Overview

Dataset statistics

Number of variables7
Number of observations336
Missing cells114
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.8 KiB
Average record size in memory57.4 B

Variable types

Numeric1
Text4
Categorical1
DateTime1

Dataset

Description해당 데이터는 인천광역시 남동구의 폐기물처리업체 현황에 관련된 자료로서, 인천광역시 남동구 폐기물처리업체 현황의 연번, 상호, 대표자, 업종, 소재지, 연락처의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104541&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
연락처 has 113 (33.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:55:03.027006
Analysis finished2024-01-28 17:55:03.719005
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.5
Minimum1
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-01-29T02:55:03.778666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.75
Q184.75
median168.5
Q3252.25
95-th percentile319.25
Maximum336
Range335
Interquartile range (IQR)167.5

Descriptive statistics

Standard deviation97.139076
Coefficient of variation (CV)0.57649303
Kurtosis-1.2
Mean168.5
Median Absolute Deviation (MAD)84
Skewness0
Sum56616
Variance9436
MonotonicityStrictly increasing
2024-01-29T02:55:03.906442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
223 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
Other values (326) 326
97.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
336 1
0.3%
335 1
0.3%
334 1
0.3%
333 1
0.3%
332 1
0.3%
331 1
0.3%
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%

상호
Text

Distinct277
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-29T02:55:04.203567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length6.0208333
Min length2

Characters and Unicode

Total characters2023
Distinct characters242
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique237 ?
Unique (%)70.5%

Sample

1st row㈜그린스코
2nd row㈜이알지서비스
3rd row㈜씨엔에스
4th row(주)미래엔텍(지점)
5th row㈜신원골드
ValueCountFrequency (%)
㈜에스쓰리알 6
 
1.7%
주)미래엔텍(지점 5
 
1.4%
㈜인천리사이클링 5
 
1.4%
㈜씨엔에스 4
 
1.1%
명민산업㈜ 4
 
1.1%
건실업 4
 
1.1%
㈜현대에코텍 4
 
1.1%
건영산업 4
 
1.1%
㈜이알지서비스 3
 
0.9%
주)동호철재 2
 
0.6%
Other values (278) 310
88.3%
2024-01-29T02:55:04.608185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 125
 
6.2%
이 86
 
4.3%
경 73
 
3.6%
( 65
 
3.2%
) 65
 
3.2%
환 63
 
3.1%
주 60
 
3.0%
지 58
 
2.9%
에 56
 
2.8%
스 55
 
2.7%
Other values (232) 1317
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1733
85.7%
Other Symbol 125
 
6.2%
Open Punctuation 65
 
3.2%
Close Punctuation 65
 
3.2%
Space Separator 15
 
0.7%
Uppercase Letter 15
 
0.7%
Decimal Number 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 86
 
5.0%
경 73
 
4.2%
환 63
 
3.6%
주 60
 
3.5%
지 58
 
3.3%
에 56
 
3.2%
스 55
 
3.2%
업 47
 
2.7%
산 37
 
2.1%
리 32
 
1.8%
Other values (215) 1166
67.3%
Uppercase Letter
ValueCountFrequency (%)
E 3
20.0%
N 3
20.0%
C 3
20.0%
V 1
 
6.7%
S 1
 
6.7%
D 1
 
6.7%
M 1
 
6.7%
P 1
 
6.7%
R 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1858
91.8%
Common 150
 
7.4%
Latin 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 125
 
6.7%
이 86
 
4.6%
경 73
 
3.9%
환 63
 
3.4%
주 60
 
3.2%
지 58
 
3.1%
에 56
 
3.0%
스 55
 
3.0%
업 47
 
2.5%
산 37
 
2.0%
Other values (216) 1198
64.5%
Latin
ValueCountFrequency (%)
E 3
20.0%
N 3
20.0%
C 3
20.0%
V 1
 
6.7%
S 1
 
6.7%
D 1
 
6.7%
M 1
 
6.7%
P 1
 
6.7%
R 1
 
6.7%
Common
ValueCountFrequency (%)
( 65
43.3%
) 65
43.3%
15
 
10.0%
2 2
 
1.3%
. 1
 
0.7%
& 1
 
0.7%
1 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1733
85.7%
ASCII 165
 
8.2%
None 125
 
6.2%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 125
100.0%
Hangul
ValueCountFrequency (%)
이 86
 
5.0%
경 73
 
4.2%
환 63
 
3.6%
주 60
 
3.5%
지 58
 
3.3%
에 56
 
3.2%
스 55
 
3.2%
업 47
 
2.7%
산 37
 
2.1%
리 32
 
1.8%
Other values (215) 1166
67.3%
ASCII
ValueCountFrequency (%)
( 65
39.4%
) 65
39.4%
15
 
9.1%
E 3
 
1.8%
N 3
 
1.8%
C 3
 
1.8%
2 2
 
1.2%
V 1
 
0.6%
. 1
 
0.6%
S 1
 
0.6%
Other values (6) 6
 
3.6%

대표자
Text

Distinct260
Distinct (%)77.6%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2024-01-29T02:55:04.899945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.2179104
Min length2

Characters and Unicode

Total characters1078
Distinct characters183
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique217 ?
Unique (%)64.8%

Sample

1st row박래수
2nd row심연규
3rd row오순용
4th row이종탁
5th row대표이사
ValueCountFrequency (%)
서종현 7
 
2.1%
이종탁 6
 
1.8%
이기중 5
 
1.5%
박경순 4
 
1.2%
조유리 4
 
1.2%
이경근 4
 
1.2%
조상학 4
 
1.2%
이경화 4
 
1.2%
오현숙 4
 
1.2%
대표이사 4
 
1.2%
Other values (251) 290
86.3%
2024-01-29T02:55:05.288139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 76
 
7.1%
이 72
 
6.7%
박 26
 
2.4%
경 26
 
2.4%
현 25
 
2.3%
정 25
 
2.3%
한 21
 
1.9%
영 21
 
1.9%
종 21
 
1.9%
진 18
 
1.7%
Other values (173) 747
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1052
97.6%
Other Punctuation 11
 
1.0%
Uppercase Letter 11
 
1.0%
Decimal Number 3
 
0.3%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 76
 
7.2%
이 72
 
6.8%
박 26
 
2.5%
경 26
 
2.5%
현 25
 
2.4%
정 25
 
2.4%
한 21
 
2.0%
영 21
 
2.0%
종 21
 
2.0%
진 18
 
1.7%
Other values (162) 721
68.5%
Uppercase Letter
ValueCountFrequency (%)
E 2
18.2%
H 2
18.2%
N 2
18.2%
J 1
9.1%
I 1
9.1%
C 1
9.1%
G 1
9.1%
Z 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1052
97.6%
Common 15
 
1.4%
Latin 11
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 76
 
7.2%
이 72
 
6.8%
박 26
 
2.5%
경 26
 
2.5%
현 25
 
2.4%
정 25
 
2.4%
한 21
 
2.0%
영 21
 
2.0%
종 21
 
2.0%
진 18
 
1.7%
Other values (162) 721
68.5%
Latin
ValueCountFrequency (%)
E 2
18.2%
H 2
18.2%
N 2
18.2%
J 1
9.1%
I 1
9.1%
C 1
9.1%
G 1
9.1%
Z 1
9.1%
Common
ValueCountFrequency (%)
, 11
73.3%
1 3
 
20.0%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1052
97.6%
ASCII 26
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 76
 
7.2%
이 72
 
6.8%
박 26
 
2.5%
경 26
 
2.5%
현 25
 
2.4%
정 25
 
2.4%
한 21
 
2.0%
영 21
 
2.0%
종 21
 
2.0%
진 18
 
1.7%
Other values (162) 721
68.5%
ASCII
ValueCountFrequency (%)
, 11
42.3%
1 3
 
11.5%
E 2
 
7.7%
H 2
 
7.7%
N 2
 
7.7%
J 1
 
3.8%
I 1
 
3.8%
C 1
 
3.8%
G 1
 
3.8%
Z 1
 
3.8%

업종
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
수집운반업
162 
폐기물처리신고
74 
재활용업(종합)
61 
재활용업(중간)
37 
중간처분업(소각전문)
 
2

Length

Max length11
Median length8
Mean length6.3511905
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중간처분업(소각전문)
2nd row중간처분업(소각전문)
3rd row재활용업(종합)
4th row재활용업(종합)
5th row재활용업(종합)

Common Values

ValueCountFrequency (%)
수집운반업 162
48.2%
폐기물처리신고 74
22.0%
재활용업(종합) 61
 
18.2%
재활용업(중간) 37
 
11.0%
중간처분업(소각전문) 2
 
0.6%

Length

2024-01-29T02:55:05.410865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:55:05.505116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업 162
48.2%
폐기물처리신고 74
22.0%
재활용업(종합 61
 
18.2%
재활용업(중간 37
 
11.0%
중간처분업(소각전문 2
 
0.6%

소재지
Text

Distinct296
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-29T02:55:05.745697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length26.806548
Min length15

Characters and Unicode

Total characters9007
Distinct characters175
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

Unique265 ?
Unique (%)78.9%

Sample

1st row인천광역시 남동구 앵고개로654번길 99
2nd row인천광역시 남동구 남동서로316번길 41
3rd row인천광역시 남동구 고잔로 61
4th row인천광역시 남동구 고잔로 50 (고잔동)
5th row인천광역시 남동구 앵고개로697번길 97 (고잔동)
ValueCountFrequency (%)
인천광역시 336
20.4%
남동구 336
20.4%
고잔동 46
 
2.8%
고잔로 26
 
1.6%
음실서로 18
 
1.1%
150 16
 
1.0%
운연로 15
 
0.9%
앵고개로697번길 12
 
0.7%
청능대로484번길 10
 
0.6%
은청로 10
 
0.6%
Other values (500) 826
50.0%
2024-01-29T02:55:06.126617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1320
 
14.7%
동 616
 
6.8%
남 386
 
4.3%
구 377
 
4.2%
인 351
 
3.9%
천 340
 
3.8%
역 339
 
3.8%
시 339
 
3.8%
광 336
 
3.7%
1 336
 
3.7%
Other values (165) 4267
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5327
59.1%
Decimal Number 1722
 
19.1%
Space Separator 1320
 
14.7%
Close Punctuation 181
 
2.0%
Open Punctuation 181
 
2.0%
Other Punctuation 139
 
1.5%
Dash Punctuation 125
 
1.4%
Uppercase Letter 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 616
 
11.6%
남 386
 
7.2%
구 377
 
7.1%
인 351
 
6.6%
천 340
 
6.4%
역 339
 
6.4%
시 339
 
6.4%
광 336
 
6.3%
로 317
 
6.0%
고 204
 
3.8%
Other values (142) 1722
32.3%
Decimal Number
ValueCountFrequency (%)
1 336
19.5%
2 233
13.5%
4 201
11.7%
3 183
10.6%
5 170
9.9%
0 169
9.8%
6 147
8.5%
7 111
 
6.4%
8 94
 
5.5%
9 78
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 136
97.8%
/ 1
 
0.7%
. 1
 
0.7%
@ 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 4
33.3%
B 4
33.3%
M 2
16.7%
L 2
16.7%
Open Punctuation
ValueCountFrequency (%)
( 180
99.4%
[ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1320
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5327
59.1%
Common 3668
40.7%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 616
 
11.6%
남 386
 
7.2%
구 377
 
7.1%
인 351
 
6.6%
천 340
 
6.4%
역 339
 
6.4%
시 339
 
6.4%
광 336
 
6.3%
로 317
 
6.0%
고 204
 
3.8%
Other values (142) 1722
32.3%
Common
ValueCountFrequency (%)
1320
36.0%
1 336
 
9.2%
2 233
 
6.4%
4 201
 
5.5%
3 183
 
5.0%
) 181
 
4.9%
( 180
 
4.9%
5 170
 
4.6%
0 169
 
4.6%
6 147
 
4.0%
Other values (9) 548
14.9%
Latin
ValueCountFrequency (%)
A 4
33.3%
B 4
33.3%
M 2
16.7%
L 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5327
59.1%
ASCII 3680
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1320
35.9%
1 336
 
9.1%
2 233
 
6.3%
4 201
 
5.5%
3 183
 
5.0%
) 181
 
4.9%
( 180
 
4.9%
5 170
 
4.6%
0 169
 
4.6%
6 147
 
4.0%
Other values (13) 560
15.2%
Hangul
ValueCountFrequency (%)
동 616
 
11.6%
남 386
 
7.2%
구 377
 
7.1%
인 351
 
6.6%
천 340
 
6.4%
역 339
 
6.4%
시 339
 
6.4%
광 336
 
6.3%
로 317
 
6.0%
고 204
 
3.8%
Other values (142) 1722
32.3%

연락처
Text

MISSING 

Distinct161
Distinct (%)72.2%
Missing113
Missing (%)33.6%
Memory size2.8 KiB
2024-01-29T02:55:06.344904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.977578
Min length9

Characters and Unicode

Total characters2671
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

Unique124 ?
Unique (%)55.6%

Sample

1st row032-822-2930
2nd row032-446-0388
3rd row032-423-8272
4th row032-433-2343
5th row032-446-2578
ValueCountFrequency (%)
032-423-8272 6
 
2.7%
032-446-2578 5
 
2.2%
032-446-6866 4
 
1.8%
032-446-0388 4
 
1.8%
032-433-2343 4
 
1.8%
032-472-0062 4
 
1.8%
032-818-2295 4
 
1.8%
032-469-7762 4
 
1.8%
032-464-0230 3
 
1.3%
032-472-5670 3
 
1.3%
Other values (151) 182
81.6%
2024-01-29T02:55:06.696218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 444
16.6%
2 442
16.5%
3 362
13.6%
0 344
12.9%
4 246
9.2%
8 174
 
6.5%
6 162
 
6.1%
1 161
 
6.0%
7 144
 
5.4%
5 106
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2227
83.4%
Dash Punctuation 444
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 442
19.8%
3 362
16.3%
0 344
15.4%
4 246
11.0%
8 174
 
7.8%
6 162
 
7.3%
1 161
 
7.2%
7 144
 
6.5%
5 106
 
4.8%
9 86
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 444
16.6%
2 442
16.5%
3 362
13.6%
0 344
12.9%
4 246
9.2%
8 174
 
6.5%
6 162
 
6.1%
1 161
 
6.0%
7 144
 
5.4%
5 106
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 444
16.6%
2 442
16.5%
3 362
13.6%
0 344
12.9%
4 246
9.2%
8 174
 
6.5%
6 162
 
6.1%
1 161
 
6.0%
7 144
 
5.4%
5 106
 
4.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2023-09-16 00:00:00
Maximum2023-09-16 00:00:00
2024-01-29T02:55:06.806592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:55:06.889399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T02:55:03.385479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:55:06.948877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.984
업종0.9841.000
2024-01-29T02:55:07.017211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.811
업종0.8111.000

Missing values

2024-01-29T02:55:03.492513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:55:03.587053image/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.
2024-01-29T02:55:03.676383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호대표자업종소재지연락처데이터기준일
01㈜그린스코박래수중간처분업(소각전문)인천광역시 남동구 앵고개로654번길 99<NA>2023-09-16
12㈜이알지서비스심연규중간처분업(소각전문)인천광역시 남동구 남동서로316번길 41032-822-29302023-09-16
23㈜씨엔에스오순용재활용업(종합)인천광역시 남동구 고잔로 61032-446-03882023-09-16
34(주)미래엔텍(지점)이종탁재활용업(종합)인천광역시 남동구 고잔로 50 (고잔동)032-423-82722023-09-16
45㈜신원골드대표이사재활용업(종합)인천광역시 남동구 앵고개로697번길 97 (고잔동)<NA>2023-09-16
56명민산업㈜오현숙재활용업(종합)인천광역시 남동구 고잔로 47-1, 47-2, 고잔동 390-10032-433-23432023-09-16
67㈜인천리사이클링이기중재활용업(종합)인천광역시 남동구 청능대로468번길 23 (고잔동)032-446-25782023-09-16
78양일엔프라㈜장나교재활용업(종합)인천광역시 남동구 남동동로93번길 44 (고잔동)032-812-20892023-09-16
89㈜유원포리머이형승재활용업(종합)인천광역시 남동구 능허대로625번길 15 (고잔동)032-811-79432023-09-16
910(주)유진상사양원길재활용업(종합)인천광역시 남동구 고잔로51번길 26 (고잔동)<NA>2023-09-16
연번상호대표자업종소재지연락처데이터기준일
326327㈜태진환경산업전소현수집운반업인천광역시 남동구 음실서로 37, 39<NA>2023-09-16
327328㈜남동메디케어김유열수집운반업인천광역시 남동구 논현고잔로130번길 29032-427-24562023-09-16
328329㈜기륭환경이주원수집운반업인천광역시 남동구 은청로 4-7, 남동공단산업용품상가 에이동 315호032-812-89392023-09-16
329330대한기초㈜한규석수집운반업인천광역시 남동구 인주대로850번길 31-3, 201호(만수동)032-465-99022023-09-16
330331영화자원김낙녀수집운반업인천광역시 남동구 논곡로 58, 3층(논현동)<NA>2023-09-16
331332㈜향우지향우수집운반업인천광역시 남동구 청능대로 559, 701호(논현동, 논현메디컬센터)<NA>2023-09-16
332333㈜엔지오기업장애인협회김교철수집운반업인천광역시 남동구 인주대로 750, 2층 (구월동)032-882-27002023-09-16
333334㈜양일엔프라장나교수집운반업인천광역시 남동구 남동동로93번길 44032-812-20892023-09-16
334335㈜이지피플지혜진수집운반업인천광역시 남동구 아암대로 1223, 315호(고잔동, 성강지식산업센터)032-817-15802023-09-16
335336대동자원심진우수집운반업인천광역시 남동구 고잔동 512-2번지<NA>2023-09-16