Overview

Dataset statistics

Number of variables7
Number of observations125
Missing cells45
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory59.1 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description서울특별시 용산구 교육종합포털교육기관 현황(기관명, 동이름, 주소, 홈페이지, 전화버호, 위도, 경도)에 대한 데이터를 제공합니다.
Author서울특별시 용산구
URLhttps://www.data.go.kr/data/15070950/fileData.do

Alerts

홈페이지 has 9 (7.2%) missing valuesMissing
위도 has 18 (14.4%) missing valuesMissing
경도 has 18 (14.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:11:47.831215
Analysis finished2023-12-12 09:11:49.156238
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

Distinct118
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T18:11:49.308099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.28
Min length3

Characters and Unicode

Total characters910
Distinct characters154
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)88.8%

Sample

1st row용산구평생학습관
2nd row한국폴리텍대학 서울정수캠퍼스
3rd row숙명여자대학교 미래교육원
4th row용산구 정신건강복지센터
5th row용산 공예관
ValueCountFrequency (%)
주민센터 16
 
10.4%
용산구 5
 
3.2%
숙명여자대학교 4
 
2.6%
후암동 3
 
1.9%
용산도서관 2
 
1.3%
용산2가동 2
 
1.3%
남영동 2
 
1.3%
청파동 2
 
1.3%
원효로1동 2
 
1.3%
용문동 2
 
1.3%
Other values (101) 114
74.0%
2023-12-12T18:11:49.686140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 45
 
4.9%
교 45
 
4.9%
원 36
 
4.0%
동 32
 
3.5%
용 30
 
3.3%
터 30
 
3.3%
29
 
3.2%
센 29
 
3.2%
산 28
 
3.1%
등 27
 
3.0%
Other values (144) 579
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 866
95.2%
Space Separator 29
 
3.2%
Decimal Number 14
 
1.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 45
 
5.2%
교 45
 
5.2%
원 36
 
4.2%
동 32
 
3.7%
용 30
 
3.5%
터 30
 
3.5%
센 29
 
3.3%
산 28
 
3.2%
등 27
 
3.1%
관 19
 
2.2%
Other values (140) 545
62.9%
Decimal Number
ValueCountFrequency (%)
2 8
57.1%
1 6
42.9%
Space Separator
ValueCountFrequency (%)
29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 866
95.2%
Common 44
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 45
 
5.2%
교 45
 
5.2%
원 36
 
4.2%
동 32
 
3.7%
용 30
 
3.5%
터 30
 
3.5%
센 29
 
3.3%
산 28
 
3.2%
등 27
 
3.1%
관 19
 
2.2%
Other values (140) 545
62.9%
Common
ValueCountFrequency (%)
29
65.9%
2 8
 
18.2%
1 6
 
13.6%
, 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 866
95.2%
ASCII 44
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 45
 
5.2%
교 45
 
5.2%
원 36
 
4.2%
동 32
 
3.7%
용 30
 
3.5%
터 30
 
3.5%
센 29
 
3.3%
산 28
 
3.2%
등 27
 
3.1%
관 19
 
2.2%
Other values (140) 545
62.9%
ASCII
ValueCountFrequency (%)
29
65.9%
2 8
 
18.2%
1 6
 
13.6%
, 1
 
2.3%

동이름
Categorical

Distinct17
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
청파동
18 
이촌1동
13 
한남동
11 
후암동
10 
원효로2동
9 
Other values (12)
64 

Length

Max length5
Median length4
Mean length3.792
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한남동
2nd row보광동
3rd row청파동
4th row이태원1동
5th row한남동

Common Values

ValueCountFrequency (%)
청파동 18
14.4%
이촌1동 13
10.4%
한남동 11
8.8%
후암동 10
 
8.0%
원효로2동 9
 
7.2%
한강로동 8
 
6.4%
용산2가동 8
 
6.4%
효창동 8
 
6.4%
원효로1동 7
 
5.6%
서빙고동 6
 
4.8%
Other values (7) 27
21.6%

Length

2023-12-12T18:11:49.836313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청파동 18
14.4%
이촌1동 13
10.4%
한남동 11
8.8%
후암동 10
 
8.0%
원효로2동 9
 
7.2%
한강로동 8
 
6.4%
용산2가동 8
 
6.4%
효창동 8
 
6.4%
원효로1동 7
 
5.6%
서빙고동 6
 
4.8%
Other values (7) 27
21.6%

주소
Text

Distinct105
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T18:11:50.164975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.224
Min length16

Characters and Unicode

Total characters2528
Distinct characters71
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)69.6%

Sample

1st row서울특별시 용산구 이태원로 224-19
2nd row서울특별시 용산구 보광로 73
3rd row서울특별시 용산구 청파로47길 100
4th row서울특별시 용산구 녹사평대로 150
5th row서울특별시 용산구 이태원로 274
ValueCountFrequency (%)
서울특별시 125
24.3%
용산구 124
24.1%
효창원로 8
 
1.6%
이태원로 7
 
1.4%
두텁바위로 7
 
1.4%
6 7
 
1.4%
100 5
 
1.0%
서빙고로 5
 
1.0%
백범로 4
 
0.8%
청파로49길 4
 
0.8%
Other values (134) 218
42.4%
2023-12-12T18:11:50.680896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
567
22.4%
서 134
 
5.3%
시 125
 
4.9%
구 125
 
4.9%
울 125
 
4.9%
별 125
 
4.9%
특 125
 
4.9%
용 124
 
4.9%
산 124
 
4.9%
로 118
 
4.7%
Other values (61) 836
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1516
60.0%
Space Separator 567
 
22.4%
Decimal Number 424
 
16.8%
Dash Punctuation 21
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 134
8.8%
시 125
 
8.2%
구 125
 
8.2%
울 125
 
8.2%
별 125
 
8.2%
특 125
 
8.2%
용 124
 
8.2%
산 124
 
8.2%
로 118
 
7.8%
길 57
 
3.8%
Other values (49) 334
22.0%
Decimal Number
ValueCountFrequency (%)
1 77
18.2%
2 62
14.6%
3 57
13.4%
4 49
11.6%
0 34
8.0%
9 32
7.5%
6 31
7.3%
5 30
 
7.1%
7 29
 
6.8%
8 23
 
5.4%
Space Separator
ValueCountFrequency (%)
567
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1516
60.0%
Common 1012
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 134
8.8%
시 125
 
8.2%
구 125
 
8.2%
울 125
 
8.2%
별 125
 
8.2%
특 125
 
8.2%
용 124
 
8.2%
산 124
 
8.2%
로 118
 
7.8%
길 57
 
3.8%
Other values (49) 334
22.0%
Common
ValueCountFrequency (%)
567
56.0%
1 77
 
7.6%
2 62
 
6.1%
3 57
 
5.6%
4 49
 
4.8%
0 34
 
3.4%
9 32
 
3.2%
6 31
 
3.1%
5 30
 
3.0%
7 29
 
2.9%
Other values (2) 44
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1516
60.0%
ASCII 1012
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
567
56.0%
1 77
 
7.6%
2 62
 
6.1%
3 57
 
5.6%
4 49
 
4.8%
0 34
 
3.4%
9 32
 
3.2%
6 31
 
3.1%
5 30
 
3.0%
7 29
 
2.9%
Other values (2) 44
 
4.3%
Hangul
ValueCountFrequency (%)
서 134
8.8%
시 125
 
8.2%
구 125
 
8.2%
울 125
 
8.2%
별 125
 
8.2%
특 125
 
8.2%
용 124
 
8.2%
산 124
 
8.2%
로 118
 
7.8%
길 57
 
3.8%
Other values (49) 334
22.0%

홈페이지
Text

MISSING 

Distinct99
Distinct (%)85.3%
Missing9
Missing (%)7.2%
Memory size1.1 KiB
2023-12-12T18:11:50.979989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length52.5
Mean length25.396552
Min length8

Characters and Unicode

Total characters2946
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)77.6%

Sample

1st rowyedu.yongsan.go.kr
2nd rowwww.kopo.ac.kr/jungsu
3rd rowopen.sookmyung.ac.kr
4th rowwww.ysmind.org
5th rowcrafts.yongsan.go.kr
ValueCountFrequency (%)
www.yongsan.go.kr 11
 
9.5%
open.sookmyung.ac.kr 3
 
2.6%
www.jungkyung.hs.kr 2
 
1.7%
www.yslibrary.or.kr/small/index.do 2
 
1.7%
www.yongsan.go.kr/site/dc/index.jsp?sitecdv=s0000412 2
 
1.7%
www.yongsan.go.kr/site/dc/index2.jsp?sitecdv=s0000455 2
 
1.7%
www.ysmind.org 2
 
1.7%
www.kopo.ac.kr/jungsu 2
 
1.7%
yongsan.kccf.or.kr 2
 
1.7%
www.yongsan.go.kr/site/dc/index.jsp?sitecdv=s0000413 2
 
1.7%
Other values (86) 86
74.1%
2023-12-12T18:11:51.491082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 357
 
12.1%
w 285
 
9.7%
s 207
 
7.0%
o 191
 
6.5%
n 191
 
6.5%
r 154
 
5.2%
g 133
 
4.5%
k 132
 
4.5%
e 128
 
4.3%
a 113
 
3.8%
Other values (37) 1055
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2252
76.4%
Other Punctuation 483
 
16.4%
Decimal Number 143
 
4.9%
Uppercase Letter 23
 
0.8%
Math Symbol 22
 
0.7%
Space Separator 14
 
0.5%
Dash Punctuation 8
 
0.3%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 285
12.7%
s 207
 
9.2%
o 191
 
8.5%
n 191
 
8.5%
r 154
 
6.8%
g 133
 
5.9%
k 132
 
5.9%
e 128
 
5.7%
a 113
 
5.0%
i 103
 
4.6%
Other values (15) 615
27.3%
Decimal Number
ValueCountFrequency (%)
0 85
59.4%
4 21
 
14.7%
1 12
 
8.4%
5 8
 
5.6%
2 7
 
4.9%
3 4
 
2.8%
7 2
 
1.4%
6 2
 
1.4%
9 1
 
0.7%
8 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 357
73.9%
/ 104
 
21.5%
? 21
 
4.3%
& 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
S 19
82.6%
L 2
 
8.7%
D 1
 
4.3%
I 1
 
4.3%
Math Symbol
ValueCountFrequency (%)
= 22
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2275
77.2%
Common 671
 
22.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 285
12.5%
s 207
 
9.1%
o 191
 
8.4%
n 191
 
8.4%
r 154
 
6.8%
g 133
 
5.8%
k 132
 
5.8%
e 128
 
5.6%
a 113
 
5.0%
i 103
 
4.5%
Other values (19) 638
28.0%
Common
ValueCountFrequency (%)
. 357
53.2%
/ 104
 
15.5%
0 85
 
12.7%
= 22
 
3.3%
4 21
 
3.1%
? 21
 
3.1%
14
 
2.1%
1 12
 
1.8%
- 8
 
1.2%
5 8
 
1.2%
Other values (8) 19
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 357
 
12.1%
w 285
 
9.7%
s 207
 
7.0%
o 191
 
6.5%
n 191
 
6.5%
r 154
 
5.2%
g 133
 
4.5%
k 132
 
4.5%
e 128
 
4.3%
a 113
 
3.8%
Other values (37) 1055
35.8%

전화번호
Text

Distinct101
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T18:11:51.792504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.488
Min length11

Characters and Unicode

Total characters1436
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)64.0%

Sample

1st row02-2199-6490
2nd row02-2001-4000
3rd row02-710-9139
4th row02-2199-8340
5th row02-2199-6180
ValueCountFrequency (%)
02-710-6903 3
 
2.4%
02-2199-8400 3
 
2.4%
02-2199-8520 3
 
2.4%
02-2199-8500 2
 
1.6%
02-2199-8580 2
 
1.6%
02-2199-8620 2
 
1.6%
02-2199-8420 2
 
1.6%
02-702-5501 2
 
1.6%
02-2199-8480 2
 
1.6%
02-2199-8560 2
 
1.6%
Other values (91) 102
81.6%
2023-12-12T18:11:52.273183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 283
19.7%
- 250
17.4%
2 212
14.8%
9 149
10.4%
1 120
8.4%
7 110
 
7.7%
8 75
 
5.2%
4 72
 
5.0%
6 64
 
4.5%
3 51
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1186
82.6%
Dash Punctuation 250
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 283
23.9%
2 212
17.9%
9 149
12.6%
1 120
10.1%
7 110
 
9.3%
8 75
 
6.3%
4 72
 
6.1%
6 64
 
5.4%
3 51
 
4.3%
5 50
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1436
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 283
19.7%
- 250
17.4%
2 212
14.8%
9 149
10.4%
1 120
8.4%
7 110
 
7.7%
8 75
 
5.2%
4 72
 
5.0%
6 64
 
4.5%
3 51
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 283
19.7%
- 250
17.4%
2 212
14.8%
9 149
10.4%
1 120
8.4%
7 110
 
7.7%
8 75
 
5.2%
4 72
 
5.0%
6 64
 
4.5%
3 51
 
3.6%

위도
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)93.5%
Missing18
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean37.442449
Minimum27.542976
Maximum37.553925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:11:52.862118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.542976
5-th percentile37.519037
Q137.528413
median37.536019
Q337.543679
95-th percentile37.550884
Maximum37.553925
Range10.010949
Interquartile range (IQR)0.01526632

Descriptive statistics

Standard deviation0.96609699
Coefficient of variation (CV)0.025802185
Kurtosis106.97706
Mean37.442449
Median Absolute Deviation (MAD)0.0078764
Skewness-10.342433
Sum4006.342
Variance0.9333434
MonotonicityNot monotonic
2023-12-12T18:11:53.076427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5176813 2
 
1.6%
37.54290069 2
 
1.6%
37.54308019 2
 
1.6%
37.54991971 2
 
1.6%
37.52135688 2
 
1.6%
37.52378179 2
 
1.6%
37.54547408 2
 
1.6%
37.53488349 1
 
0.8%
37.5315623 1
 
0.8%
37.55200031 1
 
0.8%
Other values (90) 90
72.0%
(Missing) 18
 
14.4%
ValueCountFrequency (%)
27.542976 1
0.8%
37.5176813 2
1.6%
37.51856465 1
0.8%
37.51891127 1
0.8%
37.51895191 1
0.8%
37.51923499 1
0.8%
37.5195528 1
0.8%
37.52014561 1
0.8%
37.5204768 1
0.8%
37.52050091 1
0.8%
ValueCountFrequency (%)
37.55392482 1
0.8%
37.55301013 1
0.8%
37.55200632 1
0.8%
37.55200031 1
0.8%
37.55196928 1
0.8%
37.55129701 1
0.8%
37.54991971 2
1.6%
37.54869785 1
0.8%
37.5480947 1
0.8%
37.5477533 1
0.8%

경도
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)93.5%
Missing18
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean126.04269
Minimum26.990479
Maximum127.0065
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:11:53.290530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.990479
5-th percentile126.95214
Q1126.96509
median126.97537
Q3126.99034
95-th percentile127.00087
Maximum127.0065
Range100.01602
Interquartile range (IQR)0.02525105

Descriptive statistics

Standard deviation9.6660876
Coefficient of variation (CV)0.076688998
Kurtosis106.99947
Mean126.04269
Median Absolute Deviation (MAD)0.0105635
Skewness-10.344042
Sum13486.568
Variance93.433249
MonotonicityNot monotonic
2023-12-12T18:11:53.485276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9756393 2
 
1.6%
126.9694483 2
 
1.6%
126.9842851 2
 
1.6%
126.9639049 2
 
1.6%
126.9732987 2
 
1.6%
127.0008688 2
 
1.6%
126.9650744 2
 
1.6%
127.000297 1
 
0.8%
126.9686836 1
 
0.8%
126.9676933 1
 
0.8%
Other values (90) 90
72.0%
(Missing) 18
 
14.4%
ValueCountFrequency (%)
26.99047882 1
0.8%
126.9490684 1
0.8%
126.9501815 1
0.8%
126.9515471 1
0.8%
126.9515483 1
0.8%
126.9518612 1
0.8%
126.9527829 1
0.8%
126.9545942 1
0.8%
126.9546578 1
0.8%
126.9575829 1
0.8%
ValueCountFrequency (%)
127.0064986 1
0.8%
127.0062225 1
0.8%
127.0055986 1
0.8%
127.0042997 1
0.8%
127.0020755 1
0.8%
127.0008688 2
1.6%
127.0004933 1
0.8%
127.000297 1
0.8%
127.0002857 1
0.8%
127.000181 1
0.8%

Interactions

2023-12-12T18:11:48.426413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:48.216774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:48.516954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:48.324894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:11:53.590699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동이름홈페이지위도경도
동이름1.0000.8930.0000.439
홈페이지0.8931.0001.0000.000
위도0.0001.0001.0000.000
경도0.4390.0000.0001.000
2023-12-12T18:11:53.724156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동이름
위도1.000-0.1970.000
경도-0.1971.0000.320
동이름0.0000.3201.000

Missing values

2023-12-12T18:11:48.649310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:11:48.910694image/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.
2023-12-12T18:11:49.075046image/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

기관명동이름주소홈페이지전화번호위도경도
0용산구평생학습관한남동서울특별시 용산구 이태원로 224-19yedu.yongsan.go.kr02-2199-649037.534897127.000119
1한국폴리텍대학 서울정수캠퍼스보광동서울특별시 용산구 보광로 73www.kopo.ac.kr/jungsu02-2001-400037.529975126.996817
2숙명여자대학교 미래교육원청파동서울특별시 용산구 청파로47길 100open.sookmyung.ac.kr02-710-913937.545474126.965074
3용산구 정신건강복지센터이태원1동서울특별시 용산구 녹사평대로 150www.ysmind.org02-2199-834037.53245226.990479
4용산 공예관한남동서울특별시 용산구 이태원로 274crafts.yongsan.go.kr02-2199-618037.539027127.002076
5꿈나무종합타운원효로1동서울특별시 용산구 백범로 329yongsanyouthtown.or.kr02-707-070437.538904126.965012
6용산구 자원봉사센터청파동서울특별시 용산구 청파로49길 34yongsan.seoulvc.kr/front02-718-136537.545472126.968502
7숙명여자대학교 미래교육원청파동서울특별시 용산구 청파로47길 100open.sookmyung.ac.kr/02-710-913937.545474126.965074
8별밭작은도서관한남동서울특별시 용산구 대사관로34길 49www.yslibrary.or.kr/small/smallLibDetail.do?smallLibIdx=1502-2199-874037.531241127.006223
9용산구장애인커뮤니티센터서빙고동서울특별시 용산구 서빙고로 245yscc1213.modoo.at/02-6271-959737.520501126.991106
기관명동이름주소홈페이지전화번호위도경도
115한강로동한강로동서울특별시 용산구 한강대로38길 26www.yongsan.go.kr02-2199-8560<NA><NA>
116용문동용문동서울특별시 용산구 새창로12길 13www.yongsan.go.kr/02-2199-8540<NA><NA>
117효창동효창동서울특별시 용산구 효창원로 161www.yongsan.go.kr02-2199-8520<NA><NA>
118원효로2동원효로2동서울특별시 용산구 효창원로8길 3www.yongsan.go.kr02-2199-8500<NA><NA>
119원효로1동원효로1동서울특별시 용산구 백범로 350www.yongsan.go.kr02-2199-8480<NA><NA>
120청파동청파동서울특별시 용산구 청파로49길 6www.yongsan.go.kr02-2199-8460<NA><NA>
121남영동남영동서울특별시 용산구 두텁바위로 25www.yongsan.go.kr02-2199-8440<NA><NA>
122용산2가동용산2가동서울특별시 용산구 신흥로 90www.yongsan.go.kr02-2199-8420<NA><NA>
123후암동후암동서울특별시 용산구 후암로 32 -6www.yongsan.go.kr02-2199-8400<NA><NA>
124용산도서관후암동서울특별시 용산구 두텁바위로 160yslib.sen.go.kr02-6902-777737.551969126.980148