Overview

Dataset statistics

Number of variables6
Number of observations176
Missing cells18
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory49.8 B

Variable types

Text4
Numeric1
Categorical1

Dataset

Description충청남도 부여군에 위치한 기업체 현황을 제공합니다.(업체명, 도로명주소, 생산품, 종업원수, 전화번호, 데이터기준일자)
Author충청남도 부여군
URLhttps://www.data.go.kr/data/15053309/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
생산품 has 2 (1.1%) missing valuesMissing
전화번호 has 16 (9.1%) missing valuesMissing
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:59:39.581358
Analysis finished2023-12-12 19:59:40.668546
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T04:59:40.837097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.9943182
Min length3

Characters and Unicode

Total characters1407
Distinct characters229
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)100.0%

Sample

1st row(유)동선이엔씨
2nd row(유)중부산업개발
3rd row(주) 건영에스피지
4th row(주)경희산업
5th row(주)계림전설
ValueCountFrequency (%)
주식회사 29
 
13.0%
농업회사법인 8
 
3.6%
영농조합법인 2
 
0.9%
부여지점 2
 
0.9%
유)동선이엔씨 1
 
0.4%
아주이엔지주식회사 1
 
0.4%
정이미터 1
 
0.4%
에스티에스특장(주 1
 
0.4%
솔거종합식품 1
 
0.4%
수지산업 1
 
0.4%
Other values (176) 176
78.9%
2023-12-13T04:59:41.284102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 114
 
8.1%
( 82
 
5.8%
) 82
 
5.8%
사 49
 
3.5%
47
 
3.3%
회 46
 
3.3%
업 42
 
3.0%
이 41
 
2.9%
식 40
 
2.8%
산 31
 
2.2%
Other values (219) 833
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1185
84.2%
Open Punctuation 82
 
5.8%
Close Punctuation 82
 
5.8%
Space Separator 47
 
3.3%
Uppercase Letter 8
 
0.6%
Other Punctuation 2
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 114
 
9.6%
사 49
 
4.1%
회 46
 
3.9%
업 42
 
3.5%
이 41
 
3.5%
식 40
 
3.4%
산 31
 
2.6%
농 25
 
2.1%
스 23
 
1.9%
인 20
 
1.7%
Other values (206) 754
63.6%
Uppercase Letter
ValueCountFrequency (%)
F 1
12.5%
N 1
12.5%
B 1
12.5%
R 1
12.5%
M 1
12.5%
P 1
12.5%
T 1
12.5%
L 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1186
84.3%
Common 213
 
15.1%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 114
 
9.6%
사 49
 
4.1%
회 46
 
3.9%
업 42
 
3.5%
이 41
 
3.5%
식 40
 
3.4%
산 31
 
2.6%
농 25
 
2.1%
스 23
 
1.9%
인 20
 
1.7%
Other values (207) 755
63.7%
Latin
ValueCountFrequency (%)
F 1
12.5%
N 1
12.5%
B 1
12.5%
R 1
12.5%
M 1
12.5%
P 1
12.5%
T 1
12.5%
L 1
12.5%
Common
ValueCountFrequency (%)
( 82
38.5%
) 82
38.5%
47
22.1%
. 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1185
84.2%
ASCII 221
 
15.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 114
 
9.6%
사 49
 
4.1%
회 46
 
3.9%
업 42
 
3.5%
이 41
 
3.5%
식 40
 
3.4%
산 31
 
2.6%
농 25
 
2.1%
스 23
 
1.9%
인 20
 
1.7%
Other values (206) 754
63.6%
ASCII
ValueCountFrequency (%)
( 82
37.1%
) 82
37.1%
47
21.3%
. 2
 
0.9%
F 1
 
0.5%
N 1
 
0.5%
B 1
 
0.5%
R 1
 
0.5%
M 1
 
0.5%
P 1
 
0.5%
Other values (2) 2
 
0.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

Distinct166
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T04:59:41.528658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length24.102273
Min length18

Characters and Unicode

Total characters4242
Distinct characters120
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

Unique159 ?
Unique (%)90.3%

Sample

1st row충청남도 부여군 장암면 위덕로445번길 40
2nd row충청남도 부여군 석성면 금백로 166-11
3rd row충청남도 부여군 규암면 내동로 11
4th row충청남도 부여군 석성면 증산로 95
5th row충청남도 부여군 은산면 충의로622번길 23
ValueCountFrequency (%)
충청남도 176
 
17.7%
부여군 176
 
17.7%
외 39
 
3.9%
은산면 32
 
3.2%
석성면 30
 
3.0%
장암면 18
 
1.8%
규암면 18
 
1.8%
초촌면 15
 
1.5%
임천면 15
 
1.5%
홍산면 14
 
1.4%
Other values (254) 463
46.5%
2023-12-13T04:59:41.953172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
820
19.3%
충 218
 
5.1%
부 192
 
4.5%
남 186
 
4.4%
여 184
 
4.3%
도 179
 
4.2%
군 177
 
4.2%
청 177
 
4.2%
면 168
 
4.0%
로 153
 
3.6%
Other values (110) 1788
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2601
61.3%
Space Separator 820
 
19.3%
Decimal Number 729
 
17.2%
Dash Punctuation 59
 
1.4%
Close Punctuation 13
 
0.3%
Open Punctuation 13
 
0.3%
Other Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 218
 
8.4%
부 192
 
7.4%
남 186
 
7.2%
여 184
 
7.1%
도 179
 
6.9%
군 177
 
6.8%
청 177
 
6.8%
면 168
 
6.5%
로 153
 
5.9%
지 72
 
2.8%
Other values (95) 895
34.4%
Decimal Number
ValueCountFrequency (%)
1 133
18.2%
2 129
17.7%
4 79
10.8%
3 79
10.8%
6 66
9.1%
5 65
8.9%
0 57
7.8%
7 49
 
6.7%
9 41
 
5.6%
8 31
 
4.3%
Space Separator
ValueCountFrequency (%)
820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2601
61.3%
Common 1641
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 218
 
8.4%
부 192
 
7.4%
남 186
 
7.2%
여 184
 
7.1%
도 179
 
6.9%
군 177
 
6.8%
청 177
 
6.8%
면 168
 
6.5%
로 153
 
5.9%
지 72
 
2.8%
Other values (95) 895
34.4%
Common
ValueCountFrequency (%)
820
50.0%
1 133
 
8.1%
2 129
 
7.9%
4 79
 
4.8%
3 79
 
4.8%
6 66
 
4.0%
5 65
 
4.0%
- 59
 
3.6%
0 57
 
3.5%
7 49
 
3.0%
Other values (5) 105
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2601
61.3%
ASCII 1641
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
820
50.0%
1 133
 
8.1%
2 129
 
7.9%
4 79
 
4.8%
3 79
 
4.8%
6 66
 
4.0%
5 65
 
4.0%
- 59
 
3.6%
0 57
 
3.5%
7 49
 
3.0%
Other values (5) 105
 
6.4%
Hangul
ValueCountFrequency (%)
충 218
 
8.4%
부 192
 
7.4%
남 186
 
7.2%
여 184
 
7.1%
도 179
 
6.9%
군 177
 
6.8%
청 177
 
6.8%
면 168
 
6.5%
로 153
 
5.9%
지 72
 
2.8%
Other values (95) 895
34.4%

생산품
Text

MISSING 

Distinct155
Distinct (%)89.1%
Missing2
Missing (%)1.1%
Memory size1.5 KiB
2023-12-13T04:59:42.254051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length31
Mean length10.488506
Min length1

Characters and Unicode

Total characters1825
Distinct characters325
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)84.5%

Sample

1st row산업기계, 슬러지퇴비화 장치
2nd row아스콘
3rd row하이샷시
4th row복공판
5th row수배전반
ValueCountFrequency (%)
백미 10
 
2.7%
및 10
 
2.7%
등 7
 
1.9%
레미콘 6
 
1.6%
아스콘 3
 
0.8%
외 3
 
0.8%
콘크리트 3
 
0.8%
배터리 2
 
0.5%
유량계 2
 
0.5%
배전반 2
 
0.5%
Other values (306) 322
87.0%
2023-12-13T04:59:42.723679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
196
 
10.7%
, 124
 
6.8%
조 35
 
1.9%
수 31
 
1.7%
품 30
 
1.6%
미 29
 
1.6%
용 28
 
1.5%
리 28
 
1.5%
제 26
 
1.4%
장 24
 
1.3%
Other values (315) 1274
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1393
76.3%
Space Separator 196
 
10.7%
Other Punctuation 127
 
7.0%
Uppercase Letter 80
 
4.4%
Open Punctuation 12
 
0.7%
Close Punctuation 12
 
0.7%
Dash Punctuation 4
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 35
 
2.5%
수 31
 
2.2%
품 30
 
2.2%
미 29
 
2.1%
용 28
 
2.0%
리 28
 
2.0%
제 26
 
1.9%
장 24
 
1.7%
스 23
 
1.7%
재 22
 
1.6%
Other values (287) 1117
80.2%
Uppercase Letter
ValueCountFrequency (%)
E 17
21.2%
L 10
12.5%
P 9
11.2%
D 8
10.0%
C 7
8.8%
T 5
 
6.2%
A 3
 
3.8%
S 3
 
3.8%
V 3
 
3.8%
B 2
 
2.5%
Other values (10) 13
16.2%
Other Punctuation
ValueCountFrequency (%)
, 124
97.6%
. 2
 
1.6%
· 1
 
0.8%
Space Separator
ValueCountFrequency (%)
196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1393
76.3%
Common 352
 
19.3%
Latin 80
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 35
 
2.5%
수 31
 
2.2%
품 30
 
2.2%
미 29
 
2.1%
용 28
 
2.0%
리 28
 
2.0%
제 26
 
1.9%
장 24
 
1.7%
스 23
 
1.7%
재 22
 
1.6%
Other values (287) 1117
80.2%
Latin
ValueCountFrequency (%)
E 17
21.2%
L 10
12.5%
P 9
11.2%
D 8
10.0%
C 7
8.8%
T 5
 
6.2%
A 3
 
3.8%
S 3
 
3.8%
V 3
 
3.8%
B 2
 
2.5%
Other values (10) 13
16.2%
Common
ValueCountFrequency (%)
196
55.7%
, 124
35.2%
( 12
 
3.4%
) 12
 
3.4%
- 4
 
1.1%
. 2
 
0.6%
· 1
 
0.3%
2 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1393
76.3%
ASCII 431
 
23.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
196
45.5%
, 124
28.8%
E 17
 
3.9%
( 12
 
2.8%
) 12
 
2.8%
L 10
 
2.3%
P 9
 
2.1%
D 8
 
1.9%
C 7
 
1.6%
T 5
 
1.2%
Other values (17) 31
 
7.2%
Hangul
ValueCountFrequency (%)
조 35
 
2.5%
수 31
 
2.2%
품 30
 
2.2%
미 29
 
2.1%
용 28
 
2.0%
리 28
 
2.0%
제 26
 
1.9%
장 24
 
1.7%
스 23
 
1.7%
재 22
 
1.6%
Other values (287) 1117
80.2%
None
ValueCountFrequency (%)
· 1
100.0%

종업원수
Real number (ℝ)

Distinct43
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.039773
Minimum0
Maximum442
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T04:59:42.893041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median9
Q318
95-th percentile61
Maximum442
Range442
Interquartile range (IQR)13

Descriptive statistics

Standard deviation44.45998
Coefficient of variation (CV)2.3351109
Kurtosis57.06116
Mean19.039773
Median Absolute Deviation (MAD)5
Skewness6.9753301
Sum3351
Variance1976.6898
MonotonicityNot monotonic
2023-12-13T04:59:43.037219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
5 19
 
10.8%
4 14
 
8.0%
9 13
 
7.4%
6 11
 
6.2%
1 9
 
5.1%
20 8
 
4.5%
8 8
 
4.5%
3 7
 
4.0%
2 7
 
4.0%
15 7
 
4.0%
Other values (33) 73
41.5%
ValueCountFrequency (%)
0 1
 
0.6%
1 9
5.1%
2 7
 
4.0%
3 7
 
4.0%
4 14
8.0%
5 19
10.8%
6 11
6.2%
7 6
 
3.4%
8 8
4.5%
9 13
7.4%
ValueCountFrequency (%)
442 1
0.6%
307 1
0.6%
160 1
0.6%
155 1
0.6%
100 1
0.6%
90 1
0.6%
77 1
0.6%
72 1
0.6%
70 1
0.6%
58 1
0.6%

전화번호
Text

MISSING 

Distinct156
Distinct (%)97.5%
Missing16
Missing (%)9.1%
Memory size1.5 KiB
2023-12-13T04:59:43.331262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.01875
Min length12

Characters and Unicode

Total characters1923
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)95.0%

Sample

1st row041-832-2888
2nd row041-835-9888
3rd row041-835-0030
4th row041-835-9985
5th row041-833-3865
ValueCountFrequency (%)
041-832-1571 2
 
1.2%
041-832-2888 2
 
1.2%
041-837-0151 2
 
1.2%
041-834-0294 2
 
1.2%
041-836-2564 1
 
0.6%
041-834-6556 1
 
0.6%
041-836-9973 1
 
0.6%
041-833-9655 1
 
0.6%
041-741-8305 1
 
0.6%
02-3152-9000 1
 
0.6%
Other values (146) 146
91.2%
2023-12-13T04:59:43.803136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 320
16.6%
0 281
14.6%
4 226
11.8%
3 225
11.7%
8 220
11.4%
1 215
11.2%
2 106
 
5.5%
7 94
 
4.9%
5 90
 
4.7%
6 90
 
4.7%
Other values (4) 56
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
83.2%
Dash Punctuation 320
 
16.6%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 281
17.6%
4 226
14.1%
3 225
14.1%
8 220
13.8%
1 215
13.4%
2 106
 
6.6%
7 94
 
5.9%
5 90
 
5.6%
6 90
 
5.6%
9 53
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
R 1
33.3%
S 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1920
99.8%
Latin 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
- 320
16.7%
0 281
14.6%
4 226
11.8%
3 225
11.7%
8 220
11.5%
1 215
11.2%
2 106
 
5.5%
7 94
 
4.9%
5 90
 
4.7%
6 90
 
4.7%
Latin
ValueCountFrequency (%)
A 1
33.3%
R 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 320
16.6%
0 281
14.6%
4 226
11.8%
3 225
11.7%
8 220
11.4%
1 215
11.2%
2 106
 
5.5%
7 94
 
4.9%
5 90
 
4.7%
6 90
 
4.7%
Other values (4) 56
 
2.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-10-31
176 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-31
2nd row2023-10-31
3rd row2023-10-31
4th row2023-10-31
5th row2023-10-31

Common Values

ValueCountFrequency (%)
2023-10-31 176
100.0%

Length

2023-12-13T04:59:43.960203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:44.062325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-31 176
100.0%

Interactions

2023-12-13T04:59:40.305087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T04:59:40.417582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:59:40.521844image/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.
2023-12-13T04:59:40.620313image/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

업체명도로명주소생산품종업원수전화번호데이터기준일자
0(유)동선이엔씨충청남도 부여군 장암면 위덕로445번길 40산업기계, 슬러지퇴비화 장치4041-832-28882023-10-31
1(유)중부산업개발충청남도 부여군 석성면 금백로 166-11아스콘5041-835-98882023-10-31
2(주) 건영에스피지충청남도 부여군 규암면 내동로 11하이샷시5041-835-00302023-10-31
3(주)경희산업충청남도 부여군 석성면 증산로 95복공판20041-835-99852023-10-31
4(주)계림전설충청남도 부여군 은산면 충의로622번길 23수배전반5<NA>2023-10-31
5(주)계림폴리콘충청남도 부여군 임천면 가림로 618 외 5필지폴리머콘크리트제품, 합성수지제측구수로관, 밸브실18041-833-38652023-10-31
6(주)광일산업충청남도 부여군 구룡면 흥수로 397-5포장용 판지상자13<NA>2023-10-31
7(주)그린켐텍충청남도 부여군 석성면 석성로 224-7 외 1필지PE타포린9041-837-07802023-10-31
8(주)네오캠충청남도 부여군 석성면 증산천길 140 외 2필지방수천막12041-837-37112023-10-31
9(주)뉴제일이엘이씨충청남도 부여군 은산면 은남로20번길 42금속제품단조,압형,열처리,도금 가공업11070-5222-72472023-10-31
업체명도로명주소생산품종업원수전화번호데이터기준일자
166한국조폐공사 제지본부충청남도 부여군 부여읍 염창로180번길 67 외 4필지은행권용지,특수용지,전자카드307041-830-52032023-10-31
167한신이엔에스충청남도 부여군 장암면 위덕로445번길 40상하수도 파이프20041-832-28882023-10-31
168현대레미콘 주식회사충청남도 부여군 석성면 금백로 166-13 외 2필지레미콘8041-835-85552023-10-31
169현일섬유충청남도 부여군 규암면 충절로 2266메리야스35041-835-60272023-10-31
170홍산농업협동조합충청남도 부여군 홍산면 대백제로 822백미4041-835-12802023-10-31
171후레시팜충청남도 부여군 은산면 충의로 602-21면류,육수류,조미료류9041-832-94792023-10-31
172휴먼스화공(주)충청남도 부여군 초촌면 신암로 244폭죽, 간이소화기구 등19041-832-77012023-10-31
173유성기와충청남도 부여군 구룡면 성충로 1410시멘트 한식 기와2041-833-49942023-10-31
174옥산석재충청남도 부여군 옥산면 신안로 136석재류 가공1041-832-04792023-10-31
175㈜외가집 농업회사법인충청남도 부여군 옥산면 안골로41번길 21-12장류5041-834-47062023-10-31