Overview

Dataset statistics

Number of variables8
Number of observations83
Missing cells7
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory66.6 B

Variable types

Categorical4
Text3
Numeric1

Dataset

Description인천광역시 미추홀구의 산업폐기물 배출자 신고자현황에 대한 데이터로 사업장명, 소재지,전화번호, 주요품목, 처리방법 등의 항목을 포함하여 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15060158/fileData.do

Alerts

유형 is highly overall correlated with 주요품목 and 1 other fieldsHigh correlation
주요품목 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
처리방법 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
전화번호 has 7 (8.4%) missing valuesMissing

Reproduction

Analysis started2024-04-29 22:35:54.143050
Analysis finished2024-04-29 22:35:56.878299
Duration2.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size796.0 B
사업장폐기물
52 
지정폐기물
31 

Length

Max length6
Median length6
Mean length5.626506
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사업장폐기물 52
62.7%
지정폐기물 31
37.3%

Length

2024-04-30T07:35:56.944024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:35:57.044641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장폐기물 52
62.7%
지정폐기물 31
37.3%

상호(사업장명)
Text

Distinct79
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
2024-04-30T07:35:57.271606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length7.6144578
Min length3

Characters and Unicode

Total characters632
Distinct characters192
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

Unique75 ?
Unique (%)90.4%

Sample

1st row한국세차장
2nd row(사)인천자동차검사 정비사업조합
3rd row인천IT타워관리위원회
4th row인하대학교
5th row경인지방식품의약품안전청
ValueCountFrequency (%)
한국폴리텍대학 2
 
2.0%
㈜에스엔씨 2
 
2.0%
인하공업전문대학 2
 
2.0%
인하대학교 2
 
2.0%
남인천캠퍼스 2
 
2.0%
㈜타이거일렉 1
 
1.0%
이건에너지㈜ 1
 
1.0%
홈플러스㈜인천숭의점 1
 
1.0%
㈜그린이에스에이 1
 
1.0%
백송전자㈜ 1
 
1.0%
Other values (84) 84
84.8%
2024-04-30T07:35:57.660234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 44
 
7.0%
인 30
 
4.7%
17
 
2.7%
천 17
 
2.7%
스 17
 
2.7%
업 14
 
2.2%
공 13
 
2.1%
이 12
 
1.9%
대 12
 
1.9%
리 11
 
1.7%
Other values (182) 445
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 566
89.6%
Other Symbol 44
 
7.0%
Space Separator 17
 
2.7%
Uppercase Letter 2
 
0.3%
Decimal Number 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 30
 
5.3%
천 17
 
3.0%
스 17
 
3.0%
업 14
 
2.5%
공 13
 
2.3%
이 12
 
2.1%
대 12
 
2.1%
리 11
 
1.9%
학 11
 
1.9%
지 10
 
1.8%
Other values (175) 419
74.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 44
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 610
96.5%
Common 20
 
3.2%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 44
 
7.2%
인 30
 
4.9%
천 17
 
2.8%
스 17
 
2.8%
업 14
 
2.3%
공 13
 
2.1%
이 12
 
2.0%
대 12
 
2.0%
리 11
 
1.8%
학 11
 
1.8%
Other values (176) 429
70.3%
Common
ValueCountFrequency (%)
17
85.0%
1 1
 
5.0%
) 1
 
5.0%
( 1
 
5.0%
Latin
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 566
89.6%
None 44
 
7.0%
ASCII 22
 
3.5%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 44
100.0%
Hangul
ValueCountFrequency (%)
인 30
 
5.3%
천 17
 
3.0%
스 17
 
3.0%
업 14
 
2.5%
공 13
 
2.3%
이 12
 
2.1%
대 12
 
2.1%
리 11
 
1.9%
학 11
 
1.9%
지 10
 
1.8%
Other values (175) 419
74.0%
ASCII
ValueCountFrequency (%)
17
77.3%
T 1
 
4.5%
I 1
 
4.5%
1 1
 
4.5%
) 1
 
4.5%
( 1
 
4.5%

사업자등록번호
Text

Distinct77
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
2024-04-30T07:35:57.909097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters996
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

Unique71 ?
Unique (%)85.5%

Sample

1st row131-02-21676
2nd row131-82-02346
3rd row121-82-65801
4th row131-82-00372
5th row121-83-04271
ValueCountFrequency (%)
220-81-60348 2
 
2.4%
131-82-00445 2
 
2.4%
131-82-02031 2
 
2.4%
131-82-00372 2
 
2.4%
829-82-00256 2
 
2.4%
121-81-41573 2
 
2.4%
131-81-49683 1
 
1.2%
121-81-38874 1
 
1.2%
137-81-30805 1
 
1.2%
137-81-74439 1
 
1.2%
Other values (67) 67
80.7%
2024-04-30T07:35:58.240975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 189
19.0%
- 166
16.7%
0 114
11.4%
8 112
11.2%
3 105
10.5%
2 90
9.0%
5 55
 
5.5%
6 47
 
4.7%
7 47
 
4.7%
4 42
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 830
83.3%
Dash Punctuation 166
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 189
22.8%
0 114
13.7%
8 112
13.5%
3 105
12.7%
2 90
10.8%
5 55
 
6.6%
6 47
 
5.7%
7 47
 
5.7%
4 42
 
5.1%
9 29
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 189
19.0%
- 166
16.7%
0 114
11.4%
8 112
11.2%
3 105
10.5%
2 90
9.0%
5 55
 
5.5%
6 47
 
4.7%
7 47
 
4.7%
4 42
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 189
19.0%
- 166
16.7%
0 114
11.4%
8 112
11.2%
3 105
10.5%
2 90
9.0%
5 55
 
5.5%
6 47
 
4.7%
7 47
 
4.7%
4 42
 
4.2%

소재지
Categorical

Distinct14
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size796.0 B
인천광역시 미추홀구 도화동
32 
인천광역시 미추홀구 주안동
16 
인천광역시 미추홀구 주안동
9 
인천광역시 미추홀구 용현동
8 
인천광역시 미추홀구 학익동
7 
Other values (9)
11 

Length

Max length25
Median length14
Mean length14.349398
Min length13

Unique

Unique7 ?
Unique (%)8.4%

Sample

1st row인천광역시 미추홀구 학익동
2nd row인천광역시 미추홀구 주안동
3rd row인천광역시 미추홀구 도화동
4th row인천광역시 미추홀구 용현동
5th row인천광역시 미추홀구 주안동

Common Values

ValueCountFrequency (%)
인천광역시 미추홀구 도화동 32
38.6%
인천광역시 미추홀구 주안동 16
19.3%
인천광역시 미추홀구 주안동 9
 
10.8%
인천광역시 미추홀구 용현동 8
 
9.6%
인천광역시 미추홀구 학익동 7
 
8.4%
인천광역시 미추홀구 관교동 2
 
2.4%
인천광역시 미추홀구 숭의동 2
 
2.4%
인천광역시 미추홀구 학익동 1
 
1.2%
인천광역시 미추홀구 문학동 1
 
1.2%
인천광역시 남동구 간석동 1
 
1.2%
Other values (4) 4
 
4.8%

Length

2024-04-30T07:35:58.377274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미추홀구 82
32.7%
인천광역시 81
32.3%
도화동 32
 
12.7%
주안동 25
 
10.0%
용현동 8
 
3.2%
학익동 8
 
3.2%
관교동 3
 
1.2%
숭의동 2
 
0.8%
문학동 2
 
0.8%
인천시 2
 
0.8%
Other values (6) 6
 
2.4%

전화번호
Text

MISSING 

Distinct69
Distinct (%)90.8%
Missing7
Missing (%)8.4%
Memory size796.0 B
2024-04-30T07:35:58.609548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.973684
Min length9

Characters and Unicode

Total characters910
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

Unique62 ?
Unique (%)81.6%

Sample

1st row032-832-8304
2nd row032-420-1171
3rd row032-255-6995
4th row032-860-7107
5th row032-442-4603
ValueCountFrequency (%)
032-450-0335 2
 
2.6%
032-865-8441 2
 
2.6%
032-860-7107 2
 
2.6%
032-363-9785 2
 
2.6%
032-870-2062 2
 
2.6%
032-760-0307 2
 
2.6%
032-864-7013 2
 
2.6%
032-876-2731 1
 
1.3%
032-865-3600 1
 
1.3%
032-582-8035 1
 
1.3%
Other values (59) 59
77.6%
2024-04-30T07:35:59.020151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 151
16.6%
0 149
16.4%
3 132
14.5%
2 120
13.2%
8 69
7.6%
7 66
7.3%
5 54
 
5.9%
1 52
 
5.7%
6 50
 
5.5%
4 43
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 759
83.4%
Dash Punctuation 151
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 149
19.6%
3 132
17.4%
2 120
15.8%
8 69
9.1%
7 66
8.7%
5 54
 
7.1%
1 52
 
6.9%
6 50
 
6.6%
4 43
 
5.7%
9 24
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 910
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 151
16.6%
0 149
16.4%
3 132
14.5%
2 120
13.2%
8 69
7.6%
7 66
7.3%
5 54
 
5.9%
1 52
 
5.7%
6 50
 
5.5%
4 43
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 910
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 151
16.6%
0 149
16.4%
3 132
14.5%
2 120
13.2%
8 69
7.6%
7 66
7.3%
5 54
 
5.9%
1 52
 
5.7%
6 50
 
5.5%
4 43
 
4.7%

신고연도
Real number (ℝ)

Distinct24
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.6145
Minimum1996
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-04-30T07:35:59.137684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1996
5-th percentile2001.2
Q12006
median2013
Q32019
95-th percentile2023
Maximum2024
Range28
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.4928117
Coefficient of variation (CV)0.0037229245
Kurtosis-1.0171337
Mean2012.6145
Median Absolute Deviation (MAD)6
Skewness-0.28644124
Sum167047
Variance56.142227
MonotonicityNot monotonic
2024-04-30T07:35:59.249983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2004 7
 
8.4%
2003 6
 
7.2%
2021 6
 
7.2%
2012 5
 
6.0%
2018 5
 
6.0%
2023 4
 
4.8%
2016 4
 
4.8%
2017 4
 
4.8%
2019 4
 
4.8%
2020 4
 
4.8%
Other values (14) 34
41.0%
ValueCountFrequency (%)
1996 1
 
1.2%
1998 3
3.6%
2001 1
 
1.2%
2003 6
7.2%
2004 7
8.4%
2005 3
3.6%
2007 4
4.8%
2008 2
 
2.4%
2009 2
 
2.4%
2010 2
 
2.4%
ValueCountFrequency (%)
2024 3
3.6%
2023 4
4.8%
2022 2
 
2.4%
2021 6
7.2%
2020 4
4.8%
2019 4
4.8%
2018 5
6.0%
2017 4
4.8%
2016 4
4.8%
2015 2
 
2.4%

주요품목
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
폐합성수지
19 
폐수처리오니
10 
폐황산이포함된2차폐축전지
6 
그밖의폐광물유
 
4
그 밖의 폐산
 
3
Other values (34)
41 

Length

Max length53
Median length39
Mean length9.1927711
Min length2

Unique

Unique28 ?
Unique (%)33.7%

Sample

1st row폐윤활유+폐유기용제+그 밖의 폐광물류+폐오일필터
2nd row폐황산이 포함된 2차 폐축전지+그 밖의 폐유기용제+폐페인트+폐윤활유+그 밖의 폐광물유+폐오일필터
3rd row그 밖의 폐산
4th row그 밖의 폐유기용제+그 밖의 폐산+그 밖의 폐알칼리+ 연구+검사용 폐시약
5th row할로겐족 폐유기용제+그 밖의 폐산+그 밖의 폐알칼리+그 밖의 폐유기용제

Common Values

ValueCountFrequency (%)
폐합성수지 19
22.9%
폐수처리오니 10
 
12.0%
폐황산이포함된2차폐축전지 6
 
7.2%
그밖의폐광물유 4
 
4.8%
그 밖의 폐산 3
 
3.6%
그밖의폐산 3
 
3.6%
폐흡착제 2
 
2.4%
그밖의폐기물 2
 
2.4%
폐합성수지류 2
 
2.4%
그밖의폐섬유 2
 
2.4%
Other values (29) 30
36.1%

Length

2024-04-30T07:35:59.369645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐합성수지 19
 
15.0%
밖의 18
 
14.2%
폐수처리오니 10
 
7.9%
그 8
 
6.3%
폐황산이포함된2차폐축전지 6
 
4.7%
그밖의폐광물유 4
 
3.1%
폐산 4
 
3.1%
그밖의폐산 3
 
2.4%
폐황산이 2
 
1.6%
분진 2
 
1.6%
Other values (43) 51
40.2%

처리방법
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size796.0 B
재활용(중간가공폐기물 제조)[2010]
19 
중간처분(일반소각)[2101]
13 
재활용(원료 제조)
13 
매립(민간관리형 매립시설)[2201]
6 
재활용(연료+고형연료제품제조)+중간처리(일반소각)
3 
Other values (20)
29 

Length

Max length48
Median length30
Mean length18.144578
Min length10

Unique

Unique13 ?
Unique (%)15.7%

Sample

1st row재활용(연료+고형연료제품제조)+중간처리(일반소각)
2nd row재활용(원료제조)+중간처리(일반소각)+재활용(연료+고형연료제품제조)+중간처리(고온소각)
3rd row재활용(원료 제조)
4th row중간처리(고온소각)+중간처리(증발농축)+중간처리(중화)
5th row중간처리(고온소각)+중간처리(증발농축)

Common Values

ValueCountFrequency (%)
재활용(중간가공폐기물 제조)[2010] 19
22.9%
중간처분(일반소각)[2101] 13
15.7%
재활용(원료 제조) 13
15.7%
매립(민간관리형 매립시설)[2201] 6
 
7.2%
재활용(연료+고형연료제품제조)+중간처리(일반소각) 3
 
3.6%
재활용(직접 제품제조)[2004] 3
 
3.6%
재활용(연료+고형연료제품제조) 3
 
3.6%
재활용(중간가공폐기물제조) 2
 
2.4%
재활용(직접제품제조)[2004] 2
 
2.4%
재활용(원료제조)[2003] 2
 
2.4%
Other values (15) 17
20.5%

Length

2024-04-30T07:35:59.484023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재활용(중간가공폐기물 21
16.3%
제조)[2010 19
14.7%
제조 15
11.6%
중간처분(일반소각)[2101 13
10.1%
재활용(원료 13
10.1%
매립(민간관리형 6
 
4.7%
매립시설)[2201 6
 
4.7%
재활용(연료+고형연료제품제조 5
 
3.9%
재활용(직접 3
 
2.3%
제품제조)[2004 3
 
2.3%
Other values (20) 25
19.4%

Interactions

2024-04-30T07:35:56.534173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:35:59.577925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형상호(사업장명)사업자등록번호소재지전화번호신고연도주요품목처리방법
유형1.0000.0000.0000.6780.0000.1151.0000.986
상호(사업장명)0.0001.0001.0000.9131.0000.5910.0000.000
사업자등록번호0.0001.0001.0000.8740.9990.7910.9560.798
소재지0.6780.9130.8741.0000.9680.0000.0000.000
전화번호0.0001.0000.9990.9681.0000.7310.0000.000
신고연도0.1150.5910.7910.0000.7311.0000.0000.421
주요품목1.0000.0000.9560.0000.0000.0001.0000.977
처리방법0.9860.0000.7980.0000.0000.4210.9771.000
2024-04-30T07:35:59.687780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주요품목유형처리방법소재지
주요품목1.0000.7370.6070.000
유형0.7371.0000.8310.496
처리방법0.6070.8311.0000.000
소재지0.0000.4960.0001.000
2024-04-30T07:35:59.772404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고연도유형소재지주요품목처리방법
신고연도1.0000.1160.0000.0140.169
유형0.1161.0000.4960.7370.831
소재지0.0000.4961.0000.0000.000
주요품목0.0140.7370.0001.0000.607
처리방법0.1690.8310.0000.6071.000

Missing values

2024-04-30T07:35:56.711021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:35:56.828947image/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

유형상호(사업장명)사업자등록번호소재지전화번호신고연도주요품목처리방법
0지정폐기물한국세차장131-02-21676인천광역시 미추홀구 학익동032-832-83042003폐윤활유+폐유기용제+그 밖의 폐광물류+폐오일필터재활용(연료+고형연료제품제조)+중간처리(일반소각)
1지정폐기물(사)인천자동차검사 정비사업조합131-82-02346인천광역시 미추홀구 주안동032-420-11712003폐황산이 포함된 2차 폐축전지+그 밖의 폐유기용제+폐페인트+폐윤활유+그 밖의 폐광물유+폐오일필터재활용(원료제조)+중간처리(일반소각)+재활용(연료+고형연료제품제조)+중간처리(고온소각)
2지정폐기물인천IT타워관리위원회121-82-65801인천광역시 미추홀구 도화동032-255-69952007그 밖의 폐산재활용(원료 제조)
3지정폐기물인하대학교131-82-00372인천광역시 미추홀구 용현동032-860-71072007그 밖의 폐유기용제+그 밖의 폐산+그 밖의 폐알칼리+ 연구+검사용 폐시약중간처리(고온소각)+중간처리(증발농축)+중간처리(중화)
4지정폐기물경인지방식품의약품안전청121-83-04271인천광역시 미추홀구 주안동032-442-46032004할로겐족 폐유기용제+그 밖의 폐산+그 밖의 폐알칼리+그 밖의 폐유기용제중간처리(고온소각)+중간처리(증발농축)
5지정폐기물금창부식광고121-60-05359인천광역시 미추홀구 용현동032-773-54332009폐산재활용(원료 제조)
6지정폐기물관교동아아파트131-80-03507인천광역시 미추홀구 관교동032-435-75572009그밖의폐산재활용(원료 제조)
7지정폐기물관교풍림아파트입주자대표회의133-82-60885인천광역시 미추홀구 관교동032-437-92512011그 밖의 폐산재활용(원료 제조)
8지정폐기물㈜아인121-86-13918인천광역시 미추홀구 도화동032-884-03032012그 밖의 폐유+그 밖의 폐광물유재활용(연료+고형연료제품제조)+중간처리(일반소각)
9지정폐기물인천지방법원131-83-00554인천광역시 미추홀구 학익동032-860-11942012그밖의폐산재활용(원료 제조)
유형상호(사업장명)사업자등록번호소재지전화번호신고연도주요품목처리방법
73사업장폐기물로뎀요양병원683-98-00030인천광역시 미추홀구 주안동1544-25082019그밖의폐섬유중간처분(일반소각)[2101]
74사업장폐기물인일요양병원341-94-00045인천광역시 미추홀구 주안동032-863-00512020그밖의폐섬유중간처분(일반소각)[2101]
75사업장폐기물일영산업121-18-23950인천광역시 미추홀구 도화동032-773-09532020목재가공공장 부산물재활용(연료+고형연료제품제조)
76사업장폐기물한국보훈복지의료공단 인천보훈병원829-82-00256인천광역시 미추홀구 용현동032-363-97852021폐합성수지재활용(중간가공폐기물 제조)[2010]
77사업장폐기물㈜에코프라임829-82-00256인천광역시 미추홀구 용현동032-363-97852020폐수처리오니재활용(중간가공폐기물 제조)[2010]
78사업장폐기물㈜에스엔씨121-81-41573인천광역시 미추홀구 도화동032-864-70132022그밖의분진재활용(중간가공폐기물 제조)[2010]
79사업장폐기물㈜나눌652-81-02225인천광역시 미추홀구 도화동<NA>2023폐수처리오니재활용(직접제품제조)[2004]
80사업장폐기물㈜드림씨앤씨528-81-01369인천광역시 미추홀구 도화동070-7543-92712023폐활성탄재활용(직접제품제조)[2004]
81사업장폐기물한국폴리텍대학 남인천캠퍼스131-82-02031인천시 미추홀구 염전로333번길 23(주안동)032-450-03352024폐합성수지류재활용(중간가공폐기물 제조)[2010]
82사업장폐기물주식회사 베스트리빙131-81-81740인천시 미추홀구 염전로 99(도화동)<NA>2024폐합성수지류재활용(중간가공폐기물 제조)[2010]