Overview

Dataset statistics

Number of variables16
Number of observations922
Missing cells63
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.1 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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-20893/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
실내외구분 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치유형 and 5 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치기관 and 5 other fieldsHigh correlation
설치위치(층) is highly overall correlated with Y좌표 and 2 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 8 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 망종류 and 3 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with 설치위치(층) and 1 other fieldsHigh correlation
설치위치(층) is highly imbalanced (63.7%)Imbalance
wifi접속환경 is highly imbalanced (96.8%)Imbalance
도로명주소 has 27 (2.9%) missing valuesMissing
상세주소 has 36 (3.9%) missing valuesMissing
Y좌표 is highly skewed (γ1 = 30.3414191)Skewed
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 06:05:00.127461
Analysis finished2024-05-18 06:05:05.912481
Duration5.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct922
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18T15:05:06.275569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.1800434
Min length7

Characters and Unicode

Total characters7542
Distinct characters24
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

Unique922 ?
Unique (%)100.0%

Sample

1st rowARI00191
2nd rowARI00192
3rd rowARI00193
4th rowARI00194
5th rowARI00195
ValueCountFrequency (%)
ari00191 1
 
0.1%
서울-3224-2 1
 
0.1%
서울-3686 1
 
0.1%
서울-3225-2 1
 
0.1%
서울-3226 1
 
0.1%
서울-3226-1 1
 
0.1%
서울-3226-2 1
 
0.1%
서울-3227 1
 
0.1%
서울-3227-1 1
 
0.1%
서울-3227-2 1
 
0.1%
Other values (912) 912
98.9%
2024-05-18T15:05:07.018973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1448
19.2%
1 735
 
9.7%
- 562
 
7.5%
2 512
 
6.8%
4 502
 
6.7%
울 494
 
6.5%
서 494
 
6.5%
3 329
 
4.4%
6 312
 
4.1%
5 265
 
3.5%
Other values (14) 1889
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4845
64.2%
Other Letter 1236
 
16.4%
Uppercase Letter 899
 
11.9%
Dash Punctuation 562
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1448
29.9%
1 735
15.2%
2 512
 
10.6%
4 502
 
10.4%
3 329
 
6.8%
6 312
 
6.4%
5 265
 
5.5%
9 253
 
5.2%
7 245
 
5.1%
8 244
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
G 236
26.3%
J 232
25.8%
W 106
11.8%
F 106
11.8%
S 75
 
8.3%
B 59
 
6.6%
R 27
 
3.0%
I 27
 
3.0%
A 27
 
3.0%
H 4
 
0.4%
Other Letter
ValueCountFrequency (%)
울 494
40.0%
서 494
40.0%
차 248
20.1%
Dash Punctuation
ValueCountFrequency (%)
- 562
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5407
71.7%
Hangul 1236
 
16.4%
Latin 899
 
11.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1448
26.8%
1 735
13.6%
- 562
 
10.4%
2 512
 
9.5%
4 502
 
9.3%
3 329
 
6.1%
6 312
 
5.8%
5 265
 
4.9%
9 253
 
4.7%
7 245
 
4.5%
Latin
ValueCountFrequency (%)
G 236
26.3%
J 232
25.8%
W 106
11.8%
F 106
11.8%
S 75
 
8.3%
B 59
 
6.6%
R 27
 
3.0%
I 27
 
3.0%
A 27
 
3.0%
H 4
 
0.4%
Hangul
ValueCountFrequency (%)
울 494
40.0%
서 494
40.0%
차 248
20.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6306
83.6%
Hangul 1236
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1448
23.0%
1 735
11.7%
- 562
 
8.9%
2 512
 
8.1%
4 502
 
8.0%
3 329
 
5.2%
6 312
 
4.9%
5 265
 
4.2%
9 253
 
4.0%
7 245
 
3.9%
Other values (11) 1143
18.1%
Hangul
ValueCountFrequency (%)
울 494
40.0%
서 494
40.0%
차 248
20.1%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
광진구
922 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광진구 922
100.0%

Length

2024-05-18T15:05:07.256586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:07.409250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진구 922
100.0%

와이파이명
Text

Distinct217
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18T15:05:07.708339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.9522777
Min length2

Characters and Unicode

Total characters7332
Distinct characters241
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

Unique110 ?
Unique (%)11.9%

Sample

1st row서울물연구원
2nd row서울물연구원
3rd row서울물연구원
4th row서울물연구원
5th row서울물연구원
ValueCountFrequency (%)
뚝섬한강공원 111
 
10.5%
로데오거리 59
 
5.6%
건대입구역(양꼬치거리 59
 
5.6%
및 59
 
5.6%
광진구청(미가로 37
 
3.5%
중랑천뚝방길 36
 
3.4%
강변역 33
 
3.1%
중곡역 28
 
2.7%
어린이대공원 25
 
2.4%
자양종합사회복지관 24
 
2.3%
Other values (215) 583
55.3%
2024-05-18T15:05:08.596110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 224
 
3.1%
구 219
 
3.0%
역 189
 
2.6%
광 185
 
2.5%
지 163
 
2.2%
공 159
 
2.2%
양 158
 
2.2%
강 153
 
2.1%
동 150
 
2.0%
뚝 149
 
2.0%
Other values (231) 5583
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6734
91.8%
Space Separator 132
 
1.8%
Close Punctuation 119
 
1.6%
Open Punctuation 119
 
1.6%
Decimal Number 115
 
1.6%
Connector Punctuation 65
 
0.9%
Dash Punctuation 22
 
0.3%
Uppercase Letter 18
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 224
 
3.3%
구 219
 
3.3%
역 189
 
2.8%
광 185
 
2.7%
지 163
 
2.4%
공 159
 
2.4%
양 158
 
2.3%
강 153
 
2.3%
동 150
 
2.2%
뚝 149
 
2.2%
Other values (208) 4985
74.0%
Decimal Number
ValueCountFrequency (%)
1 31
27.0%
2 24
20.9%
3 18
15.7%
4 13
11.3%
5 7
 
6.1%
9 6
 
5.2%
6 6
 
5.2%
0 6
 
5.2%
8 2
 
1.7%
7 2
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
F 6
33.3%
S 3
16.7%
K 3
16.7%
C 2
 
11.1%
B 2
 
11.1%
T 1
 
5.6%
V 1
 
5.6%
Space Separator
ValueCountFrequency (%)
132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6734
91.8%
Common 580
 
7.9%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 224
 
3.3%
구 219
 
3.3%
역 189
 
2.8%
광 185
 
2.7%
지 163
 
2.4%
공 159
 
2.4%
양 158
 
2.3%
강 153
 
2.3%
동 150
 
2.2%
뚝 149
 
2.2%
Other values (208) 4985
74.0%
Common
ValueCountFrequency (%)
132
22.8%
) 119
20.5%
( 119
20.5%
_ 65
11.2%
1 31
 
5.3%
2 24
 
4.1%
- 22
 
3.8%
3 18
 
3.1%
4 13
 
2.2%
. 8
 
1.4%
Other values (6) 29
 
5.0%
Latin
ValueCountFrequency (%)
F 6
33.3%
S 3
16.7%
K 3
16.7%
C 2
 
11.1%
B 2
 
11.1%
T 1
 
5.6%
V 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6734
91.8%
ASCII 598
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 224
 
3.3%
구 219
 
3.3%
역 189
 
2.8%
광 185
 
2.7%
지 163
 
2.4%
공 159
 
2.4%
양 158
 
2.3%
강 153
 
2.3%
동 150
 
2.2%
뚝 149
 
2.2%
Other values (208) 4985
74.0%
ASCII
ValueCountFrequency (%)
132
22.1%
) 119
19.9%
( 119
19.9%
_ 65
10.9%
1 31
 
5.2%
2 24
 
4.0%
- 22
 
3.7%
3 18
 
3.0%
4 13
 
2.2%
. 8
 
1.3%
Other values (13) 47
 
7.9%

도로명주소
Text

MISSING 

Distinct290
Distinct (%)32.4%
Missing27
Missing (%)2.9%
Memory size7.3 KiB
2024-05-18T15:05:09.137024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length15.553073
Min length4

Characters and Unicode

Total characters13920
Distinct characters160
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

Unique136 ?
Unique (%)15.2%

Sample

1st row천호대로 716-10
2nd row천호대로 716-10
3rd row천호대로 716-10
4th row천호대로 716-10
5th row천호대로 716-10
ValueCountFrequency (%)
광진구 654
21.4%
서울특별시 486
 
15.9%
강변북로 90
 
2.9%
139 86
 
2.8%
자양로 65
 
2.1%
천호대로 65
 
2.1%
자양동 49
 
1.6%
구의동 49
 
1.6%
능동로 46
 
1.5%
117 45
 
1.5%
Other values (402) 1424
46.6%
2024-05-18T15:05:10.043019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2164
 
15.5%
구 754
 
5.4%
광 692
 
5.0%
로 671
 
4.8%
진 657
 
4.7%
1 638
 
4.6%
서 505
 
3.6%
시 500
 
3.6%
울 500
 
3.6%
별 489
 
3.5%
Other values (150) 6350
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8210
59.0%
Decimal Number 3112
 
22.4%
Space Separator 2164
 
15.5%
Dash Punctuation 289
 
2.1%
Other Punctuation 55
 
0.4%
Open Punctuation 41
 
0.3%
Close Punctuation 41
 
0.3%
Uppercase Letter 5
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 754
 
9.2%
광 692
 
8.4%
로 671
 
8.2%
진 657
 
8.0%
서 505
 
6.2%
시 500
 
6.1%
울 500
 
6.1%
별 489
 
6.0%
특 486
 
5.9%
동 369
 
4.5%
Other values (128) 2587
31.5%
Decimal Number
ValueCountFrequency (%)
1 638
20.5%
3 465
14.9%
2 383
12.3%
6 357
11.5%
7 270
8.7%
4 253
 
8.1%
5 219
 
7.0%
9 195
 
6.3%
8 170
 
5.5%
0 162
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
V 1
20.0%
T 1
20.0%
F 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 44
80.0%
. 8
 
14.5%
# 3
 
5.5%
Space Separator
ValueCountFrequency (%)
2164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8210
59.0%
Common 5705
41.0%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 754
 
9.2%
광 692
 
8.4%
로 671
 
8.2%
진 657
 
8.0%
서 505
 
6.2%
시 500
 
6.1%
울 500
 
6.1%
별 489
 
6.0%
특 486
 
5.9%
동 369
 
4.5%
Other values (128) 2587
31.5%
Common
ValueCountFrequency (%)
2164
37.9%
1 638
 
11.2%
3 465
 
8.2%
2 383
 
6.7%
6 357
 
6.3%
- 289
 
5.1%
7 270
 
4.7%
4 253
 
4.4%
5 219
 
3.8%
9 195
 
3.4%
Other values (8) 472
 
8.3%
Latin
ValueCountFrequency (%)
C 2
40.0%
V 1
20.0%
T 1
20.0%
F 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8210
59.0%
ASCII 5710
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2164
37.9%
1 638
 
11.2%
3 465
 
8.1%
2 383
 
6.7%
6 357
 
6.3%
- 289
 
5.1%
7 270
 
4.7%
4 253
 
4.4%
5 219
 
3.8%
9 195
 
3.4%
Other values (12) 477
 
8.4%
Hangul
ValueCountFrequency (%)
구 754
 
9.2%
광 692
 
8.4%
로 671
 
8.2%
진 657
 
8.0%
서 505
 
6.2%
시 500
 
6.1%
울 500
 
6.1%
별 489
 
6.0%
특 486
 
5.9%
동 369
 
4.5%
Other values (128) 2587
31.5%

상세주소
Text

MISSING 

Distinct704
Distinct (%)79.5%
Missing36
Missing (%)3.9%
Memory size7.3 KiB
2024-05-18T15:05:10.561063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length22
Mean length11.454853
Min length1

Characters and Unicode

Total characters10149
Distinct characters324
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique619 ?
Unique (%)69.9%

Sample

1st row본관 1F
2nd row본관 2F
3rd row본관 2F
4th row본관 2F
5th row본관 2F
ValueCountFrequency (%)
로데오거리 59
 
3.3%
및 59
 
3.3%
건대입구역(양꼬치거리 59
 
3.3%
광진구청(미가로 37
 
2.1%
중랑천 36
 
2.0%
뚝방길 36
 
2.0%
강변역(동서울터미널 28
 
1.6%
천장 25
 
1.4%
내부 23
 
1.3%
1층 23
 
1.3%
Other values (655) 1411
78.6%
2024-05-18T15:05:11.364700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
910
 
9.0%
( 433
 
4.3%
) 433
 
4.3%
1 425
 
4.2%
_ 307
 
3.0%
옥 248
 
2.4%
2 246
 
2.4%
3 238
 
2.3%
로 214
 
2.1%
외 194
 
1.9%
Other values (314) 6501
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6029
59.4%
Decimal Number 1658
 
16.3%
Space Separator 910
 
9.0%
Open Punctuation 433
 
4.3%
Close Punctuation 433
 
4.3%
Connector Punctuation 307
 
3.0%
Uppercase Letter 130
 
1.3%
Dash Punctuation 109
 
1.1%
Lowercase Letter 93
 
0.9%
Other Punctuation 46
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 248
 
4.1%
로 214
 
3.5%
외 194
 
3.2%
리 152
 
2.5%
거 149
 
2.5%
구 144
 
2.4%
실 138
 
2.3%
가 117
 
1.9%
장 116
 
1.9%
역 116
 
1.9%
Other values (280) 4441
73.7%
Decimal Number
ValueCountFrequency (%)
1 425
25.6%
2 246
14.8%
3 238
14.4%
0 188
11.3%
5 166
 
10.0%
4 132
 
8.0%
6 100
 
6.0%
8 64
 
3.9%
7 57
 
3.4%
9 42
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
F 100
76.9%
B 11
 
8.5%
T 6
 
4.6%
K 5
 
3.8%
P 3
 
2.3%
E 2
 
1.5%
S 2
 
1.5%
U 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
b 40
43.0%
c 23
24.7%
a 15
 
16.1%
t 6
 
6.5%
v 6
 
6.5%
o 2
 
2.2%
p 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 28
60.9%
, 16
34.8%
/ 2
 
4.3%
Space Separator
ValueCountFrequency (%)
910
100.0%
Open Punctuation
ValueCountFrequency (%)
( 433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 433
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6029
59.4%
Common 3897
38.4%
Latin 223
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 248
 
4.1%
로 214
 
3.5%
외 194
 
3.2%
리 152
 
2.5%
거 149
 
2.5%
구 144
 
2.4%
실 138
 
2.3%
가 117
 
1.9%
장 116
 
1.9%
역 116
 
1.9%
Other values (280) 4441
73.7%
Common
ValueCountFrequency (%)
910
23.4%
( 433
11.1%
) 433
11.1%
1 425
10.9%
_ 307
 
7.9%
2 246
 
6.3%
3 238
 
6.1%
0 188
 
4.8%
5 166
 
4.3%
4 132
 
3.4%
Other values (9) 419
10.8%
Latin
ValueCountFrequency (%)
F 100
44.8%
b 40
 
17.9%
c 23
 
10.3%
a 15
 
6.7%
B 11
 
4.9%
t 6
 
2.7%
v 6
 
2.7%
T 6
 
2.7%
K 5
 
2.2%
P 3
 
1.3%
Other values (5) 8
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6029
59.4%
ASCII 4120
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
910
22.1%
( 433
10.5%
) 433
10.5%
1 425
10.3%
_ 307
 
7.5%
2 246
 
6.0%
3 238
 
5.8%
0 188
 
4.6%
5 166
 
4.0%
4 132
 
3.2%
Other values (24) 642
15.6%
Hangul
ValueCountFrequency (%)
옥 248
 
4.1%
로 214
 
3.5%
외 194
 
3.2%
리 152
 
2.5%
거 149
 
2.5%
구 144
 
2.4%
실 138
 
2.3%
가 117
 
1.9%
장 116
 
1.9%
역 116
 
1.9%
Other values (280) 4441
73.7%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
<NA>
722 
2층
 
43
1층
 
38
실외
 
38
3층
 
33
Other values (9)
 
48

Length

Max length4
Median length4
Mean length3.5770065
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 722
78.3%
2층 43
 
4.7%
1층 38
 
4.1%
실외 38
 
4.1%
3층 33
 
3.6%
4층 18
 
2.0%
실내 13
 
1.4%
B1층 6
 
0.7%
5층 4
 
0.4%
6층 2
 
0.2%
Other values (4) 5
 
0.5%

Length

2024-05-18T15:05:11.630065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 722
78.3%
2층 43
 
4.7%
1층 38
 
4.1%
실외 38
 
4.1%
3층 33
 
3.6%
4층 18
 
2.0%
실내 13
 
1.4%
b1층 6
 
0.7%
5층 4
 
0.4%
6층 2
 
0.2%
Other values (4) 5
 
0.5%

설치유형
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
3. 공원(하천)
199 
1. 주요거리
184 
6-2. 복지 - 노인
78 
6-1. 복지 - 사회
74 
7-2-1. 공공 - 구청사 및 별관
73 
Other values (13)
314 

Length

Max length20
Median length17
Mean length11.387202
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 (%)
3. 공원(하천) 199
21.6%
1. 주요거리 184
20.0%
6-2. 복지 - 노인 78
 
8.5%
6-1. 복지 - 사회 74
 
8.0%
7-2-1. 공공 - 구청사 및 별관 73
 
7.9%
4. 문화관광 63
 
6.8%
7-1-3. 공공 - 시산하기관 54
 
5.9%
7-2-3. 공공 - 동주민센터 48
 
5.2%
6-4. 복지 - 아동청소년 47
 
5.1%
5-1. 버스정류소(국비) 43
 
4.7%
Other values (8) 59
 
6.4%

Length

2024-05-18T15:05:12.175276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
390
 
14.1%
복지 211
 
7.6%
3 205
 
7.4%
공원(하천 199
 
7.2%
1 184
 
6.6%
주요거리 184
 
6.6%
공공 179
 
6.5%
6-2 78
 
2.8%
노인 78
 
2.8%
사회 74
 
2.7%
Other values (30) 988
35.7%

설치기관
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
디지털뉴딜(LG U+)
255 
디지털뉴딜(KT)
239 
자치구
232 
서울시(AP)
115 
버스정류소(국비)
43 
Other values (3)
38 

Length

Max length12
Median length9
Mean length8.0466377
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 (%)
디지털뉴딜(LG U+) 255
27.7%
디지털뉴딜(KT) 239
25.9%
자치구 232
25.2%
서울시(AP) 115
12.5%
버스정류소(국비) 43
 
4.7%
서울시(공유기) 18
 
2.0%
버스정류소(시비) 16
 
1.7%
서울시(LTE) 4
 
0.4%

Length

2024-05-18T15:05:12.629206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:12.976063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
디지털뉴딜(lg 255
21.7%
u 255
21.7%
디지털뉴딜(kt 239
20.3%
자치구 232
19.7%
서울시(ap 115
9.8%
버스정류소(국비 43
 
3.7%
서울시(공유기 18
 
1.5%
버스정류소(시비 16
 
1.4%
서울시(lte 4
 
0.3%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
공공WiFi
623 
과기부WiFi(핫플레이스)
190 
과기부WiFi(복지시설)
 
56
과기부WiFi
 
43
<NA>
 
10

Length

Max length14
Median length6
Mean length8.0986985
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 623
67.6%
과기부WiFi(핫플레이스) 190
 
20.6%
과기부WiFi(복지시설) 56
 
6.1%
과기부WiFi 43
 
4.7%
<NA> 10
 
1.1%

Length

2024-05-18T15:05:13.470213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:13.833805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 623
67.6%
과기부wifi(핫플레이스 190
 
20.6%
과기부wifi(복지시설 56
 
6.1%
과기부wifi 43
 
4.7%
na 10
 
1.1%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
인터넷망_뉴딜용
494 
자가망_U무선망
212 
임대망
177 
자가망_수도사업소망
 
23
<NA>
 
16

Length

Max length10
Median length8
Mean length7.0206074
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 494
53.6%
자가망_U무선망 212
23.0%
임대망 177
 
19.2%
자가망_수도사업소망 23
 
2.5%
<NA> 16
 
1.7%

Length

2024-05-18T15:05:14.352684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:14.578883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 494
53.6%
자가망_u무선망 212
23.0%
임대망 177
 
19.2%
자가망_수도사업소망 23
 
2.5%
na 16
 
1.7%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021.1529
Minimum2014
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T15:05:14.806164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2017
Q12021
median2022
Q32022
95-th percentile2023
Maximum2024
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.677415
Coefficient of variation (CV)0.00082992977
Kurtosis4.1538329
Mean2021.1529
Median Absolute Deviation (MAD)0
Skewness-1.9410346
Sum1863503
Variance2.8137211
MonotonicityNot monotonic
2024-05-18T15:05:15.183941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2022 548
59.4%
2021 123
 
13.3%
2019 70
 
7.6%
2020 62
 
6.7%
2017 46
 
5.0%
2023 38
 
4.1%
2014 13
 
1.4%
2018 12
 
1.3%
2024 10
 
1.1%
ValueCountFrequency (%)
2014 13
 
1.4%
2017 46
 
5.0%
2018 12
 
1.3%
2019 70
 
7.6%
2020 62
 
6.7%
2021 123
 
13.3%
2022 548
59.4%
2023 38
 
4.1%
2024 10
 
1.1%
ValueCountFrequency (%)
2024 10
 
1.1%
2023 38
 
4.1%
2022 548
59.4%
2021 123
 
13.3%
2020 62
 
6.7%
2019 70
 
7.6%
2018 12
 
1.3%
2017 46
 
5.0%
2014 13
 
1.4%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
실외
492 
실내
430 

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 (%)
실외 492
53.4%
실내 430
46.6%

Length

2024-05-18T15:05:15.589423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:15.852442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 492
53.4%
실내 430
46.6%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
<NA>
919 
10G 백홀, WIFI6E
 
3

Length

Max length14
Median length4
Mean length4.032538
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> 919
99.7%
10G 백홀, WIFI6E 3
 
0.3%

Length

2024-05-18T15:05:16.250002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:05:16.541656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 919
99.0%
10g 3
 
0.3%
백홀 3
 
0.3%
wifi6e 3
 
0.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct391
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.545382
Minimum37.517822
Maximum37.57105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T15:05:16.844622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.517822
5-th percentile37.52925
Q137.537652
median37.544826
Q337.552416
95-th percentile37.566521
Maximum37.57105
Range0.053228
Interquartile range (IQR)0.01476425

Descriptive statistics

Standard deviation0.011349047
Coefficient of variation (CV)0.00030227544
Kurtosis-0.55984092
Mean37.545382
Median Absolute Deviation (MAD)0.0075185
Skewness0.34927835
Sum34616.842
Variance0.00012880087
MonotonicityNot monotonic
2024-05-18T15:05:17.144005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.538532 47
 
5.1%
37.547 23
 
2.5%
37.546318 23
 
2.5%
37.556686 20
 
2.2%
37.532898 17
 
1.8%
37.552345 14
 
1.5%
37.541107 12
 
1.3%
37.551456 12
 
1.3%
37.551155 10
 
1.1%
37.539394 9
 
1.0%
Other values (381) 735
79.7%
ValueCountFrequency (%)
37.517822 6
0.7%
37.524445 5
0.5%
37.527195 1
 
0.1%
37.527847 1
 
0.1%
37.52785 2
 
0.2%
37.52837 1
 
0.1%
37.528374 3
0.3%
37.528454 3
0.3%
37.5285 1
 
0.1%
37.52855 1
 
0.1%
ValueCountFrequency (%)
37.57105 3
0.3%
37.570522 3
0.3%
37.57028 1
 
0.1%
37.570107 2
0.2%
37.57009 1
 
0.1%
37.570072 3
0.3%
37.569637 3
0.3%
37.56924 1
 
0.1%
37.56917 1
 
0.1%
37.568752 2
0.2%

Y좌표
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct383
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12507
Minimum126.88268
Maximum172.108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-05-18T15:05:17.614428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.88268
5-th percentile127.0634
Q1127.07159
median127.08165
Q3127.08878
95-th percentile127.10619
Maximum172.108
Range45.22532
Interquartile range (IQR)0.01719

Descriptive statistics

Standard deviation1.483416
Coefficient of variation (CV)0.011668949
Kurtosis921.06855
Mean127.12507
Median Absolute Deviation (MAD)0.008125
Skewness30.341419
Sum117209.32
Variance2.2005229
MonotonicityNot monotonic
2024-05-18T15:05:18.026413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.082375 47
 
5.1%
127.091896 23
 
2.5%
127.10655 23
 
2.5%
127.08484 20
 
2.2%
127.07523 17
 
1.8%
126.89989 14
 
1.5%
127.097336 12
 
1.3%
127.07718 11
 
1.2%
127.07159 10
 
1.1%
127.06672 9
 
1.0%
Other values (373) 736
79.8%
ValueCountFrequency (%)
126.88268 1
 
0.1%
126.89395 3
 
0.3%
126.89595 3
 
0.3%
126.89989 14
1.5%
126.90213 4
 
0.4%
126.97085 6
0.7%
127.01593 5
 
0.5%
127.059326 1
 
0.1%
127.06 2
 
0.2%
127.06225 1
 
0.1%
ValueCountFrequency (%)
172.108 1
 
0.1%
127.1108 1
 
0.1%
127.11057 4
 
0.4%
127.10829 4
 
0.4%
127.108284 1
 
0.1%
127.10798 3
 
0.3%
127.10683 1
 
0.1%
127.10682 7
 
0.8%
127.10675 1
 
0.1%
127.10655 23
2.5%

작업일자
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-05-18 11:12:54.0
232 
2024-05-18 11:13:04.0
177 
2024-05-18 11:13:01.0
150 
2024-05-18 11:13:03.0
89 
2024-05-18 11:13:05.0
67 
Other values (9)
207 

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 11:12:54.0 232
25.2%
2024-05-18 11:13:04.0 177
19.2%
2024-05-18 11:13:01.0 150
16.3%
2024-05-18 11:13:03.0 89
 
9.7%
2024-05-18 11:13:05.0 67
 
7.3%
2024-05-18 11:12:52.0 66
 
7.2%
2024-05-18 11:12:59.0 61
 
6.6%
2024-05-18 11:13:00.0 31
 
3.4%
2024-05-18 11:12:58.0 14
 
1.5%
2024-05-18 11:12:57.0 12
 
1.3%
Other values (4) 23
 
2.5%

Length

2024-05-18T15:05:18.352381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-18 922
50.0%
11:12:54.0 232
 
12.6%
11:13:04.0 177
 
9.6%
11:13:01.0 150
 
8.1%
11:13:03.0 89
 
4.8%
11:13:05.0 67
 
3.6%
11:12:52.0 66
 
3.6%
11:12:59.0 61
 
3.3%
11:13:00.0 31
 
1.7%
11:12:58.0 14
 
0.8%
Other values (5) 35
 
1.9%

Interactions

2024-05-18T15:05:03.763295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:02.192008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:02.972536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:04.009342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:02.451923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:03.237956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:04.269160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:02.723819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:05:03.596208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T15:05:18.580411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.6580.317NaN0.3170.5560.9210.277NaN0.317
설치유형0.6581.0000.9270.9370.8900.7840.9910.6500.6080.896
설치기관0.3170.9271.0000.9800.8190.8690.8130.4770.0000.971
서비스구분NaN0.9370.9801.0000.7670.7440.7870.4730.0000.924
망종류0.3170.8900.8190.7671.0000.9360.7180.4680.0530.966
설치년도0.5560.7840.8690.7440.9361.0000.6730.3720.0000.833
실내외구분0.9210.9910.8130.7870.7180.6731.0000.3440.0000.791
X좌표0.2770.6500.4770.4730.4680.3720.3441.0000.0000.564
Y좌표NaN0.6080.0000.0000.0530.0000.0000.0001.0000.000
작업일자0.3170.8960.9710.9240.9660.8330.7910.5640.0001.000
2024-05-18T15:05:18.912276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실내외구분설치기관작업일자망종류설치유형설치위치(층)wifi접속환경서비스구분
실내외구분1.0000.6310.6360.5120.9120.8961.0000.578
설치기관0.6311.0000.8890.7260.7330.2861.0000.806
작업일자0.6360.8891.0000.7600.5730.2861.0000.801
망종류0.5120.7260.7601.0000.7270.2861.0000.404
설치유형0.9120.7330.5730.7271.0000.3511.0000.812
설치위치(층)0.8960.2860.2860.2860.3511.000NaN1.000
wifi접속환경1.0001.0001.0001.0001.000NaN1.0001.000
서비스구분0.5780.8060.8010.4040.8121.0001.0001.000
2024-05-18T15:05:19.230241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.000-0.011-0.0830.2850.4590.4750.4130.6770.5211.0000.530
X좌표-0.0111.0000.2770.1260.3130.2510.3010.2970.2631.0000.267
Y좌표-0.0830.2771.0001.0000.4810.0000.0000.0350.0001.0000.000
설치위치(층)0.2850.1261.0001.0000.3510.2861.0000.2860.8960.0000.286
설치유형0.4590.3130.4810.3511.0000.7330.8120.7270.9121.0000.573
설치기관0.4750.2510.0000.2860.7331.0000.8060.7260.6311.0000.889
서비스구분0.4130.3010.0001.0000.8120.8061.0000.4040.5781.0000.801
망종류0.6770.2970.0350.2860.7270.7260.4041.0000.5121.0000.760
실내외구분0.5210.2630.0000.8960.9120.6310.5780.5121.0001.0000.636
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.000
작업일자0.5300.2670.0000.2860.5730.8890.8010.7600.6361.0001.000

Missing values

2024-05-18T15:05:04.651060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T15:05:05.228840image/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.
2024-05-18T15:05:05.649057image/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
0ARI00191광진구서울물연구원천호대로 716-10본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
1ARI00192광진구서울물연구원천호대로 716-10본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
2ARI00193광진구서울물연구원천호대로 716-10본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
3ARI00194광진구서울물연구원천호대로 716-10본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
4ARI00195광진구서울물연구원천호대로 716-10본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
5ARI00196광진구서울물연구원천호대로 716-10본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
6ARI00197광진구서울물연구원천호대로 716-10본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
7ARI00198광진구서울물연구원천호대로 716-10본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
8ARI00199광진구서울물연구원천호대로 716-10본관 4F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
9ARI00200광진구서울물연구원천호대로 716-10별관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.547127.0918962024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
912서울5차-0641광진구광진정보도서관서울특별시 광진구 아차산로 78길 90라운지 옆 외벽2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.551083127.110572024-05-18 11:13:06.0
913서울5차-0643광진구광진정보도서관서울특별시 광진구 아차산로 78길 90영상감상실1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.551083127.110572024-05-18 11:13:06.0
914서울5차-0643-1광진구광진정보도서관서울특별시 광진구 아차산로 78길 90라운지 안내 앞2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.551083127.110572024-05-18 11:13:06.0
915서울5차-0643-2광진구광진정보도서관서울특별시 광진구 아차산로 78길 90영상감상실 좌측지하1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.551083127.110572024-05-18 11:13:06.0
916서울5차-0644광진구아차산숲속도서관서울특별시 광진구 워커힐로 127여자화장실 천장내부2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.552837127.1012024-05-18 11:13:06.0
917서울5차-0645광진구아차산숲속도서관서울특별시 광진구 워커힐로 127무인카페위 천장내부2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.552837127.1012024-05-18 11:13:06.0
918서울5차-0646광진구아차산숲속도서관서울특별시 광진구 워커힐로 127로비1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.552837127.1012024-05-18 11:13:06.0
919서울5차-0646-1광진구아차산숲속도서관서울특별시 광진구 워커힐로 127복도2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.552837127.1012024-05-18 11:13:06.0
920서울5차-0647광진구자양한강도서관서울특별시 광진구 뚝섬로52길 66복도 엘리베이터 옆 천장내부3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.52936127.077412024-05-18 11:13:06.0
921서울5차-0648광진구자양한강도서관서울특별시 광진구 뚝섬로52길 66스마트도서관 옆1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.5292127.0777052024-05-18 11:13:06.0