Overview

Dataset statistics

Number of variables11
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory93.7 B

Variable types

Numeric1
Categorical7
Text3

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
시군명 is highly overall correlated with 대기분야 and 1 other fieldsHigh correlation
대기분야 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
수질분야 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
순번 is highly overall correlated with 대기분야 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
업소명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:48:30.707114
Analysis finished2024-03-14 02:48:31.400379
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-03-14T11:48:31.452434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2024-03-14T11:48:31.561892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

시군명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
전주시
22 
익산시
5 
군산시
5 
임실군
 
1
고창군
 
1
Other values (2)
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)11.1%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row익산시
5th row전주시

Common Values

ValueCountFrequency (%)
전주시 22
61.1%
익산시 5
 
13.9%
군산시 5
 
13.9%
임실군 1
 
2.8%
고창군 1
 
2.8%
남원시 1
 
2.8%
완주군 1
 
2.8%

Length

2024-03-14T11:48:31.662493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:31.751063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 22
61.1%
익산시 5
 
13.9%
군산시 5
 
13.9%
임실군 1
 
2.8%
고창군 1
 
2.8%
남원시 1
 
2.8%
완주군 1
 
2.8%

업소명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T11:48:31.933486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length7.3888889
Min length3

Characters and Unicode

Total characters266
Distinct characters87
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row광진환경㈜
2nd row㈜유성테크
3rd row(유)지구엔비텍
4th row(유)호일엔지니어링
5th row(주)이앤에스테크
ValueCountFrequency (%)
광진환경㈜ 1
 
2.7%
유)은하환경산업 1
 
2.7%
유)대금환경 1
 
2.7%
유)부광건설 1
 
2.7%
유)푸른이엔텍 1
 
2.7%
유)일토씨엔엠 1
 
2.7%
유)미래건설 1
 
2.7%
주)파인리포먼스 1
 
2.7%
유)대신환경개발 1
 
2.7%
주)대한 1
 
2.7%
Other values (27) 27
73.0%
2024-03-14T11:48:32.235830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 24
 
9.0%
) 24
 
9.0%
유 19
 
7.1%
㈜ 11
 
4.1%
엔 10
 
3.8%
설 8
 
3.0%
건 8
 
3.0%
이 8
 
3.0%
환 7
 
2.6%
경 7
 
2.6%
Other values (77) 140
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
77.4%
Open Punctuation 24
 
9.0%
Close Punctuation 24
 
9.0%
Other Symbol 11
 
4.1%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 19
 
9.2%
엔 10
 
4.9%
설 8
 
3.9%
건 8
 
3.9%
이 8
 
3.9%
환 7
 
3.4%
경 7
 
3.4%
주 7
 
3.4%
크 6
 
2.9%
지 6
 
2.9%
Other values (73) 120
58.3%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 217
81.6%
Common 49
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 19
 
8.8%
㈜ 11
 
5.1%
엔 10
 
4.6%
설 8
 
3.7%
건 8
 
3.7%
이 8
 
3.7%
환 7
 
3.2%
경 7
 
3.2%
주 7
 
3.2%
크 6
 
2.8%
Other values (74) 126
58.1%
Common
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
77.4%
ASCII 49
 
18.4%
None 11
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
1
 
2.0%
Hangul
ValueCountFrequency (%)
유 19
 
9.2%
엔 10
 
4.9%
설 8
 
3.9%
건 8
 
3.9%
이 8
 
3.9%
환 7
 
3.4%
경 7
 
3.4%
주 7
 
3.4%
크 6
 
2.9%
지 6
 
2.9%
Other values (73) 120
58.3%
None
ValueCountFrequency (%)
㈜ 11
100.0%

도로명주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T11:48:32.472748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24.5
Mean length20.083333
Min length11

Characters and Unicode

Total characters723
Distinct characters114
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 호반3길 7 (덕진동2가)
2nd row전주시 완산구 송정중앙로 29 (효자동1가)
3rd row전주시 덕진구 비석날로 99 (팔복동2가)
4th row익산시 춘포면 궁성로 272
5th row전주시 완산구 서곡6길 23-4 (효자동3가)
ValueCountFrequency (%)
전주시 22
 
14.0%
덕진구 14
 
8.9%
완산구 8
 
5.1%
군산시 5
 
3.2%
익산시 5
 
3.2%
우아동3가 4
 
2.5%
인후동1가 2
 
1.3%
11 2
 
1.3%
원만성로 2
 
1.3%
효자동1가 2
 
1.3%
Other values (90) 91
58.0%
2024-03-14T11:48:32.797491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
16.7%
시 33
 
4.6%
동 29
 
4.0%
( 27
 
3.7%
) 27
 
3.7%
1 25
 
3.5%
전 24
 
3.3%
주 23
 
3.2%
로 22
 
3.0%
구 22
 
3.0%
Other values (104) 370
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 416
57.5%
Decimal Number 122
 
16.9%
Space Separator 121
 
16.7%
Open Punctuation 27
 
3.7%
Close Punctuation 27
 
3.7%
Dash Punctuation 10
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 33
 
7.9%
동 29
 
7.0%
전 24
 
5.8%
주 23
 
5.5%
로 22
 
5.3%
구 22
 
5.3%
산 22
 
5.3%
길 17
 
4.1%
진 17
 
4.1%
덕 16
 
3.8%
Other values (90) 191
45.9%
Decimal Number
ValueCountFrequency (%)
1 25
20.5%
2 20
16.4%
3 18
14.8%
7 14
11.5%
8 10
 
8.2%
4 9
 
7.4%
0 8
 
6.6%
5 8
 
6.6%
9 6
 
4.9%
6 4
 
3.3%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
57.5%
Common 307
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 33
 
7.9%
동 29
 
7.0%
전 24
 
5.8%
주 23
 
5.5%
로 22
 
5.3%
구 22
 
5.3%
산 22
 
5.3%
길 17
 
4.1%
진 17
 
4.1%
덕 16
 
3.8%
Other values (90) 191
45.9%
Common
ValueCountFrequency (%)
121
39.4%
( 27
 
8.8%
) 27
 
8.8%
1 25
 
8.1%
2 20
 
6.5%
3 18
 
5.9%
7 14
 
4.6%
8 10
 
3.3%
- 10
 
3.3%
4 9
 
2.9%
Other values (4) 26
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
57.5%
ASCII 307
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
39.4%
( 27
 
8.8%
) 27
 
8.8%
1 25
 
8.1%
2 20
 
6.5%
3 18
 
5.9%
7 14
 
4.6%
8 10
 
3.3%
- 10
 
3.3%
4 9
 
2.9%
Other values (4) 26
 
8.5%
Hangul
ValueCountFrequency (%)
시 33
 
7.9%
동 29
 
7.0%
전 24
 
5.8%
주 23
 
5.5%
로 22
 
5.3%
구 22
 
5.3%
산 22
 
5.3%
길 17
 
4.1%
진 17
 
4.1%
덕 16
 
3.8%
Other values (90) 191
45.9%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T11:48:32.975081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length12.388889
Min length12

Characters and Unicode

Total characters446
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row063-254-8150
2nd row063-222-7968
3rd row063-211-8001
4th row063-832-5271
5th row063-273-5251
ValueCountFrequency (%)
063-254-8150 1
 
2.7%
063-221-2211 1
 
2.7%
063-564-1940 1
 
2.7%
063-245-0984 1
 
2.7%
063-452-1367 1
 
2.7%
063-631-5050 1
 
2.7%
063-236-3777 1
 
2.7%
063-451-0552 1
 
2.7%
063-858-5111 1
 
2.7%
063-225-7407 1
 
2.7%
Other values (27) 27
73.0%
2024-03-14T11:48:33.377747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 74
16.6%
3 66
14.8%
0 62
13.9%
6 56
12.6%
2 50
11.2%
5 32
7.2%
4 30
6.7%
1 29
 
6.5%
8 19
 
4.3%
7 18
 
4.0%
Other values (3) 10
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
83.0%
Dash Punctuation 74
 
16.6%
Other Punctuation 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 66
17.8%
0 62
16.8%
6 56
15.1%
2 50
13.5%
5 32
8.6%
4 30
8.1%
1 29
7.8%
8 19
 
5.1%
7 18
 
4.9%
9 8
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 74
16.6%
3 66
14.8%
0 62
13.9%
6 56
12.6%
2 50
11.2%
5 32
7.2%
4 30
6.7%
1 29
 
6.5%
8 19
 
4.3%
7 18
 
4.0%
Other values (3) 10
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 74
16.6%
3 66
14.8%
0 62
13.9%
6 56
12.6%
2 50
11.2%
5 32
7.2%
4 30
6.7%
1 29
 
6.5%
8 19
 
4.3%
7 18
 
4.0%
Other values (3) 10
 
2.2%

대기분야
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
26 
○
10 

Length

Max length4
Median length4
Mean length3.1666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row○
3rd row○
4th row○
5th row○

Common Values

ValueCountFrequency (%)
<NA> 26
72.2%
○ 10
 
27.8%

Length

2024-03-14T11:48:33.540454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:33.624484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
72.2%
○ 10
 
27.8%

수질분야
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
○
32 
<NA>
4 

Length

Max length4
Median length1
Mean length1.3333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row○
2nd row○
3rd row○
4th row○
5th row○

Common Values

ValueCountFrequency (%)
○ 32
88.9%
<NA> 4
 
11.1%

Length

2024-03-14T11:48:33.710565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:33.792541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
○ 32
88.9%
na 4
 
11.1%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
환경보전과
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경보전과 36
100.0%

Length

2024-03-14T11:48:33.888794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:33.967577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경보전과 36
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
공개
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 36
100.0%

Length

2024-03-14T11:48:34.044480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:34.117300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 36
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2015.1
36 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 36
100.0%

Length

2024-03-14T11:48:34.403855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:34.475556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 36
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
1년
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 36
100.0%

Length

2024-03-14T11:48:34.562770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:34.658430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 36
100.0%

Interactions

2024-03-14T11:48:31.024306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:48:34.706595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업소명도로명주소전화번호
순번1.0000.2551.0001.0001.000
시군명0.2551.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
2024-03-14T11:48:34.784405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명대기분야수질분야
시군명1.0001.0001.000
대기분야1.0001.0001.000
수질분야1.0001.0001.000
2024-03-14T11:48:34.862031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명대기분야수질분야
순번1.0000.0001.0001.000
시군명0.0001.0001.0001.000
대기분야1.0001.0001.0001.000
수질분야1.0001.0001.0001.000

Missing values

2024-03-14T11:48:31.206709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:48:31.353870image/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

순번시군명업소명도로명주소전화번호대기분야수질분야자료출처공개여부작성일갱신주기
01전주시광진환경㈜전주시 덕진구 호반3길 7 (덕진동2가)063-254-8150<NA>○환경보전과공개2015.11년
12전주시㈜유성테크전주시 완산구 송정중앙로 29 (효자동1가)063-222-7968○○환경보전과공개2015.11년
23전주시(유)지구엔비텍전주시 덕진구 비석날로 99 (팔복동2가)063-211-8001○○환경보전과공개2015.11년
34익산시(유)호일엔지니어링익산시 춘포면 궁성로 272063-832-5271○○환경보전과공개2015.11년
45전주시(주)이앤에스테크전주시 완산구 서곡6길 23-4 (효자동3가)063-273-5251○○환경보전과공개2015.11년
56전주시㈜청송이앤티전주시 덕진구 동부대로 727 (우아동3가)063-242-4690○<NA>환경보전과공개2015.11년
67익산시㈜광산테크익산시 석암로13길 71 (팔봉동)063-835-2823○<NA>환경보전과공개2015.11년
78전주시바다정수산업㈜전주시 덕진구 원만성로 5 (만성동)063-211-4331<NA>○환경보전과공개2015.11년
89전주시(유)도영종합건설전주시 완산구 메너머2길 21-10 (중화산동2가)063-229-5025<NA>○환경보전과공개2015.11년
910전주시(유)한백종합건설전주시 덕진구 도당산3길 8-4 (우아동3가)063-242-4130<NA>○환경보전과공개2015.11년
순번시군명업소명도로명주소전화번호대기분야수질분야자료출처공개여부작성일갱신주기
2627전주시(유)대금환경전주시 덕진구 산재마을길 59 (금상동)063-242-7532<NA>○환경보전과공개2015.11년
2728익산시(주)대한익산시 익산대로26길 17-1 (남중동)063-858-5111<NA>○환경보전과공개2015.11년
2829전주시(유)금영이엔텍전주시 완산구 용머리로 73 (효자동1가)063-223-0153<NA>○환경보전과공개2015.11년
2930전주시(유)라인환경기술전주시 덕진구 용덕길 3-30063-288-7001○○환경보전과공개2015.11년
3031군산시(주)이레엔텍군산시 미성로 417063-464-9256<NA>○환경보전과공개2015.11년
3132전주시(주)국성건설엔지니어링전주시 완산구 서신로 57(서신동)063-251-3330<NA>○환경보전과공개2015.11년
3233익산시㈜보원건설산업익산시 황등면 후정4길 58-36063-858-0850<NA>○환경보전과공개2015.11년
3334완주군(유)도일이엔지완주군 삼례읍 용전길 7(하리)063-253-6136<NA>○환경보전과공개2015.11년
3435군산시(유)블루그린링크군산시 가도로 81 (오식도동)063-225-7407, 063-471-7407<NA>○환경보전과공개2015.11년
3536군산시에너원주식회사군산시 외항로 884 (소룡동)063-466-7700○<NA>환경보전과공개2015.11년