Overview

Dataset statistics

Number of variables31
Number of observations24
Missing cells252
Missing cells (%)33.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory270.5 B

Variable types

Categorical12
Numeric4
DateTime3
Unsupported8
Text4

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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-19323/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 has constant value ""Constant
폐업일자 is highly imbalanced (57.6%)Imbalance
허용보관량 is highly imbalanced (75.0%)Imbalance
인허가취소일자 has 24 (100.0%) missing valuesMissing
휴업시작일자 has 23 (95.8%) missing valuesMissing
휴업종료일자 has 24 (100.0%) missing valuesMissing
재개업일자 has 24 (100.0%) missing valuesMissing
전화번호 has 17 (70.8%) missing valuesMissing
소재지면적 has 24 (100.0%) missing valuesMissing
지번주소 has 2 (8.3%) missing valuesMissing
도로명주소 has 1 (4.2%) missing valuesMissing
도로명우편번호 has 15 (62.5%) missing valuesMissing
업태구분명 has 24 (100.0%) missing valuesMissing
좌표정보(X) has 1 (4.2%) missing valuesMissing
좌표정보(Y) has 1 (4.2%) missing valuesMissing
폐기물처리업별처리구분명 has 24 (100.0%) missing valuesMissing
폐기물구분명 has 24 (100.0%) missing valuesMissing
허용보관량내용 has 24 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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
폐기물구분명 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 10:37:24.379010
Analysis finished2024-04-06 10:37:25.081916
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
3210000
24 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 24
100.0%

Length

2024-04-06T19:37:25.238904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:25.383226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 24
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2100009 × 1017
Minimum3.2100009 × 1017
Maximum3.2100009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T19:37:25.530550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2100009 × 1017
5-th percentile3.2100009 × 1017
Q13.2100009 × 1017
median3.2100009 × 1017
Q33.2100009 × 1017
95-th percentile3.2100009 × 1017
Maximum3.2100009 × 1017
Range2100000
Interquartile range (IQR)425024

Descriptive statistics

Standard deviation546329.6
Coefficient of variation (CV)1.7019609 × 10-12
Kurtosis0.46936673
Mean3.2100009 × 1017
Median Absolute Deviation (MAD)100000
Skewness1.0911105
Sum7.7040022 × 1018
Variance2.9847604 × 1011
MonotonicityStrictly increasing
2024-04-06T19:37:25.768924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
321000092200100001 1
 
4.2%
321000092200700012 1
 
4.2%
321000092202200001 1
 
4.2%
321000092202000001 1
 
4.2%
321000092201900001 1
 
4.2%
321000092201700001 1
 
4.2%
321000092201500002 1
 
4.2%
321000092201200001 1
 
4.2%
321000092201100001 1
 
4.2%
321000092200800001 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
321000092200100001 1
4.2%
321000092200200001 1
4.2%
321000092200600001 1
4.2%
321000092200600002 1
4.2%
321000092200600003 1
4.2%
321000092200700001 1
4.2%
321000092200700002 1
4.2%
321000092200700003 1
4.2%
321000092200700004 1
4.2%
321000092200700006 1
4.2%
ValueCountFrequency (%)
321000092202200001 1
4.2%
321000092202000001 1
4.2%
321000092201900001 1
4.2%
321000092201700001 1
4.2%
321000092201500002 1
4.2%
321000092201200001 1
4.2%
321000092201100001 1
4.2%
321000092200800001 1
4.2%
321000092200700016 1
4.2%
321000092200700014 1
4.2%

인허가일자
Date

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2001-08-02 00:00:00
Maximum2023-02-08 00:00:00
2024-04-06T19:37:26.016017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:37:26.262945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
1
19 
3
4 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 19
79.2%
3 4
 
16.7%
2 1
 
4.2%

Length

2024-04-06T19:37:26.523870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:26.689767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19
79.2%
3 4
 
16.7%
2 1
 
4.2%

영업상태명
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
영업/정상
19 
폐업
4 
휴업
 
1

Length

Max length5
Median length5
Mean length4.375
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 19
79.2%
폐업 4
 
16.7%
휴업 1
 
4.2%

Length

2024-04-06T19:37:26.880672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:27.102092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 19
79.2%
폐업 4
 
16.7%
휴업 1
 
4.2%

상세영업상태코드
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
BBBB
19 
2
4 
1
 
1

Length

Max length4
Median length4
Mean length3.375
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 19
79.2%
2 4
 
16.7%
1 1
 
4.2%

Length

2024-04-06T19:37:27.346521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:27.547339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 19
79.2%
2 4
 
16.7%
1 1
 
4.2%

상세영업상태명
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
영업
19 
폐업
4 
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업 19
79.2%
폐업 4
 
16.7%
휴업 1
 
4.2%

Length

2024-04-06T19:37:27.754810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:27.927921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 19
79.2%
폐업 4
 
16.7%
휴업 1
 
4.2%

폐업일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
20 
20080131
 
1
20080725
 
1
20090713
 
1
20160415
 
1

Length

Max length8
Median length4
Mean length4.6666667
Min length4

Unique

Unique4 ?
Unique (%)16.7%

Sample

1st row<NA>
2nd row20080131
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
83.3%
20080131 1
 
4.2%
20080725 1
 
4.2%
20090713 1
 
4.2%
20160415 1
 
4.2%

Length

2024-04-06T19:37:28.146571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:28.368408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
83.3%
20080131 1
 
4.2%
20080725 1
 
4.2%
20090713 1
 
4.2%
20160415 1
 
4.2%

휴업시작일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing23
Missing (%)95.8%
Memory size324.0 B
Minimum2023-02-07 00:00:00
Maximum2023-02-07 00:00:00
2024-04-06T19:37:28.530893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:37:28.697875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

전화번호
Text

MISSING 

Distinct5
Distinct (%)71.4%
Missing17
Missing (%)70.8%
Memory size324.0 B
2024-04-06T19:37:28.959913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.142857
Min length9

Characters and Unicode

Total characters78
Distinct characters9
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

Unique3 ?
Unique (%)42.9%

Sample

1st row02-5235-060
2nd row02-525-4466
3rd row02-525-4466
4th row025611300
5th row031-422-6624
ValueCountFrequency (%)
02-525-4466 2
28.6%
031-422-6624 2
28.6%
02-5235-060 1
14.3%
025611300 1
14.3%
080-001-8484 1
14.3%
2024-04-06T19:37:29.444478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.9%
2 13
16.7%
- 12
15.4%
4 10
12.8%
6 10
12.8%
5 7
9.0%
1 5
 
6.4%
3 4
 
5.1%
8 3
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
84.6%
Dash Punctuation 12
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
21.2%
2 13
19.7%
4 10
15.2%
6 10
15.2%
5 7
10.6%
1 5
 
7.6%
3 4
 
6.1%
8 3
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
17.9%
2 13
16.7%
- 12
15.4%
4 10
12.8%
6 10
12.8%
5 7
9.0%
1 5
 
6.4%
3 4
 
5.1%
8 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
17.9%
2 13
16.7%
- 12
15.4%
4 10
12.8%
6 10
12.8%
5 7
9.0%
1 5
 
6.4%
3 4
 
5.1%
8 3
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

소재지우편번호
Categorical

Distinct5
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
137070
8 
<NA>
7 
137060
4 
137130
4 
137062
1 

Length

Max length6
Median length6
Mean length5.4166667
Min length4

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row<NA>
2nd row137070
3rd row137060
4th row137070
5th row137060

Common Values

ValueCountFrequency (%)
137070 8
33.3%
<NA> 7
29.2%
137060 4
16.7%
137130 4
16.7%
137062 1
 
4.2%

Length

2024-04-06T19:37:29.702782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:29.950465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
137070 8
33.3%
na 7
29.2%
137060 4
16.7%
137130 4
16.7%
137062 1
 
4.2%

지번주소
Text

MISSING 

Distinct14
Distinct (%)63.6%
Missing2
Missing (%)8.3%
Memory size324.0 B
2024-04-06T19:37:30.211799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length25.272727
Min length20

Characters and Unicode

Total characters556
Distinct characters48
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

Unique9 ?
Unique (%)40.9%

Sample

1st row서울특별시 서초구 서초동 1588-7 석탑오피스텔
2nd row서울특별시 서초구 서초동 1603-69번지
3rd row서울특별시 서초구 방배동 480-3번지
4th row서울특별시 서초구 서초동 1592-10번지 한진오피스텔 808호
5th row서울특별시 서초구 방배동 480-3번지
ValueCountFrequency (%)
서울특별시 22
21.4%
서초구 22
21.4%
서초동 8
 
7.8%
방배동 6
 
5.8%
양재동 6
 
5.8%
480-3번지 4
 
3.9%
1592-10번지 4
 
3.9%
363-2번지 3
 
2.9%
한진오피스텔 3
 
2.9%
우면동 2
 
1.9%
Other values (18) 23
22.3%
2024-04-06T19:37:31.107109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
17.3%
서 55
 
9.9%
초 31
 
5.6%
울 24
 
4.3%
동 22
 
4.0%
특 22
 
4.0%
별 22
 
4.0%
시 22
 
4.0%
구 22
 
4.0%
- 20
 
3.6%
Other values (38) 220
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
59.5%
Decimal Number 109
 
19.6%
Space Separator 96
 
17.3%
Dash Punctuation 20
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 55
16.6%
초 31
 
9.4%
울 24
 
7.3%
동 22
 
6.6%
특 22
 
6.6%
별 22
 
6.6%
시 22
 
6.6%
구 22
 
6.6%
번 15
 
4.5%
지 15
 
4.5%
Other values (26) 81
24.5%
Decimal Number
ValueCountFrequency (%)
1 18
16.5%
3 16
14.7%
8 15
13.8%
0 13
11.9%
2 10
9.2%
7 9
8.3%
9 8
7.3%
5 7
 
6.4%
4 7
 
6.4%
6 6
 
5.5%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
59.5%
Common 225
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 55
16.6%
초 31
 
9.4%
울 24
 
7.3%
동 22
 
6.6%
특 22
 
6.6%
별 22
 
6.6%
시 22
 
6.6%
구 22
 
6.6%
번 15
 
4.5%
지 15
 
4.5%
Other values (26) 81
24.5%
Common
ValueCountFrequency (%)
96
42.7%
- 20
 
8.9%
1 18
 
8.0%
3 16
 
7.1%
8 15
 
6.7%
0 13
 
5.8%
2 10
 
4.4%
7 9
 
4.0%
9 8
 
3.6%
5 7
 
3.1%
Other values (2) 13
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
59.5%
ASCII 225
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
42.7%
- 20
 
8.9%
1 18
 
8.0%
3 16
 
7.1%
8 15
 
6.7%
0 13
 
5.8%
2 10
 
4.4%
7 9
 
4.0%
9 8
 
3.6%
5 7
 
3.1%
Other values (2) 13
 
5.8%
Hangul
ValueCountFrequency (%)
서 55
16.6%
초 31
 
9.4%
울 24
 
7.3%
동 22
 
6.6%
특 22
 
6.6%
별 22
 
6.6%
시 22
 
6.6%
구 22
 
6.6%
번 15
 
4.5%
지 15
 
4.5%
Other values (26) 81
24.5%

도로명주소
Text

MISSING 

Distinct15
Distinct (%)65.2%
Missing1
Missing (%)4.2%
Memory size324.0 B
2024-04-06T19:37:31.843086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length32.695652
Min length24

Characters and Unicode

Total characters752
Distinct characters69
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

Unique10 ?
Unique (%)43.5%

Sample

1st row서울특별시 서초구 효령로53길 18, 석탑오피스텔 509호 (서초동)
2nd row서울특별시 서초구 효령로 307 (서초동)
3rd row서울특별시 서초구 효령로2길 25 (방배동)
4th row서울특별시 서초구 반포대로18길 8, 808호 (서초동,한진오피스텔)
5th row서울특별시 서초구 효령로2길 25 (방배동)
ValueCountFrequency (%)
서울특별시 23
 
16.3%
서초구 23
 
16.3%
방배동 8
 
5.7%
양재동 5
 
3.5%
8 4
 
2.8%
반포대로18길 4
 
2.8%
서초동 4
 
2.8%
25 4
 
2.8%
효령로2길 4
 
2.8%
92 3
 
2.1%
Other values (43) 59
41.8%
2024-04-06T19:37:32.697523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
17.6%
서 58
 
7.7%
초 33
 
4.4%
2 27
 
3.6%
울 25
 
3.3%
시 23
 
3.1%
특 23
 
3.1%
별 23
 
3.1%
동 23
 
3.1%
( 23
 
3.1%
Other values (59) 362
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
58.5%
Space Separator 132
 
17.6%
Decimal Number 115
 
15.3%
Open Punctuation 23
 
3.1%
Close Punctuation 23
 
3.1%
Other Punctuation 18
 
2.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 58
 
13.2%
초 33
 
7.5%
울 25
 
5.7%
시 23
 
5.2%
특 23
 
5.2%
별 23
 
5.2%
동 23
 
5.2%
로 23
 
5.2%
구 23
 
5.2%
길 21
 
4.8%
Other values (44) 165
37.5%
Decimal Number
ValueCountFrequency (%)
2 27
23.5%
1 22
19.1%
8 16
13.9%
0 12
10.4%
5 9
 
7.8%
6 8
 
7.0%
3 8
 
7.0%
4 6
 
5.2%
9 5
 
4.3%
7 2
 
1.7%
Space Separator
ValueCountFrequency (%)
132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
58.5%
Common 312
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 58
 
13.2%
초 33
 
7.5%
울 25
 
5.7%
시 23
 
5.2%
특 23
 
5.2%
별 23
 
5.2%
동 23
 
5.2%
로 23
 
5.2%
구 23
 
5.2%
길 21
 
4.8%
Other values (44) 165
37.5%
Common
ValueCountFrequency (%)
132
42.3%
2 27
 
8.7%
( 23
 
7.4%
) 23
 
7.4%
1 22
 
7.1%
, 18
 
5.8%
8 16
 
5.1%
0 12
 
3.8%
5 9
 
2.9%
6 8
 
2.6%
Other values (5) 22
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
58.5%
ASCII 312
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
42.3%
2 27
 
8.7%
( 23
 
7.4%
) 23
 
7.4%
1 22
 
7.1%
, 18
 
5.8%
8 16
 
5.1%
0 12
 
3.8%
5 9
 
2.9%
6 8
 
2.6%
Other values (5) 22
 
7.1%
Hangul
ValueCountFrequency (%)
서 58
 
13.2%
초 33
 
7.5%
울 25
 
5.7%
시 23
 
5.2%
특 23
 
5.2%
별 23
 
5.2%
동 23
 
5.2%
로 23
 
5.2%
구 23
 
5.2%
길 21
 
4.8%
Other values (44) 165
37.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)77.8%
Missing15
Missing (%)62.5%
Infinite0
Infinite (%)0.0%
Mean21288
Minimum6652
Maximum137837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T19:37:32.963276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6652
5-th percentile6652.8
Q16677
median6763
Q36772
95-th percentile85411
Maximum137837
Range131185
Interquartile range (IQR)95

Descriptive statistics

Standard deviation43705.904
Coefficient of variation (CV)2.053077
Kurtosis8.9999659
Mean21288
Median Absolute Deviation (MAD)61
Skewness2.9999923
Sum191592
Variance1.910206 × 109
MonotonicityNot monotonic
2024-04-06T19:37:33.162864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6772 2
 
8.3%
6763 2
 
8.3%
6654 1
 
4.2%
137837 1
 
4.2%
6702 1
 
4.2%
6652 1
 
4.2%
6677 1
 
4.2%
(Missing) 15
62.5%
ValueCountFrequency (%)
6652 1
4.2%
6654 1
4.2%
6677 1
4.2%
6702 1
4.2%
6763 2
8.3%
6772 2
8.3%
137837 1
4.2%
ValueCountFrequency (%)
137837 1
4.2%
6772 2
8.3%
6763 2
8.3%
6702 1
4.2%
6677 1
4.2%
6654 1
4.2%
6652 1
4.2%

사업장명
Text

Distinct15
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-06T19:37:33.450157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.3333333
Min length4

Characters and Unicode

Total characters152
Distinct characters52
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

Unique10 ?
Unique (%)41.7%

Sample

1st row파크중기
2nd row신한건기
3rd row태광골재산업-주
4th row명천건기
5th row태광골재산업(주)
ValueCountFrequency (%)
명천건기 6
23.1%
태광골재산업-주 2
 
7.7%
태광골재산업(주 2
 
7.7%
주)용아개발 2
 
7.7%
주)터원 2
 
7.7%
주식회사 2
 
7.7%
파크중기 1
 
3.8%
신한건기 1
 
3.8%
신진건기 1
 
3.8%
용아개발 1
 
3.8%
Other values (6) 6
23.1%
2024-04-06T19:37:34.046782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 14
 
9.2%
( 10
 
6.6%
) 10
 
6.6%
기 9
 
5.9%
건 8
 
5.3%
천 6
 
3.9%
명 6
 
3.9%
산 5
 
3.3%
재 4
 
2.6%
광 4
 
2.6%
Other values (42) 76
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128
84.2%
Open Punctuation 10
 
6.6%
Close Punctuation 10
 
6.6%
Space Separator 2
 
1.3%
Dash Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
10.9%
기 9
 
7.0%
건 8
 
6.2%
천 6
 
4.7%
명 6
 
4.7%
산 5
 
3.9%
재 4
 
3.1%
광 4
 
3.1%
태 4
 
3.1%
아 4
 
3.1%
Other values (38) 64
50.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128
84.2%
Common 24
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
10.9%
기 9
 
7.0%
건 8
 
6.2%
천 6
 
4.7%
명 6
 
4.7%
산 5
 
3.9%
재 4
 
3.1%
광 4
 
3.1%
태 4
 
3.1%
아 4
 
3.1%
Other values (38) 64
50.0%
Common
ValueCountFrequency (%)
( 10
41.7%
) 10
41.7%
2
 
8.3%
- 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128
84.2%
ASCII 24
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 14
 
10.9%
기 9
 
7.0%
건 8
 
6.2%
천 6
 
4.7%
명 6
 
4.7%
산 5
 
3.9%
재 4
 
3.1%
광 4
 
3.1%
태 4
 
3.1%
아 4
 
3.1%
Other values (38) 64
50.0%
ASCII
ValueCountFrequency (%)
( 10
41.7%
) 10
41.7%
2
 
8.3%
- 2
 
8.3%

최종수정일자
Date

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2007-07-14 11:58:12
Maximum2023-11-14 17:26:29
2024-04-06T19:37:34.390013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:37:34.732237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

데이터갱신구분
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
I
18 
U
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 18
75.0%
U 6
 
25.0%

Length

2024-04-06T19:37:35.043027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:35.190261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 18
75.0%
u 6
 
25.0%

데이터갱신일자
Categorical

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2018-08-31 23:59:59.0
16 
2021-12-04 23:03:00.0
2 
2022-10-31 23:06:00.0
 
1
2022-10-31 23:05:00.0
 
1
2022-12-01 23:00:00.0
 
1
Other values (3)
3 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique6 ?
Unique (%)25.0%

Sample

1st row2022-10-31 23:06:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 16
66.7%
2021-12-04 23:03:00.0 2
 
8.3%
2022-10-31 23:06:00.0 1
 
4.2%
2022-10-31 23:05:00.0 1
 
4.2%
2022-12-01 23:00:00.0 1
 
4.2%
2022-12-06 23:06:00.0 1
 
4.2%
2020-12-22 00:23:05.0 1
 
4.2%
2021-12-06 00:09:00.0 1
 
4.2%

Length

2024-04-06T19:37:35.336318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:35.508081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 16
33.3%
23:59:59.0 16
33.3%
2021-12-04 2
 
4.2%
23:03:00.0 2
 
4.2%
2022-10-31 2
 
4.2%
23:06:00.0 2
 
4.2%
23:05:00.0 1
 
2.1%
2022-12-01 1
 
2.1%
23:00:00.0 1
 
2.1%
2022-12-06 1
 
2.1%
Other values (4) 4
 
8.3%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)56.5%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean201118.94
Minimum198433.51
Maximum204045.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T19:37:35.720661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198433.51
5-th percentile198846.47
Q1199187.94
median201070.37
Q3202245.56
95-th percentile204045.31
Maximum204045.31
Range5611.7965
Interquartile range (IQR)3057.6212

Descriptive statistics

Standard deviation1815.0926
Coefficient of variation (CV)0.0090249707
Kurtosis-1.0374986
Mean201118.94
Median Absolute Deviation (MAD)1796.9232
Skewness0.10850435
Sum4625735.7
Variance3294561.1
MonotonicityNot monotonic
2024-04-06T19:37:35.956306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
198846.470172966 4
16.7%
200934.988115227 4
16.7%
204045.305024541 3
12.5%
203059.646700644 2
8.3%
202245.563563211 2
8.3%
201162.55241589 1
 
4.2%
201505.867572503 1
 
4.2%
201153.543582527 1
 
4.2%
199273.451150404 1
 
4.2%
202161.81616549 1
 
4.2%
Other values (3) 3
12.5%
ValueCountFrequency (%)
198433.508570776 1
 
4.2%
198846.470172966 4
16.7%
199102.43349418 1
 
4.2%
199273.451150404 1
 
4.2%
200934.988115227 4
16.7%
201070.374374053 1
 
4.2%
201153.543582527 1
 
4.2%
201162.55241589 1
 
4.2%
201505.867572503 1
 
4.2%
202161.81616549 1
 
4.2%
ValueCountFrequency (%)
204045.305024541 3
12.5%
203059.646700644 2
8.3%
202245.563563211 2
8.3%
202161.81616549 1
 
4.2%
201505.867572503 1
 
4.2%
201162.55241589 1
 
4.2%
201153.543582527 1
 
4.2%
201070.374374053 1
 
4.2%
200934.988115227 4
16.7%
199273.451150404 1
 
4.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)56.5%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean441755.75
Minimum439960.53
Maximum442981.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T19:37:36.185997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439960.53
5-th percentile440037.55
Q1440812.28
median441785.54
Q3442673.44
95-th percentile442706.53
Maximum442981.23
Range3020.6995
Interquartile range (IQR)1861.1584

Descriptive statistics

Standard deviation955.06208
Coefficient of variation (CV)0.0021619686
Kurtosis-1.0393048
Mean441755.75
Median Absolute Deviation (MAD)918.05582
Skewness-0.47792364
Sum10160382
Variance912143.57
MonotonicityNot monotonic
2024-04-06T19:37:36.380372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
441558.751745641 4
16.7%
442703.597815233 4
16.7%
440730.746663947 3
12.5%
439960.533113874 2
8.3%
440812.28085619 2
8.3%
442589.558473708 1
 
4.2%
442604.471763741 1
 
4.2%
442643.280772 1
 
4.2%
442016.470294138 1
 
4.2%
441785.541995966 1
 
4.2%
Other values (3) 3
12.5%
ValueCountFrequency (%)
439960.533113874 2
8.3%
440730.746663947 3
12.5%
440812.28085619 2
8.3%
441558.751745641 4
16.7%
441785.541995966 1
 
4.2%
442016.470294138 1
 
4.2%
442267.561719178 1
 
4.2%
442589.558473708 1
 
4.2%
442604.471763741 1
 
4.2%
442643.280772 1
 
4.2%
ValueCountFrequency (%)
442981.232614759 1
 
4.2%
442706.851934959 1
 
4.2%
442703.597815233 4
16.7%
442643.280772 1
 
4.2%
442604.471763741 1
 
4.2%
442589.558473708 1
 
4.2%
442267.561719178 1
 
4.2%
442016.470294138 1
 
4.2%
441785.541995966 1
 
4.2%
441558.751745641 4
16.7%

환경업무구분명
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
건설폐기물처리업사업계획(허가)신청
17 
<NA>
7 

Length

Max length18
Median length18
Mean length13.916667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 17
70.8%
<NA> 7
29.2%

Length

2024-04-06T19:37:36.959780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:37.161402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 17
70.8%
na 7
29.2%

폐기물처리업구분명
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
17 
수집운반업(건설폐기물)
7 

Length

Max length12
Median length4
Mean length6.3333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
70.8%
수집운반업(건설폐기물) 7
29.2%

Length

2024-04-06T19:37:37.376276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:37.605925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
70.8%
수집운반업(건설폐기물 7
29.2%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

폐기물구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

허용보관량
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
0
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
0 1
 
4.2%

Length

2024-04-06T19:37:37.801694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:37:37.972947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
0 1
 
4.2%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)100.0%
Memory size348.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
032100003210000922001000012001-08-02<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-5235-060<NA><NA>서울특별시 서초구 서초동 1588-7 석탑오피스텔서울특별시 서초구 효령로53길 18, 석탑오피스텔 509호 (서초동)6654파크중기2023-11-14 17:26:29U2022-10-31 23:06:00.0<NA>201162.552416442589.558474<NA><NA><NA><NA><NA><NA>
1321000032100009220020000120020427<NA>3폐업2폐업20080131<NA><NA><NA><NA><NA>137070서울특별시 서초구 서초동 1603-69번지서울특별시 서초구 효령로 307 (서초동)<NA>신한건기2008-02-01 15:30:53I2018-08-31 23:59:59.0<NA>201505.867573442604.471764건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
2321000032100009220060000120060418<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137060서울특별시 서초구 방배동 480-3번지서울특별시 서초구 효령로2길 25 (방배동)<NA>태광골재산업-주2008-09-18 14:31:54I2018-08-31 23:59:59.0<NA>198846.470173441558.751746건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
3321000032100009220060000220060710<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137070서울특별시 서초구 서초동 1592-10번지 한진오피스텔 808호서울특별시 서초구 반포대로18길 8, 808호 (서초동,한진오피스텔)<NA>명천건기2012-11-27 14:26:28I2018-08-31 23:59:59.0<NA>200934.988115442703.597815건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
4321000032100009220060000320061031<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137060서울특별시 서초구 방배동 480-3번지서울특별시 서초구 효령로2길 25 (방배동)<NA>태광골재산업(주)2007-07-14 11:58:12I2018-08-31 23:59:59.0<NA>198846.470173441558.751746건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
5321000032100009220070000120070124<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137060서울특별시 서초구 방배동 480-3번지서울특별시 서초구 효령로2길 25 (방배동)<NA>태광골재산업-주2007-07-14 11:58:12I2018-08-31 23:59:59.0<NA>198846.470173441558.751746건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
6321000032100009220070000220070130<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137070서울특별시 서초구 서초동 1592-10번지 한진오피스텔 808서울특별시 서초구 반포대로18길 8 (서초동,한진오피스텔 808)<NA>명천건기2007-07-14 11:58:12I2018-08-31 23:59:59.0<NA>200934.988115442703.597815건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
7321000032100009220070000320070131<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137130서울특별시 서초구 양재동 363-2번지서울특별시 서초구 강남대로2길 92 (양재동)<NA>(주)용아개발2007-08-16 13:15:27I2018-08-31 23:59:59.0<NA>204045.305025440730.746664건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
8321000032100009220070000420070131<NA>3폐업2폐업20080725<NA><NA><NA><NA><NA>137070서울특별시 서초구 서초동 1588-1번지 신성오피스텔 1203호서울특별시 서초구 반포대로14길 54 (서초동,신성오피스텔 1203호)<NA>신진건기2008-07-25 15:18:38I2018-08-31 23:59:59.0<NA>201153.543583442643.280772건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
9321000032100009220070000620070209<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137130서울특별시 서초구 양재동 363-2번지서울특별시 서초구 강남대로2길 92 (양재동)<NA>용아개발2007-07-14 11:58:12I2018-08-31 23:59:59.0<NA>204045.305025440730.746664건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
14321000032100009220070001420070521<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137130서울특별시 서초구 양재동 363-2번지서울특별시 서초구 강남대로2길 92 (양재동)<NA>(주)용아개발2007-11-09 17:10:46I2018-08-31 23:59:59.0<NA>204045.305025440730.746664건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA>
15321000032100009220070001620070625<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-525-4466<NA>137070서울특별시 서초구 양재동 217 서울오토갤러리서울특별시 서초구 양재대로11길 36, 서울오토갤러리 은관 613호 (양재동)6772명천건기2022-05-11 17:26:25U2021-12-04 23:03:00.0<NA>203059.646701439960.533114<NA><NA><NA><NA><NA><NA>
16321000032100009220080000120080711<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>137062서울특별시 서초구 방배동 979-13번지서울특별시 서초구 효령로21길 7 (방배동)<NA>(주)아이디일일구닷컴2008-07-11 14:10:50I2018-08-31 23:59:59.0<NA>199273.45115442016.470294건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
17321000032100009220110000120110422<NA>1영업/정상BBBB영업<NA><NA><NA><NA>025611300<NA>137130서울특별시 서초구 양재동 178-6번지<NA><NA>(주)페트라환경2012-11-30 16:29:29I2018-08-31 23:59:59.0<NA>202161.816165441785.541996건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
18321000032100009220120000120160415<NA>3폐업2폐업20160415<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초대로19길 44, 1층 나호 (방배동)137837경일공영(주)2016-04-15 16:48:29I2018-08-31 23:59:59.0<NA>199102.433494442981.232615건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
1932100003210000922015000022015-06-07<NA>1영업/정상BBBB영업<NA><NA><NA><NA>031-422-6624<NA><NA>서울특별시 서초구 우면동 7-4 우현서울특별시 서초구 바우뫼로6길 22, 201호 (우면동, 우현)6763(주)터원2023-11-13 09:07:52U2022-10-31 23:05:00.0<NA>202245.563563440812.280856<NA><NA><NA><NA><NA><NA>
2032100003210000922017000012023-02-08<NA>2휴업1휴업<NA>2023-02-07<NA><NA><NA><NA><NA><NA>서울특별시 서초구 남부순환로 2201, 402호 (방배동, 방배 리더스빌)6702(주)현대리싸이클링2023-02-08 15:11:20U2022-12-01 23:00:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2132100003210000922019000012019-10-22<NA>1영업/정상BBBB영업<NA><NA><NA><NA>080-001-8484<NA><NA>서울특별시 서초구 서초동 1593-7 서초이오빌서울특별시 서초구 효령로53길 45, 2층 201-10호 (서초동, 서초이오빌)6652주식회사 한국파쇄2023-07-14 16:17:06U2022-12-06 23:06:00.0<NA>201070.374374442706.851935<NA><NA><NA><NA><NA><NA>
22321000032100009220200000120201218<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 437-3 인성빌딩서울특별시 서초구 방배천로18길 6, 인성빌딩 6층 (방배동)6677주식회사 산들환경2020-12-18 14:00:21I2020-12-22 00:23:05.0<NA>198433.508571442267.561719건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
23321000032100009220220000120220607<NA>1영업/정상BBBB영업<NA><NA><NA><NA>031-422-6624<NA><NA>서울특별시 서초구 우면동 7-4 우현서울특별시 서초구 바우뫼로6길 22, 201호 (우면동, 우현)6763(주)터원2022-06-07 10:00:28I2021-12-06 00:09:00.0<NA>202245.563563440812.280856<NA><NA><NA><NA><NA><NA>