Overview

Dataset statistics

Number of variables31
Number of observations33
Missing cells367
Missing cells (%)35.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory266.0 B

Variable types

Categorical9
Numeric3
DateTime4
Unsupported8
Text7

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),환경업무구분명,폐기물처리업구분명,폐기물처리업별처리구분명,폐기물구분명,허용보관량,허용보관량내용
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19320/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
폐기물구분명 has constant value ""Constant
인허가취소일자 has 33 (100.0%) missing valuesMissing
폐업일자 has 18 (54.5%) missing valuesMissing
휴업시작일자 has 33 (100.0%) missing valuesMissing
휴업종료일자 has 33 (100.0%) missing valuesMissing
재개업일자 has 33 (100.0%) missing valuesMissing
전화번호 has 9 (27.3%) missing valuesMissing
소재지면적 has 33 (100.0%) missing valuesMissing
소재지우편번호 has 9 (27.3%) missing valuesMissing
지번주소 has 1 (3.0%) missing valuesMissing
도로명주소 has 17 (51.5%) missing valuesMissing
도로명우편번호 has 17 (51.5%) missing valuesMissing
업태구분명 has 33 (100.0%) missing valuesMissing
폐기물처리업별처리구분명 has 33 (100.0%) missing valuesMissing
폐기물구분명 has 32 (97.0%) missing valuesMissing
허용보관량내용 has 33 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기물처리업별처리구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 12:22:52.497707
Analysis finished2024-04-06 12:22:53.364489
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
3180000
33 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 33
100.0%

Length

2024-04-06T21:22:53.500591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:22:53.722993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 33
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1800009 × 1017
Minimum3.1800009 × 1017
Maximum3.1800009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T21:22:53.897242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1800009 × 1017
5-th percentile3.1800009 × 1017
Q13.1800009 × 1017
median3.1800009 × 1017
Q33.1800009 × 1017
95-th percentile3.1800009 × 1017
Maximum3.1800009 × 1017
Range2100002
Interquartile range (IQR)500032

Descriptive statistics

Standard deviation571200.68
Coefficient of variation (CV)1.796228 × 10-12
Kurtosis0.35111285
Mean3.1800009 × 1017
Median Absolute Deviation (MAD)300032
Skewness0.82271522
Sum-7.952741 × 1018
Variance3.2627022 × 1011
MonotonicityStrictly increasing
2024-04-06T21:22:54.123166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
318000092200100001 1
 
3.0%
318000092201200001 1
 
3.0%
318000092201000001 1
 
3.0%
318000092201100001 1
 
3.0%
318000092201100002 1
 
3.0%
318000092201100003 1
 
3.0%
318000092201100004 1
 
3.0%
318000092201100005 1
 
3.0%
318000092201200002 1
 
3.0%
318000092200100002 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
318000092200100001 1
3.0%
318000092200100002 1
3.0%
318000092200200001 1
3.0%
318000092200200002 1
3.0%
318000092200400002 1
3.0%
318000092200400003 1
3.0%
318000092200400004 1
3.0%
318000092200600001 1
3.0%
318000092200600002 1
3.0%
318000092200600003 1
3.0%
ValueCountFrequency (%)
318000092202200003 1
3.0%
318000092202200002 1
3.0%
318000092202200001 1
3.0%
318000092201700001 1
3.0%
318000092201500002 1
3.0%
318000092201500001 1
3.0%
318000092201200002 1
3.0%
318000092201200001 1
3.0%
318000092201100005 1
3.0%
318000092201100004 1
3.0%

인허가일자
Date

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2002-03-23 00:00:00
Maximum2023-04-21 00:00:00
2024-04-06T21:22:54.362123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:22:54.595257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
18 
3
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 18
54.5%
3 15
45.5%

Length

2024-04-06T21:22:54.835686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:22:55.001494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
54.5%
3 15
45.5%

영업상태명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
영업/정상
18 
폐업
15 

Length

Max length5
Median length5
Mean length3.6363636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 18
54.5%
폐업 15
45.5%

Length

2024-04-06T21:22:55.223085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:22:55.480070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 18
54.5%
폐업 15
45.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
BBBB
18 
2
15 

Length

Max length4
Median length4
Mean length2.6363636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd rowBBBB
4th rowBBBB
5th rowBBBB

Common Values

ValueCountFrequency (%)
BBBB 18
54.5%
2 15
45.5%

Length

2024-04-06T21:22:55.684520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:22:55.875336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 18
54.5%
2 15
45.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
영업
18 
폐업
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업
4th row영업
5th row영업

Common Values

ValueCountFrequency (%)
영업 18
54.5%
폐업 15
45.5%

Length

2024-04-06T21:22:56.039067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:22:56.195453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 18
54.5%
폐업 15
45.5%

폐업일자
Date

MISSING 

Distinct13
Distinct (%)86.7%
Missing18
Missing (%)54.5%
Memory size396.0 B
Minimum2007-07-19 00:00:00
Maximum2024-02-19 00:00:00
2024-04-06T21:22:56.346286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:22:56.535556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

전화번호
Text

MISSING 

Distinct20
Distinct (%)83.3%
Missing9
Missing (%)27.3%
Memory size396.0 B
2024-04-06T21:22:56.821529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.75
Min length7

Characters and Unicode

Total characters234
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

Unique16 ?
Unique (%)66.7%

Sample

1st row2631-0451
2nd row26331638
3rd row02-834-9091
4th row8349091
5th row26310451
ValueCountFrequency (%)
8349091 2
 
8.3%
02-2631-0100 2
 
8.3%
02-834-9091 2
 
8.3%
26310451 2
 
8.3%
26720808 1
 
4.2%
2631-0451 1
 
4.2%
02-877-9050 1
 
4.2%
2069-2978 1
 
4.2%
02-831-7979 1
 
4.2%
02-2608-8774 1
 
4.2%
Other values (10) 10
41.7%
2024-04-06T21:22:57.352080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
18.4%
2 32
13.7%
- 26
11.1%
1 20
8.5%
6 20
8.5%
3 19
8.1%
8 18
7.7%
7 18
7.7%
9 17
 
7.3%
4 11
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
88.9%
Dash Punctuation 26
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
20.7%
2 32
15.4%
1 20
9.6%
6 20
9.6%
3 19
9.1%
8 18
8.7%
7 18
8.7%
9 17
 
8.2%
4 11
 
5.3%
5 10
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
18.4%
2 32
13.7%
- 26
11.1%
1 20
8.5%
6 20
8.5%
3 19
8.1%
8 18
7.7%
7 18
7.7%
9 17
 
7.3%
4 11
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
18.4%
2 32
13.7%
- 26
11.1%
1 20
8.5%
6 20
8.5%
3 19
8.1%
8 18
7.7%
7 18
7.7%
9 17
 
7.3%
4 11
 
4.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

소재지우편번호
Text

MISSING 

Distinct13
Distinct (%)54.2%
Missing9
Missing (%)27.3%
Memory size396.0 B
2024-04-06T21:22:57.590180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2083333
Min length6

Characters and Unicode

Total characters149
Distinct characters10
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

Unique9 ?
Unique (%)37.5%

Sample

1st row150-032
2nd row150102
3rd row150-814
4th row150070
5th row150-032
ValueCountFrequency (%)
150032 7
29.2%
150-032 3
12.5%
150070 3
12.5%
150958 2
 
8.3%
150102 1
 
4.2%
150-814 1
 
4.2%
150901 1
 
4.2%
150072 1
 
4.2%
150093 1
 
4.2%
158-097 1
 
4.2%
Other values (3) 3
12.5%
2024-04-06T21:22:58.050385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47
31.5%
1 28
18.8%
5 26
17.4%
3 12
 
8.1%
2 12
 
8.1%
7 6
 
4.0%
9 6
 
4.0%
- 5
 
3.4%
8 4
 
2.7%
4 3
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144
96.6%
Dash Punctuation 5
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
32.6%
1 28
19.4%
5 26
18.1%
3 12
 
8.3%
2 12
 
8.3%
7 6
 
4.2%
9 6
 
4.2%
8 4
 
2.8%
4 3
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47
31.5%
1 28
18.8%
5 26
17.4%
3 12
 
8.1%
2 12
 
8.1%
7 6
 
4.0%
9 6
 
4.0%
- 5
 
3.4%
8 4
 
2.7%
4 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47
31.5%
1 28
18.8%
5 26
17.4%
3 12
 
8.1%
2 12
 
8.1%
7 6
 
4.0%
9 6
 
4.0%
- 5
 
3.4%
8 4
 
2.7%
4 3
 
2.0%

지번주소
Text

MISSING 

Distinct27
Distinct (%)84.4%
Missing1
Missing (%)3.0%
Memory size396.0 B
2024-04-06T21:22:58.405253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length27.1875
Min length20

Characters and Unicode

Total characters870
Distinct characters71
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)71.9%

Sample

1st row서울특별시 영등포구 영등포동2가 94-24 카보드동우빌딩 405호
2nd row서울특별시 영등포구 양평동2가 38-1번지 삼성아파트상사302호
3rd row서울특별시 영등포구 대림동 709-5
4th row서울특별시 영등포구 대림동 709-5번지
5th row서울특별시 영등포구 영등포동2가 94-29
ValueCountFrequency (%)
서울특별시 32
21.5%
영등포구 32
21.5%
영등포동2가 13
 
8.7%
대림동 8
 
5.4%
문래동5가 5
 
3.4%
709-5 4
 
2.7%
대륭오피스텔 3
 
2.0%
94-29번지 3
 
2.0%
709-5번지 2
 
1.3%
405호 2
 
1.3%
Other values (40) 45
30.2%
2024-04-06T21:22:58.987438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
15.4%
포 46
 
5.3%
영 46
 
5.3%
등 46
 
5.3%
2 34
 
3.9%
동 34
 
3.9%
시 33
 
3.8%
구 32
 
3.7%
서 32
 
3.7%
별 32
 
3.7%
Other values (61) 401
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 547
62.9%
Decimal Number 163
 
18.7%
Space Separator 134
 
15.4%
Dash Punctuation 26
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 46
 
8.4%
영 46
 
8.4%
등 46
 
8.4%
동 34
 
6.2%
시 33
 
6.0%
구 32
 
5.9%
서 32
 
5.9%
별 32
 
5.9%
특 32
 
5.9%
울 32
 
5.9%
Other values (49) 182
33.3%
Decimal Number
ValueCountFrequency (%)
2 34
20.9%
9 28
17.2%
4 27
16.6%
5 19
11.7%
1 17
10.4%
0 14
8.6%
7 12
 
7.4%
3 8
 
4.9%
8 2
 
1.2%
6 2
 
1.2%
Space Separator
ValueCountFrequency (%)
134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 547
62.9%
Common 323
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 46
 
8.4%
영 46
 
8.4%
등 46
 
8.4%
동 34
 
6.2%
시 33
 
6.0%
구 32
 
5.9%
서 32
 
5.9%
별 32
 
5.9%
특 32
 
5.9%
울 32
 
5.9%
Other values (49) 182
33.3%
Common
ValueCountFrequency (%)
134
41.5%
2 34
 
10.5%
9 28
 
8.7%
4 27
 
8.4%
- 26
 
8.0%
5 19
 
5.9%
1 17
 
5.3%
0 14
 
4.3%
7 12
 
3.7%
3 8
 
2.5%
Other values (2) 4
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 547
62.9%
ASCII 323
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
41.5%
2 34
 
10.5%
9 28
 
8.7%
4 27
 
8.4%
- 26
 
8.0%
5 19
 
5.9%
1 17
 
5.3%
0 14
 
4.3%
7 12
 
3.7%
3 8
 
2.5%
Other values (2) 4
 
1.2%
Hangul
ValueCountFrequency (%)
포 46
 
8.4%
영 46
 
8.4%
등 46
 
8.4%
동 34
 
6.2%
시 33
 
6.0%
구 32
 
5.9%
서 32
 
5.9%
별 32
 
5.9%
특 32
 
5.9%
울 32
 
5.9%
Other values (49) 182
33.3%

도로명주소
Text

MISSING 

Distinct15
Distinct (%)93.8%
Missing17
Missing (%)51.5%
Memory size396.0 B
2024-04-06T21:22:59.360692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length35.5625
Min length24

Characters and Unicode

Total characters569
Distinct characters81
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)87.5%

Sample

1st row서울특별시 영등포구 버드나루로7길 7, 405호 (영등포동2가)
2nd row서울특별시 영등포구 대림로 149 (대림동)
3rd row서울특별시 영등포구 대림로 149 (대림동)
4th row서울특별시 영등포구 버드나루로 41, 407호 (영등포동2가, 진흥빌딩)
5th row서울특별시 영등포구 대림로 149 (대림동, 후지빌딩)
ValueCountFrequency (%)
서울특별시 16
 
15.5%
영등포구 16
 
15.5%
대림동 4
 
3.9%
영등포동2가 4
 
3.9%
대림로 3
 
2.9%
149 3
 
2.9%
문래동5가 3
 
2.9%
버드나루로 3
 
2.9%
대륭오피스텔 2
 
1.9%
27 2
 
1.9%
Other values (44) 47
45.6%
2024-04-06T21:22:59.968245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
15.3%
영 21
 
3.7%
등 21
 
3.7%
포 21
 
3.7%
동 19
 
3.3%
시 17
 
3.0%
서 16
 
2.8%
울 16
 
2.8%
특 16
 
2.8%
별 16
 
2.8%
Other values (71) 319
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 350
61.5%
Space Separator 87
 
15.3%
Decimal Number 85
 
14.9%
Close Punctuation 16
 
2.8%
Open Punctuation 16
 
2.8%
Other Punctuation 14
 
2.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 21
 
6.0%
등 21
 
6.0%
포 21
 
6.0%
동 19
 
5.4%
시 17
 
4.9%
서 16
 
4.6%
울 16
 
4.6%
특 16
 
4.6%
별 16
 
4.6%
구 16
 
4.6%
Other values (56) 171
48.9%
Decimal Number
ValueCountFrequency (%)
1 16
18.8%
7 13
15.3%
4 11
12.9%
5 11
12.9%
3 9
10.6%
0 9
10.6%
2 8
9.4%
9 4
 
4.7%
6 2
 
2.4%
8 2
 
2.4%
Space Separator
ValueCountFrequency (%)
87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
61.5%
Common 219
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 21
 
6.0%
등 21
 
6.0%
포 21
 
6.0%
동 19
 
5.4%
시 17
 
4.9%
서 16
 
4.6%
울 16
 
4.6%
특 16
 
4.6%
별 16
 
4.6%
구 16
 
4.6%
Other values (56) 171
48.9%
Common
ValueCountFrequency (%)
87
39.7%
) 16
 
7.3%
1 16
 
7.3%
( 16
 
7.3%
, 14
 
6.4%
7 13
 
5.9%
4 11
 
5.0%
5 11
 
5.0%
3 9
 
4.1%
0 9
 
4.1%
Other values (5) 17
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 350
61.5%
ASCII 219
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
39.7%
) 16
 
7.3%
1 16
 
7.3%
( 16
 
7.3%
, 14
 
6.4%
7 13
 
5.9%
4 11
 
5.0%
5 11
 
5.0%
3 9
 
4.1%
0 9
 
4.1%
Other values (5) 17
 
7.8%
Hangul
ValueCountFrequency (%)
영 21
 
6.0%
등 21
 
6.0%
포 21
 
6.0%
동 19
 
5.4%
시 17
 
4.9%
서 16
 
4.6%
울 16
 
4.6%
특 16
 
4.6%
별 16
 
4.6%
구 16
 
4.6%
Other values (56) 171
48.9%

도로명우편번호
Text

MISSING 

Distinct12
Distinct (%)75.0%
Missing17
Missing (%)51.5%
Memory size396.0 B
2024-04-06T21:23:00.238607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.375
Min length5

Characters and Unicode

Total characters86
Distinct characters10
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

Unique10 ?
Unique (%)62.5%

Sample

1st row07249
2nd row150-814
3rd row150908
4th row07249
5th row07417
ValueCountFrequency (%)
07249 3
18.8%
07285 3
18.8%
150-814 1
 
6.2%
150908 1
 
6.2%
07417 1
 
6.2%
07299 1
 
6.2%
150947 1
 
6.2%
07412 1
 
6.2%
150104 1
 
6.2%
150037 1
 
6.2%
Other values (2) 2
12.5%
2024-04-06T21:23:00.855487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
22.1%
7 15
17.4%
2 10
11.6%
1 10
11.6%
4 9
10.5%
5 8
9.3%
9 7
 
8.1%
8 6
 
7.0%
- 1
 
1.2%
3 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85
98.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
22.4%
7 15
17.6%
2 10
11.8%
1 10
11.8%
4 9
10.6%
5 8
9.4%
9 7
 
8.2%
8 6
 
7.1%
3 1
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
22.1%
7 15
17.4%
2 10
11.6%
1 10
11.6%
4 9
10.5%
5 8
9.3%
9 7
 
8.1%
8 6
 
7.0%
- 1
 
1.2%
3 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
22.1%
7 15
17.4%
2 10
11.6%
1 10
11.6%
4 9
10.5%
5 8
9.3%
9 7
 
8.1%
8 6
 
7.0%
- 1
 
1.2%
3 1
 
1.2%

사업장명
Text

Distinct26
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-04-06T21:23:01.207591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.0909091
Min length4

Characters and Unicode

Total characters201
Distinct characters75
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row창조중기
2nd row삼일공동사업장
3rd row우진중기
4th row우진중기
5th row세보건설
ValueCountFrequency (%)
우진중기 3
 
8.8%
주)스마트산업개발 3
 
8.8%
세보건설 2
 
5.9%
근화건기 2
 
5.9%
진기건설기계 2
 
5.9%
주)우인산업개발 1
 
2.9%
주식회사 1
 
2.9%
창조중기 1
 
2.9%
대두이엔지 1
 
2.9%
마이건설중기 1
 
2.9%
Other values (17) 17
50.0%
2024-04-06T21:23:01.814319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 18
 
9.0%
건 11
 
5.5%
주 11
 
5.5%
중 10
 
5.0%
( 10
 
5.0%
) 10
 
5.0%
개 6
 
3.0%
발 6
 
3.0%
우 5
 
2.5%
설 5
 
2.5%
Other values (65) 109
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
89.6%
Open Punctuation 10
 
5.0%
Close Punctuation 10
 
5.0%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 18
 
10.0%
건 11
 
6.1%
주 11
 
6.1%
중 10
 
5.6%
개 6
 
3.3%
발 6
 
3.3%
우 5
 
2.8%
설 5
 
2.8%
업 5
 
2.8%
진 5
 
2.8%
Other values (62) 98
54.4%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
89.6%
Common 21
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 18
 
10.0%
건 11
 
6.1%
주 11
 
6.1%
중 10
 
5.6%
개 6
 
3.3%
발 6
 
3.3%
우 5
 
2.8%
설 5
 
2.8%
업 5
 
2.8%
진 5
 
2.8%
Other values (62) 98
54.4%
Common
ValueCountFrequency (%)
( 10
47.6%
) 10
47.6%
1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
89.6%
ASCII 21
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 18
 
10.0%
건 11
 
6.1%
주 11
 
6.1%
중 10
 
5.6%
개 6
 
3.3%
발 6
 
3.3%
우 5
 
2.8%
설 5
 
2.8%
업 5
 
2.8%
진 5
 
2.8%
Other values (62) 98
54.4%
ASCII
ValueCountFrequency (%)
( 10
47.6%
) 10
47.6%
1
 
4.8%

최종수정일자
Date

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2007-07-07 13:18:37
Maximum2024-04-04 16:48:17
2024-04-06T21:23:02.081587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:02.880207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
I
19 
U
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowI
3rd rowU
4th rowI
5th rowU

Common Values

ValueCountFrequency (%)
I 19
57.6%
U 14
42.4%

Length

2024-04-06T21:23:03.237976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:03.505645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 19
57.6%
u 14
42.4%

데이터갱신일자
Date

Distinct14
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T21:23:03.722826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:04.025192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

좌표정보(X)
Real number (ℝ)

Distinct19
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191371.4
Minimum189549.85
Maximum194592.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T21:23:04.272001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile189982.76
Q1190870.82
median191094.02
Q3192081.26
95-th percentile192228.73
Maximum194592.28
Range5042.4294
Interquartile range (IQR)1210.4368

Descriptive statistics

Standard deviation1027.5419
Coefficient of variation (CV)0.0053693597
Kurtosis1.5553236
Mean191371.4
Median Absolute Deviation (MAD)986.58401
Skewness0.54367889
Sum6315256.2
Variance1055842.3
MonotonicityNot monotonic
2024-04-06T21:23:04.500864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
191094.016051179 6
18.2%
190023.48828661 4
12.1%
192215.648586084 4
12.1%
192081.258332212 2
 
6.1%
191979.46040147 2
 
6.1%
192080.600057217 2
 
6.1%
192094.006876261 1
 
3.0%
191270.785220809 1
 
3.0%
192248.346145094 1
 
3.0%
192027.62098867 1
 
3.0%
Other values (9) 9
27.3%
ValueCountFrequency (%)
189549.847307536 1
 
3.0%
189921.671894763 1
 
3.0%
190023.48828661 4
12.1%
190107.95828772 1
 
3.0%
190691.303227228 1
 
3.0%
190870.8215611 1
 
3.0%
190996.357288859 1
 
3.0%
191082.569137819 1
 
3.0%
191094.016051179 6
18.2%
191270.785220809 1
 
3.0%
ValueCountFrequency (%)
194592.276750438 1
 
3.0%
192248.346145094 1
 
3.0%
192215.648586084 4
12.1%
192094.006876261 1
 
3.0%
192081.258332212 2
6.1%
192080.600057217 2
6.1%
192027.62098867 1
 
3.0%
191999.3981953 1
 
3.0%
191979.46040147 2
6.1%
191270.785220809 1
 
3.0%

좌표정보(Y)
Real number (ℝ)

Distinct19
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean445863.15
Minimum443560.03
Maximum448231.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-06T21:23:04.748077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443560.03
5-th percentile443570.44
Q1445841.38
median446626.89
Q3446740.3
95-th percentile446968.44
Maximum448231.31
Range4671.2758
Interquartile range (IQR)898.92365

Descriptive statistics

Standard deviation1360.0841
Coefficient of variation (CV)0.003050452
Kurtosis-0.56228962
Mean445863.15
Median Absolute Deviation (MAD)424.57501
Skewness-0.8695955
Sum14713484
Variance1849828.9
MonotonicityNot monotonic
2024-04-06T21:23:05.096511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
443570.443536531 6
18.2%
446044.579840782 4
12.1%
446687.339692779 4
12.1%
446666.765547843 2
 
6.1%
446740.301257223 2
 
6.1%
446761.824144739 2
 
6.1%
446736.958364328 1
 
3.0%
445905.234717171 1
 
3.0%
446626.894515805 1
 
3.0%
446764.152565179 1
 
3.0%
Other values (9) 9
27.3%
ValueCountFrequency (%)
443560.031672374 1
 
3.0%
443570.443536531 6
18.2%
443994.299099236 1
 
3.0%
445841.377603245 1
 
3.0%
445905.234717171 1
 
3.0%
445990.538307199 1
 
3.0%
446044.579840782 4
12.1%
446268.481210069 1
 
3.0%
446626.894515805 1
 
3.0%
446666.765547843 2
 
6.1%
ValueCountFrequency (%)
448231.307431202 1
 
3.0%
447051.469526227 1
 
3.0%
446913.092679857 1
 
3.0%
446911.977891643 1
 
3.0%
446764.152565179 1
 
3.0%
446761.824144739 2
6.1%
446740.301257223 2
6.1%
446736.958364328 1
 
3.0%
446687.339692779 4
12.1%
446666.765547843 2
6.1%

환경업무구분명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
건설폐기물처리업사업계획(허가)신청
21 
<NA>
12 

Length

Max length18
Median length18
Mean length12.909091
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row건설폐기물처리업사업계획(허가)신청
3rd row<NA>
4th row건설폐기물처리업사업계획(허가)신청
5th row<NA>

Common Values

ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 21
63.6%
<NA> 12
36.4%

Length

2024-04-06T21:23:05.431104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:05.628382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 21
63.6%
na 12
36.4%

폐기물처리업구분명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
수집운반업(건설폐기물)
19 
<NA>
14 

Length

Max length12
Median length12
Mean length8.6060606
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row수집운반업(건설폐기물)
3rd row<NA>
4th row수집운반업(건설폐기물)
5th row<NA>

Common Values

ValueCountFrequency (%)
수집운반업(건설폐기물) 19
57.6%
<NA> 14
42.4%

Length

2024-04-06T21:23:05.873368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:06.149221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업(건설폐기물 19
57.6%
na 14
42.4%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

폐기물구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2024-04-06T21:23:06.400335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row건설폐기물
ValueCountFrequency (%)
건설폐기물 1
100.0%
2024-04-06T21:23:06.852530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
건 1
20.0%
설 1
20.0%
폐 1
20.0%
기 1
20.0%
물 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 1
20.0%
설 1
20.0%
폐 1
20.0%
기 1
20.0%
물 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
건 1
20.0%
설 1
20.0%
폐 1
20.0%
기 1
20.0%
물 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
건 1
20.0%
설 1
20.0%
폐 1
20.0%
기 1
20.0%
물 1
20.0%

허용보관량
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
22 
0
11 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 22
66.7%
0 11
33.3%

Length

2024-04-06T21:23:07.086076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:07.261014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
66.7%
0 11
33.3%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
031800003180000922001000012023-04-21<NA>3폐업2폐업2023-04-21<NA><NA><NA>2631-0451<NA>150-032서울특별시 영등포구 영등포동2가 94-24 카보드동우빌딩 405호서울특별시 영등포구 버드나루로7길 7, 405호 (영등포동2가)07249창조중기2023-04-21 14:43:11U2022-12-03 22:03:00.0<NA>191979.460401446740.301257<NA><NA><NA><NA><NA><NA>
1318000031800009220010000220130328<NA>3폐업2폐업20130328<NA><NA><NA>26331638<NA>150102서울특별시 영등포구 양평동2가 38-1번지 삼성아파트상사302호<NA><NA>삼일공동사업장2013-03-28 09:01:52I2018-08-31 23:59:59.0<NA>189549.847308446913.09268건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
231800003180000922002000012002-03-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-834-9091<NA>150-814서울특별시 영등포구 대림동 709-5서울특별시 영등포구 대림로 149 (대림동)150-814우진중기2024-04-04 16:48:17U2023-12-04 00:06:00.0<NA>191094.016051443570.443537<NA><NA><NA><NA><NA><NA>
3318000031800009220020000220020323<NA>1영업/정상BBBB영업<NA><NA><NA><NA>8349091<NA>150070서울특별시 영등포구 대림동 709-5번지<NA><NA>우진중기2007-11-09 10:20:38I2018-08-31 23:59:59.0<NA>191094.016051443570.443537건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
431800003180000922004000022004-10-06<NA>1영업/정상BBBB영업<NA><NA><NA><NA>26310451<NA>150-032서울특별시 영등포구 영등포동2가 94-29<NA><NA>세보건설2023-10-25 08:28:25U2022-10-30 22:07:00.0<NA>192215.648586446687.339693<NA><NA><NA><NA><NA><NA>
5318000031800009220040000320120727<NA>3폐업2폐업20120727<NA><NA><NA>2633-6600<NA>150901서울특별시 영등포구 영등포동2가 94-119번지 리버타워빌딩 504호<NA><NA>성심중기2012-07-27 17:37:07I2018-08-31 23:59:59.0<NA>192080.600057446761.824145건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
6318000031800009220040000420040723<NA>3폐업2폐업20090421<NA><NA><NA><NA><NA>150032서울특별시 영등포구 영등포동2가 94-118번지<NA><NA>봉래건기2009-04-21 15:29:41I2018-08-31 23:59:59.0<NA>192094.006876446736.958364건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
7318000031800009220060000120060224<NA>1영업/정상BBBB영업<NA><NA><NA><NA>8349091<NA>150070서울특별시 영등포구 대림동 709-5<NA><NA>근화건기2021-12-08 17:58:42U2021-12-10 02:40:00.0<NA>191094.016051443570.443537건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
8318000031800009220060000220060317<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>150072서울특별시 영등포구 대림동 709-5번지서울특별시 영등포구 대림로 149 (대림동)150908우진중기2011-10-30 16:39:23I2018-08-31 23:59:59.0<NA>191094.016051443570.443537건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
9318000031800009220060000320060317<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>150070서울특별시 영등포구 대림동 709-5<NA><NA>근화건기2021-12-08 17:59:13U2021-12-10 02:40:00.0<NA>191094.016051443570.443537건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
2331800003180000922011000042011-01-20<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-868-7000<NA><NA>서울특별시 영등포구 대림동 742-1서울특별시 영등포구 대림로35가길 8, 2층 (대림동)07412대림환경개발2023-12-13 09:13:18U2022-11-01 23:05:00.0<NA>190870.821561443994.299099<NA><NA><NA><NA><NA><NA>
2431800003180000922011000052011-01-04<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2608-8774<NA>158-097서울특별시 영등포구 문래동5가 2 대륭오피스텔서울특별시 영등포구 선유로 27, 대륭오피스텔 11층 1103호 (문래동5가)07285으뜸환경(주)2024-03-21 13:22:26U2023-12-02 22:03:00.0<NA>190023.488287446044.579841<NA><NA><NA><NA><NA><NA>
25318000031800009220120000120140129<NA>3폐업2폐업20140129<NA><NA><NA>02-2631-0100<NA>150958서울특별시 영등포구 문래동5가 2번지 대륭오피스텔 415호<NA><NA>(주)스마트산업개발2014-01-29 09:23:56I2018-08-31 23:59:59.0<NA>190023.488287446044.579841건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
26318000031800009220120000220120803<NA>3폐업2폐업20120803<NA><NA><NA>02-831-7979<NA>150904서울특별시 영등포구 대림동 709-6번지<NA><NA>금영환경개발(주)2012-08-03 17:59:29I2018-08-31 23:59:59.0<NA>191082.569138443560.031672건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
27318000031800009220150000120150324<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>150104서울특별시 영등포구 양평동4가 79-2번지서울특별시 영등포구 선유로49길 17 (양평동4가)150104(주)지엘엠2015-03-24 14:50:50I2018-08-31 23:59:59.0<NA>190691.303227448231.307431건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
28318000031800009220150000220150414<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>150037서울특별시 영등포구 영등포동7가 94-322번지서울특별시 영등포구 버드나루로 66, 304호 (영등포동7가, 대일빌딩)150037(주)한국포도중기2015-04-14 09:24:35I2018-08-31 23:59:59.0<NA>191999.398195446911.977892건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
2931800003180000922017000012017-04-06<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2631-0100<NA><NA>서울특별시 영등포구 문래동5가 10 하우스디 비즈 417호서울특별시 영등포구 선유로3길 10, 하우스디 비즈 4층 417호 (문래동5가)07285(주)스마트산업개발2024-03-22 16:24:48U2023-12-02 22:04:00.0<NA>189921.671895445990.538307<NA><NA><NA><NA><NA><NA>
30318000031800009220220000120220103<NA>1영업/정상BBBB영업<NA><NA><NA><NA>2069-2978<NA><NA>서울특별시 영등포구 문래동5가 2 대륭오피스텔서울특별시 영등포구 선유로 27, 대륭오피스텔 515호 (문래동5가)07285성원토건(주)2022-02-21 09:52:59U2022-02-23 02:40:00.0<NA>190023.488287446044.579841건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
3131800003180000922022000022022-11-01<NA>1영업/정상BBBB영업<NA><NA><NA><NA>028877520<NA><NA>서울특별시 영등포구 영등포동2가 94-119 리버타워오피스텔서울특별시 영등포구 버드나루로 50, 리버타워오피스텔 501호 (영등포동2가)07248마이건설중기2024-02-29 09:54:13U2023-12-03 00:02:00.0<NA>192080.600057446761.824145<NA><NA><NA><NA><NA><NA>
32318000031800009220220000320221115<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동3가 15-1 월드메르디앙비즈센터서울특별시 영등포구 양산로 53, 월드메르디앙비즈센터 (양평동3가)07271주식회사 서영토건2022-11-15 13:52:57I2021-10-31 23:07:00.0<NA>190107.958288447051.469526<NA><NA><NA><NA><NA><NA>