Overview

Dataset statistics

Number of variables8
Number of observations48
Missing cells96
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory69.8 B

Variable types

Numeric1
Text4
Categorical1
Unsupported2

Dataset

Description송파구의 사업장 폐기물 배출자 신고현황입니다. 배출업체명, 소재지, 전화번호, 폐기물 종류의 정보를 담고 있습니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15060146/fileData.do

Alerts

비 고 has 48 (100.0%) missing valuesMissing
Unnamed: 7 has 48 (100.0%) missing valuesMissing
연번 has unique valuesUnique
배출자(업체) 명 has unique valuesUnique
전화번호 has unique valuesUnique
비 고 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 16:59:56.519796
Analysis finished2023-12-12 16:59:57.238263
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:59:57.316404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2023-12-13T01:59:57.524553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

배출자(업체) 명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T01:59:57.752009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length10.8125
Min length4

Characters and Unicode

Total characters519
Distinct characters143
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row강동수산(주)
2nd row수협중앙회가락동공판장
3rd row서울건해산물(주)
4th row경찰병원
5th row롯데쇼핑(주)롯데백화점 잠실점
ValueCountFrequency (%)
롯데쇼핑(주)롯데마트 2
 
3.1%
주)호텔롯데 2
 
3.1%
주식회사 2
 
3.1%
잠실점 2
 
3.1%
가든파이브 1
 
1.6%
인천가공사업소 1
 
1.6%
농협경제지주(주 1
 
1.6%
향군타워사업본부 1
 
1.6%
대한민국재향군인회 1
 
1.6%
웍스(주 1
 
1.6%
Other values (50) 50
78.1%
2023-12-13T01:59:58.131145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 29
 
5.6%
( 27
 
5.2%
) 27
 
5.2%
16
 
3.1%
롯 15
 
2.9%
데 15
 
2.9%
가 11
 
2.1%
산 11
 
2.1%
사 10
 
1.9%
서 10
 
1.9%
Other values (133) 348
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 447
86.1%
Open Punctuation 27
 
5.2%
Close Punctuation 27
 
5.2%
Space Separator 16
 
3.1%
Other Symbol 1
 
0.2%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
6.5%
롯 15
 
3.4%
데 15
 
3.4%
가 11
 
2.5%
산 11
 
2.5%
사 10
 
2.2%
서 10
 
2.2%
점 10
 
2.2%
회 9
 
2.0%
울 9
 
2.0%
Other values (128) 318
71.1%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
86.3%
Common 71
 
13.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
6.5%
롯 15
 
3.3%
데 15
 
3.3%
가 11
 
2.5%
산 11
 
2.5%
사 10
 
2.2%
서 10
 
2.2%
점 10
 
2.2%
회 9
 
2.0%
울 9
 
2.0%
Other values (129) 319
71.2%
Common
ValueCountFrequency (%)
( 27
38.0%
) 27
38.0%
16
22.5%
5 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 447
86.1%
ASCII 71
 
13.7%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 29
 
6.5%
롯 15
 
3.4%
데 15
 
3.4%
가 11
 
2.5%
산 11
 
2.5%
사 10
 
2.2%
서 10
 
2.2%
점 10
 
2.2%
회 9
 
2.0%
울 9
 
2.0%
Other values (128) 318
71.1%
ASCII
ValueCountFrequency (%)
( 27
38.0%
) 27
38.0%
16
22.5%
5 1
 
1.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T01:59:58.355258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32.5
Mean length25.5625
Min length19

Characters and Unicode

Total characters1227
Distinct characters95
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)68.8%

Sample

1st row서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)
2nd row서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)
3rd row서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)
4th row서울시 송파구 송이로 123 (가락동,경찰병원환자식당)
5th row서울시 송파구 올림픽로 240 (잠실동)
ValueCountFrequency (%)
송파구 48
18.0%
서울시 47
17.6%
양재대로 15
 
5.6%
932 15
 
5.6%
올림픽로 15
 
5.6%
가락동 14
 
5.2%
신천동 9
 
3.4%
문정동 7
 
2.6%
잠실동 7
 
2.6%
청과동 6
 
2.2%
Other values (56) 84
31.5%
2023-12-13T01:59:58.702535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
18.3%
동 59
 
4.8%
시 55
 
4.5%
송 52
 
4.2%
파 52
 
4.2%
서 50
 
4.1%
울 50
 
4.1%
구 50
 
4.1%
로 48
 
3.9%
( 48
 
3.9%
Other values (85) 538
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 740
60.3%
Space Separator 225
 
18.3%
Decimal Number 147
 
12.0%
Open Punctuation 48
 
3.9%
Close Punctuation 48
 
3.9%
Other Punctuation 17
 
1.4%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
 
8.0%
시 55
 
7.4%
송 52
 
7.0%
파 52
 
7.0%
서 50
 
6.8%
울 50
 
6.8%
구 50
 
6.8%
로 48
 
6.5%
가 20
 
2.7%
대 19
 
2.6%
Other values (69) 285
38.5%
Decimal Number
ValueCountFrequency (%)
2 34
23.1%
3 28
19.0%
9 16
10.9%
0 15
10.2%
1 15
10.2%
5 13
 
8.8%
4 11
 
7.5%
6 9
 
6.1%
8 4
 
2.7%
7 2
 
1.4%
Space Separator
ValueCountFrequency (%)
225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 740
60.3%
Common 486
39.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
 
8.0%
시 55
 
7.4%
송 52
 
7.0%
파 52
 
7.0%
서 50
 
6.8%
울 50
 
6.8%
구 50
 
6.8%
로 48
 
6.5%
가 20
 
2.7%
대 19
 
2.6%
Other values (69) 285
38.5%
Common
ValueCountFrequency (%)
225
46.3%
( 48
 
9.9%
) 48
 
9.9%
2 34
 
7.0%
3 28
 
5.8%
, 17
 
3.5%
9 16
 
3.3%
0 15
 
3.1%
1 15
 
3.1%
5 13
 
2.7%
Other values (5) 27
 
5.6%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 740
60.3%
ASCII 487
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
225
46.2%
( 48
 
9.9%
) 48
 
9.9%
2 34
 
7.0%
3 28
 
5.7%
, 17
 
3.5%
9 16
 
3.3%
0 15
 
3.1%
1 15
 
3.1%
5 13
 
2.7%
Other values (6) 28
 
5.7%
Hangul
ValueCountFrequency (%)
동 59
 
8.0%
시 55
 
7.4%
송 52
 
7.0%
파 52
 
7.0%
서 50
 
6.8%
울 50
 
6.8%
구 50
 
6.8%
로 48
 
6.5%
가 20
 
2.7%
대 19
 
2.6%
Other values (69) 285
38.5%

전화번호
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T01:59:58.937751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.604167
Min length11

Characters and Unicode

Total characters557
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

Unique48 ?
Unique (%)100.0%

Sample

1st row02-3435-3300
2nd row02-407-4463
3rd row02-407-7875
4th row02-404-2231
5th row02-411-5551
ValueCountFrequency (%)
02-3435-3300 1
 
2.1%
02-407-4463 1
 
2.1%
02-409-2101 1
 
2.1%
02-3435-1615 1
 
2.1%
02-408-3818 1
 
2.1%
02-2180-3922 1
 
2.1%
02-411-1204 1
 
2.1%
02-2047-6040 1
 
2.1%
02-2157-5110 1
 
2.1%
02-2157-0143 1
 
2.1%
Other values (38) 38
79.2%
2023-12-13T01:59:59.324200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 103
18.5%
2 101
18.1%
- 96
17.2%
1 55
9.9%
3 49
8.8%
4 49
8.8%
5 32
 
5.7%
7 24
 
4.3%
8 21
 
3.8%
6 15
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 461
82.8%
Dash Punctuation 96
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 103
22.3%
2 101
21.9%
1 55
11.9%
3 49
10.6%
4 49
10.6%
5 32
 
6.9%
7 24
 
5.2%
8 21
 
4.6%
6 15
 
3.3%
9 12
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 557
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 103
18.5%
2 101
18.1%
- 96
17.2%
1 55
9.9%
3 49
8.8%
4 49
8.8%
5 32
 
5.7%
7 24
 
4.3%
8 21
 
3.8%
6 15
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 103
18.5%
2 101
18.1%
- 96
17.2%
1 55
9.9%
3 49
8.8%
4 49
8.8%
5 32
 
5.7%
7 24
 
4.3%
8 21
 
3.8%
6 15
 
2.7%

폐기물 종류
Text

Distinct41
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T01:59:59.580932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length43
Mean length29.145833
Min length3

Characters and Unicode

Total characters1399
Distinct characters55
Distinct categories5 ?
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 (%)75.0%

Sample

1st row그밖의폐기물, 수산물가공잔재물,폐가구류,폐폴리염화비닐수지류, 음식물류폐기물, 폐발포합성수지
2nd row수산물가공잔재물,그밖의폐기물,음식물류폐기물,폐가구류,폐폴리염화비닐수지류,폐발포합성수지
3rd row그밖의폐기물, 폐폴리염화비닐수지류
4th row그밖의폐기물,폐합성수지류,음식물류폐기물
5th row그밖의폐기물, 그밖의폐목재류,폐합성수지류, 축산물가공잔재물, 음식물류폐기물
ValueCountFrequency (%)
음식물류폐기물 28
17.0%
그밖의 24
14.5%
폐합성수지류 21
12.7%
그밖의폐기물 18
10.9%
폐기물 12
 
7.3%
식물성잔재물 7
 
4.2%
폐식용유 3
 
1.8%
폐폴리염화비닐수지류 3
 
1.8%
폐발포합성수지 3
 
1.8%
동물성유지류 2
 
1.2%
Other values (36) 44
26.7%
2023-12-13T01:59:59.972237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
물 149
 
10.7%
폐 148
 
10.6%
, 124
 
8.9%
117
 
8.4%
류 95
 
6.8%
기 74
 
5.3%
그 57
 
4.1%
의 57
 
4.1%
밖 57
 
4.1%
식 52
 
3.7%
Other values (45) 469
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1156
82.6%
Other Punctuation 124
 
8.9%
Space Separator 117
 
8.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 149
12.9%
폐 148
12.8%
류 95
 
8.2%
기 74
 
6.4%
그 57
 
4.9%
의 57
 
4.9%
밖 57
 
4.9%
식 52
 
4.5%
성 51
 
4.4%
지 50
 
4.3%
Other values (41) 366
31.7%
Other Punctuation
ValueCountFrequency (%)
, 124
100.0%
Space Separator
ValueCountFrequency (%)
117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1156
82.6%
Common 243
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 149
12.9%
폐 148
12.8%
류 95
 
8.2%
기 74
 
6.4%
그 57
 
4.9%
의 57
 
4.9%
밖 57
 
4.9%
식 52
 
4.5%
성 51
 
4.4%
지 50
 
4.3%
Other values (41) 366
31.7%
Common
ValueCountFrequency (%)
, 124
51.0%
117
48.1%
( 1
 
0.4%
) 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1156
82.6%
ASCII 243
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
물 149
12.9%
폐 148
12.8%
류 95
 
8.2%
기 74
 
6.4%
그 57
 
4.9%
의 57
 
4.9%
밖 57
 
4.9%
식 52
 
4.5%
성 51
 
4.4%
지 50
 
4.3%
Other values (41) 366
31.7%
ASCII
ValueCountFrequency (%)
, 124
51.0%
117
48.1%
( 1
 
0.4%
) 1
 
0.4%

폐기물성질 . 상태
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
고상
41 
고상,액상
7 

Length

Max length5
Median length2
Mean length2.4375
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고상 41
85.4%
고상,액상 7
 
14.6%

Length

2023-12-13T02:00:00.131092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:00:00.253983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고상 41
85.4%
고상,액상 7
 
14.6%

비 고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

Interactions

2023-12-13T01:59:56.868214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:00:00.352237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번배출자(업체) 명소재지전화번호폐기물 종류폐기물성질 . 상태
연번1.0001.0000.9421.0000.9550.441
배출자(업체) 명1.0001.0001.0001.0001.0001.000
소재지0.9421.0001.0001.0000.0000.852
전화번호1.0001.0001.0001.0001.0001.000
폐기물 종류0.9551.0000.0001.0001.0001.000
폐기물성질 . 상태0.4411.0000.8521.0001.0001.000
2023-12-13T02:00:00.477416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번폐기물성질 . 상태
연번1.0000.302
폐기물성질 . 상태0.3021.000

Missing values

2023-12-13T01:59:57.022969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:59:57.187310image/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

연번배출자(업체) 명소재지전화번호폐기물 종류폐기물성질 . 상태비 고Unnamed: 7
01강동수산(주)서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)02-3435-3300그밖의폐기물, 수산물가공잔재물,폐가구류,폐폴리염화비닐수지류, 음식물류폐기물, 폐발포합성수지고상<NA><NA>
12수협중앙회가락동공판장서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)02-407-4463수산물가공잔재물,그밖의폐기물,음식물류폐기물,폐가구류,폐폴리염화비닐수지류,폐발포합성수지고상<NA><NA>
23서울건해산물(주)서울시 송파구 양재대로 932, 농수산물도매시장 수산물시장동 (가락동)02-407-7875그밖의폐기물, 폐폴리염화비닐수지류고상<NA><NA>
34경찰병원서울시 송파구 송이로 123 (가락동,경찰병원환자식당)02-404-2231그밖의폐기물,폐합성수지류,음식물류폐기물고상<NA><NA>
45롯데쇼핑(주)롯데백화점 잠실점서울시 송파구 올림픽로 240 (잠실동)02-411-5551그밖의폐기물, 그밖의폐목재류,폐합성수지류, 축산물가공잔재물, 음식물류폐기물고상<NA><NA>
56롯데쇼핑(주)롯데마트 송파점서울시 송파구 중대로 80 (문정동)02-2006-7791그밖의폐기물, 축산물가공전재물,폐합성수지류, 음식물류폐기물, 그밖의 폐목재류고상,액상<NA><NA>
67롯데쇼핑(주)롯데캐슬플라자서울시 송파구 올림픽로 300 (신천동)02-3213-2655폐합성수지류,그밖의폐기물,음식물류폐기물고상<NA><NA>
78롯데쇼핑(주)롯데마트 잠실점서울시 송파구 올림픽로 240 (잠실동)02-411-8411그밖의폐기물, 폐합성수지류, 그밖의폐목재류, 음식물류폐기물, 폐식용유, 축산물가공잔재물고상<NA><NA>
89롯데쇼핑(주)에비뉴엘월드타워점서울시 송파구 올림픽로 300 (신천동)02-3213-2651폐합성수지류,폐식용유,폐가구류,그밖의폐기물, 음식물류폐기물고상,액상<NA><NA>
910롯데물산(주)서울시 송파구 올림픽로 300 (신천동)02-411-5100폐합성수지류,그밖의폐기물,폐식용유,음식물류폐기물고상,액상<NA><NA>
연번배출자(업체) 명소재지전화번호폐기물 종류폐기물성질 . 상태비 고Unnamed: 7
3839가락몰종합유통협의회서울시 송파구 양재대로 932 (가락동)02-6978-0087그밖의 식물성잔재물, 음식물류폐기물고상<NA><NA>
3940가락몰유통인조합서울시 송파구 양재대로 932 (가락동)02-6978-3112그 밖의 식물성잔재물고상<NA><NA>
4041국제해양수산(주)서울시 송파구 새말로 125 (문정동)02-403-7773수산물가공잔재물고상<NA><NA>
4142롯데물산(주)월드타워점서울시 송파구 올림픽로 300 (신천동, 월드타워)02-3213-5408폐합성수지류, 그밖의 폐기물, 목재가공공장 부산물, 음식물류폐기물고상<NA><NA>
4243쿠팡풀필먼트서비스(유)서울시 송파구 송파대로 55, 서울복합물류 E동 (장지동)02-6150-5090폐합성수지류, 그밖의 식물성잔재류, 그밖의 페목재류고상<NA><NA>
4344(주)두산베어스서울시 송파구 올림픽로 25, 잠실야구장 (잠실동)02-2202-3835폐합성수지류, 그밖의 폐기물고상<NA><NA>
4445(주)엘지스포츠서울시 송파구 올림픽로 26, 잠실야구장 (잠실동)02-2202-3834폐합성수지류, 그밖의 폐기물고상<NA><NA>
4546한국전력공사 강동송파지사서울시 송파구 송파대로 155 (문정동)20-480-2273폐전주고상<NA><NA>
4647주식회사 엔테크코리아서울시 송파구 오금로11길 61-17 (오금동)02-412-2585폐금속캔류, 폐유리병류고상<NA><NA>
4748의료법인 참예원의료재단서울시 송파구 마천로 164 (오금동)02-409-2114음식물류폐기물, 그밖의 폐섬유고상<NA><NA>