Overview

Dataset statistics

Number of variables47
Number of observations304
Missing cells3116
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory120.4 KiB
Average record size in memory405.4 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19282/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (82.4%)Imbalance
건물소유구분명 is highly imbalanced (53.0%)Imbalance
여성종사자수 is highly imbalanced (54.0%)Imbalance
남성종사자수 is highly imbalanced (66.8%)Imbalance
인허가취소일자 has 304 (100.0%) missing valuesMissing
폐업일자 has 97 (31.9%) missing valuesMissing
휴업시작일자 has 304 (100.0%) missing valuesMissing
휴업종료일자 has 304 (100.0%) missing valuesMissing
재개업일자 has 304 (100.0%) missing valuesMissing
전화번호 has 113 (37.2%) missing valuesMissing
도로명주소 has 76 (25.0%) missing valuesMissing
도로명우편번호 has 83 (27.3%) missing valuesMissing
건물지상층수 has 123 (40.5%) missing valuesMissing
사용시작지상층 has 150 (49.3%) missing valuesMissing
사용끝지상층 has 147 (48.4%) missing valuesMissing
발한실여부 has 98 (32.2%) missing valuesMissing
조건부허가신고사유 has 304 (100.0%) missing valuesMissing
조건부허가시작일자 has 304 (100.0%) missing valuesMissing
조건부허가종료일자 has 304 (100.0%) missing valuesMissing
다중이용업소여부 has 89 (29.3%) 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
소재지면적 has 6 (2.0%) zerosZeros
건물지상층수 has 117 (38.5%) zerosZeros
사용시작지상층 has 17 (5.6%) zerosZeros
사용끝지상층 has 20 (6.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:48:55.578578
Analysis finished2024-05-11 06:48:56.400508
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
3050000
304 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 304
100.0%

Length

2024-05-11T15:48:56.462879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:56.561556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 304
100.0%

관리번호
Text

UNIQUE 

Distinct304
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T15:48:56.782260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6688
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

Unique304 ?
Unique (%)100.0%

Sample

1st row3050000-206-1987-00001
2nd row3050000-206-1991-02933
3rd row3050000-206-1991-02934
4th row3050000-206-1992-02871
5th row3050000-206-1993-02880
ValueCountFrequency (%)
3050000-206-1987-00001 1
 
0.3%
3050000-206-2014-00009 1
 
0.3%
3050000-206-2015-00003 1
 
0.3%
3050000-206-2015-00002 1
 
0.3%
3050000-206-2015-00001 1
 
0.3%
3050000-206-2014-00014 1
 
0.3%
3050000-206-2014-00013 1
 
0.3%
3050000-206-2014-00012 1
 
0.3%
3050000-206-2014-00011 1
 
0.3%
3050000-206-1991-02933 1
 
0.3%
Other values (294) 294
96.7%
2024-05-11T15:48:57.128282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3331
49.8%
- 912
 
13.6%
2 713
 
10.7%
3 397
 
5.9%
5 366
 
5.5%
6 363
 
5.4%
1 311
 
4.7%
9 111
 
1.7%
4 67
 
1.0%
8 62
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5776
86.4%
Dash Punctuation 912
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3331
57.7%
2 713
 
12.3%
3 397
 
6.9%
5 366
 
6.3%
6 363
 
6.3%
1 311
 
5.4%
9 111
 
1.9%
4 67
 
1.2%
8 62
 
1.1%
7 55
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3331
49.8%
- 912
 
13.6%
2 713
 
10.7%
3 397
 
5.9%
5 366
 
5.5%
6 363
 
5.4%
1 311
 
4.7%
9 111
 
1.7%
4 67
 
1.0%
8 62
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3331
49.8%
- 912
 
13.6%
2 713
 
10.7%
3 397
 
5.9%
5 366
 
5.5%
6 363
 
5.4%
1 311
 
4.7%
9 111
 
1.7%
4 67
 
1.0%
8 62
 
0.9%

인허가일자
Date

Distinct283
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum1987-08-04 00:00:00
Maximum2024-01-17 00:00:00
2024-05-11T15:48:57.290419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:48:57.448658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
3
207 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 207
68.1%
1 97
31.9%

Length

2024-05-11T15:48:57.599918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:57.739388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 207
68.1%
1 97
31.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
폐업
207 
영업/정상
97 

Length

Max length5
Median length2
Mean length2.9572368
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 207
68.1%
영업/정상 97
31.9%

Length

2024-05-11T15:48:57.864737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:57.973488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 207
68.1%
영업/정상 97
31.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2
207 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 207
68.1%
1 97
31.9%

Length

2024-05-11T15:48:58.087835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:58.197683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 207
68.1%
1 97
31.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
폐업
207 
영업
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 207
68.1%
영업 97
31.9%

Length

2024-05-11T15:48:58.306423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:48:58.420568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 207
68.1%
영업 97
31.9%

폐업일자
Date

MISSING 

Distinct195
Distinct (%)94.2%
Missing97
Missing (%)31.9%
Memory size2.5 KiB
Minimum2003-03-20 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T15:48:58.532826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:48:58.677647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

전화번호
Text

MISSING 

Distinct182
Distinct (%)95.3%
Missing113
Missing (%)37.2%
Memory size2.5 KiB
2024-05-11T15:48:58.965862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.350785
Min length8

Characters and Unicode

Total characters1977
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

Unique174 ?
Unique (%)91.1%

Sample

1st row02 7941674
2nd row02 9239557
3rd row02 7792270
4th row02 9234768
5th row0222158333
ValueCountFrequency (%)
02 77
 
26.0%
070 5
 
1.7%
0222431366 3
 
1.0%
0222483100 2
 
0.7%
02960 2
 
0.7%
0222172233 2
 
0.7%
22158545 2
 
0.7%
0222486350 2
 
0.7%
0222433011 2
 
0.7%
0222152250 2
 
0.7%
Other values (195) 197
66.6%
2024-05-11T15:48:59.467331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 502
25.4%
0 316
16.0%
3 163
 
8.2%
4 152
 
7.7%
1 147
 
7.4%
135
 
6.8%
9 129
 
6.5%
7 125
 
6.3%
5 119
 
6.0%
6 97
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1842
93.2%
Space Separator 135
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 502
27.3%
0 316
17.2%
3 163
 
8.8%
4 152
 
8.3%
1 147
 
8.0%
9 129
 
7.0%
7 125
 
6.8%
5 119
 
6.5%
6 97
 
5.3%
8 92
 
5.0%
Space Separator
ValueCountFrequency (%)
135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 502
25.4%
0 316
16.0%
3 163
 
8.2%
4 152
 
7.7%
1 147
 
7.4%
135
 
6.8%
9 129
 
6.5%
7 125
 
6.3%
5 119
 
6.0%
6 97
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 502
25.4%
0 316
16.0%
3 163
 
8.2%
4 152
 
7.7%
1 147
 
7.4%
135
 
6.8%
9 129
 
6.5%
7 125
 
6.3%
5 119
 
6.0%
6 97
 
4.9%

소재지면적
Real number (ℝ)

ZEROS 

Distinct202
Distinct (%)66.9%
Missing2
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean68.469768
Minimum0
Maximum997.56
Zeros6
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:48:59.654366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q129.61
median49.5
Q378.29
95-th percentile164.898
Maximum997.56
Range997.56
Interquartile range (IQR)48.68

Descriptive statistics

Standard deviation92.136702
Coefficient of variation (CV)1.3456552
Kurtosis63.360948
Mean68.469768
Median Absolute Deviation (MAD)22.97
Skewness6.9395545
Sum20677.87
Variance8489.1718
MonotonicityNot monotonic
2024-05-11T15:48:59.818985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 25
 
8.2%
66.0 13
 
4.3%
49.5 12
 
3.9%
60.0 10
 
3.3%
30.0 8
 
2.6%
50.0 7
 
2.3%
0.0 6
 
2.0%
99.0 5
 
1.6%
16.5 4
 
1.3%
24.0 3
 
1.0%
Other values (192) 209
68.8%
ValueCountFrequency (%)
0.0 6
2.0%
3.3 1
 
0.3%
6.0 2
 
0.7%
6.6 1
 
0.3%
8.0 1
 
0.3%
10.0 1
 
0.3%
11.1 1
 
0.3%
11.6 1
 
0.3%
11.84 1
 
0.3%
12.0 2
 
0.7%
ValueCountFrequency (%)
997.56 1
0.3%
960.76 1
0.3%
412.68 1
0.3%
362.99 1
0.3%
342.0 1
0.3%
268.32 1
0.3%
230.18 1
0.3%
222.69 1
0.3%
198.0 1
0.3%
189.78 1
0.3%

소재지우편번호
Text

Distinct80
Distinct (%)26.5%
Missing2
Missing (%)0.7%
Memory size2.5 KiB
2024-05-11T15:49:00.091041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1490066
Min length6

Characters and Unicode

Total characters1857
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

Unique32 ?
Unique (%)10.6%

Sample

1st row130-864
2nd row130824
3rd row130840
4th row130824
5th row130838
ValueCountFrequency (%)
130805 31
 
10.3%
130811 19
 
6.3%
130823 17
 
5.6%
130844 15
 
5.0%
130876 10
 
3.3%
130846 10
 
3.3%
130867 10
 
3.3%
130838 9
 
3.0%
130843 8
 
2.6%
130812 8
 
2.6%
Other values (70) 165
54.6%
2024-05-11T15:49:00.550776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 395
21.3%
1 380
20.5%
3 366
19.7%
8 316
17.0%
4 99
 
5.3%
6 62
 
3.3%
5 61
 
3.3%
2 59
 
3.2%
7 53
 
2.9%
- 45
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1812
97.6%
Dash Punctuation 45
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 395
21.8%
1 380
21.0%
3 366
20.2%
8 316
17.4%
4 99
 
5.5%
6 62
 
3.4%
5 61
 
3.4%
2 59
 
3.3%
7 53
 
2.9%
9 21
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 395
21.3%
1 380
20.5%
3 366
19.7%
8 316
17.0%
4 99
 
5.3%
6 62
 
3.3%
5 61
 
3.3%
2 59
 
3.2%
7 53
 
2.9%
- 45
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 395
21.3%
1 380
20.5%
3 366
19.7%
8 316
17.0%
4 99
 
5.3%
6 62
 
3.3%
5 61
 
3.3%
2 59
 
3.2%
7 53
 
2.9%
- 45
 
2.4%

지번주소
Text

Distinct280
Distinct (%)92.7%
Missing2
Missing (%)0.7%
Memory size2.5 KiB
2024-05-11T15:49:00.942994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length26.688742
Min length16

Characters and Unicode

Total characters8060
Distinct characters191
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

Unique267 ?
Unique (%)88.4%

Sample

1st row서울특별시 동대문구 제기동 1140-4
2nd row서울특별시 동대문구 용두동 759-1
3rd row서울특별시 동대문구 장안동 347-2 (장평8길 10)
4th row서울특별시 동대문구 용두동 739-1
5th row서울특별시 동대문구 장안동 305-6 A동, 지하1층,지상1층
ValueCountFrequency (%)
서울특별시 302
20.0%
동대문구 301
19.9%
장안동 73
 
4.8%
답십리동 64
 
4.2%
용두동 41
 
2.7%
신설동 41
 
2.7%
휘경동 20
 
1.3%
전농동 20
 
1.3%
청량리동 17
 
1.1%
제기동 14
 
0.9%
Other values (421) 617
40.9%
2024-05-11T15:49:01.622827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1402
 
17.4%
동 632
 
7.8%
대 323
 
4.0%
문 312
 
3.9%
서 306
 
3.8%
시 304
 
3.8%
별 302
 
3.7%
특 302
 
3.7%
울 302
 
3.7%
구 302
 
3.7%
Other values (181) 3573
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4515
56.0%
Decimal Number 1734
 
21.5%
Space Separator 1402
 
17.4%
Dash Punctuation 287
 
3.6%
Close Punctuation 43
 
0.5%
Open Punctuation 43
 
0.5%
Uppercase Letter 17
 
0.2%
Lowercase Letter 10
 
0.1%
Other Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 632
14.0%
대 323
 
7.2%
문 312
 
6.9%
서 306
 
6.8%
시 304
 
6.7%
별 302
 
6.7%
특 302
 
6.7%
울 302
 
6.7%
구 302
 
6.7%
호 95
 
2.1%
Other values (149) 1335
29.6%
Decimal Number
ValueCountFrequency (%)
1 294
17.0%
2 240
13.8%
3 230
13.3%
4 201
11.6%
0 183
10.6%
5 155
8.9%
9 142
8.2%
6 112
 
6.5%
8 93
 
5.4%
7 84
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
k 1
10.0%
o 1
10.0%
c 1
10.0%
s 1
10.0%
u 1
10.0%
i 1
10.0%
r 1
10.0%
d 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
35.3%
S 2
 
11.8%
X 2
 
11.8%
J 2
 
11.8%
B 2
 
11.8%
H 1
 
5.9%
R 1
 
5.9%
K 1
 
5.9%
Space Separator
ValueCountFrequency (%)
1402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 287
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4515
56.0%
Common 3518
43.6%
Latin 27
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 632
14.0%
대 323
 
7.2%
문 312
 
6.9%
서 306
 
6.8%
시 304
 
6.7%
별 302
 
6.7%
특 302
 
6.7%
울 302
 
6.7%
구 302
 
6.7%
호 95
 
2.1%
Other values (149) 1335
29.6%
Latin
ValueCountFrequency (%)
A 6
22.2%
S 2
 
7.4%
X 2
 
7.4%
J 2
 
7.4%
B 2
 
7.4%
e 2
 
7.4%
k 1
 
3.7%
H 1
 
3.7%
o 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%
Common
ValueCountFrequency (%)
1402
39.9%
1 294
 
8.4%
- 287
 
8.2%
2 240
 
6.8%
3 230
 
6.5%
4 201
 
5.7%
0 183
 
5.2%
5 155
 
4.4%
9 142
 
4.0%
6 112
 
3.2%
Other values (5) 272
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4515
56.0%
ASCII 3545
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1402
39.5%
1 294
 
8.3%
- 287
 
8.1%
2 240
 
6.8%
3 230
 
6.5%
4 201
 
5.7%
0 183
 
5.2%
5 155
 
4.4%
9 142
 
4.0%
6 112
 
3.2%
Other values (22) 299
 
8.4%
Hangul
ValueCountFrequency (%)
동 632
14.0%
대 323
 
7.2%
문 312
 
6.9%
서 306
 
6.8%
시 304
 
6.7%
별 302
 
6.7%
특 302
 
6.7%
울 302
 
6.7%
구 302
 
6.7%
호 95
 
2.1%
Other values (149) 1335
29.6%

도로명주소
Text

MISSING 

Distinct219
Distinct (%)96.1%
Missing76
Missing (%)25.0%
Memory size2.5 KiB
2024-05-11T15:49:01.927778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length34.798246
Min length24

Characters and Unicode

Total characters7934
Distinct characters202
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)92.1%

Sample

1st row서울특별시 동대문구 약령중앙로 7-4, 2층 (제기동)
2nd row서울특별시 동대문구 안암로16길 14, 2층 (용두동)
3rd row서울특별시 동대문구 장한로27가길 34 (장안동, A동, 지하1층,지상1층)
4th row서울특별시 동대문구 왕산로19다길 7, 302호 (제기동, 동서빌딩)
5th row서울특별시 동대문구 천호대로 385 (장안동)
ValueCountFrequency (%)
서울특별시 228
 
15.0%
동대문구 227
 
14.9%
장안동 50
 
3.3%
답십리동 46
 
3.0%
1층 37
 
2.4%
천호대로 36
 
2.4%
3층 32
 
2.1%
2층 32
 
2.1%
용두동 27
 
1.8%
신설동 25
 
1.6%
Other values (388) 785
51.5%
2024-05-11T15:49:02.440605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1297
 
16.3%
동 491
 
6.2%
대 303
 
3.8%
, 274
 
3.5%
1 274
 
3.5%
문 239
 
3.0%
시 239
 
3.0%
서 237
 
3.0%
울 236
 
3.0%
) 234
 
2.9%
Other values (192) 4110
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4547
57.3%
Space Separator 1297
 
16.3%
Decimal Number 1291
 
16.3%
Other Punctuation 275
 
3.5%
Close Punctuation 234
 
2.9%
Open Punctuation 234
 
2.9%
Dash Punctuation 26
 
0.3%
Uppercase Letter 18
 
0.2%
Lowercase Letter 10
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 491
 
10.8%
대 303
 
6.7%
문 239
 
5.3%
시 239
 
5.3%
서 237
 
5.2%
울 236
 
5.2%
로 229
 
5.0%
별 228
 
5.0%
구 228
 
5.0%
특 228
 
5.0%
Other values (158) 1889
41.5%
Decimal Number
ValueCountFrequency (%)
1 274
21.2%
2 192
14.9%
3 180
13.9%
0 151
11.7%
4 117
9.1%
5 112
8.7%
8 79
 
6.1%
6 70
 
5.4%
7 62
 
4.8%
9 54
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
d 1
10.0%
u 1
10.0%
o 1
10.0%
k 1
10.0%
c 1
10.0%
i 1
10.0%
r 1
10.0%
s 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
27.8%
A 4
22.2%
S 2
 
11.1%
X 2
 
11.1%
J 2
 
11.1%
H 1
 
5.6%
K 1
 
5.6%
R 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 274
99.6%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1297
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Open Punctuation
ValueCountFrequency (%)
( 234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4547
57.3%
Common 3359
42.3%
Latin 28
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 491
 
10.8%
대 303
 
6.7%
문 239
 
5.3%
시 239
 
5.3%
서 237
 
5.2%
울 236
 
5.2%
로 229
 
5.0%
별 228
 
5.0%
구 228
 
5.0%
특 228
 
5.0%
Other values (158) 1889
41.5%
Common
ValueCountFrequency (%)
1297
38.6%
, 274
 
8.2%
1 274
 
8.2%
) 234
 
7.0%
( 234
 
7.0%
2 192
 
5.7%
3 180
 
5.4%
0 151
 
4.5%
4 117
 
3.5%
5 112
 
3.3%
Other values (7) 294
 
8.8%
Latin
ValueCountFrequency (%)
B 5
17.9%
A 4
14.3%
S 2
 
7.1%
e 2
 
7.1%
X 2
 
7.1%
J 2
 
7.1%
d 1
 
3.6%
u 1
 
3.6%
o 1
 
3.6%
H 1
 
3.6%
Other values (7) 7
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4547
57.3%
ASCII 3387
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1297
38.3%
, 274
 
8.1%
1 274
 
8.1%
) 234
 
6.9%
( 234
 
6.9%
2 192
 
5.7%
3 180
 
5.3%
0 151
 
4.5%
4 117
 
3.5%
5 112
 
3.3%
Other values (24) 322
 
9.5%
Hangul
ValueCountFrequency (%)
동 491
 
10.8%
대 303
 
6.7%
문 239
 
5.3%
시 239
 
5.3%
서 237
 
5.2%
울 236
 
5.2%
로 229
 
5.0%
별 228
 
5.0%
구 228
 
5.0%
특 228
 
5.0%
Other values (158) 1889
41.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct87
Distinct (%)39.4%
Missing83
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean2577.1629
Minimum2422
Maximum4147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:02.610011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2422
5-th percentile2439
Q12536
median2586
Q32604
95-th percentile2644
Maximum4147
Range1725
Interquartile range (IQR)68

Descriptive statistics

Standard deviation121.07106
Coefficient of variation (CV)0.046978426
Kurtosis129.18912
Mean2577.1629
Median Absolute Deviation (MAD)29
Skewness9.8479321
Sum569553
Variance14658.201
MonotonicityNot monotonic
2024-05-11T15:49:02.788984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2586 15
 
4.9%
2602 15
 
4.9%
2582 9
 
3.0%
2633 8
 
2.6%
2604 8
 
2.6%
2644 8
 
2.6%
2490 7
 
2.3%
2585 6
 
2.0%
2603 6
 
2.0%
2438 5
 
1.6%
Other values (77) 134
44.1%
(Missing) 83
27.3%
ValueCountFrequency (%)
2422 1
 
0.3%
2423 1
 
0.3%
2428 1
 
0.3%
2429 1
 
0.3%
2436 1
 
0.3%
2437 1
 
0.3%
2438 5
1.6%
2439 2
 
0.7%
2445 1
 
0.3%
2451 2
 
0.7%
ValueCountFrequency (%)
4147 1
 
0.3%
2645 3
 
1.0%
2644 8
2.6%
2643 1
 
0.3%
2639 2
 
0.7%
2637 2
 
0.7%
2636 1
 
0.3%
2635 4
1.3%
2633 8
2.6%
2631 2
 
0.7%

사업장명
Text

Distinct297
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-05-11T15:49:03.052414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.8355263
Min length2

Characters and Unicode

Total characters2382
Distinct characters301
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

Unique291 ?
Unique (%)95.7%

Sample

1st row(주)동방디에스시스템
2nd row(주)선일씨에스
3rd row남양티에스(주)
4th row(주)삼보기획
5th row남인개발(주)
ValueCountFrequency (%)
주식회사 18
 
5.3%
중앙보안시스템(주 3
 
0.9%
주 3
 
0.9%
주)상우알에스 2
 
0.6%
체스넛 2
 
0.6%
주)문성시스템 2
 
0.6%
범호크린서비스 2
 
0.6%
늘크린 2
 
0.6%
클린데이 2
 
0.6%
엔피스그린 2
 
0.6%
Other values (299) 299
88.7%
2024-05-11T15:49:03.520025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 214
 
9.0%
( 186
 
7.8%
) 186
 
7.8%
스 90
 
3.8%
이 66
 
2.8%
에 58
 
2.4%
사 45
 
1.9%
린 41
 
1.7%
회 37
 
1.6%
리 35
 
1.5%
Other values (291) 1424
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1949
81.8%
Open Punctuation 186
 
7.8%
Close Punctuation 186
 
7.8%
Space Separator 33
 
1.4%
Uppercase Letter 22
 
0.9%
Other Punctuation 3
 
0.1%
Lowercase Letter 2
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 214
 
11.0%
스 90
 
4.6%
이 66
 
3.4%
에 58
 
3.0%
사 45
 
2.3%
린 41
 
2.1%
회 37
 
1.9%
리 35
 
1.8%
씨 32
 
1.6%
비 32
 
1.6%
Other values (269) 1299
66.6%
Uppercase Letter
ValueCountFrequency (%)
S 4
18.2%
C 4
18.2%
E 2
9.1%
F 2
9.1%
O 1
 
4.5%
N 1
 
4.5%
A 1
 
4.5%
D 1
 
4.5%
L 1
 
4.5%
R 1
 
4.5%
Other values (4) 4
18.2%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
s 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 186
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1949
81.8%
Common 409
 
17.2%
Latin 24
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 214
 
11.0%
스 90
 
4.6%
이 66
 
3.4%
에 58
 
3.0%
사 45
 
2.3%
린 41
 
2.1%
회 37
 
1.9%
리 35
 
1.8%
씨 32
 
1.6%
비 32
 
1.6%
Other values (269) 1299
66.6%
Latin
ValueCountFrequency (%)
S 4
16.7%
C 4
16.7%
E 2
 
8.3%
F 2
 
8.3%
O 1
 
4.2%
N 1
 
4.2%
A 1
 
4.2%
D 1
 
4.2%
L 1
 
4.2%
R 1
 
4.2%
Other values (6) 6
25.0%
Common
ValueCountFrequency (%)
( 186
45.5%
) 186
45.5%
33
 
8.1%
& 2
 
0.5%
5 1
 
0.2%
. 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1949
81.8%
ASCII 433
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 214
 
11.0%
스 90
 
4.6%
이 66
 
3.4%
에 58
 
3.0%
사 45
 
2.3%
린 41
 
2.1%
회 37
 
1.9%
리 35
 
1.8%
씨 32
 
1.6%
비 32
 
1.6%
Other values (269) 1299
66.6%
ASCII
ValueCountFrequency (%)
( 186
43.0%
) 186
43.0%
33
 
7.6%
S 4
 
0.9%
C 4
 
0.9%
E 2
 
0.5%
& 2
 
0.5%
F 2
 
0.5%
O 1
 
0.2%
N 1
 
0.2%
Other values (12) 12
 
2.8%

최종수정일자
Date

Distinct299
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2003-04-10 00:00:00
Maximum2024-04-29 13:26:44
2024-05-11T15:49:03.721780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:49:03.886381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
I
185 
U
119 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 185
60.9%
U 119
39.1%

Length

2024-05-11T15:49:04.059827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:04.460276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 185
60.9%
u 119
39.1%

데이터갱신일자
Date

Distinct112
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T15:49:04.597120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:49:04.761558image/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 size2.5 KiB
건물위생관리업
296 
건물위생관리업 기타
 
8

Length

Max length10
Median length7
Mean length7.0789474
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 296
97.4%
건물위생관리업 기타 8
 
2.6%

Length

2024-05-11T15:49:04.944443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:05.064495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 304
97.4%
기타 8
 
2.6%

좌표정보(X)
Real number (ℝ)

Distinct208
Distinct (%)69.1%
Missing3
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean204274.86
Minimum195509.58
Maximum206489.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:05.216534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195509.58
5-th percentile202158.85
Q1202852.21
median204487
Q3205428.92
95-th percentile206204.31
Maximum206489.46
Range10979.877
Interquartile range (IQR)2576.7148

Descriptive statistics

Standard deviation1461.7334
Coefficient of variation (CV)0.0071557185
Kurtosis2.7391229
Mean204274.86
Median Absolute Deviation (MAD)1224.2653
Skewness-0.88454935
Sum61486734
Variance2136664.5
MonotonicityNot monotonic
2024-05-11T15:49:05.398597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204486.997989395 11
 
3.6%
205248.297856492 6
 
2.0%
204089.817117361 6
 
2.0%
205401.574373249 6
 
2.0%
204687.977091636 5
 
1.6%
202181.999386105 4
 
1.3%
205428.921463301 4
 
1.3%
202491.159882878 4
 
1.3%
205518.063017957 4
 
1.3%
204762.02916529 4
 
1.3%
Other values (198) 247
81.2%
ValueCountFrequency (%)
195509.580070948 1
 
0.3%
202012.621510207 1
 
0.3%
202033.22548938 1
 
0.3%
202042.817335648 3
1.0%
202046.336404167 1
 
0.3%
202081.864808843 1
 
0.3%
202090.972773264 1
 
0.3%
202106.332424669 1
 
0.3%
202116.938316772 1
 
0.3%
202123.025510581 3
1.0%
ValueCountFrequency (%)
206489.457295721 3
1.0%
206484.233644024 1
 
0.3%
206483.555525111 3
1.0%
206386.640489187 1
 
0.3%
206375.404579295 1
 
0.3%
206311.053490627 1
 
0.3%
206304.862287075 1
 
0.3%
206266.986777135 2
0.7%
206230.127019263 1
 
0.3%
206229.74201299 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

Distinct208
Distinct (%)69.1%
Missing3
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean452478.15
Minimum449388.27
Maximum455613
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:05.595510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449388.27
5-th percentile451108.05
Q1451864.88
median452379.24
Q3453001.37
95-th percentile454247.18
Maximum455613
Range6224.7275
Interquartile range (IQR)1136.4952

Descriptive statistics

Standard deviation953.88618
Coefficient of variation (CV)0.0021081376
Kurtosis0.45161296
Mean452478.15
Median Absolute Deviation (MAD)560.52523
Skewness0.5537879
Sum1.3619592 × 108
Variance909898.84
MonotonicityNot monotonic
2024-05-11T15:49:05.851435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451928.85891879 11
 
3.6%
454247.178669814 6
 
2.0%
453314.135663101 6
 
2.0%
451108.047802152 6
 
2.0%
451578.200073082 5
 
1.6%
452138.418312791 4
 
1.3%
451103.146980087 4
 
1.3%
452378.673834246 4
 
1.3%
451314.767735832 4
 
1.3%
451508.878103131 4
 
1.3%
Other values (198) 247
81.2%
ValueCountFrequency (%)
449388.269219974 1
 
0.3%
450987.048392613 1
 
0.3%
451027.075395798 1
 
0.3%
451031.672241199 1
 
0.3%
451038.454241239 1
 
0.3%
451065.321633611 1
 
0.3%
451094.412855942 1
 
0.3%
451103.146980087 4
1.3%
451108.047802152 6
2.0%
451122.88876405 4
1.3%
ValueCountFrequency (%)
455612.996762285 1
0.3%
455584.872318917 1
0.3%
455275.835949587 1
0.3%
454847.087355503 1
0.3%
454801.612861763 1
0.3%
454716.539499581 1
0.3%
454676.339652544 1
0.3%
454408.747383272 1
0.3%
454382.661169644 1
0.3%
454373.058356279 1
0.3%

위생업태명
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
건물위생관리업
208 
<NA>
89 
건물위생관리업 기타
 
7

Length

Max length10
Median length7
Mean length6.1907895
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 208
68.4%
<NA> 89
29.3%
건물위생관리업 기타 7
 
2.3%

Length

2024-05-11T15:49:06.091863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:06.254169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 215
69.1%
na 89
28.6%
기타 7
 
2.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)7.2%
Missing123
Missing (%)40.5%
Infinite0
Infinite (%)0.0%
Mean1.8618785
Minimum0
Maximum14
Zeros117
Zeros (%)38.5%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:06.388676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile9
Maximum14
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.9340406
Coefficient of variation (CV)1.5758497
Kurtosis2.2266256
Mean1.8618785
Median Absolute Deviation (MAD)0
Skewness1.5959164
Sum337
Variance8.6085942
MonotonicityNot monotonic
2024-05-11T15:49:06.562151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 117
38.5%
5 20
 
6.6%
4 13
 
4.3%
3 11
 
3.6%
9 7
 
2.3%
7 4
 
1.3%
6 2
 
0.7%
1 2
 
0.7%
13 1
 
0.3%
14 1
 
0.3%
Other values (3) 3
 
1.0%
(Missing) 123
40.5%
ValueCountFrequency (%)
0 117
38.5%
1 2
 
0.7%
2 1
 
0.3%
3 11
 
3.6%
4 13
 
4.3%
5 20
 
6.6%
6 2
 
0.7%
7 4
 
1.3%
8 1
 
0.3%
9 7
 
2.3%
ValueCountFrequency (%)
14 1
 
0.3%
13 1
 
0.3%
10 1
 
0.3%
9 7
 
2.3%
8 1
 
0.3%
7 4
 
1.3%
6 2
 
0.7%
5 20
6.6%
4 13
4.3%
3 11
3.6%

건물지하층수
Categorical

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
137 
0
133 
1
24 
2
 
7
4
 
2

Length

Max length4
Median length1
Mean length2.3519737
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 137
45.1%
0 133
43.8%
1 24
 
7.9%
2 7
 
2.3%
4 2
 
0.7%
3 1
 
0.3%

Length

2024-05-11T15:49:06.742972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:06.906400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
45.1%
0 133
43.8%
1 24
 
7.9%
2 7
 
2.3%
4 2
 
0.7%
3 1
 
0.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)9.7%
Missing150
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean7.6038961
Minimum0
Maximum501
Zeros17
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:07.039402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile8.35
Maximum501
Range501
Interquartile range (IQR)3

Descriptive statistics

Standard deviation43.144751
Coefficient of variation (CV)5.6740321
Kurtosis115.93973
Mean7.6038961
Median Absolute Deviation (MAD)1
Skewness10.498039
Sum1171
Variance1861.4695
MonotonicityNot monotonic
2024-05-11T15:49:07.203348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 30
 
9.9%
3 30
 
9.9%
1 25
 
8.2%
2 22
 
7.2%
0 17
 
5.6%
5 13
 
4.3%
6 4
 
1.3%
7 3
 
1.0%
8 2
 
0.7%
9 2
 
0.7%
Other values (5) 6
 
2.0%
(Missing) 150
49.3%
ValueCountFrequency (%)
0 17
5.6%
1 25
8.2%
2 22
7.2%
3 30
9.9%
4 30
9.9%
5 13
4.3%
6 4
 
1.3%
7 3
 
1.0%
8 2
 
0.7%
9 2
 
0.7%
ValueCountFrequency (%)
501 1
 
0.3%
201 1
 
0.3%
14 1
 
0.3%
11 2
 
0.7%
10 1
 
0.3%
9 2
 
0.7%
8 2
 
0.7%
7 3
 
1.0%
6 4
 
1.3%
5 13
4.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)10.2%
Missing147
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean8.0573248
Minimum0
Maximum501
Zeros20
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-05-11T15:49:07.353781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile9
Maximum501
Range501
Interquartile range (IQR)3

Descriptive statistics

Standard deviation43.388118
Coefficient of variation (CV)5.3849284
Kurtosis110.67667
Mean8.0573248
Median Absolute Deviation (MAD)1
Skewness10.154219
Sum1265
Variance1882.5287
MonotonicityNot monotonic
2024-05-11T15:49:07.534524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 31
 
10.2%
4 29
 
9.5%
1 25
 
8.2%
2 22
 
7.2%
0 20
 
6.6%
5 13
 
4.3%
7 3
 
1.0%
6 3
 
1.0%
8 2
 
0.7%
9 2
 
0.7%
Other values (6) 7
 
2.3%
(Missing) 147
48.4%
ValueCountFrequency (%)
0 20
6.6%
1 25
8.2%
2 22
7.2%
3 31
10.2%
4 29
9.5%
5 13
4.3%
6 3
 
1.0%
7 3
 
1.0%
8 2
 
0.7%
9 2
 
0.7%
ValueCountFrequency (%)
501 1
 
0.3%
201 1
 
0.3%
101 1
 
0.3%
14 1
 
0.3%
11 2
0.7%
10 1
 
0.3%
9 2
0.7%
8 2
0.7%
7 3
1.0%
6 3
1.0%

사용시작지하층
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
229 
0
53 
1
 
20
2
 
2

Length

Max length4
Median length4
Mean length3.2598684
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> 229
75.3%
0 53
 
17.4%
1 20
 
6.6%
2 2
 
0.7%

Length

2024-05-11T15:49:07.720446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:07.878176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 229
75.3%
0 53
 
17.4%
1 20
 
6.6%
2 2
 
0.7%

사용끝지하층
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
230 
0
54 
1
 
18
2
 
2

Length

Max length4
Median length4
Mean length3.2697368
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> 230
75.7%
0 54
 
17.8%
1 18
 
5.9%
2 2
 
0.7%

Length

2024-05-11T15:49:08.091736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:08.285599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
75.7%
0 54
 
17.8%
1 18
 
5.9%
2 2
 
0.7%

한실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
150 

Length

Max length4
Median length4
Mean length2.5197368
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> 154
50.7%
0 150
49.3%

Length

2024-05-11T15:49:08.447994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:08.567576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
50.7%
0 150
49.3%

양실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
150 

Length

Max length4
Median length4
Mean length2.5197368
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> 154
50.7%
0 150
49.3%

Length

2024-05-11T15:49:08.696621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:08.826348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
50.7%
0 150
49.3%

욕실수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
150 

Length

Max length4
Median length4
Mean length2.5197368
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> 154
50.7%
0 150
49.3%

Length

2024-05-11T15:49:08.984007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:09.142036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
50.7%
0 150
49.3%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing98
Missing (%)32.2%
Memory size740.0 B
False
206 
(Missing)
98 
ValueCountFrequency (%)
False 206
67.8%
(Missing) 98
32.2%
2024-05-11T15:49:09.267916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
150 

Length

Max length4
Median length4
Mean length2.5197368
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> 154
50.7%
0 150
49.3%

Length

2024-05-11T15:49:09.429714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:09.577789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
50.7%
0 150
49.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing304
Missing (%)100.0%
Memory size2.8 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
248 
임대
53 
자가
 
3

Length

Max length4
Median length4
Mean length3.6315789
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 248
81.6%
임대 53
 
17.4%
자가 3
 
1.0%

Length

2024-05-11T15:49:09.819831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:09.984418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 248
81.6%
임대 53
 
17.4%
자가 3
 
1.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
154 
0
150 

Length

Max length4
Median length4
Mean length2.5197368
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> 154
50.7%
0 150
49.3%

Length

2024-05-11T15:49:10.137372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:10.283364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
50.7%
0 150
49.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
250 
0
51 
1
 
3

Length

Max length4
Median length4
Mean length3.4671053
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> 250
82.2%
0 51
 
16.8%
1 3
 
1.0%

Length

2024-05-11T15:49:10.492164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:10.664638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 250
82.2%
0 51
 
16.8%
1 3
 
1.0%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
249 
0
51 
1
 
2
101
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.4638158
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> 249
81.9%
0 51
 
16.8%
1 2
 
0.7%
101 1
 
0.3%
2 1
 
0.3%

Length

2024-05-11T15:49:10.817358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:10.991022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
81.9%
0 51
 
16.8%
1 2
 
0.7%
101 1
 
0.3%
2 1
 
0.3%

회수건조수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
166 
0
138 

Length

Max length4
Median length4
Mean length2.6381579
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> 166
54.6%
0 138
45.4%

Length

2024-05-11T15:49:11.163393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:11.294497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
54.6%
0 138
45.4%

침대수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
172 
0
132 

Length

Max length4
Median length4
Mean length2.6973684
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> 172
56.6%
0 132
43.4%

Length

2024-05-11T15:49:11.468331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:11.618744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 172
56.6%
0 132
43.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing89
Missing (%)29.3%
Memory size740.0 B
False
215 
(Missing)
89 
ValueCountFrequency (%)
False 215
70.7%
(Missing) 89
29.3%
2024-05-11T15:49:11.748624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030500003050000-206-1987-000011987-08-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 7941674115.7130-864서울특별시 동대문구 제기동 1140-4서울특별시 동대문구 약령중앙로 7-4, 2층 (제기동)2569(주)동방디에스시스템2023-07-14 09:34:42U2022-12-06 23:06:00.0건물위생관리업203160.859654452970.739422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130500003050000-206-1991-0293319911129<NA>3폐업2폐업20051031<NA><NA><NA>02 923955757.99130824서울특별시 동대문구 용두동 759-1<NA><NA>(주)선일씨에스2004-03-23 00:00:00I2018-08-31 23:59:59.0건물위생관리업202370.090672453073.856455건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230500003050000-206-1991-0293420030227<NA>3폐업2폐업20110523<NA><NA><NA>02 779227074.19130840서울특별시 동대문구 장안동 347-2 (장평8길 10)<NA><NA>남양티에스(주)2008-03-13 15:03:09I2018-08-31 23:59:59.0건물위생관리업206148.369814451774.619978건물위생관리업3<NA>22<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
330500003050000-206-1992-0287119920702<NA>3폐업2폐업20200327<NA><NA><NA>02 923476866.0130824서울특별시 동대문구 용두동 739-1서울특별시 동대문구 안암로16길 14, 2층 (용두동)2578(주)삼보기획2020-03-27 11:14:19U2020-03-29 02:40:00.0건물위생관리업202486.703402453241.54107건물위생관리업5122<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
430500003050000-206-1993-0288019930617<NA>1영업/정상1영업<NA><NA><NA><NA>022215833393.26130838서울특별시 동대문구 장안동 305-6 A동, 지하1층,지상1층서울특별시 동대문구 장한로27가길 34 (장안동, A동, 지하1층,지상1층)2528남인개발(주)2022-11-29 10:08:37U2021-11-02 00:01:00.0건물위생관리업206229.742013452479.072911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
530500003050000-206-1993-0288319931209<NA>3폐업2폐업20081013<NA><NA><NA>02960 0115342.0130867서울특별시 동대문구 청량리동 235-6 4층 (망우로 33)<NA><NA>(주)프로에스콤2008-03-13 15:31:32I2018-08-31 23:59:59.0건물위생관리업204190.108783453415.795068건물위생관리업5<NA>44<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
630500003050000-206-1993-0288519931209<NA>3폐업2폐업20170915<NA><NA><NA>02 922525562.9130864서울특별시 동대문구 제기동 1158-32 동서빌딩 302호서울특별시 동대문구 왕산로19다길 7, 302호 (제기동, 동서빌딩)2576대아건물관리(주)2017-09-15 13:47:25I2018-08-31 23:59:59.0건물위생관리업202852.206689452952.770264건물위생관리업5133<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
730500003050000-206-1994-0288719941107<NA>3폐업2폐업20080708<NA><NA><NA>022237478694.1130823서울특별시 동대문구 용두동 236-48 우신빌딩(403호) (용말길 19)<NA><NA>명진시설관리(주)2008-03-13 14:56:19I2018-08-31 23:59:59.0건물위생관리업202474.626504452684.679817건물위생관리업5<NA>44<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
830500003050000-206-1994-0289319940415<NA>3폐업2폐업20170518<NA><NA><NA>0222433011124.6130844서울특별시 동대문구 장안동 415-10서울특별시 동대문구 천호대로 385 (장안동)<NA>(주)영가2017-05-18 13:39:10I2018-08-31 23:59:59.0건물위생관리업205401.574373451108.047802건물위생관리업903300000N0<NA><NA><NA>임대0<NA><NA>00N
930500003050000-206-1996-0291119960402<NA>3폐업2폐업20030716<NA><NA><NA>02 9224900198.0130811서울특별시 동대문구 신설동 97-31 성산빌딩401호<NA><NA>(주)동양상사2003-04-10 00:00:00I2018-08-31 23:59:59.0건물위생관리업202254.127021452569.41048건물위생관리업5<NA>44<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
29430500003050000-206-2023-000042023-03-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.47130-823서울특별시 동대문구 용두동 237-26 용천빌서울특별시 동대문구 천호대로25길 29, 102호 (용두동, 용천빌)2585에코쉴드2023-03-10 16:02:47I2022-12-02 23:02:00.0건물위생관리업202930.138114452579.798142<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29530500003050000-206-2023-000062023-04-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 2242757833.0130-820서울특별시 동대문구 용두동 118-108서울특별시 동대문구 무학로28길 9-1, 4층 (용두동)2584해피크린2023-04-28 10:36:26I2022-12-03 21:00:00.0건물위생관리업202685.037894452493.797223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29630500003050000-206-2023-000072023-05-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0130-863서울특별시 동대문구 제기동 122-398서울특별시 동대문구 고산자로56길 48-1, 1층 (제기동)2466크린피움2023-05-19 14:21:19I2022-12-04 22:01:00.0건물위생관리업203357.501315454169.483488<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29730500003050000-206-2023-000082023-06-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.9130-846서울특별시 동대문구 장안동 466-7서울특별시 동대문구 천호대로 455, 5층 (장안동)2645(주)주유코퍼레이션2023-06-13 11:29:32I2022-12-05 23:05:00.0건물위생관리업206084.625089450987.048393<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29830500003050000-206-2023-000092023-07-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>155.0130-810서울특별시 동대문구 신설동 76-29서울특별시 동대문구 왕산로 9-1, 2층 (신설동)2580주우에이치알2023-09-27 17:02:23U2022-12-08 22:09:00.0건물위생관리업202106.332425452671.256794<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29930500003050000-206-2023-000102023-10-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 2246111866.0130-837서울특별시 동대문구 장안동 166-22 태광주택서울특별시 동대문구 답십리로66길 88, 태광주택 2층 (장안동)2626(주) 늘크린2023-10-27 14:11:08I2022-10-30 22:09:00.0건물위생관리업205786.3483451864.876778<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30030500003050000-206-2023-000112023-11-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.0130-869서울특별시 동대문구 청량리동 412서울특별시 동대문구 홍릉로 64-3, 1층 (청량리동)2484덕수클린2023-11-13 15:24:49I2022-10-31 23:07:00.0건물위생관리업203781.694673453756.572636<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30130500003050000-206-2023-000122023-11-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.0130-824서울특별시 동대문구 용두동 729-6서울특별시 동대문구 무학로49길 26, 3층 (용두동)2578주식회사 정우씨엔에스2023-11-21 17:08:13I2022-10-31 22:03:00.0건물위생관리업202427.170864453222.200282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30230500003050000-206-2024-000012024-01-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>43.68130-867서울특별시 동대문구 청량리동 54-13서울특별시 동대문구 왕산로43길 50-4, 지하1층 (청량리동)2487엔피스그린 주식회사2024-01-04 13:53:06I2023-12-01 00:06:00.0건물위생관리업204119.726899453638.356411<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30330500003050000-206-2024-000022024-01-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-876서울특별시 동대문구 휘경동 191-3서울특별시 동대문구 회기로 195, 6층 (휘경동)2445원준2024-01-17 17:13:10I2023-11-30 23:09:00.0건물위생관리업205022.515415454212.542182<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>