Overview

Dataset statistics

Number of variables16
Number of observations1185
Missing cells56
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory151.7 KiB
Average record size in memory131.1 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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-20905/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
실내외구분 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
망종류 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 설치위치(층) and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with 설치위치(층) and 1 other fieldsHigh correlation
설치위치(층) is highly imbalanced (91.2%)Imbalance
서비스구분 is highly imbalanced (67.3%)Imbalance
wifi접속환경 is highly imbalanced (96.7%)Imbalance
도로명주소 has 18 (1.5%) missing valuesMissing
상세주소 has 38 (3.2%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 03:52:05.750748
Analysis finished2024-05-18 03:52:15.700333
Duration9.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-05-18T12:52:16.534916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.1485232
Min length7

Characters and Unicode

Total characters9656
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

Unique1185 ?
Unique (%)100.0%

Sample

1st rowBS100308
2nd rowBS100309
3rd rowBS100310
4th rowBS100311
5th rowBS100312
ValueCountFrequency (%)
bs100308 1
 
0.1%
gr200012 1
 
0.1%
gr200010 1
 
0.1%
gr200009 1
 
0.1%
gr200008 1
 
0.1%
gr200007 1
 
0.1%
gr200006 1
 
0.1%
gr200005 1
 
0.1%
gr200004 1
 
0.1%
gr200003 1
 
0.1%
Other values (1175) 1175
99.2%
2024-05-18T12:52:18.226980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2920
30.2%
1 1080
 
11.2%
R 870
 
9.0%
G 870
 
9.0%
2 724
 
7.5%
3 520
 
5.4%
4 494
 
5.1%
9 288
 
3.0%
5 286
 
3.0%
6 241
 
2.5%
Other values (10) 1363
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6980
72.3%
Uppercase Letter 2096
 
21.7%
Other Letter 339
 
3.5%
Dash Punctuation 241
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2920
41.8%
1 1080
 
15.5%
2 724
 
10.4%
3 520
 
7.4%
4 494
 
7.1%
9 288
 
4.1%
5 286
 
4.1%
6 241
 
3.5%
7 219
 
3.1%
8 208
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
R 870
41.5%
G 870
41.5%
S 94
 
4.5%
W 93
 
4.4%
F 93
 
4.4%
B 76
 
3.6%
Other Letter
ValueCountFrequency (%)
울 146
43.1%
서 146
43.1%
차 47
 
13.9%
Dash Punctuation
ValueCountFrequency (%)
- 241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7221
74.8%
Latin 2096
 
21.7%
Hangul 339
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2920
40.4%
1 1080
 
15.0%
2 724
 
10.0%
3 520
 
7.2%
4 494
 
6.8%
9 288
 
4.0%
5 286
 
4.0%
6 241
 
3.3%
- 241
 
3.3%
7 219
 
3.0%
Latin
ValueCountFrequency (%)
R 870
41.5%
G 870
41.5%
S 94
 
4.5%
W 93
 
4.4%
F 93
 
4.4%
B 76
 
3.6%
Hangul
ValueCountFrequency (%)
울 146
43.1%
서 146
43.1%
차 47
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9317
96.5%
Hangul 339
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2920
31.3%
1 1080
 
11.6%
R 870
 
9.3%
G 870
 
9.3%
2 724
 
7.8%
3 520
 
5.6%
4 494
 
5.3%
9 288
 
3.1%
5 286
 
3.1%
6 241
 
2.6%
Other values (7) 1024
 
11.0%
Hangul
ValueCountFrequency (%)
울 146
43.1%
서 146
43.1%
차 47
 
13.9%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
구로구
1185 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구로구 1185
100.0%

Length

2024-05-18T12:52:18.844480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:19.254639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구로구 1185
100.0%

와이파이명
Text

Distinct480
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-05-18T12:52:19.795314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.4877637
Min length3

Characters and Unicode

Total characters8873
Distinct characters366
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

Unique352 ?
Unique (%)29.7%

Sample

1st row버스정류소_개봉역.영화아파트
2nd row버스정류소_개봉역.한마을아파트
3rd row버스정류소_거리공원
4th row버스정류소_경인중학교.개봉사거리
5th row버스정류소_경인중학교.개봉사거리
ValueCountFrequency (%)
생활지역 111
 
8.4%
구로구청 78
 
5.9%
버스정류소 64
 
4.8%
주민센터 29
 
2.2%
구로동 22
 
1.7%
구로종합사회복지관 21
 
1.6%
시립구로청소년센터 20
 
1.5%
궁동종합사회복지관 19
 
1.4%
안양천공원 19
 
1.4%
화원종합사회복지관 18
 
1.4%
Other values (495) 922
69.7%
2024-05-18T12:52:21.067547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 452
 
5.1%
로 318
 
3.6%
지 279
 
3.1%
소 264
 
3.0%
동 263
 
3.0%
류 255
 
2.9%
스 235
 
2.6%
정 211
 
2.4%
버 208
 
2.3%
역 186
 
2.1%
Other values (356) 6202
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7639
86.1%
Decimal Number 676
 
7.6%
Space Separator 140
 
1.6%
Connector Punctuation 139
 
1.6%
Dash Punctuation 111
 
1.3%
Uppercase Letter 89
 
1.0%
Open Punctuation 26
 
0.3%
Close Punctuation 26
 
0.3%
Other Punctuation 23
 
0.3%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 452
 
5.9%
로 318
 
4.2%
지 279
 
3.7%
소 264
 
3.5%
동 263
 
3.4%
류 255
 
3.3%
스 235
 
3.1%
정 211
 
2.8%
버 208
 
2.7%
역 186
 
2.4%
Other values (319) 4968
65.0%
Uppercase Letter
ValueCountFrequency (%)
C 29
32.6%
T 15
16.9%
V 14
15.7%
S 6
 
6.7%
K 6
 
6.7%
G 5
 
5.6%
I 4
 
4.5%
P 2
 
2.2%
B 2
 
2.2%
L 1
 
1.1%
Other values (5) 5
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 160
23.7%
2 111
16.4%
7 96
14.2%
3 59
 
8.7%
4 55
 
8.1%
5 52
 
7.7%
0 40
 
5.9%
9 35
 
5.2%
8 34
 
5.0%
6 34
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
i 1
25.0%
o 1
25.0%
s 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 21
91.3%
/ 1
 
4.3%
, 1
 
4.3%
Space Separator
ValueCountFrequency (%)
140
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7639
86.1%
Common 1141
 
12.9%
Latin 93
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 452
 
5.9%
로 318
 
4.2%
지 279
 
3.7%
소 264
 
3.5%
동 263
 
3.4%
류 255
 
3.3%
스 235
 
3.1%
정 211
 
2.8%
버 208
 
2.7%
역 186
 
2.4%
Other values (319) 4968
65.0%
Latin
ValueCountFrequency (%)
C 29
31.2%
T 15
16.1%
V 14
15.1%
S 6
 
6.5%
K 6
 
6.5%
G 5
 
5.4%
I 4
 
4.3%
P 2
 
2.2%
B 2
 
2.2%
l 1
 
1.1%
Other values (9) 9
 
9.7%
Common
ValueCountFrequency (%)
1 160
14.0%
140
12.3%
_ 139
12.2%
2 111
9.7%
- 111
9.7%
7 96
8.4%
3 59
 
5.2%
4 55
 
4.8%
5 52
 
4.6%
0 40
 
3.5%
Other values (8) 178
15.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7639
86.1%
ASCII 1234
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 452
 
5.9%
로 318
 
4.2%
지 279
 
3.7%
소 264
 
3.5%
동 263
 
3.4%
류 255
 
3.3%
스 235
 
3.1%
정 211
 
2.8%
버 208
 
2.7%
역 186
 
2.4%
Other values (319) 4968
65.0%
ASCII
ValueCountFrequency (%)
1 160
13.0%
140
11.3%
_ 139
11.3%
2 111
9.0%
- 111
9.0%
7 96
 
7.8%
3 59
 
4.8%
4 55
 
4.5%
5 52
 
4.2%
0 40
 
3.2%
Other values (27) 271
22.0%

도로명주소
Text

MISSING 

Distinct742
Distinct (%)63.6%
Missing18
Missing (%)1.5%
Memory size9.4 KiB
2024-05-18T12:52:21.913894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length11.724079
Min length3

Characters and Unicode

Total characters13682
Distinct characters223
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique631 ?
Unique (%)54.1%

Sample

1st row경인로
2nd row고척제1동 69-9
3rd row구로5 49-4
4th row개봉동 156-5
5th row개봉동 146-24
ValueCountFrequency (%)
구로동 312
 
10.7%
구로구 191
 
6.6%
서울특별시 143
 
4.9%
개봉동 102
 
3.5%
435 78
 
2.7%
오류동 74
 
2.5%
고척동 70
 
2.4%
신도림동 61
 
2.1%
가리봉동 42
 
1.4%
항동 31
 
1.1%
Other values (905) 1806
62.1%
2024-05-18T12:52:23.554018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1746
 
12.8%
1 1064
 
7.8%
로 923
 
6.7%
동 912
 
6.7%
구 796
 
5.8%
- 758
 
5.5%
2 670
 
4.9%
3 575
 
4.2%
4 528
 
3.9%
5 405
 
3.0%
Other values (213) 5305
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6116
44.7%
Decimal Number 4885
35.7%
Space Separator 1746
 
12.8%
Dash Punctuation 758
 
5.5%
Open Punctuation 68
 
0.5%
Close Punctuation 68
 
0.5%
Other Punctuation 23
 
0.2%
Uppercase Letter 16
 
0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 923
 
15.1%
동 912
 
14.9%
구 796
 
13.0%
길 201
 
3.3%
봉 176
 
2.9%
오 165
 
2.7%
서 150
 
2.5%
울 149
 
2.4%
시 148
 
2.4%
별 143
 
2.3%
Other values (187) 2353
38.5%
Decimal Number
ValueCountFrequency (%)
1 1064
21.8%
2 670
13.7%
3 575
11.8%
4 528
10.8%
5 405
 
8.3%
6 386
 
7.9%
7 375
 
7.7%
8 315
 
6.4%
0 297
 
6.1%
9 270
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 4
25.0%
C 4
25.0%
T 3
18.8%
I 2
12.5%
V 2
12.5%
K 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 15
65.2%
# 3
 
13.0%
/ 3
 
13.0%
. 2
 
8.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
1746
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 758
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7548
55.2%
Hangul 6116
44.7%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 923
 
15.1%
동 912
 
14.9%
구 796
 
13.0%
길 201
 
3.3%
봉 176
 
2.9%
오 165
 
2.7%
서 150
 
2.5%
울 149
 
2.4%
시 148
 
2.4%
별 143
 
2.3%
Other values (187) 2353
38.5%
Common
ValueCountFrequency (%)
1746
23.1%
1 1064
14.1%
- 758
10.0%
2 670
 
8.9%
3 575
 
7.6%
4 528
 
7.0%
5 405
 
5.4%
6 386
 
5.1%
7 375
 
5.0%
8 315
 
4.2%
Other values (8) 726
9.6%
Latin
ValueCountFrequency (%)
B 4
22.2%
C 4
22.2%
T 3
16.7%
I 2
11.1%
V 2
11.1%
Ⅱ 1
 
5.6%
K 1
 
5.6%
Ⅲ 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7564
55.3%
Hangul 6116
44.7%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1746
23.1%
1 1064
14.1%
- 758
10.0%
2 670
 
8.9%
3 575
 
7.6%
4 528
 
7.0%
5 405
 
5.4%
6 386
 
5.1%
7 375
 
5.0%
8 315
 
4.2%
Other values (14) 742
9.8%
Hangul
ValueCountFrequency (%)
로 923
 
15.1%
동 912
 
14.9%
구 796
 
13.0%
길 201
 
3.3%
봉 176
 
2.9%
오 165
 
2.7%
서 150
 
2.5%
울 149
 
2.4%
시 148
 
2.4%
별 143
 
2.3%
Other values (187) 2353
38.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

상세주소
Text

MISSING 

Distinct880
Distinct (%)76.7%
Missing38
Missing (%)3.2%
Memory size9.4 KiB
2024-05-18T12:52:24.237716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length8.6843941
Min length1

Characters and Unicode

Total characters9961
Distinct characters321
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

Unique765 ?
Unique (%)66.7%

Sample

1st row17-009
2nd row17-010
3rd row17-107
4th row17-011
5th row17-012
ValueCountFrequency (%)
cctv 323
 
14.4%
천장 76
 
3.4%
가로등주 66
 
2.9%
복도 37
 
1.7%
36
 
1.6%
옥내1 34
 
1.5%
3층 28
 
1.2%
2층 25
 
1.1%
구로동 24
 
1.1%
구로 23
 
1.0%
Other values (910) 1568
70.0%
2024-05-18T12:52:25.756810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1098
 
11.0%
C 662
 
6.6%
1 636
 
6.4%
T 335
 
3.4%
2 332
 
3.3%
V 331
 
3.3%
7 327
 
3.3%
로 287
 
2.9%
3 265
 
2.7%
- 228
 
2.3%
Other values (311) 5460
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4165
41.8%
Decimal Number 2598
26.1%
Uppercase Letter 1465
 
14.7%
Space Separator 1098
 
11.0%
Dash Punctuation 228
 
2.3%
Open Punctuation 134
 
1.3%
Close Punctuation 134
 
1.3%
Connector Punctuation 81
 
0.8%
Other Punctuation 51
 
0.5%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 287
 
6.9%
구 170
 
4.1%
장 151
 
3.6%
지 141
 
3.4%
관 133
 
3.2%
층 119
 
2.9%
동 119
 
2.9%
복 118
 
2.8%
내 110
 
2.6%
옥 101
 
2.4%
Other values (273) 2716
65.2%
Uppercase Letter
ValueCountFrequency (%)
C 662
45.2%
T 335
22.9%
V 331
22.6%
F 99
 
6.8%
B 11
 
0.8%
P 9
 
0.6%
I 4
 
0.3%
A 4
 
0.3%
K 3
 
0.2%
E 2
 
0.1%
Other values (3) 5
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 636
24.5%
2 332
12.8%
7 327
12.6%
3 265
10.2%
4 213
 
8.2%
6 193
 
7.4%
0 193
 
7.4%
5 178
 
6.9%
9 139
 
5.4%
8 122
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 37
72.5%
. 6
 
11.8%
, 4
 
7.8%
& 2
 
3.9%
; 2
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
t 2
28.6%
g 2
28.6%
o 1
14.3%
l 1
14.3%
e 1
14.3%
Space Separator
ValueCountFrequency (%)
1098
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4324
43.4%
Hangul 4165
41.8%
Latin 1472
 
14.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 287
 
6.9%
구 170
 
4.1%
장 151
 
3.6%
지 141
 
3.4%
관 133
 
3.2%
층 119
 
2.9%
동 119
 
2.9%
복 118
 
2.8%
내 110
 
2.6%
옥 101
 
2.4%
Other values (273) 2716
65.2%
Common
ValueCountFrequency (%)
1098
25.4%
1 636
14.7%
2 332
 
7.7%
7 327
 
7.6%
3 265
 
6.1%
- 228
 
5.3%
4 213
 
4.9%
6 193
 
4.5%
0 193
 
4.5%
5 178
 
4.1%
Other values (10) 661
15.3%
Latin
ValueCountFrequency (%)
C 662
45.0%
T 335
22.8%
V 331
22.5%
F 99
 
6.7%
B 11
 
0.7%
P 9
 
0.6%
I 4
 
0.3%
A 4
 
0.3%
K 3
 
0.2%
t 2
 
0.1%
Other values (8) 12
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5796
58.2%
Hangul 4165
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1098
18.9%
C 662
11.4%
1 636
11.0%
T 335
 
5.8%
2 332
 
5.7%
V 331
 
5.7%
7 327
 
5.6%
3 265
 
4.6%
- 228
 
3.9%
4 213
 
3.7%
Other values (28) 1369
23.6%
Hangul
ValueCountFrequency (%)
로 287
 
6.9%
구 170
 
4.1%
장 151
 
3.6%
지 141
 
3.4%
관 133
 
3.2%
층 119
 
2.9%
동 119
 
2.9%
복 118
 
2.8%
내 110
 
2.6%
옥 101
 
2.4%
Other values (273) 2716
65.2%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
<NA>
1151 
구로 디지털단지
 
25
5층
 
3
2층
 
2
3층
 
2

Length

Max length8
Median length4
Mean length4.0691983
Min length2

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> 1151
97.1%
구로 디지털단지 25
 
2.1%
5층 3
 
0.3%
2층 2
 
0.2%
3층 2
 
0.2%
4층 2
 
0.2%

Length

2024-05-18T12:52:26.336768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:26.757031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1151
95.1%
구로 25
 
2.1%
디지털단지 25
 
2.1%
5층 3
 
0.2%
2층 2
 
0.2%
3층 2
 
0.2%
4층 2
 
0.2%

설치유형
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1. 주요거리
359 
3. 공원(하천)
168 
5-2. 버스정류소(시비)
144 
7-2-1. 공공 - 구청사 및 별관
78 
6-1. 복지 - 사회
69 
Other values (15)
367 

Length

Max length21
Median length20
Mean length11.275105
Min length7

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row5-1. 버스정류소(국비)
2nd row5-1. 버스정류소(국비)
3rd row5-1. 버스정류소(국비)
4th row5-1. 버스정류소(국비)
5th row5-1. 버스정류소(국비)

Common Values

ValueCountFrequency (%)
1. 주요거리 359
30.3%
3. 공원(하천) 168
14.2%
5-2. 버스정류소(시비) 144
12.2%
7-2-1. 공공 - 구청사 및 별관 78
 
6.6%
6-1. 복지 - 사회 69
 
5.8%
5-1. 버스정류소(국비) 58
 
4.9%
7-2-3. 공공 - 동주민센터 54
 
4.6%
2. 전통시장 50
 
4.2%
6-4. 복지 - 아동청소년 41
 
3.5%
6-3. 복지 - 장애인 32
 
2.7%
Other values (10) 132
 
11.1%

Length

2024-05-18T12:52:27.187701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
381
 
11.4%
1 359
 
10.7%
주요거리 359
 
10.7%
복지 191
 
5.7%
공공 190
 
5.7%
3 168
 
5.0%
공원(하천 168
 
5.0%
버스정류소(시비 144
 
4.3%
5-2 144
 
4.3%
및 107
 
3.2%
Other values (36) 1135
33.9%

설치기관
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
자치구
628 
자치구에스넷1차
242 
디지털뉴딜(KT)
96 
서울시(AP)
87 
버스정류소(국비)
 
58
Other values (3)
74 

Length

Max length12
Median length3
Mean length5.5907173
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자치구 628
53.0%
자치구에스넷1차 242
 
20.4%
디지털뉴딜(KT) 96
 
8.1%
서울시(AP) 87
 
7.3%
버스정류소(국비) 58
 
4.9%
디지털뉴딜(LG U+) 50
 
4.2%
버스정류소(시비) 18
 
1.5%
서울시(공유기) 6
 
0.5%

Length

2024-05-18T12:52:27.643157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:27.997612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 628
50.9%
자치구에스넷1차 242
 
19.6%
디지털뉴딜(kt 96
 
7.8%
서울시(ap 87
 
7.0%
버스정류소(국비 58
 
4.7%
디지털뉴딜(lg 50
 
4.0%
u 50
 
4.0%
버스정류소(시비 18
 
1.5%
서울시(공유기 6
 
0.5%

서비스구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
공공WiFi
1019 
과기부WiFi(복지시설)
 
98
과기부WiFi
 
58
<NA>
 
9
과기부WiFi(핫플레이스)
 
1

Length

Max length14
Median length6
Mean length6.6194093
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 1019
86.0%
과기부WiFi(복지시설) 98
 
8.3%
과기부WiFi 58
 
4.9%
<NA> 9
 
0.8%
과기부WiFi(핫플레이스) 1
 
0.1%

Length

2024-05-18T12:52:28.387581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:28.764846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 1019
86.0%
과기부wifi(복지시설 98
 
8.3%
과기부wifi 58
 
4.9%
na 9
 
0.8%
과기부wifi(핫플레이스 1
 
0.1%

망종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
자가망_U무선망
888 
인터넷망_뉴딜용
146 
임대망
133 
<NA>
 
18

Length

Max length8
Median length8
Mean length7.3780591
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가망_U무선망 888
74.9%
인터넷망_뉴딜용 146
 
12.3%
임대망 133
 
11.2%
<NA> 18
 
1.5%

Length

2024-05-18T12:52:29.335155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:29.718412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 888
74.9%
인터넷망_뉴딜용 146
 
12.3%
임대망 133
 
11.2%
na 18
 
1.5%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.492
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T12:52:30.126250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2017
Q12019
median2020
Q32022
95-th percentile2023
Maximum2023
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9482697
Coefficient of variation (CV)0.00096425511
Kurtosis-0.91288859
Mean2020.492
Median Absolute Deviation (MAD)2
Skewness-0.33694749
Sum2394283
Variance3.7957549
MonotonicityNot monotonic
2024-05-18T12:52:30.621406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020 307
25.9%
2023 250
21.1%
2022 182
15.4%
2021 139
11.7%
2018 125
10.5%
2017 104
 
8.8%
2019 68
 
5.7%
2016 10
 
0.8%
ValueCountFrequency (%)
2016 10
 
0.8%
2017 104
 
8.8%
2018 125
10.5%
2019 68
 
5.7%
2020 307
25.9%
2021 139
11.7%
2022 182
15.4%
2023 250
21.1%
ValueCountFrequency (%)
2023 250
21.1%
2022 182
15.4%
2021 139
11.7%
2020 307
25.9%
2019 68
 
5.7%
2018 125
10.5%
2017 104
 
8.8%
2016 10
 
0.8%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
실외
780 
실내
405 

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 780
65.8%
실내 405
34.2%

Length

2024-05-18T12:52:31.005654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:31.287315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 780
65.8%
실내 405
34.2%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
<NA>
1181 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
4

Length

Max length27
Median length4
Mean length4.0776371
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> 1181
99.7%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 4
 
0.3%

Length

2024-05-18T12:52:31.590164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:52:31.930478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1181
98.3%
보안접속 4
 
0.3%
임시적용(머큐리 4
 
0.3%
proxy 4
 
0.3%
서버 4
 
0.3%
개발중 4
 
0.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct809
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.494714
Minimum37.474777
Maximum37.515167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T12:52:32.426979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.474777
5-th percentile37.48193
Q137.489418
median37.49543
Q337.500057
95-th percentile37.507732
Maximum37.515167
Range0.04039
Interquartile range (IQR)0.010639

Descriptive statistics

Standard deviation0.0078122472
Coefficient of variation (CV)0.00020835596
Kurtosis-0.41695419
Mean37.494714
Median Absolute Deviation (MAD)0.005394
Skewness0.026701335
Sum44431.236
Variance6.1031206 × 10-5
MonotonicityNot monotonic
2024-05-18T12:52:33.231088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.49543 79
 
6.7%
37.486824 21
 
1.8%
37.499134 19
 
1.6%
37.49733 18
 
1.5%
37.496716 16
 
1.4%
37.48245 14
 
1.2%
37.500088 12
 
1.0%
37.491356 12
 
1.0%
37.50118 12
 
1.0%
37.48993 11
 
0.9%
Other values (799) 971
81.9%
ValueCountFrequency (%)
37.474777 1
0.1%
37.474995 1
0.1%
37.47522 1
0.1%
37.475933 1
0.1%
37.476032 1
0.1%
37.476578 1
0.1%
37.477356 1
0.1%
37.478634 1
0.1%
37.47864 1
0.1%
37.47866 1
0.1%
ValueCountFrequency (%)
37.515167 1
 
0.1%
37.514507 1
 
0.1%
37.514095 1
 
0.1%
37.513798 1
 
0.1%
37.5133 5
0.4%
37.513012 1
 
0.1%
37.512814 2
 
0.2%
37.512684 1
 
0.1%
37.512653 1
 
0.1%
37.512215 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct810
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.86513
Minimum126.80943
Maximum126.902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-05-18T12:52:34.070535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.80943
5-th percentile126.82487
Q1126.84257
median126.87234
Q3126.88751
95-th percentile126.89296
Maximum126.902
Range0.092575
Interquartile range (IQR)0.044935

Descriptive statistics

Standard deviation0.023968576
Coefficient of variation (CV)0.00018892958
Kurtosis-1.3231964
Mean126.86513
Median Absolute Deviation (MAD)0.01738
Skewness-0.38133669
Sum150335.18
Variance0.00057449262
MonotonicityNot monotonic
2024-05-18T12:52:34.593433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.88751 78
 
6.6%
126.89082 21
 
1.8%
126.82957 19
 
1.6%
126.880135 18
 
1.5%
126.823265 16
 
1.4%
126.88932 16
 
1.4%
126.889725 14
 
1.2%
126.84125 12
 
1.0%
126.84115 11
 
0.9%
126.88341 11
 
0.9%
Other values (800) 969
81.8%
ValueCountFrequency (%)
126.809425 1
0.1%
126.81654 1
0.1%
126.81676 2
0.2%
126.81746 1
0.1%
126.81766 1
0.1%
126.81899 1
0.1%
126.819 1
0.1%
126.820595 1
0.1%
126.82062 1
0.1%
126.82149 1
0.1%
ValueCountFrequency (%)
126.902 1
0.1%
126.90184 1
0.1%
126.90178 1
0.1%
126.901726 1
0.1%
126.90155 1
0.1%
126.90143 1
0.1%
126.90128 1
0.1%
126.9 1
0.1%
126.899956 1
0.1%
126.89933 1
0.1%

작업일자
Date

Distinct14
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
Minimum2024-05-18 11:12:52
Maximum2024-05-18 11:13:06
2024-05-18T12:52:35.507987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:36.174983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

Interactions

2024-05-18T12:52:12.388943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:09.619401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:11.107432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:12.790073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:10.079290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:11.708290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:13.164402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:10.617663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:52:12.077892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T12:52:36.709156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.8221.000NaN1.0001.0001.0000.8220.8221.000
설치유형0.8221.0000.8900.9540.9370.8191.0000.6910.7070.889
설치기관1.0000.8901.0000.9800.9470.8270.8480.2760.3740.958
서비스구분NaN0.9540.9801.0000.7030.6760.6350.2200.2700.915
망종류1.0000.9370.9470.7031.0000.7650.3520.2920.3691.000
설치년도1.0000.8190.8270.6760.7651.0000.6830.2860.3820.906
실내외구분1.0001.0000.8480.6350.3520.6831.0000.4020.3280.817
X좌표0.8220.6910.2760.2200.2920.2860.4021.0000.6040.474
Y좌표0.8220.7070.3740.2700.3690.3820.3280.6041.0000.550
작업일자1.0000.8890.9580.9151.0000.9060.8170.4740.5501.000
2024-05-18T12:52:37.232009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실내외구분wifi접속환경서비스구분설치위치(층)설치유형설치기관망종류
실내외구분1.0001.0000.4410.9520.9810.6660.561
wifi접속환경1.0001.0001.000NaN1.0001.0001.000
서비스구분0.4411.0001.0001.0000.7460.8080.740
설치위치(층)0.952NaN1.0001.0000.7750.9520.952
설치유형0.9811.0000.7460.7751.0000.6170.841
설치기관0.6661.0000.8080.9520.6171.0000.967
망종류0.5611.0000.7400.9520.8410.9671.000
2024-05-18T12:52:37.835873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.0000.121-0.0670.9520.4950.5850.5380.7010.7411.000
X좌표0.1211.000-0.0390.7750.2890.1350.1330.1820.3081.000
Y좌표-0.067-0.0391.0000.7750.3010.1880.1640.2370.2511.000
설치위치(층)0.9520.7750.7751.0000.7750.9521.0000.9520.9520.000
설치유형0.4950.2890.3010.7751.0000.6170.7460.8410.9811.000
설치기관0.5850.1350.1880.9520.6171.0000.8080.9670.6661.000
서비스구분0.5380.1330.1641.0000.7460.8081.0000.7400.4411.000
망종류0.7010.1820.2370.9520.8410.9670.7401.0000.5611.000
실내외구분0.7410.3080.2510.9520.9810.6660.4410.5611.0001.000
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T12:52:13.715168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T12:52:14.795388image/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.
2024-05-18T12:52:15.325696image/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
0BS100308구로구버스정류소_개봉역.영화아파트경인로17-009<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.496796126.86062024-05-18 11:12:52.0
1BS100309구로구버스정류소_개봉역.한마을아파트고척제1동 69-917-010<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.49648126.862052024-05-18 11:12:52.0
2BS100310구로구버스정류소_거리공원구로5 49-417-107<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.49991126.8915252024-05-18 11:12:52.0
3BS100311구로구버스정류소_경인중학교.개봉사거리개봉동 156-517-011<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.497353126.855522024-05-18 11:12:52.0
4BS100312구로구버스정류소_경인중학교.개봉사거리개봉동 146-2417-012<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.49717126.855132024-05-18 11:12:52.0
5BS100313구로구버스정류소_고대구로병원후문구로2 80-2417-113<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.49311126.884352024-05-18 11:12:52.0
6BS100314구로구버스정류소_구로1동우체국구일로4길 6517-237<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.491486126.874662024-05-18 11:12:52.0
7BS100315구로구버스정류소_구로도서관.대성스카이렉스구로5 107-217-108<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.499676126.891222024-05-18 11:12:52.0
8BS100316구로구버스정류소_구로디지털단지역시흥대로17-013<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.4831126.901552024-05-18 11:12:52.0
9BS100317구로구버스정류소_구로우체국.이펜하우스3단지후문천왕동 32-417-701<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.4817126.842142024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1175서울4차-6077구로구구로소방서서울특별시 구로구 경인로 408(고척1동), 2층 민원실2F_민원실_1<NA>7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실내<NA>37.497807126.865232024-05-18 11:13:05.0
1176서울5차-0133구로구구로구치매안심센터분소서울특별시 구로구 오류1동 54-5사무실5층7-2-2. 공공 - 구의회 및 보건소디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.49546126.844112024-05-18 11:13:06.0
1177서울5차-0133-1구로구구로구치매안심센터분소서울특별시 구로구 오류1동 54-5가족카페 기억다방5층7-2-2. 공공 - 구의회 및 보건소디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.49546126.844112024-05-18 11:13:06.0
1178서울5차-0133-2구로구구로구치매안심센터분소서울특별시 구로구 오류1동 54-5프로그램실5층7-2-2. 공공 - 구의회 및 보건소디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.49546126.844112024-05-18 11:13:06.0
1179서울5차-0804구로구길가온혜명서울특별시 구로구 오리로22나길 14201호실2층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499897126.83042024-05-18 11:13:06.0
1180서울5차-0804-1구로구길가온혜명서울특별시 구로구 오리로22나길 14301호실3층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499897126.83042024-05-18 11:13:06.0
1181서울5차-0804-2구로구길가온혜명서울특별시 구로구 오리로22나길 14401호실4층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499897126.83042024-05-18 11:13:06.0
1182서울5차-0805구로구길가온혜명서울특별시 구로구 오리로22나길 14202호실2층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499958126.830342024-05-18 11:13:06.0
1183서울5차-0805-1구로구길가온혜명서울특별시 구로구 오리로22나길 14302호실3층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499958126.830342024-05-18 11:13:06.0
1184서울5차-0805-2구로구길가온혜명서울특별시 구로구 오리로22나길 14402호실4층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.499958126.830342024-05-18 11:13:06.0