Overview

Dataset statistics

Number of variables6
Number of observations28
Missing cells5
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory54.7 B

Variable types

Numeric2
Text4

Dataset

Description경남도내 도단위 여성단체 현황이며, 2023년 6월말 기준으로 현행화된 자료입니다. 도단위 여성단체 28개 단체로 경상남도여성단체협의회 소속 13개 단체, 경남여성단체연합 소속 4개 단체, 그외 11개 단체가 있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3083576

Alerts

전화번호 has 1 (3.6%) missing valuesMissing
팩스번호 has 4 (14.3%) missing valuesMissing
연번 has unique valuesUnique
단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:37:17.246608
Analysis finished2023-12-11 00:37:18.126716
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T09:37:18.436294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2023-12-11T09:37:18.537352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

단체명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T09:37:18.709620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length13.821429
Min length8

Characters and Unicode

Total characters387
Distinct characters97
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row경상남도여성단체협의회
2nd row경상남도새마을부녀회
3rd row한국생활개선경상남도연합회
4th row경남·울산재향군인회여성회
5th row고향을생각하는주부들의모임 경상남도지회
ValueCountFrequency (%)
경상남도여성단체협의회 1
 
3.1%
경상남도새마을부녀회 1
 
3.1%
사)한국여자의사회경상남도지회 1
 
3.1%
사)대한영양사협회경상남도영양사회 1
 
3.1%
경남여성연대 1
 
3.1%
새시대를여는여성의힘 1
 
3.1%
한국여성농업인경남연합회 1
 
3.1%
한국걸스카우트경남연맹 1
 
3.1%
전문직여성한국연맹창원지부 1
 
3.1%
대한민국전몰군경미망인경남지부 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T09:37:19.042218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 30
 
7.8%
경 27
 
7.0%
남 26
 
6.7%
사 25
 
6.5%
여 15
 
3.9%
한 14
 
3.6%
도 13
 
3.4%
( 13
 
3.4%
) 13
 
3.4%
성 12
 
3.1%
Other values (87) 199
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
90.7%
Open Punctuation 13
 
3.4%
Close Punctuation 13
 
3.4%
Space Separator 4
 
1.0%
Uppercase Letter 4
 
1.0%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 30
 
8.5%
경 27
 
7.7%
남 26
 
7.4%
사 25
 
7.1%
여 15
 
4.3%
한 14
 
4.0%
도 13
 
3.7%
성 12
 
3.4%
상 12
 
3.4%
지 10
 
2.8%
Other values (79) 167
47.6%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
W 1
25.0%
C 1
25.0%
A 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
90.7%
Common 32
 
8.3%
Latin 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 30
 
8.5%
경 27
 
7.7%
남 26
 
7.4%
사 25
 
7.1%
여 15
 
4.3%
한 14
 
4.0%
도 13
 
3.7%
성 12
 
3.4%
상 12
 
3.4%
지 10
 
2.8%
Other values (79) 167
47.6%
Common
ValueCountFrequency (%)
( 13
40.6%
) 13
40.6%
4
 
12.5%
· 2
 
6.2%
Latin
ValueCountFrequency (%)
Y 1
25.0%
W 1
25.0%
C 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
90.7%
ASCII 34
 
8.8%
None 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 30
 
8.5%
경 27
 
7.7%
남 26
 
7.4%
사 25
 
7.1%
여 15
 
4.3%
한 14
 
4.0%
도 13
 
3.7%
성 12
 
3.4%
상 12
 
3.4%
지 10
 
2.8%
Other values (79) 167
47.6%
ASCII
ValueCountFrequency (%)
( 13
38.2%
) 13
38.2%
4
 
11.8%
Y 1
 
2.9%
W 1
 
2.9%
C 1
 
2.9%
A 1
 
2.9%
None
ValueCountFrequency (%)
· 2
100.0%

소재지
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T09:37:19.251745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length33.25
Min length22

Characters and Unicode

Total characters931
Distinct characters121
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row경상남도 창원시 의창구 용지로 240 도여성능력개발센터 323호
2nd row경상남도 창원시 의창구 우곡로 217번길6, 8층 (명서동)
3rd row경상남도 진주 대신로 570(초전동) 농업기술원내
4th row경상남도 창원시 의창구 우곡로 217번길 34(명서동)
5th row경상남도 창원시 의창구 원이대로 627(신월동) 농협경남지역본부내
ValueCountFrequency (%)
경상남도 28
 
15.7%
창원시 25
 
14.0%
의창구 10
 
5.6%
성산구 7
 
3.9%
중앙대로 4
 
2.2%
용지로 4
 
2.2%
마산합포구 4
 
2.2%
마산회원구 4
 
2.2%
창이대로 2
 
1.1%
263 2
 
1.1%
Other values (78) 88
49.4%
2023-12-11T09:37:19.555965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
 
16.1%
창 38
 
4.1%
남 37
 
4.0%
경 34
 
3.7%
상 34
 
3.7%
원 32
 
3.4%
도 30
 
3.2%
시 28
 
3.0%
동 27
 
2.9%
구 25
 
2.7%
Other values (111) 496
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 601
64.6%
Space Separator 150
 
16.1%
Decimal Number 128
 
13.7%
Open Punctuation 19
 
2.0%
Close Punctuation 19
 
2.0%
Other Punctuation 11
 
1.2%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 38
 
6.3%
남 37
 
6.2%
경 34
 
5.7%
상 34
 
5.7%
원 32
 
5.3%
도 30
 
5.0%
시 28
 
4.7%
동 27
 
4.5%
구 25
 
4.2%
로 25
 
4.2%
Other values (93) 291
48.4%
Decimal Number
ValueCountFrequency (%)
1 24
18.8%
2 21
16.4%
5 14
10.9%
0 13
10.2%
3 13
10.2%
6 12
9.4%
7 11
8.6%
8 7
 
5.5%
9 7
 
5.5%
4 6
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
A 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
150
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 601
64.6%
Common 327
35.1%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 38
 
6.3%
남 37
 
6.2%
경 34
 
5.7%
상 34
 
5.7%
원 32
 
5.3%
도 30
 
5.0%
시 28
 
4.7%
동 27
 
4.5%
구 25
 
4.2%
로 25
 
4.2%
Other values (93) 291
48.4%
Common
ValueCountFrequency (%)
150
45.9%
1 24
 
7.3%
2 21
 
6.4%
( 19
 
5.8%
) 19
 
5.8%
5 14
 
4.3%
0 13
 
4.0%
3 13
 
4.0%
6 12
 
3.7%
7 11
 
3.4%
Other values (5) 31
 
9.5%
Latin
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 601
64.6%
ASCII 330
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
45.5%
1 24
 
7.3%
2 21
 
6.4%
( 19
 
5.8%
) 19
 
5.8%
5 14
 
4.2%
0 13
 
3.9%
3 13
 
3.9%
6 12
 
3.6%
7 11
 
3.3%
Other values (8) 34
 
10.3%
Hangul
ValueCountFrequency (%)
창 38
 
6.3%
남 37
 
6.2%
경 34
 
5.7%
상 34
 
5.7%
원 32
 
5.3%
도 30
 
5.0%
시 28
 
4.7%
동 27
 
4.5%
구 25
 
4.2%
로 25
 
4.2%
Other values (93) 291
48.4%

우편번호
Real number (ℝ)

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51723.25
Minimum51210
Maximum57233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T09:37:19.655352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51210
5-th percentile51255.2
Q151419.5
median51438.5
Q351515
95-th percentile52605.75
Maximum57233
Range6023
Interquartile range (IQR)95.5

Descriptive statistics

Standard deviation1129.7354
Coefficient of variation (CV)0.021841925
Kurtosis22.912393
Mean51723.25
Median Absolute Deviation (MAD)58.5
Skewness4.6711217
Sum1448251
Variance1276302
MonotonicityNot monotonic
2023-12-11T09:37:19.745702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
51430 3
 
10.7%
51436 3
 
10.7%
51444 2
 
7.1%
51515 2
 
7.1%
51388 2
 
7.1%
51504 1
 
3.6%
51751 1
 
3.6%
51210 1
 
3.6%
51454 1
 
3.6%
51720 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
51210 1
 
3.6%
51237 1
 
3.6%
51289 1
 
3.6%
51334 1
 
3.6%
51339 1
 
3.6%
51388 2
7.1%
51430 3
10.7%
51434 1
 
3.6%
51436 3
10.7%
51441 1
 
3.6%
ValueCountFrequency (%)
57233 1
3.6%
53066 1
3.6%
51751 1
3.6%
51735 1
3.6%
51722 1
3.6%
51720 1
3.6%
51515 2
7.1%
51504 1
3.6%
51490 1
3.6%
51454 1
3.6%

전화번호
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing1
Missing (%)3.6%
Memory size356.0 B
2023-12-11T09:37:19.903106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters324
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

Unique27 ?
Unique (%)100.0%

Sample

1st row055-262-5221
2nd row055-273-0668
3rd row055-254-1894
4th row055-288-9091
5th row055-268-1721
ValueCountFrequency (%)
055-262-5221 1
 
3.7%
055-242-5043 1
 
3.7%
055-240-6227 1
 
3.7%
055-268-6846 1
 
3.7%
055-238-0389 1
 
3.7%
055-268-1675 1
 
3.7%
055-246-8240 1
 
3.7%
055-298-2740 1
 
3.7%
055-241-1349 1
 
3.7%
055-682-4954 1
 
3.7%
Other values (17) 17
63.0%
2023-12-11T09:37:20.162001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 61
18.8%
- 54
16.7%
2 50
15.4%
0 41
12.7%
6 25
7.7%
8 22
 
6.8%
3 18
 
5.6%
4 16
 
4.9%
1 13
 
4.0%
7 13
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
83.3%
Dash Punctuation 54
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 61
22.6%
2 50
18.5%
0 41
15.2%
6 25
9.3%
8 22
 
8.1%
3 18
 
6.7%
4 16
 
5.9%
1 13
 
4.8%
7 13
 
4.8%
9 11
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 61
18.8%
- 54
16.7%
2 50
15.4%
0 41
12.7%
6 25
7.7%
8 22
 
6.8%
3 18
 
5.6%
4 16
 
4.9%
1 13
 
4.0%
7 13
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 61
18.8%
- 54
16.7%
2 50
15.4%
0 41
12.7%
6 25
7.7%
8 22
 
6.8%
3 18
 
5.6%
4 16
 
4.9%
1 13
 
4.0%
7 13
 
4.0%

팩스번호
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing4
Missing (%)14.3%
Memory size356.0 B
2023-12-11T09:37:20.324215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.041667
Min length11

Characters and Unicode

Total characters289
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

Unique24 ?
Unique (%)100.0%

Sample

1st row055-262-5251
2nd row055-254-1859
3rd row055-288-9089
4th row055268-1729
5th row055-223-1811
ValueCountFrequency (%)
055-281-3950 1
 
4.2%
055-254-1859 1
 
4.2%
0303-3440-0361 1
 
4.2%
055-268-6847 1
 
4.2%
055-238-0390 1
 
4.2%
055-263-2334 1
 
4.2%
055-245-8240 1
 
4.2%
055-241-1348 1
 
4.2%
055-681-0127 1
 
4.2%
055-278-2781 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T09:37:20.585195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 57
19.7%
- 47
16.3%
0 39
13.5%
2 37
12.8%
8 23
8.0%
1 17
 
5.9%
4 17
 
5.9%
3 16
 
5.5%
6 15
 
5.2%
9 11
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242
83.7%
Dash Punctuation 47
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 57
23.6%
0 39
16.1%
2 37
15.3%
8 23
9.5%
1 17
 
7.0%
4 17
 
7.0%
3 16
 
6.6%
6 15
 
6.2%
9 11
 
4.5%
7 10
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 289
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 57
19.7%
- 47
16.3%
0 39
13.5%
2 37
12.8%
8 23
8.0%
1 17
 
5.9%
4 17
 
5.9%
3 16
 
5.5%
6 15
 
5.2%
9 11
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 57
19.7%
- 47
16.3%
0 39
13.5%
2 37
12.8%
8 23
8.0%
1 17
 
5.9%
4 17
 
5.9%
3 16
 
5.5%
6 15
 
5.2%
9 11
 
3.8%

Interactions

2023-12-11T09:37:17.718010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:17.518632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:17.807546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:17.624203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:37:20.665015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단체명소재지우편번호전화번호팩스번호
연번1.0001.0000.9320.0001.0001.000
단체명1.0001.0001.0001.0001.0001.000
소재지0.9321.0001.0001.0001.0001.000
우편번호0.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
팩스번호1.0001.0001.0001.0001.0001.000
2023-12-11T09:37:20.741544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.162
우편번호0.1621.000

Missing values

2023-12-11T09:37:17.930965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:37:18.016670image/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.
2023-12-11T09:37:18.087713image/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

연번단체명소재지우편번호전화번호팩스번호
01경상남도여성단체협의회경상남도 창원시 의창구 용지로 240 도여성능력개발센터 323호51430055-262-5221055-262-5251
12경상남도새마을부녀회경상남도 창원시 의창구 우곡로 217번길6, 8층 (명서동)51388055-273-0668<NA>
23한국생활개선경상남도연합회경상남도 진주 대신로 570(초전동) 농업기술원내57233055-254-1894055-254-1859
34경남·울산재향군인회여성회경상남도 창원시 의창구 우곡로 217번길 34(명서동)51388055-288-9091055-288-9089
45고향을생각하는주부들의모임 경상남도지회경상남도 창원시 의창구 원이대로 627(신월동) 농협경남지역본부내51444055-268-1721055268-1729
56(사)대한미용사회경상남도지회경상남도 창원시 마산회원구 내서읍 중리상곡로 136, 동신2차A 상가 204호51289055-223-2011055-223-1811
67(사)소비자교육중앙회경상남도지부경상남도 창원시 마산합포구 합포북1길 9, 신동방빌딩 4층51334055-242-8334055-224-1449
78한국부인회경상남도지부경상남도 창원시 성산구 중앙대로 111(중앙동), 평화오피스텔 909호51515055-286-8909055-244-8585
89(사)경상남도여약사회경상남도 창원시 의창구 용지로 153번길3(용호동)오피스프라자 808호51436055-287-7287055-287-7290
910(사)대한간호협회경상남도간호사회경상남도 창원시 성산구 중앙대로 263, 403호(오피스프라자)51436055-262-6006055-262-6098
연번단체명소재지우편번호전화번호팩스번호
1819경남여성지도자협의회경상남도 창원시 마산회원구 봉암공단14길 5, 2층51339<NA><NA>
1920경남YWCA협의회경상남도 거제시 탑곡로 75, 거제시노동복지회관51735055-682-4954055-681-0127
2021대한민국전몰군경미망인경남지부경상남도 창원시 의창구 창이대로 510(용호동) 경남보훈회관 3층51430055-241-1349055-241-1348
2122전문직여성한국연맹창원지부경상남도 창원시 마산회원구 내서읍 경남대로 91151237055-298-2740<NA>
2223한국걸스카우트경남연맹경상남도 창원시 마산합포구 동서동로 18(신포동)롯데백화점OT 152351720055-246-8240055-245-8240
2324한국여성농업인경남연합회경상남도 창원시 의창구 원이대로 627(신월동) 농협경남지역본부내51444055-268-1675055-263-2334
2425새시대를여는여성의힘 경남여성연대경상남도 창원시 성산구 창이대로 663번길5(사파동)미남빌딩 지하 102호51454055-238-0389055-238-0390
2526(사)대한영양사협회경상남도영양사회경상남도 창원시 성산구 중앙대로 111(중앙동) 평화오피스텔 709호51515055-268-6846055-268-6847
2627(사)한국여자의사회경상남도지회경상남도 창원시 마산회원구 3.15대로 727 미래메디컬51210055-240-6227<NA>
2728(사)대한조산협회경남조산사회경상남도 창원시 마산합포구 월영동서로 1(해운동) 해동빌딩 5층51751055-252-3322055-252-3239