Overview

Dataset statistics

Number of variables16
Number of observations760
Missing cells13
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.4 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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-20906/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 2 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
X좌표 is highly overall correlated with Y좌표 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
설치위치(층) is highly imbalanced (92.4%)Imbalance
wifi접속환경 is highly imbalanced (93.4%)Imbalance
도로명주소 has 13 (1.7%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-17 22:43:34.915570
Analysis finished2024-05-17 22:43:42.432196
Duration7.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct760
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-05-18T07:43:42.922035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.3486842
Min length7

Characters and Unicode

Total characters6345
Distinct characters20
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

Unique760 ?
Unique (%)100.0%

Sample

1st rowBS100341
2nd rowBS100342
3rd rowBS100343
4th rowBS100344
5th rowBS100345
ValueCountFrequency (%)
bs100341 1
 
0.1%
서울-2029 1
 
0.1%
서울-2082 1
 
0.1%
서울-2021 1
 
0.1%
서울-2022 1
 
0.1%
서울-2023 1
 
0.1%
서울-2024 1
 
0.1%
서울-2025 1
 
0.1%
서울-2026 1
 
0.1%
서울-2027 1
 
0.1%
Other values (750) 750
98.7%
2024-05-18T07:43:44.911055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 960
15.1%
1 830
13.1%
7 420
 
6.6%
4 399
 
6.3%
2 395
 
6.2%
6 382
 
6.0%
- 364
 
5.7%
3 329
 
5.2%
서 263
 
4.1%
울 263
 
4.1%
Other values (10) 1740
27.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4291
67.6%
Uppercase Letter 1008
 
15.9%
Other Letter 682
 
10.7%
Dash Punctuation 364
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 960
22.4%
1 830
19.3%
7 420
9.8%
4 399
9.3%
2 395
9.2%
6 382
 
8.9%
3 329
 
7.7%
9 212
 
4.9%
5 200
 
4.7%
8 164
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
W 251
24.9%
F 251
24.9%
G 182
18.1%
C 182
18.1%
S 78
 
7.7%
B 64
 
6.3%
Other Letter
ValueCountFrequency (%)
서 263
38.6%
울 263
38.6%
차 156
22.9%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4655
73.4%
Latin 1008
 
15.9%
Hangul 682
 
10.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 960
20.6%
1 830
17.8%
7 420
9.0%
4 399
8.6%
2 395
8.5%
6 382
 
8.2%
- 364
 
7.8%
3 329
 
7.1%
9 212
 
4.6%
5 200
 
4.3%
Latin
ValueCountFrequency (%)
W 251
24.9%
F 251
24.9%
G 182
18.1%
C 182
18.1%
S 78
 
7.7%
B 64
 
6.3%
Hangul
ValueCountFrequency (%)
서 263
38.6%
울 263
38.6%
차 156
22.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5663
89.3%
Hangul 682
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 960
17.0%
1 830
14.7%
7 420
 
7.4%
4 399
 
7.0%
2 395
 
7.0%
6 382
 
6.7%
- 364
 
6.4%
3 329
 
5.8%
W 251
 
4.4%
F 251
 
4.4%
Other values (7) 1082
19.1%
Hangul
ValueCountFrequency (%)
서 263
38.6%
울 263
38.6%
차 156
22.9%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
금천구
760 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금천구 760
100.0%

Length

2024-05-18T07:43:45.663771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:46.318588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금천구 760
100.0%

와이파이명
Text

Distinct215
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-05-18T07:43:46.829638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length9.3644737
Min length3

Characters and Unicode

Total characters7117
Distinct characters294
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

Unique119 ?
Unique (%)15.7%

Sample

1st row버스정류소_금천패션아울렛사거리.W몰
2nd row버스정류소_가산동주민센터.금천글로벌센터
3rd row버스정류소_구로세관
4th row버스정류소_구립가산도서관.두산위브아파트
5th row버스정류소_금빛공원앞
ValueCountFrequency (%)
안양천산책로 60
 
6.8%
서울시립금천청소년센터 38
 
4.3%
금천구청 37
 
4.2%
서울특별시남부여성발전센터 36
 
4.1%
g밸리디지털산업단지 35
 
3.9%
가산디지털단지역 27
 
3.0%
청담종합사회복지관 21
 
2.4%
벽산5단지apt 16
 
1.8%
금천한내어르신복지센터 16
 
1.8%
독산2동주민센터 15
 
1.7%
Other values (226) 587
66.1%
2024-05-18T07:43:48.132953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 314
 
4.4%
지 298
 
4.2%
산 279
 
3.9%
금 245
 
3.4%
터 218
 
3.1%
센 215
 
3.0%
시 193
 
2.7%
청 133
 
1.9%
소 131
 
1.8%
동 129
 
1.8%
Other values (284) 4962
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6510
91.5%
Decimal Number 147
 
2.1%
Space Separator 128
 
1.8%
Uppercase Letter 108
 
1.5%
Connector Punctuation 64
 
0.9%
Open Punctuation 59
 
0.8%
Close Punctuation 59
 
0.8%
Other Punctuation 25
 
0.4%
Dash Punctuation 17
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 314
 
4.8%
지 298
 
4.6%
산 279
 
4.3%
금 245
 
3.8%
터 218
 
3.3%
센 215
 
3.3%
시 193
 
3.0%
청 133
 
2.0%
소 131
 
2.0%
동 129
 
2.0%
Other values (257) 4355
66.9%
Uppercase Letter
ValueCountFrequency (%)
G 37
34.3%
T 17
15.7%
P 17
15.7%
A 16
14.8%
E 6
 
5.6%
M 6
 
5.6%
W 3
 
2.8%
C 2
 
1.9%
N 2
 
1.9%
I 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 36
24.5%
2 31
21.1%
3 30
20.4%
5 22
15.0%
4 12
 
8.2%
6 11
 
7.5%
7 2
 
1.4%
9 2
 
1.4%
8 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 22
88.0%
, 3
 
12.0%
Space Separator
ValueCountFrequency (%)
128
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6510
91.5%
Common 499
 
7.0%
Latin 108
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 314
 
4.8%
지 298
 
4.6%
산 279
 
4.3%
금 245
 
3.8%
터 218
 
3.3%
센 215
 
3.3%
시 193
 
3.0%
청 133
 
2.0%
소 131
 
2.0%
동 129
 
2.0%
Other values (257) 4355
66.9%
Common
ValueCountFrequency (%)
128
25.7%
_ 64
12.8%
( 59
11.8%
) 59
11.8%
1 36
 
7.2%
2 31
 
6.2%
3 30
 
6.0%
. 22
 
4.4%
5 22
 
4.4%
- 17
 
3.4%
Other values (6) 31
 
6.2%
Latin
ValueCountFrequency (%)
G 37
34.3%
T 17
15.7%
P 17
15.7%
A 16
14.8%
E 6
 
5.6%
M 6
 
5.6%
W 3
 
2.8%
C 2
 
1.9%
N 2
 
1.9%
I 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6510
91.5%
ASCII 607
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 314
 
4.8%
지 298
 
4.6%
산 279
 
4.3%
금 245
 
3.8%
터 218
 
3.3%
센 215
 
3.3%
시 193
 
3.0%
청 133
 
2.0%
소 131
 
2.0%
동 129
 
2.0%
Other values (257) 4355
66.9%
ASCII
ValueCountFrequency (%)
128
21.1%
_ 64
10.5%
( 59
9.7%
) 59
9.7%
G 37
 
6.1%
1 36
 
5.9%
2 31
 
5.1%
3 30
 
4.9%
. 22
 
3.6%
5 22
 
3.6%
Other values (17) 119
19.6%

도로명주소
Text

MISSING 

Distinct311
Distinct (%)41.6%
Missing13
Missing (%)1.7%
Memory size6.1 KiB
2024-05-18T07:43:48.994836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length13.390897
Min length4

Characters and Unicode

Total characters10003
Distinct characters120
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

Unique226 ?
Unique (%)30.3%

Sample

1st row디지털로 188
2nd row가산동 144-7
3rd row가산동 356-5
4th row가산동 7710
5th row금하로 668
ValueCountFrequency (%)
금천구 264
 
13.0%
서울특별시 262
 
12.9%
시흥동 90
 
4.4%
시흥대로 75
 
3.7%
독산동 59
 
2.9%
금하로 50
 
2.5%
73길 42
 
2.1%
70 42
 
2.1%
54 39
 
1.9%
안양천산책로 36
 
1.8%
Other values (386) 1078
52.9%
2024-05-18T07:43:50.446863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1292
 
12.9%
1 510
 
5.1%
로 506
 
5.1%
시 491
 
4.9%
금 408
 
4.1%
3 370
 
3.7%
천 355
 
3.5%
2 348
 
3.5%
산 336
 
3.4%
0 294
 
2.9%
Other values (110) 5093
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5412
54.1%
Decimal Number 2895
28.9%
Space Separator 1292
 
12.9%
Dash Punctuation 270
 
2.7%
Open Punctuation 53
 
0.5%
Close Punctuation 53
 
0.5%
Other Punctuation 22
 
0.2%
Math Symbol 4
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 506
 
9.3%
시 491
 
9.1%
금 408
 
7.5%
천 355
 
6.6%
산 336
 
6.2%
구 293
 
5.4%
길 275
 
5.1%
서 270
 
5.0%
울 266
 
4.9%
특 262
 
4.8%
Other values (92) 1950
36.0%
Decimal Number
ValueCountFrequency (%)
1 510
17.6%
3 370
12.8%
2 348
12.0%
0 294
10.2%
5 250
8.6%
7 246
8.5%
6 241
8.3%
4 231
8.0%
8 209
7.2%
9 196
 
6.8%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
. 1
 
4.5%
Space Separator
ValueCountFrequency (%)
1292
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5412
54.1%
Common 4589
45.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 506
 
9.3%
시 491
 
9.1%
금 408
 
7.5%
천 355
 
6.6%
산 336
 
6.2%
구 293
 
5.4%
길 275
 
5.1%
서 270
 
5.0%
울 266
 
4.9%
특 262
 
4.8%
Other values (92) 1950
36.0%
Common
ValueCountFrequency (%)
1292
28.2%
1 510
 
11.1%
3 370
 
8.1%
2 348
 
7.6%
0 294
 
6.4%
- 270
 
5.9%
5 250
 
5.4%
7 246
 
5.4%
6 241
 
5.3%
4 231
 
5.0%
Other values (7) 537
11.7%
Latin
ValueCountFrequency (%)
F 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5412
54.1%
ASCII 4591
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1292
28.1%
1 510
 
11.1%
3 370
 
8.1%
2 348
 
7.6%
0 294
 
6.4%
- 270
 
5.9%
5 250
 
5.4%
7 246
 
5.4%
6 241
 
5.2%
4 231
 
5.0%
Other values (8) 539
11.7%
Hangul
ValueCountFrequency (%)
로 506
 
9.3%
시 491
 
9.1%
금 408
 
7.5%
천 355
 
6.6%
산 336
 
6.2%
구 293
 
5.4%
길 275
 
5.1%
서 270
 
5.0%
울 266
 
4.9%
특 262
 
4.8%
Other values (92) 1950
36.0%

상세주소
Text

Distinct642
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-05-18T07:43:51.131538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length14.364474
Min length1

Characters and Unicode

Total characters10917
Distinct characters376
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)74.9%

Sample

1st row18-114
2nd row18-120
3rd row18-998
4th row18-122
5th row18-232
ValueCountFrequency (%)
앞 82
 
4.1%
55
 
2.8%
복도 44
 
2.2%
안양천제방길 39
 
2.0%
시립금천청소년센터 33
 
1.7%
금천구청 33
 
1.7%
내 28
 
1.4%
독산동 27
 
1.4%
cctv 26
 
1.3%
시흥동 25
 
1.3%
Other values (820) 1593
80.3%
2024-05-18T07:43:52.236228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1226
 
11.2%
1 838
 
7.7%
2 332
 
3.0%
- 316
 
2.9%
3 282
 
2.6%
( 277
 
2.5%
) 277
 
2.5%
_ 268
 
2.5%
0 213
 
2.0%
8 184
 
1.7%
Other values (366) 6704
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5277
48.3%
Decimal Number 2491
22.8%
Space Separator 1226
 
11.2%
Uppercase Letter 579
 
5.3%
Dash Punctuation 316
 
2.9%
Open Punctuation 277
 
2.5%
Close Punctuation 277
 
2.5%
Connector Punctuation 268
 
2.5%
Lowercase Letter 137
 
1.3%
Other Punctuation 66
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 177
 
3.4%
로 176
 
3.3%
동 153
 
2.9%
천 153
 
2.9%
앞 145
 
2.7%
층 138
 
2.6%
내 118
 
2.2%
안 112
 
2.1%
시 111
 
2.1%
지 110
 
2.1%
Other values (311) 3884
73.6%
Lowercase Letter
ValueCountFrequency (%)
p 57
41.6%
i 56
40.9%
t 6
 
4.4%
g 3
 
2.2%
m 2
 
1.5%
c 2
 
1.5%
v 1
 
0.7%
x 1
 
0.7%
r 1
 
0.7%
e 1
 
0.7%
Other values (7) 7
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
F 161
27.8%
C 98
16.9%
T 62
 
10.7%
P 52
 
9.0%
N 46
 
7.9%
V 45
 
7.8%
A 34
 
5.9%
S 20
 
3.5%
B 20
 
3.5%
U 18
 
3.1%
Other values (6) 23
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 838
33.6%
2 332
 
13.3%
3 282
 
11.3%
0 213
 
8.6%
8 184
 
7.4%
4 161
 
6.5%
5 130
 
5.2%
6 127
 
5.1%
7 118
 
4.7%
9 106
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 56
84.8%
; 3
 
4.5%
& 3
 
4.5%
' 2
 
3.0%
# 2
 
3.0%
Other Symbol
ValueCountFrequency (%)
▲ 2
66.7%
㈜ 1
33.3%
Space Separator
ValueCountFrequency (%)
1226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 316
100.0%
Open Punctuation
ValueCountFrequency (%)
( 277
100.0%
Close Punctuation
ValueCountFrequency (%)
) 277
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5278
48.3%
Common 4923
45.1%
Latin 716
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 177
 
3.4%
로 176
 
3.3%
동 153
 
2.9%
천 153
 
2.9%
앞 145
 
2.7%
층 138
 
2.6%
내 118
 
2.2%
안 112
 
2.1%
시 111
 
2.1%
지 110
 
2.1%
Other values (312) 3885
73.6%
Latin
ValueCountFrequency (%)
F 161
22.5%
C 98
13.7%
T 62
 
8.7%
p 57
 
8.0%
i 56
 
7.8%
P 52
 
7.3%
N 46
 
6.4%
V 45
 
6.3%
A 34
 
4.7%
S 20
 
2.8%
Other values (23) 85
11.9%
Common
ValueCountFrequency (%)
1226
24.9%
1 838
17.0%
2 332
 
6.7%
- 316
 
6.4%
3 282
 
5.7%
( 277
 
5.6%
) 277
 
5.6%
_ 268
 
5.4%
0 213
 
4.3%
8 184
 
3.7%
Other values (11) 710
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5637
51.6%
Hangul 5277
48.3%
Geometric Shapes 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1226
21.7%
1 838
14.9%
2 332
 
5.9%
- 316
 
5.6%
3 282
 
5.0%
( 277
 
4.9%
) 277
 
4.9%
_ 268
 
4.8%
0 213
 
3.8%
8 184
 
3.3%
Other values (43) 1424
25.3%
Hangul
ValueCountFrequency (%)
산 177
 
3.4%
로 176
 
3.3%
동 153
 
2.9%
천 153
 
2.9%
앞 145
 
2.7%
층 138
 
2.6%
내 118
 
2.2%
안 112
 
2.1%
시 111
 
2.1%
지 110
 
2.1%
Other values (311) 3884
73.6%
Geometric Shapes
ValueCountFrequency (%)
▲ 2
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
<NA>
745 
-
 
6
3층
 
5
4층
 
2
1층
 
2

Length

Max length4
Median length4
Mean length3.9526316
Min length1

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> 745
98.0%
- 6
 
0.8%
3층 5
 
0.7%
4층 2
 
0.3%
1층 2
 
0.3%

Length

2024-05-18T07:43:52.832090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:53.427081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 745
98.0%
6
 
0.8%
3층 5
 
0.7%
4층 2
 
0.3%
1층 2
 
0.3%

설치유형
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
1. 주요거리
157 
3. 공원(하천)
134 
6-4. 복지 - 아동청소년
79 
7-2-3. 공공 - 동주민센터
63 
5-1. 버스정류소(국비)
50 
Other values (14)
277 

Length

Max length21
Median length17
Mean length11.739474
Min length7

Unique

Unique2 ?
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 (%)
1. 주요거리 157
20.7%
3. 공원(하천) 134
17.6%
6-4. 복지 - 아동청소년 79
10.4%
7-2-3. 공공 - 동주민센터 63
8.3%
5-1. 버스정류소(국비) 50
 
6.6%
7-1-3. 공공 - 시산하기관 43
 
5.7%
6-2. 복지 - 노인 40
 
5.3%
6-1. 복지 - 사회 40
 
5.3%
7-2-1. 공공 - 구청사 및 별관 37
 
4.9%
2. 전통시장 35
 
4.6%
Other values (9) 82
10.8%

Length

2024-05-18T07:43:53.994418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
351
15.3%
복지 179
 
7.8%
공공 172
 
7.5%
1 157
 
6.8%
주요거리 157
 
6.8%
공원(하천 134
 
5.8%
3 134
 
5.8%
6-4 79
 
3.4%
아동청소년 79
 
3.4%
7-2-3 63
 
2.7%
Other values (34) 793
34.5%

설치기관
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
서울시(AP)
248 
자치구
180 
디지털뉴딜(LG U+)
157 
디지털뉴딜(KT)
106 
버스정류소(국비)
50 
Other values (3)
 
19

Length

Max length12
Median length9
Mean length7.5394737
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 (%)
서울시(AP) 248
32.6%
자치구 180
23.7%
디지털뉴딜(LG U+) 157
20.7%
디지털뉴딜(KT) 106
13.9%
버스정류소(국비) 50
 
6.6%
버스정류소(시비) 14
 
1.8%
서울시(공유기) 3
 
0.4%
자치구(공유기) 2
 
0.3%

Length

2024-05-18T07:43:54.445601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:54.886353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울시(ap 248
27.0%
자치구 180
19.6%
디지털뉴딜(lg 157
17.1%
u 157
17.1%
디지털뉴딜(kt 106
11.6%
버스정류소(국비 50
 
5.5%
버스정류소(시비 14
 
1.5%
서울시(공유기 3
 
0.3%
자치구(공유기 2
 
0.2%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
공공WiFi
588 
과기부WiFi(복지시설)
81 
과기부WiFi
 
50
과기부WiFi(핫플레이스)
 
26
<NA>
 
15

Length

Max length14
Median length6
Mean length7.0460526
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 588
77.4%
과기부WiFi(복지시설) 81
 
10.7%
과기부WiFi 50
 
6.6%
과기부WiFi(핫플레이스) 26
 
3.4%
<NA> 15
 
2.0%

Length

2024-05-18T07:43:55.517593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:55.883103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 588
77.4%
과기부wifi(복지시설 81
 
10.7%
과기부wifi 50
 
6.6%
과기부wifi(핫플레이스 26
 
3.4%
na 15
 
2.0%

망종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
자가망_U무선망
358 
인터넷망_뉴딜용
263 
임대망
125 
<NA>
 
14

Length

Max length8
Median length8
Mean length7.1039474
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가망_U무선망 358
47.1%
인터넷망_뉴딜용 263
34.6%
임대망 125
 
16.4%
<NA> 14
 
1.8%

Length

2024-05-18T07:43:56.457019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:56.979799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 358
47.1%
인터넷망_뉴딜용 263
34.6%
임대망 125
 
16.4%
na 14
 
1.8%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6763
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-05-18T07:43:57.351350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2016
Q12018
median2020
Q32022
95-th percentile2022.05
Maximum2023
Range10
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.532626
Coefficient of variation (CV)0.0012539762
Kurtosis-0.015751097
Mean2019.6763
Median Absolute Deviation (MAD)2
Skewness-0.77128811
Sum1534954
Variance6.4141946
MonotonicityNot monotonic
2024-05-18T07:43:57.730574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2022 249
32.8%
2017 131
17.2%
2019 125
16.4%
2021 83
 
10.9%
2018 54
 
7.1%
2023 38
 
5.0%
2013 35
 
4.6%
2020 28
 
3.7%
2016 16
 
2.1%
2014 1
 
0.1%
ValueCountFrequency (%)
2013 35
 
4.6%
2014 1
 
0.1%
2016 16
 
2.1%
2017 131
17.2%
2018 54
 
7.1%
2019 125
16.4%
2020 28
 
3.7%
2021 83
 
10.9%
2022 249
32.8%
2023 38
 
5.0%
ValueCountFrequency (%)
2023 38
 
5.0%
2022 249
32.8%
2021 83
 
10.9%
2020 28
 
3.7%
2019 125
16.4%
2018 54
 
7.1%
2017 131
17.2%
2016 16
 
2.1%
2014 1
 
0.1%
2013 35
 
4.6%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
실외
380 
실내
380 

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 (%)
실외 380
50.0%
실내 380
50.0%

Length

2024-05-18T07:43:58.279588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:58.678838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 380
50.0%
실내 380
50.0%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
<NA>
754 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
6

Length

Max length27
Median length4
Mean length4.1815789
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> 754
99.2%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 6
 
0.8%

Length

2024-05-18T07:43:58.955426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:59.236805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 754
96.2%
보안접속 6
 
0.8%
임시적용(머큐리 6
 
0.8%
proxy 6
 
0.8%
서버 6
 
0.8%
개발중 6
 
0.8%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct429
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.461706
Minimum37.433926
Maximum37.485615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-05-18T07:43:59.600811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.433926
5-th percentile37.446156
Q137.452156
median37.46311
Q337.47021
95-th percentile37.480722
Maximum37.485615
Range0.051689
Interquartile range (IQR)0.018054

Descriptive statistics

Standard deviation0.011462054
Coefficient of variation (CV)0.00030596721
Kurtosis-0.84354288
Mean37.461706
Median Absolute Deviation (MAD)0.0097655
Skewness0.053466662
Sum28470.897
Variance0.00013137868
MonotonicityNot monotonic
2024-05-18T07:44:00.051024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45683 37
 
4.9%
37.448223 33
 
4.3%
37.4517 21
 
2.8%
37.457146 15
 
2.0%
37.46311 11
 
1.4%
37.463577 11
 
1.4%
37.450092 10
 
1.3%
37.47689 9
 
1.2%
37.46946 8
 
1.1%
37.45009 8
 
1.1%
Other values (419) 597
78.6%
ValueCountFrequency (%)
37.433926 1
 
0.1%
37.4345 2
 
0.3%
37.434563 1
 
0.1%
37.43484 1
 
0.1%
37.435524 1
 
0.1%
37.437626 1
 
0.1%
37.4385 5
0.7%
37.43858 1
 
0.1%
37.438885 1
 
0.1%
37.43891 1
 
0.1%
ValueCountFrequency (%)
37.485615 1
 
0.1%
37.485085 1
 
0.1%
37.48506 1
 
0.1%
37.48467 2
0.3%
37.484146 1
 
0.1%
37.483826 1
 
0.1%
37.48346 2
0.3%
37.483295 1
 
0.1%
37.483006 1
 
0.1%
37.482822 3
0.4%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct421
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.89872
Minimum126.53178
Maximum126.92554
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-05-18T07:44:00.466386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53178
5-th percentile126.87902
Q1126.89169
median126.90012
Q3126.90664
95-th percentile126.91569
Maximum126.92554
Range0.393765
Interquartile range (IQR)0.0149535

Descriptive statistics

Standard deviation0.017518363
Coefficient of variation (CV)0.00013804996
Kurtosis253.01504
Mean126.89872
Median Absolute Deviation (MAD)0.007425
Skewness-12.16815
Sum96443.026
Variance0.00030689305
MonotonicityNot monotonic
2024-05-18T07:44:00.991389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8954 37
 
4.9%
126.91569 33
 
4.3%
126.91363 21
 
2.8%
126.887024 15
 
2.0%
126.90339 11
 
1.4%
126.90645 11
 
1.4%
126.916504 10
 
1.3%
126.90416 9
 
1.2%
126.89178 9
 
1.2%
126.90642 8
 
1.1%
Other values (411) 596
78.4%
ValueCountFrequency (%)
126.53178 1
0.1%
126.87339 2
0.3%
126.87409 2
0.3%
126.8741 2
0.3%
126.874115 1
0.1%
126.8742 1
0.1%
126.874756 1
0.1%
126.874825 1
0.1%
126.87499 1
0.1%
126.875465 1
0.1%
ValueCountFrequency (%)
126.925545 1
0.1%
126.9229 1
0.1%
126.9221 1
0.1%
126.9217 1
0.1%
126.921394 1
0.1%
126.92106 1
0.1%
126.92076 1
0.1%
126.92064 1
0.1%
126.92063 1
0.1%
126.92051 1
0.1%

작업일자
Date

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
Minimum2024-05-17 11:12:52
Maximum2024-05-17 11:13:06
2024-05-18T07:44:01.522982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:44:02.302892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-18T07:43:39.937439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:37.751540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:38.827910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:40.396211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:38.035806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:39.202921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:40.939382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:38.366507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:39.519213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T07:44:02.647700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.803NaNNaNNaNNaN1.0000.5750.932NaN
설치유형0.8031.0000.9200.9140.9500.8800.9720.7380.4710.919
설치기관NaN0.9201.0000.9810.8670.8650.5170.4790.2820.972
서비스구분NaN0.9140.9811.0000.5690.7020.6520.4640.1110.983
망종류NaN0.9500.8670.5691.0000.9700.1280.4140.2070.939
설치년도NaN0.8800.8650.7020.9701.0000.4040.4810.3040.849
실내외구분1.0000.9720.5170.6520.1280.4041.0000.4320.2110.690
X좌표0.5750.7380.4790.4640.4140.4810.4321.0000.6400.600
Y좌표0.9320.4710.2820.1110.2070.3040.2110.6401.0000.534
작업일자NaN0.9190.9720.9830.9390.8490.6900.6000.5341.000
2024-05-18T07:44:03.162057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치기관실내외구분설치위치(층)wifi접속환경설치유형서비스구분망종류
설치기관1.0000.3881.0001.0000.7130.8100.850
실내외구분0.3881.0000.9201.0000.9580.4550.211
설치위치(층)1.0000.9201.000NaN0.827NaN1.000
wifi접속환경1.0001.000NaN1.0001.0001.0001.000
설치유형0.7130.9580.8271.0001.0000.7610.754
서비스구분0.8100.455NaN1.0000.7611.0000.577
망종류0.8500.2111.0001.0000.7540.5771.000
2024-05-18T07:44:03.608750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.000-0.0490.0501.0000.5540.5580.5370.7910.4501.000
X좌표-0.0491.000-0.6320.3330.3830.2520.2940.2730.3301.000
Y좌표0.050-0.6321.0000.6980.2830.1850.1040.0650.3451.000
설치위치(층)1.0000.3330.6981.0000.8271.0000.0001.0000.9200.000
설치유형0.5540.3830.2830.8271.0000.7130.7610.7540.9581.000
설치기관0.5580.2520.1851.0000.7131.0000.8100.8500.3881.000
서비스구분0.5370.2940.1040.0000.7610.8101.0000.5770.4551.000
망종류0.7910.2730.0651.0000.7540.8500.5771.0000.2111.000
실내외구분0.4500.3300.3450.9200.9580.3880.4550.2111.0001.000
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T07:43:41.422227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:43:42.146031image/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.

Sample

관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
0BS100341금천구버스정류소_금천패션아울렛사거리.W몰디지털로 18818-114<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47766126.887882024-05-17 11:12:52.0
1BS100342금천구버스정류소_가산동주민센터.금천글로벌센터가산동 144-718-120<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.476612126.89212024-05-17 11:12:52.0
2BS100343금천구버스정류소_구로세관가산동 356-518-998<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47249126.884942024-05-17 11:12:52.0
3BS100344금천구버스정류소_구립가산도서관.두산위브아파트가산동 771018-122<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47447126.893942024-05-17 11:12:52.0
4BS100345금천구버스정류소_금빛공원앞금하로 66818-232<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.453106126.90432024-05-17 11:12:52.0
5BS100346금천구버스정류소_금천구청.금천경찰서시흥대로18-007<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.45921126.898872024-05-17 11:12:52.0
6BS100347금천구버스정류소_금천구청.금천경찰서시흥대로18-008<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.457726126.899092024-05-17 11:12:52.0
7BS100348금천구버스정류소_금천우체국시흥대로18-003<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.469135126.898092024-05-17 11:12:52.0
8BS100349금천구버스정류소_금천우체국시흥대로18-004<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.470135126.8982024-05-17 11:12:52.0
9BS100350금천구버스정류소_금천폭포공원.천주교시흥성당시흥동 936-418-165<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.447712126.903522024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
750서울5차-0759금천구모아래마을마당서울특별시 금천구 가산동 237-68(CCTV) P350-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.4731126.889322024-05-17 11:13:06.0
751서울5차-0818금천구구로공단노동자생활체험관서울특별시 금천구 벚꽃로44길 17사무실 벽부3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.482822126.883632024-05-17 11:13:06.0
752서울5차-0819금천구금천청소년문화의집서울특별시 금천구 시흥대로 164라운지3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
753서울5차-0819-1금천구금천청소년문화의집서울특별시 금천구 시흥대로 164아트존3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
754서울5차-0819-2금천구금천청소년문화의집서울특별시 금천구 시흥대로 164플레이존3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
755서울5차-0820금천구금천청소년문화의집서울특별시 금천구 시흥대로 164관장실 모니터 옆3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
756서울5차-0820-1금천구금천청소년문화의집서울특별시 금천구 시흥대로 164자치활동실4층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
757서울5차-0820-2금천구금천청소년문화의집서울특별시 금천구 시흥대로 164동아리방 라운지4층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.448875126.903212024-05-17 11:13:06.0
758서울5차-1009금천구구로공단노동자생활체험관서울특별시 금천구 벚꽃로44길 17정수기 뒤1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.482822126.883632024-05-17 11:13:06.0
759서울5차-1009-1금천구구로공단노동자생활체험관서울특별시 금천구 벚꽃로44길 17가리봉상회 에어컨 뒤1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.482822126.883632024-05-17 11:13:06.0