Overview

Dataset statistics

Number of variables33
Number of observations151
Missing cells1529
Missing cells (%)30.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.4 KiB
Average record size in memory280.9 B

Variable types

Numeric4
DateTime4
Unsupported6
Categorical13
Text6

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,업종구분명,종별명,주생산품명,배출시설조업시간,배출시설연간가동일수,방지시설조업시간,방지시설연간가동일수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16118/S/1/datasetView.do

Alerts

휴업종료일자 is highly imbalanced (87.5%)Imbalance
재개업일자 is highly imbalanced (87.5%)Imbalance
데이터갱신일자 is highly imbalanced (58.1%)Imbalance
업태구분명 is highly imbalanced (60.6%)Imbalance
업종구분명 is highly imbalanced (62.7%)Imbalance
배출시설연간가동일수 is highly imbalanced (82.4%)Imbalance
방지시설연간가동일수 is highly imbalanced (82.4%)Imbalance
인허가취소일자 has 151 (100.0%) missing valuesMissing
폐업일자 has 100 (66.2%) missing valuesMissing
휴업시작일자 has 141 (93.4%) missing valuesMissing
전화번호 has 86 (57.0%) missing valuesMissing
소재지면적 has 151 (100.0%) missing valuesMissing
소재지우편번호 has 43 (28.5%) missing valuesMissing
도로명주소 has 76 (50.3%) missing valuesMissing
도로명우편번호 has 108 (71.5%) missing valuesMissing
좌표정보(X) has 34 (22.5%) missing valuesMissing
좌표정보(Y) has 34 (22.5%) missing valuesMissing
종별명 has 151 (100.0%) missing valuesMissing
주생산품명 has 151 (100.0%) missing valuesMissing
배출시설조업시간 has 151 (100.0%) missing valuesMissing
방지시설조업시간 has 151 (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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주생산품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 00:27:16.227175
Analysis finished2024-05-11 00:27:17.361040
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct22
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3133841.1
Minimum3000000
Maximum3230000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:27:17.526283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13060000
median3160000
Q33205000
95-th percentile3230000
Maximum3230000
Range230000
Interquartile range (IQR)145000

Descriptive statistics

Standard deviation76462.286
Coefficient of variation (CV)0.024398904
Kurtosis-1.2493216
Mean3133841.1
Median Absolute Deviation (MAD)60000
Skewness-0.42719182
Sum4.7321 × 108
Variance5.8464812 × 109
MonotonicityNot monotonic
2024-05-11T00:27:17.841509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3010000 18
11.9%
3210000 15
9.9%
3230000 15
9.9%
3160000 14
 
9.3%
3180000 12
 
7.9%
3150000 10
 
6.6%
3220000 8
 
5.3%
3170000 8
 
5.3%
3100000 8
 
5.3%
3060000 7
 
4.6%
Other values (12) 36
23.8%
ValueCountFrequency (%)
3000000 1
 
0.7%
3010000 18
11.9%
3020000 5
 
3.3%
3030000 2
 
1.3%
3040000 7
 
4.6%
3050000 2
 
1.3%
3060000 7
 
4.6%
3080000 1
 
0.7%
3090000 5
 
3.3%
3100000 8
5.3%
ValueCountFrequency (%)
3230000 15
9.9%
3220000 8
5.3%
3210000 15
9.9%
3200000 4
 
2.6%
3190000 3
 
2.0%
3180000 12
7.9%
3170000 8
5.3%
3160000 14
9.3%
3150000 10
6.6%
3130000 4
 
2.6%

관리번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1592721 × 1017
Minimum3.0000005 × 1017
Maximum7.0000005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:27:18.219553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000005 × 1017
5-th percentile3.0100005 × 1017
Q13.0600005 × 1017
median3.1600005 × 1017
Q33.2100005 × 1017
95-th percentile3.2300005 × 1017
Maximum7.0000005 × 1017
Range4 × 1017
Interquartile range (IQR)1.5 × 1016

Descriptive statistics

Standard deviation3.237882 × 1016
Coefficient of variation (CV)0.10248823
Kurtosis134.31861
Mean3.1592721 × 1017
Median Absolute Deviation (MAD)6 × 1015
Skewness11.256619
Sum-7.6352242 × 1018
Variance1.048388 × 1033
MonotonicityNot monotonic
2024-05-11T00:27:18.790121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
313000053202200006 1
 
0.7%
318000053200700002 1
 
0.7%
318000053000000001 1
 
0.7%
318000053200100004 1
 
0.7%
318000053200200001 1
 
0.7%
318000053200300001 1
 
0.7%
318000053200500001 1
 
0.7%
318000053200600001 1
 
0.7%
318000053200600002 1
 
0.7%
318000053200100003 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
300000053200700001 1
0.7%
301000053198400001 1
0.7%
301000053198600004 1
0.7%
301000053198700002 1
0.7%
301000053198700003 1
0.7%
301000053198700005 1
0.7%
301000053198700006 1
0.7%
301000053198700007 1
0.7%
301000053198700008 1
0.7%
301000053198800009 1
0.7%
ValueCountFrequency (%)
700000053200000003 1
0.7%
323000053202200001 1
0.7%
323000053201700001 1
0.7%
323000053201500001 1
0.7%
323000053200900001 1
0.7%
323000053200400002 1
0.7%
323000053200400001 1
0.7%
323000053200200002 1
0.7%
323000053200100007 1
0.7%
323000053200100006 1
0.7%

인허가일자
Date

Distinct143
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1984-01-30 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T00:27:19.220417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:27:19.701223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
93 
3
51 
2
 
7

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 93
61.6%
3 51
33.8%
2 7
 
4.6%

Length

2024-05-11T00:27:20.148580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:20.730458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 93
61.6%
3 51
33.8%
2 7
 
4.6%

영업상태명
Categorical

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
93 
폐업
51 
휴업
 
7

Length

Max length5
Median length5
Mean length3.8476821
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 93
61.6%
폐업 51
33.8%
휴업 7
 
4.6%

Length

2024-05-11T00:27:21.141506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:21.522475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 93
61.6%
폐업 51
33.8%
휴업 7
 
4.6%

상세영업상태코드
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
11
90 
2
51 
1
 
7
3
 
3

Length

Max length2
Median length2
Mean length1.5960265
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 90
59.6%
2 51
33.8%
1 7
 
4.6%
3 3
 
2.0%

Length

2024-05-11T00:27:21.958257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:22.323214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 90
59.6%
2 51
33.8%
1 7
 
4.6%
3 3
 
2.0%

상세영업상태명
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업
90 
폐업
51 
휴업
 
7
재개업
 
3

Length

Max length3
Median length2
Mean length2.0198675
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 90
59.6%
폐업 51
33.8%
휴업 7
 
4.6%
재개업 3
 
2.0%

Length

2024-05-11T00:27:22.747591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:23.145298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 90
59.6%
폐업 51
33.8%
휴업 7
 
4.6%
재개업 3
 
2.0%

폐업일자
Date

MISSING 

Distinct49
Distinct (%)96.1%
Missing100
Missing (%)66.2%
Memory size1.3 KiB
Minimum2001-02-26 00:00:00
Maximum2022-10-21 00:00:00
2024-05-11T00:27:23.550949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:27:24.032645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

휴업시작일자
Date

MISSING 

Distinct7
Distinct (%)70.0%
Missing141
Missing (%)93.4%
Memory size1.3 KiB
Minimum2002-09-24 00:00:00
Maximum2023-09-23 00:00:00
2024-05-11T00:27:24.448611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:27:24.923516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
20200916
 
3
20020924
 
1

Length

Max length8
Median length4
Mean length4.1059603
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
97.4%
20200916 3
 
2.0%
20020924 1
 
0.7%

Length

2024-05-11T00:27:25.445547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:25.885144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
97.4%
20200916 3
 
2.0%
20020924 1
 
0.7%

재개업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
20200916
 
3
20020924
 
1

Length

Max length8
Median length4
Mean length4.1059603
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
97.4%
20200916 3
 
2.0%
20020924 1
 
0.7%

Length

2024-05-11T00:27:26.293552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:26.887758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
97.4%
20200916 3
 
2.0%
20020924 1
 
0.7%

전화번호
Text

MISSING 

Distinct61
Distinct (%)93.8%
Missing86
Missing (%)57.0%
Memory size1.3 KiB
2024-05-11T00:27:27.664156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.9076923
Min length7

Characters and Unicode

Total characters644
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)87.7%

Sample

1st row02-3272-0903
2nd row02-465-1771
3rd row02-3785-3459
4th row02 4637196
5th row0236650516
ValueCountFrequency (%)
02 16
 
18.4%
32720903 2
 
2.3%
025888357 2
 
2.3%
0234927203 2
 
2.3%
02-975-8422 2
 
2.3%
8435076 1
 
1.1%
02861 1
 
1.1%
02-837-1146 1
 
1.1%
02-3782-0114 1
 
1.1%
028320600 1
 
1.1%
Other values (58) 58
66.7%
2024-05-11T00:27:29.047884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 115
17.9%
0 112
17.4%
3 55
8.5%
5 54
8.4%
7 45
 
7.0%
8 43
 
6.7%
4 43
 
6.7%
9 39
 
6.1%
1 39
 
6.1%
- 38
 
5.9%
Other values (2) 61
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 581
90.2%
Dash Punctuation 38
 
5.9%
Space Separator 25
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 115
19.8%
0 112
19.3%
3 55
9.5%
5 54
9.3%
7 45
 
7.7%
8 43
 
7.4%
4 43
 
7.4%
9 39
 
6.7%
1 39
 
6.7%
6 36
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 115
17.9%
0 112
17.4%
3 55
8.5%
5 54
8.4%
7 45
 
7.0%
8 43
 
6.7%
4 43
 
6.7%
9 39
 
6.1%
1 39
 
6.1%
- 38
 
5.9%
Other values (2) 61
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 115
17.9%
0 112
17.4%
3 55
8.5%
5 54
8.4%
7 45
 
7.0%
8 43
 
6.7%
4 43
 
6.7%
9 39
 
6.1%
1 39
 
6.1%
- 38
 
5.9%
Other values (2) 61
9.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Text

MISSING 

Distinct89
Distinct (%)82.4%
Missing43
Missing (%)28.5%
Memory size1.3 KiB
2024-05-11T00:27:29.947447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0277778
Min length6

Characters and Unicode

Total characters651
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)66.7%

Sample

1st row140-200
2nd row133120
3rd rownull
4th row100095
5th row142103
ValueCountFrequency (%)
137130 3
 
2.8%
138190 3
 
2.8%
133120 2
 
1.9%
150044 2
 
1.9%
135856 2
 
1.9%
137060 2
 
1.9%
137072 2
 
1.9%
156090 2
 
1.9%
150070 2
 
1.9%
150834 2
 
1.9%
Other values (79) 86
79.6%
2024-05-11T00:27:31.541259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 161
24.7%
0 148
22.7%
3 86
13.2%
5 65
10.0%
2 58
 
8.9%
4 32
 
4.9%
7 30
 
4.6%
8 27
 
4.1%
9 20
 
3.1%
6 15
 
2.3%
Other values (5) 9
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 642
98.6%
Lowercase Letter 4
 
0.6%
Dash Punctuation 3
 
0.5%
Space Separator 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 161
25.1%
0 148
23.1%
3 86
13.4%
5 65
10.1%
2 58
 
9.0%
4 32
 
5.0%
7 30
 
4.7%
8 27
 
4.2%
9 20
 
3.1%
6 15
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 647
99.4%
Latin 4
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 161
24.9%
0 148
22.9%
3 86
13.3%
5 65
10.0%
2 58
 
9.0%
4 32
 
4.9%
7 30
 
4.6%
8 27
 
4.2%
9 20
 
3.1%
6 15
 
2.3%
Other values (2) 5
 
0.8%
Latin
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 161
24.7%
0 148
22.7%
3 86
13.2%
5 65
10.0%
2 58
 
8.9%
4 32
 
4.9%
7 30
 
4.6%
8 27
 
4.1%
9 20
 
3.1%
6 15
 
2.3%
Other values (5) 9
 
1.4%

지번주소
Text

Distinct141
Distinct (%)94.0%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2024-05-11T00:27:32.623899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length23.966667
Min length15

Characters and Unicode

Total characters3595
Distinct characters201
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)88.0%

Sample

1st row서울특별시 마포구 현석동 220 밤섬현대아파트 상가동 103호
2nd row서울특별시 송파구 문정동 642 테라타워2 비동 1101호
3rd row서울특별시 용산구 동자동 45 센트레빌아스테리움서울 A동 1104호
4th row서울특별시 용산구 이태원동 137-8
5th row서울특별시 성동구 성수동2가 315-71
ValueCountFrequency (%)
서울특별시 149
 
21.4%
중구 17
 
2.4%
송파구 15
 
2.2%
영등포구 14
 
2.0%
서초구 14
 
2.0%
구로구 14
 
2.0%
금천구 9
 
1.3%
강서구 9
 
1.3%
강남구 8
 
1.1%
노원구 8
 
1.1%
Other values (321) 439
63.1%
2024-05-11T00:27:34.020251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
714
19.9%
서 182
 
5.1%
구 173
 
4.8%
1 162
 
4.5%
동 162
 
4.5%
울 151
 
4.2%
시 150
 
4.2%
특 149
 
4.1%
별 149
 
4.1%
- 126
 
3.5%
Other values (191) 1477
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1994
55.5%
Decimal Number 751
 
20.9%
Space Separator 714
 
19.9%
Dash Punctuation 126
 
3.5%
Uppercase Letter 9
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 182
 
9.1%
구 173
 
8.7%
동 162
 
8.1%
울 151
 
7.6%
시 150
 
7.5%
특 149
 
7.5%
별 149
 
7.5%
가 40
 
2.0%
로 29
 
1.5%
중 28
 
1.4%
Other values (171) 781
39.2%
Decimal Number
ValueCountFrequency (%)
1 162
21.6%
2 106
14.1%
3 83
11.1%
0 79
10.5%
4 76
10.1%
6 70
9.3%
5 58
 
7.7%
7 44
 
5.9%
9 41
 
5.5%
8 32
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
22.2%
B 2
22.2%
D 1
11.1%
K 1
11.1%
C 1
11.1%
J 1
11.1%
T 1
11.1%
Space Separator
ValueCountFrequency (%)
714
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1994
55.5%
Common 1592
44.3%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 182
 
9.1%
구 173
 
8.7%
동 162
 
8.1%
울 151
 
7.6%
시 150
 
7.5%
특 149
 
7.5%
별 149
 
7.5%
가 40
 
2.0%
로 29
 
1.5%
중 28
 
1.4%
Other values (171) 781
39.2%
Common
ValueCountFrequency (%)
714
44.8%
1 162
 
10.2%
- 126
 
7.9%
2 106
 
6.7%
3 83
 
5.2%
0 79
 
5.0%
4 76
 
4.8%
6 70
 
4.4%
5 58
 
3.6%
7 44
 
2.8%
Other values (3) 74
 
4.6%
Latin
ValueCountFrequency (%)
A 2
22.2%
B 2
22.2%
D 1
11.1%
K 1
11.1%
C 1
11.1%
J 1
11.1%
T 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1994
55.5%
ASCII 1601
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
714
44.6%
1 162
 
10.1%
- 126
 
7.9%
2 106
 
6.6%
3 83
 
5.2%
0 79
 
4.9%
4 76
 
4.7%
6 70
 
4.4%
5 58
 
3.6%
7 44
 
2.7%
Other values (10) 83
 
5.2%
Hangul
ValueCountFrequency (%)
서 182
 
9.1%
구 173
 
8.7%
동 162
 
8.1%
울 151
 
7.6%
시 150
 
7.5%
특 149
 
7.5%
별 149
 
7.5%
가 40
 
2.0%
로 29
 
1.5%
중 28
 
1.4%
Other values (171) 781
39.2%

도로명주소
Text

MISSING 

Distinct71
Distinct (%)94.7%
Missing76
Missing (%)50.3%
Memory size1.3 KiB
2024-05-11T00:27:34.799638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length32.133333
Min length21

Characters and Unicode

Total characters2410
Distinct characters202
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)89.3%

Sample

1st row서울특별시 마포구 신수로3길 19, 밤섬현대아파트 상가동 103층 (현석동)
2nd row서울특별시 송파구 송파대로 201, 비동 1101층 (문정동, 테라타워2)
3rd row서울특별시 용산구 한강대로 372, A동 1104호 (동자동, 센트레빌아스테리움서울)
4th row서울특별시 용산구 우사단로 36 (이태원동)
5th row서울특별시 강서구 공항대로57길 24 (등촌동)
ValueCountFrequency (%)
서울특별시 74
 
16.5%
구로구 10
 
2.2%
송파구 10
 
2.2%
서초구 8
 
1.8%
금천구 8
 
1.8%
노원구 7
 
1.6%
중구 7
 
1.6%
2층 6
 
1.3%
가산동 6
 
1.3%
광진구 5
 
1.1%
Other values (240) 307
68.5%
2024-05-11T00:27:36.306016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
405
 
16.8%
동 95
 
3.9%
로 94
 
3.9%
서 92
 
3.8%
구 92
 
3.8%
1 76
 
3.2%
울 76
 
3.2%
2 76
 
3.2%
( 75
 
3.1%
시 75
 
3.1%
Other values (192) 1254
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1414
58.7%
Space Separator 405
 
16.8%
Decimal Number 368
 
15.3%
Open Punctuation 75
 
3.1%
Close Punctuation 75
 
3.1%
Other Punctuation 54
 
2.2%
Dash Punctuation 10
 
0.4%
Uppercase Letter 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 95
 
6.7%
로 94
 
6.6%
서 92
 
6.5%
구 92
 
6.5%
울 76
 
5.4%
시 75
 
5.3%
특 74
 
5.2%
별 74
 
5.2%
길 37
 
2.6%
산 30
 
2.1%
Other values (173) 675
47.7%
Decimal Number
ValueCountFrequency (%)
1 76
20.7%
2 76
20.7%
3 38
10.3%
0 32
8.7%
4 32
8.7%
7 28
 
7.6%
5 26
 
7.1%
6 23
 
6.2%
8 19
 
5.2%
9 18
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
J 2
22.2%
C 2
22.2%
A 2
22.2%
Space Separator
ValueCountFrequency (%)
405
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1414
58.7%
Common 987
41.0%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 95
 
6.7%
로 94
 
6.6%
서 92
 
6.5%
구 92
 
6.5%
울 76
 
5.4%
시 75
 
5.3%
특 74
 
5.2%
별 74
 
5.2%
길 37
 
2.6%
산 30
 
2.1%
Other values (173) 675
47.7%
Common
ValueCountFrequency (%)
405
41.0%
1 76
 
7.7%
2 76
 
7.7%
( 75
 
7.6%
) 75
 
7.6%
, 54
 
5.5%
3 38
 
3.9%
0 32
 
3.2%
4 32
 
3.2%
7 28
 
2.8%
Other values (5) 96
 
9.7%
Latin
ValueCountFrequency (%)
B 3
33.3%
J 2
22.2%
C 2
22.2%
A 2
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1414
58.7%
ASCII 996
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
405
40.7%
1 76
 
7.6%
2 76
 
7.6%
( 75
 
7.5%
) 75
 
7.5%
, 54
 
5.4%
3 38
 
3.8%
0 32
 
3.2%
4 32
 
3.2%
7 28
 
2.8%
Other values (9) 105
 
10.5%
Hangul
ValueCountFrequency (%)
동 95
 
6.7%
로 94
 
6.6%
서 92
 
6.5%
구 92
 
6.5%
울 76
 
5.4%
시 75
 
5.3%
특 74
 
5.2%
별 74
 
5.2%
길 37
 
2.6%
산 30
 
2.1%
Other values (173) 675
47.7%

도로명우편번호
Text

MISSING 

Distinct41
Distinct (%)95.3%
Missing108
Missing (%)71.5%
Memory size1.3 KiB
2024-05-11T00:27:36.902390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4651163
Min length5

Characters and Unicode

Total characters235
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

Unique39 ?
Unique (%)90.7%

Sample

1st row04092
2nd row05854
3rd row04323
4th row157030
5th row08584
ValueCountFrequency (%)
153783 2
 
4.7%
02072 2
 
4.7%
07621 1
 
2.3%
08298 1
 
2.3%
05615 1
 
2.3%
153801 1
 
2.3%
04092 1
 
2.3%
153803 1
 
2.3%
121140 1
 
2.3%
07564 1
 
2.3%
Other values (31) 31
72.1%
2024-05-11T00:27:38.104951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
18.3%
1 36
15.3%
3 30
12.8%
5 24
10.2%
8 22
9.4%
2 21
8.9%
6 15
 
6.4%
7 14
 
6.0%
9 14
 
6.0%
4 14
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 233
99.1%
Dash Punctuation 2
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
18.5%
1 36
15.5%
3 30
12.9%
5 24
10.3%
8 22
9.4%
2 21
9.0%
6 15
 
6.4%
7 14
 
6.0%
9 14
 
6.0%
4 14
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
18.3%
1 36
15.3%
3 30
12.8%
5 24
10.2%
8 22
9.4%
2 21
8.9%
6 15
 
6.4%
7 14
 
6.0%
9 14
 
6.0%
4 14
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
18.3%
1 36
15.3%
3 30
12.8%
5 24
10.2%
8 22
9.4%
2 21
8.9%
6 15
 
6.4%
7 14
 
6.0%
9 14
 
6.0%
4 14
 
6.0%

사업장명
Text

Distinct132
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:27:39.066443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length7.9337748
Min length2

Characters and Unicode

Total characters1198
Distinct characters159
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)75.5%

Sample

1st row태평양환경컨설팅 주식회사
2nd row(주)그린환경
3rd row가나기술산업주식회사
4th row주식회사 정우 이엔에스
5th row(주)동양그린하이테크
ValueCountFrequency (%)
주)정우기연 3
 
1.9%
주식회사 3
 
1.9%
한국정화(주 2
 
1.3%
대한통운(주 2
 
1.3%
미래수질환경(주 2
 
1.3%
주)신의환경 2
 
1.3%
청정환경 2
 
1.3%
주)호진환경 2
 
1.3%
바이오메카(주 2
 
1.3%
주)선양엔지니어링 2
 
1.3%
Other values (125) 135
86.0%
2024-05-11T00:27:40.322339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 128
 
10.7%
) 109
 
9.1%
( 107
 
8.9%
경 59
 
4.9%
환 56
 
4.7%
엔 34
 
2.8%
지 28
 
2.3%
이 24
 
2.0%
스 22
 
1.8%
사 17
 
1.4%
Other values (149) 614
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 970
81.0%
Close Punctuation 109
 
9.1%
Open Punctuation 107
 
8.9%
Space Separator 6
 
0.5%
Dash Punctuation 3
 
0.3%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 128
 
13.2%
경 59
 
6.1%
환 56
 
5.8%
엔 34
 
3.5%
지 28
 
2.9%
이 24
 
2.5%
스 22
 
2.3%
사 17
 
1.8%
한 17
 
1.8%
링 16
 
1.6%
Other values (142) 569
58.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
C 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 970
81.0%
Common 225
 
18.8%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 128
 
13.2%
경 59
 
6.1%
환 56
 
5.8%
엔 34
 
3.5%
지 28
 
2.9%
이 24
 
2.5%
스 22
 
2.3%
사 17
 
1.8%
한 17
 
1.8%
링 16
 
1.6%
Other values (142) 569
58.7%
Common
ValueCountFrequency (%)
) 109
48.4%
( 107
47.6%
6
 
2.7%
- 3
 
1.3%
Latin
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 970
81.0%
ASCII 228
 
19.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 128
 
13.2%
경 59
 
6.1%
환 56
 
5.8%
엔 34
 
3.5%
지 28
 
2.9%
이 24
 
2.5%
스 22
 
2.3%
사 17
 
1.8%
한 17
 
1.8%
링 16
 
1.6%
Other values (142) 569
58.7%
ASCII
ValueCountFrequency (%)
) 109
47.8%
( 107
46.9%
6
 
2.6%
- 3
 
1.3%
E 1
 
0.4%
N 1
 
0.4%
C 1
 
0.4%

최종수정일자
Date

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2000-09-15 11:02:09
Maximum2024-04-05 18:06:24
2024-05-11T00:27:40.785025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:27:41.425218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
117 
U
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 117
77.5%
U 34
 
22.5%

Length

2024-05-11T00:27:41.886649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:42.224582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 117
77.5%
u 34
 
22.5%

데이터갱신일자
Categorical

IMBALANCE 

Distinct36
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2018-08-31 23:59:59.0
111 
2020-09-18 02:40:00.0
 
4
2023-12-04 00:07:00.0
 
2
2023-11-30 22:01:00.0
 
2
2022-12-08 22:00:00.0
 
1
Other values (31)
31 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique32 ?
Unique (%)21.2%

Sample

1st row2022-12-02 23:06:00.0
2nd row2022-12-05 00:04:00.0
3rd row2023-12-04 00:07:00.0
4th row2023-12-04 00:07:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 111
73.5%
2020-09-18 02:40:00.0 4
 
2.6%
2023-12-04 00:07:00.0 2
 
1.3%
2023-11-30 22:01:00.0 2
 
1.3%
2022-12-08 22:00:00.0 1
 
0.7%
2022-12-05 00:04:00.0 1
 
0.7%
2021-02-27 02:40:00.0 1
 
0.7%
2020-10-16 02:40:00.0 1
 
0.7%
2019-03-10 02:40:00.0 1
 
0.7%
2020-08-06 02:40:00.0 1
 
0.7%
Other values (26) 26
 
17.2%

Length

2024-05-11T00:27:42.639997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 111
36.8%
23:59:59.0 111
36.8%
02:40:00.0 19
 
6.3%
2020-09-18 4
 
1.3%
2023-11-30 3
 
1.0%
22:07:00.0 3
 
1.0%
00:07:00.0 2
 
0.7%
22:01:00.0 2
 
0.7%
00:04:00.0 2
 
0.7%
2023-12-04 2
 
0.7%
Other values (40) 43
 
14.2%

업태구분명
Categorical

IMBALANCE 

Distinct12
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
117 
분뇨 처리업
 
11
하수, 분뇨 및 축산폐기물 처리업
 
8
하수처리, 폐기물처리 및 청소관련 서비스업
 
4
하수, 폐수 및 분뇨 처리업
 
2
Other values (7)
 
9

Length

Max length24
Median length4
Mean length6.205298
Min length4

Unique

Unique5 ?
Unique (%)3.3%

Sample

1st row그외 기타 달리 분류되지 않은 개인 서비스업
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row하수, 분뇨 및 축산폐기물 처리업

Common Values

ValueCountFrequency (%)
<NA> 117
77.5%
분뇨 처리업 11
 
7.3%
하수, 분뇨 및 축산폐기물 처리업 8
 
5.3%
하수처리, 폐기물처리 및 청소관련 서비스업 4
 
2.6%
하수, 폐수 및 분뇨 처리업 2
 
1.3%
환경상담 및 관련 엔지니어링 서비스업 2
 
1.3%
분뇨 및 축산폐기물 처리업 2
 
1.3%
그외 기타 달리 분류되지 않은 개인 서비스업 1
 
0.7%
기타 건물건설관련 전문 공사업 1
 
0.7%
종합 건설업 1
 
0.7%
Other values (2) 2
 
1.3%

Length

2024-05-11T00:27:43.043989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 117
47.2%
처리업 23
 
9.3%
분뇨 23
 
9.3%
및 19
 
7.7%
하수 10
 
4.0%
축산폐기물 10
 
4.0%
서비스업 7
 
2.8%
하수처리 4
 
1.6%
폐기물처리 4
 
1.6%
청소관련 4
 
1.6%
Other values (19) 27
 
10.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)92.3%
Missing34
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean198860.98
Minimum183131.03
Maximum212784.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:27:43.564909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183131.03
5-th percentile187241.68
Q1190694.88
median199824.85
Q3205828.56
95-th percentile209720.42
Maximum212784.62
Range29653.587
Interquartile range (IQR)15133.679

Descriptive statistics

Standard deviation7950.2387
Coefficient of variation (CV)0.039978876
Kurtosis-1.2714703
Mean198860.98
Median Absolute Deviation (MAD)7146.0727
Skewness-0.16095184
Sum23266735
Variance63206296
MonotonicityNot monotonic
2024-05-11T00:27:44.268716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208774.508763872 2
 
1.3%
187809.462543639 2
 
1.3%
190295.141464557 2
 
1.3%
197620.676444642 2
 
1.3%
189127.981104583 2
 
1.3%
204619.143523595 2
 
1.3%
196996.127113139 2
 
1.3%
203891.041008756 2
 
1.3%
184229.740132067 2
 
1.3%
193532.600274812 1
 
0.7%
Other values (98) 98
64.9%
(Missing) 34
 
22.5%
ValueCountFrequency (%)
183131.028798764 1
0.7%
184229.740132067 2
1.3%
185761.610347719 1
0.7%
185828.474932856 1
0.7%
186916.777913245 1
0.7%
187322.90355485 1
0.7%
187533.878903298 1
0.7%
187809.462543639 2
1.3%
187827.22116065 1
0.7%
187918.667297764 1
0.7%
ValueCountFrequency (%)
212784.616145219 1
0.7%
212085.653992635 1
0.7%
211788.824 1
0.7%
210780.126180232 1
0.7%
210191.986403297 1
0.7%
210053.802513945 1
0.7%
209637.078215509 1
0.7%
209268.321106193 1
0.7%
209042.662929298 1
0.7%
208920.309871536 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)92.3%
Missing34
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean447756.77
Minimum427643.07
Maximum463887.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:27:44.738474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum427643.07
5-th percentile441627.1
Q1442917.66
median445488.73
Q3450993.84
95-th percentile459811.69
Maximum463887.94
Range36244.868
Interquartile range (IQR)8076.1859

Descriptive statistics

Standard deviation6228.3744
Coefficient of variation (CV)0.013910174
Kurtosis0.79632703
Mean447756.77
Median Absolute Deviation (MAD)3446.2863
Skewness0.66549017
Sum52387542
Variance38792648
MonotonicityNot monotonic
2024-05-11T00:27:45.445295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455336.495054007 2
 
1.3%
450046.546516858 2
 
1.3%
443841.455440573 2
 
1.3%
450361.506112161 2
 
1.3%
442460.505542105 2
 
1.3%
463887.942604325 2
 
1.3%
442714.034347352 2
 
1.3%
441636.969240722 2
 
1.3%
449362.914352826 2
 
1.3%
443907.905571294 1
 
0.7%
Other values (98) 98
64.9%
(Missing) 34
 
22.5%
ValueCountFrequency (%)
427643.0746251 1
0.7%
440295.618804889 1
0.7%
440764.426277932 1
0.7%
440963.790624982 1
0.7%
441431.482365654 1
0.7%
441618.071646624 1
0.7%
441629.361414684 1
0.7%
441636.969240722 2
1.3%
441665.146287428 1
0.7%
441720.322 1
0.7%
ValueCountFrequency (%)
463887.942604325 2
1.3%
463533.259200639 1
0.7%
462714.188504333 1
0.7%
461782.719034388 1
0.7%
461582.803734992 1
0.7%
459368.915209276 1
0.7%
459141.573121253 1
0.7%
459060.733452516 1
0.7%
458960.471391303 1
0.7%
458461.080892026 1
0.7%

환경업무구분명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
분뇨등관련영업관리
133 
<NA>
18 

Length

Max length9
Median length9
Mean length8.4039735
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등관련영업관리 133
88.1%
<NA> 18
 
11.9%

Length

2024-05-11T00:27:46.093797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:46.600692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등관련영업관리 133
88.1%
na 18
 
11.9%

업종구분명
Categorical

IMBALANCE 

Distinct11
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
120 
분뇨 처리업
 
10
하수, 분뇨 및 축산폐기물 처리업
 
8
하수처리, 폐기물처리 및 청소관련 서비스업
 
4
환경상담 및 관련 엔지니어링 서비스업
 
2
Other values (6)
 
7

Length

Max length23
Median length4
Mean length5.986755
Min length4

Unique

Unique5 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row하수, 분뇨 및 축산폐기물 처리업

Common Values

ValueCountFrequency (%)
<NA> 120
79.5%
분뇨 처리업 10
 
6.6%
하수, 분뇨 및 축산폐기물 처리업 8
 
5.3%
하수처리, 폐기물처리 및 청소관련 서비스업 4
 
2.6%
환경상담 및 관련 엔지니어링 서비스업 2
 
1.3%
분뇨 및 축산폐기물 처리업 2
 
1.3%
기타 건물건설관련 전문 공사업 1
 
0.7%
종합 건설업 1
 
0.7%
하수, 폐수 및 분뇨 처리업 1
 
0.7%
그외 기타 축산업 1
 
0.7%

Length

2024-05-11T00:27:47.091983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 120
50.6%
분뇨 21
 
8.9%
처리업 21
 
8.9%
및 18
 
7.6%
축산폐기물 10
 
4.2%
하수 9
 
3.8%
서비스업 6
 
2.5%
하수처리 4
 
1.7%
폐기물처리 4
 
1.7%
청소관련 4
 
1.7%
Other values (15) 20
 
8.4%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

배출시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
0
 
4

Length

Max length4
Median length4
Mean length3.9205298
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
97.4%
0 4
 
2.6%

Length

2024-05-11T00:27:47.582056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:48.125753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
97.4%
0 4
 
2.6%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

방지시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
0
 
4

Length

Max length4
Median length4
Mean length3.9205298
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
97.4%
0 4
 
2.6%

Length

2024-05-11T00:27:48.469952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:27:48.808886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
97.4%
0 4
 
2.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
031300003130000532022000062022-07-18<NA>1영업/정상11영업<NA><NA><NA><NA>02-3272-0903<NA><NA>서울특별시 마포구 현석동 220 밤섬현대아파트 상가동 103호서울특별시 마포구 신수로3길 19, 밤섬현대아파트 상가동 103층 (현석동)04092태평양환경컨설팅 주식회사2023-03-14 14:13:53I2022-12-02 23:06:00.0그외 기타 달리 분류되지 않은 개인 서비스업193979.616534448935.013231<NA><NA><NA><NA><NA><NA><NA><NA>
132300003230000532017000012017-04-24<NA>1영업/정상11영업<NA><NA><NA><NA>02-465-1771<NA><NA>서울특별시 송파구 문정동 642 테라타워2 비동 1101호서울특별시 송파구 송파대로 201, 비동 1101층 (문정동, 테라타워2)05854(주)그린환경2023-05-02 15:16:50U2022-12-05 00:04:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230200003020000532024000012024-04-04<NA>1영업/정상11영업<NA><NA><NA><NA>02-3785-3459<NA><NA>서울특별시 용산구 동자동 45 센트레빌아스테리움서울 A동 1104호서울특별시 용산구 한강대로 372, A동 1104호 (동자동, 센트레빌아스테리움서울)04323가나기술산업주식회사2024-04-05 18:04:17I2023-12-04 00:07:00.0<NA>197563.069806449934.157783<NA><NA><NA><NA><NA><NA><NA><NA>
330200003020000532005000012005-08-16<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>140-200서울특별시 용산구 이태원동 137-8서울특별시 용산구 우사단로 36 (이태원동)<NA>주식회사 정우 이엔에스2024-04-05 18:06:24U2023-12-04 00:07:00.0<NA>199554.378391447915.516566<NA><NA><NA><NA><NA><NA><NA><NA>
4303000030300005320010000120011115<NA>1영업/정상11영업<NA><NA><NA><NA>02 4637196<NA>133120서울특별시 성동구 성수동2가 315-71<NA><NA>(주)동양그린하이테크2002-08-06 15:49:32I2018-08-31 23:59:59.0하수, 분뇨 및 축산폐기물 처리업204827.433052449134.994666분뇨등관련영업관리하수, 분뇨 및 축산폐기물 처리업<NA><NA><NA><NA><NA><NA>
5315000031500005320000001420020311<NA>3폐업2폐업20170125<NA><NA><NA>0236650516<NA>null서울특별시 강서구 등촌동 649-13 남정빌딩 301호호서울특별시 강서구 공항대로57길 24 (등촌동)157030청우기연(주)2017-01-25 14:55:20I2018-08-31 23:59:59.0<NA>187809.462544450046.546517분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
6317000031700005320180000120190109<NA>3폐업2폐업20190418<NA><NA><NA>0221692589<NA><NA>서울특별시 금천구 독산동 291-1 현대지식산업센터서울특별시 금천구 두산로 70, 현대지식산업센터 B동 422-1호 (독산동)08584대한환경안전기술2019-04-23 16:10:50U2019-04-25 02:40:00.0<NA>190694.880295440764.426278분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
7301000030100005319920001319921005<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>100095서울특별시 중구 남대문로5가 541서울특별시 중구 한강대로 416 (남대문로5가)<NA>덕성환경2000-12-14 15:22:05I2018-08-31 23:59:59.0<NA>197620.676445450361.506112분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
832300003230000532004000012004-02-17<NA>3폐업2폐업2021-10-18<NA><NA><NA>4078500<NA><NA>서울특별시 송파구 오금동 128-3 그린빌딩서울특별시 송파구 동남로 297, 그린빌딩 2층 (오금동)05729(주)청수이앤에스2023-02-10 15:16:33U2022-12-01 23:02:00.0<NA>212085.653993444436.131145<NA><NA><NA><NA><NA><NA><NA><NA>
9301000030100005320170000120170504<NA>1영업/정상11영업<NA><NA><NA><NA>02-2273-1094<NA><NA>서울특별시 중구 광희동1가 182-21 신생빌딩 502호서울특별시 중구 을지로44길 13, 502호 (광희동1가, 신생빌딩)04561(주)지앤지엔지니어링2017-05-10 17:22:25I2018-08-31 23:59:59.0기타 건물건설관련 전문 공사업200523.291875451462.625534분뇨등관련영업관리기타 건물건설관련 전문 공사업<NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
141323000032300005320010000120010417<NA>3폐업2폐업20040226<NA><NA><NA><NA><NA>138170서울특별시 송파구 송파동 103서울특별시 송파구 가락로 176 (송파동)<NA>동양수처리2007-10-24 15:37:48I2018-08-31 23:59:59.0<NA>210053.802514444673.058429분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
142323000032300005320010000220010913<NA>3폐업2폐업20160902<NA><NA><NA><NA><NA>138190서울특별시 송파구 석촌동 226-16서울특별시 송파구 가락로 23 (석촌동)138190천지환경건설(주)2016-09-02 13:49:55I2018-08-31 23:59:59.0<NA>208681.713236444049.266351분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
143323000032300005320010000420011025<NA>3폐업2폐업20031008<NA><NA><NA><NA><NA>138190서울특별시 송파구 석촌동 226-5<NA><NA>(주)크린워터2007-10-24 15:38:28I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA>
144323000032300005320020000220021021<NA>3폐업2폐업20031208<NA><NA><NA><NA><NA>138180서울특별시 송파구 삼전동 111-1<NA><NA>청정환경2007-10-24 15:41:29I2018-08-31 23:59:59.0분뇨 처리업<NA><NA>분뇨등관련영업관리분뇨 처리업<NA><NA><NA><NA><NA><NA>
145323000032300005320010000620010913<NA>3폐업2폐업20110614<NA><NA><NA>024245701<NA>138843서울특별시 송파구 석촌동 156-4서울특별시 송파구 석촌호수로18길 11-11 (석촌동)<NA>(주)동양이알디2016-09-02 13:46:06I2018-08-31 23:59:59.0하수, 분뇨 및 축산폐기물 처리업208920.309872444889.662668분뇨등관련영업관리하수, 분뇨 및 축산폐기물 처리업<NA><NA><NA><NA><NA><NA>
146317000031700005320130000220131230<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 481-2서울특별시 금천구 가산디지털1로 233, 1202호 (가산동, 에이스하이엔드9차)153023(주)정우기연2022-04-25 11:03:48U2021-12-03 22:07:00.0<NA>189174.55857442636.320101<NA><NA><NA><NA><NA><NA><NA><NA>
147315000031500005320180000220180719<NA>3폐업2폐업20220502<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 614-120서울특별시 강서구 개화동로25길 73 (방화동)07621(주)바른관리2022-05-02 13:15:59I2021-12-05 00:04:00.0분뇨 처리업183131.028799451431.601811<NA><NA><NA><NA><NA><NA><NA><NA>
148323000032300005320040000220040330<NA>3폐업2폐업20190819<NA><NA><NA>422-6462<NA><NA>서울특별시 송파구 마천동 33서울특별시 송파구 마천로 251 (마천동, 대산빌딩)05734미령환경개발(주)2022-11-25 16:53:47U2021-10-31 22:07:00.0<NA>212784.616145444102.405015<NA><NA><NA><NA><NA><NA><NA><NA>
14932300003230000532022000012022-04-05<NA>1영업/정상11영업<NA><NA><NA><NA>02-475-2298<NA><NA>서울특별시 송파구 석촌동 150-28서울특별시 송파구 석촌호수로20길 32-1, 미소지움 101호 (석촌동)05615신우2024-01-19 15:57:33U2023-11-30 22:01:00.0<NA>209042.662929444719.438608<NA><NA><NA><NA><NA><NA><NA><NA>
15032300003230000532015000012015-07-28<NA>1영업/정상11영업<NA><NA><NA><NA>02-512-3282<NA><NA>서울특별시 송파구 문정동 632 가든파이브웍스서울특별시 송파구 충민로 52, 가든파이브웍스 A동 1013호 (문정동)05839대윤환경(주)2024-02-15 18:00:56U2023-12-01 23:07:00.0<NA>210780.12618441730.920486<NA><NA><NA><NA><NA><NA><NA><NA>