Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
Duplicate rows (%)0.1%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Text3
Categorical1
Numeric1

Dataset

Description올바로시스템에서 운영하는 폐기물 중 사업장폐기물에 대한 정보현황(기초시군구, 업체명, 폐기물구분 등)입니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15084025/fileData.do

Alerts

Dataset has 13 (0.1%) duplicate rowsDuplicates
연간배출량(톤) is highly skewed (γ1 = 93.47004817)Skewed

Reproduction

Analysis started2023-12-12 12:43:41.154285
Analysis finished2023-12-12 12:43:42.152507
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기초시군구(관할관청)
Text

Distinct275
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:43:42.405903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.2051
Min length5

Characters and Unicode

Total characters82051
Distinct characters153
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row경상남도 하동군
2nd row경기도 파주시
3rd row서울특별시 서초구
4th row경기도 부천시 중동
5th row충청북도 청주시 흥덕구
ValueCountFrequency (%)
경기도 1549
 
8.3%
경상북도 677
 
3.6%
충청북도 676
 
3.6%
부산광역시 660
 
3.5%
경상남도 645
 
3.5%
남구 552
 
3.0%
한강유역환경청 525
 
2.8%
낙동강유역환경청 521
 
2.8%
충청남도 520
 
2.8%
전라남도 503
 
2.7%
Other values (256) 11767
63.3%
2023-12-12T21:43:43.224649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8595
 
10.5%
시 6884
 
8.4%
도 5421
 
6.6%
경 5084
 
6.2%
역 3815
 
4.6%
청 3621
 
4.4%
구 3567
 
4.3%
광 2649
 
3.2%
남 2489
 
3.0%
산 2403
 
2.9%
Other values (143) 37523
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73456
89.5%
Space Separator 8595
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 6884
 
9.4%
도 5421
 
7.4%
경 5084
 
6.9%
역 3815
 
5.2%
청 3621
 
4.9%
구 3567
 
4.9%
광 2649
 
3.6%
남 2489
 
3.4%
산 2403
 
3.3%
북 2093
 
2.8%
Other values (142) 35430
48.2%
Space Separator
ValueCountFrequency (%)
8595
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73456
89.5%
Common 8595
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 6884
 
9.4%
도 5421
 
7.4%
경 5084
 
6.9%
역 3815
 
5.2%
청 3621
 
4.9%
구 3567
 
4.9%
광 2649
 
3.6%
남 2489
 
3.4%
산 2403
 
3.3%
북 2093
 
2.8%
Other values (142) 35430
48.2%
Common
ValueCountFrequency (%)
8595
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73456
89.5%
ASCII 8595
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8595
100.0%
Hangul
ValueCountFrequency (%)
시 6884
 
9.4%
도 5421
 
7.4%
경 5084
 
6.9%
역 3815
 
5.2%
청 3621
 
4.9%
구 3567
 
4.9%
광 2649
 
3.6%
남 2489
 
3.4%
산 2403
 
3.3%
북 2093
 
2.8%
Other values (142) 35430
48.2%

업체명
Text

Distinct4452
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:43:43.533572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length44
Mean length11.5274
Min length1

Characters and Unicode

Total characters115274
Distinct characters715
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2258 ?
Unique (%)22.6%

Sample

1st row하동군 옥종공공하수처리장
2nd row케이에스폐차산업 주식회사
3rd row서울특별시 품질 시험소
4th row(주)이마트 중동점
5th row주) 엠비아이
ValueCountFrequency (%)
주식회사 381
 
2.5%
슬레이트 243
 
1.6%
2020년 177
 
1.2%
해체처리공사 88
 
0.6%
의료법인 76
 
0.5%
주 71
 
0.5%
충주시 66
 
0.4%
주)엘지화학 60
 
0.4%
및 59
 
0.4%
주)이마트 59
 
0.4%
Other values (5581) 13908
91.6%
2023-12-12T21:43:44.055454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 7191
 
6.2%
) 6876
 
6.0%
( 6867
 
6.0%
5204
 
4.5%
공 2641
 
2.3%
사 2220
 
1.9%
이 1991
 
1.7%
장 1866
 
1.6%
원 1824
 
1.6%
스 1755
 
1.5%
Other values (705) 76839
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90911
78.9%
Close Punctuation 6884
 
6.0%
Open Punctuation 6875
 
6.0%
Space Separator 5204
 
4.5%
Decimal Number 2986
 
2.6%
Uppercase Letter 1218
 
1.1%
Dash Punctuation 649
 
0.6%
Lowercase Letter 340
 
0.3%
Other Punctuation 139
 
0.1%
Connector Punctuation 56
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 7191
 
7.9%
공 2641
 
2.9%
사 2220
 
2.4%
이 1991
 
2.2%
장 1866
 
2.1%
원 1824
 
2.0%
스 1755
 
1.9%
산 1585
 
1.7%
업 1442
 
1.6%
리 1424
 
1.6%
Other values (632) 66972
73.7%
Uppercase Letter
ValueCountFrequency (%)
S 204
16.7%
K 164
13.5%
C 122
10.0%
L 115
9.4%
G 107
8.8%
A 69
 
5.7%
M 54
 
4.4%
P 53
 
4.4%
T 48
 
3.9%
O 32
 
2.6%
Other values (16) 250
20.5%
Lowercase Letter
ValueCountFrequency (%)
l 66
19.4%
i 47
13.8%
o 42
12.4%
a 31
9.1%
s 28
8.2%
c 25
 
7.4%
p 20
 
5.9%
b 17
 
5.0%
g 17
 
5.0%
n 11
 
3.2%
Other values (12) 36
10.6%
Decimal Number
ValueCountFrequency (%)
2 1142
38.2%
0 825
27.6%
1 436
 
14.6%
3 230
 
7.7%
4 83
 
2.8%
7 64
 
2.1%
8 62
 
2.1%
5 58
 
1.9%
9 47
 
1.6%
6 39
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 76
54.7%
. 37
26.6%
/ 22
 
15.8%
: 2
 
1.4%
* 1
 
0.7%
？ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 6876
99.9%
] 8
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 6867
99.9%
[ 8
 
0.1%
Space Separator
ValueCountFrequency (%)
5204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 649
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 56
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90914
78.9%
Common 22802
 
19.8%
Latin 1558
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 7191
 
7.9%
공 2641
 
2.9%
사 2220
 
2.4%
이 1991
 
2.2%
장 1866
 
2.1%
원 1824
 
2.0%
스 1755
 
1.9%
산 1585
 
1.7%
업 1442
 
1.6%
리 1424
 
1.6%
Other values (633) 66975
73.7%
Latin
ValueCountFrequency (%)
S 204
 
13.1%
K 164
 
10.5%
C 122
 
7.8%
L 115
 
7.4%
G 107
 
6.9%
A 69
 
4.4%
l 66
 
4.2%
M 54
 
3.5%
P 53
 
3.4%
T 48
 
3.1%
Other values (38) 556
35.7%
Common
ValueCountFrequency (%)
) 6876
30.2%
( 6867
30.1%
5204
22.8%
2 1142
 
5.0%
0 825
 
3.6%
- 649
 
2.8%
1 436
 
1.9%
3 230
 
1.0%
4 83
 
0.4%
, 76
 
0.3%
Other values (14) 414
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90910
78.9%
ASCII 24359
 
21.1%
None 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 7191
 
7.9%
공 2641
 
2.9%
사 2220
 
2.4%
이 1991
 
2.2%
장 1866
 
2.1%
원 1824
 
2.0%
스 1755
 
1.9%
산 1585
 
1.7%
업 1442
 
1.6%
리 1424
 
1.6%
Other values (631) 66971
73.7%
ASCII
ValueCountFrequency (%)
) 6876
28.2%
( 6867
28.2%
5204
21.4%
2 1142
 
4.7%
0 825
 
3.4%
- 649
 
2.7%
1 436
 
1.8%
3 230
 
0.9%
S 204
 
0.8%
K 164
 
0.7%
Other values (61) 1762
 
7.2%
None
ValueCountFrequency (%)
㈜ 3
75.0%
？ 1
 
25.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

폐기물구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
해당없음
4290 
사업장배출시설계폐기물
3798 
사업장생활계폐기물
1912 

Length

Max length11
Median length9
Mean length7.6146
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장배출시설계폐기물
2nd row사업장배출시설계폐기물
3rd row해당없음
4th row사업장생활계폐기물
5th row사업장생활계폐기물

Common Values

ValueCountFrequency (%)
해당없음 4290
42.9%
사업장배출시설계폐기물 3798
38.0%
사업장생활계폐기물 1912
19.1%

Length

2023-12-12T21:43:44.248347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:43:44.384942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 4290
42.9%
사업장배출시설계폐기물 3798
38.0%
사업장생활계폐기물 1912
19.1%

폐기물명
Text

Distinct178
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:43:44.640350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length66
Mean length20.2317
Min length2

Characters and Unicode

Total characters202317
Distinct characters295
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.2%

Sample

1st row하수처리오니
2nd row금속성폐촉매
3rd row그 밖의 폐산
4th row음식물류폐기물
5th row음식물류폐기물
ValueCountFrequency (%)
밖의 2839
 
8.1%
그 2839
 
8.1%
제외한다 1751
 
5.0%
폐합성수지류(폐염화비닐수지류는 1463
 
4.2%
말한다 1373
 
3.9%
폐유 1167
 
3.3%
및 917
 
2.6%
등을 831
 
2.4%
폐광물유[아스팔트유ㆍ그리스(grease)ㆍ방청유 503
 
1.4%
수용성절삭유 503
 
1.4%
Other values (295) 20705
59.3%
2023-12-12T21:43:44.993480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24891
 
12.3%
폐 12392
 
6.1%
유 8281
 
4.1%
의 5235
 
2.6%
물 5168
 
2.6%
수 4407
 
2.2%
기 4370
 
2.2%
류 4366
 
2.2%
ㆍ 4117
 
2.0%
한 3627
 
1.8%
Other values (285) 125463
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162577
80.4%
Space Separator 24891
 
12.3%
Open Punctuation 4123
 
2.0%
Close Punctuation 4123
 
2.0%
Lowercase Letter 3054
 
1.5%
Other Punctuation 1979
 
1.0%
Decimal Number 1552
 
0.8%
Uppercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 12392
 
7.6%
유 8281
 
5.1%
의 5235
 
3.2%
물 5168
 
3.2%
수 4407
 
2.7%
기 4370
 
2.7%
류 4366
 
2.7%
ㆍ 4117
 
2.5%
한 3627
 
2.2%
성 3586
 
2.2%
Other values (260) 107028
65.8%
Lowercase Letter
ValueCountFrequency (%)
e 1018
33.3%
a 509
16.7%
s 503
16.5%
g 503
16.5%
r 503
16.5%
t 6
 
0.2%
h 6
 
0.2%
l 6
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 647
41.7%
0 503
32.4%
1 217
 
14.0%
8 179
 
11.5%
4 6
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 3441
83.5%
[ 503
 
12.2%
「 179
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 3441
83.5%
] 503
 
12.2%
」 179
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 10
55.6%
D 4
 
22.2%
L 4
 
22.2%
Other Punctuation
ValueCountFrequency (%)
, 1975
99.8%
? 4
 
0.2%
Space Separator
ValueCountFrequency (%)
24891
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162571
80.4%
Common 36668
 
18.1%
Latin 3072
 
1.5%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 12392
 
7.6%
유 8281
 
5.1%
의 5235
 
3.2%
물 5168
 
3.2%
수 4407
 
2.7%
기 4370
 
2.7%
류 4366
 
2.7%
ㆍ 4117
 
2.5%
한 3627
 
2.2%
성 3586
 
2.2%
Other values (258) 107022
65.8%
Common
ValueCountFrequency (%)
24891
67.9%
( 3441
 
9.4%
) 3441
 
9.4%
, 1975
 
5.4%
2 647
 
1.8%
] 503
 
1.4%
0 503
 
1.4%
[ 503
 
1.4%
1 217
 
0.6%
「 179
 
0.5%
Other values (4) 368
 
1.0%
Latin
ValueCountFrequency (%)
e 1018
33.1%
a 509
16.6%
s 503
16.4%
g 503
16.4%
r 503
16.4%
C 10
 
0.3%
t 6
 
0.2%
h 6
 
0.2%
l 6
 
0.2%
D 4
 
0.1%
Han
ValueCountFrequency (%)
冶 3
50.0%
金 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158454
78.3%
ASCII 39382
 
19.5%
Compat Jamo 4117
 
2.0%
None 358
 
0.2%
CJK 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24891
63.2%
( 3441
 
8.7%
) 3441
 
8.7%
, 1975
 
5.0%
e 1018
 
2.6%
2 647
 
1.6%
a 509
 
1.3%
] 503
 
1.3%
0 503
 
1.3%
[ 503
 
1.3%
Other values (13) 1951
 
5.0%
Hangul
ValueCountFrequency (%)
폐 12392
 
7.8%
유 8281
 
5.2%
의 5235
 
3.3%
물 5168
 
3.3%
수 4407
 
2.8%
기 4370
 
2.8%
류 4366
 
2.8%
한 3627
 
2.3%
성 3586
 
2.3%
지 3543
 
2.2%
Other values (257) 103479
65.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4117
100.0%
None
ValueCountFrequency (%)
「 179
50.0%
」 179
50.0%
CJK
ValueCountFrequency (%)
冶 3
50.0%
金 3
50.0%

연간배출량(톤)
Real number (ℝ)

SKEWED 

Distinct7105
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2231.216
Minimum0
Maximum9561909
Zeros50
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:43:45.129287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0291
Q12.5
median23.83
Q3164.37
95-th percentile3181.1375
Maximum9561909
Range9561909
Interquartile range (IQR)161.87

Descriptive statistics

Standard deviation97983.08
Coefficient of variation (CV)43.914655
Kurtosis9072.0238
Mean2231.216
Median Absolute Deviation (MAD)23.73
Skewness93.470048
Sum22312160
Variance9.600684 × 109
MonotonicityNot monotonic
2023-12-12T21:43:45.266524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 111
 
1.1%
0.02 69
 
0.7%
0.0 50
 
0.5%
0.1 49
 
0.5%
0.05 44
 
0.4%
0.027 44
 
0.4%
1.0 32
 
0.3%
0.026 30
 
0.3%
0.2 29
 
0.3%
0.03 29
 
0.3%
Other values (7095) 9513
95.1%
ValueCountFrequency (%)
0.0 50
0.5%
0.0003 2
 
< 0.1%
0.0004 1
 
< 0.1%
0.0005 1
 
< 0.1%
0.001 7
 
0.1%
0.0015 1
 
< 0.1%
0.0017 1
 
< 0.1%
0.002 10
 
0.1%
0.0021 1
 
< 0.1%
0.0025 1
 
< 0.1%
ValueCountFrequency (%)
9561909.0 1
< 0.1%
1510300.0 1
< 0.1%
1169582.76 1
< 0.1%
634690.0 1
< 0.1%
322947.0 1
< 0.1%
307960.0 1
< 0.1%
269687.62 1
< 0.1%
164160.77 1
< 0.1%
158361.54 1
< 0.1%
149502.02 1
< 0.1%

Interactions

2023-12-12T21:43:41.857540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:43:45.359753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물구분연간배출량(톤)
폐기물구분1.0000.035
연간배출량(톤)0.0351.000
2023-12-12T21:43:45.439954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연간배출량(톤)폐기물구분
연간배출량(톤)1.0000.010
폐기물구분0.0101.000

Missing values

2023-12-12T21:43:41.979523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:43:42.097075image/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

기초시군구(관할관청)업체명폐기물구분폐기물명연간배출량(톤)
23127경상남도 하동군하동군 옥종공공하수처리장사업장배출시설계폐기물하수처리오니32.81
2759경기도 파주시케이에스폐차산업 주식회사사업장배출시설계폐기물금속성폐촉매4.083
29015서울특별시 서초구서울특별시 품질 시험소해당없음그 밖의 폐산0.02
1182경기도 부천시 중동(주)이마트 중동점사업장생활계폐기물음식물류폐기물203.242
34535충청북도 청주시 흥덕구주) 엠비아이사업장생활계폐기물음식물류폐기물3.04
19061강원도 양구군양구군 상하수도사업소-국토정중앙면공공하수처리시설사업장배출시설계폐기물그 밖의 폐기물7.87
28898서울특별시 금천구넥시오랩해당없음폐질산1.34
32057전라북도 완주군(주)대유에이피사업장배출시설계폐기물폐활성탄48.0
24716광주광역시 북구앰코테크놀로지코리아(주)사업장배출시설계폐기물폐발포합성수지23.63
34230충청북도 청주시 서원구오비맥주(주) 청주공장사업장배출시설계폐기물그 밖의 폐수처리오니65.97
기초시군구(관할관청)업체명폐기물구분폐기물명연간배출량(톤)
17163충청북도 청주시 서원구(주)장충동왕족발사업장배출시설계폐기물음식물류폐기물59.76
265강원도 원주시성지의료재단 성지병원해당없음일반의료폐기물49.464357
5717경상북도 영천시2020년 경상북도 영천시 슬레이트 철거 지원사업 2권역(정세민)해당없음석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등0.01
33566충청남도 천안시 동남구맑은물사업본부사업장배출시설계폐기물분뇨처리오니861.74
22265경상남도 거제시세양기업(주)사업장배출시설계폐기물폐합성수지류(폐염화비닐수지류는 제외한다)96.23
21880경기도 하남시친환경사업소(자원순환과)사업장배출시설계폐기물폐합성수지류(폐염화비닐수지류는 제외한다)3645.41
6561광주광역시 서구(주)호남청과-일반폐기물사업장생활계폐기물그 밖의 식물성잔재물383.45
4126경상남도 산청군산청군 생활폐기물소각시설해당없음생활폐기물 소각시설 비산재55.89
31134전라남도 구례군구례군 재난폐기물 운반 및 처리 용역사업장생활계폐기물폐합성수지류(폐염화비닐수지류는 제외한다)21734.93
13683전라남도 신안군2020년 전남 신안군 슬레이트 지붕해체 및 처리공사(3권역)-김광래해당없음석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등0.01

Duplicate rows

Most frequently occurring

기초시군구(관할관청)업체명폐기물구분폐기물명연간배출량(톤)# duplicates
0경기도 오산시(주)정진넥스텍사업장배출시설계폐기물폐합성수지류(폐염화비닐수지류는 제외한다)22.832
1경상남도 창녕군(주)중앙자동차해체재활용산업해당없음그 밖의 폐유기용제2.02
2경상남도 함안군경남폐차장유한회사해당없음폐윤활유(「자원의 절약과 재활용촉진에 관한 법률 시행령」 제18조에 따른 재활용의무 대상 제품ㆍ포장재인 기어유 및 내연기관용 윤활유를 말한다)12.02
3경상북도 구미시(주)지씨선산해당없음폐황산이 포함된 2차폐축전지0.02
4낙동강유역환경청현대제철(주)해당없음석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등0.22
5부산광역시 수영구지산의원해당없음손상성폐기물0.0312
6서울특별시 강남구(주)아스타아이비에스-지정해당없음그 밖의 폐산1.02
7서울특별시 서초구서울특별시 품질 시험소해당없음그 밖의 폐산0.022
8울산광역시 남구롯데케미칼 주식회사 울산1공장사업장배출시설계폐기물그 밖의 폐냉매물질0.02
9전라남도 장흥군한국한의학진흥원해당없음그 밖의 폐유기용제2.02