Overview

Dataset statistics

Number of variables8
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory68.2 B

Variable types

Categorical3
Text3
Numeric2

Dataset

Description제주특별자치도 제주시 관내 장애인복지시설 관련 현황 데이터를 제공합니다. 항목 : 시설구분1, 시설구분2, 시설명, 소재지, 정원, 현원, 전화번호
URLhttps://www.data.go.kr/data/15056363/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
시설구분2 is highly overall correlated with 정원 and 2 other fieldsHigh correlation
시설구분1 is highly overall correlated with 정원 and 2 other fieldsHigh correlation
정원 is highly overall correlated with 현원 and 2 other fieldsHigh correlation
현원 is highly overall correlated with 정원 and 2 other fieldsHigh correlation
시설구분1 is highly imbalanced (54.8%)Imbalance
시설명 has unique valuesUnique
정원 has 1 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:38:55.145606
Analysis finished2023-12-12 04:38:56.352744
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
장애인복지시설
52 
정신건강시설
7 
노숙인재활시설
 
2

Length

Max length7
Median length7
Mean length6.8852459
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장애인복지시설 52
85.2%
정신건강시설 7
 
11.5%
노숙인재활시설 2
 
3.3%

Length

2023-12-12T13:38:56.418810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:56.536314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인복지시설 52
85.2%
정신건강시설 7
 
11.5%
노숙인재활시설 2
 
3.3%

시설구분2
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
주간보호시설
21 
거주시설
10 
공동생활가정
7 
직업재활시설
7 
단기거주시설
6 
Other values (5)
10 

Length

Max length9
Median length6
Mean length5.7377049
Min length4

Unique

Unique4 ?
Unique (%)6.6%

Sample

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

Common Values

ValueCountFrequency (%)
주간보호시설 21
34.4%
거주시설 10
16.4%
공동생활가정 7
 
11.5%
직업재활시설 7
 
11.5%
단기거주시설 6
 
9.8%
정신재활시설 6
 
9.8%
의료재활시설 1
 
1.6%
정신요양시설 1
 
1.6%
노숙인재활시설 1
 
1.6%
노숙인종합지원센터 1
 
1.6%

Length

2023-12-12T13:38:56.660818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:56.806189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주간보호시설 21
34.4%
거주시설 10
16.4%
공동생활가정 7
 
11.5%
직업재활시설 7
 
11.5%
단기거주시설 6
 
9.8%
정신재활시설 6
 
9.8%
의료재활시설 1
 
1.6%
정신요양시설 1
 
1.6%
노숙인재활시설 1
 
1.6%
노숙인종합지원센터 1
 
1.6%

시설명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-12T13:38:57.124427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.4754098
Min length2

Characters and Unicode

Total characters456
Distinct characters131
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row아가의집
2nd row송죽원
3rd row제주장애인요양원
4th row제주애덕의집
5th row가롤로의집
ValueCountFrequency (%)
공동생활가정 3
 
4.2%
주간보호시설 3
 
4.2%
주간보호센터 2
 
2.8%
천사나래주간보호센터 1
 
1.4%
한라주간보호센터 1
 
1.4%
희망나래활동센터 1
 
1.4%
한솔주간활동센터 1
 
1.4%
행복한쉼터 1
 
1.4%
제주가톨릭장애인 1
 
1.4%
신장장애인 1
 
1.4%
Other values (57) 57
79.2%
2023-12-12T13:38:57.578253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 28
 
6.1%
터 26
 
5.7%
센 21
 
4.6%
활 17
 
3.7%
간 17
 
3.7%
동 16
 
3.5%
장 15
 
3.3%
애 15
 
3.3%
인 14
 
3.1%
11
 
2.4%
Other values (121) 276
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
97.6%
Space Separator 11
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 28
 
6.3%
터 26
 
5.8%
센 21
 
4.7%
활 17
 
3.8%
간 17
 
3.8%
동 16
 
3.6%
장 15
 
3.4%
애 15
 
3.4%
인 14
 
3.1%
원 10
 
2.2%
Other values (120) 266
59.8%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 445
97.6%
Common 11
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 28
 
6.3%
터 26
 
5.8%
센 21
 
4.7%
활 17
 
3.8%
간 17
 
3.8%
동 16
 
3.6%
장 15
 
3.4%
애 15
 
3.4%
인 14
 
3.1%
원 10
 
2.2%
Other values (120) 266
59.8%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
97.6%
ASCII 11
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 28
 
6.3%
터 26
 
5.8%
센 21
 
4.7%
활 17
 
3.8%
간 17
 
3.8%
동 16
 
3.6%
장 15
 
3.4%
애 15
 
3.4%
인 14
 
3.1%
원 10
 
2.2%
Other values (120) 266
59.8%
ASCII
ValueCountFrequency (%)
11
100.0%

소재지
Text

Distinct54
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-12T13:38:57.925337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length26.622951
Min length22

Characters and Unicode

Total characters1624
Distinct characters113
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)78.7%

Sample

1st row제주특별자치도 제주시 조천읍 함와로 267-5
2nd row제주특별자치도 제주시 애월읍 하소로 747-23
3rd row제주특별자치도 제주시 첨단로 202(영평동)
4th row제주특별자치도 제주시 기와5길 87(화북이동)
5th row제주특별자치도 제주시 기와5길 87(화북이동)
ValueCountFrequency (%)
제주특별자치도 61
21.7%
제주시 60
21.4%
한림읍 7
 
2.5%
애월읍 6
 
2.1%
기와5길 5
 
1.8%
조천읍 5
 
1.8%
아봉로 4
 
1.4%
87(화북이동 3
 
1.1%
하소로 3
 
1.1%
해안마을2길 3
 
1.1%
Other values (112) 124
44.1%
2023-12-12T13:38:58.385418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
220
 
13.5%
제 121
 
7.5%
주 121
 
7.5%
도 77
 
4.7%
특 61
 
3.8%
별 61
 
3.8%
자 61
 
3.8%
치 61
 
3.8%
시 60
 
3.7%
1 50
 
3.1%
Other values (103) 731
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1044
64.3%
Decimal Number 236
 
14.5%
Space Separator 220
 
13.5%
Close Punctuation 41
 
2.5%
Open Punctuation 41
 
2.5%
Dash Punctuation 30
 
1.8%
Other Punctuation 11
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 121
 
11.6%
주 121
 
11.6%
도 77
 
7.4%
특 61
 
5.8%
별 61
 
5.8%
자 61
 
5.8%
치 61
 
5.8%
시 60
 
5.7%
동 47
 
4.5%
로 37
 
3.5%
Other values (87) 337
32.3%
Decimal Number
ValueCountFrequency (%)
1 50
21.2%
2 35
14.8%
4 32
13.6%
7 28
11.9%
5 20
 
8.5%
0 19
 
8.1%
3 18
 
7.6%
8 15
 
6.4%
9 10
 
4.2%
6 9
 
3.8%
Space Separator
ValueCountFrequency (%)
220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1044
64.3%
Common 579
35.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 121
 
11.6%
주 121
 
11.6%
도 77
 
7.4%
특 61
 
5.8%
별 61
 
5.8%
자 61
 
5.8%
치 61
 
5.8%
시 60
 
5.7%
동 47
 
4.5%
로 37
 
3.5%
Other values (87) 337
32.3%
Common
ValueCountFrequency (%)
220
38.0%
1 50
 
8.6%
) 41
 
7.1%
( 41
 
7.1%
2 35
 
6.0%
4 32
 
5.5%
- 30
 
5.2%
7 28
 
4.8%
5 20
 
3.5%
0 19
 
3.3%
Other values (5) 63
 
10.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1044
64.3%
ASCII 580
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220
37.9%
1 50
 
8.6%
) 41
 
7.1%
( 41
 
7.1%
2 35
 
6.0%
4 32
 
5.5%
- 30
 
5.2%
7 28
 
4.8%
5 20
 
3.4%
0 19
 
3.3%
Other values (6) 64
 
11.0%
Hangul
ValueCountFrequency (%)
제 121
 
11.6%
주 121
 
11.6%
도 77
 
7.4%
특 61
 
5.8%
별 61
 
5.8%
자 61
 
5.8%
치 61
 
5.8%
시 60
 
5.7%
동 47
 
4.5%
로 37
 
3.5%
Other values (87) 337
32.3%

정원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.737705
Minimum0
Maximum250
Zeros1
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-12T13:38:58.562144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q115
median20
Q334
95-th percentile60
Maximum250
Range250
Interquartile range (IQR)19

Descriptive statistics

Standard deviation33.77815
Coefficient of variation (CV)1.1753948
Kurtosis31.227624
Mean28.737705
Median Absolute Deviation (MAD)10
Skewness4.9737572
Sum1753
Variance1140.9634
MonotonicityNot monotonic
2023-12-12T13:38:58.757849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20 12
19.7%
15 7
 
11.5%
30 6
 
9.8%
40 5
 
8.2%
4 5
 
8.2%
34 2
 
3.3%
50 2
 
3.3%
10 2
 
3.3%
250 1
 
1.6%
16 1
 
1.6%
Other values (18) 18
29.5%
ValueCountFrequency (%)
0 1
 
1.6%
4 5
8.2%
5 1
 
1.6%
7 1
 
1.6%
8 1
 
1.6%
9 1
 
1.6%
10 2
 
3.3%
13 1
 
1.6%
14 1
 
1.6%
15 7
11.5%
ValueCountFrequency (%)
250 1
 
1.6%
100 1
 
1.6%
62 1
 
1.6%
60 1
 
1.6%
55 1
 
1.6%
50 2
 
3.3%
46 1
 
1.6%
41 1
 
1.6%
40 5
8.2%
38 1
 
1.6%

현원
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.754098
Minimum2
Maximum167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-12T13:38:58.930925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q113
median20
Q332
95-th percentile59
Maximum167
Range165
Interquartile range (IQR)19

Descriptive statistics

Standard deviation27.50676
Coefficient of variation (CV)1.0281326
Kurtosis13.270845
Mean26.754098
Median Absolute Deviation (MAD)10
Skewness3.2126039
Sum1632
Variance756.62186
MonotonicityNot monotonic
2023-12-12T13:38:59.092031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
20 8
 
13.1%
15 4
 
6.6%
3 3
 
4.9%
40 3
 
4.9%
30 3
 
4.9%
7 2
 
3.3%
28 2
 
3.3%
4 2
 
3.3%
2 2
 
3.3%
6 2
 
3.3%
Other values (24) 30
49.2%
ValueCountFrequency (%)
2 2
3.3%
3 3
4.9%
4 2
3.3%
6 2
3.3%
7 2
3.3%
9 1
 
1.6%
10 2
3.3%
12 1
 
1.6%
13 2
3.3%
14 2
3.3%
ValueCountFrequency (%)
167 1
 
1.6%
130 1
 
1.6%
71 1
 
1.6%
59 1
 
1.6%
57 1
 
1.6%
50 1
 
1.6%
49 1
 
1.6%
46 1
 
1.6%
40 3
4.9%
38 2
3.3%

전화번호
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-12T13:38:59.373378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016393
Min length12

Characters and Unicode

Total characters733
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

Unique59 ?
Unique (%)96.7%

Sample

1st row064-783-9000
2nd row064-799-8555
3rd row064-702-2321
4th row064-724-8101
5th row064-723-0245
ValueCountFrequency (%)
064-747-1371 2
 
3.3%
064-783-9000 1
 
1.6%
064-783-0928 1
 
1.6%
064-721-7300 1
 
1.6%
064-796-8161 1
 
1.6%
064-721-4440 1
 
1.6%
064-748-5544 1
 
1.6%
064-712-1633 1
 
1.6%
064-751-1197 1
 
1.6%
064-724-0999 1
 
1.6%
Other values (50) 50
82.0%
2023-12-12T13:38:59.768439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
7 96
13.1%
4 89
12.1%
6 85
11.6%
5 48
 
6.5%
1 44
 
6.0%
2 42
 
5.7%
9 40
 
5.5%
3 36
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 611
83.4%
Dash Punctuation 122
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
17.3%
7 96
15.7%
4 89
14.6%
6 85
13.9%
5 48
7.9%
1 44
7.2%
2 42
 
6.9%
9 40
 
6.5%
3 36
 
5.9%
8 25
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 733
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
7 96
13.1%
4 89
12.1%
6 85
11.6%
5 48
 
6.5%
1 44
 
6.0%
2 42
 
5.7%
9 40
 
5.5%
3 36
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.6%
0 106
14.5%
7 96
13.1%
4 89
12.1%
6 85
11.6%
5 48
 
6.5%
1 44
 
6.0%
2 42
 
5.7%
9 40
 
5.5%
3 36
 
4.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-03-01
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-01
2nd row2023-03-01
3rd row2023-03-01
4th row2023-03-01
5th row2023-03-01

Common Values

ValueCountFrequency (%)
2023-03-01 61
100.0%

Length

2023-12-12T13:38:59.958862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:00.092674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-01 61
100.0%

Interactions

2023-12-12T13:38:55.830339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.627168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.950570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.726900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:39:00.183311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분1시설구분2시설명소재지정원현원전화번호
시설구분11.0001.0001.0000.9690.6110.7011.000
시설구분21.0001.0001.0000.9450.9880.9270.980
시설명1.0001.0001.0001.0001.0001.0001.000
소재지0.9690.9451.0001.0000.8760.9791.000
정원0.6110.9881.0000.8761.0000.9001.000
현원0.7010.9271.0000.9790.9001.0001.000
전화번호1.0000.9801.0001.0001.0001.0001.000
2023-12-12T13:39:00.320775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분2시설구분1
시설구분21.0000.938
시설구분10.9381.000
2023-12-12T13:39:00.760561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원현원시설구분1시설구분2
정원1.0000.8870.5860.843
현원0.8871.0000.5940.790
시설구분10.5860.5941.0000.938
시설구분20.8430.7900.9381.000

Missing values

2023-12-12T13:38:56.133197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:38:56.297939image/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.

Sample

시설구분1시설구분2시설명소재지정원현원전화번호데이터기준일자
0장애인복지시설거주시설아가의집제주특별자치도 제주시 조천읍 함와로 267-53434064-783-90002023-03-01
1장애인복지시설거주시설송죽원제주특별자치도 제주시 애월읍 하소로 747-233432064-799-85552023-03-01
2장애인복지시설거주시설제주장애인요양원제주특별자치도 제주시 첨단로 202(영평동)3231064-702-23212023-03-01
3장애인복지시설거주시설제주애덕의집제주특별자치도 제주시 기와5길 87(화북이동)5049064-724-81012023-03-01
4장애인복지시설거주시설가롤로의집제주특별자치도 제주시 기와5길 87(화북이동)3030064-723-02452023-03-01
5장애인복지시설거주시설창암재활원제주특별자치도 제주시 애월읍 산록서로 482-343838064-799-15552023-03-01
6장애인복지시설거주시설사랑의집제주특별자치도 제주시 기와5길 115(화북이동)4038064-725-99312023-03-01
7장애인복지시설거주시설벧엘제주특별자치도 제주시 한림읍 명월남길 58-14133064-796-60862023-03-01
8장애인복지시설거주시설케어하우스제주특별자치도 제주시 첨단로 202(영평동)3029064-702-94232023-03-01
9장애인복지시설거주시설송향원제주특별자치도 제주시 애월읍 하소로 747-423022064-799-80772023-03-01
시설구분1시설구분2시설명소재지정원현원전화번호데이터기준일자
51장애인복지시설주간보호시설선정주간활동센터제주특별자치도 제주시 우평로 28-2(노형동)2020064-713-51802023-03-01
52정신건강시설정신요양시설무지개마을제주특별자치도 제주시 아봉로 449-1(월평동)250167064-723-22562023-03-01
53정신건강시설정신재활시설제주정신재활센터제주특별자치도 제주시 동광로1길 11, 4층 (이도일동, 영재빌딩)4040064-742-95002023-03-01
54정신건강시설정신재활시설길정신건강센터제주특별자치도 제주시 한림읍 한림뱅디길 88-175031064-796-70032023-03-01
55정신건강시설정신재활시설그루터기제주특별자치도 제주시 원당북로 65(삼양일동)3028064-759-22542023-03-01
56정신건강시설정신재활시설공생하우스제주특별자치도 제주시 아봉로 449-10(월평동)107064-723-22592023-03-01
57정신건강시설정신재활시설볼리션제주특별자치도 제주시 설촌로2길 30, 101호(삼양이동)2320064-702-84762023-03-01
58정신건강시설정신재활시설우리야제주특별자치도 제주시 신설동길 3-1(일도이동)84064-751-74002023-03-01
59노숙인재활시설노숙인재활시설제주시희망원제주특별자치도 제주시 아봉로 451(월평동)10071064-721-07112023-03-01
60노숙인재활시설노숙인종합지원센터희망나눔종합지원센터제주특별자치도 제주시 탑동로15길 2(삼도이동)6057064-753-07112023-03-01