Overview

Dataset statistics

Number of variables6
Number of observations204
Missing cells110
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory48.6 B

Variable types

Text5
Categorical1

Alerts

권리주체소재지(도로명) has 38 (18.6%) missing valuesMissing
사업장소재지(도로명) has 72 (35.3%) missing valuesMissing

Reproduction

Analysis started2024-01-09 20:36:38.182134
Analysis finished2024-01-09 20:36:38.808998
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct192
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T05:36:38.981171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.5980392
Min length3

Characters and Unicode

Total characters938
Distinct characters184
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

Unique182 ?
Unique (%)89.2%

Sample

1st row김영상 농장
2nd row삼화농장
3rd row부자농장
4th row대흥농장
5th row김동식농장
ValueCountFrequency (%)
농장 18
 
8.0%
수훈농장 3
 
1.3%
대흥농장 3
 
1.3%
부자농장 2
 
0.9%
백암농장 2
 
0.9%
강희석농장 2
 
0.9%
유림농장 2
 
0.9%
영진농장 2
 
0.9%
우리농장 2
 
0.9%
k&c 2
 
0.9%
Other values (184) 186
83.0%
2024-01-10T05:36:39.388889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
195
20.8%
188
20.0%
20
 
2.1%
20
 
2.1%
17
 
1.8%
15
 
1.6%
14
 
1.5%
13
 
1.4%
11
 
1.2%
11
 
1.2%
Other values (174) 434
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
95.5%
Space Separator 20
 
2.1%
Decimal Number 12
 
1.3%
Lowercase Letter 4
 
0.4%
Other Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
195
21.8%
188
21.0%
20
 
2.2%
17
 
1.9%
15
 
1.7%
14
 
1.6%
13
 
1.5%
11
 
1.2%
11
 
1.2%
9
 
1.0%
Other values (163) 403
45.0%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 5
41.7%
3 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
k 2
50.0%
c 2
50.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
95.5%
Common 36
 
3.8%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
195
21.8%
188
21.0%
20
 
2.2%
17
 
1.9%
15
 
1.7%
14
 
1.6%
13
 
1.5%
11
 
1.2%
11
 
1.2%
9
 
1.0%
Other values (163) 403
45.0%
Common
ValueCountFrequency (%)
20
55.6%
1 6
 
16.7%
2 5
 
13.9%
& 2
 
5.6%
) 1
 
2.8%
( 1
 
2.8%
3 1
 
2.8%
Latin
ValueCountFrequency (%)
k 2
33.3%
c 2
33.3%
F 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
95.5%
ASCII 42
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
195
21.8%
188
21.0%
20
 
2.2%
17
 
1.9%
15
 
1.7%
14
 
1.6%
13
 
1.5%
11
 
1.2%
11
 
1.2%
9
 
1.0%
Other values (163) 403
45.0%
ASCII
ValueCountFrequency (%)
20
47.6%
1 6
 
14.3%
2 5
 
11.9%
k 2
 
4.8%
& 2
 
4.8%
c 2
 
4.8%
F 1
 
2.4%
B 1
 
2.4%
) 1
 
2.4%
( 1
 
2.4%

주사육업종
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
육계
171 
종계업
33 

Length

Max length3
Median length2
Mean length2.1617647
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
육계 171
83.8%
종계업 33
 
16.2%

Length

2024-01-10T05:36:39.525378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:36:39.857939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
육계 171
83.8%
종계업 33
 
16.2%
Distinct181
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T05:36:40.114916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length27.323529
Min length4

Characters and Unicode

Total characters5574
Distinct characters151
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)79.9%

Sample

1st row경기도 수원시 장안구 송죽동 135번지 3호 17통 1반 우림빌라 102호
2nd row충청남도 당진시 석문면 삼봉리 19번지
3rd row충청남도 당진시 석문면 통정리 1016번지
4th row충청남도 당진시 신평면 부수리 239번지
5th row충청남도 당진시 신평면 부수리 174번지
ValueCountFrequency (%)
충청남도 180
 
14.6%
당진시 175
 
14.2%
1통 43
 
3.5%
2통 32
 
2.6%
신평면 23
 
1.9%
고대면 23
 
1.9%
합덕읍 22
 
1.8%
1호 21
 
1.7%
정미면 19
 
1.5%
19
 
1.5%
Other values (372) 675
54.8%
2024-01-10T05:36:40.524933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1422
25.5%
210
 
3.8%
1 204
 
3.7%
201
 
3.6%
200
 
3.6%
195
 
3.5%
184
 
3.3%
182
 
3.3%
181
 
3.2%
181
 
3.2%
Other values (141) 2414
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3275
58.8%
Space Separator 1422
25.5%
Decimal Number 877
 
15.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
210
 
6.4%
201
 
6.1%
200
 
6.1%
195
 
6.0%
184
 
5.6%
182
 
5.6%
181
 
5.5%
181
 
5.5%
181
 
5.5%
164
 
5.0%
Other values (130) 1396
42.6%
Decimal Number
ValueCountFrequency (%)
1 204
23.3%
2 143
16.3%
3 85
9.7%
4 80
 
9.1%
0 74
 
8.4%
6 65
 
7.4%
5 62
 
7.1%
7 61
 
7.0%
9 58
 
6.6%
8 45
 
5.1%
Space Separator
ValueCountFrequency (%)
1422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3275
58.8%
Common 2299
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
210
 
6.4%
201
 
6.1%
200
 
6.1%
195
 
6.0%
184
 
5.6%
182
 
5.6%
181
 
5.5%
181
 
5.5%
181
 
5.5%
164
 
5.0%
Other values (130) 1396
42.6%
Common
ValueCountFrequency (%)
1422
61.9%
1 204
 
8.9%
2 143
 
6.2%
3 85
 
3.7%
4 80
 
3.5%
0 74
 
3.2%
6 65
 
2.8%
5 62
 
2.7%
7 61
 
2.7%
9 58
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3275
58.8%
ASCII 2299
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1422
61.9%
1 204
 
8.9%
2 143
 
6.2%
3 85
 
3.7%
4 80
 
3.5%
0 74
 
3.2%
6 65
 
2.8%
5 62
 
2.7%
7 61
 
2.7%
9 58
 
2.5%
Hangul
ValueCountFrequency (%)
210
 
6.4%
201
 
6.1%
200
 
6.1%
195
 
6.0%
184
 
5.6%
182
 
5.6%
181
 
5.5%
181
 
5.5%
181
 
5.5%
164
 
5.0%
Other values (130) 1396
42.6%
Distinct145
Distinct (%)87.3%
Missing38
Missing (%)18.6%
Memory size1.7 KiB
2024-01-10T05:36:40.757351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length47
Mean length24.993976
Min length18

Characters and Unicode

Total characters4149
Distinct characters202
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)77.7%

Sample

1st row경기도 수원시 장안구 만석로 237-1, 102호 (송죽동,우림빌라)
2nd row충청남도 당진시 석문면 마섬길 74-65
3rd row충청남도 당진시 신평면 독우물길 112-1
4th row경기도 용인시 수지구 만현로67번길 9, 204동 603호(상현동, 만현마을2단지아이파크)
5th row충청남도 당진시 당진읍 사기소길 100-65
ValueCountFrequency (%)
충청남도 149
 
17.0%
당진시 139
 
15.8%
고대면 20
 
2.3%
정미면 18
 
2.1%
신평면 16
 
1.8%
합덕읍 15
 
1.7%
경기도 14
 
1.6%
면천면 13
 
1.5%
당진읍 11
 
1.3%
대호지면 11
 
1.3%
Other values (338) 472
53.8%
2024-01-10T05:36:41.127193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
712
 
17.2%
170
 
4.1%
1 167
 
4.0%
164
 
4.0%
157
 
3.8%
156
 
3.8%
154
 
3.7%
152
 
3.7%
150
 
3.6%
127
 
3.1%
Other values (192) 2040
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2451
59.1%
Decimal Number 774
 
18.7%
Space Separator 712
 
17.2%
Dash Punctuation 107
 
2.6%
Other Punctuation 37
 
0.9%
Close Punctuation 32
 
0.8%
Open Punctuation 32
 
0.8%
Uppercase Letter 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
170
 
6.9%
164
 
6.7%
157
 
6.4%
156
 
6.4%
154
 
6.3%
152
 
6.2%
150
 
6.1%
127
 
5.2%
94
 
3.8%
84
 
3.4%
Other values (173) 1043
42.6%
Decimal Number
ValueCountFrequency (%)
1 167
21.6%
2 105
13.6%
0 88
11.4%
3 87
11.2%
4 67
8.7%
6 66
 
8.5%
8 50
 
6.5%
7 49
 
6.3%
5 49
 
6.3%
9 46
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 35
94.6%
. 2
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2451
59.1%
Common 1694
40.8%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
170
 
6.9%
164
 
6.7%
157
 
6.4%
156
 
6.4%
154
 
6.3%
152
 
6.2%
150
 
6.1%
127
 
5.2%
94
 
3.8%
84
 
3.4%
Other values (173) 1043
42.6%
Common
ValueCountFrequency (%)
712
42.0%
1 167
 
9.9%
- 107
 
6.3%
2 105
 
6.2%
0 88
 
5.2%
3 87
 
5.1%
4 67
 
4.0%
6 66
 
3.9%
8 50
 
3.0%
7 49
 
2.9%
Other values (6) 196
 
11.6%
Latin
ValueCountFrequency (%)
B 2
50.0%
e 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2451
59.1%
ASCII 1698
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
712
41.9%
1 167
 
9.8%
- 107
 
6.3%
2 105
 
6.2%
0 88
 
5.2%
3 87
 
5.1%
4 67
 
3.9%
6 66
 
3.9%
8 50
 
2.9%
7 49
 
2.9%
Other values (9) 200
 
11.8%
Hangul
ValueCountFrequency (%)
170
 
6.9%
164
 
6.7%
157
 
6.4%
156
 
6.4%
154
 
6.3%
152
 
6.2%
150
 
6.1%
127
 
5.2%
94
 
3.8%
84
 
3.4%
Other values (173) 1043
42.6%
Distinct181
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T05:36:41.460390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length25.995098
Min length4

Characters and Unicode

Total characters5303
Distinct characters107
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)80.4%

Sample

1st row충청남도 당진시 고대면 슬항리 807번지
2nd row충청남도 당진시 석문면 삼봉리 19번지
3rd row충청남도 당진시 석문면 통정리 1016번지
4th row충청남도 당진시 신평면 부수리 239번지
5th row충청남도 당진시 신평면 부수리 174번지
ValueCountFrequency (%)
충청남도 200
 
17.1%
당진시 200
 
17.1%
1호 34
 
2.9%
고대면 29
 
2.5%
2호 27
 
2.3%
신평면 26
 
2.2%
26
 
2.2%
합덕읍 26
 
2.2%
정미면 19
 
1.6%
면천면 17
 
1.5%
Other values (274) 566
48.4%
2024-01-10T05:36:41.949666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1366
25.8%
228
 
4.3%
210
 
4.0%
207
 
3.9%
206
 
3.9%
204
 
3.8%
201
 
3.8%
200
 
3.8%
200
 
3.8%
197
 
3.7%
Other values (97) 2084
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3184
60.0%
Space Separator 1366
25.8%
Decimal Number 738
 
13.9%
Dash Punctuation 9
 
0.2%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
228
 
7.2%
210
 
6.6%
207
 
6.5%
206
 
6.5%
204
 
6.4%
201
 
6.3%
200
 
6.3%
200
 
6.3%
197
 
6.2%
188
 
5.9%
Other values (84) 1143
35.9%
Decimal Number
ValueCountFrequency (%)
1 149
20.2%
2 112
15.2%
3 88
11.9%
6 62
8.4%
4 62
8.4%
0 58
 
7.9%
5 57
 
7.7%
9 56
 
7.6%
8 52
 
7.0%
7 42
 
5.7%
Space Separator
ValueCountFrequency (%)
1366
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3184
60.0%
Common 2119
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
228
 
7.2%
210
 
6.6%
207
 
6.5%
206
 
6.5%
204
 
6.4%
201
 
6.3%
200
 
6.3%
200
 
6.3%
197
 
6.2%
188
 
5.9%
Other values (84) 1143
35.9%
Common
ValueCountFrequency (%)
1366
64.5%
1 149
 
7.0%
2 112
 
5.3%
3 88
 
4.2%
6 62
 
2.9%
4 62
 
2.9%
0 58
 
2.7%
5 57
 
2.7%
9 56
 
2.6%
8 52
 
2.5%
Other values (3) 57
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3184
60.0%
ASCII 2119
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1366
64.5%
1 149
 
7.0%
2 112
 
5.3%
3 88
 
4.2%
6 62
 
2.9%
4 62
 
2.9%
0 58
 
2.7%
5 57
 
2.7%
9 56
 
2.6%
8 52
 
2.5%
Other values (3) 57
 
2.7%
Hangul
ValueCountFrequency (%)
228
 
7.2%
210
 
6.6%
207
 
6.5%
206
 
6.5%
204
 
6.4%
201
 
6.3%
200
 
6.3%
200
 
6.3%
197
 
6.2%
188
 
5.9%
Other values (84) 1143
35.9%
Distinct119
Distinct (%)90.2%
Missing72
Missing (%)35.3%
Memory size1.7 KiB
2024-01-10T05:36:42.307670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length22.537879
Min length18

Characters and Unicode

Total characters2975
Distinct characters144
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

Unique108 ?
Unique (%)81.8%

Sample

1st row충청남도 당진시 고대면 보덕포로 320-30
2nd row충청남도 당진시 석문면 마섬길 74-65
3rd row충청남도 당진시 신평면 독우물길 112-1
4th row충청남도 당진시 송악읍 본당로 16
5th row충청남도 당진시 사기소길 100-65 (사기소동)
ValueCountFrequency (%)
충청남도 132
19.8%
당진시 132
19.8%
합덕읍 18
 
2.7%
신평면 15
 
2.2%
면천면 13
 
1.9%
고대면 12
 
1.8%
정미면 12
 
1.8%
순성면 10
 
1.5%
송악읍 10
 
1.5%
석문면 9
 
1.3%
Other values (209) 304
45.6%
2024-01-10T05:36:42.779247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
18.0%
138
 
4.6%
138
 
4.6%
137
 
4.6%
133
 
4.5%
132
 
4.4%
132
 
4.4%
132
 
4.4%
110
 
3.7%
1 94
 
3.2%
Other values (134) 1294
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1816
61.0%
Space Separator 535
 
18.0%
Decimal Number 507
 
17.0%
Dash Punctuation 88
 
3.0%
Close Punctuation 14
 
0.5%
Open Punctuation 14
 
0.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
138
 
7.6%
138
 
7.6%
137
 
7.5%
133
 
7.3%
132
 
7.3%
132
 
7.3%
132
 
7.3%
110
 
6.1%
68
 
3.7%
66
 
3.6%
Other values (119) 630
34.7%
Decimal Number
ValueCountFrequency (%)
1 94
18.5%
2 75
14.8%
3 57
11.2%
9 49
9.7%
6 44
8.7%
4 44
8.7%
7 39
7.7%
5 36
 
7.1%
8 35
 
6.9%
0 34
 
6.7%
Space Separator
ValueCountFrequency (%)
535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1816
61.0%
Common 1159
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
138
 
7.6%
138
 
7.6%
137
 
7.5%
133
 
7.3%
132
 
7.3%
132
 
7.3%
132
 
7.3%
110
 
6.1%
68
 
3.7%
66
 
3.6%
Other values (119) 630
34.7%
Common
ValueCountFrequency (%)
535
46.2%
1 94
 
8.1%
- 88
 
7.6%
2 75
 
6.5%
3 57
 
4.9%
9 49
 
4.2%
6 44
 
3.8%
4 44
 
3.8%
7 39
 
3.4%
5 36
 
3.1%
Other values (5) 98
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1816
61.0%
ASCII 1159
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
46.2%
1 94
 
8.1%
- 88
 
7.6%
2 75
 
6.5%
3 57
 
4.9%
9 49
 
4.2%
6 44
 
3.8%
4 44
 
3.8%
7 39
 
3.4%
5 36
 
3.1%
Other values (5) 98
 
8.5%
Hangul
ValueCountFrequency (%)
138
 
7.6%
138
 
7.6%
137
 
7.5%
133
 
7.3%
132
 
7.3%
132
 
7.3%
132
 
7.3%
110
 
6.1%
68
 
3.7%
66
 
3.6%
Other values (119) 630
34.7%

Missing values

2024-01-10T05:36:38.557078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:36:38.656859image/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.
2024-01-10T05:36:38.759834image/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

사업장명칭주사육업종권리주체소재지(지번)권리주체소재지(도로명)사업장소재지(지번)사업장소재지(도로명)
0김영상 농장육계경기도 수원시 장안구 송죽동 135번지 3호 17통 1반 우림빌라 102호경기도 수원시 장안구 만석로 237-1, 102호 (송죽동,우림빌라)충청남도 당진시 고대면 슬항리 807번지충청남도 당진시 고대면 보덕포로 320-30
1삼화농장육계충청남도 당진시 석문면 삼봉리 19번지충청남도 당진시 석문면 마섬길 74-65충청남도 당진시 석문면 삼봉리 19번지충청남도 당진시 석문면 마섬길 74-65
2부자농장육계충청남도 당진시 석문면 통정리 1016번지<NA>충청남도 당진시 석문면 통정리 1016번지<NA>
3대흥농장육계충청남도 당진시 신평면 부수리 239번지<NA>충청남도 당진시 신평면 부수리 239번지<NA>
4김동식농장육계충청남도 당진시 신평면 부수리 174번지충청남도 당진시 신평면 독우물길 112-1충청남도 당진시 신평면 부수리 174번지충청남도 당진시 신평면 독우물길 112-1
5최동호농장육계충청남도 당진시 신평면 한정리 377번지<NA>충청남도 당진시 신평면 한정리 377번지<NA>
6이경식농장육계충청남도 당진시 송악읍 반촌리 20번지 6호 2통경기도 용인시 수지구 만현로67번길 9, 204동 603호(상현동, 만현마을2단지아이파크)충청남도 당진시 송악읍 반촌리 20번지 6호충청남도 당진시 송악읍 본당로 16
7이병일농장육계충청남도 당진시 사기소동 398번지 2통충청남도 당진시 당진읍 사기소길 100-65충청남도 당진시 사기소동 398번지충청남도 당진시 사기소길 100-65 (사기소동)
8이을호농장육계충청남도 당진시 신평면 부수리 344번지 7호<NA>충청남도 당진시 신평면 부수리 340번지 1호충청남도 당진시 신평면 고역길 84
9이병세농장육계충청남도 당진시 신평면 신흥리 284번지 1통충청남도 당진시 신평면 지무골길 15충청남도 당진시 신평면 신흥리 284번지<NA>
사업장명칭주사육업종권리주체소재지(지번)권리주체소재지(도로명)사업장소재지(지번)사업장소재지(도로명)
194상민농장종계업충청남도 당진시 정미면 대운산리 산 23번지 1호충청남도 당진시 정미면 구울미길 55-6충청남도 당진시 고대면 당진포리 2050번지<NA>
195대흥농장종계업경기도 용인시 처인구 마평동 957번지 1통 15반 푸른마을 용인자이아파트 105동 1002호경기도 용인시 처인구 금학로 520,105동 1002호 (마평동,푸른마을 용인자이아파트)충청남도 당진시 신평면 부수리 239번지<NA>
196이경흔종계업충청남도 당진시 대호지면 송전리 16번지충청남도 당진시 대호지면 문헌로 98충청남도 당진시 대호지면 송전리 산 16번지충청남도 당진시 대호지면 문헌로 98
197우리농장종계업충청남도 당진시 정미면 승산리 263번지충청남도 당진시 정미면 수시미길 64-229충청남도 당진시 정미면 승산리 307번지 3호충청남도 당진시 정미면 수시미길 64-229 (양계장)
198한얼축산종계업충청남도 당진시 대호지면 송전리 산 16번지충청남도 당진시 대호지면 문헌로 98충청남도 당진시 대호지면 송전리 산 16번지충청남도 당진시 대호지면 문헌로 98
199수훈농장종계업충청남도 당진시 송악읍 반촌리 420번지 6호 1통 명지아파트 104동 411호충청남도 당진시 신평면 섭실길 114-20, 101동 202호(봉학마을아파트)충청남도 당진시 우강면 세류리 120번지 13호충청남도 당진시 우강면 세류골길 112-15
200수훈농장종계업충청남도 당진시 신평면 거산리 430번지 1호 1통 봉학마을아파트 101동 202호충청남도 당진시 신평면 섭실길 114-20, 101동 202호(봉학마을아파트)충청남도 당진시 송산면 유곡리 1번지 146호<NA>
201효동농장종계업충청남도 당진시 송악읍 기지시리 146번지충청남도 당진시 면천면 갈밭2길 89-18충청남도 당진시 송악읍 기지시리 78번지 9호충청남도 당진시 송악읍 틀모시로 760-20
202대흥농장종계업충청남도 당진시 신평면 부수리 239번지<NA>충청남도 당진시 신평면 부수리 239번지<NA>
203합덕농장종계업경기도 수원시 권선구 입북동 810번지 14통 8반 서수원자이아파트 108동 1001호경기도 수원시 권선구 입북로 50,108동 1001호 (입북동,서수원자이아파트)충청남도 당진시 합덕읍 석우리 48번지 8호<NA>