Overview

Dataset statistics

Number of variables9
Number of observations51
Missing cells36
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory75.6 B

Variable types

Numeric1
Boolean1
Text4
Categorical2
DateTime1

Dataset

Description충청남도 홍성군 직업소개소 현황으로 유무료구분, 법인명, 법인대표자, 운영상태, 전화번호, 사업소 주소, 데이터 기준일 등을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=439&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028220

Alerts

운영상태 has constant value ""Constant
데이터기준일자 has constant value ""Constant
유무료구분 is highly overall correlated with 법인개인구분High correlation
법인개인구분 is highly overall correlated with 유무료구분High correlation
유무료구분 is highly imbalanced (60.3%)Imbalance
법인개인구분 is highly imbalanced (60.3%)Imbalance
사업소 전화번호 has 36 (70.6%) missing valuesMissing
순번 has unique valuesUnique
법인명 has unique valuesUnique
사업소주소 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:30:12.365911
Analysis finished2024-01-09 20:30:12.937442
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-01-10T05:30:13.002698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-01-10T05:30:13.122917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

유무료구분
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
47 
False
 
4
ValueCountFrequency (%)
True 47
92.2%
False 4
 
7.8%
2024-01-10T05:30:13.228836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

법인명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-10T05:30:13.415642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.7843137
Min length4

Characters and Unicode

Total characters346
Distinct characters112
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

Unique51 ?
Unique (%)100.0%

Sample

1st row삼성인력
2nd row명진인력
3rd row동원인력
4th row백호인력
5th row매일조경인력
ValueCountFrequency (%)
삼성인력 1
 
1.9%
혜성여성인력사무소 1
 
1.9%
신도시직업소개소 1
 
1.9%
태평직업소개소 1
 
1.9%
하나인력 1
 
1.9%
h.s 1
 
1.9%
직업소개소 1
 
1.9%
뽀빠이직업소개소 1
 
1.9%
모두인력개발 1
 
1.9%
홍성제일인력사무소 1
 
1.9%
Other values (42) 42
80.8%
2024-01-10T05:30:13.740215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 46
 
13.3%
인 32
 
9.2%
력 31
 
9.0%
개 24
 
6.9%
업 20
 
5.8%
직 19
 
5.5%
성 10
 
2.9%
홍 7
 
2.0%
무 4
 
1.2%
료 4
 
1.2%
Other values (102) 149
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
98.8%
Uppercase Letter 2
 
0.6%
Other Punctuation 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 46
 
13.5%
인 32
 
9.4%
력 31
 
9.1%
개 24
 
7.0%
업 20
 
5.8%
직 19
 
5.6%
성 10
 
2.9%
홍 7
 
2.0%
무 4
 
1.2%
료 4
 
1.2%
Other values (98) 145
42.4%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
98.8%
Latin 2
 
0.6%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 46
 
13.5%
인 32
 
9.4%
력 31
 
9.1%
개 24
 
7.0%
업 20
 
5.8%
직 19
 
5.6%
성 10
 
2.9%
홍 7
 
2.0%
무 4
 
1.2%
료 4
 
1.2%
Other values (98) 145
42.4%
Latin
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%
Common
ValueCountFrequency (%)
. 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
98.8%
ASCII 4
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 46
 
13.5%
인 32
 
9.4%
력 31
 
9.1%
개 24
 
7.0%
업 20
 
5.8%
직 19
 
5.6%
성 10
 
2.9%
홍 7
 
2.0%
무 4
 
1.2%
료 4
 
1.2%
Other values (98) 145
42.4%
ASCII
ValueCountFrequency (%)
H 1
25.0%
. 1
25.0%
S 1
25.0%
1
25.0%

법인대표자명
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-10T05:30:13.950696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters153
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)96.1%

Sample

1st row박규철
2nd row박명진
3rd row백명기
4th row박진복
5th row최장석
ValueCountFrequency (%)
김선태 2
 
3.9%
이광연 1
 
2.0%
박태진 1
 
2.0%
최황락 1
 
2.0%
손희대 1
 
2.0%
이승범 1
 
2.0%
원자희 1
 
2.0%
윤훈선 1
 
2.0%
김귀선 1
 
2.0%
조정암 1
 
2.0%
Other values (40) 40
78.4%
2024-01-10T05:30:14.247735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 9
 
5.9%
이 8
 
5.2%
선 5
 
3.3%
진 4
 
2.6%
조 4
 
2.6%
영 4
 
2.6%
호 4
 
2.6%
박 4
 
2.6%
명 4
 
2.6%
희 4
 
2.6%
Other values (65) 103
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
5.9%
이 8
 
5.2%
선 5
 
3.3%
진 4
 
2.6%
조 4
 
2.6%
영 4
 
2.6%
호 4
 
2.6%
박 4
 
2.6%
명 4
 
2.6%
희 4
 
2.6%
Other values (65) 103
67.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
5.9%
이 8
 
5.2%
선 5
 
3.3%
진 4
 
2.6%
조 4
 
2.6%
영 4
 
2.6%
호 4
 
2.6%
박 4
 
2.6%
명 4
 
2.6%
희 4
 
2.6%
Other values (65) 103
67.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 9
 
5.9%
이 8
 
5.2%
선 5
 
3.3%
진 4
 
2.6%
조 4
 
2.6%
영 4
 
2.6%
호 4
 
2.6%
박 4
 
2.6%
명 4
 
2.6%
희 4
 
2.6%
Other values (65) 103
67.3%

법인개인구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
개인
47 
법인
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 47
92.2%
법인 4
 
7.8%

Length

2024-01-10T05:30:14.361584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:30:14.441798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 47
92.2%
법인 4
 
7.8%

운영상태
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
영업중
51 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 51
100.0%

Length

2024-01-10T05:30:14.529838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:30:14.610735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 51
100.0%

사업소 전화번호
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing36
Missing (%)70.6%
Memory size540.0 B
2024-01-10T05:30:14.743309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters180
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row041-641-6699
2nd row041-632-0339
3rd row041-634-9388
4th row041-632-5500
5th row041-635-1036
ValueCountFrequency (%)
041-641-6699 1
 
5.9%
041 1
 
5.9%
041-641-1583 1
 
5.9%
041-633-1101 1
 
5.9%
041-632-5555 1
 
5.9%
041-634-0405 1
 
5.9%
4544 1
 
5.9%
633 1
 
5.9%
041-631-4848 1
 
5.9%
041-632-0339 1
 
5.9%
Other values (7) 7
41.2%
2024-01-10T05:30:15.043267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 28
15.6%
4 26
14.4%
1 26
14.4%
0 24
13.3%
3 22
12.2%
6 20
11.1%
5 13
7.2%
8 7
 
3.9%
2 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
83.3%
Dash Punctuation 28
 
15.6%
Space Separator 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 26
17.3%
1 26
17.3%
0 24
16.0%
3 22
14.7%
6 20
13.3%
5 13
8.7%
8 7
 
4.7%
2 6
 
4.0%
9 4
 
2.7%
7 2
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 28
15.6%
4 26
14.4%
1 26
14.4%
0 24
13.3%
3 22
12.2%
6 20
11.1%
5 13
7.2%
8 7
 
3.9%
2 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 28
15.6%
4 26
14.4%
1 26
14.4%
0 24
13.3%
3 22
12.2%
6 20
11.1%
5 13
7.2%
8 7
 
3.9%
2 6
 
3.3%
9 4
 
2.2%
Other values (2) 4
 
2.2%

사업소주소
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-10T05:30:15.300042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length30
Mean length24.823529
Min length19

Characters and Unicode

Total characters1266
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row충청남도 홍성군 홍성읍 의사로63번길 10
2nd row충청남도 홍성군 홍성읍 대학길 21
3rd row충청남도 홍성군 장곡면 홍남동로 493
4th row충청남도 홍성군 홍성읍 충절로1053번길 51
5th row충청남도 홍성군 광천읍 광천로273번길 78
ValueCountFrequency (%)
홍성군 52
18.5%
충청남도 51
18.1%
홍성읍 36
 
12.8%
광천읍 9
 
3.2%
2층 7
 
2.5%
1층 5
 
1.8%
홍남로 4
 
1.4%
의사로72번길 3
 
1.1%
의사로36번길 3
 
1.1%
문화로 2
 
0.7%
Other values (99) 109
38.8%
2024-01-10T05:30:15.663600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
230
18.2%
홍 96
 
7.6%
성 89
 
7.0%
충 59
 
4.7%
남 58
 
4.6%
도 52
 
4.1%
군 52
 
4.1%
청 52
 
4.1%
1 52
 
4.1%
읍 47
 
3.7%
Other values (60) 479
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
60.7%
Decimal Number 237
 
18.7%
Space Separator 230
 
18.2%
Other Punctuation 19
 
1.5%
Dash Punctuation 10
 
0.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 96
12.5%
성 89
11.6%
충 59
 
7.7%
남 58
 
7.6%
도 52
 
6.8%
군 52
 
6.8%
청 52
 
6.8%
읍 47
 
6.1%
로 47
 
6.1%
길 33
 
4.3%
Other values (45) 183
23.8%
Decimal Number
ValueCountFrequency (%)
1 52
21.9%
2 39
16.5%
3 27
11.4%
6 24
10.1%
0 21
8.9%
4 18
 
7.6%
7 17
 
7.2%
9 15
 
6.3%
5 14
 
5.9%
8 10
 
4.2%
Space Separator
ValueCountFrequency (%)
230
100.0%
Other Punctuation
ValueCountFrequency (%)
. 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 768
60.7%
Common 498
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 96
12.5%
성 89
11.6%
충 59
 
7.7%
남 58
 
7.6%
도 52
 
6.8%
군 52
 
6.8%
청 52
 
6.8%
읍 47
 
6.1%
로 47
 
6.1%
길 33
 
4.3%
Other values (45) 183
23.8%
Common
ValueCountFrequency (%)
230
46.2%
1 52
 
10.4%
2 39
 
7.8%
3 27
 
5.4%
6 24
 
4.8%
0 21
 
4.2%
. 19
 
3.8%
4 18
 
3.6%
7 17
 
3.4%
9 15
 
3.0%
Other values (5) 36
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 768
60.7%
ASCII 498
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
230
46.2%
1 52
 
10.4%
2 39
 
7.8%
3 27
 
5.4%
6 24
 
4.8%
0 21
 
4.2%
. 19
 
3.8%
4 18
 
3.6%
7 17
 
3.4%
9 15
 
3.0%
Other values (5) 36
 
7.2%
Hangul
ValueCountFrequency (%)
홍 96
12.5%
성 89
11.6%
충 59
 
7.7%
남 58
 
7.6%
도 52
 
6.8%
군 52
 
6.8%
청 52
 
6.8%
읍 47
 
6.1%
로 47
 
6.1%
길 33
 
4.3%
Other values (45) 183
23.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2023-09-27 00:00:00
Maximum2023-09-27 00:00:00
2024-01-10T05:30:15.763715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:30:15.853501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T05:30:12.679295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:30:15.932592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분법인명법인대표자명법인개인구분사업소 전화번호사업소주소
순번1.0000.0001.0000.9550.0001.0001.000
유무료구분0.0001.0001.0000.0000.9761.0001.000
법인명1.0001.0001.0001.0001.0001.0001.000
법인대표자명0.9550.0001.0001.0000.0001.0001.000
법인개인구분0.0000.9761.0000.0001.0001.0001.000
사업소 전화번호1.0001.0001.0001.0001.0001.0001.000
사업소주소1.0001.0001.0001.0001.0001.0001.000
2024-01-10T05:30:16.049625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인개인구분유무료구분
법인개인구분1.0000.861
유무료구분0.8611.000
2024-01-10T05:30:16.142223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분법인개인구분
순번1.0000.0000.000
유무료구분0.0001.0000.861
법인개인구분0.0000.8611.000

Missing values

2024-01-10T05:30:12.777741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:30:12.889996image/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

순번유무료구분법인명법인대표자명법인개인구분운영상태사업소 전화번호사업소주소데이터기준일자
01Y삼성인력박규철개인영업중<NA>충청남도 홍성군 홍성읍 의사로63번길 102023-09-27
12Y명진인력박명진개인영업중<NA>충청남도 홍성군 홍성읍 대학길 212023-09-27
23Y동원인력백명기개인영업중<NA>충청남도 홍성군 장곡면 홍남동로 4932023-09-27
34Y백호인력박진복개인영업중<NA>충청남도 홍성군 홍성읍 충절로1053번길 512023-09-27
45Y매일조경인력최장석개인영업중041-641-6699충청남도 홍성군 광천읍 광천로273번길 782023-09-27
56Y우리인력양승규개인영업중<NA>충청남도 홍성군 홍성읍 의사로72번길 30-112023-09-27
67Y명품인력안계만개인영업중<NA>충청남도 홍성군 광천읍 광천로359번길 17. 102호2023-09-27
78N홍성농어업회의소김선태법인영업중041-632-0339충청남도 홍성군 홍성읍 내포로 230. 홍성군 농업기술센터. 생활과학관 2층2023-09-27
89Y프로헤드헌터김정민개인영업중041-634-9388충청남도 홍성군 홍북읍 충남대로 140. 좋은사람들 빌딩 2층 209호2023-09-27
910Y조용한직업소개소조용한개인영업중<NA>충청남도 홍성군 광천읍 홍남로 627. 2층 2호2023-09-27
순번유무료구분법인명법인대표자명법인개인구분운영상태사업소 전화번호사업소주소데이터기준일자
4142Y홍성직업소개소신순영개인영업중041-631-0622충청남도 홍성군 홍성읍 문화로 162-12023-09-27
4243Y효자인력전양수개인영업중041-631-4848충청남도 홍성군 홍성읍 의사로49번길 17-72023-09-27
4344Y가나인력서준모개인영업중041 633 4544충청남도 홍성군 홍성읍 충서로 12432023-09-27
4445Y내포인력이재호개인영업중041-634-0405충청남도 홍성군 홍성읍 도청대로 192023-09-27
4546Y홍성인력직업소개소이문호개인영업중041-632-5555충청남도 홍성군 홍성읍 의사로 262023-09-27
4647Y거산인력개발유료직업소개소김진숙개인영업중<NA>충청남도 홍성군 홍성읍 조양로85번길 142023-09-27
4748Y도청인력유료직업소개소정윤석개인영업중041-633-1101충청남도 홍성군 홍성읍 의사로72번길 26. 1층2023-09-27
4849Y광천인력직업소개소한학재개인영업중041-641-1583충청남도 홍성군 광천읍 광천로428번길 162023-09-27
4950Y매일전문인력소개소박태진개인영업중<NA>충청남도 홍성군 홍성읍 충서로1322번길 6-62023-09-27
5051N홍성장애인무료직업소개소복천규법인영업중041-634-0267충청남도 홍성군 홍성읍 조양로33번길 172023-09-27