Overview

Dataset statistics

Number of variables9
Number of observations38
Missing cells27
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory76.5 B

Variable types

Numeric1
Boolean1
Text4
Categorical3

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
순번 is highly overall correlated with 유무료구분 and 1 other fieldsHigh correlation
유무료구분 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
법인개인구분 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
유무료구분 is highly imbalanced (51.5%)Imbalance
법인개인구분 is highly imbalanced (51.5%)Imbalance
사업소전화번호 has 27 (71.1%) missing valuesMissing
순번 has unique valuesUnique
법인명 has unique valuesUnique
법인대표자명 has unique valuesUnique
사업소주소 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:30:03.152664
Analysis finished2024-01-09 20:30:03.772554
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.5
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-10T05:30:03.843063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.85
Q110.25
median19.5
Q328.75
95-th percentile36.15
Maximum38
Range37
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation11.113055
Coefficient of variation (CV)0.56990028
Kurtosis-1.2
Mean19.5
Median Absolute Deviation (MAD)9.5
Skewness0
Sum741
Variance123.5
MonotonicityStrictly increasing
2024-01-10T05:30:03.983145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1 1
 
2.6%
30 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
31 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%
29 1
2.6%

유무료구분
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size170.0 B
True
34 
False
4 
ValueCountFrequency (%)
True 34
89.5%
False 4
 
10.5%
2024-01-10T05:30:04.087161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

법인명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-01-10T05:30:04.267523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length8
Min length2

Characters and Unicode

Total characters304
Distinct characters103
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row매일인력
2nd row미성
3rd row머슴건축인력
4th row월드직업소개소
5th row희망인력
ValueCountFrequency (%)
매일인력 1
 
2.6%
삼성유료직업소개소 1
 
2.6%
충남기독교사회봉사회(홍성사회복지관 1
 
2.6%
충청직업소개소 1
 
2.6%
수림인력개발유료직업소개소 1
 
2.6%
가온해피케어 1
 
2.6%
도청인력유료직업소개소 1
 
2.6%
매일전문인력소개소 1
 
2.6%
홍성직업소개소 1
 
2.6%
내포인력 1
 
2.6%
Other values (29) 29
74.4%
2024-01-10T05:30:04.620693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 44
 
14.5%
개 24
 
7.9%
인 23
 
7.6%
력 21
 
6.9%
업 20
 
6.6%
직 19
 
6.2%
성 9
 
3.0%
홍 7
 
2.3%
사 5
 
1.6%
료 5
 
1.6%
Other values (93) 127
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
98.0%
Uppercase Letter 2
 
0.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Space Separator 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 44
 
14.8%
개 24
 
8.1%
인 23
 
7.7%
력 21
 
7.0%
업 20
 
6.7%
직 19
 
6.4%
성 9
 
3.0%
홍 7
 
2.3%
사 5
 
1.7%
료 5
 
1.7%
Other values (87) 121
40.6%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
98.0%
Common 4
 
1.3%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 44
 
14.8%
개 24
 
8.1%
인 23
 
7.7%
력 21
 
7.0%
업 20
 
6.7%
직 19
 
6.4%
성 9
 
3.0%
홍 7
 
2.3%
사 5
 
1.7%
료 5
 
1.7%
Other values (87) 121
40.6%
Common
ValueCountFrequency (%)
( 1
25.0%
) 1
25.0%
1
25.0%
. 1
25.0%
Latin
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
98.0%
ASCII 6
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 44
 
14.8%
개 24
 
8.1%
인 23
 
7.7%
력 21
 
7.0%
업 20
 
6.7%
직 19
 
6.4%
성 9
 
3.0%
홍 7
 
2.3%
사 5
 
1.7%
료 5
 
1.7%
Other values (87) 121
40.6%
ASCII
ValueCountFrequency (%)
( 1
16.7%
) 1
16.7%
H 1
16.7%
1
16.7%
S 1
16.7%
. 1
16.7%

법인대표자명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-01-10T05:30:04.834220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters114
Distinct characters66
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

Unique38 ?
Unique (%)100.0%

Sample

1st row조권행
2nd row김동선
3rd row한명수
4th row허상범
5th row방철신
ValueCountFrequency (%)
조권행 1
 
2.6%
박규철 1
 
2.6%
김정순 1
 
2.6%
이광연 1
 
2.6%
최황락 1
 
2.6%
이영희 1
 
2.6%
정윤석 1
 
2.6%
박태진 1
 
2.6%
신순영 1
 
2.6%
이재호 1
 
2.6%
Other values (28) 28
73.7%
2024-01-10T05:30:05.159042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
6.1%
이 5
 
4.4%
희 5
 
4.4%
한 4
 
3.5%
재 4
 
3.5%
선 4
 
3.5%
최 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
윤 3
 
2.6%
Other values (56) 73
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
6.1%
이 5
 
4.4%
희 5
 
4.4%
한 4
 
3.5%
재 4
 
3.5%
선 4
 
3.5%
최 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
윤 3
 
2.6%
Other values (56) 73
64.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
6.1%
이 5
 
4.4%
희 5
 
4.4%
한 4
 
3.5%
재 4
 
3.5%
선 4
 
3.5%
최 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
윤 3
 
2.6%
Other values (56) 73
64.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
6.1%
이 5
 
4.4%
희 5
 
4.4%
한 4
 
3.5%
재 4
 
3.5%
선 4
 
3.5%
최 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
윤 3
 
2.6%
Other values (56) 73
64.0%

법인개인구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
개인
34 
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 34
89.5%
법인 4
 
10.5%

Length

2024-01-10T05:30:05.296718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:30:05.408365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 34
89.5%
법인 4
 
10.5%

운영상태
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
영업중
38 

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 38
100.0%

Length

2024-01-10T05:30:05.531880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:30:05.637160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 38
100.0%

사업소전화번호
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing27
Missing (%)71.1%
Memory size436.0 B
2024-01-10T05:30:05.789398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters132
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

Unique11 ?
Unique (%)100.0%

Sample

1st row041-635-1036
2nd row041-633-3785
3rd row041-633-1101
4th row041-633-4814
5th row041-631-0848
ValueCountFrequency (%)
041-635-1036 1
9.1%
041-633-3785 1
9.1%
041-633-1101 1
9.1%
041-633-4814 1
9.1%
041-631-0848 1
9.1%
041-632-5555 1
9.1%
041-641-1583 1
9.1%
041-631-0960 1
9.1%
041-631-5815 1
9.1%
041-632-2008 1
9.1%
2024-01-10T05:30:06.041820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
16.7%
- 22
16.7%
0 19
14.4%
4 16
12.1%
3 16
12.1%
6 14
10.6%
5 9
6.8%
8 7
 
5.3%
2 4
 
3.0%
7 2
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 110
83.3%
Dash Punctuation 22
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
20.0%
0 19
17.3%
4 16
14.5%
3 16
14.5%
6 14
12.7%
5 9
8.2%
8 7
 
6.4%
2 4
 
3.6%
7 2
 
1.8%
9 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 132
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
16.7%
- 22
16.7%
0 19
14.4%
4 16
12.1%
3 16
12.1%
6 14
10.6%
5 9
6.8%
8 7
 
5.3%
2 4
 
3.0%
7 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
16.7%
- 22
16.7%
0 19
14.4%
4 16
12.1%
3 16
12.1%
6 14
10.6%
5 9
6.8%
8 7
 
5.3%
2 4
 
3.0%
7 2
 
1.5%

사업소주소
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-01-10T05:30:06.247572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24.5
Mean length22.368421
Min length19

Characters and Unicode

Total characters850
Distinct characters47
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

Unique38 ?
Unique (%)100.0%

Sample

1st row충청남도 홍성군 광천읍 광천로273번길 78
2nd row충청남도 홍성군 홍북읍 도청대로 234
3rd row충청남도 홍성군 홍성읍 내포로146번길 41
4th row충청남도 홍성군 홍성읍 아문길29번길 66-10
5th row충청남도 홍성군 홍성읍 의사로36번길 8
ValueCountFrequency (%)
충청남도 38
20.0%
홍성군 38
20.0%
홍성읍 29
15.3%
광천읍 5
 
2.6%
충서로 3
 
1.6%
의사로 3
 
1.6%
14 2
 
1.1%
의사로36번길 2
 
1.1%
도청대로 2
 
1.1%
문화로 2
 
1.1%
Other values (62) 66
34.7%
2024-01-10T05:30:06.581206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
17.9%
홍 70
 
8.2%
성 69
 
8.1%
충 45
 
5.3%
남 40
 
4.7%
도 40
 
4.7%
청 40
 
4.7%
군 38
 
4.5%
읍 35
 
4.1%
로 34
 
4.0%
Other values (37) 287
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 539
63.4%
Space Separator 152
 
17.9%
Decimal Number 152
 
17.9%
Dash Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 70
13.0%
성 69
12.8%
충 45
8.3%
남 40
 
7.4%
도 40
 
7.4%
청 40
 
7.4%
군 38
 
7.1%
읍 35
 
6.5%
로 34
 
6.3%
길 24
 
4.5%
Other values (25) 104
19.3%
Decimal Number
ValueCountFrequency (%)
1 34
22.4%
3 20
13.2%
6 19
12.5%
2 18
11.8%
0 13
 
8.6%
4 13
 
8.6%
7 9
 
5.9%
8 9
 
5.9%
9 9
 
5.9%
5 8
 
5.3%
Space Separator
ValueCountFrequency (%)
152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 539
63.4%
Common 311
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 70
13.0%
성 69
12.8%
충 45
8.3%
남 40
 
7.4%
도 40
 
7.4%
청 40
 
7.4%
군 38
 
7.1%
읍 35
 
6.5%
로 34
 
6.3%
길 24
 
4.5%
Other values (25) 104
19.3%
Common
ValueCountFrequency (%)
152
48.9%
1 34
 
10.9%
3 20
 
6.4%
6 19
 
6.1%
2 18
 
5.8%
0 13
 
4.2%
4 13
 
4.2%
7 9
 
2.9%
8 9
 
2.9%
9 9
 
2.9%
Other values (2) 15
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 539
63.4%
ASCII 311
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
48.9%
1 34
 
10.9%
3 20
 
6.4%
6 19
 
6.1%
2 18
 
5.8%
0 13
 
4.2%
4 13
 
4.2%
7 9
 
2.9%
8 9
 
2.9%
9 9
 
2.9%
Other values (2) 15
 
4.8%
Hangul
ValueCountFrequency (%)
홍 70
13.0%
성 69
12.8%
충 45
8.3%
남 40
 
7.4%
도 40
 
7.4%
청 40
 
7.4%
군 38
 
7.1%
읍 35
 
6.5%
로 34
 
6.3%
길 24
 
4.5%
Other values (25) 104
19.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
2021-08-31
38 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-31
2nd row2021-08-31
3rd row2021-08-31
4th row2021-08-31
5th row2021-08-31

Common Values

ValueCountFrequency (%)
2021-08-31 38
100.0%

Length

2024-01-10T05:30:06.696827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:30:06.782924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-31 38
100.0%

Interactions

2024-01-10T05:30:03.484759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:30:06.843301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분법인명법인대표자명법인개인구분사업소전화번호사업소주소
순번1.0001.0001.0001.0001.0001.0001.000
유무료구분1.0001.0001.0001.0000.9751.0001.000
법인명1.0001.0001.0001.0001.0001.0001.000
법인대표자명1.0001.0001.0001.0001.0001.0001.000
법인개인구분1.0000.9751.0001.0001.0001.0001.000
사업소전화번호1.0001.0001.0001.0001.0001.0001.000
사업소주소1.0001.0001.0001.0001.0001.0001.000
2024-01-10T05:30:06.957080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인개인구분유무료구분
법인개인구분1.0000.856
유무료구분0.8561.000
2024-01-10T05:30:07.049984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분법인개인구분
순번1.0000.8820.882
유무료구분0.8821.0000.856
법인개인구분0.8820.8561.000

Missing values

2024-01-10T05:30:03.592792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:30:03.715282image/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

순번유무료구분법인명법인대표자명법인개인구분운영상태사업소전화번호사업소주소데이터기준일자
01Y매일인력조권행개인영업중<NA>충청남도 홍성군 광천읍 광천로273번길 782021-08-31
12Y미성김동선개인영업중<NA>충청남도 홍성군 홍북읍 도청대로 2342021-08-31
23Y머슴건축인력한명수개인영업중<NA>충청남도 홍성군 홍성읍 내포로146번길 412021-08-31
34Y월드직업소개소허상범개인영업중<NA>충청남도 홍성군 홍성읍 아문길29번길 66-102021-08-31
45Y희망인력방철신개인영업중<NA>충청남도 홍성군 홍성읍 의사로36번길 82021-08-31
56Y서부농촌직업소개소김성남개인영업중<NA>충청남도 홍성군 서부면 이호길 402021-08-31
67Y소원안전인력김병우개인영업중<NA>충청남도 홍성군 광천읍 충서로 3192021-08-31
78Y일손인력취업알선공사최진환개인영업중<NA>충청남도 홍성군 홍성읍 충절로1053번길 232021-08-31
89Y더존인력이한재개인영업중<NA>충청남도 홍성군 광천읍 홍남로 6982021-08-31
910Y백두산인력직업소개소조찬호개인영업중<NA>충청남도 홍성군 광천읍 광천로329번길 202021-08-31
순번유무료구분법인명법인대표자명법인개인구분운영상태사업소전화번호사업소주소데이터기준일자
2829Y주선건축인력직업소개소주승교개인영업중041-631-0848충청남도 홍성군 홍성읍 충절로 10362021-08-31
2930Y내포인력이재호개인영업중<NA>충청남도 홍성군 홍성읍 도청대로 192021-08-31
3031Y거산인력개발유료직업소개소김진숙개인영업중<NA>충청남도 홍성군 홍성읍 조양로85번길 142021-08-31
3132Y가나인력서준모개인영업중<NA>충청남도 홍성군 홍성읍 충서로 12432021-08-31
3233Y홍성인력직업소개소인기삼개인영업중041-632-5555충청남도 홍성군 홍성읍 의사로 262021-08-31
3334Y광천인력직업소개소한학재개인영업중041-641-1583충청남도 홍성군 광천읍 광천로428번길 162021-08-31
3435N홍성군노인종합복지관한재선법인영업중041-631-0960충청남도 홍성군 홍성읍 내포로146번길 30-112021-08-31
3536N충남홍성지역자활센터윤명희법인영업중041-631-5815충청남도 홍성군 홍성읍 의사로72번길 41-82021-08-31
3637N충남기독교사회봉사회(홍성사회복지관)김정순법인영업중041-632-2008충청남도 홍성군 홍성읍 조양로75번길 172021-08-31
3738N홍성장애인무료직업소개소복천규법인영업중041-634-0267충청남도 홍성군 금마면 장성리 2302021-08-31