%)
도봉구 667
 
18.0%
서울특별시 232
 
6.2%
마들로 178
 
4.8%
도봉구청 91
 
2.5%
656 89
 
2.4%
주민센터 83
 
2.2%
시루봉로 58
 
1.6%
도봉로 57
 
1.5%
노해로 43
 
1.2%
창동 42
 
1.1%
Other values (758) 2173
58.5%
2024-05-18T14:46:05.450954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2736
 
14.6%
봉 1104
 
5.9%
도 1078
 
5.7%
로 830
 
4.4%
구 805
 
4.3%
1 795
 
4.2%
6 595
 
3.2%
3 508
 
2.7%
2 503
 
2.7%
길 482
 
2.6%
Other values (300) 9349
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11049
58.8%
Decimal Number 4030
 
21.5%
Space Separator 2736
 
14.6%
Close Punctuation 330
 
1.8%
Open Punctuation 329
 
1.8%
Dash Punctuation 235
 
1.3%
Other Punctuation 31
 
0.2%
Uppercase Letter 24
 
0.1%
Connector Punctuation 14
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 1104
 
10.0%
도 1078
 
9.8%
로 830
 
7.5%
구 805
 
7.3%
길 482
 
4.4%
시 342
 
3.1%
동 332
 
3.0%
서 281
 
2.5%
울 245
 
2.2%
별 239
 
2.2%
Other values (271) 5311
48.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
20.8%
C 4
16.7%
S 3
12.5%
A 3
12.5%
G 2
 
8.3%
P 2
 
8.3%
B 1
 
4.2%
I 1
 
4.2%
U 1
 
4.2%
V 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 795
19.7%
6 595
14.8%
3 508
12.6%
2 503
12.5%
5 423
10.5%
4 304
 
7.5%
9 252
 
6.3%
7 228
 
5.7%
0 212
 
5.3%
8 210
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 27
87.1%
. 4
 
12.9%
Space Separator
ValueCountFrequency (%)
2736
100.0%
Close Punctuation
ValueCountFrequency (%)
) 330
100.0%
Open Punctuation
ValueCountFrequency (%)
( 329
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11049
58.8%
Common 7712
41.1%
Latin 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 1104
 
10.0%
도 1078
 
9.8%
로 830
 
7.5%
구 805
 
7.3%
길 482
 
4.4%
시 342
 
3.1%
동 332
 
3.0%
서 281
 
2.5%
울 245
 
2.2%
별 239
 
2.2%
Other values (271) 5311
48.1%
Common
ValueCountFrequency (%)
2736
35.5%
1 795
 
10.3%
6 595
 
7.7%
3 508
 
6.6%
2 503
 
6.5%
5 423
 
5.5%
) 330
 
4.3%
( 329
 
4.3%
4 304
 
3.9%
9 252
 
3.3%
Other values (8) 937
 
12.1%
Latin
ValueCountFrequency (%)
T 5
20.8%
C 4
16.7%
S 3
12.5%
A 3
12.5%
G 2
 
8.3%
P 2
 
8.3%
B 1
 
4.2%
I 1
 
4.2%
U 1
 
4.2%
V 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11049
58.8%
ASCII 7736
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2736
35.4%
1 795
 
10.3%
6 595
 
7.7%
3 508
 
6.6%
2 503
 
6.5%
5 423
 
5.5%
) 330
 
4.3%
( 329
 
4.3%
4 304
 
3.9%
9 252
 
3.3%
Other values (19) 961
 
12.4%
Hangul
ValueCountFrequency (%)
봉 1104
 
10.0%
도 1078
 
9.8%
로 830
 
7.5%
구 805
 
7.3%
길 482
 
4.4%
시 342
 
3.1%
동 332
 
3.0%
서 281
 
2.5%
울 245
 
2.2%
별 239
 
2.2%
Other values (271) 5311
48.1%

상세주소
Text

Distinct799
Distinct (%)81.3%
Missing7
Missing (%)0.7%
Memory size7.9 KiB
2024-05-18T14:46:06.442065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length20
Mean length8.180061
Min length1

Characters and Unicode

Total characters8041
Distinct characters307
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique726 ?
Unique (%)73.9%

Sample

1st row10-013
2nd row10-014
3rd row10-133
4th row10-011
5th row10-012
ValueCountFrequency (%)
2층 47
 
2.9%
중앙센터 43
 
2.7%
3층 41
 
2.5%
창동 39
 
2.4%
1층 37
 
2.3%
복도 34
 
2.1%
가로등 31
 
1.9%
4층 28
 
1.7%
방학동 27
 
1.7%
도깨비시장 21
 
1.3%
Other values (740) 1272
78.5%
2024-05-18T14:46:08.334250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
637
 
7.9%
1 593
 
7.4%
0 348
 
4.3%
2 280
 
3.5%
층 248
 
3.1%
3 241
 
3.0%
) 232
 
2.9%
( 232
 
2.9%
4 213
 
2.6%
옥 171
 
2.1%
Other values (297) 4846
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4307
53.6%
Decimal Number 2091
26.0%
Space Separator 637
 
7.9%
Uppercase Letter 351
 
4.4%
Close Punctuation 232
 
2.9%
Open Punctuation 232
 
2.9%
Connector Punctuation 87
 
1.1%
Dash Punctuation 74
 
0.9%
Lowercase Letter 19
 
0.2%
Other Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 248
 
5.8%
옥 171
 
4.0%
실 143
 
3.3%
도 132
 
3.1%
동 117
 
2.7%
장 116
 
2.7%
내 104
 
2.4%
창 101
 
2.3%
터 99
 
2.3%
시 95
 
2.2%
Other values (254) 2981
69.2%
Uppercase Letter
ValueCountFrequency (%)
C 136
38.7%
P 87
24.8%
F 42
 
12.0%
S 41
 
11.7%
I 19
 
5.4%
B 10
 
2.8%
G 5
 
1.4%
T 2
 
0.6%
M 2
 
0.6%
R 2
 
0.6%
Other values (4) 5
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 593
28.4%
0 348
16.6%
2 280
13.4%
3 241
11.5%
4 213
 
10.2%
5 97
 
4.6%
6 92
 
4.4%
7 88
 
4.2%
8 72
 
3.4%
9 67
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
c 5
26.3%
o 4
21.1%
s 2
 
10.5%
m 2
 
10.5%
u 1
 
5.3%
r 1
 
5.3%
e 1
 
5.3%
p 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 7
63.6%
# 2
 
18.2%
/ 1
 
9.1%
? 1
 
9.1%
Space Separator
ValueCountFrequency (%)
637
100.0%
Close Punctuation
ValueCountFrequency (%)
) 232
100.0%
Open Punctuation
ValueCountFrequency (%)
( 232
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4306
53.6%
Common 3364
41.8%
Latin 370
 
4.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 248
 
5.8%
옥 171
 
4.0%
실 143
 
3.3%
도 132
 
3.1%
동 117
 
2.7%
장 116
 
2.7%
내 104
 
2.4%
창 101
 
2.3%
터 99
 
2.3%
시 95
 
2.2%
Other values (253) 2980
69.2%
Latin
ValueCountFrequency (%)
C 136
36.8%
P 87
23.5%
F 42
 
11.4%
S 41
 
11.1%
I 19
 
5.1%
B 10
 
2.7%
G 5
 
1.4%
c 5
 
1.4%
o 4
 
1.1%
T 2
 
0.5%
Other values (14) 19
 
5.1%
Common
ValueCountFrequency (%)
637
18.9%
1 593
17.6%
0 348
10.3%
2 280
8.3%
3 241
 
7.2%
) 232
 
6.9%
( 232
 
6.9%
4 213
 
6.3%
5 97
 
2.9%
6 92
 
2.7%
Other values (9) 399
11.9%
Han
ValueCountFrequency (%)
女 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4306
53.6%
ASCII 3734
46.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
637
17.1%
1 593
15.9%
0 348
9.3%
2 280
 
7.5%
3 241
 
6.5%
) 232
 
6.2%
( 232
 
6.2%
4 213
 
5.7%
C 136
 
3.6%
5 97
 
2.6%
Other values (33) 725
19.4%
Hangul
ValueCountFrequency (%)
층 248
 
5.8%
옥 171
 
4.0%
실 143
 
3.3%
도 132
 
3.1%
동 117
 
2.7%
장 116
 
2.7%
내 104
 
2.4%
창 101
 
2.3%
터 99
 
2.3%
시 95
 
2.2%
Other values (253) 2980
69.2%
CJK
ValueCountFrequency (%)
女 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
811 
2층
 
42
1층
 
40
3층
 
37
4층
 
22
Other values (6)
 
38

Length

Max length4
Median length4
Mean length3.6888889
Min length2

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> 811
81.9%
2층 42
 
4.2%
1층 40
 
4.0%
3층 37
 
3.7%
4층 22
 
2.2%
지하1층 20
 
2.0%
B1층 8
 
0.8%
5층 6
 
0.6%
6층 2
 
0.2%
B2층 1
 
0.1%

Length

2024-05-18T14:46:09.132576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 811
81.9%
2층 42
 
4.2%
1층 40
 
4.0%
3층 37
 
3.7%
4층 22
 
2.2%
지하1층 20
 
2.0%
b1층 8
 
0.8%
5층 6
 
0.6%
6층 2
 
0.2%
b2층 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
3. 공원(하천)
167 
1. 주요거리
166 
7-2-3. 공공 - 동주민센터
101 
4. 문화관광
98 
7-2-1. 공공 - 구청사 및 별관
91 
Other values (13)
367 

Length

Max length21
Median length20
Mean length11.471717
Min length7

Unique

Unique3 ?
Unique (%)0.3%

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) 167
16.9%
1. 주요거리 166
16.8%
7-2-3. 공공 - 동주민센터 101
10.2%
4. 문화관광 98
9.9%
7-2-1. 공공 - 구청사 및 별관 91
9.2%
2. 전통시장 76
7.7%
6-2. 복지 - 노인 71
7.2%
6-1. 복지 - 사회 60
 
6.1%
5-1. 버스정류소(국비) 46
 
4.6%
6-4. 복지 - 아동청소년 29
 
2.9%
Other values (8) 85
8.6%

Length

2024-05-18T14:46:09.991447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
424
 
13.9%
공공 232
 
7.6%
복지 192
 
6.3%
3 167
 
5.5%
공원(하천 167
 
5.5%
1 166
 
5.4%
주요거리 166
 
5.4%
및 111
 
3.6%
7-2-3 101
 
3.3%
동주민센터 101
 
3.3%
Other values (32) 1223
40.1%

설치기관
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
자치구
300 
자치구에스넷1차
241 
서울시(AP)
172 
디지털뉴딜(KT)
166 
디지털뉴딜(LG U+)
47 
Other values (3)
64 

Length

Max length12
Median length9
Mean length6.7272727
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 300
30.3%
자치구에스넷1차 241
24.3%
서울시(AP) 172
17.4%
디지털뉴딜(KT) 166
16.8%
디지털뉴딜(LG U+) 47
 
4.7%
버스정류소(국비) 46
 
4.6%
버스정류소(시비) 12
 
1.2%
서울시(공유기) 6
 
0.6%

Length

2024-05-18T14:46:10.570265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:46:10.946815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 300
28.9%
자치구에스넷1차 241
23.2%
서울시(ap 172
16.6%
디지털뉴딜(kt 166
16.0%
디지털뉴딜(lg 47
 
4.5%
u 47
 
4.5%
버스정류소(국비 46
 
4.4%
버스정류소(시비 12
 
1.2%
서울시(공유기 6
 
0.6%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
공공Wifi
679 
공공WiFi
97 
과기부WiFi(복지시설)
95 
과기부WiFi(핫플레이스)
73 
과기부WiFi
 
46

Length

Max length14
Median length6
Mean length7.3080808
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공Wifi 679
68.6%
공공WiFi 97
 
9.8%
과기부WiFi(복지시설) 95
 
9.6%
과기부WiFi(핫플레이스) 73
 
7.4%
과기부WiFi 46
 
4.6%

Length

2024-05-18T14:46:11.746736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:46:12.260066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 776
78.4%
과기부wifi(복지시설 95
 
9.6%
과기부wifi(핫플레이스 73
 
7.4%
과기부wifi 46
 
4.6%

망종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
자가망U-무선망
624 
인터넷망_뉴딜용
213 
임대망
118 
자가망_U무선망
 
20
<NA>
 
12

Length

Max length9
Median length8
Mean length7.3585859
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가망U-무선망 624
63.0%
인터넷망_뉴딜용 213
 
21.5%
임대망 118
 
11.9%
자가망_U무선망 20
 
2.0%
<NA> 12
 
1.2%
인터넷망_기관자체 3
 
0.3%

Length

2024-05-18T14:46:12.745329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:46:13.154732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망u-무선망 624
63.0%
인터넷망_뉴딜용 213
 
21.5%
임대망 118
 
11.9%
자가망_u무선망 20
 
2.0%
na 12
 
1.2%
인터넷망_기관자체 3
 
0.3%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.8596
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-18T14:46:13.571247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2018
Q12020
median2021
Q32022
95-th percentile2023
Maximum2023
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3931378
Coefficient of variation (CV)0.00068937883
Kurtosis-2.4442426 × 10-6
Mean2020.8596
Median Absolute Deviation (MAD)1
Skewness-0.53724593
Sum2000651
Variance1.940833
MonotonicityNot monotonic
2024-05-18T14:46:14.089844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020 327
33.0%
2022 311
31.4%
2021 149
15.1%
2023 93
 
9.4%
2018 48
 
4.8%
2019 42
 
4.2%
2017 19
 
1.9%
2016 1
 
0.1%
ValueCountFrequency (%)
2016 1
 
0.1%
2017 19
 
1.9%
2018 48
 
4.8%
2019 42
 
4.2%
2020 327
33.0%
2021 149
15.1%
2022 311
31.4%
2023 93
 
9.4%
ValueCountFrequency (%)
2023 93
 
9.4%
2022 311
31.4%
2021 149
15.1%
2020 327
33.0%
2019 42
 
4.2%
2018 48
 
4.8%
2017 19
 
1.9%
2016 1
 
0.1%

실내외구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
실내
525 
실외
464 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0020202
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
실내 525
53.0%
실외 464
46.9%
<NA> 1
 
0.1%

Length

2024-05-18T14:46:14.615535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:46:15.026902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 525
53.0%
실외 464
46.9%
na 1
 
0.1%

wifi접속환경
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing990
Missing (%)100.0%
Memory size8.8 KiB

X좌표
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct443
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.746796
Minimum0
Maximum37.693707
Zeros24
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-18T14:46:15.299512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.638073
Q137.648701
median37.658231
Q337.66916
95-th percentile37.683991
Maximum37.693707
Range37.693707
Interquartile range (IQR)0.02045875

Descriptive statistics

Standard deviation5.7950494
Coefficient of variation (CV)0.15770217
Kurtosis36.464385
Mean36.746796
Median Absolute Deviation (MAD)0.01076
Skewness-6.1960066
Sum36379.328
Variance33.582598
MonotonicityNot monotonic
2024-05-18T14:46:15.906526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.66916 76
 
7.7%
37.658115 40
 
4.0%
0.0 24
 
2.4%
37.66931 20
 
2.0%
37.669674 20
 
2.0%
37.653984 20
 
2.0%
37.657986 19
 
1.9%
37.644672 15
 
1.5%
37.681355 14
 
1.4%
37.656418 13
 
1.3%
Other values (433) 729
73.6%
ValueCountFrequency (%)
0.0 24
2.4%
37.567085 1
 
0.1%
37.580406 1
 
0.1%
37.63198 1
 
0.1%
37.63324 1
 
0.1%
37.63339 1
 
0.1%
37.634544 1
 
0.1%
37.634804 1
 
0.1%
37.63581 1
 
0.1%
37.636093 1
 
0.1%
ValueCountFrequency (%)
37.693707 1
 
0.1%
37.691822 3
0.3%
37.691345 2
0.2%
37.690468 1
 
0.1%
37.69035 1
 
0.1%
37.690033 1
 
0.1%
37.689503 3
0.3%
37.689194 2
0.2%
37.688858 2
0.2%
37.688812 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct419
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.96033
Minimum0
Maximum127.48852
Zeros24
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-18T14:46:16.600006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile127.01582
Q1127.03369
median127.04102
Q3127.04668
95-th percentile127.0507
Maximum127.48852
Range127.48852
Interquartile range (IQR)0.01299375

Descriptive statistics

Standard deviation19.548768
Coefficient of variation (CV)0.15770181
Kurtosis36.464747
Mean123.96033
Median Absolute Deviation (MAD)0.006043
Skewness-6.1960515
Sum122720.73
Variance382.15434
MonotonicityNot monotonic
2024-05-18T14:46:17.255961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.047066 76
 
7.7%
127.050705 40
 
4.0%
0.0 24
 
2.4%
127.04653 22
 
2.2%
127.03863 21
 
2.1%
127.03264 20
 
2.0%
127.0388 19
 
1.9%
127.04397 15
 
1.5%
127.05038 14
 
1.4%
127.02796 14
 
1.4%
Other values (409) 725
73.2%
ValueCountFrequency (%)
0.0 24
2.4%
127.01268 1
 
0.1%
127.01363 1
 
0.1%
127.01368 1
 
0.1%
127.014244 1
 
0.1%
127.01429 1
 
0.1%
127.0143 1
 
0.1%
127.0144 4
 
0.4%
127.01446 1
 
0.1%
127.014595 1
 
0.1%
ValueCountFrequency (%)
127.48852 1
 
0.1%
127.05392 1
 
0.1%
127.05305 1
 
0.1%
127.05225 1
 
0.1%
127.0521 1
 
0.1%
127.05155 7
0.7%
127.05147 1
 
0.1%
127.05139 1
 
0.1%
127.051 1
 
0.1%
127.05099 2
 
0.2%

작업일자
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2024-05-18 11:12:53.0
443 
2024-05-18 11:13:00.0
189 
2024-05-18 11:13:03.0
116 
2024-05-18 11:12:58.0
51 
2024-05-18 11:12:59.0
51 
Other values (7)
140 

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 11:12:53.0 443
44.7%
2024-05-18 11:13:00.0 189
19.1%
2024-05-18 11:13:03.0 116
 
11.7%
2024-05-18 11:12:58.0 51
 
5.2%
2024-05-18 11:12:59.0 51
 
5.2%
2024-05-18 11:13:02.0 50
 
5.1%
2024-05-18 11:13:05.0 31
 
3.1%
2024-05-18 11:12:52.0 26
 
2.6%
2024-05-18 11:13:04.0 16
 
1.6%
2024-05-18 11:12:57.0 7
 
0.7%
Other values (2) 10
 
1.0%

Length

2024-05-18T14:46:17.774417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-18 990
50.0%
11:12:53.0 443
22.4%
11:13:00.0 189
 
9.5%
11:13:03.0 116
 
5.9%
11:12:58.0 51
 
2.6%
11:12:59.0 51
 
2.6%
11:13:02.0 50
 
2.5%
11:13:05.0 31
 
1.6%
11:12:52.0 26
 
1.3%
11:13:04.0 16
 
0.8%
Other values (3) 17
 
0.9%

Interactions

2024-05-18T14:45:56.487875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:54.234477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:55.241695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:56.986459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:54.569995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:55.622792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:57.363327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:54.930309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:56.041825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:46:18.049119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.5170.278NaN0.0000.7170.000NaNNaN0.355
설치유형0.5171.0000.9380.9550.8670.8361.0000.4510.4510.923
설치기관0.2780.9381.0000.8890.7790.7570.8980.2990.2990.948
서비스구분NaN0.9550.8891.0000.9250.5930.4050.0700.0700.883
망종류0.0000.8670.7790.9251.0000.5920.1480.0830.0830.900
설치년도0.7170.8360.7570.5930.5921.0000.3920.1920.1920.759
실내외구분0.0001.0000.8980.4050.1480.3921.0000.2250.2250.725
X좌표NaN0.4510.2990.0700.0830.1920.2251.0000.9990.163
Y좌표NaN0.4510.2990.0700.0830.1920.2250.9991.0000.163
작업일자0.3550.9230.9480.8830.9000.7590.7250.1630.1631.000
2024-05-18T14:46:18.542286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형작업일자실내외구분망종류서비스구분설치기관
설치위치(층)1.0000.2900.2150.0000.0001.0000.207
설치유형0.2901.0000.6280.9800.6740.8620.764
작업일자0.2150.6281.0000.5720.5870.7420.772
실내외구분0.0000.9800.5721.0000.1800.4930.723
망종류0.0000.6740.5870.1801.0000.6200.650
서비스구분1.0000.8620.7420.4930.6201.0000.806
설치기관0.2070.7640.7720.7230.6500.8061.000
2024-05-18T14:46:18.931049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분작업일자
설치년도1.000-0.0860.0030.4770.5260.4960.4350.5170.4190.464
X좌표-0.0861.0000.3691.0000.3530.2240.0860.1010.1450.126
Y좌표0.0030.3691.0001.0000.3530.2240.0860.1010.1450.126
설치위치(층)0.4771.0001.0001.0000.2900.2071.0000.0000.0000.215
설치유형0.5260.3530.3530.2901.0000.7640.8620.6740.9800.628
설치기관0.4960.2240.2240.2070.7641.0000.8060.6500.7230.772
서비스구분0.4350.0860.0861.0000.8620.8061.0000.6200.4930.742
망종류0.5170.1010.1010.0000.6740.6500.6201.0000.1800.587
실내외구분0.4190.1450.1450.0000.9800.7230.4930.1801.0000.572
작업일자0.4640.1260.1260.2150.6280.7720.7420.5870.5721.000

Missing values

2024-05-18T14:45:58.270230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:45:58.954959image/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.
2024-05-18T14:45:59.358102image/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
0BS100468도봉구버스정류소_도봉구민회관도봉로10-013<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.65456127.038172024-05-18 11:12:52.0
1BS100469도봉구버스정류소_도봉구민회관도봉로10-014<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.65397127.037982024-05-18 11:12:52.0
2BS100470도봉구버스정류소_도봉구청방학동 72010-133<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.668957127.046332024-05-18 11:12:52.0
3BS100471도봉구버스정류소_도봉보건소도봉로10-011<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.658936127.0407642024-05-18 11:12:52.0
4BS100472도봉구버스정류소_도봉보건소.북한산아이파크아파트도봉로10-012<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.658203127.040522024-05-18 11:12:52.0
5BS100473도봉구버스정류소_도봉산역도봉로10-001<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.689194127.045432024-05-18 11:12:52.0
6BS100474도봉구버스정류소_도봉산역도봉로10-002<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.68857127.0458152024-05-18 11:12:52.0
7BS100475도봉구버스정류소_도봉소방서.방학남부역도봉로10-009<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.666332127.0429842024-05-18 11:12:52.0
8BS100476도봉구버스정류소_도봉소방서.방학남부역도봉로10-010<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.665676127.043052024-05-18 11:12:52.0
9BS100477도봉구버스정류소_도봉역도봉동 89-16010-156<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.68031127.0465242024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
980서울4차-6717도봉구유쾌한집1호서울특별시 도봉구 도봉산3길 12-14, 201호2F_201 티비_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
981서울4차-6718도봉구유쾌한집1호서울특별시 도봉구 도봉산3길 12-14, 202호3F_티비다이 천장_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
982서울4차-6719도봉구유쾌한집2호서울특별시 도봉구 도봉산3길 12-14, 203호4F_402_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
983서울4차-6720도봉구유쾌한집2호서울특별시 도봉구 도봉산3길 12-14, 303호3F_301_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
984서울4차-6721도봉구유쾌한집3호서울특별시 도봉구 도봉산3길 12-14, 301호5F_티비다이_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
985서울4차-6722도봉구유쾌한집3호서울특별시 도봉구 도봉산3길 12-14, 302호5F_티비다이_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
986서울4차-6723도봉구유쾌한집4호서울특별시 도봉구 도봉산3길 12-14, 401호4F_401호_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
987서울4차-6724도봉구유쾌한집4호서울특별시 도봉구 도봉산3길 12-14, 402호4F_401호_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
988서울4차-6725도봉구유쾌한집4호서울특별시 도봉구 도봉산3길 12-14, 501호2F_203호_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0
989서울4차-6726도봉구유쾌한집4호서울특별시 도봉구 도봉산3길 12-14, 502호2F_202호_1<NA>6-3. 복지 - 장애인디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.68709127.043322024-05-18 11:13:05.0