Overview

Dataset statistics

Number of variables9
Number of observations164
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory11.8 KiB
Average record size in memory73.8 B

Variable types

Categorical7
Text2

Dataset

Description대전광역시 유성구에 있는 대기 및 수질에 대한 환경오염물칠 배출업소에 대한 데이터로 업체명, 소재지, 업종, 종별, 신고허가, 폐수처리방식, 폐수처리공법, 배출허용기준 지역구분에 대한 데이터를 제공합니다.폐수처리방식, 폐수처리공법, 배출허용기준 지역구분에 대한 데이터는 수질 오염물질 배출업소에만 해당되는 데이터입니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15107128/fileData.do

Alerts

Dataset has 1 (0.6%) duplicate rowsDuplicates
폐수처리방식 is highly overall correlated with 업종 and 2 other fieldsHigh correlation
폐수처리공법 is highly overall correlated with 업종 and 4 other fieldsHigh correlation
구분 is highly overall correlated with 업종 and 1 other fieldsHigh correlation
종별 is highly overall correlated with 업종 and 3 other fieldsHigh correlation
업종 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
신고허가 is highly overall correlated with 업종 and 3 other fieldsHigh correlation
배출허용기준 지역구분 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
업종 is highly imbalanced (54.8%)Imbalance
종별 is highly imbalanced (65.0%)Imbalance
신고허가 is highly imbalanced (86.8%)Imbalance

Reproduction

Analysis started2023-12-12 15:43:36.748613
Analysis finished2023-12-12 15:43:38.091338
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
수질
123 
대기
39 
대기+수질
 
2

Length

Max length5
Median length2
Mean length2.0365854
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수질 123
75.0%
대기 39
 
23.8%
대기+수질 2
 
1.2%

Length

2023-12-13T00:43:38.159679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:38.263333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수질 123
75.0%
대기 39
 
23.8%
대기+수질 2
 
1.2%

업체명
Text

Distinct159
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T00:43:38.481955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length7.6890244
Min length2

Characters and Unicode

Total characters1261
Distinct characters258
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)93.9%

Sample

1st row한국지엠서대전서비스센타㈜
2nd row신대광
3rd row케이에스모터스
4th row유성현대서비스
5th row오토월드자동차공업사
ValueCountFrequency (%)
현대오일뱅크 4
 
1.9%
직영 3
 
1.4%
롯데쇼핑 3
 
1.4%
롯데마트 3
 
1.4%
서대전점 3
 
1.4%
정다운 2
 
0.9%
농업회사법인 2
 
0.9%
홈플러스 2
 
0.9%
대전 2
 
0.9%
셀세모 2
 
0.9%
Other values (185) 188
87.9%
2023-12-13T00:43:38.926670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
4.0%
유 44
 
3.5%
대 42
 
3.3%
스 40
 
3.2%
차 37
 
2.9%
세 35
 
2.8%
소 34
 
2.7%
전 31
 
2.5%
장 27
 
2.1%
성 26
 
2.1%
Other values (248) 895
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1146
90.9%
Space Separator 50
 
4.0%
Uppercase Letter 27
 
2.1%
Lowercase Letter 15
 
1.2%
Decimal Number 7
 
0.6%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Other Symbol 2
 
0.2%
Other Punctuation 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 44
 
3.8%
대 42
 
3.7%
스 40
 
3.5%
차 37
 
3.2%
세 35
 
3.1%
소 34
 
3.0%
전 31
 
2.7%
장 27
 
2.4%
성 26
 
2.3%
주 25
 
2.2%
Other values (217) 805
70.2%
Uppercase Letter
ValueCountFrequency (%)
G 4
14.8%
S 4
14.8%
I 3
11.1%
C 3
11.1%
P 3
11.1%
L 3
11.1%
K 2
7.4%
T 2
7.4%
D 1
 
3.7%
J 1
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
l 2
13.3%
i 2
13.3%
n 1
 
6.7%
a 1
 
6.7%
g 1
 
6.7%
t 1
 
6.7%
h 1
 
6.7%
f 1
 
6.7%
s 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
1 2
28.6%
4 1
 
14.3%
5 1
 
14.3%
Space Separator
ValueCountFrequency (%)
50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1148
91.0%
Common 70
 
5.6%
Latin 43
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 44
 
3.8%
대 42
 
3.7%
스 40
 
3.5%
차 37
 
3.2%
세 35
 
3.0%
소 34
 
3.0%
전 31
 
2.7%
장 27
 
2.4%
성 26
 
2.3%
주 25
 
2.2%
Other values (218) 807
70.3%
Latin
ValueCountFrequency (%)
G 4
 
9.3%
S 4
 
9.3%
e 4
 
9.3%
I 3
 
7.0%
C 3
 
7.0%
P 3
 
7.0%
L 3
 
7.0%
K 2
 
4.7%
T 2
 
4.7%
l 2
 
4.7%
Other values (12) 13
30.2%
Common
ValueCountFrequency (%)
50
71.4%
) 6
 
8.6%
( 6
 
8.6%
2 3
 
4.3%
1 2
 
2.9%
/ 1
 
1.4%
4 1
 
1.4%
5 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1146
90.9%
ASCII 112
 
8.9%
None 2
 
0.2%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
44.6%
) 6
 
5.4%
( 6
 
5.4%
G 4
 
3.6%
S 4
 
3.6%
e 4
 
3.6%
I 3
 
2.7%
2 3
 
2.7%
C 3
 
2.7%
P 3
 
2.7%
Other values (19) 26
23.2%
Hangul
ValueCountFrequency (%)
유 44
 
3.8%
대 42
 
3.7%
스 40
 
3.5%
차 37
 
3.2%
세 35
 
3.1%
소 34
 
3.0%
전 31
 
2.7%
장 27
 
2.4%
성 26
 
2.3%
주 25
 
2.2%
Other values (217) 805
70.2%
None
ValueCountFrequency (%)
㈜ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지
Text

Distinct161
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T00:43:39.245854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length30
Mean length23.304878
Min length15

Characters and Unicode

Total characters3822
Distinct characters100
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

Unique158 ?
Unique (%)96.3%

Sample

1st row대전광역시 유성구 계백로 809
2nd row대전광역시 유성구 진잠로 67
3rd row대전광역시 유성구 대학로76번길 99
4th row대전광역시 유성구 한밭대로 398
5th row대전광역시 유성구 유성대로 488 (복용동)
ValueCountFrequency (%)
대전광역시 164
21.4%
유성구 163
21.2%
유성대로 19
 
2.5%
원내동 17
 
2.2%
계백로 11
 
1.4%
현충원로 10
 
1.3%
구암동 10
 
1.3%
장대동 10
 
1.3%
488 8
 
1.0%
북유성대로 8
 
1.0%
Other values (233) 348
45.3%
2023-12-13T00:43:39.718406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
604
 
15.8%
대 247
 
6.5%
성 201
 
5.3%
유 199
 
5.2%
구 176
 
4.6%
전 164
 
4.3%
광 164
 
4.3%
역 164
 
4.3%
시 164
 
4.3%
로 157
 
4.1%
Other values (90) 1582
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2356
61.6%
Space Separator 604
 
15.8%
Decimal Number 595
 
15.6%
Open Punctuation 111
 
2.9%
Close Punctuation 111
 
2.9%
Dash Punctuation 27
 
0.7%
Other Punctuation 10
 
0.3%
Uppercase Letter 6
 
0.2%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 247
10.5%
성 201
 
8.5%
유 199
 
8.4%
구 176
 
7.5%
전 164
 
7.0%
광 164
 
7.0%
역 164
 
7.0%
시 164
 
7.0%
로 157
 
6.7%
동 135
 
5.7%
Other values (73) 585
24.8%
Decimal Number
ValueCountFrequency (%)
1 111
18.7%
2 68
11.4%
8 63
10.6%
3 60
10.1%
6 56
9.4%
9 54
9.1%
5 51
8.6%
7 49
8.2%
4 48
8.1%
0 35
 
5.9%
Space Separator
ValueCountFrequency (%)
604
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2356
61.6%
Common 1460
38.2%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 247
10.5%
성 201
 
8.5%
유 199
 
8.4%
구 176
 
7.5%
전 164
 
7.0%
광 164
 
7.0%
역 164
 
7.0%
시 164
 
7.0%
로 157
 
6.7%
동 135
 
5.7%
Other values (73) 585
24.8%
Common
ValueCountFrequency (%)
604
41.4%
1 111
 
7.6%
( 111
 
7.6%
) 111
 
7.6%
2 68
 
4.7%
8 63
 
4.3%
3 60
 
4.1%
6 56
 
3.8%
9 54
 
3.7%
5 51
 
3.5%
Other values (6) 171
 
11.7%
Latin
ValueCountFrequency (%)
B 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2356
61.6%
ASCII 1466
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
604
41.2%
1 111
 
7.6%
( 111
 
7.6%
) 111
 
7.6%
2 68
 
4.6%
8 63
 
4.3%
3 60
 
4.1%
6 56
 
3.8%
9 54
 
3.7%
5 51
 
3.5%
Other values (7) 177
 
12.1%
Hangul
ValueCountFrequency (%)
대 247
10.5%
성 201
 
8.5%
유 199
 
8.4%
구 176
 
7.5%
전 164
 
7.0%
광 164
 
7.0%
역 164
 
7.0%
시 164
 
7.0%
로 157
 
6.7%
동 135
 
5.7%
Other values (73) 585
24.8%

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct31
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
세차
113 
자동차종합수리업
12 
자동차정비업
 
5
대형종합할인매장
 
4
음식 및 숙박업
 
2
Other values (26)
28 

Length

Max length15
Median length2
Mean length3.5487805
Min length2

Unique

Unique24 ?
Unique (%)14.6%

Sample

1st row운수시설및장비수선
2nd row자동차정비업
3rd row자동차정비업
4th row자동차정비업
5th row자동차정비업

Common Values

ValueCountFrequency (%)
세차 113
68.9%
자동차종합수리업 12
 
7.3%
자동차정비업 5
 
3.0%
대형종합할인매장 4
 
2.4%
음식 및 숙박업 2
 
1.2%
서비스업 2
 
1.2%
이화학실험시설 2
 
1.2%
교육서비스 1
 
0.6%
숙박업 1
 
0.6%
호텔업 1
 
0.6%
Other values (21) 21
 
12.8%

Length

2023-12-13T00:43:39.878280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
세차 113
63.8%
자동차종합수리업 12
 
6.8%
자동차정비업 5
 
2.8%
및 5
 
2.8%
대형종합할인매장 4
 
2.3%
숙박업 3
 
1.7%
음식 2
 
1.1%
서비스업 2
 
1.1%
이화학실험시설 2
 
1.1%
세탁 1
 
0.6%
Other values (28) 28
 
15.8%

종별
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
5
146 
4
16 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 146
89.0%
4 16
 
9.8%
3 2
 
1.2%

Length

2023-12-13T00:43:40.006114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:40.107476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 146
89.0%
4 16
 
9.8%
3 2
 
1.2%

신고허가
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
신고
161 
허가
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신고 161
98.2%
허가 3
 
1.8%

Length

2023-12-13T00:43:40.219489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:40.323631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신고 161
98.2%
허가 3
 
1.8%

폐수처리방식
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
하폐종 유입
85 
<NA>
40 
직방류
35 
전량위탁
 
4

Length

Max length6
Median length6
Mean length4.8231707
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하폐종 유입 85
51.8%
<NA> 40
24.4%
직방류 35
21.3%
전량위탁 4
 
2.4%

Length

2023-12-13T00:43:40.490450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:40.616339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하폐종 85
34.1%
유입 85
34.1%
na 40
16.1%
직방류 35
14.1%
전량위탁 4
 
1.6%

폐수처리공법
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
물리화학
91 
<NA>
39 
물리
19 
위탁
 
4
물리적
 
4
Other values (4)
 
7

Length

Max length14
Median length4
Mean length3.8231707
Min length2

Unique

Unique3 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
물리화학 91
55.5%
<NA> 39
23.8%
물리 19
 
11.6%
위탁 4
 
2.4%
물리적 4
 
2.4%
물리화학적 4
 
2.4%
위탁+물리화학생물 1
 
0.6%
물리화학생물 1
 
0.6%
물리화학(공동방지시설유입) 1
 
0.6%

Length

2023-12-13T00:43:40.770331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:40.914073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물리화학 91
55.5%
na 39
23.8%
물리 19
 
11.6%
위탁 4
 
2.4%
물리적 4
 
2.4%
물리화학적 4
 
2.4%
위탁+물리화학생물 1
 
0.6%
물리화학생물 1
 
0.6%
물리화학(공동방지시설유입 1
 
0.6%

배출허용기준 지역구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
나
125 
<NA>
39 

Length

Max length4
Median length1
Mean length1.7134146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나 125
76.2%
<NA> 39
 
23.8%

Length

2023-12-13T00:43:41.085508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:41.294713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나 125
76.2%
na 39
 
23.8%

Correlations

2023-12-13T00:43:41.396164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종종별신고허가폐수처리방식폐수처리공법
구분1.0000.9750.7480.0000.0000.000
업종0.9751.0000.9941.0000.9260.877
종별0.7480.9941.0000.5440.0000.863
신고허가0.0001.0000.5441.0000.0000.948
폐수처리방식0.0000.9260.0000.0001.0000.782
폐수처리공법0.0000.8770.8630.9480.7821.000
2023-12-13T00:43:41.550390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐수처리방식폐수처리공법구분종별업종신고허가배출허용기준 지역구분
폐수처리방식1.0000.6830.0000.0000.6700.0001.000
폐수처리공법0.6831.0000.0000.6670.6020.7811.000
구분0.0000.0001.0000.4050.7660.0001.000
종별0.0000.6670.4051.0000.8320.8091.000
업종0.6700.6020.7660.8321.0000.9091.000
신고허가0.0000.7810.0000.8090.9091.0001.000
배출허용기준 지역구분1.0001.0001.0001.0001.0001.0001.000
2023-12-13T00:43:41.694161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종종별신고허가폐수처리방식폐수처리공법배출허용기준 지역구분
구분1.0000.7660.4050.0000.0000.0001.000
업종0.7661.0000.8320.9090.6700.6021.000
종별0.4050.8321.0000.8090.0000.6671.000
신고허가0.0000.9090.8091.0000.0000.7811.000
폐수처리방식0.0000.6700.0000.0001.0000.6831.000
폐수처리공법0.0000.6020.6670.7810.6831.0001.000
배출허용기준 지역구분1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T00:43:37.884632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:43:38.041859image/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

구분업체명소재지업종종별신고허가폐수처리방식폐수처리공법배출허용기준 지역구분
0대기한국지엠서대전서비스센타㈜대전광역시 유성구 계백로 809운수시설및장비수선4신고<NA><NA><NA>
1대기신대광대전광역시 유성구 진잠로 67자동차정비업4신고<NA><NA><NA>
2대기케이에스모터스대전광역시 유성구 대학로76번길 99자동차정비업5신고<NA><NA><NA>
3대기유성현대서비스대전광역시 유성구 한밭대로 398자동차정비업5신고<NA><NA><NA>
4대기오토월드자동차공업사대전광역시 유성구 유성대로 488 (복용동)자동차정비업5신고<NA><NA><NA>
5대기르노삼성자동차서대전정비사업소대전광역시 유성구 유성대로 34 (원내동)자동차종합수리업5신고<NA><NA><NA>
6대기+수질한성자동차 대전유성서비스센터대전광역시 유성구 북유성대로 352 (반석동)자동차종합정비업5신고하폐종 유입물리화학나
7대기신나는 모터스대전광역시 유성구 온천동로 5자동차종합수리업5신고<NA><NA><NA>
8대기서일모터스대전광역시 유성구 유성대로 26-26자동차정비업5신고<NA><NA><NA>
9대기부영주택대전광역시 유성구 유성대로 42-95금속조립구조재제조업4신고<NA><NA><NA>
구분업체명소재지업종종별신고허가폐수처리방식폐수처리공법배출허용기준 지역구분
154수질몽키스패너세차장대전광역시 유성구 반석서로19번길 41(지족동)세차5신고직방류물리화학나
155수질봉산손세차장대전광역시 유성구 원내로 69-8(원내동)세차5신고하폐종 유입물리화학나
156수질태화광택대전광역시 유성구 유성대로 488, 117호(복용동)세차5신고직방류물리화학나
157수질한밭대학교(E1동 공동실험실습관)대전광역시 유성구 동서대로 125 (덕명동)이화학실험시설5신고전량위탁위탁나
158수질혹시 프리미엄 세차장대전광역시 유성구 장대로80번길 39세차5신고하폐종 유입물리화학나
159수질신동광택대전광역시 유성구 복용동로 35, 지하 B146, B147호(복용동, 디오토몰)세차5신고하폐종 유입물리화학(공동방지시설유입)나
160수질루페스 빅풋 디테일링센터 대전유성점대전광역시 유성구 진잠로 136(원내동)세차5신고하폐종 유입물리화학나
161수질정다운대전광역시 유성구 유성대로654번길 87세차5신고하폐종 유입물리화학나
162수질고운차 깨끗하게대전광역시 유성구 계룡로74번길 85, 1층(봉명동)세차5신고하폐종 유입물리화학나
163수질롯데쇼핑 롯데마트 서대전점대전광역시 유성구 원내동 369-1번지세차5신고하폐종 유입물리나

Duplicate rows

Most frequently occurring

구분업체명소재지업종종별신고허가폐수처리방식폐수처리공법배출허용기준 지역구분# duplicates
0수질태화광택대전광역시 유성구 유성대로 488, 117호(복용동)세차5신고직방류물리화학나2