Overview

Dataset statistics

Number of variables47
Number of observations275
Missing cells2748
Missing cells (%)21.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory108.6 KiB
Average record size in memory404.5 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
Boolean2

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),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-19283/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (96.5%)Imbalance
위생업태명 is highly imbalanced (51.9%)Imbalance
사용끝지하층 is highly imbalanced (67.2%)Imbalance
발한실여부 is highly imbalanced (95.7%)Imbalance
건물소유구분명 is highly imbalanced (60.2%)Imbalance
여성종사자수 is highly imbalanced (60.2%)Imbalance
남성종사자수 is highly imbalanced (62.0%)Imbalance
인허가취소일자 has 275 (100.0%) missing valuesMissing
폐업일자 has 86 (31.3%) missing valuesMissing
휴업시작일자 has 275 (100.0%) missing valuesMissing
휴업종료일자 has 275 (100.0%) missing valuesMissing
재개업일자 has 275 (100.0%) missing valuesMissing
전화번호 has 82 (29.8%) missing valuesMissing
도로명주소 has 83 (30.2%) missing valuesMissing
도로명우편번호 has 85 (30.9%) missing valuesMissing
좌표정보(X) has 4 (1.5%) missing valuesMissing
좌표정보(Y) has 4 (1.5%) missing valuesMissing
건물지상층수 has 91 (33.1%) missing valuesMissing
사용시작지상층 has 104 (37.8%) missing valuesMissing
사용끝지상층 has 167 (60.7%) missing valuesMissing
발한실여부 has 61 (22.2%) missing valuesMissing
조건부허가신고사유 has 275 (100.0%) missing valuesMissing
조건부허가시작일자 has 275 (100.0%) missing valuesMissing
조건부허가종료일자 has 275 (100.0%) missing valuesMissing
다중이용업소여부 has 56 (20.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 148 (53.8%) zerosZeros
사용시작지상층 has 48 (17.5%) zerosZeros
사용끝지상층 has 13 (4.7%) zerosZeros

Reproduction

Analysis started2024-05-11 08:11:14.281403
Analysis finished2024-05-11 08:11:14.983038
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3060000
275 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 275
100.0%

Length

2024-05-11T17:11:15.045327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:15.138975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 275
100.0%

관리번호
Text

UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T17:11:15.304006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6050
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

Unique275 ?
Unique (%)100.0%

Sample

1st row3060000-206-1987-02411
2nd row3060000-206-1987-02412
3rd row3060000-206-1989-02412
4th row3060000-206-1991-02414
5th row3060000-206-1992-02416
ValueCountFrequency (%)
3060000-206-1987-02411 1
 
0.4%
3060000-206-2015-00001 1
 
0.4%
3060000-206-2014-00014 1
 
0.4%
3060000-206-2014-00015 1
 
0.4%
3060000-206-2014-00016 1
 
0.4%
3060000-206-2014-00017 1
 
0.4%
3060000-206-2014-00018 1
 
0.4%
3060000-206-2017-00007 1
 
0.4%
3060000-206-2015-00003 1
 
0.4%
3060000-206-2012-00003 1
 
0.4%
Other values (265) 265
96.4%
2024-05-11T17:11:15.639249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2947
48.7%
- 825
 
13.6%
2 697
 
11.5%
6 601
 
9.9%
3 344
 
5.7%
1 275
 
4.5%
4 108
 
1.8%
9 103
 
1.7%
5 56
 
0.9%
8 48
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5225
86.4%
Dash Punctuation 825
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2947
56.4%
2 697
 
13.3%
6 601
 
11.5%
3 344
 
6.6%
1 275
 
5.3%
4 108
 
2.1%
9 103
 
2.0%
5 56
 
1.1%
8 48
 
0.9%
7 46
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6050
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2947
48.7%
- 825
 
13.6%
2 697
 
11.5%
6 601
 
9.9%
3 344
 
5.7%
1 275
 
4.5%
4 108
 
1.8%
9 103
 
1.7%
5 56
 
0.9%
8 48
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2947
48.7%
- 825
 
13.6%
2 697
 
11.5%
6 601
 
9.9%
3 344
 
5.7%
1 275
 
4.5%
4 108
 
1.8%
9 103
 
1.7%
5 56
 
0.9%
8 48
 
0.8%
Distinct267
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1987-12-21 00:00:00
Maximum2024-03-19 00:00:00
2024-05-11T17:11:15.781526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:11:15.920299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3
189 
1
86 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 189
68.7%
1 86
31.3%

Length

2024-05-11T17:11:16.046382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:16.130924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 189
68.7%
1 86
31.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
189 
영업/정상
86 

Length

Max length5
Median length2
Mean length2.9381818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 189
68.7%
영업/정상 86
31.3%

Length

2024-05-11T17:11:16.232694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:16.325898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 189
68.7%
영업/정상 86
31.3%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2
189 
1
86 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 189
68.7%
1 86
31.3%

Length

2024-05-11T17:11:16.417029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:16.508298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 189
68.7%
1 86
31.3%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
189 
영업
86 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 189
68.7%
영업 86
31.3%

Length

2024-05-11T17:11:16.624653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:16.730465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 189
68.7%
영업 86
31.3%

폐업일자
Date

MISSING 

Distinct163
Distinct (%)86.2%
Missing86
Missing (%)31.3%
Memory size2.3 KiB
Minimum1993-06-25 00:00:00
Maximum2024-04-16 00:00:00
2024-05-11T17:11:16.841280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:11:16.978813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

전화번호
Text

MISSING 

Distinct186
Distinct (%)96.4%
Missing82
Missing (%)29.8%
Memory size2.3 KiB
2024-05-11T17:11:17.231370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.051813
Min length7

Characters and Unicode

Total characters1940
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

Unique180 ?
Unique (%)93.3%

Sample

1st row02 4964383
2nd row02 4964383
3rd row0209771657
4th row0209725420
5th row0204390291
ValueCountFrequency (%)
02 79
 
24.9%
02433 5
 
1.6%
0222085144 3
 
0.9%
02496 3
 
0.9%
02495 3
 
0.9%
02434 2
 
0.6%
02435 2
 
0.6%
070 2
 
0.6%
02491 2
 
0.6%
02437 2
 
0.6%
Other values (209) 214
67.5%
2024-05-11T17:11:17.596503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 356
18.4%
0 330
17.0%
4 217
11.2%
3 159
8.2%
9 157
8.1%
150
7.7%
1 141
 
7.3%
7 126
 
6.5%
8 117
 
6.0%
5 96
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1790
92.3%
Space Separator 150
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 356
19.9%
0 330
18.4%
4 217
12.1%
3 159
8.9%
9 157
8.8%
1 141
 
7.9%
7 126
 
7.0%
8 117
 
6.5%
5 96
 
5.4%
6 91
 
5.1%
Space Separator
ValueCountFrequency (%)
150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 356
18.4%
0 330
17.0%
4 217
11.2%
3 159
8.2%
9 157
8.1%
150
7.7%
1 141
 
7.3%
7 126
 
6.5%
8 117
 
6.0%
5 96
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 356
18.4%
0 330
17.0%
4 217
11.2%
3 159
8.2%
9 157
8.1%
150
7.7%
1 141
 
7.3%
7 126
 
6.5%
8 117
 
6.0%
5 96
 
4.9%
Distinct184
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T17:11:17.922934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9927273
Min length3

Characters and Unicode

Total characters1373
Distinct characters12
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

Unique151 ?
Unique (%)54.9%

Sample

1st row498.74
2nd row198.86
3rd row.00
4th row97.50
5th row.00
ValueCountFrequency (%)
00 22
 
8.0%
33.00 11
 
4.0%
66.00 8
 
2.9%
20.00 5
 
1.8%
25.00 5
 
1.8%
99.00 5
 
1.8%
16.50 5
 
1.8%
35.10 4
 
1.5%
40.00 4
 
1.5%
95.00 3
 
1.1%
Other values (174) 203
73.8%
2024-05-11T17:11:18.412400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 335
24.4%
. 275
20.0%
6 105
 
7.6%
2 101
 
7.4%
1 101
 
7.4%
3 99
 
7.2%
5 94
 
6.8%
9 79
 
5.8%
4 66
 
4.8%
8 60
 
4.4%
Other values (2) 58
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1096
79.8%
Other Punctuation 277
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 335
30.6%
6 105
 
9.6%
2 101
 
9.2%
1 101
 
9.2%
3 99
 
9.0%
5 94
 
8.6%
9 79
 
7.2%
4 66
 
6.0%
8 60
 
5.5%
7 56
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 275
99.3%
, 2
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 335
24.4%
. 275
20.0%
6 105
 
7.6%
2 101
 
7.4%
1 101
 
7.4%
3 99
 
7.2%
5 94
 
6.8%
9 79
 
5.8%
4 66
 
4.8%
8 60
 
4.4%
Other values (2) 58
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 335
24.4%
. 275
20.0%
6 105
 
7.6%
2 101
 
7.4%
1 101
 
7.4%
3 99
 
7.2%
5 94
 
6.8%
9 79
 
5.8%
4 66
 
4.8%
8 60
 
4.4%
Other values (2) 58
 
4.2%
Distinct90
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T17:11:18.700626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1236364
Min length6

Characters and Unicode

Total characters1684
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

Unique30 ?
Unique (%)10.9%

Sample

1st row131858
2nd row131858
3rd row131853
4th row131852
5th row131821
ValueCountFrequency (%)
131861 13
 
4.7%
131865 12
 
4.4%
131881 12
 
4.4%
131872 11
 
4.0%
131811 10
 
3.6%
131852 9
 
3.3%
131802 8
 
2.9%
131819 8
 
2.9%
131807 8
 
2.9%
131821 7
 
2.5%
Other values (80) 177
64.4%
2024-05-11T17:11:19.078425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 657
39.0%
3 319
18.9%
8 315
18.7%
6 66
 
3.9%
5 66
 
3.9%
2 65
 
3.9%
0 61
 
3.6%
7 52
 
3.1%
- 34
 
2.0%
4 25
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1650
98.0%
Dash Punctuation 34
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 657
39.8%
3 319
19.3%
8 315
19.1%
6 66
 
4.0%
5 66
 
4.0%
2 65
 
3.9%
0 61
 
3.7%
7 52
 
3.2%
4 25
 
1.5%
9 24
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1684
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 657
39.0%
3 319
18.9%
8 315
18.7%
6 66
 
3.9%
5 66
 
3.9%
2 65
 
3.9%
0 61
 
3.6%
7 52
 
3.1%
- 34
 
2.0%
4 25
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 657
39.0%
3 319
18.9%
8 315
18.7%
6 66
 
3.9%
5 66
 
3.9%
2 65
 
3.9%
0 61
 
3.6%
7 52
 
3.1%
- 34
 
2.0%
4 25
 
1.5%
Distinct256
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T17:11:19.436645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length23.16
Min length16

Characters and Unicode

Total characters6369
Distinct characters165
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)87.3%

Sample

1st row서울특별시 중랑구 상봉동 83-1
2nd row서울특별시 중랑구 상봉동 83 상봉시외버스터미널
3rd row서울특별시 중랑구 묵동 245-6
4th row서울특별시 중랑구 묵동 244-117
5th row서울특별시 중랑구 면목동 149-6
ValueCountFrequency (%)
서울특별시 275
21.9%
중랑구 275
21.9%
면목동 79
 
6.3%
상봉동 43
 
3.4%
신내동 41
 
3.3%
중화동 39
 
3.1%
망우동 38
 
3.0%
묵동 35
 
2.8%
262-1 7
 
0.6%
지상1층 6
 
0.5%
Other values (334) 416
33.2%
2024-05-11T17:11:19.933651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1182
18.6%
317
 
5.0%
1 300
 
4.7%
289
 
4.5%
279
 
4.4%
277
 
4.3%
276
 
4.3%
275
 
4.3%
275
 
4.3%
275
 
4.3%
Other values (155) 2624
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3541
55.6%
Decimal Number 1375
 
21.6%
Space Separator 1182
 
18.6%
Dash Punctuation 241
 
3.8%
Lowercase Letter 12
 
0.2%
Uppercase Letter 11
 
0.2%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
317
 
9.0%
289
 
8.2%
279
 
7.9%
277
 
7.8%
276
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
81
 
2.3%
Other values (129) 922
26.0%
Decimal Number
ValueCountFrequency (%)
1 300
21.8%
2 173
12.6%
4 167
12.1%
3 162
11.8%
0 128
9.3%
6 111
 
8.1%
5 101
 
7.3%
7 91
 
6.6%
8 82
 
6.0%
9 60
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
A 2
18.2%
V 2
18.2%
K 2
18.2%
Y 1
 
9.1%
M 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
r 2
16.7%
t 2
16.7%
n 2
16.7%
c 2
16.7%
Space Separator
ValueCountFrequency (%)
1182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 241
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3541
55.6%
Common 2805
44.0%
Latin 23
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
317
 
9.0%
289
 
8.2%
279
 
7.9%
277
 
7.8%
276
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
81
 
2.3%
Other values (129) 922
26.0%
Common
ValueCountFrequency (%)
1182
42.1%
1 300
 
10.7%
- 241
 
8.6%
2 173
 
6.2%
4 167
 
6.0%
3 162
 
5.8%
0 128
 
4.6%
6 111
 
4.0%
5 101
 
3.6%
7 91
 
3.2%
Other values (5) 149
 
5.3%
Latin
ValueCountFrequency (%)
e 4
17.4%
S 3
13.0%
r 2
8.7%
A 2
8.7%
t 2
8.7%
n 2
8.7%
c 2
8.7%
V 2
8.7%
K 2
8.7%
Y 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3541
55.6%
ASCII 2828
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1182
41.8%
1 300
 
10.6%
- 241
 
8.5%
2 173
 
6.1%
4 167
 
5.9%
3 162
 
5.7%
0 128
 
4.5%
6 111
 
3.9%
5 101
 
3.6%
7 91
 
3.2%
Other values (16) 172
 
6.1%
Hangul
ValueCountFrequency (%)
317
 
9.0%
289
 
8.2%
279
 
7.9%
277
 
7.8%
276
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
275
 
7.8%
81
 
2.3%
Other values (129) 922
26.0%

도로명주소
Text

MISSING 

Distinct185
Distinct (%)96.4%
Missing83
Missing (%)30.2%
Memory size2.3 KiB
2024-05-11T17:11:20.212939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length46
Mean length33.026042
Min length22

Characters and Unicode

Total characters6341
Distinct characters189
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)93.2%

Sample

1st row서울특별시 중랑구 상봉로 117 (상봉동)
2nd row서울특별시 중랑구 상봉로 117, 상봉시외버스터미널 지하1층 (상봉동)
3rd row서울특별시 중랑구 신내역로 213, 3층 305호 (신내동)
4th row서울특별시 중랑구 공릉로 77, 2층 201호 (묵동)
5th row서울특별시 중랑구 동일로143길 19 (중화동, 4층 406호)
ValueCountFrequency (%)
서울특별시 192
 
15.5%
중랑구 192
 
15.5%
면목동 48
 
3.9%
1층 32
 
2.6%
상봉동 29
 
2.3%
신내동 28
 
2.3%
망우동 26
 
2.1%
중화동 25
 
2.0%
묵동 23
 
1.9%
3층 16
 
1.3%
Other values (361) 631
50.8%
2024-05-11T17:11:20.930330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1050
 
16.6%
1 287
 
4.5%
257
 
4.1%
253
 
4.0%
217
 
3.4%
198
 
3.1%
193
 
3.0%
192
 
3.0%
192
 
3.0%
192
 
3.0%
Other values (179) 3310
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3570
56.3%
Decimal Number 1096
 
17.3%
Space Separator 1050
 
16.6%
Open Punctuation 192
 
3.0%
Close Punctuation 192
 
3.0%
Other Punctuation 179
 
2.8%
Dash Punctuation 27
 
0.4%
Uppercase Letter 21
 
0.3%
Lowercase Letter 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
257
 
7.2%
253
 
7.1%
217
 
6.1%
198
 
5.5%
193
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
Other values (148) 1492
41.8%
Decimal Number
ValueCountFrequency (%)
1 287
26.2%
3 148
13.5%
2 122
11.1%
0 106
 
9.7%
4 97
 
8.9%
5 83
 
7.6%
6 70
 
6.4%
8 64
 
5.8%
9 62
 
5.7%
7 57
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
A 7
33.3%
S 3
14.3%
R 2
 
9.5%
B 2
 
9.5%
K 2
 
9.5%
V 2
 
9.5%
D 1
 
4.8%
M 1
 
4.8%
Y 1
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 4
28.6%
c 2
14.3%
n 2
14.3%
t 2
14.3%
r 2
14.3%
b 1
 
7.1%
s 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1050
100.0%
Open Punctuation
ValueCountFrequency (%)
( 192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Other Punctuation
ValueCountFrequency (%)
, 179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3570
56.3%
Common 2736
43.1%
Latin 35
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
257
 
7.2%
253
 
7.1%
217
 
6.1%
198
 
5.5%
193
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
Other values (148) 1492
41.8%
Latin
ValueCountFrequency (%)
A 7
20.0%
e 4
11.4%
S 3
8.6%
R 2
 
5.7%
B 2
 
5.7%
c 2
 
5.7%
K 2
 
5.7%
V 2
 
5.7%
n 2
 
5.7%
t 2
 
5.7%
Other values (6) 7
20.0%
Common
ValueCountFrequency (%)
1050
38.4%
1 287
 
10.5%
( 192
 
7.0%
) 192
 
7.0%
, 179
 
6.5%
3 148
 
5.4%
2 122
 
4.5%
0 106
 
3.9%
4 97
 
3.5%
5 83
 
3.0%
Other values (5) 280
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3570
56.3%
ASCII 2771
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1050
37.9%
1 287
 
10.4%
( 192
 
6.9%
) 192
 
6.9%
, 179
 
6.5%
3 148
 
5.3%
2 122
 
4.4%
0 106
 
3.8%
4 97
 
3.5%
5 83
 
3.0%
Other values (21) 315
 
11.4%
Hangul
ValueCountFrequency (%)
257
 
7.2%
253
 
7.1%
217
 
6.1%
198
 
5.5%
193
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
192
 
5.4%
Other values (148) 1492
41.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)55.8%
Missing85
Missing (%)30.9%
Infinite0
Infinite (%)0.0%
Mean2108.9526
Minimum2001
Maximum2262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:21.072889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2008.45
Q12048
median2110.5
Q32166
95-th percentile2235.2
Maximum2262
Range261
Interquartile range (IQR)118

Descriptive statistics

Standard deviation73.914457
Coefficient of variation (CV)0.035047946
Kurtosis-1.0806142
Mean2108.9526
Median Absolute Deviation (MAD)62
Skewness0.27677498
Sum400701
Variance5463.347
MonotonicityNot monotonic
2024-05-11T17:11:21.220951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2055 8
 
2.9%
2118 6
 
2.2%
2024 6
 
2.2%
2048 5
 
1.8%
2014 5
 
1.8%
2122 5
 
1.8%
2163 4
 
1.5%
2180 4
 
1.5%
2050 4
 
1.5%
2151 4
 
1.5%
Other values (96) 139
50.5%
(Missing) 85
30.9%
ValueCountFrequency (%)
2001 1
 
0.4%
2003 2
0.7%
2004 2
0.7%
2005 1
 
0.4%
2006 1
 
0.4%
2007 2
0.7%
2008 1
 
0.4%
2009 3
1.1%
2010 1
 
0.4%
2011 1
 
0.4%
ValueCountFrequency (%)
2262 2
0.7%
2260 1
0.4%
2259 1
0.4%
2252 1
0.4%
2246 2
0.7%
2244 1
0.4%
2243 1
0.4%
2237 1
0.4%
2233 1
0.4%
2227 2
0.7%
Distinct266
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T17:11:21.495833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length13
Mean length7.3345455
Min length2

Characters and Unicode

Total characters2017
Distinct characters275
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)93.8%

Sample

1st row(주)신한공사
2nd row(주)신한공사
3rd row영창흥업주식회사
4th row삼덕시스템(주)
5th row현대저수조용역
ValueCountFrequency (%)
주식회사 28
 
8.7%
봉화크린환경 3
 
0.9%
주)신한공사 2
 
0.6%
사단법인 2
 
0.6%
주)엠케이터치크린 2
 
0.6%
서비스 2
 
0.6%
시스템 2
 
0.6%
클린 2
 
0.6%
365크린 2
 
0.6%
무진클린 2
 
0.6%
Other values (271) 274
85.4%
2024-05-11T17:11:21.879783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
7.8%
( 126
 
6.2%
) 126
 
6.2%
56
 
2.8%
53
 
2.6%
52
 
2.6%
51
 
2.5%
46
 
2.3%
39
 
1.9%
34
 
1.7%
Other values (265) 1277
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1692
83.9%
Open Punctuation 126
 
6.2%
Close Punctuation 126
 
6.2%
Space Separator 46
 
2.3%
Uppercase Letter 18
 
0.9%
Decimal Number 7
 
0.3%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
157
 
9.3%
56
 
3.3%
53
 
3.1%
52
 
3.1%
51
 
3.0%
39
 
2.3%
34
 
2.0%
33
 
2.0%
32
 
1.9%
31
 
1.8%
Other values (245) 1154
68.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
C 3
16.7%
M 2
11.1%
B 2
11.1%
K 1
 
5.6%
J 1
 
5.6%
N 1
 
5.6%
E 1
 
5.6%
G 1
 
5.6%
L 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
3 3
42.9%
5 2
28.6%
6 2
28.6%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
i 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1692
83.9%
Common 305
 
15.1%
Latin 20
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
157
 
9.3%
56
 
3.3%
53
 
3.1%
52
 
3.1%
51
 
3.0%
39
 
2.3%
34
 
2.0%
33
 
2.0%
32
 
1.9%
31
 
1.8%
Other values (245) 1154
68.2%
Latin
ValueCountFrequency (%)
S 3
15.0%
C 3
15.0%
M 2
10.0%
B 2
10.0%
n 1
 
5.0%
i 1
 
5.0%
K 1
 
5.0%
J 1
 
5.0%
N 1
 
5.0%
E 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
( 126
41.3%
) 126
41.3%
46
 
15.1%
3 3
 
1.0%
5 2
 
0.7%
6 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1692
83.9%
ASCII 325
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
157
 
9.3%
56
 
3.3%
53
 
3.1%
52
 
3.1%
51
 
3.0%
39
 
2.3%
34
 
2.0%
33
 
2.0%
32
 
1.9%
31
 
1.8%
Other values (245) 1154
68.2%
ASCII
ValueCountFrequency (%)
( 126
38.8%
) 126
38.8%
46
 
14.2%
3 3
 
0.9%
S 3
 
0.9%
C 3
 
0.9%
M 2
 
0.6%
B 2
 
0.6%
5 2
 
0.6%
6 2
 
0.6%
Other values (10) 10
 
3.1%
Distinct245
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2001-10-04 00:00:00
Maximum2024-04-16 14:03:55
2024-05-11T17:11:22.010802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:11:22.148089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
I
193 
U
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 193
70.2%
U 82
29.8%

Length

2024-05-11T17:11:22.281598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:22.383637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 193
70.2%
u 82
29.8%
Distinct108
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-05-11T17:11:22.492660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:11:22.626807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
건물위생관리업
274 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0109091
Min length7

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 274
99.6%
건물위생관리업 기타 1
 
0.4%

Length

2024-05-11T17:11:22.773500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:22.876370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 275
99.6%
기타 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct216
Distinct (%)79.7%
Missing4
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean207655.84
Minimum206257.37
Maximum209856.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:22.997483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206257.37
5-th percentile206464.08
Q1206909.95
median207583.25
Q3208295.1
95-th percentile209085.93
Maximum209856.12
Range3598.7415
Interquartile range (IQR)1385.1538

Descriptive statistics

Standard deviation845.34762
Coefficient of variation (CV)0.0040709071
Kurtosis-0.92351537
Mean207655.84
Median Absolute Deviation (MAD)697.88587
Skewness0.29816184
Sum56274732
Variance714612.6
MonotonicityNot monotonic
2024-05-11T17:11:23.157887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209085.926142332 7
 
2.5%
207990.479257211 5
 
1.8%
206788.048632489 5
 
1.8%
208295.099818379 4
 
1.5%
206988.452084227 3
 
1.1%
208185.587866215 3
 
1.1%
207661.4483404 3
 
1.1%
208269.433219878 3
 
1.1%
208057.437370858 3
 
1.1%
207265.548012042 3
 
1.1%
Other values (206) 232
84.4%
(Missing) 4
 
1.5%
ValueCountFrequency (%)
206257.374608034 1
0.4%
206282.069944454 1
0.4%
206315.621494545 2
0.7%
206328.066671402 1
0.4%
206345.47354923 2
0.7%
206383.897778215 2
0.7%
206404.41703852 1
0.4%
206438.692517058 1
0.4%
206444.373964952 1
0.4%
206448.314200373 1
0.4%
ValueCountFrequency (%)
209856.1161416 2
 
0.7%
209438.885311392 1
 
0.4%
209376.610753394 1
 
0.4%
209354.835874679 1
 
0.4%
209334.242134459 1
 
0.4%
209200.036845418 1
 
0.4%
209136.214507305 1
 
0.4%
209116.981356523 2
 
0.7%
209103.13902339 1
 
0.4%
209085.926142332 7
2.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct216
Distinct (%)79.7%
Missing4
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean455123.76
Minimum452269.92
Maximum457438.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:23.296539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452269.92
5-th percentile453227.88
Q1454232.83
median455042.98
Q3455915.66
95-th percentile457183.64
Maximum457438.91
Range5168.9897
Interquartile range (IQR)1682.8245

Descriptive statistics

Standard deviation1217.5314
Coefficient of variation (CV)0.0026751655
Kurtosis-0.75989312
Mean455123.76
Median Absolute Deviation (MAD)839.70516
Skewness0.058218791
Sum1.2333854 × 108
Variance1482382.6
MonotonicityNot monotonic
2024-05-11T17:11:23.431201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457283.215342184 7
 
2.5%
457183.637796144 5
 
1.8%
455850.935638819 5
 
1.8%
456014.999180519 4
 
1.5%
454636.535002113 3
 
1.1%
455005.951408018 3
 
1.1%
455671.574410523 3
 
1.1%
457021.162035231 3
 
1.1%
454845.243765481 3
 
1.1%
453869.73876459 3
 
1.1%
Other values (206) 232
84.4%
(Missing) 4
 
1.5%
ValueCountFrequency (%)
452269.920040532 1
0.4%
452543.846521132 1
0.4%
452596.829793311 1
0.4%
452653.903398494 1
0.4%
452666.306495265 1
0.4%
452898.678301479 1
0.4%
452919.770174065 1
0.4%
452953.151332981 2
0.7%
452991.036422095 1
0.4%
453016.520719267 1
0.4%
ValueCountFrequency (%)
457438.909754748 1
 
0.4%
457302.240283913 1
 
0.4%
457283.215342184 7
2.5%
457225.567456607 1
 
0.4%
457224.572523308 1
 
0.4%
457219.369142777 1
 
0.4%
457183.637796144 5
1.8%
457113.638411288 2
 
0.7%
457087.081125398 1
 
0.4%
457086.600082519 1
 
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
건물위생관리업
218 
<NA>
56 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.4
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 218
79.3%
<NA> 56
 
20.4%
건물위생관리업 기타 1
 
0.4%

Length

2024-05-11T17:11:23.568618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:23.674311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 219
79.3%
na 56
 
20.3%
기타 1
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.9%
Missing91
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean0.72826087
Minimum0
Maximum12
Zeros148
Zeros (%)53.8%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:23.762497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7216288
Coefficient of variation (CV)2.3640276
Kurtosis11.137156
Mean0.72826087
Median Absolute Deviation (MAD)0
Skewness2.9424327
Sum134
Variance2.9640057
MonotonicityNot monotonic
2024-05-11T17:11:23.881589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 148
53.8%
3 12
 
4.4%
5 8
 
2.9%
2 5
 
1.8%
4 5
 
1.8%
1 3
 
1.1%
12 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
(Missing) 91
33.1%
ValueCountFrequency (%)
0 148
53.8%
1 3
 
1.1%
2 5
 
1.8%
3 12
 
4.4%
4 5
 
1.8%
5 8
 
2.9%
6 1
 
0.4%
7 1
 
0.4%
12 1
 
0.4%
ValueCountFrequency (%)
12 1
 
0.4%
7 1
 
0.4%
6 1
 
0.4%
5 8
 
2.9%
4 5
 
1.8%
3 12
 
4.4%
2 5
 
1.8%
1 3
 
1.1%
0 148
53.8%
Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
169 
<NA>
97 
1
 
9

Length

Max length4
Median length1
Mean length2.0581818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 169
61.5%
<NA> 97
35.3%
1 9
 
3.3%

Length

2024-05-11T17:11:24.006058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:24.104205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
61.5%
na 97
35.3%
1 9
 
3.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)7.6%
Missing104
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean6.7192982
Minimum0
Maximum803
Zeros48
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:24.191612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum803
Range803
Interquartile range (IQR)3

Descriptive statistics

Standard deviation61.299387
Coefficient of variation (CV)9.1228853
Kurtosis170.45455
Mean6.7192982
Median Absolute Deviation (MAD)1
Skewness13.045743
Sum1149
Variance3757.6149
MonotonicityNot monotonic
2024-05-11T17:11:24.319346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 48
17.5%
1 43
15.6%
3 28
 
10.2%
2 22
 
8.0%
4 12
 
4.4%
5 8
 
2.9%
9 3
 
1.1%
6 2
 
0.7%
803 1
 
0.4%
14 1
 
0.4%
Other values (3) 3
 
1.1%
(Missing) 104
37.8%
ValueCountFrequency (%)
0 48
17.5%
1 43
15.6%
2 22
8.0%
3 28
10.2%
4 12
 
4.4%
5 8
 
2.9%
6 2
 
0.7%
8 1
 
0.4%
9 3
 
1.1%
10 1
 
0.4%
ValueCountFrequency (%)
803 1
 
0.4%
16 1
 
0.4%
14 1
 
0.4%
10 1
 
0.4%
9 3
 
1.1%
8 1
 
0.4%
6 2
 
0.7%
5 8
 
2.9%
4 12
4.4%
3 28
10.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)20.4%
Missing167
Missing (%)60.7%
Infinite0
Infinite (%)0.0%
Mean31.731481
Minimum0
Maximum803
Zeros13
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T17:11:24.454803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile273.35
Maximum803
Range803
Interquartile range (IQR)3

Descriptive statistics

Standard deviation109.13651
Coefficient of variation (CV)3.4393764
Kurtosis26.71426
Mean31.731481
Median Absolute Deviation (MAD)2
Skewness4.7981878
Sum3427
Variance11910.778
MonotonicityNot monotonic
2024-05-11T17:11:24.577374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 27
 
9.8%
3 23
 
8.4%
0 13
 
4.7%
2 13
 
4.7%
4 8
 
2.9%
5 5
 
1.8%
9 3
 
1.1%
6 2
 
0.7%
503 1
 
0.4%
8 1
 
0.4%
Other values (12) 12
 
4.4%
(Missing) 167
60.7%
ValueCountFrequency (%)
0 13
4.7%
1 27
9.8%
2 13
4.7%
3 23
8.4%
4 8
 
2.9%
5 5
 
1.8%
6 2
 
0.7%
8 1
 
0.4%
9 3
 
1.1%
10 1
 
0.4%
ValueCountFrequency (%)
803 1
0.4%
503 1
0.4%
309 1
0.4%
307 1
0.4%
302 1
0.4%
301 1
0.4%
222 1
0.4%
201 1
0.4%
108 1
0.4%
105 1
0.4%
Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
192 
0
63 
1
 
19
3
 
1

Length

Max length4
Median length4
Mean length3.0945455
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 192
69.8%
0 63
 
22.9%
1 19
 
6.9%
3 1
 
0.4%

Length

2024-05-11T17:11:24.723607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:24.823655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 192
69.8%
0 63
 
22.9%
1 19
 
6.9%
3 1
 
0.4%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
236 
0
27 
1
 
9
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.5745455
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 236
85.8%
0 27
 
9.8%
1 9
 
3.3%
2 2
 
0.7%
4 1
 
0.4%

Length

2024-05-11T17:11:24.925896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:25.023296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 236
85.8%
0 27
 
9.8%
1 9
 
3.3%
2 2
 
0.7%
4 1
 
0.4%

한실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
173 
<NA>
102 

Length

Max length4
Median length1
Mean length2.1127273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 173
62.9%
<NA> 102
37.1%

Length

2024-05-11T17:11:25.167803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:25.268035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 173
62.9%
na 102
37.1%

양실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
173 
<NA>
102 

Length

Max length4
Median length1
Mean length2.1127273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 173
62.9%
<NA> 102
37.1%

Length

2024-05-11T17:11:25.374431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:25.477282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 173
62.9%
na 102
37.1%

욕실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
173 
<NA>
102 

Length

Max length4
Median length1
Mean length2.1127273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 173
62.9%
<NA> 102
37.1%

Length

2024-05-11T17:11:25.582975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:25.678899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 173
62.9%
na 102
37.1%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.9%
Missing61
Missing (%)22.2%
Memory size682.0 B
False
213 
True
 
1
(Missing)
61 
ValueCountFrequency (%)
False 213
77.5%
True 1
 
0.4%
(Missing) 61
 
22.2%
2024-05-11T17:11:25.805204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
173 
<NA>
102 

Length

Max length4
Median length1
Mean length2.1127273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 173
62.9%
<NA> 102
37.1%

Length

2024-05-11T17:11:25.925912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:26.034632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 173
62.9%
na 102
37.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
236 
임대
37 
자가
 
2

Length

Max length4
Median length4
Mean length3.7163636
Min length2

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> 236
85.8%
임대 37
 
13.5%
자가 2
 
0.7%

Length

2024-05-11T17:11:26.163780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:26.272598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 236
85.8%
임대 37
 
13.5%
자가 2
 
0.7%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
138 
0
137 

Length

Max length4
Median length4
Mean length2.5054545
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> 138
50.2%
0 137
49.8%

Length

2024-05-11T17:11:26.376645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:26.483300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 138
50.2%
0 137
49.8%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
216 
0
49 
1
 
8
2
 
1
31
 
1

Length

Max length4
Median length4
Mean length3.36
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
78.5%
0 49
 
17.8%
1 8
 
2.9%
2 1
 
0.4%
31 1
 
0.4%

Length

2024-05-11T17:11:26.576452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:26.684701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
78.5%
0 49
 
17.8%
1 8
 
2.9%
2 1
 
0.4%
31 1
 
0.4%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
216 
0
44 
1
 
12
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.3563636
Min length1

Unique

Unique3 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
78.5%
0 44
 
16.0%
1 12
 
4.4%
2 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%

Length

2024-05-11T17:11:26.789178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:26.889655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
78.5%
0 44
 
16.0%
1 12
 
4.4%
2 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
148 
0
127 

Length

Max length4
Median length4
Mean length2.6145455
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> 148
53.8%
0 127
46.2%

Length

2024-05-11T17:11:27.296319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:27.417985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
53.8%
0 127
46.2%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
151 
0
124 

Length

Max length4
Median length4
Mean length2.6472727
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> 151
54.9%
0 124
45.1%

Length

2024-05-11T17:11:27.531936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:11:27.633451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
54.9%
0 124
45.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing56
Missing (%)20.4%
Memory size682.0 B
False
219 
(Missing)
56 
ValueCountFrequency (%)
False 219
79.6%
(Missing) 56
 
20.4%
2024-05-11T17:11:27.723668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030600003060000-206-1987-0241119871221<NA>3폐업2폐업20171228<NA><NA><NA>02 4964383498.74131858서울특별시 중랑구 상봉동 83-1서울특별시 중랑구 상봉로 117 (상봉동)2151(주)신한공사2017-12-28 14:11:22I2018-08-31 23:59:59.0건물위생관리업208057.437371454845.243765건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130600003060000-206-1987-0241219871221<NA>3폐업2폐업20200116<NA><NA><NA>02 4964383198.86131858서울특별시 중랑구 상봉동 83 상봉시외버스터미널서울특별시 중랑구 상봉로 117, 상봉시외버스터미널 지하1층 (상봉동)2151(주)신한공사2020-01-16 13:31:51U2020-01-18 02:40:00.0건물위생관리업208107.165701454926.717886건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230600003060000-206-1989-0241219891123<NA>3폐업2폐업19991015<NA><NA><NA>0209771657.00131853서울특별시 중랑구 묵동 245-6<NA><NA>영창흥업주식회사2002-01-31 00:00:00I2018-08-31 23:59:59.0건물위생관리업206821.108968456096.359567건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330600003060000-206-1991-0241419910824<NA>3폐업2폐업19930625<NA><NA><NA>020972542097.50131852서울특별시 중랑구 묵동 244-117<NA><NA>삼덕시스템(주)2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업206678.212185456372.652149건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430600003060000-206-1992-0241619920313<NA>3폐업2폐업19950124<NA><NA><NA>0204390291.00131821서울특별시 중랑구 면목동 149-6<NA><NA>현대저수조용역2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업207265.548012453869.738765건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530600003060000-206-1992-0241819921205<NA>3폐업2폐업19950601<NA><NA><NA>02 4382266307.15131811서울특별시 중랑구 면목동 23-11<NA><NA>성산실업2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업208236.442292454120.357484건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630600003060000-206-1992-0241919921106<NA>3폐업2폐업20051222<NA><NA><NA>02 435 633069.30131811서울특별시 중랑구 면목동 14-1<NA><NA>창영산업관리2004-11-16 00:00:00I2018-08-31 23:59:59.0건물위생관리업208575.031469454065.010277건물위생관리업3<NA>33<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730600003060000-206-1993-0241319930421<NA>1영업/정상1영업<NA><NA><NA><NA>0209740162184.22131865서울특별시 중랑구 신내동 255-1서울특별시 중랑구 신내역로 213, 3층 305호 (신내동)2055(주)동명환경2022-04-20 16:36:02U2021-12-03 22:02:00.0건물위생관리업209334.242134457438.909755<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830600003060000-206-1993-0241519930714<NA>3폐업2폐업19970217<NA><NA><NA>0209718253.00131852서울특별시 중랑구 묵동 239-131<NA><NA>연성기업2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업206647.407139456550.047771건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930600003060000-206-1993-0242119930903<NA>3폐업2폐업19950126<NA><NA><NA>0202090400294.00131861서울특별시 중랑구 상봉동 128-9<NA><NA>홀덴무역개발2001-10-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업206988.452084454636.535002건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
26530600003060000-206-2022-000172022-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>64.02131-880서울특별시 중랑구 중화동 317-14서울특별시 중랑구 동일로123길 79-4 (중화동)2106형우씨엠(CM)2024-01-05 15:48:17I2023-12-01 00:07:00.0건물위생관리업206610.000097455159.111332<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26630600003060000-206-2023-0000120230104<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.30131803서울특별시 중랑구 망우동 343-1서울특별시 중랑구 망우로73길 31, 1층 103호 (망우동)2060나눔클린2023-01-04 17:09:46I2022-12-01 00:06:00.0건물위생관리업209042.420842455518.700423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26730600003060000-206-2023-0000220230111<NA>1영업/정상1영업<NA><NA><NA><NA><NA>146.07131801서울특별시 중랑구 망우동 450-3 월드레져스포츠서울특별시 중랑구 용마공원로5길 28, 월드레져스포츠 지하1층 (망우동)2180주식회사 다나눔2023-01-11 11:54:37I2022-11-30 23:03:00.0건물위생관리업208997.751243454703.026547<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26830600003060000-206-2023-000032023-04-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.00131-875서울특별시 중랑구 중화동 283-3서울특별시 중랑구 동일로 838, 1층 다솜공인중개사무소 일부호 (중화동)2047쓱싹기동대2023-04-27 16:15:22I2022-12-03 22:09:00.0건물위생관리업206921.807525455888.451631<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26930600003060000-206-2023-000042023-06-22<NA>3폐업2폐업2024-04-16<NA><NA><NA>02 978901062.56131-851서울특별시 중랑구 묵동 233-12 파랑새피아노서울특별시 중랑구 중랑역로 243, 파랑새피아노 201호 (묵동)2001주식회사 라인탑2024-04-16 14:03:55U2023-12-03 23:08:00.0건물위생관리업206583.974772456986.82816<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27030600003060000-206-2023-000052023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.02131-865서울특별시 중랑구 신내동 262-1 신내 데시앙플렉스 지식산업센터서울특별시 중랑구 신내역로3길 40-36, 신내 데시앙플렉스 지식산업센터 B동 902호 (신내동)2055주식회사 예가컴퍼니2023-09-01 09:52:09I2022-12-09 00:03:00.0건물위생관리업209085.926142457283.215342<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27130600003060000-206-2023-000062023-09-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.50131-830서울특별시 중랑구 면목동 374-13 송광카센타서울특별시 중랑구 면목로27길 32, 송광카센타 1층 (면목동)2244청소일번지2023-09-26 14:56:40I2022-12-08 22:08:00.0건물위생관리업207309.282505452543.846521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27230600003060000-206-2023-000072023-10-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.00131-802서울특별시 중랑구 망우동 136-19서울특별시 중랑구 망우로81길 18, 지하1층 (망우동)2064정성클린2023-10-04 11:58:42I2022-10-31 00:06:00.0건물위생관리업209438.885311455455.433742<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27330600003060000-206-2024-000012024-01-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30131-853서울특별시 중랑구 묵동 245-6서울특별시 중랑구 동일로 859, 가동 2층 D-126호 (묵동)2010대일이엔씨2024-01-16 11:08:28I2023-11-30 23:08:00.0건물위생관리업206821.108968456096.359567<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27430600003060000-206-2024-000022024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.03131-875서울특별시 중랑구 중화동 1-3 샘물교회서울특별시 중랑구 상봉중앙로5나길 28, 샘물교회 1층 101호 (중화동)2090클린 서비스2024-03-19 13:52:18I2023-12-02 22:01:00.0건물위생관리업207583.252393455472.803343<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>