Overview

Dataset statistics

Number of variables16
Number of observations667
Missing cells21
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory85.5 KiB
Average record size in memory131.2 B

Variable types

Text4
Categorical8
Numeric3
DateTime1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-20897/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치기관 and 3 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 3 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with 설치유형 and 1 other fieldsHigh correlation
설치위치(층) is highly imbalanced (51.0%)Imbalance
wifi접속환경 is highly imbalanced (87.9%)Imbalance
도로명주소 has 9 (1.3%) missing valuesMissing
상세주소 has 12 (1.8%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-17 21:58:03.169416
Analysis finished2024-05-17 21:58:08.865238
Duration5.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct667
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-18T06:58:09.329691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.2593703
Min length7

Characters and Unicode

Total characters5509
Distinct characters22
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

Unique667 ?
Unique (%)100.0%

Sample

1st rowARI00090
2nd rowARI00091
3rd rowARI00092
4th rowARI00093
5th rowARI00094
ValueCountFrequency (%)
ari00090 1
 
0.1%
서울-2710-1 1
 
0.1%
서울-2711 1
 
0.1%
서울-2711-1 1
 
0.1%
서울-2711-2 1
 
0.1%
서울-2712 1
 
0.1%
서울-2713 1
 
0.1%
서울-2713-1 1
 
0.1%
서울-2713-2 1
 
0.1%
서울-2714 1
 
0.1%
Other values (657) 657
98.5%
2024-05-18T06:58:10.250687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1090
19.8%
1 731
13.3%
- 439
 
8.0%
2 359
 
6.5%
울 311
 
5.6%
서 311
 
5.6%
4 275
 
5.0%
B 274
 
5.0%
3 266
 
4.8%
G 227
 
4.1%
Other values (12) 1226
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3599
65.3%
Uppercase Letter 739
 
13.4%
Other Letter 732
 
13.3%
Dash Punctuation 439
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1090
30.3%
1 731
20.3%
2 359
 
10.0%
4 275
 
7.6%
3 266
 
7.4%
5 206
 
5.7%
6 198
 
5.5%
7 189
 
5.3%
9 172
 
4.8%
8 113
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 274
37.1%
G 227
30.7%
W 63
 
8.5%
F 63
 
8.5%
S 55
 
7.4%
R 19
 
2.6%
I 19
 
2.6%
A 19
 
2.6%
Other Letter
ValueCountFrequency (%)
울 311
42.5%
서 311
42.5%
차 110
 
15.0%
Dash Punctuation
ValueCountFrequency (%)
- 439
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4038
73.3%
Latin 739
 
13.4%
Hangul 732
 
13.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1090
27.0%
1 731
18.1%
- 439
10.9%
2 359
 
8.9%
4 275
 
6.8%
3 266
 
6.6%
5 206
 
5.1%
6 198
 
4.9%
7 189
 
4.7%
9 172
 
4.3%
Latin
ValueCountFrequency (%)
B 274
37.1%
G 227
30.7%
W 63
 
8.5%
F 63
 
8.5%
S 55
 
7.4%
R 19
 
2.6%
I 19
 
2.6%
A 19
 
2.6%
Hangul
ValueCountFrequency (%)
울 311
42.5%
서 311
42.5%
차 110
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4777
86.7%
Hangul 732
 
13.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1090
22.8%
1 731
15.3%
- 439
9.2%
2 359
 
7.5%
4 275
 
5.8%
B 274
 
5.7%
3 266
 
5.6%
G 227
 
4.8%
5 206
 
4.3%
6 198
 
4.1%
Other values (9) 712
14.9%
Hangul
ValueCountFrequency (%)
울 311
42.5%
서 311
42.5%
차 110
 
15.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
강북구
667 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강북구 667
100.0%

Length

2024-05-18T06:58:10.564078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:10.761599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강북구 667
100.0%

와이파이명
Text

Distinct194
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-18T06:58:11.046145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length8.4947526
Min length2

Characters and Unicode

Total characters5666
Distinct characters252
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

Unique96 ?
Unique (%)14.4%

Sample

1st row북부수도사업소
2nd row북부수도사업소
3rd row북부수도사업소
4th row북부수도사업소
5th row북부수도사업소
ValueCountFrequency (%)
강북구청 41
 
5.8%
수유역 27
 
3.8%
번동2단지종합사회복지관 26
 
3.7%
강북노인종합복지관 25
 
3.5%
시립강북청소년센터 21
 
3.0%
강북장애인종합복지관 21
 
3.0%
북부수도사업소 19
 
2.7%
우이천 19
 
2.7%
강북구육아종합지원센터 17
 
2.4%
종합사회복지관 12
 
1.7%
Other values (197) 483
67.9%
2024-05-18T06:58:12.140536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
북 294
 
5.2%
강 256
 
4.5%
지 217
 
3.8%
터 177
 
3.1%
센 175
 
3.1%
동 171
 
3.0%
합 144
 
2.5%
관 142
 
2.5%
종 128
 
2.3%
구 127
 
2.2%
Other values (242) 3835
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5423
95.7%
Decimal Number 99
 
1.7%
Connector Punctuation 47
 
0.8%
Space Separator 44
 
0.8%
Other Punctuation 16
 
0.3%
Close Punctuation 12
 
0.2%
Open Punctuation 12
 
0.2%
Dash Punctuation 7
 
0.1%
Uppercase Letter 5
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 294
 
5.4%
강 256
 
4.7%
지 217
 
4.0%
터 177
 
3.3%
센 175
 
3.2%
동 171
 
3.2%
합 144
 
2.7%
관 142
 
2.6%
종 128
 
2.4%
구 127
 
2.3%
Other values (222) 3592
66.2%
Decimal Number
ValueCountFrequency (%)
2 35
35.4%
3 23
23.2%
1 15
15.2%
4 9
 
9.1%
5 7
 
7.1%
9 5
 
5.1%
8 3
 
3.0%
7 1
 
1.0%
0 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
K 2
40.0%
U 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 15
93.8%
? 1
 
6.2%
Connector Punctuation
ValueCountFrequency (%)
_ 47
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5423
95.7%
Common 237
 
4.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 294
 
5.4%
강 256
 
4.7%
지 217
 
4.0%
터 177
 
3.3%
센 175
 
3.2%
동 171
 
3.2%
합 144
 
2.7%
관 142
 
2.6%
종 128
 
2.4%
구 127
 
2.3%
Other values (222) 3592
66.2%
Common
ValueCountFrequency (%)
_ 47
19.8%
44
18.6%
2 35
14.8%
3 23
9.7%
. 15
 
6.3%
1 15
 
6.3%
) 12
 
5.1%
( 12
 
5.1%
4 9
 
3.8%
- 7
 
3.0%
Other values (6) 18
 
7.6%
Latin
ValueCountFrequency (%)
S 2
33.3%
K 2
33.3%
e 1
16.7%
U 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5423
95.7%
ASCII 243
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
북 294
 
5.4%
강 256
 
4.7%
지 217
 
4.0%
터 177
 
3.3%
센 175
 
3.2%
동 171
 
3.2%
합 144
 
2.7%
관 142
 
2.6%
종 128
 
2.4%
구 127
 
2.3%
Other values (222) 3592
66.2%
ASCII
ValueCountFrequency (%)
_ 47
19.3%
44
18.1%
2 35
14.4%
3 23
9.5%
. 15
 
6.2%
1 15
 
6.2%
) 12
 
4.9%
( 12
 
4.9%
4 9
 
3.7%
- 7
 
2.9%
Other values (10) 24
9.9%

도로명주소
Text

MISSING 

Distinct269
Distinct (%)40.9%
Missing9
Missing (%)1.3%
Memory size5.3 KiB
2024-05-18T06:58:12.702150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length14.753799
Min length5

Characters and Unicode

Total characters9708
Distinct characters146
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

Unique174 ?
Unique (%)26.4%

Sample

1st row한천로 935
2nd row한천로 935
3rd row한천로 935
4th row한천로 935
5th row한천로 935
ValueCountFrequency (%)
강북구 310
 
15.0%
서울특별시 286
 
13.8%
수유동 110
 
5.3%
번동 76
 
3.7%
미아동 76
 
3.7%
한천로 61
 
2.9%
오현로 51
 
2.5%
192-59 39
 
1.9%
인수봉로 34
 
1.6%
24 27
 
1.3%
Other values (360) 1002
48.4%
2024-05-18T06:58:13.851716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1420
 
14.6%
1 543
 
5.6%
2 481
 
5.0%
로 361
 
3.7%
동 340
 
3.5%
- 315
 
3.2%
강 313
 
3.2%
구 312
 
3.2%
북 311
 
3.2%
시 311
 
3.2%
Other values (136) 5001
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4878
50.2%
Decimal Number 2939
30.3%
Space Separator 1420
 
14.6%
Dash Punctuation 315
 
3.2%
Other Punctuation 67
 
0.7%
Close Punctuation 35
 
0.4%
Open Punctuation 35
 
0.4%
Math Symbol 7
 
0.1%
Uppercase Letter 6
 
0.1%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 361
 
7.4%
동 340
 
7.0%
강 313
 
6.4%
구 312
 
6.4%
북 311
 
6.4%
시 311
 
6.4%
서 310
 
6.4%
울 310
 
6.4%
특 286
 
5.9%
별 286
 
5.9%
Other values (108) 1738
35.6%
Decimal Number
ValueCountFrequency (%)
1 543
18.5%
2 481
16.4%
3 303
10.3%
9 303
10.3%
0 268
9.1%
4 264
9.0%
5 242
8.2%
6 193
 
6.6%
8 189
 
6.4%
7 153
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 37
55.2%
. 23
34.3%
/ 5
 
7.5%
& 1
 
1.5%
; 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
t 1
16.7%
m 1
16.7%
i 1
16.7%
o 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
F 4
66.7%
S 1
 
16.7%
K 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 315
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4878
50.2%
Common 4818
49.6%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 361
 
7.4%
동 340
 
7.0%
강 313
 
6.4%
구 312
 
6.4%
북 311
 
6.4%
시 311
 
6.4%
서 310
 
6.4%
울 310
 
6.4%
특 286
 
5.9%
별 286
 
5.9%
Other values (108) 1738
35.6%
Common
ValueCountFrequency (%)
1420
29.5%
1 543
 
11.3%
2 481
 
10.0%
- 315
 
6.5%
3 303
 
6.3%
9 303
 
6.3%
0 268
 
5.6%
4 264
 
5.5%
5 242
 
5.0%
6 193
 
4.0%
Other values (10) 486
 
10.1%
Latin
ValueCountFrequency (%)
F 4
33.3%
d 2
16.7%
t 1
 
8.3%
S 1
 
8.3%
m 1
 
8.3%
i 1
 
8.3%
o 1
 
8.3%
K 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4878
50.2%
ASCII 4830
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1420
29.4%
1 543
 
11.2%
2 481
 
10.0%
- 315
 
6.5%
3 303
 
6.3%
9 303
 
6.3%
0 268
 
5.5%
4 264
 
5.5%
5 242
 
5.0%
6 193
 
4.0%
Other values (18) 498
 
10.3%
Hangul
ValueCountFrequency (%)
로 361
 
7.4%
동 340
 
7.0%
강 313
 
6.4%
구 312
 
6.4%
북 311
 
6.4%
시 311
 
6.4%
서 310
 
6.4%
울 310
 
6.4%
특 286
 
5.9%
별 286
 
5.9%
Other values (108) 1738
35.6%

상세주소
Text

MISSING 

Distinct497
Distinct (%)75.9%
Missing12
Missing (%)1.8%
Memory size5.3 KiB
2024-05-18T06:58:14.395004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length29
Mean length11.090076
Min length2

Characters and Unicode

Total characters7264
Distinct characters323
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique425 ?
Unique (%)64.9%

Sample

1st row본관 1F
2nd row본관 1F
3rd row본관 1F
4th row본관 2F
5th row본관 2F
ValueCountFrequency (%)
cctv 61
 
4.4%
옥내1 51
 
3.7%
1f 40
 
2.9%
종합사회복지관 35
 
2.5%
복도 31
 
2.2%
2f 29
 
2.1%
앞 28
 
2.0%
수유역인근(먹자골목 27
 
2.0%
옥내2 27
 
2.0%
민원실 25
 
1.8%
Other values (476) 1028
74.4%
2024-05-18T06:58:15.108022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
728
 
10.0%
1 320
 
4.4%
) 284
 
3.9%
( 283
 
3.9%
2 240
 
3.3%
F 204
 
2.8%
옥 201
 
2.8%
_ 149
 
2.1%
실 145
 
2.0%
C 137
 
1.9%
Other values (313) 4573
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4002
55.1%
Decimal Number 1159
 
16.0%
Space Separator 728
 
10.0%
Uppercase Letter 526
 
7.2%
Close Punctuation 284
 
3.9%
Open Punctuation 283
 
3.9%
Connector Punctuation 149
 
2.1%
Dash Punctuation 100
 
1.4%
Other Punctuation 22
 
0.3%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 201
 
5.0%
실 145
 
3.6%
내 134
 
3.3%
지 125
 
3.1%
관 115
 
2.9%
강 103
 
2.6%
층 96
 
2.4%
사 87
 
2.2%
복 86
 
2.1%
외 84
 
2.1%
Other values (277) 2826
70.6%
Uppercase Letter
ValueCountFrequency (%)
F 204
38.8%
C 137
26.0%
T 69
 
13.1%
V 69
 
13.1%
B 27
 
5.1%
W 4
 
0.8%
D 4
 
0.8%
G 4
 
0.8%
P 4
 
0.8%
U 1
 
0.2%
Other values (3) 3
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 320
27.6%
2 240
20.7%
3 137
11.8%
0 135
11.6%
4 84
 
7.2%
9 62
 
5.3%
5 55
 
4.7%
6 51
 
4.4%
8 47
 
4.1%
7 28
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
v 1
20.0%
t 1
20.0%
g 1
20.0%
n 1
20.0%
a 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 20
90.9%
# 2
 
9.1%
Space Separator
ValueCountFrequency (%)
728
100.0%
Close Punctuation
ValueCountFrequency (%)
) 284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 283
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4001
55.1%
Common 2731
37.6%
Latin 531
 
7.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 201
 
5.0%
실 145
 
3.6%
내 134
 
3.3%
지 125
 
3.1%
관 115
 
2.9%
강 103
 
2.6%
층 96
 
2.4%
사 87
 
2.2%
복 86
 
2.1%
외 84
 
2.1%
Other values (276) 2825
70.6%
Common
ValueCountFrequency (%)
728
26.7%
1 320
11.7%
) 284
 
10.4%
( 283
 
10.4%
2 240
 
8.8%
_ 149
 
5.5%
3 137
 
5.0%
0 135
 
4.9%
- 100
 
3.7%
4 84
 
3.1%
Other values (8) 271
 
9.9%
Latin
ValueCountFrequency (%)
F 204
38.4%
C 137
25.8%
T 69
 
13.0%
V 69
 
13.0%
B 27
 
5.1%
W 4
 
0.8%
D 4
 
0.8%
G 4
 
0.8%
P 4
 
0.8%
v 1
 
0.2%
Other values (8) 8
 
1.5%
Han
ValueCountFrequency (%)
熱 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4001
55.1%
ASCII 3262
44.9%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
728
22.3%
1 320
9.8%
) 284
 
8.7%
( 283
 
8.7%
2 240
 
7.4%
F 204
 
6.3%
_ 149
 
4.6%
C 137
 
4.2%
3 137
 
4.2%
0 135
 
4.1%
Other values (26) 645
19.8%
Hangul
ValueCountFrequency (%)
옥 201
 
5.0%
실 145
 
3.6%
내 134
 
3.3%
지 125
 
3.1%
관 115
 
2.9%
강 103
 
2.6%
층 96
 
2.4%
사 87
 
2.2%
복 86
 
2.1%
외 84
 
2.1%
Other values (276) 2825
70.6%
CJK
ValueCountFrequency (%)
熱 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct21
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
403 
1F
107 
2F
 
37
3F
 
31
4F
 
19
Other values (16)
70 

Length

Max length4
Median length4
Mean length3.2443778
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 403
60.4%
1F 107
 
16.0%
2F 37
 
5.5%
3F 31
 
4.6%
4F 19
 
2.8%
1층 15
 
2.2%
B1F 13
 
1.9%
5F 9
 
1.3%
6F 5
 
0.7%
지하1층 5
 
0.7%
Other values (11) 23
 
3.4%

Length

2024-05-18T06:58:15.579833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 403
60.4%
1f 107
 
16.0%
2f 37
 
5.5%
3f 31
 
4.6%
4f 19
 
2.8%
1층 15
 
2.2%
b1f 13
 
1.9%
5f 9
 
1.3%
6f 5
 
0.7%
지하1층 5
 
0.7%
Other values (11) 23
 
3.4%

설치유형
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
6-4. 복지 - 아동청소년
80 
3. 공원(하천)
74 
1. 주요거리
61 
7-2-1. 공공 - 구청사 및 별관
56 
6-1. 복지 - 사회
53 
Other values (14)
343 

Length

Max length21
Median length15
Mean length13.056972
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 (%)
6-4. 복지 - 아동청소년 80
12.0%
3. 공원(하천) 74
11.1%
1. 주요거리 61
9.1%
7-2-1. 공공 - 구청사 및 별관 56
8.4%
6-1. 복지 - 사회 53
7.9%
4. 문화관광 52
7.8%
6-3. 복지 - 장애인 47
7.0%
6-2. 복지 - 노인 47
7.0%
7-2-3. 공공 - 동주민센터 43
 
6.4%
5-1. 버스정류소(국비) 39
 
5.8%
Other values (9) 115
17.2%

Length

2024-05-18T06:58:15.986654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
414
17.7%
복지 235
 
10.0%
공공 179
 
7.6%
및 89
 
3.8%
6-4 80
 
3.4%
아동청소년 80
 
3.4%
3 74
 
3.2%
공원(하천 74
 
3.2%
1 61
 
2.6%
주요거리 61
 
2.6%
Other values (34) 993
42.4%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
자치구
227 
디지털뉴딜(KT)
177 
디지털뉴딜(LG U+)
134 
서울시(AP)
62 
버스정류소(국비)
39 
Other values (2)
28 

Length

Max length12
Median length9
Mean length7.3448276
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자치구 227
34.0%
디지털뉴딜(KT) 177
26.5%
디지털뉴딜(LG U+) 134
20.1%
서울시(AP) 62
 
9.3%
버스정류소(국비) 39
 
5.8%
서울시(공유기) 20
 
3.0%
버스정류소(시비) 8
 
1.2%

Length

2024-05-18T06:58:16.372798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:16.707853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 227
28.3%
디지털뉴딜(kt 177
22.1%
디지털뉴딜(lg 134
16.7%
u 134
16.7%
서울시(ap 62
 
7.7%
버스정류소(국비 39
 
4.9%
서울시(공유기 20
 
2.5%
버스정류소(시비 8
 
1.0%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
공공WiFi
390 
과기부WiFi(복지시설)
119 
과기부WiFi(핫플레이스)
82 
과기부WiFi
 
39
<NA>
 
37

Length

Max length14
Median length6
Mean length8.17991
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 390
58.5%
과기부WiFi(복지시설) 119
 
17.8%
과기부WiFi(핫플레이스) 82
 
12.3%
과기부WiFi 39
 
5.8%
<NA> 37
 
5.5%

Length

2024-05-18T06:58:17.114415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:17.441666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 390
58.5%
과기부wifi(복지시설 119
 
17.8%
과기부wifi(핫플레이스 82
 
12.3%
과기부wifi 39
 
5.8%
na 37
 
5.5%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
인터넷망_뉴딜용
311 
자가망_U무선망
240 
임대망
89 
자가망_수도사업소망
 
19
<NA>
 
8

Length

Max length10
Median length8
Mean length7.3418291
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷망_뉴딜용 311
46.6%
자가망_U무선망 240
36.0%
임대망 89
 
13.3%
자가망_수도사업소망 19
 
2.8%
<NA> 8
 
1.2%

Length

2024-05-18T06:58:17.846005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:18.275218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 311
46.6%
자가망_u무선망 240
36.0%
임대망 89
 
13.3%
자가망_수도사업소망 19
 
2.8%
na 8
 
1.2%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021.3823
Minimum2018
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-18T06:58:18.607572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.3465066
Coefficient of variation (CV)0.00066613157
Kurtosis-0.44110862
Mean2021.3823
Median Absolute Deviation (MAD)1
Skewness-0.86067704
Sum1348262
Variance1.8130799
MonotonicityNot monotonic
2024-05-18T06:58:18.969154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 322
48.3%
2019 113
 
16.9%
2023 107
 
16.0%
2021 86
 
12.9%
2020 31
 
4.6%
2018 8
 
1.2%
ValueCountFrequency (%)
2018 8
 
1.2%
2019 113
 
16.9%
2020 31
 
4.6%
2021 86
 
12.9%
2022 322
48.3%
2023 107
 
16.0%
ValueCountFrequency (%)
2023 107
 
16.0%
2022 322
48.3%
2021 86
 
12.9%
2020 31
 
4.6%
2019 113
 
16.9%
2018 8
 
1.2%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
실내
458 
실외
209 

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 (%)
실내 458
68.7%
실외 209
31.3%

Length

2024-05-18T06:58:19.551362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:19.860743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 458
68.7%
실외 209
31.3%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
656 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
11

Length

Max length27
Median length4
Mean length4.3793103
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> 656
98.4%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 11
 
1.6%

Length

2024-05-18T06:58:20.194063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T06:58:20.507298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 656
92.3%
보안접속 11
 
1.5%
임시적용(머큐리 11
 
1.5%
proxy 11
 
1.5%
서버 11
 
1.5%
개발중 11
 
1.5%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct282
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.63335
Minimum37.611336
Maximum37.663105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-18T06:58:20.862653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.611336
5-th percentile37.616351
Q137.626907
median37.633427
Q337.639816
95-th percentile37.6474
Maximum37.663105
Range0.051769
Interquartile range (IQR)0.012909

Descriptive statistics

Standard deviation0.0095307621
Coefficient of variation (CV)0.00025325309
Kurtosis-0.008532581
Mean37.63335
Median Absolute Deviation (MAD)0.00652
Skewness0.054641747
Sum25101.444
Variance9.0835426 × 10-5
MonotonicityNot monotonic
2024-05-18T06:58:21.359462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.63969 39
 
5.8%
37.635704 27
 
4.0%
37.645676 22
 
3.3%
37.634155 19
 
2.8%
37.640476 17
 
2.5%
37.629066 15
 
2.2%
37.632217 15
 
2.2%
37.6474 12
 
1.8%
37.625675 12
 
1.8%
37.629627 11
 
1.6%
Other values (272) 478
71.7%
ValueCountFrequency (%)
37.611336 1
 
0.1%
37.61177 1
 
0.1%
37.612003 1
 
0.1%
37.612423 1
 
0.1%
37.61257 1
 
0.1%
37.61285 3
0.4%
37.612885 1
 
0.1%
37.612896 1
 
0.1%
37.613316 2
0.3%
37.613365 1
 
0.1%
ValueCountFrequency (%)
37.663105 1
0.1%
37.66223 1
0.1%
37.662094 1
0.1%
37.662045 1
0.1%
37.66189 1
0.1%
37.661278 2
0.3%
37.653908 1
0.1%
37.65389 1
0.1%
37.653732 1
0.1%
37.65362 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct281
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.70019
Minimum126.91929
Maximum172.01723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-05-18T06:58:21.694561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.91929
5-th percentile127.0085
Q1127.01743
median127.02562
Q3127.03612
95-th percentile127.04549
Maximum172.01723
Range45.09794
Interquartile range (IQR)0.018695

Descriptive statistics

Standard deviation5.4716062
Coefficient of variation (CV)0.042847283
Kurtosis62.188829
Mean127.70019
Median Absolute Deviation (MAD)0.009376
Skewness8.0001287
Sum85176.027
Variance29.938474
MonotonicityNot monotonic
2024-05-18T06:58:21.988460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.02562 39
 
5.8%
127.01871 27
 
4.0%
127.006226 22
 
3.3%
127.03874 20
 
3.0%
127.036125 19
 
2.8%
127.01258 17
 
2.5%
127.03873 15
 
2.2%
127.01339 12
 
1.8%
127.01737 12
 
1.8%
127.041794 11
 
1.6%
Other values (271) 473
70.9%
ValueCountFrequency (%)
126.91929 1
 
0.1%
127.00478 1
 
0.1%
127.006226 22
3.3%
127.00748 1
 
0.1%
127.007484 1
 
0.1%
127.00759 1
 
0.1%
127.007614 2
 
0.3%
127.00773 1
 
0.1%
127.00817 1
 
0.1%
127.00847 1
 
0.1%
ValueCountFrequency (%)
172.01723 10
1.5%
127.04968 1
 
0.1%
127.04812 1
 
0.1%
127.047226 1
 
0.1%
127.046616 1
 
0.1%
127.0466 2
 
0.3%
127.04659 3
 
0.4%
127.04645 1
 
0.1%
127.04629 1
 
0.1%
127.046265 3
 
0.4%

작업일자
Date

Distinct12
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2024-05-17 11:12:52
Maximum2024-05-17 11:13:06
2024-05-18T06:58:22.234313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:22.551336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-18T06:58:06.793594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:05.235184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:06.012012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:07.049081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:05.494592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:06.279231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:07.306496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:05.758550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:58:06.536474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T06:58:22.815761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.7581.000NaN1.0000.4860.7290.0000.0001.000
설치유형0.7581.0000.9270.9460.9340.7930.9750.7380.5840.908
설치기관1.0000.9271.0000.8570.9360.7770.4380.3820.1340.963
서비스구분NaN0.9460.8571.0000.8890.5920.9030.4090.1090.954
망종류1.0000.9340.9360.8891.0000.6350.2210.4290.2260.922
설치년도0.4860.7930.7770.5920.6351.0000.1510.4250.1950.845
실내외구분0.7290.9750.4380.9030.2210.1511.0000.4400.0920.542
X좌표0.0000.7380.3820.4090.4290.4250.4401.0000.2950.524
Y좌표0.0000.5840.1340.1090.2260.1950.0920.2951.0000.148
작업일자1.0000.9080.9630.9540.9220.8450.5420.5240.1481.000
2024-05-18T06:58:23.147077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)실내외구분설치유형wifi접속환경서비스구분설치기관망종류
설치위치(층)1.0000.5700.388NaN1.0000.9650.965
실내외구분0.5701.0000.9611.0000.7170.4680.147
설치유형0.3880.9611.0001.0000.8320.7480.801
wifi접속환경NaN1.0001.0001.0001.0001.0001.000
서비스구분1.0000.7170.8321.0001.0000.7840.567
설치기관0.9650.4680.7481.0000.7841.0000.832
망종류0.9650.1470.8011.0000.5670.8321.000
2024-05-18T06:58:23.405996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.0000.066-0.0410.2230.5090.6190.5190.5760.1941.000
X좌표0.0661.000-0.4340.0000.3820.2040.2540.2690.3361.000
Y좌표-0.041-0.4341.0000.0000.5160.1430.0720.1500.0581.000
설치위치(층)0.2230.0000.0001.0000.3880.9651.0000.9650.5700.000
설치유형0.5090.3820.5160.3881.0000.7480.8320.8010.9611.000
설치기관0.6190.2040.1430.9650.7481.0000.7840.8320.4681.000
서비스구분0.5190.2540.0721.0000.8320.7841.0000.5670.7171.000
망종류0.5760.2690.1500.9650.8010.8320.5671.0000.1471.000
실내외구분0.1940.3360.0580.5700.9610.4680.7170.1471.0001.000
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T06:58:07.681935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T06:58:08.192934image/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.
2024-05-18T06:58:08.634197image/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
0ARI00090강북구북부수도사업소한천로 935본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
1ARI00091강북구북부수도사업소한천로 935본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
2ARI00092강북구북부수도사업소한천로 935본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
3ARI00093강북구북부수도사업소한천로 935본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
4ARI00094강북구북부수도사업소한천로 935본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
5ARI00095강북구북부수도사업소한천로 935본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
6ARI00096강북구북부수도사업소한천로 935본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
7ARI00097강북구북부수도사업소한천로 935본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
8ARI00098강북구북부수도사업소한천로 935본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
9ARI00099강북구북부수도사업소한천로 935본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.634155127.0361252024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
657서울5차-0154강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 복도3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
658서울5차-0154-1강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 사무실4층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
659서울5차-0154-2강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 직업적응훈련실4층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
660서울5차-0155강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 열림터5층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
661서울5차-0155-1강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 복도5층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
662서울5차-0155-2강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 열림작업장6층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
663서울5차-0156강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 직업평가실6층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
664서울5차-0156-1강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 강당 좌측7층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
665서울5차-0156-2강북구강북장애인종합복지관서울특별시 강북구 오현로 187-6(별관) 강당 우측7층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.629066127.038732024-05-17 11:13:06.0
666서울5차-0835강북구강북구청앞먹자골목서울특별시 강북구 한천로 1039(CCTV) 주정차036-1. 주요거리디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.63999127.026352024-05-17 11:13:06.0