Overview

Dataset statistics

Number of variables31
Number of observations29
Missing cells305
Missing cells (%)33.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory269.6 B

Variable types

Categorical10
Numeric4
DateTime3
Unsupported9
Text5

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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-19315/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (63.8%)Imbalance
영업상태명 is highly imbalanced (63.8%)Imbalance
상세영업상태코드 is highly imbalanced (63.8%)Imbalance
상세영업상태명 is highly imbalanced (63.8%)Imbalance
폐업일자 is highly imbalanced (72.8%)Imbalance
인허가취소일자 has 29 (100.0%) missing valuesMissing
휴업시작일자 has 29 (100.0%) missing valuesMissing
휴업종료일자 has 29 (100.0%) missing valuesMissing
재개업일자 has 29 (100.0%) missing valuesMissing
전화번호 has 6 (20.7%) missing valuesMissing
소재지면적 has 29 (100.0%) missing valuesMissing
소재지우편번호 has 21 (72.4%) missing valuesMissing
지번주소 has 7 (24.1%) missing valuesMissing
도로명주소 has 3 (10.3%) missing valuesMissing
도로명우편번호 has 3 (10.3%) missing valuesMissing
업태구분명 has 29 (100.0%) missing valuesMissing
좌표정보(X) has 2 (6.9%) missing valuesMissing
좌표정보(Y) has 2 (6.9%) missing valuesMissing
폐기물처리업별처리구분명 has 29 (100.0%) missing valuesMissing
폐기물구분명 has 29 (100.0%) missing valuesMissing
허용보관량내용 has 29 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
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 started2024-04-17 16:40:50.771044
Analysis finished2024-04-17 16:40:51.067209
Duration0.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
3130000
29 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 29
100.0%

Length

2024-04-18T01:40:51.113584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:51.180726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 29
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1631044 × 1017
Minimum3.1300009 × 1017
Maximum4.0900009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-18T01:40:51.261667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1300009 × 1017
5-th percentile3.1300009 × 1017
Q13.1300009 × 1017
median3.1300009 × 1017
Q33.1300009 × 1017
95-th percentile3.1300009 × 1017
Maximum4.0900009 × 1017
Range9.6 × 1016
Interquartile range (IQR)1299968

Descriptive statistics

Standard deviation1.7826752 × 1016
Coefficient of variation (CV)0.056358407
Kurtosis29
Mean3.1631044 × 1017
Median Absolute Deviation (MAD)400000
Skewness5.3851648
Sum9.1730027 × 1018
Variance3.177931 × 1032
MonotonicityStrictly increasing
2024-04-18T01:40:51.375031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
313000092200100006 1
 
3.4%
313000092200100011 1
 
3.4%
409000092200700001 1
 
3.4%
313000092202200001 1
 
3.4%
313000092202100003 1
 
3.4%
313000092202100002 1
 
3.4%
313000092202100001 1
 
3.4%
313000092202000004 1
 
3.4%
313000092202000003 1
 
3.4%
313000092202000002 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
313000092200100006 1
3.4%
313000092200100011 1
3.4%
313000092200100012 1
3.4%
313000092200300002 1
3.4%
313000092200300006 1
3.4%
313000092200400001 1
3.4%
313000092200700001 1
3.4%
313000092200700002 1
3.4%
313000092201000001 1
3.4%
313000092201000002 1
3.4%
ValueCountFrequency (%)
409000092200700001 1
3.4%
313000092202200001 1
3.4%
313000092202100003 1
3.4%
313000092202100002 1
3.4%
313000092202100001 1
3.4%
313000092202000004 1
3.4%
313000092202000003 1
3.4%
313000092202000002 1
3.4%
313000092202000001 1
3.4%
313000092201900004 1
3.4%

인허가일자
Date

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2001-07-24 00:00:00
Maximum2024-03-20 00:00:00
2024-04-18T01:40:51.462226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:40:51.548857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
27 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 27
93.1%
3 2
 
6.9%

Length

2024-04-18T01:40:51.642297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:51.710127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
93.1%
3 2
 
6.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
영업/정상
27 
폐업
 
2

Length

Max length5
Median length5
Mean length4.7931034
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 27
93.1%
폐업 2
 
6.9%

Length

2024-04-18T01:40:51.794811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:51.868913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 27
93.1%
폐업 2
 
6.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
BBBB
27 
2
 
2

Length

Max length4
Median length4
Mean length3.7931034
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 27
93.1%
2 2
 
6.9%

Length

2024-04-18T01:40:51.959321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:52.052581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 27
93.1%
2 2
 
6.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
영업
27 
폐업
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 27
93.1%
폐업 2
 
6.9%

Length

2024-04-18T01:40:52.138946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:52.207792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 27
93.1%
폐업 2
 
6.9%

폐업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
27 
20141113
 
1
20160630
 
1

Length

Max length8
Median length4
Mean length4.2758621
Min length4

Unique

Unique2 ?
Unique (%)6.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
93.1%
20141113 1
 
3.4%
20160630 1
 
3.4%

Length

2024-04-18T01:40:52.286176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:52.365564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
93.1%
20141113 1
 
3.4%
20160630 1
 
3.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

전화번호
Text

MISSING 

Distinct21
Distinct (%)91.3%
Missing6
Missing (%)20.7%
Memory size364.0 B
2024-04-18T01:40:52.488730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.434783
Min length7

Characters and Unicode

Total characters240
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

Unique19 ?
Unique (%)82.6%

Sample

1st row02-325-9981
2nd row02-375-1280
3rd row3259981
4th row02-306-0404
5th row02-306-0404
ValueCountFrequency (%)
3055252 2
 
8.7%
02-306-0404 2
 
8.7%
02-3152-8162 1
 
4.3%
02-325-9981 1
 
4.3%
02-326-0044 1
 
4.3%
023733753 1
 
4.3%
02-6925-0009 1
 
4.3%
02-523-0903 1
 
4.3%
02-6402-6667 1
 
4.3%
02-3159-3345 1
 
4.3%
Other values (11) 11
47.8%
2024-04-18T01:40:52.733305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54
22.5%
2 35
14.6%
- 33
13.8%
3 26
10.8%
5 24
10.0%
4 16
 
6.7%
6 13
 
5.4%
7 13
 
5.4%
1 11
 
4.6%
9 8
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 207
86.2%
Dash Punctuation 33
 
13.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54
26.1%
2 35
16.9%
3 26
12.6%
5 24
11.6%
4 16
 
7.7%
6 13
 
6.3%
7 13
 
6.3%
1 11
 
5.3%
9 8
 
3.9%
8 7
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54
22.5%
2 35
14.6%
- 33
13.8%
3 26
10.8%
5 24
10.0%
4 16
 
6.7%
6 13
 
5.4%
7 13
 
5.4%
1 11
 
4.6%
9 8
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54
22.5%
2 35
14.6%
- 33
13.8%
3 26
10.8%
5 24
10.0%
4 16
 
6.7%
6 13
 
5.4%
7 13
 
5.4%
1 11
 
4.6%
9 8
 
3.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

소재지우편번호
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing21
Missing (%)72.4%
Memory size364.0 B
2024-04-18T01:40:52.846386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.375
Min length6

Characters and Unicode

Total characters51
Distinct characters8
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

Unique6 ?
Unique (%)75.0%

Sample

1st row121-850
2nd row121250
3rd row121850
4th row121270
5th row121-270
ValueCountFrequency (%)
121270 2
25.0%
121-850 1
12.5%
121250 1
12.5%
121850 1
12.5%
121-270 1
12.5%
121-251 1
12.5%
121240 1
12.5%
2024-04-18T01:40:53.041187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
33.3%
2 14
27.5%
0 7
13.7%
5 4
 
7.8%
7 3
 
5.9%
- 3
 
5.9%
8 2
 
3.9%
4 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
94.1%
Dash Punctuation 3
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
35.4%
2 14
29.2%
0 7
14.6%
5 4
 
8.3%
7 3
 
6.2%
8 2
 
4.2%
4 1
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
33.3%
2 14
27.5%
0 7
13.7%
5 4
 
7.8%
7 3
 
5.9%
- 3
 
5.9%
8 2
 
3.9%
4 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
33.3%
2 14
27.5%
0 7
13.7%
5 4
 
7.8%
7 3
 
5.9%
- 3
 
5.9%
8 2
 
3.9%
4 1
 
2.0%

지번주소
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing7
Missing (%)24.1%
Memory size364.0 B
2024-04-18T01:40:53.215025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length29.045455
Min length18

Characters and Unicode

Total characters639
Distinct characters89
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row서울특별시 마포구 성산동 591-1번지 이안상암1차 307호
2nd row서울특별시 마포구 상암동 2-79
3rd row서울특별시 마포구 상암동 1447번지
4th row서울특별시 마포구 성산동 209-1 진영빌딩 207호
5th row서울특별시 마포구 상암동 상암택지개발지구5블럭 상암근린상가326ㄹ호
ValueCountFrequency (%)
서울특별시 22
17.7%
마포구 22
17.7%
상암동 11
 
8.9%
성산동 6
 
4.8%
서울산업진흥원 4
 
3.2%
1602 3
 
2.4%
2층 3
 
2.4%
상암 3
 
2.4%
중동 2
 
1.6%
오피스텔 2
 
1.6%
Other values (44) 46
37.1%
2024-04-18T01:40:53.476586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
 
17.1%
서 26
 
4.1%
울 26
 
4.1%
마 25
 
3.9%
구 25
 
3.9%
동 24
 
3.8%
2 23
 
3.6%
포 23
 
3.6%
상 23
 
3.6%
특 22
 
3.4%
Other values (79) 313
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
62.1%
Decimal Number 115
 
18.0%
Space Separator 109
 
17.1%
Dash Punctuation 13
 
2.0%
Uppercase Letter 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 26
 
6.5%
울 26
 
6.5%
마 25
 
6.3%
구 25
 
6.3%
동 24
 
6.0%
포 23
 
5.8%
상 23
 
5.8%
특 22
 
5.5%
별 22
 
5.5%
시 22
 
5.5%
Other values (63) 159
40.1%
Decimal Number
ValueCountFrequency (%)
2 23
20.0%
1 21
18.3%
0 12
10.4%
6 11
9.6%
7 11
9.6%
4 10
8.7%
3 10
8.7%
5 7
 
6.1%
9 7
 
6.1%
8 3
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
M 1
20.0%
D 1
20.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
62.1%
Common 237
37.1%
Latin 5
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 26
 
6.5%
울 26
 
6.5%
마 25
 
6.3%
구 25
 
6.3%
동 24
 
6.0%
포 23
 
5.8%
상 23
 
5.8%
특 22
 
5.5%
별 22
 
5.5%
시 22
 
5.5%
Other values (63) 159
40.1%
Common
ValueCountFrequency (%)
109
46.0%
2 23
 
9.7%
1 21
 
8.9%
- 13
 
5.5%
0 12
 
5.1%
6 11
 
4.6%
7 11
 
4.6%
4 10
 
4.2%
3 10
 
4.2%
5 7
 
3.0%
Other values (2) 10
 
4.2%
Latin
ValueCountFrequency (%)
A 2
40.0%
M 1
20.0%
D 1
20.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
62.0%
ASCII 242
37.9%
Compat Jamo 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
45.0%
2 23
 
9.5%
1 21
 
8.7%
- 13
 
5.4%
0 12
 
5.0%
6 11
 
4.5%
7 11
 
4.5%
4 10
 
4.1%
3 10
 
4.1%
5 7
 
2.9%
Other values (6) 15
 
6.2%
Hangul
ValueCountFrequency (%)
서 26
 
6.6%
울 26
 
6.6%
마 25
 
6.3%
구 25
 
6.3%
동 24
 
6.1%
포 23
 
5.8%
상 23
 
5.8%
특 22
 
5.6%
별 22
 
5.6%
시 22
 
5.6%
Other values (62) 158
39.9%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

도로명주소
Text

MISSING 

Distinct25
Distinct (%)96.2%
Missing3
Missing (%)10.3%
Memory size364.0 B
2024-04-18T01:40:53.691164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38.5
Mean length37.923077
Min length23

Characters and Unicode

Total characters986
Distinct characters111
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)92.3%

Sample

1st row서울특별시 마포구 월드컵로 204, 307호 (성산동, 이안상암)
2nd row서울특별시 마포구 월드컵로 190, 1003호 (성산동, 이안상암Ⅱ)
3rd row서울특별시 마포구 성암로 211-5, 1층 (상암동)
4th row서울특별시 마포구 성암로 211 (상암동)
5th row서울특별시 마포구 월드컵북로 78, 진영빌딩 207호 (성산동)
ValueCountFrequency (%)
서울특별시 26
 
13.4%
마포구 25
 
12.9%
성산동 9
 
4.6%
상암동 9
 
4.6%
월드컵북로 7
 
3.6%
2층 5
 
2.6%
400 4
 
2.1%
서울산업진흥원 4
 
2.1%
상암 4
 
2.1%
월드컵로 3
 
1.5%
Other values (84) 98
50.5%
2024-04-18T01:40:53.994981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168
 
17.0%
1 41
 
4.2%
동 32
 
3.2%
, 32
 
3.2%
서 31
 
3.1%
울 31
 
3.1%
마 28
 
2.8%
구 28
 
2.8%
0 27
 
2.7%
포 27
 
2.7%
Other values (101) 541
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 560
56.8%
Space Separator 168
 
17.0%
Decimal Number 158
 
16.0%
Other Punctuation 32
 
3.2%
Close Punctuation 26
 
2.6%
Open Punctuation 26
 
2.6%
Uppercase Letter 11
 
1.1%
Dash Punctuation 4
 
0.4%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 32
 
5.7%
서 31
 
5.5%
울 31
 
5.5%
마 28
 
5.0%
구 28
 
5.0%
포 27
 
4.8%
별 26
 
4.6%
시 26
 
4.6%
특 26
 
4.6%
로 24
 
4.3%
Other values (75) 281
50.2%
Decimal Number
ValueCountFrequency (%)
1 41
25.9%
0 27
17.1%
2 22
13.9%
3 17
10.8%
4 15
 
9.5%
7 11
 
7.0%
8 8
 
5.1%
9 7
 
4.4%
5 5
 
3.2%
6 5
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
A 2
18.2%
D 1
9.1%
M 1
9.1%
C 1
9.1%
E 1
9.1%
L 1
9.1%
S 1
9.1%
O 1
9.1%
N 1
9.1%
B 1
9.1%
Space Separator
ValueCountFrequency (%)
168
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
56.8%
Common 414
42.0%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 32
 
5.7%
서 31
 
5.5%
울 31
 
5.5%
마 28
 
5.0%
구 28
 
5.0%
포 27
 
4.8%
별 26
 
4.6%
시 26
 
4.6%
특 26
 
4.6%
로 24
 
4.3%
Other values (75) 281
50.2%
Common
ValueCountFrequency (%)
168
40.6%
1 41
 
9.9%
, 32
 
7.7%
0 27
 
6.5%
) 26
 
6.3%
( 26
 
6.3%
2 22
 
5.3%
3 17
 
4.1%
4 15
 
3.6%
7 11
 
2.7%
Other values (5) 29
 
7.0%
Latin
ValueCountFrequency (%)
A 2
16.7%
D 1
8.3%
M 1
8.3%
C 1
8.3%
E 1
8.3%
L 1
8.3%
S 1
8.3%
O 1
8.3%
N 1
8.3%
B 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 560
56.8%
ASCII 425
43.1%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
39.5%
1 41
 
9.6%
, 32
 
7.5%
0 27
 
6.4%
) 26
 
6.1%
( 26
 
6.1%
2 22
 
5.2%
3 17
 
4.0%
4 15
 
3.5%
7 11
 
2.6%
Other values (15) 40
 
9.4%
Hangul
ValueCountFrequency (%)
동 32
 
5.7%
서 31
 
5.5%
울 31
 
5.5%
마 28
 
5.0%
구 28
 
5.0%
포 27
 
4.8%
별 26
 
4.6%
시 26
 
4.6%
특 26
 
4.6%
로 24
 
4.3%
Other values (75) 281
50.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)69.2%
Missing3
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean8573.8846
Minimum3914
Maximum121841
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-18T01:40:54.099321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3914
5-th percentile3919.75
Q13927
median3938
Q33975
95-th percentile5652.5
Maximum121841
Range117927
Interquartile range (IQR)48

Descriptive statistics

Standard deviation23106.171
Coefficient of variation (CV)2.6949477
Kurtosis25.979107
Mean8573.8846
Median Absolute Deviation (MAD)13
Skewness5.0960976
Sum222921
Variance5.3389514 × 108
MonotonicityNot monotonic
2024-04-18T01:40:54.189479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3938 5
17.2%
3925 4
13.8%
3927 2
 
6.9%
3914 1
 
3.4%
3966 1
 
3.4%
6170 1
 
3.4%
121841 1
 
3.4%
3959 1
 
3.4%
3918 1
 
3.4%
3978 1
 
3.4%
Other values (8) 8
27.6%
(Missing) 3
 
10.3%
ValueCountFrequency (%)
3914 1
 
3.4%
3918 1
 
3.4%
3925 4
13.8%
3927 2
 
6.9%
3930 1
 
3.4%
3933 1
 
3.4%
3938 5
17.2%
3941 1
 
3.4%
3959 1
 
3.4%
3961 1
 
3.4%
ValueCountFrequency (%)
121841 1
3.4%
6170 1
3.4%
4100 1
3.4%
4071 1
3.4%
3999 1
3.4%
3996 1
3.4%
3978 1
3.4%
3966 1
3.4%
3961 1
3.4%
3959 1
3.4%

사업장명
Text

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-18T01:40:54.332155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4827586
Min length4

Characters and Unicode

Total characters188
Distinct characters72
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

Unique22 ?
Unique (%)75.9%

Sample

1st row홍진상운
2nd row홍익건설중기
3rd row혜광중기
4th row대신덤프
5th row대신덤프
ValueCountFrequency (%)
팔팔덤프 3
 
9.7%
대신덤프 2
 
6.5%
주식회사 2
 
6.5%
주)케이제이 2
 
6.5%
현원환경(주 1
 
3.2%
홍진상운 1
 
3.2%
다온이앤티 1
 
3.2%
주)건영환경물류 1
 
3.2%
협신환경컨설팅 1
 
3.2%
주)일한개발 1
 
3.2%
Other values (16) 16
51.6%
2024-04-18T01:40:54.584041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 15
 
8.0%
( 13
 
6.9%
) 13
 
6.9%
이 13
 
6.9%
팔 6
 
3.2%
환 6
 
3.2%
경 6
 
3.2%
프 5
 
2.7%
덤 5
 
2.7%
개 4
 
2.1%
Other values (62) 102
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
85.1%
Open Punctuation 13
 
6.9%
Close Punctuation 13
 
6.9%
Space Separator 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 15
 
9.4%
이 13
 
8.1%
팔 6
 
3.8%
환 6
 
3.8%
경 6
 
3.8%
프 5
 
3.1%
덤 5
 
3.1%
개 4
 
2.5%
설 4
 
2.5%
발 4
 
2.5%
Other values (59) 92
57.5%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
85.1%
Common 28
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 15
 
9.4%
이 13
 
8.1%
팔 6
 
3.8%
환 6
 
3.8%
경 6
 
3.8%
프 5
 
3.1%
덤 5
 
3.1%
개 4
 
2.5%
설 4
 
2.5%
발 4
 
2.5%
Other values (59) 92
57.5%
Common
ValueCountFrequency (%)
( 13
46.4%
) 13
46.4%
2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
85.1%
ASCII 28
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 15
 
9.4%
이 13
 
8.1%
팔 6
 
3.8%
환 6
 
3.8%
경 6
 
3.8%
프 5
 
3.1%
덤 5
 
3.1%
개 4
 
2.5%
설 4
 
2.5%
발 4
 
2.5%
Other values (59) 92
57.5%
ASCII
ValueCountFrequency (%)
( 13
46.4%
) 13
46.4%
2
 
7.1%

최종수정일자
Date

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2007-08-08 10:20:14
Maximum2024-04-05 09:16:45
2024-04-18T01:40:54.682760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:40:54.771001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
U
20 
I
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 20
69.0%
I 9
31.0%

Length

2024-04-18T01:40:54.864454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:54.933188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 20
69.0%
i 9
31.0%

데이터갱신일자
Date

Distinct20
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-18T01:40:54.998594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:40:55.079372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)81.5%
Missing2
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean191879.62
Minimum189624.68
Maximum205604.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-18T01:40:55.169801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189624.68
5-th percentile190182.07
Q1190726.43
median191348.22
Q3191964.91
95-th percentile193856.95
Maximum205604.01
Range15979.337
Interquartile range (IQR)1238.4793

Descriptive statistics

Standard deviation2916.1399
Coefficient of variation (CV)0.015197757
Kurtosis20.46631
Mean191879.62
Median Absolute Deviation (MAD)641.17118
Skewness4.2921869
Sum5180749.7
Variance8503871.8
MonotonicityNot monotonic
2024-04-18T01:40:55.486809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
190182.067334395 4
 
13.8%
191284.3945348 2
 
6.9%
191362.641381599 2
 
6.9%
192513.961688702 1
 
3.4%
190707.050644566 1
 
3.4%
192332.918156777 1
 
3.4%
191890.005893327 1
 
3.4%
191262.003894104 1
 
3.4%
191397.589463829 1
 
3.4%
194343.471516512 1
 
3.4%
Other values (12) 12
41.4%
(Missing) 2
 
6.9%
ValueCountFrequency (%)
189624.675468841 1
 
3.4%
190182.067334395 4
13.8%
190641.868358376 1
 
3.4%
190707.050644566 1
 
3.4%
190745.816653699 1
 
3.4%
190767.853792746 1
 
3.4%
191262.003894104 1
 
3.4%
191284.3945348 2
6.9%
191318.835539489 1
 
3.4%
191348.221823456 1
 
3.4%
ValueCountFrequency (%)
205604.012147798 1
3.4%
194343.471516512 1
3.4%
192721.723596783 1
3.4%
192563.814988726 1
3.4%
192513.961688702 1
3.4%
192332.918156777 1
3.4%
192039.820018429 1
3.4%
191890.005893327 1
3.4%
191467.830887267 1
3.4%
191435.876990887 1
3.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)81.5%
Missing2
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean451552.95
Minimum445826.27
Maximum453872.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-18T01:40:55.585512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445826.27
5-th percentile449684.2
Q1450891.5
median451460.54
Q3452761.53
95-th percentile453141.68
Maximum453872.4
Range8046.1284
Interquartile range (IQR)1870.0302

Descriptive statistics

Standard deviation1582.5403
Coefficient of variation (CV)0.0035046615
Kurtosis5.6208842
Mean451552.95
Median Absolute Deviation (MAD)962.04575
Skewness-1.7525052
Sum12191930
Variance2504433.6
MonotonicityNot monotonic
2024-04-18T01:40:55.677366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
453141.676626027 4
 
13.8%
451460.53743524 2
 
6.9%
451523.367819928 2
 
6.9%
450966.302367257 1
 
3.4%
452644.967927455 1
 
3.4%
449461.477885688 1
 
3.4%
450598.415183464 1
 
3.4%
452422.583184869 1
 
3.4%
451116.947315843 1
 
3.4%
450203.900484327 1
 
3.4%
Other values (12) 12
41.4%
(Missing) 2
 
6.9%
ValueCountFrequency (%)
445826.270916213 1
3.4%
449461.477885688 1
3.4%
450203.900484327 1
3.4%
450377.043740241 1
3.4%
450598.415183464 1
3.4%
450719.394284708 1
3.4%
450816.701318344 1
3.4%
450966.302367257 1
3.4%
451116.947315843 1
3.4%
451328.488369456 1
3.4%
ValueCountFrequency (%)
453872.3993323 1
 
3.4%
453141.676626027 4
13.8%
452882.295042959 1
 
3.4%
452878.096240989 1
 
3.4%
452644.967927455 1
 
3.4%
452454.955218912 1
 
3.4%
452422.583184869 1
 
3.4%
451990.707795053 1
 
3.4%
451523.367819928 2
6.9%
451460.53743524 2
6.9%

환경업무구분명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
16 
건설폐기물처리업사업계획(허가)신청
13 

Length

Max length18
Median length4
Mean length10.275862
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 16
55.2%
건설폐기물처리업사업계획(허가)신청 13
44.8%

Length

2024-04-18T01:40:55.789614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:55.864965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
55.2%
건설폐기물처리업사업계획(허가)신청 13
44.8%

폐기물처리업구분명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
17 
수집운반업(건설폐기물)
12 

Length

Max length12
Median length4
Mean length7.3103448
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
58.6%
수집운반업(건설폐기물) 12
41.4%

Length

2024-04-18T01:40:55.952200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:56.030642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
58.6%
수집운반업(건설폐기물 12
41.4%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

폐기물구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

허용보관량
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
24 
0
5 

Length

Max length4
Median length4
Mean length3.4827586
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> 24
82.8%
0 5
 
17.2%

Length

2024-04-18T01:40:56.109717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:40:56.182524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
82.8%
0 5
 
17.2%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
031300003130000922001000062024-03-20<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-325-9981<NA>121-850<NA>서울특별시 마포구 월드컵로 204, 307호 (성산동, 이안상암)3938홍진상운2024-03-26 17:10:14U2023-12-02 22:08:00.0<NA>191284.394535451460.537435<NA><NA><NA><NA><NA><NA>
1313000031300009220010001120100420<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-375-1280<NA>121250<NA>서울특별시 마포구 월드컵로 190, 1003호 (성산동, 이안상암Ⅱ)3938홍익건설중기2016-11-03 17:59:51I2018-08-31 23:59:59.0<NA>191467.830887451328.488369건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
2313000031300009220010001220100415<NA>1영업/정상BBBB영업<NA><NA><NA><NA>3259981<NA>121850서울특별시 마포구 성산동 591-1번지 이안상암1차 307호<NA><NA>혜광중기2010-04-15 10:22:46I2018-08-31 23:59:59.0<NA>191284.394535451460.537435건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
331300003130000922003000022019-11-18<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-306-0404<NA><NA>서울특별시 마포구 상암동 2-79서울특별시 마포구 성암로 211-5, 1층 (상암동)3927대신덤프2024-04-05 09:16:45U2023-12-04 00:07:00.0<NA>190745.816654452878.096241<NA><NA><NA><NA><NA><NA>
4313000031300009220030000620191118<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-306-0404<NA><NA>서울특별시 마포구 상암동 1447번지서울특별시 마포구 성암로 211 (상암동)3927대신덤프2019-11-18 10:04:56U2019-11-20 02:40:00.0<NA>190767.853793452882.295043건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
5313000031300009220040000120220804<NA>1영업/정상BBBB영업<NA><NA><NA><NA>023374700<NA><NA>서울특별시 마포구 성산동 209-1 진영빌딩 207호서울특별시 마포구 월드컵북로 78, 진영빌딩 207호 (성산동)3978삼은이엔지2022-08-04 14:13:28U2021-12-08 00:07:00.0<NA>192513.961689450966.302367<NA><NA><NA><NA><NA><NA>
6313000031300009220070000120070808<NA>1영업/정상BBBB영업<NA><NA><NA><NA>3055252<NA>121270서울특별시 마포구 상암동 상암택지개발지구5블럭 상암근린상가326ㄹ호<NA><NA>팔팔덤프2007-08-08 13:57:39I2018-08-31 23:59:59.0<NA><NA><NA>건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
731300003130000922007000022019-10-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>305-5252<NA>121-270서울특별시 마포구 상암동 28-62서울특별시 마포구 월드컵북로43길 28, 301호 (상암동)3914팔팔덤프2024-04-05 09:16:44U2023-12-04 00:07:00.0<NA>190641.868358452454.955219<NA><NA><NA><NA><NA><NA>
831300003130000922010000012022-12-13<NA>1영업/정상BBBB영업<NA><NA><NA><NA>070-4015-5888<NA>121-251서울특별시 마포구 성산동 86-4서울특별시 마포구 성산로 154, 402호 (성산동, 충영빌딩)3966우리이엔브이(주)2023-11-16 20:11:02U2022-10-31 23:08:00.0<NA>192039.820018451386.82634<NA><NA><NA><NA><NA><NA>
9313000031300009220100000220100609<NA>3폐업2폐업20141113<NA><NA><NA>7016046<NA>121240<NA>서울특별시 강남구 봉은사로 628, 3층 (삼성동, ELSON빌딩)6170센트로건설(주)2016-04-20 17:34:19I2018-08-31 23:59:59.0<NA>205604.012148445826.270916건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
19313000031300009220190000420221201<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6402-6667<NA><NA>서울특별시 마포구 성산동 591-6 상암 퍼스티지 더올림 오피스텔 403호서울특별시 마포구 모래내로1길 17, 상암 퍼스티지 더올림 오피스텔 403호 (성산동)3938천우환경산업(주)2022-12-01 17:48:38U2021-11-02 00:03:00.0<NA>191348.221823451447.299638<NA><NA><NA><NA><NA><NA>
20313000031300009220200000120200416<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-523-0903<NA><NA>서울특별시 마포구 성산동 590-1 상암 두산위브센티움 1314호서울특별시 마포구 월드컵로36길 14, 상암 두산위브센티움 1314호 (성산동)3938주식회사 일하는소리2022-10-25 09:34:49U2021-10-30 22:07:00.0<NA>191362.641382451523.36782<NA><NA><NA><NA><NA><NA>
21313000031300009220200000220200715<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 1602 서울산업진흥원서울특별시 마포구 월드컵북로 400, 서울산업진흥원 2층 (상암동)3925(주)은성개발2020-09-29 10:40:16U2020-10-01 02:40:00.0<NA>190182.067334453141.676626건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
2231300003130000922020000032020-07-24<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6925-0009<NA><NA>서울특별시 마포구 노고산동 107-17 우정마샹스 오피스텔서울특별시 마포구 백범로 8, 우정마샹스 오피스텔 524호 (노고산동)4100(주)대양제이씨2023-11-03 13:24:48U2022-11-01 00:05:00.0<NA>194343.471517450203.900484<NA><NA><NA><NA><NA><NA>
2331300003130000922020000042022-06-30<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 471-2 프리마빌딩서울특별시 마포구 방울내로11길 37, 프리마빌딩 319호 (망원동)3961(주)일한개발2023-05-23 16:35:10U2022-12-04 22:05:00.0<NA>191397.589464451116.947316<NA><NA><NA><NA><NA><NA>
24313000031300009220210000120210420<NA>1영업/정상BBBB영업<NA><NA><NA><NA>023733753<NA><NA>서울특별시 마포구 중동 390 DMC마포청구아파트서울특별시 마포구 성암로11길 60, 101동 1107호 (중동, DMC마포청구아파트)3933협신환경컨설팅2021-04-20 10:31:03U2021-04-22 02:40:00.0<NA>191262.003894452422.583185건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
25313000031300009220210000220210826<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 1602 서울산업진흥원 2층 A동 127호서울특별시 마포구 월드컵북로 400, 서울산업진흥원 2층 A동 127호 (상암동)3925(주)케이제이2021-09-02 11:20:44U2021-09-04 02:40:00.0<NA>190182.067334453141.676626건설폐기물처리업사업계획(허가)신청<NA><NA><NA>0<NA>
26313000031300009220210000320210903<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-335-2007<NA><NA>서울특별시 마포구 성산동 649-4서울특별시 마포구 월드컵로 100, 3층 (성산동)3996(주)건영환경물류2021-09-03 10:34:09I2021-09-05 00:22:49.0<NA>191890.005893450598.415183건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0<NA>
2731300003130000922022000012022-12-21<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 합정동 372-28 지층서울특별시 마포구 성지길 25-11, 지층 (합정동)4071에이스환경2023-03-02 16:06:44U2022-12-03 00:04:00.0<NA>192332.918157449461.477886<NA><NA><NA><NA><NA><NA>
28313000040900009220070000120070808<NA>1영업/정상BBBB영업<NA><NA><NA><NA>3055252<NA>121270서울특별시 마포구 상암동 상암택지개발지구5블럭상암근린상가326호<NA><NA>팔팔덤프2007-08-08 10:20:14I2018-08-31 23:59:59.0<NA><NA><NA>건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>