Overview

Dataset statistics

Number of variables16
Number of observations914
Missing cells37
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory117.1 KiB
Average record size in memory131.1 B

Variable types

Text4
Categorical9
Numeric3

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-20910/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치년도 and 8 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 2 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
X좌표 is highly overall correlated with Y좌표 and 2 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치위치(층) is highly imbalanced (84.7%)Imbalance
wifi접속환경 is highly imbalanced (88.4%)Imbalance
도로명주소 has 33 (3.6%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 05:45:15.330096
Analysis finished2024-05-18 05:45:23.036995
Duration7.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct914
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18T14:45:23.409025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.368709
Min length7

Characters and Unicode

Total characters7649
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

Unique914 ?
Unique (%)100.0%

Sample

1st rowBS100692
2nd rowBS100693
3rd rowBS100694
4th rowBS100695
5th rowBS100696
ValueCountFrequency (%)
bs100692 1
 
0.1%
서울-3174-1 1
 
0.1%
wf201499 1
 
0.1%
wf201512 1
 
0.1%
wf201500 1
 
0.1%
wf201501 1
 
0.1%
wf201503 1
 
0.1%
wf201504 1
 
0.1%
wf201505 1
 
0.1%
wf201506 1
 
0.1%
Other values (904) 904
98.9%
2024-05-18T14:45:24.690197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1661
21.7%
1 965
12.6%
2 612
 
8.0%
7 392
 
5.1%
- 366
 
4.8%
S 364
 
4.8%
4 358
 
4.7%
3 336
 
4.4%
W 307
 
4.0%
F 291
 
3.8%
Other values (12) 1997
26.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5245
68.6%
Uppercase Letter 1319
 
17.2%
Other Letter 719
 
9.4%
Dash Punctuation 366
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1661
31.7%
1 965
18.4%
2 612
 
11.7%
7 392
 
7.5%
4 358
 
6.8%
3 336
 
6.4%
6 283
 
5.4%
5 247
 
4.7%
9 208
 
4.0%
8 183
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
S 364
27.6%
W 307
23.3%
F 291
22.1%
C 210
15.9%
B 123
 
9.3%
N 16
 
1.2%
G 4
 
0.3%
H 4
 
0.3%
Other Letter
ValueCountFrequency (%)
울 270
37.6%
서 270
37.6%
차 179
24.9%
Dash Punctuation
ValueCountFrequency (%)
- 366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5611
73.4%
Latin 1319
 
17.2%
Hangul 719
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1661
29.6%
1 965
17.2%
2 612
 
10.9%
7 392
 
7.0%
- 366
 
6.5%
4 358
 
6.4%
3 336
 
6.0%
6 283
 
5.0%
5 247
 
4.4%
9 208
 
3.7%
Latin
ValueCountFrequency (%)
S 364
27.6%
W 307
23.3%
F 291
22.1%
C 210
15.9%
B 123
 
9.3%
N 16
 
1.2%
G 4
 
0.3%
H 4
 
0.3%
Hangul
ValueCountFrequency (%)
울 270
37.6%
서 270
37.6%
차 179
24.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6930
90.6%
Hangul 719
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1661
24.0%
1 965
13.9%
2 612
 
8.8%
7 392
 
5.7%
- 366
 
5.3%
S 364
 
5.3%
4 358
 
5.2%
3 336
 
4.8%
W 307
 
4.4%
F 291
 
4.2%
Other values (9) 1278
18.4%
Hangul
ValueCountFrequency (%)
울 270
37.6%
서 270
37.6%
차 179
24.9%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
서초구
914 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 914
100.0%

Length

2024-05-18T14:45:25.347549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:25.593405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초구 914
100.0%

와이파이명
Text

Distinct277
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18T14:45:26.172794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length7.8161926
Min length3

Characters and Unicode

Total characters7144
Distinct characters295
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

Unique170 ?
Unique (%)18.6%

Sample

1st row버스정류소_LH서초아파트
2nd row버스정류소_경문고등학교
3rd row버스정류소_고속터미널
4th row버스정류소_고속터미널
5th row버스정류소_교육개발원입구
ValueCountFrequency (%)
서초구청 65
 
6.7%
보건환경연구원 59
 
6.1%
서울시 55
 
5.7%
어린이병원 55
 
5.7%
반포한강공원 38
 
3.9%
인재개발원 30
 
3.1%
여의천일대 18
 
1.8%
서초4동주민센터 17
 
1.7%
내곡동주민센터 17
 
1.7%
방배유스센터 15
 
1.5%
Other values (268) 604
62.1%
2024-05-18T14:45:27.352616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 337
 
4.7%
서 333
 
4.7%
초 238
 
3.3%
터 214
 
3.0%
구 203
 
2.8%
센 189
 
2.6%
스 172
 
2.4%
소 164
 
2.3%
동 156
 
2.2%
공 141
 
2.0%
Other values (285) 4997
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6788
95.0%
Connector Punctuation 123
 
1.7%
Decimal Number 110
 
1.5%
Space Separator 59
 
0.8%
Other Punctuation 35
 
0.5%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%
Uppercase Letter 5
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 337
 
5.0%
서 333
 
4.9%
초 238
 
3.5%
터 214
 
3.2%
구 203
 
3.0%
센 189
 
2.8%
스 172
 
2.5%
소 164
 
2.4%
동 156
 
2.3%
공 141
 
2.1%
Other values (267) 4641
68.4%
Decimal Number
ValueCountFrequency (%)
1 34
30.9%
3 25
22.7%
4 24
21.8%
2 22
20.0%
5 2
 
1.8%
8 2
 
1.8%
7 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
L 1
20.0%
H 1
20.0%
B 1
20.0%
S 1
20.0%
X 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 123
100.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Other Punctuation
ValueCountFrequency (%)
. 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6788
95.0%
Common 351
 
4.9%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 337
 
5.0%
서 333
 
4.9%
초 238
 
3.5%
터 214
 
3.2%
구 203
 
3.0%
센 189
 
2.8%
스 172
 
2.5%
소 164
 
2.4%
동 156
 
2.3%
공 141
 
2.1%
Other values (267) 4641
68.4%
Common
ValueCountFrequency (%)
_ 123
35.0%
59
16.8%
. 35
 
10.0%
1 34
 
9.7%
3 25
 
7.1%
4 24
 
6.8%
2 22
 
6.3%
) 11
 
3.1%
( 11
 
3.1%
5 2
 
0.6%
Other values (3) 5
 
1.4%
Latin
ValueCountFrequency (%)
L 1
20.0%
H 1
20.0%
B 1
20.0%
S 1
20.0%
X 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6788
95.0%
ASCII 356
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 337
 
5.0%
서 333
 
4.9%
초 238
 
3.5%
터 214
 
3.2%
구 203
 
3.0%
센 189
 
2.8%
스 172
 
2.5%
소 164
 
2.4%
동 156
 
2.3%
공 141
 
2.1%
Other values (267) 4641
68.4%
ASCII
ValueCountFrequency (%)
_ 123
34.6%
59
16.6%
. 35
 
9.8%
1 34
 
9.6%
3 25
 
7.0%
4 24
 
6.7%
2 22
 
6.2%
) 11
 
3.1%
( 11
 
3.1%
5 2
 
0.6%
Other values (8) 10
 
2.8%

도로명주소
Text

MISSING 

Distinct352
Distinct (%)40.0%
Missing33
Missing (%)3.6%
Memory size7.3 KiB
2024-05-18T14:45:28.063711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length38
Mean length13.46311
Min length3

Characters and Unicode

Total characters11861
Distinct characters171
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

Unique271 ?
Unique (%)30.8%

Sample

1st row우면동 379-3
2nd row동작대로
3rd row신반포로
4th row신반포로
5th row강남대로
ValueCountFrequency (%)
서초구 293
 
12.0%
서울특별시 182
 
7.5%
남부순환로 122
 
5.0%
서울시 94
 
3.9%
2584 85
 
3.5%
30 65
 
2.7%
장군마을3길 59
 
2.4%
반포동 43
 
1.8%
헌릉로 41
 
1.7%
260 41
 
1.7%
Other values (465) 1416
58.0%
2024-05-18T14:45:29.486378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1560
 
13.2%
서 675
 
5.7%
로 568
 
4.8%
2 557
 
4.7%
1 543
 
4.6%
3 457
 
3.9%
4 438
 
3.7%
초 388
 
3.3%
0 373
 
3.1%
5 330
 
2.8%
Other values (161) 5972
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6264
52.8%
Decimal Number 3486
29.4%
Space Separator 1560
 
13.2%
Dash Punctuation 294
 
2.5%
Open Punctuation 99
 
0.8%
Close Punctuation 95
 
0.8%
Uppercase Letter 27
 
0.2%
Other Punctuation 20
 
0.2%
Connector Punctuation 14
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 675
 
10.8%
로 568
 
9.1%
초 388
 
6.2%
길 314
 
5.0%
구 297
 
4.7%
울 278
 
4.4%
시 277
 
4.4%
동 277
 
4.4%
남 214
 
3.4%
부 183
 
2.9%
Other values (131) 2793
44.6%
Decimal Number
ValueCountFrequency (%)
2 557
16.0%
1 543
15.6%
3 457
13.1%
4 438
12.6%
0 373
10.7%
5 330
9.5%
8 311
8.9%
6 196
 
5.6%
9 153
 
4.4%
7 128
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
C 8
29.6%
F 6
22.2%
T 4
14.8%
V 4
14.8%
P 1
 
3.7%
X 1
 
3.7%
L 1
 
3.7%
S 1
 
3.7%
B 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 13
65.0%
. 5
 
25.0%
& 1
 
5.0%
; 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
g 1
50.0%
Space Separator
ValueCountFrequency (%)
1560
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 294
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6264
52.8%
Common 5568
46.9%
Latin 29
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 675
 
10.8%
로 568
 
9.1%
초 388
 
6.2%
길 314
 
5.0%
구 297
 
4.7%
울 278
 
4.4%
시 277
 
4.4%
동 277
 
4.4%
남 214
 
3.4%
부 183
 
2.9%
Other values (131) 2793
44.6%
Common
ValueCountFrequency (%)
1560
28.0%
2 557
 
10.0%
1 543
 
9.8%
3 457
 
8.2%
4 438
 
7.9%
0 373
 
6.7%
5 330
 
5.9%
8 311
 
5.6%
- 294
 
5.3%
6 196
 
3.5%
Other values (9) 509
 
9.1%
Latin
ValueCountFrequency (%)
C 8
27.6%
F 6
20.7%
T 4
13.8%
V 4
13.8%
t 1
 
3.4%
P 1
 
3.4%
g 1
 
3.4%
X 1
 
3.4%
L 1
 
3.4%
S 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6264
52.8%
ASCII 5597
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1560
27.9%
2 557
 
10.0%
1 543
 
9.7%
3 457
 
8.2%
4 438
 
7.8%
0 373
 
6.7%
5 330
 
5.9%
8 311
 
5.6%
- 294
 
5.3%
6 196
 
3.5%
Other values (20) 538
 
9.6%
Hangul
ValueCountFrequency (%)
서 675
 
10.8%
로 568
 
9.1%
초 388
 
6.2%
길 314
 
5.0%
구 297
 
4.7%
울 278
 
4.4%
시 277
 
4.4%
동 277
 
4.4%
남 214
 
3.4%
부 183
 
2.9%
Other values (131) 2793
44.6%

상세주소
Text

Distinct749
Distinct (%)82.3%
Missing4
Missing (%)0.4%
Memory size7.3 KiB
2024-05-18T14:45:30.308188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length33
Mean length11.631868
Min length1

Characters and Unicode

Total characters10585
Distinct characters370
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique666 ?
Unique (%)73.2%

Sample

1st row22-607
2nd row22-031
3rd row22-019
4th row22-020
5th row22-001
ValueCountFrequency (%)
2층 87
 
4.3%
3층 60
 
3.0%
1층 53
 
2.6%
4층 53
 
2.6%
cctv관리번호 50
 
2.5%
본관 49
 
2.4%
앞 46
 
2.3%
복도 34
 
1.7%
cctv 34
 
1.7%
뽈대_1 29
 
1.4%
Other values (857) 1526
75.5%
2024-05-18T14:45:31.840187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1111
 
10.5%
2 695
 
6.6%
1 690
 
6.5%
0 464
 
4.4%
층 358
 
3.4%
- 307
 
2.9%
3 285
 
2.7%
관 246
 
2.3%
) 222
 
2.1%
( 222
 
2.1%
Other values (360) 5985
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4520
42.7%
Decimal Number 2957
27.9%
Space Separator 1111
 
10.5%
Uppercase Letter 813
 
7.7%
Dash Punctuation 307
 
2.9%
Close Punctuation 222
 
2.1%
Open Punctuation 222
 
2.1%
Lowercase Letter 177
 
1.7%
Connector Punctuation 168
 
1.6%
Other Punctuation 85
 
0.8%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 358
 
7.9%
관 246
 
5.4%
실 142
 
3.1%
리 120
 
2.7%
원 101
 
2.2%
동 101
 
2.2%
앞 76
 
1.7%
호 74
 
1.6%
옥 74
 
1.6%
내 73
 
1.6%
Other values (314) 3155
69.8%
Uppercase Letter
ValueCountFrequency (%)
C 219
26.9%
T 116
14.3%
V 114
14.0%
F 98
12.1%
P 83
 
10.2%
N 44
 
5.4%
B 38
 
4.7%
A 38
 
4.7%
S 17
 
2.1%
E 14
 
1.7%
Other values (5) 32
 
3.9%
Decimal Number
ValueCountFrequency (%)
2 695
23.5%
1 690
23.3%
0 464
15.7%
3 285
9.6%
5 199
 
6.7%
4 175
 
5.9%
7 156
 
5.3%
6 103
 
3.5%
8 101
 
3.4%
9 89
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
c 82
46.3%
t 39
22.0%
v 37
20.9%
e 6
 
3.4%
p 3
 
1.7%
o 2
 
1.1%
i 2
 
1.1%
n 2
 
1.1%
j 2
 
1.1%
r 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 57
67.1%
: 16
 
18.8%
. 11
 
12.9%
/ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
1111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 307
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 168
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5074
47.9%
Hangul 4521
42.7%
Latin 990
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 358
 
7.9%
관 246
 
5.4%
실 142
 
3.1%
리 120
 
2.7%
원 101
 
2.2%
동 101
 
2.2%
앞 76
 
1.7%
호 74
 
1.6%
옥 74
 
1.6%
내 73
 
1.6%
Other values (315) 3156
69.8%
Latin
ValueCountFrequency (%)
C 219
22.1%
T 116
11.7%
V 114
11.5%
F 98
9.9%
P 83
 
8.4%
c 82
 
8.3%
N 44
 
4.4%
t 39
 
3.9%
B 38
 
3.8%
A 38
 
3.8%
Other values (15) 119
12.0%
Common
ValueCountFrequency (%)
1111
21.9%
2 695
13.7%
1 690
13.6%
0 464
9.1%
- 307
 
6.1%
3 285
 
5.6%
) 222
 
4.4%
( 222
 
4.4%
5 199
 
3.9%
4 175
 
3.4%
Other values (10) 704
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6064
57.3%
Hangul 4520
42.7%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1111
18.3%
2 695
11.5%
1 690
11.4%
0 464
 
7.7%
- 307
 
5.1%
3 285
 
4.7%
) 222
 
3.7%
( 222
 
3.7%
C 219
 
3.6%
5 199
 
3.3%
Other values (35) 1650
27.2%
Hangul
ValueCountFrequency (%)
층 358
 
7.9%
관 246
 
5.4%
실 142
 
3.1%
리 120
 
2.7%
원 101
 
2.2%
동 101
 
2.2%
앞 76
 
1.7%
호 74
 
1.6%
옥 74
 
1.6%
내 73
 
1.6%
Other values (314) 3155
69.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
<NA>
854 
-
 
22
1층
 
10
1
 
6
4층
 
6
Other values (6)
 
16

Length

Max length4
Median length4
Mean length3.8347921
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 854
93.4%
- 22
 
2.4%
1층 10
 
1.1%
1 6
 
0.7%
4층 6
 
0.7%
3층 5
 
0.5%
B1 4
 
0.4%
2층 3
 
0.3%
2 2
 
0.2%
3 1
 
0.1%

Length

2024-05-18T14:45:32.760127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 854
93.4%
22
 
2.4%
1층 10
 
1.1%
1 6
 
0.7%
4층 6
 
0.7%
3층 5
 
0.5%
b1 4
 
0.4%
2층 3
 
0.3%
2 2
 
0.2%
3 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
3. 공원(하천)
160 
7-1-3. 공공 - 시산하기관
118 
7-2-3. 공공 - 동주민센터
103 
1. 주요거리
101 
5-1. 버스정류소(국비)
92 
Other values (13)
340 

Length

Max length21
Median length17
Mean length13.315098
Min length7

Unique

Unique1 ?
Unique (%)0.1%

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) 160
17.5%
7-1-3. 공공 - 시산하기관 118
12.9%
7-2-3. 공공 - 동주민센터 103
11.3%
1. 주요거리 101
11.1%
5-1. 버스정류소(국비) 92
10.1%
7-2-1. 공공 - 구청사 및 별관 77
8.4%
6-3. 복지 - 장애인 69
7.5%
6-2. 복지 - 노인 44
 
4.8%
6-4. 복지 - 아동청소년 32
 
3.5%
5-2. 버스정류소(시비) 31
 
3.4%
Other values (8) 87
9.5%

Length

2024-05-18T14:45:33.335391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
500
16.6%
공공 327
 
10.8%
복지 173
 
5.7%
3 169
 
5.6%
공원(하천 160
 
5.3%
7-1-3 118
 
3.9%
시산하기관 118
 
3.9%
7-2-3 103
 
3.4%
동주민센터 103
 
3.4%
주요거리 101
 
3.4%
Other values (31) 1142
37.9%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
서울시(AP)
306 
디지털뉴딜(LG U+)
270 
자치구
210 
버스정류소(국비)
92 
버스정류소(시비)
31 
Other values (2)
 
5

Length

Max length12
Median length9
Mean length7.8326039
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
서울시(AP) 306
33.5%
디지털뉴딜(LG U+) 270
29.5%
자치구 210
23.0%
버스정류소(국비) 92
 
10.1%
버스정류소(시비) 31
 
3.4%
서울시(LTE) 4
 
0.4%
서울시(공유기) 1
 
0.1%

Length

2024-05-18T14:45:34.039839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:34.606889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울시(ap 306
25.8%
디지털뉴딜(lg 270
22.8%
u 270
22.8%
자치구 210
17.7%
버스정류소(국비 92
 
7.8%
버스정류소(시비 31
 
2.6%
서울시(lte 4
 
0.3%
서울시(공유기 1
 
0.1%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
공공WiFi
681 
과기부WiFi
92 
과기부WiFi(핫플레이스)
 
58
<NA>
 
50
과기부WiFi(복지시설)
 
33

Length

Max length14
Median length6
Mean length6.7516411
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 681
74.5%
과기부WiFi 92
 
10.1%
과기부WiFi(핫플레이스) 58
 
6.3%
<NA> 50
 
5.5%
과기부WiFi(복지시설) 33
 
3.6%

Length

2024-05-18T14:45:35.430429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:35.964841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 681
74.5%
과기부wifi 92
 
10.1%
과기부wifi(핫플레이스 58
 
6.3%
na 50
 
5.5%
과기부wifi(복지시설 33
 
3.6%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
자가망_U무선망
305 
인터넷망_뉴딜용
270 
임대망
225 
전용회선_30M
80 
<NA>
34 

Length

Max length8
Median length8
Mean length6.6203501
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가망_U무선망 305
33.4%
인터넷망_뉴딜용 270
29.5%
임대망 225
24.6%
전용회선_30M 80
 
8.8%
<NA> 34
 
3.7%

Length

2024-05-18T14:45:36.614210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:37.124118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 305
33.4%
인터넷망_뉴딜용 270
29.5%
임대망 225
24.6%
전용회선_30m 80
 
8.8%
na 34
 
3.7%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.3085
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T14:45:37.658857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12019
median2021
Q32022
95-th percentile2023
Maximum2023
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7677262
Coefficient of variation (CV)0.00087497833
Kurtosis-0.89321143
Mean2020.3085
Median Absolute Deviation (MAD)1
Skewness-0.47286365
Sum1846562
Variance3.1248559
MonotonicityNot monotonic
2024-05-18T14:45:38.018579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2022 261
28.6%
2021 177
19.4%
2019 147
16.1%
2020 121
13.2%
2017 99
 
10.8%
2018 60
 
6.6%
2023 49
 
5.4%
ValueCountFrequency (%)
2017 99
 
10.8%
2018 60
 
6.6%
2019 147
16.1%
2020 121
13.2%
2021 177
19.4%
2022 261
28.6%
2023 49
 
5.4%
ValueCountFrequency (%)
2023 49
 
5.4%
2022 261
28.6%
2021 177
19.4%
2020 121
13.2%
2019 147
16.1%
2018 60
 
6.6%
2017 99
 
10.8%

실내외구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
실내
503 
실외
408 
<NA>
 
2
실회
 
1

Length

Max length4
Median length2
Mean length2.0043764
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
실내 503
55.0%
실외 408
44.6%
<NA> 2
 
0.2%
실회 1
 
0.1%

Length

2024-05-18T14:45:38.493635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:38.834952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 503
55.0%
실외 408
44.6%
na 2
 
0.2%
실회 1
 
0.1%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
<NA>
882 
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정
 
30
주무관님 취소
 
1
10G 백홀, WIFI6E
 
1

Length

Max length53
Median length4
Mean length5.6225383
Min length4

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> 882
96.5%
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정 30
 
3.3%
주무관님 취소 1
 
0.1%
10G 백홀, WIFI6E 1
 
0.1%

Length

2024-05-18T14:45:39.244986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:45:39.753873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 882
70.7%
후 60
 
4.8%
6월말 30
 
2.4%
예정 30
 
2.4%
적용 30
 
2.4%
전체 30
 
2.4%
6.20~6.24 30
 
2.4%
cns링크 30
 
2.4%
임시적용 30
 
2.4%
2~3개 30
 
2.4%
Other values (7) 65
 
5.2%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct428
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.398972
Minimum0
Maximum45.498795
Zeros3
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T14:45:40.317335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.455917
Q137.470247
median37.48247
Q337.494106
95-th percentile37.513385
Maximum45.498795
Range45.498795
Interquartile range (IQR)0.0238585

Descriptive statistics

Standard deviation2.198747
Coefficient of variation (CV)0.058791643
Kurtosis274.27739
Mean37.398972
Median Absolute Deviation (MAD)0.0117535
Skewness-16.06491
Sum34182.661
Variance4.8344886
MonotonicityNot monotonic
2024-05-18T14:45:41.041056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.48357 74
 
8.1%
37.464703 59
 
6.5%
37.455917 36
 
3.9%
37.455467 19
 
2.1%
37.47101 18
 
2.0%
37.46193 17
 
1.9%
37.502697 17
 
1.9%
37.47826 15
 
1.6%
37.4795 15
 
1.6%
37.4855 14
 
1.5%
Other values (418) 630
68.9%
ValueCountFrequency (%)
0.0 3
0.3%
37.43071 1
 
0.1%
37.43521 1
 
0.1%
37.44732 1
 
0.1%
37.44779 1
 
0.1%
37.448574 1
 
0.1%
37.449448 1
 
0.1%
37.45287 1
 
0.1%
37.453667 1
 
0.1%
37.45447 1
 
0.1%
ValueCountFrequency (%)
45.498795 1
0.1%
44.498795 1
0.1%
43.498795 1
0.1%
42.498795 1
0.1%
41.498795 1
0.1%
40.498795 1
0.1%
39.498795 1
0.1%
38.498795 1
0.1%
37.62901 1
0.1%
37.52703 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct423
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.64526
Minimum0
Maximum134.99052
Zeros3
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T14:45:41.675804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.98569
Q1127.00685
median127.02402
Q3127.03422
95-th percentile127.06903
Maximum134.99052
Range134.99052
Interquartile range (IQR)0.027371

Descriptive statistics

Standard deviation7.2866724
Coefficient of variation (CV)0.057536086
Kurtosis298.81103
Mean126.64526
Median Absolute Deviation (MAD)0.01307
Skewness-17.284985
Sum115753.77
Variance53.095595
MonotonicityNot monotonic
2024-05-18T14:45:42.272091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0327 74
 
8.1%
127.03241 59
 
6.5%
127.06903 36
 
3.9%
127.068855 19
 
2.1%
127.01095 18
 
2.0%
127.05117 17
 
1.9%
127.0221 17
 
1.9%
127.01931 15
 
1.6%
126.99907 15
 
1.6%
127.022 14
 
1.5%
Other values (413) 630
68.9%
ValueCountFrequency (%)
0.0 3
0.3%
126.98064 1
 
0.1%
126.98105 2
0.2%
126.981804 1
 
0.1%
126.98194 1
 
0.1%
126.98202 1
 
0.1%
126.98207 1
 
0.1%
126.982285 1
 
0.1%
126.98233 1
 
0.1%
126.98253 1
 
0.1%
ValueCountFrequency (%)
134.99052 1
0.1%
133.99052 1
0.1%
132.99052 1
0.1%
131.99052 1
0.1%
130.99052 1
0.1%
129.99052 1
0.1%
128.99052 1
0.1%
127.990524 1
0.1%
127.092186 2
0.2%
127.09145 1
0.1%

작업일자
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18 11:12:57.0
234 
2024-05-18 11:12:59.0
111 
2024-05-18 11:12:58.0
90 
2024-05-18 11:13:00.0
90 
2024-05-18 11:13:05.0
87 
Other values (9)
302 

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 11:12:57.0 234
25.6%
2024-05-18 11:12:59.0 111
12.1%
2024-05-18 11:12:58.0 90
 
9.8%
2024-05-18 11:13:00.0 90
 
9.8%
2024-05-18 11:13:05.0 87
 
9.5%
2024-05-18 11:12:52.0 86
 
9.4%
2024-05-18 11:13:04.0 63
 
6.9%
2024-05-18 11:13:02.0 54
 
5.9%
2024-05-18 11:13:06.0 47
 
5.1%
2024-05-18 11:13:03.0 19
 
2.1%
Other values (4) 33
 
3.6%

Length

2024-05-18T14:45:42.698328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-18 914
50.0%
11:12:57.0 234
 
12.8%
11:12:59.0 111
 
6.1%
11:12:58.0 90
 
4.9%
11:13:00.0 90
 
4.9%
11:13:05.0 87
 
4.8%
11:12:52.0 86
 
4.7%
11:13:04.0 63
 
3.4%
11:13:02.0 54
 
3.0%
11:13:06.0 47
 
2.6%
Other values (5) 52
 
2.8%

Interactions

2024-05-18T14:45:20.584955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:18.782138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:19.704723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:20.875595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:19.150682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:19.988196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:21.134208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:19.414984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:45:20.235412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:45:42.937527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
설치위치(층)1.0000.9671.000NaN1.0001.0000.995NaN0.951NaN1.000
설치유형0.9671.0000.9280.9110.9010.9400.9010.9360.6520.3570.876
설치기관1.0000.9281.0000.7750.8360.7470.546NaN0.1350.0630.985
서비스구분NaN0.9110.7751.0000.8190.6450.3791.0000.0000.0000.936
망종류1.0000.9010.8360.8191.0000.7880.288NaN0.0870.0220.908
설치년도1.0000.9400.7470.6450.7881.0000.727NaN0.2220.1440.924
실내외구분0.9950.9010.5460.3790.2880.7271.0001.0000.0760.0000.652
wifi접속환경NaN0.936NaN1.000NaNNaN1.0001.000NaNNaN0.000
X좌표0.9510.6520.1350.0000.0870.2220.076NaN1.0001.0000.000
Y좌표NaN0.3570.0630.0000.0220.1440.000NaN1.0001.0000.000
작업일자1.0000.8760.9850.9360.9080.9240.6520.0000.0000.0001.000
2024-05-18T14:45:43.295161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형wifi접속환경작업일자실내외구분망종류서비스구분설치기관
설치위치(층)1.0000.711NaN0.9280.8700.9281.0000.928
설치유형0.7111.0000.6880.5310.6690.7490.7560.754
wifi접속환경NaN0.6881.0000.0000.9831.0000.9831.000
작업일자0.9280.5310.0001.0000.4640.7690.8500.807
실내외구분0.8700.6690.9830.4641.0000.2770.3680.433
망종류0.9280.7491.0000.7690.2771.0000.4630.694
서비스구분1.0000.7560.9830.8500.3680.4631.0000.661
설치기관0.9280.7541.0000.8070.4330.6940.6611.000
2024-05-18T14:45:43.622455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.0000.191-0.2750.9280.6120.5330.4820.6450.3921.0000.724
X좌표0.1911.000-0.5380.7520.3830.0910.0000.0820.0221.0000.000
Y좌표-0.275-0.5381.0001.0000.2790.0670.0000.0140.0001.0000.000
설치위치(층)0.9280.7521.0001.0000.7110.9281.0000.9280.8700.0000.928
설치유형0.6120.3830.2790.7111.0000.7540.7560.7490.6690.6880.531
설치기관0.5330.0910.0670.9280.7541.0000.6610.6940.4331.0000.807
서비스구분0.4820.0000.0001.0000.7560.6611.0000.4630.3680.9830.850
망종류0.6450.0820.0140.9280.7490.6940.4631.0000.2771.0000.769
실내외구분0.3920.0220.0000.8700.6690.4330.3680.2771.0000.9830.464
wifi접속환경1.0001.0001.0000.0000.6881.0000.9831.0000.9831.0000.000
작업일자0.7240.0000.0000.9280.5310.8070.8500.7690.4640.0001.000

Missing values

2024-05-18T14:45:21.629130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:45:22.352859image/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.
2024-05-18T14:45:22.789703image/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
0BS100692서초구버스정류소_LH서초아파트우면동 379-322-607<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.46001127.025362024-05-18 11:12:52.0
1BS100693서초구버스정류소_경문고등학교동작대로22-031<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.490437126.982742024-05-18 11:12:52.0
2BS100694서초구버스정류소_고속터미널신반포로22-019<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.506294127.005292024-05-18 11:12:52.0
3BS100695서초구버스정류소_고속터미널신반포로22-020<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.505737127.003792024-05-18 11:12:52.0
4BS100696서초구버스정류소_교육개발원입구강남대로22-001<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47859127.038482024-05-18 11:12:52.0
5BS100697서초구버스정류소_교육개발원입구강남대로22-002<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.477818127.038762024-05-18 11:12:52.0
6BS100698서초구버스정류소_구룡사논현로 3522-304<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.474022127.0481342024-05-18 11:12:52.0
7BS100699서초구버스정류소_구룡사앞양재동 402-1022-303<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47021127.048852024-05-18 11:12:52.0
8BS100700서초구버스정류소_구룡사입구논현로 722-305<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.47209127.0501252024-05-18 11:12:52.0
9BS100701서초구버스정류소_구반포역신반포로22-023<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.501945126.990032024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
904서울5차-1134서초구장안경로당서울특별시 서초구 서초대로55길 13에어컨 옆1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.49593127.015352024-05-18 11:13:06.0
905서울5차-1135서초구반포3동경로당서울특별시 서초구 신반포로15길 28할아버지방 정수기 위2층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.50509126.994852024-05-18 11:13:06.0
906서울5차-1136서초구서초구립기념당서울특별시 서초구 방배중앙로 159-6TV 천장1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.493294126.9860842024-05-18 11:13:06.0
907서울5차-1138서초구방배2동제2경로당서울특별시 서초구 방배천로16길 5TV 옆1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.482277126.983132024-05-18 11:13:06.0
908서울5차-1164서초구잔디마을경로당서울특별시 서초구 매헌로6길58TV 위 천장 내부1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.46625127.035552024-05-18 11:13:06.0
909서울5차-1165서초구염곡경로당서울특별시 서초구 염곡말길9TV 뒤 할아버지방1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.461834127.050552024-05-18 11:13:06.0
910서울5차-1166서초구샘마을경로당서울특별시 서초구 샘마을길8에어컨 위1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.45816127.071492024-05-18 11:13:06.0
911서울5차-1168서초구우면형촌경로당서울특별시 서초구 형촌10길3TV 위 천장 내부1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.46639127.019762024-05-18 11:13:06.0
912서울5차-1170서초구안골마을경로당서울특별시 서초구 내곡동 192-3거울 위1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.456005127.0632552024-05-18 11:13:06.0
913서울5차-1172서초구새쟁이마을경로당서울특별시 서초구 신원동 22-2TV 위 천장 내부1층6-2. 복지 - 노인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.43521127.06992024-05-18 11:13:06.0