Overview

Dataset statistics

Number of variables16
Number of observations746
Missing cells27
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory95.6 KiB
Average record size in memory131.2 B

Variable types

Text4
Categorical8
Numeric3
DateTime1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20901/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
실내외구분 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 6 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 6 other fieldsHigh correlation
X좌표 is highly overall correlated with 설치위치(층) and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (91.9%)Imbalance
wifi접속환경 is highly imbalanced (91.4%)Imbalance
도로명주소 has 21 (2.8%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 00:26:43.771864
Analysis finished2024-05-18 00:26:51.971274
Duration8.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct746
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-18T09:26:52.874605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.5710456
Min length7

Characters and Unicode

Total characters6394
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

Unique746 ?
Unique (%)100.0%

Sample

1st rowARI00001
2nd rowARI00002
3rd rowARI00003
4th rowARI00004
5th rowARI00005
ValueCountFrequency (%)
ari00001 1
 
0.1%
wf190694 1
 
0.1%
wf190684 1
 
0.1%
wf190685 1
 
0.1%
wf190712 1
 
0.1%
wf190686 1
 
0.1%
wf190687 1
 
0.1%
wf190688 1
 
0.1%
wf190689 1
 
0.1%
wf190690 1
 
0.1%
Other values (736) 736
98.7%
2024-05-18T09:26:54.457603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1246
19.5%
1 755
11.8%
2 396
 
6.2%
4 375
 
5.9%
S 327
 
5.1%
6 313
 
4.9%
5 310
 
4.8%
- 292
 
4.6%
7 291
 
4.6%
M 224
 
3.5%
Other values (13) 1865
29.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4204
65.7%
Uppercase Letter 1368
 
21.4%
Other Letter 530
 
8.3%
Dash Punctuation 292
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1246
29.6%
1 755
18.0%
2 396
 
9.4%
4 375
 
8.9%
6 313
 
7.4%
5 310
 
7.4%
7 291
 
6.9%
9 194
 
4.6%
3 177
 
4.2%
8 147
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
S 327
23.9%
M 224
16.4%
D 224
16.4%
W 182
13.3%
F 182
13.3%
B 82
 
6.0%
R 49
 
3.6%
I 49
 
3.6%
A 49
 
3.6%
Other Letter
ValueCountFrequency (%)
울 209
39.4%
서 209
39.4%
차 112
21.1%
Dash Punctuation
ValueCountFrequency (%)
- 292
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4496
70.3%
Latin 1368
 
21.4%
Hangul 530
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1246
27.7%
1 755
16.8%
2 396
 
8.8%
4 375
 
8.3%
6 313
 
7.0%
5 310
 
6.9%
- 292
 
6.5%
7 291
 
6.5%
9 194
 
4.3%
3 177
 
3.9%
Latin
ValueCountFrequency (%)
S 327
23.9%
M 224
16.4%
D 224
16.4%
W 182
13.3%
F 182
13.3%
B 82
 
6.0%
R 49
 
3.6%
I 49
 
3.6%
A 49
 
3.6%
Hangul
ValueCountFrequency (%)
울 209
39.4%
서 209
39.4%
차 112
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5864
91.7%
Hangul 530
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1246
21.2%
1 755
12.9%
2 396
 
6.8%
4 375
 
6.4%
S 327
 
5.6%
6 313
 
5.3%
5 310
 
5.3%
- 292
 
5.0%
7 291
 
5.0%
M 224
 
3.8%
Other values (10) 1335
22.8%
Hangul
ValueCountFrequency (%)
울 209
39.4%
서 209
39.4%
차 112
21.1%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
서대문구
746 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 746
100.0%

Length

2024-05-18T09:26:55.096342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:26:55.402973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 746
100.0%

와이파이명
Text

Distinct183
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-18T09:26:55.996094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length8.2158177
Min length3

Characters and Unicode

Total characters6129
Distinct characters237
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

Unique69 ?
Unique (%)9.2%

Sample

1st row상수도사업본부
2nd row상수도사업본부
3rd row상수도사업본부
4th row상수도사업본부
5th row상수도사업본부
ValueCountFrequency (%)
홍제천 60
 
7.8%
서대문구청 38
 
4.9%
상수도사업본부 32
 
4.1%
서대문종합사회복지관 27
 
3.5%
독립공원형무소역사관 24
 
3.1%
신촌연세로 24
 
3.1%
북아현문화체육센터 21
 
2.7%
서부수도사업소 17
 
2.2%
서대문구의회 17
 
2.2%
서대문청소년센터 15
 
1.9%
Other values (178) 499
64.5%
2024-05-18T09:26:57.124810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 288
 
4.7%
서 271
 
4.4%
문 269
 
4.4%
소 172
 
2.8%
터 171
 
2.8%
센 164
 
2.7%
사 133
 
2.2%
구 131
 
2.1%
관 129
 
2.1%
홍 124
 
2.0%
Other values (227) 4277
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5816
94.9%
Decimal Number 137
 
2.2%
Connector Punctuation 82
 
1.3%
Space Separator 28
 
0.5%
Other Punctuation 24
 
0.4%
Uppercase Letter 17
 
0.3%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%
Lowercase Letter 4
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 288
 
5.0%
서 271
 
4.7%
문 269
 
4.6%
소 172
 
3.0%
터 171
 
2.9%
센 164
 
2.8%
사 133
 
2.3%
구 131
 
2.3%
관 129
 
2.2%
홍 124
 
2.1%
Other values (204) 3964
68.2%
Decimal Number
ValueCountFrequency (%)
1 51
37.2%
2 30
21.9%
3 23
16.8%
4 11
 
8.0%
0 6
 
4.4%
5 5
 
3.6%
6 5
 
3.6%
8 3
 
2.2%
7 2
 
1.5%
9 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
D 5
29.4%
C 5
29.4%
M 5
29.4%
T 1
 
5.9%
K 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 21
87.5%
? 3
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 82
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5816
94.9%
Common 292
 
4.8%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 288
 
5.0%
서 271
 
4.7%
문 269
 
4.6%
소 172
 
3.0%
터 171
 
2.9%
센 164
 
2.8%
사 133
 
2.3%
구 131
 
2.3%
관 129
 
2.2%
홍 124
 
2.1%
Other values (204) 3964
68.2%
Common
ValueCountFrequency (%)
_ 82
28.1%
1 51
17.5%
2 30
 
10.3%
28
 
9.6%
3 23
 
7.9%
. 21
 
7.2%
4 11
 
3.8%
( 10
 
3.4%
) 10
 
3.4%
0 6
 
2.1%
Other values (7) 20
 
6.8%
Latin
ValueCountFrequency (%)
D 5
23.8%
C 5
23.8%
M 5
23.8%
e 4
19.0%
T 1
 
4.8%
K 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5816
94.9%
ASCII 313
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 288
 
5.0%
서 271
 
4.7%
문 269
 
4.6%
소 172
 
3.0%
터 171
 
2.9%
센 164
 
2.8%
사 133
 
2.3%
구 131
 
2.3%
관 129
 
2.2%
홍 124
 
2.1%
Other values (204) 3964
68.2%
ASCII
ValueCountFrequency (%)
_ 82
26.2%
1 51
16.3%
2 30
 
9.6%
28
 
8.9%
3 23
 
7.3%
. 21
 
6.7%
4 11
 
3.5%
( 10
 
3.2%
) 10
 
3.2%
0 6
 
1.9%
Other values (13) 41
13.1%

도로명주소
Text

MISSING 

Distinct251
Distinct (%)34.6%
Missing21
Missing (%)2.8%
Memory size6.0 KiB
2024-05-18T09:26:57.989951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length13.322759
Min length3

Characters and Unicode

Total characters9659
Distinct characters201
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

Unique118 ?
Unique (%)16.3%

Sample

1st row서소문로 51
2nd row서소문로 51
3rd row서소문로 51
4th row서소문로 51
5th row서소문로 51
ValueCountFrequency (%)
서대문구 230
 
11.3%
서울특별시 202
 
9.9%
연희로 89
 
4.4%
모래내로 63
 
3.1%
통일로 61
 
3.0%
51 42
 
2.1%
248 35
 
1.7%
서소문로 35
 
1.7%
177 28
 
1.4%
251 24
 
1.2%
Other values (363) 1223
60.2%
2024-05-18T09:26:59.386060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1322
 
13.7%
로 557
 
5.8%
1 554
 
5.7%
서 500
 
5.2%
2 442
 
4.6%
문 305
 
3.2%
3 288
 
3.0%
대 283
 
2.9%
4 267
 
2.8%
길 247
 
2.6%
Other values (191) 4894
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5288
54.7%
Decimal Number 2533
26.2%
Space Separator 1322
 
13.7%
Dash Punctuation 206
 
2.1%
Uppercase Letter 98
 
1.0%
Close Punctuation 55
 
0.6%
Open Punctuation 55
 
0.6%
Other Punctuation 54
 
0.6%
Lowercase Letter 39
 
0.4%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 557
 
10.5%
서 500
 
9.5%
문 305
 
5.8%
대 283
 
5.4%
길 247
 
4.7%
구 236
 
4.5%
시 221
 
4.2%
울 211
 
4.0%
별 207
 
3.9%
특 202
 
3.8%
Other values (150) 2319
43.9%
Uppercase Letter
ValueCountFrequency (%)
C 31
31.6%
T 20
20.4%
V 15
15.3%
F 6
 
6.1%
S 5
 
5.1%
E 4
 
4.1%
B 4
 
4.1%
A 3
 
3.1%
L 3
 
3.1%
O 2
 
2.0%
Other values (5) 5
 
5.1%
Decimal Number
ValueCountFrequency (%)
1 554
21.9%
2 442
17.4%
3 288
11.4%
4 267
10.5%
5 237
9.4%
7 210
 
8.3%
8 156
 
6.2%
6 143
 
5.6%
9 119
 
4.7%
0 117
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
l 9
23.1%
c 6
15.4%
e 3
 
7.7%
u 3
 
7.7%
w 3
 
7.7%
o 3
 
7.7%
r 3
 
7.7%
d 3
 
7.7%
t 3
 
7.7%
v 3
 
7.7%
Space Separator
ValueCountFrequency (%)
1322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5288
54.7%
Common 4234
43.8%
Latin 137
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 557
 
10.5%
서 500
 
9.5%
문 305
 
5.8%
대 283
 
5.4%
길 247
 
4.7%
구 236
 
4.5%
시 221
 
4.2%
울 211
 
4.0%
별 207
 
3.9%
특 202
 
3.8%
Other values (150) 2319
43.9%
Latin
ValueCountFrequency (%)
C 31
22.6%
T 20
14.6%
V 15
10.9%
l 9
 
6.6%
c 6
 
4.4%
F 6
 
4.4%
S 5
 
3.6%
E 4
 
2.9%
B 4
 
2.9%
e 3
 
2.2%
Other values (15) 34
24.8%
Common
ValueCountFrequency (%)
1322
31.2%
1 554
13.1%
2 442
 
10.4%
3 288
 
6.8%
4 267
 
6.3%
5 237
 
5.6%
7 210
 
5.0%
- 206
 
4.9%
8 156
 
3.7%
6 143
 
3.4%
Other values (6) 409
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5288
54.7%
ASCII 4371
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1322
30.2%
1 554
12.7%
2 442
 
10.1%
3 288
 
6.6%
4 267
 
6.1%
5 237
 
5.4%
7 210
 
4.8%
- 206
 
4.7%
8 156
 
3.6%
6 143
 
3.3%
Other values (31) 546
12.5%
Hangul
ValueCountFrequency (%)
로 557
 
10.5%
서 500
 
9.5%
문 305
 
5.8%
대 283
 
5.4%
길 247
 
4.7%
구 236
 
4.5%
시 221
 
4.2%
울 211
 
4.0%
별 207
 
3.9%
특 202
 
3.8%
Other values (150) 2319
43.9%

상세주소
Text

Distinct526
Distinct (%)71.1%
Missing6
Missing (%)0.8%
Memory size6.0 KiB
2024-05-18T09:27:00.096593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length30
Mean length10.054054
Min length2

Characters and Unicode

Total characters7440
Distinct characters295
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

Unique416 ?
Unique (%)56.2%

Sample

1st row본관 1F
2nd row본관 2F
3rd row본관 2F
4th row본관 2F
5th row본관 2F
ValueCountFrequency (%)
2층 59
 
4.2%
주민센터 49
 
3.5%
1층 44
 
3.1%
본관 43
 
3.0%
3층 36
 
2.5%
홍제천 30
 
2.1%
서대문구청 29
 
2.1%
복도 26
 
1.8%
4층 24
 
1.7%
북아현문화체육센터 21
 
1.5%
Other values (532) 1051
74.4%
2024-05-18T09:27:01.354865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
674
 
9.1%
1 523
 
7.0%
2 305
 
4.1%
3 267
 
3.6%
0 250
 
3.4%
- 243
 
3.3%
층 224
 
3.0%
_ 183
 
2.5%
( 178
 
2.4%
) 178
 
2.4%
Other values (285) 4415
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3628
48.8%
Decimal Number 1897
25.5%
Space Separator 674
 
9.1%
Uppercase Letter 361
 
4.9%
Dash Punctuation 243
 
3.3%
Connector Punctuation 183
 
2.5%
Open Punctuation 178
 
2.4%
Close Punctuation 178
 
2.4%
Lowercase Letter 62
 
0.8%
Other Punctuation 36
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 224
 
6.2%
서 150
 
4.1%
관 115
 
3.2%
옥 107
 
2.9%
터 107
 
2.9%
센 94
 
2.6%
문 77
 
2.1%
구 76
 
2.1%
대 66
 
1.8%
복 65
 
1.8%
Other values (244) 2547
70.2%
Uppercase Letter
ValueCountFrequency (%)
F 130
36.0%
C 97
26.9%
V 48
 
13.3%
T 48
 
13.3%
B 14
 
3.9%
P 6
 
1.7%
E 5
 
1.4%
U 4
 
1.1%
O 2
 
0.6%
S 2
 
0.6%
Other values (5) 5
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 523
27.6%
2 305
16.1%
3 267
14.1%
0 250
13.2%
4 172
 
9.1%
5 147
 
7.7%
8 72
 
3.8%
7 70
 
3.7%
6 57
 
3.0%
9 34
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
c 26
41.9%
v 13
21.0%
t 13
21.0%
o 4
 
6.5%
f 4
 
6.5%
d 1
 
1.6%
m 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 30
83.3%
/ 4
 
11.1%
? 1
 
2.8%
' 1
 
2.8%
Space Separator
ValueCountFrequency (%)
674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 243
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 183
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3628
48.8%
Common 3389
45.6%
Latin 423
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 224
 
6.2%
서 150
 
4.1%
관 115
 
3.2%
옥 107
 
2.9%
터 107
 
2.9%
센 94
 
2.6%
문 77
 
2.1%
구 76
 
2.1%
대 66
 
1.8%
복 65
 
1.8%
Other values (244) 2547
70.2%
Latin
ValueCountFrequency (%)
F 130
30.7%
C 97
22.9%
V 48
 
11.3%
T 48
 
11.3%
c 26
 
6.1%
B 14
 
3.3%
v 13
 
3.1%
t 13
 
3.1%
P 6
 
1.4%
E 5
 
1.2%
Other values (12) 23
 
5.4%
Common
ValueCountFrequency (%)
674
19.9%
1 523
15.4%
2 305
9.0%
3 267
 
7.9%
0 250
 
7.4%
- 243
 
7.2%
_ 183
 
5.4%
( 178
 
5.3%
) 178
 
5.3%
4 172
 
5.1%
Other values (9) 416
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3812
51.2%
Hangul 3628
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
674
17.7%
1 523
13.7%
2 305
 
8.0%
3 267
 
7.0%
0 250
 
6.6%
- 243
 
6.4%
_ 183
 
4.8%
( 178
 
4.7%
) 178
 
4.7%
4 172
 
4.5%
Other values (31) 839
22.0%
Hangul
ValueCountFrequency (%)
층 224
 
6.2%
서 150
 
4.1%
관 115
 
3.2%
옥 107
 
2.9%
터 107
 
2.9%
센 94
 
2.6%
문 77
 
2.1%
구 76
 
2.1%
대 66
 
1.8%
복 65
 
1.8%
Other values (244) 2547
70.2%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
730 
2층
 
6
3층
 
5
1층
 
4
지향성에서 무지향성으로 교체
 
1

Length

Max length15
Median length4
Mean length3.9745308
Min length2

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> 730
97.9%
2층 6
 
0.8%
3층 5
 
0.7%
1층 4
 
0.5%
지향성에서 무지향성으로 교체 1
 
0.1%

Length

2024-05-18T09:27:01.968251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:02.453633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 730
97.6%
2층 6
 
0.8%
3층 5
 
0.7%
1층 4
 
0.5%
지향성에서 1
 
0.1%
무지향성으로 1
 
0.1%
교체 1
 
0.1%

설치유형
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3. 공원(하천)
114 
1. 주요거리
103 
5-1. 버스정류소(국비)
61 
6-1. 복지 - 사회
56 
7-2-1. 공공 - 구청사 및 별관
54 
Other values (12)
358 

Length

Max length21
Median length17
Mean length12.776139
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 (%)
3. 공원(하천) 114
15.3%
1. 주요거리 103
13.8%
5-1. 버스정류소(국비) 61
8.2%
6-1. 복지 - 사회 56
7.5%
7-2-1. 공공 - 구청사 및 별관 54
7.2%
7-1-3. 공공 - 시산하기관 53
7.1%
7-2-3. 공공 - 동주민센터 53
7.1%
6-3. 복지 - 장애인 43
 
5.8%
6-4. 복지 - 아동청소년 42
 
5.6%
4. 문화관광 38
 
5.1%
Other values (7) 129
17.3%

Length

2024-05-18T09:27:02.920658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
397
 
16.1%
공공 227
 
9.2%
복지 170
 
6.9%
3 114
 
4.6%
공원(하천 114
 
4.6%
1 103
 
4.2%
주요거리 103
 
4.2%
및 88
 
3.6%
5-1 61
 
2.5%
버스정류소(국비 61
 
2.5%
Other values (30) 1024
41.6%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
자치구
242 
서울시(AP)
207 
디지털뉴딜(LG U+)
121 
디지털뉴딜(KT)
88 
버스정류소(국비)
61 
Other values (2)
27 

Length

Max length12
Median length9
Mean length6.9772118
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 242
32.4%
서울시(AP) 207
27.7%
디지털뉴딜(LG U+) 121
16.2%
디지털뉴딜(KT) 88
 
11.8%
버스정류소(국비) 61
 
8.2%
버스정류소(시비) 21
 
2.8%
서울시(공유기) 6
 
0.8%

Length

2024-05-18T09:27:03.208595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:03.609566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 242
27.9%
서울시(ap 207
23.9%
디지털뉴딜(lg 121
14.0%
u 121
14.0%
디지털뉴딜(kt 88
 
10.1%
버스정류소(국비 61
 
7.0%
버스정류소(시비 21
 
2.4%
서울시(공유기 6
 
0.7%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
공공WiFi
573 
과기부WiFi
61 
과기부WiFi(복지시설)
 
52
과기부WiFi(핫플레이스)
 
45
<NA>
 
15

Length

Max length14
Median length6
Mean length7.0120643
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 573
76.8%
과기부WiFi 61
 
8.2%
과기부WiFi(복지시설) 52
 
7.0%
과기부WiFi(핫플레이스) 45
 
6.0%
<NA> 15
 
2.0%

Length

2024-05-18T09:27:04.011295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:04.344873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 573
76.8%
과기부wifi 61
 
8.2%
과기부wifi(복지시설 52
 
7.0%
과기부wifi(핫플레이스 45
 
6.0%
na 15
 
2.0%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
자가망_U무선망
329 
인터넷망_뉴딜용
209 
임대망
138 
자가망_수도사업소망
49 
<NA>
 
21

Length

Max length10
Median length8
Mean length7.0938338
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 329
44.1%
인터넷망_뉴딜용 209
28.0%
임대망 138
18.5%
자가망_수도사업소망 49
 
6.6%
<NA> 21
 
2.8%

Length

2024-05-18T09:27:04.822431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:05.165299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 329
44.1%
인터넷망_뉴딜용 209
28.0%
임대망 138
18.5%
자가망_수도사업소망 49
 
6.6%
na 21
 
2.8%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.9853
Minimum2013
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-18T09:27:05.545451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12017
median2019
Q32022
95-th percentile2023
Maximum2024
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2524307
Coefficient of variation (CV)0.0016109235
Kurtosis-0.61821311
Mean2018.9853
Median Absolute Deviation (MAD)2
Skewness-0.75970188
Sum1506163
Variance10.578306
MonotonicityNot monotonic
2024-05-18T09:27:05.976274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2022 194
26.0%
2019 159
21.3%
2013 129
17.3%
2021 88
11.8%
2017 76
 
10.2%
2020 34
 
4.6%
2023 33
 
4.4%
2018 17
 
2.3%
2016 9
 
1.2%
2024 7
 
0.9%
ValueCountFrequency (%)
2013 129
17.3%
2016 9
 
1.2%
2017 76
 
10.2%
2018 17
 
2.3%
2019 159
21.3%
2020 34
 
4.6%
2021 88
11.8%
2022 194
26.0%
2023 33
 
4.4%
2024 7
 
0.9%
ValueCountFrequency (%)
2024 7
 
0.9%
2023 33
 
4.4%
2022 194
26.0%
2021 88
11.8%
2020 34
 
4.6%
2019 159
21.3%
2018 17
 
2.3%
2017 76
 
10.2%
2016 9
 
1.2%
2013 129
17.3%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
실내
453 
실외
293 

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 453
60.7%
실외 293
39.3%

Length

2024-05-18T09:27:06.324041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:06.638185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 453
60.7%
실외 293
39.3%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
738 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
8

Length

Max length27
Median length4
Mean length4.2466488
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> 738
98.9%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 8
 
1.1%

Length

2024-05-18T09:27:07.062956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:27:07.351152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 738
94.9%
보안접속 8
 
1.0%
임시적용(머큐리 8
 
1.0%
proxy 8
 
1.0%
서버 8
 
1.0%
개발중 8
 
1.0%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct332
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.574996
Minimum37.55573
Maximum37.603207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-18T09:27:07.684590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.55573
5-th percentile37.558937
Q137.568054
median37.575576
Q337.580776
95-th percentile37.594341
Maximum37.603207
Range0.047477
Interquartile range (IQR)0.0127225

Descriptive statistics

Standard deviation0.010330313
Coefficient of variation (CV)0.00027492519
Kurtosis-0.33968195
Mean37.574996
Median Absolute Deviation (MAD)0.0062335
Skewness0.22841562
Sum28030.947
Variance0.00010671536
MonotonicityNot monotonic
2024-05-18T09:27:08.176964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.561924 32
 
4.3%
37.579075 32
 
4.3%
37.571434 21
 
2.8%
37.561836 21
 
2.8%
37.57817 17
 
2.3%
37.583054 17
 
2.3%
37.57855 15
 
2.0%
37.580196 13
 
1.7%
37.578922 12
 
1.6%
37.576565 10
 
1.3%
Other values (322) 556
74.5%
ValueCountFrequency (%)
37.55573 1
0.1%
37.555786 1
0.1%
37.55579 1
0.1%
37.555885 1
0.1%
37.555965 1
0.1%
37.556065 1
0.1%
37.556194 1
0.1%
37.55659 1
0.1%
37.556614 1
0.1%
37.55685 2
0.3%
ValueCountFrequency (%)
37.603207 1
 
0.1%
37.603043 1
 
0.1%
37.602596 1
 
0.1%
37.601627 1
 
0.1%
37.601593 1
 
0.1%
37.59988 2
0.3%
37.59903 1
 
0.1%
37.598907 4
0.5%
37.59869 2
0.3%
37.598225 2
0.3%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct327
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93859
Minimum126.90347
Maximum126.96922
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-18T09:27:08.686672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90347
5-th percentile126.91379
Q1126.92811
median126.93693
Q3126.9497
95-th percentile126.96608
Maximum126.96922
Range0.06575
Interquartile range (IQR)0.02159

Descriptive statistics

Standard deviation0.015148669
Coefficient of variation (CV)0.00011933856
Kurtosis-0.68649731
Mean126.93859
Median Absolute Deviation (MAD)0.011517
Skewness0.023668467
Sum94696.187
Variance0.00022948216
MonotonicityNot monotonic
2024-05-18T09:27:09.164322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.96675 32
 
4.3%
126.93679 32
 
4.3%
126.92006 21
 
2.8%
126.95544 21
 
2.8%
126.952415 17
 
2.3%
126.93842 17
 
2.3%
126.93425 15
 
2.0%
126.936226 15
 
2.0%
126.938416 12
 
1.6%
126.937614 10
 
1.3%
Other values (317) 554
74.3%
ValueCountFrequency (%)
126.90347 1
0.1%
126.904526 1
0.1%
126.90478 2
0.3%
126.90514 1
0.1%
126.90579 1
0.1%
126.90706 1
0.1%
126.90832 1
0.1%
126.90833 1
0.1%
126.90844 1
0.1%
126.9091 2
0.3%
ValueCountFrequency (%)
126.96922 1
 
0.1%
126.96765 3
 
0.4%
126.96675 32
4.3%
126.96657 1
 
0.1%
126.96616 1
 
0.1%
126.96583 1
 
0.1%
126.96445 1
 
0.1%
126.964424 8
 
1.1%
126.96349 1
 
0.1%
126.963005 1
 
0.1%

작업일자
Date

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2024-05-17 11:12:52
Maximum2024-05-17 11:13:06
2024-05-18T09:27:09.553577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:27:10.405960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-18T09:26:48.574396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:46.485687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:47.510762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:48.908775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:46.877854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:47.897192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:49.307333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:47.186048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:26:48.263870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:27:10.713335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.0000.6981.000NaN1.000NaN1.0000.7330.5251.000
설치유형0.6981.0000.9130.8720.9760.8390.9620.7240.7490.893
설치기관1.0000.9131.0000.8640.8840.8050.4500.3760.4380.937
서비스구분NaN0.8720.8641.0000.8540.8900.7350.3820.3990.867
망종류1.0000.9760.8840.8541.0000.9550.3180.5280.6550.923
설치년도NaN0.8390.8050.8900.9551.0000.7820.5020.4530.879
실내외구분1.0000.9620.4500.7350.3180.7821.0000.4510.4150.785
X좌표0.7330.7240.3760.3820.5280.5020.4511.0000.8340.494
Y좌표0.5250.7490.4380.3990.6550.4530.4150.8341.0000.598
작업일자1.0000.8930.9370.8670.9230.8790.7850.4940.5981.000
2024-05-18T09:27:11.224929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실내외구분망종류설치유형설치기관서비스구분wifi접속환경설치위치(층)
실내외구분1.0000.2120.9500.4810.5281.0000.926
망종류0.2121.0000.7980.7600.5111.0000.926
설치유형0.9500.7981.0000.7230.6941.0000.700
설치기관0.4810.7600.7231.0000.7961.0000.926
서비스구분0.5280.5110.6940.7961.0001.000NaN
wifi접속환경1.0001.0001.0001.0001.0001.000NaN
설치위치(층)0.9260.9260.7000.926NaNNaN1.000
2024-05-18T09:27:11.868064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.000-0.0680.0791.0000.5710.6420.5910.7470.6691.000
X좌표-0.0681.000-0.0950.6370.3820.2010.2360.3430.3451.000
Y좌표0.079-0.0951.0000.4960.4080.2390.2480.4540.3171.000
설치위치(층)1.0000.6370.4961.0000.7000.926NaN0.9260.9260.000
설치유형0.5710.3820.4080.7001.0000.7230.6940.7980.9501.000
설치기관0.6420.2010.2390.9260.7231.0000.7960.7600.4811.000
서비스구분0.5910.2360.248NaN0.6940.7961.0000.5110.5281.000
망종류0.7470.3430.4540.9260.7980.7600.5111.0000.2121.000
실내외구분0.6690.3450.3170.9260.9500.4810.5280.2121.0001.000
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T09:26:49.877483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:26:50.975838image/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.
2024-05-18T09:26:51.635073image/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
0ARI00001서대문구상수도사업본부서소문로 51본관 1F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
1ARI00002서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
2ARI00003서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
3ARI00004서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
4ARI00005서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
5ARI00008서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
6ARI00009서대문구상수도사업본부서소문로 51본관 2F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
7ARI00010서대문구상수도사업본부서소문로 51본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
8ARI00011서대문구상수도사업본부서소문로 51본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
9ARI00012서대문구상수도사업본부서소문로 51본관 3F<NA>7-1-3. 공공 - 시산하기관서울시(AP)공공WiFi자가망_수도사업소망2019실내<NA>37.561924126.966752024-05-17 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
736서울5차-0544서대문구신일지역아동센터서울특별시 서대문구 독립문로8길 107로비3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.56574126.9589542024-05-17 11:13:06.0
737서울5차-0544-1서대문구신일지역아동센터서울특별시 서대문구 독립문로8길 107다목적실 중앙3층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.56574126.9589542024-05-17 11:13:06.0
738서울5차-0629서대문구서대문장애인주간보호시설서울특별시 서대문구 북아현로 4차길 4TV 위3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.560833126.960322024-05-17 11:13:06.0
739서울5차-0629-1서대문구서대문장애인주간보호시설서울특별시 서대문구 북아현로 4차길 4출입구 우측3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.560833126.960322024-05-17 11:13:06.0
740서울5차-0630서대문구서대문장애인주간보호시설서울특별시 서대문구 북아현로 4차길 4사무실3층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.560833126.960322024-05-17 11:13:06.0
741서울5차-0630-1서대문구서대문장애인주간보호시설서울특별시 서대문구 북아현로 4차길 4식당2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.560833126.960322024-05-17 11:13:06.0
742서울5차-0631서대문구늘품장애인보호작업장서울특별시 서대문구 홍은중앙로 105사무실 출입구2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.59988126.94852024-05-17 11:13:06.0
743서울5차-0631-1서대문구늘품장애인보호작업장서울특별시 서대문구 홍은중앙로 105다목적실 에어컨 뒤2층6-3. 복지 - 장애인디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.59988126.94852024-05-17 11:13:06.0
744서울5차-0633서대문구신일지역아동센터서울특별시 서대문구 독립문로8길 107다목적실21층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.56574126.9589542024-05-17 11:13:06.0
745서울5차-0633-1서대문구신일지역아동센터서울특별시 서대문구 독립문로8길 107출입구 위1층6-4. 복지 - 아동청소년디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.56574126.9589542024-05-17 11:13:06.0