Overview

Dataset statistics

Number of variables6
Number of observations44
Missing cells10
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory51.9 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description전북특별자치도 진안군 관내 사업장 폐기물 배출신고자 현황에 대한 데이터입니다. 업체명, 도로명주소, 신고된 폐기물 종류와 전화번호 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15065123/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 10 (22.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:25:38.722815
Analysis finished2024-03-14 17:25:40.123595
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T02:25:40.271348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2024-03-15T02:25:40.510725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

상호
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T02:25:41.319981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length10.045455
Min length5

Characters and Unicode

Total characters442
Distinct characters143
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

Unique42 ?
Unique (%)95.5%

Sample

1st rowOK아스콘(유)
2nd row(주)함소아제약 진안공장
3rd row주식회사 그린파이프
4th row주식회사 팜덕 세븐(SEVEN)지점
5th row(유)대성환경
ValueCountFrequency (%)
진안공장 3
 
4.9%
주식회사 3
 
4.9%
유)o.k 2
 
3.3%
영농조합법인 2
 
3.3%
진안폐차장 1
 
1.6%
농업회사법인 1
 
1.6%
유한회사 1
 
1.6%
이삭 1
 
1.6%
한국수자원공사 1
 
1.6%
유)강성산업개발 1
 
1.6%
Other values (45) 45
73.8%
2024-03-15T02:25:42.616963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 31
 
7.0%
) 31
 
7.0%
주 21
 
4.8%
17
 
3.8%
진 15
 
3.4%
사 11
 
2.5%
안 11
 
2.5%
유 10
 
2.3%
공 10
 
2.3%
장 10
 
2.3%
Other values (133) 275
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
78.5%
Open Punctuation 31
 
7.0%
Close Punctuation 31
 
7.0%
Space Separator 17
 
3.8%
Uppercase Letter 14
 
3.2%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 21
 
6.1%
진 15
 
4.3%
사 11
 
3.2%
안 11
 
3.2%
유 10
 
2.9%
공 10
 
2.9%
장 10
 
2.9%
업 8
 
2.3%
농 7
 
2.0%
인 6
 
1.7%
Other values (120) 238
68.6%
Uppercase Letter
ValueCountFrequency (%)
K 3
21.4%
O 3
21.4%
E 2
14.3%
A 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
N 1
 
7.1%
V 1
 
7.1%
S 1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 347
78.5%
Common 81
 
18.3%
Latin 14
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 21
 
6.1%
진 15
 
4.3%
사 11
 
3.2%
안 11
 
3.2%
유 10
 
2.9%
공 10
 
2.9%
장 10
 
2.9%
업 8
 
2.3%
농 7
 
2.0%
인 6
 
1.7%
Other values (120) 238
68.6%
Latin
ValueCountFrequency (%)
K 3
21.4%
O 3
21.4%
E 2
14.3%
A 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
N 1
 
7.1%
V 1
 
7.1%
S 1
 
7.1%
Common
ValueCountFrequency (%)
( 31
38.3%
) 31
38.3%
17
21.0%
. 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
78.5%
ASCII 95
 
21.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 31
32.6%
) 31
32.6%
17
17.9%
K 3
 
3.2%
O 3
 
3.2%
. 2
 
2.1%
E 2
 
2.1%
A 1
 
1.1%
P 1
 
1.1%
C 1
 
1.1%
Other values (3) 3
 
3.2%
Hangul
ValueCountFrequency (%)
주 21
 
6.1%
진 15
 
4.3%
사 11
 
3.2%
안 11
 
3.2%
유 10
 
2.9%
공 10
 
2.9%
장 10
 
2.9%
업 8
 
2.3%
농 7
 
2.0%
인 6
 
1.7%
Other values (120) 238
68.6%

사업장도로명주소
Text

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T02:25:43.590972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length38
Mean length27.022727
Min length22

Characters and Unicode

Total characters1189
Distinct characters95
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

Unique40 ?
Unique (%)90.9%

Sample

1st row전북특별자치도 진안군 진안읍 반월길 29
2nd row전북특별자치도 진안군 진안읍 홍삼한방로 42
3rd row전북특별자치도 진안군 진안읍 거북바위로3길 15-6
4th row전북특별자치도 진안군 진안읍 거북바위로1길 11
5th row전북특별자치도 진안군 부귀면 전진로 2091
ValueCountFrequency (%)
전북특별자치도 44
19.2%
진안군 44
19.2%
진안읍 28
 
12.2%
부귀면 7
 
3.1%
전진로 7
 
3.1%
홍삼한방로 5
 
2.2%
연장리 4
 
1.7%
반월길 3
 
1.3%
거북바위로3길 3
 
1.3%
마령면 3
 
1.3%
Other values (67) 81
35.4%
2024-03-15T02:25:44.918221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
 
16.2%
진 84
 
7.1%
안 76
 
6.4%
1 53
 
4.5%
전 51
 
4.3%
북 50
 
4.2%
도 46
 
3.9%
군 45
 
3.8%
특 44
 
3.7%
별 44
 
3.7%
Other values (85) 503
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 778
65.4%
Space Separator 193
 
16.2%
Decimal Number 179
 
15.1%
Dash Punctuation 23
 
1.9%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Connector Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 84
 
10.8%
안 76
 
9.8%
전 51
 
6.6%
북 50
 
6.4%
도 46
 
5.9%
군 45
 
5.8%
특 44
 
5.7%
별 44
 
5.7%
자 44
 
5.7%
치 44
 
5.7%
Other values (70) 250
32.1%
Decimal Number
ValueCountFrequency (%)
1 53
29.6%
2 28
15.6%
6 20
 
11.2%
9 18
 
10.1%
3 17
 
9.5%
8 11
 
6.1%
5 10
 
5.6%
7 8
 
4.5%
0 7
 
3.9%
4 7
 
3.9%
Space Separator
ValueCountFrequency (%)
193
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 778
65.4%
Common 411
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 84
 
10.8%
안 76
 
9.8%
전 51
 
6.6%
북 50
 
6.4%
도 46
 
5.9%
군 45
 
5.8%
특 44
 
5.7%
별 44
 
5.7%
자 44
 
5.7%
치 44
 
5.7%
Other values (70) 250
32.1%
Common
ValueCountFrequency (%)
193
47.0%
1 53
 
12.9%
2 28
 
6.8%
- 23
 
5.6%
6 20
 
4.9%
9 18
 
4.4%
3 17
 
4.1%
8 11
 
2.7%
5 10
 
2.4%
7 8
 
1.9%
Other values (5) 30
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 778
65.4%
ASCII 411
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
193
47.0%
1 53
 
12.9%
2 28
 
6.8%
- 23
 
5.6%
6 20
 
4.9%
9 18
 
4.4%
3 17
 
4.1%
8 11
 
2.7%
5 10
 
2.4%
7 8
 
1.9%
Other values (5) 30
 
7.3%
Hangul
ValueCountFrequency (%)
진 84
 
10.8%
안 76
 
9.8%
전 51
 
6.6%
북 50
 
6.4%
도 46
 
5.9%
군 45
 
5.8%
특 44
 
5.7%
별 44
 
5.7%
자 44
 
5.7%
치 44
 
5.7%
Other values (70) 250
32.1%

신고된 폐기물 종류
Text

Distinct36
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T02:25:45.947218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length33
Mean length19.727273
Min length2

Characters and Unicode

Total characters868
Distinct characters96
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)70.5%

Sample

1st row폐아스팔트콘크리트
2nd row그 밖의 폐기물
3rd row폐합성수지류(폐염화비닐수지류는 제외한다)
4th row그 밖의 폐기물, 폐합성수지류, 축산물가공잔재물, 동물성유지류, 폐수처리오니
5th row폐합성수지류(폐염화비닐수지류는 제외한다), 그 밖의 폐기물
ValueCountFrequency (%)
밖의 18
 
12.0%
그 18
 
12.0%
폐합성수지류 15
 
10.0%
폐수처리오니 11
 
7.3%
식물성잔재물 8
 
5.3%
폐기물 7
 
4.7%
제외한다 6
 
4.0%
폐합성수지류(폐염화비닐수지류는 6
 
4.0%
그밖의 3
 
2.0%
공정오니 3
 
2.0%
Other values (45) 55
36.7%
2024-03-15T02:25:47.412201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
12.2%
폐 77
 
8.9%
, 50
 
5.8%
물 45
 
5.2%
수 43
 
5.0%
성 36
 
4.1%
류 36
 
4.1%
지 30
 
3.5%
밖 24
 
2.8%
그 24
 
2.8%
Other values (86) 397
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 696
80.2%
Space Separator 106
 
12.2%
Other Punctuation 50
 
5.8%
Open Punctuation 7
 
0.8%
Close Punctuation 7
 
0.8%
Decimal Number 1
 
0.1%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 77
 
11.1%
물 45
 
6.5%
수 43
 
6.2%
성 36
 
5.2%
류 36
 
5.2%
지 30
 
4.3%
밖 24
 
3.4%
그 24
 
3.4%
의 24
 
3.4%
합 23
 
3.3%
Other values (80) 334
48.0%
Space Separator
ValueCountFrequency (%)
106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 696
80.2%
Common 172
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 77
 
11.1%
물 45
 
6.5%
수 43
 
6.2%
성 36
 
5.2%
류 36
 
5.2%
지 30
 
4.3%
밖 24
 
3.4%
그 24
 
3.4%
의 24
 
3.4%
합 23
 
3.3%
Other values (80) 334
48.0%
Common
ValueCountFrequency (%)
106
61.6%
, 50
29.1%
( 7
 
4.1%
) 7
 
4.1%
1 1
 
0.6%
_ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 695
80.1%
ASCII 172
 
19.8%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
61.6%
, 50
29.1%
( 7
 
4.1%
) 7
 
4.1%
1 1
 
0.6%
_ 1
 
0.6%
Hangul
ValueCountFrequency (%)
폐 77
 
11.1%
물 45
 
6.5%
수 43
 
6.2%
성 36
 
5.2%
류 36
 
5.2%
지 30
 
4.3%
밖 24
 
3.5%
그 24
 
3.5%
의 24
 
3.5%
합 23
 
3.3%
Other values (79) 333
47.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

전화번호
Text

MISSING 

Distinct32
Distinct (%)94.1%
Missing10
Missing (%)22.7%
Memory size480.0 B
2024-03-15T02:25:48.200571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters408
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

Unique30 ?
Unique (%)88.2%

Sample

1st row063-433-5610
2nd row063-433-8310
3rd row063-433-8016
4th row063-433-9177
5th row063-430-7512
ValueCountFrequency (%)
063-432-1150 2
 
5.9%
063-433-5605 2
 
5.9%
063-433-1100 1
 
2.9%
063-251-5201 1
 
2.9%
063-433-3388 1
 
2.9%
063-433-6567 1
 
2.9%
063-430-4272 1
 
2.9%
063-472-6321 1
 
2.9%
063-433-5610 1
 
2.9%
063-432-6350 1
 
2.9%
Other values (22) 22
64.7%
2024-03-15T02:25:49.504413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 99
24.3%
- 68
16.7%
0 58
14.2%
6 47
11.5%
4 35
 
8.6%
1 28
 
6.9%
5 24
 
5.9%
2 20
 
4.9%
7 15
 
3.7%
8 9
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 340
83.3%
Dash Punctuation 68
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 99
29.1%
0 58
17.1%
6 47
13.8%
4 35
 
10.3%
1 28
 
8.2%
5 24
 
7.1%
2 20
 
5.9%
7 15
 
4.4%
8 9
 
2.6%
9 5
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 99
24.3%
- 68
16.7%
0 58
14.2%
6 47
11.5%
4 35
 
8.6%
1 28
 
6.9%
5 24
 
5.9%
2 20
 
4.9%
7 15
 
3.7%
8 9
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 99
24.3%
- 68
16.7%
0 58
14.2%
6 47
11.5%
4 35
 
8.6%
1 28
 
6.9%
5 24
 
5.9%
2 20
 
4.9%
7 15
 
3.7%
8 9
 
2.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
2023-11-30
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 44
100.0%

Length

2024-03-15T02:25:49.912110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:25:50.189602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 44
100.0%

Interactions

2024-03-15T02:25:39.385070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:25:50.520516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호사업장도로명주소신고된 폐기물 종류전화번호
연번1.0000.9330.8630.7640.843
상호0.9331.0001.0000.9871.000
사업장도로명주소0.8631.0001.0000.9550.998
신고된 폐기물 종류0.7640.9870.9551.0000.946
전화번호0.8431.0000.9980.9461.000

Missing values

2024-03-15T02:25:39.709251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:25:40.048572image/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

연번상호사업장도로명주소신고된 폐기물 종류전화번호데이터기준일자
01OK아스콘(유)전북특별자치도 진안군 진안읍 반월길 29폐아스팔트콘크리트063-433-56102023-11-30
12(주)함소아제약 진안공장전북특별자치도 진안군 진안읍 홍삼한방로 42그 밖의 폐기물063-433-83102023-11-30
23주식회사 그린파이프전북특별자치도 진안군 진안읍 거북바위로3길 15-6폐합성수지류(폐염화비닐수지류는 제외한다)063-433-80162023-11-30
34주식회사 팜덕 세븐(SEVEN)지점전북특별자치도 진안군 진안읍 거북바위로1길 11그 밖의 폐기물, 폐합성수지류, 축산물가공잔재물, 동물성유지류, 폐수처리오니<NA>2023-11-30
45(유)대성환경전북특별자치도 진안군 부귀면 전진로 2091폐합성수지류(폐염화비닐수지류는 제외한다), 그 밖의 폐기물063-433-91772023-11-30
56(유)일토씨엔엠(진안공공하수처리장)전북특별자치도 진안군 진안읍 학천변길 99그 밖의 폐기물, 하수처리오니063-430-75122023-11-30
67늘푸른 영농조합법인전북특별자치도 진안군 진안읍 홍삼한방로 21-61 (늘푸름영농조합법인)그 밖의 폐수처리오니<NA>2023-11-30
78두현종합폐차장전북특별자치도 진안군 부귀면 전진로 2611-26폐합성수지류(폐염화비닐수지류는 제외한다), 폐타이어, 자동차회수폐냉매물질<NA>2023-11-30
89전북인삼농협 지엠피전북특별자치도 진안군 진안읍 홍삼한방로 22-22그 밖의 식물성잔재물063-433-21112023-11-30
910무진장축협물류센타전북특별자치도 진안군 진안읍 전진로 2729 (연장리 1615-5_1615-6_1615-7_1615-8)폐합성수지류063-433-81102023-11-30
연번상호사업장도로명주소신고된 폐기물 종류전화번호데이터기준일자
3435(주)에너라인전북특별자치도 진안군 진안읍 연장리 1066-18기타<NA>2023-11-30
3536(주)백년산업전북특별자치도 진안군 동향면 동계로 328폐석재<NA>2023-11-30
3637(주)이엔코리아전북특별자치도 진안군 진안읍 연장리 1066-10소각재, 폐합성수지류<NA>2023-11-30
3738(주)건보전북특별자치도 진안군 진안읍 거북바위로1길 19-6그 밖의 공정오니, 그 밖의 폐수처리오니, 그 밖의 공정오니063-433-01332023-11-30
3839(주)반석레미콘아스콘지점전북특별자치도 진안군 용담면 안용로 1196폐아스팔트콘크리트063-433-77702023-11-30
3940(유)신영전북특별자치도 진안군 마령면 관진로 1451폐합성수지류, 폐가구류, 그밖의폐목재류063-433-92932023-11-30
4041(주)반석레미콘전북특별자치도 진안군 용담면 안용로 1196 (반석레미콘)그 밖의 무기성오니, 폐콘크리트063-433-86602023-11-30
4142한국농협김치조합공동사업법인 전북지사전북특별자치도 진안군 부귀면 가정길 6 (외 1필지)그 밖의 폐수처리오니, 그 밖의 식물성잔재물063-433-53562023-11-30
4243진안군청(분뇨 및 가축분뇨공공처리시설)전북특별자치도 진안군 진안읍 전진로 3183-99분뇨처리오니, 그 밖의 폐기물, 가축분뇨처리오니, 분뇨처리오니, 그밖의무기성오니, 폐활성탄063-430-25552023-11-30
4344(유)O.K전북특별자치도 진안군 진안읍 반월길 39폐유, 폐유기용제, 폐수처리오니, 생활폐기물063-433-56052023-11-30