Overview

Dataset statistics

Number of variables16
Number of observations1088
Missing cells229
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory139.3 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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20903/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
서비스구분 is highly overall correlated with 설치유형 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
작업일자 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치기관 and 5 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 8 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 3 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (82.0%)Imbalance
wifi접속환경 is highly imbalanced (90.1%)Imbalance
도로명주소 has 47 (4.3%) missing valuesMissing
상세주소 has 182 (16.7%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 00:54:07.215220
Analysis finished2024-05-18 00:54:16.217135
Duration9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1088
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
2024-05-18T09:54:16.608128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.3943015
Min length7

Characters and Unicode

Total characters9133
Distinct characters23
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

Unique1088 ?
Unique (%)100.0%

Sample

1st rowARI00109
2nd rowARI00112
3rd rowARI00113
4th rowARI00114
5th rowARI00115
ValueCountFrequency (%)
ari00109 1
 
0.1%
yc230059 1
 
0.1%
yc230054 1
 
0.1%
yc230055 1
 
0.1%
yc230056 1
 
0.1%
yc230057 1
 
0.1%
yc230058 1
 
0.1%
ari00112 1
 
0.1%
yc230061 1
 
0.1%
ari00119 1
 
0.1%
Other values (1078) 1078
99.1%
2024-05-18T09:54:17.552814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2060
22.6%
1 1121
12.3%
2 575
 
6.3%
- 521
 
5.7%
Y 491
 
5.4%
C 491
 
5.4%
5 462
 
5.1%
4 385
 
4.2%
서 352
 
3.9%
울 352
 
3.9%
Other values (13) 2323
25.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6177
67.6%
Uppercase Letter 1539
 
16.9%
Other Letter 896
 
9.8%
Dash Punctuation 521
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2060
33.3%
1 1121
18.1%
2 575
 
9.3%
5 462
 
7.5%
4 385
 
6.2%
6 340
 
5.5%
3 335
 
5.4%
7 317
 
5.1%
9 299
 
4.8%
8 283
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
Y 491
31.9%
C 491
31.9%
S 156
 
10.1%
W 116
 
7.5%
F 116
 
7.5%
B 109
 
7.1%
R 20
 
1.3%
I 20
 
1.3%
A 20
 
1.3%
Other Letter
ValueCountFrequency (%)
서 352
39.3%
울 352
39.3%
차 192
21.4%
Dash Punctuation
ValueCountFrequency (%)
- 521
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6698
73.3%
Latin 1539
 
16.9%
Hangul 896
 
9.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2060
30.8%
1 1121
16.7%
2 575
 
8.6%
- 521
 
7.8%
5 462
 
6.9%
4 385
 
5.7%
6 340
 
5.1%
3 335
 
5.0%
7 317
 
4.7%
9 299
 
4.5%
Latin
ValueCountFrequency (%)
Y 491
31.9%
C 491
31.9%
S 156
 
10.1%
W 116
 
7.5%
F 116
 
7.5%
B 109
 
7.1%
R 20
 
1.3%
I 20
 
1.3%
A 20
 
1.3%
Hangul
ValueCountFrequency (%)
서 352
39.3%
울 352
39.3%
차 192
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8237
90.2%
Hangul 896
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2060
25.0%
1 1121
13.6%
2 575
 
7.0%
- 521
 
6.3%
Y 491
 
6.0%
C 491
 
6.0%
5 462
 
5.6%
4 385
 
4.7%
6 340
 
4.1%
3 335
 
4.1%
Other values (10) 1456
17.7%
Hangul
ValueCountFrequency (%)
서 352
39.3%
울 352
39.3%
차 192
21.4%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
양천구
1088 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양천구 1088
100.0%

Length

2024-05-18T09:54:17.957386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:18.289572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 1088
100.0%

와이파이명
Text

Distinct319
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
2024-05-18T09:54:18.599106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.0496324
Min length3

Characters and Unicode

Total characters8758
Distinct characters273
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

Unique184 ?
Unique (%)16.9%

Sample

1st row강서수도사업소
2nd row강서수도사업소
3rd row강서수도사업소
4th row강서수도사업소
5th row강서수도사업소
ValueCountFrequency (%)
서남병원 72
 
6.4%
목동주경기장 50
 
4.4%
양천구청 43
 
3.8%
목동야구장 40
 
3.6%
신월동걷고싶은거리 25
 
2.2%
신월종합사회복지관 24
 
2.1%
강서수도사업소 20
 
1.8%
신월6동주민센터 19
 
1.7%
목동로데오 19
 
1.7%
신월3동 18
 
1.6%
Other values (315) 796
70.7%
2024-05-18T09:54:19.325647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 460
 
5.3%
신 371
 
4.2%
목 299
 
3.4%
서 248
 
2.8%
터 225
 
2.6%
소 221
 
2.5%
센 212
 
2.4%
정 208
 
2.4%
양 194
 
2.2%
월 190
 
2.2%
Other values (263) 6130
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8294
94.7%
Decimal Number 199
 
2.3%
Connector Punctuation 110
 
1.3%
Other Punctuation 40
 
0.5%
Space Separator 38
 
0.4%
Close Punctuation 32
 
0.4%
Open Punctuation 32
 
0.4%
Uppercase Letter 9
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 460
 
5.5%
신 371
 
4.5%
목 299
 
3.6%
서 248
 
3.0%
터 225
 
2.7%
소 221
 
2.7%
센 212
 
2.6%
정 208
 
2.5%
양 194
 
2.3%
월 190
 
2.3%
Other values (246) 5666
68.3%
Decimal Number
ValueCountFrequency (%)
3 55
27.6%
4 31
15.6%
1 29
14.6%
6 24
12.1%
2 24
12.1%
5 23
11.6%
7 8
 
4.0%
0 5
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
C 4
44.4%
B 3
33.3%
S 2
22.2%
Connector Punctuation
ValueCountFrequency (%)
_ 110
100.0%
Other Punctuation
ValueCountFrequency (%)
. 40
100.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8294
94.7%
Common 455
 
5.2%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 460
 
5.5%
신 371
 
4.5%
목 299
 
3.6%
서 248
 
3.0%
터 225
 
2.7%
소 221
 
2.7%
센 212
 
2.6%
정 208
 
2.5%
양 194
 
2.3%
월 190
 
2.3%
Other values (246) 5666
68.3%
Common
ValueCountFrequency (%)
_ 110
24.2%
3 55
12.1%
. 40
 
8.8%
38
 
8.4%
) 32
 
7.0%
( 32
 
7.0%
4 31
 
6.8%
1 29
 
6.4%
6 24
 
5.3%
2 24
 
5.3%
Other values (4) 40
 
8.8%
Latin
ValueCountFrequency (%)
C 4
44.4%
B 3
33.3%
S 2
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8294
94.7%
ASCII 464
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 460
 
5.5%
신 371
 
4.5%
목 299
 
3.6%
서 248
 
3.0%
터 225
 
2.7%
소 221
 
2.7%
센 212
 
2.6%
정 208
 
2.5%
양 194
 
2.3%
월 190
 
2.3%
Other values (246) 5666
68.3%
ASCII
ValueCountFrequency (%)
_ 110
23.7%
3 55
11.9%
. 40
 
8.6%
38
 
8.2%
) 32
 
6.9%
( 32
 
6.9%
4 31
 
6.7%
1 29
 
6.2%
6 24
 
5.2%
2 24
 
5.2%
Other values (7) 49
10.6%

도로명주소
Text

MISSING 

Distinct427
Distinct (%)41.0%
Missing47
Missing (%)4.3%
Memory size8.6 KiB
2024-05-18T09:54:19.915296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length14.318924
Min length5

Characters and Unicode

Total characters14906
Distinct characters172
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

Unique319 ?
Unique (%)30.6%

Sample

1st row목동동로 151
2nd row목동동로 151
3rd row목동동로 151
4th row목동동로 151
5th row목동동로 151
ValueCountFrequency (%)
양천구 361
 
11.3%
서울특별시 232
 
7.2%
신정동 200
 
6.2%
목동동로 130
 
4.1%
서울시 120
 
3.7%
안양천로 107
 
3.3%
939 105
 
3.3%
신월동 91
 
2.8%
목동서로 91
 
2.8%
신정이펜1로 74
 
2.3%
Other values (523) 1690
52.8%
2024-05-18T09:54:20.892900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2161
 
14.5%
로 890
 
6.0%
동 871
 
5.8%
1 711
 
4.8%
3 567
 
3.8%
양 517
 
3.5%
천 495
 
3.3%
신 483
 
3.2%
목 471
 
3.2%
서 456
 
3.1%
Other values (162) 7284
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8207
55.1%
Decimal Number 3668
24.6%
Space Separator 2161
 
14.5%
Open Punctuation 302
 
2.0%
Close Punctuation 301
 
2.0%
Dash Punctuation 228
 
1.5%
Other Punctuation 30
 
0.2%
Uppercase Letter 5
 
< 0.1%
Connector Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 890
 
10.8%
동 871
 
10.6%
양 517
 
6.3%
천 495
 
6.0%
신 483
 
5.9%
목 471
 
5.7%
서 456
 
5.6%
구 366
 
4.5%
시 364
 
4.4%
울 353
 
4.3%
Other values (142) 2941
35.8%
Decimal Number
ValueCountFrequency (%)
1 711
19.4%
3 567
15.5%
9 434
11.8%
2 380
10.4%
5 341
9.3%
0 332
9.1%
4 291
7.9%
7 227
 
6.2%
8 195
 
5.3%
6 190
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 15
50.0%
. 13
43.3%
# 2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
F 3
60.0%
B 2
40.0%
Space Separator
ValueCountFrequency (%)
2161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 302
100.0%
Close Punctuation
ValueCountFrequency (%)
) 301
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8207
55.1%
Common 6694
44.9%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 890
 
10.8%
동 871
 
10.6%
양 517
 
6.3%
천 495
 
6.0%
신 483
 
5.9%
목 471
 
5.7%
서 456
 
5.6%
구 366
 
4.5%
시 364
 
4.4%
울 353
 
4.3%
Other values (142) 2941
35.8%
Common
ValueCountFrequency (%)
2161
32.3%
1 711
 
10.6%
3 567
 
8.5%
9 434
 
6.5%
2 380
 
5.7%
5 341
 
5.1%
0 332
 
5.0%
( 302
 
4.5%
) 301
 
4.5%
4 291
 
4.3%
Other values (8) 874
13.1%
Latin
ValueCountFrequency (%)
F 3
60.0%
B 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8207
55.1%
ASCII 6699
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2161
32.3%
1 711
 
10.6%
3 567
 
8.5%
9 434
 
6.5%
2 380
 
5.7%
5 341
 
5.1%
0 332
 
5.0%
( 302
 
4.5%
) 301
 
4.5%
4 291
 
4.3%
Other values (10) 879
13.1%
Hangul
ValueCountFrequency (%)
로 890
 
10.8%
동 871
 
10.6%
양 517
 
6.3%
천 495
 
6.0%
신 483
 
5.9%
목 471
 
5.7%
서 456
 
5.6%
구 366
 
4.5%
시 364
 
4.4%
울 353
 
4.3%
Other values (142) 2941
35.8%

상세주소
Text

MISSING 

Distinct678
Distinct (%)74.8%
Missing182
Missing (%)16.7%
Memory size8.6 KiB
2024-05-18T09:54:21.517517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length10.213024
Min length2

Characters and Unicode

Total characters9253
Distinct characters371
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

Unique580 ?
Unique (%)64.0%

Sample

1st row본관 1F
2nd row본관 1F
3rd row본관 2F
4th row본관 2F
5th row본관 2F
ValueCountFrequency (%)
2층 85
 
4.7%
1층 81
 
4.5%
복도 78
 
4.4%
3층 74
 
4.1%
앞 73
 
4.1%
4층 47
 
2.6%
도서관 22
 
1.2%
신월종합사회복지관 21
 
1.2%
본관 20
 
1.1%
관중석 20
 
1.1%
Other values (750) 1269
70.9%
2024-05-18T09:54:22.711328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
884
 
9.6%
1 700
 
7.6%
층 411
 
4.4%
2 370
 
4.0%
) 308
 
3.3%
( 308
 
3.3%
3 275
 
3.0%
5 243
 
2.6%
실 192
 
2.1%
_ 190
 
2.1%
Other values (361) 5372
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4880
52.7%
Decimal Number 2150
23.2%
Space Separator 884
 
9.6%
Close Punctuation 308
 
3.3%
Open Punctuation 308
 
3.3%
Uppercase Letter 202
 
2.2%
Connector Punctuation 190
 
2.1%
Dash Punctuation 183
 
2.0%
Lowercase Letter 130
 
1.4%
Other Punctuation 18
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 411
 
8.4%
실 192
 
3.9%
옥 152
 
3.1%
관 140
 
2.9%
내 136
 
2.8%
복 128
 
2.6%
도 121
 
2.5%
앞 115
 
2.4%
지 111
 
2.3%
신 99
 
2.0%
Other values (327) 3275
67.1%
Uppercase Letter
ValueCountFrequency (%)
F 102
50.5%
C 31
 
15.3%
T 21
 
10.4%
V 16
 
7.9%
P 6
 
3.0%
K 5
 
2.5%
B 5
 
2.5%
A 4
 
2.0%
S 4
 
2.0%
E 4
 
2.0%
Other values (3) 4
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 700
32.6%
2 370
17.2%
3 275
 
12.8%
5 243
 
11.3%
4 146
 
6.8%
0 128
 
6.0%
6 89
 
4.1%
7 76
 
3.5%
9 63
 
2.9%
8 60
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
c 63
48.5%
t 33
25.4%
v 32
24.6%
w 2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 17
94.4%
? 1
 
5.6%
Space Separator
ValueCountFrequency (%)
884
100.0%
Close Punctuation
ValueCountFrequency (%)
) 308
100.0%
Open Punctuation
ValueCountFrequency (%)
( 308
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4880
52.7%
Common 4041
43.7%
Latin 332
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 411
 
8.4%
실 192
 
3.9%
옥 152
 
3.1%
관 140
 
2.9%
내 136
 
2.8%
복 128
 
2.6%
도 121
 
2.5%
앞 115
 
2.4%
지 111
 
2.3%
신 99
 
2.0%
Other values (327) 3275
67.1%
Common
ValueCountFrequency (%)
884
21.9%
1 700
17.3%
2 370
9.2%
) 308
 
7.6%
( 308
 
7.6%
3 275
 
6.8%
5 243
 
6.0%
_ 190
 
4.7%
- 183
 
4.5%
4 146
 
3.6%
Other values (7) 434
10.7%
Latin
ValueCountFrequency (%)
F 102
30.7%
c 63
19.0%
t 33
 
9.9%
v 32
 
9.6%
C 31
 
9.3%
T 21
 
6.3%
V 16
 
4.8%
P 6
 
1.8%
K 5
 
1.5%
B 5
 
1.5%
Other values (7) 18
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4880
52.7%
ASCII 4373
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
884
20.2%
1 700
16.0%
2 370
8.5%
) 308
 
7.0%
( 308
 
7.0%
3 275
 
6.3%
5 243
 
5.6%
_ 190
 
4.3%
- 183
 
4.2%
4 146
 
3.3%
Other values (24) 766
17.5%
Hangul
ValueCountFrequency (%)
층 411
 
8.4%
실 192
 
3.9%
옥 152
 
3.1%
관 140
 
2.9%
내 136
 
2.8%
복 128
 
2.6%
도 121
 
2.5%
앞 115
 
2.4%
지 111
 
2.3%
신 99
 
2.0%
Other values (327) 3275
67.1%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
<NA>
1007 
4층
 
19
5층
 
15
7층
 
11
1층
 
9
Other values (5)
 
27

Length

Max length4
Median length4
Mean length3.8556985
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1007
92.6%
4층 19
 
1.7%
5층 15
 
1.4%
7층 11
 
1.0%
1층 9
 
0.8%
6층 9
 
0.8%
3층 8
 
0.7%
2층 6
 
0.6%
지하1층 3
 
0.3%
- 1
 
0.1%

Length

2024-05-18T09:54:23.157883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:23.526075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1007
92.6%
4층 19
 
1.7%
5층 15
 
1.4%
7층 11
 
1.0%
1층 9
 
0.8%
6층 9
 
0.8%
3층 8
 
0.7%
2층 6
 
0.6%
지하1층 3
 
0.3%
1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
4. 문화관광
186 
3. 공원(하천)
97 
7-1-3. 공공 - 시산하기관
95 
7-2-3. 공공 - 동주민센터
95 
1. 주요거리
78 
Other values (13)
537 

Length

Max length21
Median length17
Mean length12.594669
Min length7

Unique

Unique0 ?
Unique (%)0.0%

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 (%)
4. 문화관광 186
17.1%
3. 공원(하천) 97
8.9%
7-1-3. 공공 - 시산하기관 95
8.7%
7-2-3. 공공 - 동주민센터 95
8.7%
1. 주요거리 78
 
7.2%
5-2. 버스정류소(시비) 71
 
6.5%
6-2. 복지 - 노인 70
 
6.4%
5-1. 버스정류소(국비) 62
 
5.7%
7-2-1. 공공 - 구청사 및 별관 59
 
5.4%
6-4. 복지 - 아동청소년 57
 
5.2%
Other values (8) 218
20.0%

Length

2024-05-18T09:54:23.969184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
567
 
16.2%
공공 346
 
9.9%
복지 221
 
6.3%
4 186
 
5.3%
문화관광 186
 
5.3%
3 97
 
2.8%
공원(하천 97
 
2.8%
및 96
 
2.7%
7-2-3 95
 
2.7%
시산하기관 95
 
2.7%
Other values (32) 1516
43.3%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
자치구
491 
디지털뉴딜(LG U+)
312 
서울시(AP)
123 
버스정류소(국비)
62 
버스정류소(시비)
 
47
Other values (2)
53 

Length

Max length12
Median length9
Mean length6.9145221
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자치구 491
45.1%
디지털뉴딜(LG U+) 312
28.7%
서울시(AP) 123
 
11.3%
버스정류소(국비) 62
 
5.7%
버스정류소(시비) 47
 
4.3%
디지털뉴딜(KT) 40
 
3.7%
서울시(공유기) 13
 
1.2%

Length

2024-05-18T09:54:24.358530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:24.716725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 491
35.1%
디지털뉴딜(lg 312
22.3%
u 312
22.3%
서울시(ap 123
 
8.8%
버스정류소(국비 62
 
4.4%
버스정류소(시비 47
 
3.4%
디지털뉴딜(kt 40
 
2.9%
서울시(공유기 13
 
0.9%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
공공WiFi
785 
과기부WiFi(복지시설)
96 
<NA>
81 
과기부WiFi(핫플레이스)
 
64
과기부WiFi
 
62

Length

Max length14
Median length6
Mean length6.9963235
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 785
72.2%
과기부WiFi(복지시설) 96
 
8.8%
<NA> 81
 
7.4%
과기부WiFi(핫플레이스) 64
 
5.9%
과기부WiFi 62
 
5.7%

Length

2024-05-18T09:54:24.960497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:25.147920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 785
72.2%
과기부wifi(복지시설 96
 
8.8%
na 81
 
7.4%
과기부wifi(핫플레이스 64
 
5.9%
과기부wifi 62
 
5.7%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
자가망_U무선망
492 
인터넷망_뉴딜용
352 
임대망
177 
<NA>
 
47
자가망_수도사업소망
 
20

Length

Max length10
Median length8
Mean length7.0505515
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 (%)
자가망_U무선망 492
45.2%
인터넷망_뉴딜용 352
32.4%
임대망 177
 
16.3%
<NA> 47
 
4.3%
자가망_수도사업소망 20
 
1.8%

Length

2024-05-18T09:54:25.433089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:25.766127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 492
45.2%
인터넷망_뉴딜용 352
32.4%
임대망 177
 
16.3%
na 47
 
4.3%
자가망_수도사업소망 20
 
1.8%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.1756
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.7 KiB
2024-05-18T09:54:26.000760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2017
Q12019
median2021
Q32022
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0172827
Coefficient of variation (CV)0.000998568
Kurtosis0.56409194
Mean2020.1756
Median Absolute Deviation (MAD)2
Skewness-0.77360923
Sum2197951
Variance4.0694293
MonotonicityNot monotonic
2024-05-18T09:54:26.406861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2022 316
29.0%
2019 292
26.8%
2021 154
14.2%
2018 116
 
10.7%
2023 81
 
7.4%
2020 61
 
5.6%
2015 29
 
2.7%
2017 17
 
1.6%
2016 10
 
0.9%
2014 9
 
0.8%
ValueCountFrequency (%)
2012 3
 
0.3%
2014 9
 
0.8%
2015 29
 
2.7%
2016 10
 
0.9%
2017 17
 
1.6%
2018 116
 
10.7%
2019 292
26.8%
2020 61
 
5.6%
2021 154
14.2%
2022 316
29.0%
ValueCountFrequency (%)
2023 81
 
7.4%
2022 316
29.0%
2021 154
14.2%
2020 61
 
5.6%
2019 292
26.8%
2018 116
 
10.7%
2017 17
 
1.6%
2016 10
 
0.9%
2015 29
 
2.7%
2014 9
 
0.8%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
실내
727 
실외
361 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실내 727
66.8%
실외 361
33.2%

Length

2024-05-18T09:54:26.763727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:27.092175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 727
66.8%
실외 361
33.2%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
<NA>
1074 
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정
 
14

Length

Max length53
Median length4
Mean length4.6305147
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> 1074
98.7%
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정 14
 
1.3%

Length

2024-05-18T09:54:27.426886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:27.829866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1074
86.5%
후 28
 
2.3%
6.20~6.24 14
 
1.1%
proxy 14
 
1.1%
서버개발 14
 
1.1%
2~3개 14
 
1.1%
임시적용 14
 
1.1%
6월말 14
 
1.1%
cns링크 14
 
1.1%
전체 14
 
1.1%
Other values (2) 28
 
2.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct485
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.524415
Minimum37.183975
Maximum37.549713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.7 KiB
2024-05-18T09:54:28.225928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.183975
5-th percentile37.511119
Q137.517033
median37.524259
Q337.53238
95-th percentile37.541565
Maximum37.549713
Range0.365738
Interquartile range (IQR)0.015347

Descriptive statistics

Standard deviation0.017577755
Coefficient of variation (CV)0.00046843517
Kurtosis257.52347
Mean37.524415
Median Absolute Deviation (MAD)0.0072265
Skewness-13.313921
Sum40826.563
Variance0.00030897749
MonotonicityNot monotonic
2024-05-18T09:54:28.750291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.530556 87
 
8.0%
37.51202 72
 
6.6%
37.517033 43
 
4.0%
37.520035 21
 
1.9%
37.519573 20
 
1.8%
37.515987 20
 
1.8%
37.518135 19
 
1.7%
37.534103 18
 
1.7%
37.530567 15
 
1.4%
37.51992 15
 
1.4%
Other values (475) 758
69.7%
ValueCountFrequency (%)
37.183975 2
0.2%
37.506317 1
 
0.1%
37.506454 1
 
0.1%
37.507088 1
 
0.1%
37.508022 1
 
0.1%
37.50818 1
 
0.1%
37.508213 1
 
0.1%
37.508404 1
 
0.1%
37.50855 3
0.3%
37.508717 1
 
0.1%
ValueCountFrequency (%)
37.549713 1
0.1%
37.54964 1
0.1%
37.549335 1
0.1%
37.548832 1
0.1%
37.54849 1
0.1%
37.548454 1
0.1%
37.548256 2
0.2%
37.54822 1
0.1%
37.548153 1
0.1%
37.548004 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct474
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85646
Minimum126.82336
Maximum127.11369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.7 KiB
2024-05-18T09:54:29.173769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82336
5-th percentile126.82724
Q1126.83529
median126.86232
Q3126.87054
95-th percentile126.88104
Maximum127.11369
Range0.290326
Interquartile range (IQR)0.035247

Descriptive statistics

Standard deviation0.022120193
Coefficient of variation (CV)0.00017437182
Kurtosis32.22327
Mean126.85646
Median Absolute Deviation (MAD)0.0169175
Skewness2.8274408
Sum138019.83
Variance0.00048930294
MonotonicityNot monotonic
2024-05-18T09:54:29.641997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.88088 87
 
8.0%
126.83313 72
 
6.6%
126.86646 44
 
4.0%
126.84737 21
 
1.9%
126.86976 20
 
1.8%
126.863914 20
 
1.8%
126.8454 19
 
1.7%
126.829926 18
 
1.7%
126.86995 15
 
1.4%
126.88104 15
 
1.4%
Other values (464) 757
69.6%
ValueCountFrequency (%)
126.823364 1
 
0.1%
126.82396 1
 
0.1%
126.82426 3
 
0.3%
126.82464 1
 
0.1%
126.8252 1
 
0.1%
126.8253 5
0.5%
126.8255 8
0.7%
126.82577 1
 
0.1%
126.82611 1
 
0.1%
126.82622 1
 
0.1%
ValueCountFrequency (%)
127.11369 2
0.2%
126.96459 1
0.1%
126.88825 1
0.1%
126.88792 1
0.1%
126.88633 1
0.1%
126.88575 1
0.1%
126.88547 1
0.1%
126.88511 1
0.1%
126.88474 2
0.2%
126.88444 1
0.1%

작업일자
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
2024-05-17 11:13:01.0
589 
2024-05-17 11:13:06.0
180 
2024-05-17 11:12:52.0
77 
2024-05-17 11:13:00.0
76 
2024-05-17 11:12:57.0
 
47
Other values (6)
119 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-17 11:12:52.0
2nd row2024-05-17 11:12:52.0
3rd row2024-05-17 11:12:52.0
4th row2024-05-17 11:12:52.0
5th row2024-05-17 11:12:52.0

Common Values

ValueCountFrequency (%)
2024-05-17 11:13:01.0 589
54.1%
2024-05-17 11:13:06.0 180
 
16.5%
2024-05-17 11:12:52.0 77
 
7.1%
2024-05-17 11:13:00.0 76
 
7.0%
2024-05-17 11:12:57.0 47
 
4.3%
2024-05-17 11:13:04.0 44
 
4.0%
2024-05-17 11:12:59.0 36
 
3.3%
2024-05-17 11:13:02.0 21
 
1.9%
2024-05-17 11:13:05.0 11
 
1.0%
2024-05-17 11:12:53.0 5
 
0.5%

Length

2024-05-18T09:54:30.079692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-17 1088
50.0%
11:13:01.0 589
27.1%
11:13:06.0 180
 
8.3%
11:12:52.0 77
 
3.5%
11:13:00.0 76
 
3.5%
11:12:57.0 47
 
2.2%
11:13:04.0 44
 
2.0%
11:12:59.0 36
 
1.7%
11:13:02.0 21
 
1.0%
11:13:05.0 11
 
0.5%
Other values (2) 7
 
0.3%

Interactions

2024-05-18T09:54:14.015778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:12.344018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:13.191295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:14.274791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:12.607778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:13.461600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:14.556728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:12.890541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:13.741127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:54:30.319807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.710NaNNaNNaNNaN1.0000.4100.127NaN
설치유형0.7101.0000.8870.9430.8210.8530.9890.6790.4750.870
설치기관NaN0.8871.0000.8440.8960.7540.4840.3120.2570.939
서비스구분NaN0.9430.8441.0000.8560.6670.7440.1420.1700.825
망종류NaN0.8210.8960.8561.0000.7490.1640.1620.1250.858
설치년도NaN0.8530.7540.6670.7491.0000.4260.4310.3170.711
실내외구분1.0000.9890.4840.7440.1640.4261.0000.0500.0250.503
X좌표0.4100.6790.3120.1420.1620.4310.0501.0000.7310.442
Y좌표0.1270.4750.2570.1700.1250.3170.0250.7311.0000.376
작업일자NaN0.8700.9390.8250.8580.7110.5030.4420.3761.000
2024-05-18T09:54:30.562443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서비스구분실내외구분작업일자설치유형망종류설치기관설치위치(층)wifi접속환경
서비스구분1.0000.5360.6670.8270.5130.764NaN1.000
실내외구분0.5361.0000.4820.9070.1090.5180.9551.000
작업일자0.6670.4821.0000.5590.7070.8311.0001.000
설치유형0.8270.9070.5591.0000.6060.6620.4971.000
망종류0.5130.1090.7070.6061.0000.7761.0001.000
설치기관0.7640.5180.8310.6620.7761.0001.0001.000
설치위치(층)NaN0.9551.0000.4971.0001.0001.000NaN
wifi접속환경1.0001.0001.0001.0001.0001.000NaN1.000
2024-05-18T09:54:30.861925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경작업일자
설치년도1.000-0.070-0.0841.0000.4390.5300.4950.5910.4251.0000.398
X좌표-0.0701.0000.1130.3900.4080.2210.1350.1530.0831.0000.288
Y좌표-0.0840.1131.0000.1160.2640.1670.1400.1020.0301.0000.217
설치위치(층)1.0000.3900.1161.0000.4971.0000.0001.0000.9550.0001.000
설치유형0.4390.4080.2640.4971.0000.6620.8270.6060.9071.0000.559
설치기관0.5300.2210.1671.0000.6621.0000.7640.7760.5181.0000.831
서비스구분0.4950.1350.1400.0000.8270.7641.0000.5130.5361.0000.667
망종류0.5910.1530.1021.0000.6060.7760.5131.0000.1091.0000.707
실내외구분0.4250.0830.0300.9550.9070.5180.5360.1091.0001.0000.482
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.000
작업일자0.3980.2880.2171.0000.5590.8310.6670.7070.4821.0001.000

Missing values

2024-05-18T09:54:14.949261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:54:15.591707image/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.
2024-05-18T09:54:16.011526image/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
0ARI00109양천구강서수도사업소목동동로 151본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
1ARI00112양천구강서수도사업소목동동로 151본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
2ARI00113양천구강서수도사업소목동동로 151본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
3ARI00114양천구강서수도사업소목동동로 151본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
4ARI00115양천구강서수도사업소목동동로 151본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
5ARI00116양천구강서수도사업소목동동로 151본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
6ARI00117양천구강서수도사업소목동동로 151본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
7ARI00118양천구강서수도사업소목동동로 151본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
8ARI00119양천구강서수도사업소목동동로 151본관 4F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
9ARI00120양천구강서수도사업소목동동로 151본관 4F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.519573126.869762024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1078서울5차-1030-2양천구서남병원서울특별시 양천구 신정이펜1로 206102호실6층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1079서울5차-1031양천구서남병원서울특별시 양천구 신정이펜1로 20대이룸7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1080서울5차-1031-1양천구서남병원서울특별시 양천구 신정이펜1로 207114호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1081서울5차-1031-2양천구서남병원서울특별시 양천구 신정이펜1로 207112호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1082서울5차-1032양천구서남병원서울특별시 양천구 신정이펜1로 207110호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1083서울5차-1032-1양천구서남병원서울특별시 양천구 신정이펜1로 207108호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1084서울5차-1032-2양천구서남병원서울특별시 양천구 신정이펜1로 207102호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1085서울5차-1033양천구서남병원서울특별시 양천구 신정이펜1로 207105호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1086서울5차-1033-1양천구서남병원서울특별시 양천구 신정이펜1로 207106호실7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0
1087서울5차-1033-2양천구서남병원서울특별시 양천구 신정이펜1로 20TPS실 앞7층7-1-3. 공공 - 시산하기관디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.51202126.833132024-05-17 11:13:06.0