Overview

Dataset statistics

Number of variables47
Number of observations1025
Missing cells13148
Missing cells (%)27.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory404.5 KiB
Average record size in memory404.1 B

Variable types

Categorical16
Text7
DateTime4
Unsupported7
Numeric11
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-19298/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (97.1%)Imbalance
위생업태명 is highly imbalanced (60.2%)Imbalance
인허가취소일자 has 1025 (100.0%) missing valuesMissing
폐업일자 has 263 (25.7%) missing valuesMissing
휴업시작일자 has 1025 (100.0%) missing valuesMissing
휴업종료일자 has 1025 (100.0%) missing valuesMissing
재개업일자 has 1025 (100.0%) missing valuesMissing
전화번호 has 260 (25.4%) missing valuesMissing
도로명주소 has 280 (27.3%) missing valuesMissing
도로명우편번호 has 283 (27.6%) missing valuesMissing
건물지상층수 has 407 (39.7%) missing valuesMissing
건물지하층수 has 408 (39.8%) missing valuesMissing
사용시작지상층 has 364 (35.5%) missing valuesMissing
사용끝지상층 has 411 (40.1%) missing valuesMissing
사용시작지하층 has 679 (66.2%) missing valuesMissing
사용끝지하층 has 721 (70.3%) missing valuesMissing
발한실여부 has 180 (17.6%) missing valuesMissing
조건부허가신고사유 has 1025 (100.0%) missing valuesMissing
조건부허가시작일자 has 1025 (100.0%) missing valuesMissing
조건부허가종료일자 has 1025 (100.0%) missing valuesMissing
여성종사자수 has 774 (75.5%) missing valuesMissing
남성종사자수 has 772 (75.3%) missing valuesMissing
다중이용업소여부 has 151 (14.7%) 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 557 (54.3%) zerosZeros
건물지하층수 has 560 (54.6%) zerosZeros
사용시작지상층 has 91 (8.9%) zerosZeros
사용끝지상층 has 48 (4.7%) zerosZeros
사용시작지하층 has 283 (27.6%) zerosZeros
사용끝지하층 has 241 (23.5%) zerosZeros
여성종사자수 has 67 (6.5%) zerosZeros
남성종사자수 has 30 (2.9%) zerosZeros

Reproduction

Analysis started2024-05-11 04:01:51.205945
Analysis finished2024-05-11 04:01:54.067287
Duration2.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
3210000
1025 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3210000 1025
100.0%

Length

2024-05-11T04:01:54.280729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:54.635273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 1025
100.0%

관리번호
Text

UNIQUE 

Distinct1025
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T04:01:55.266783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22550
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

Unique1025 ?
Unique (%)100.0%

Sample

1st row3210000-206-1987-02096
2nd row3210000-206-1987-02098
3rd row3210000-206-1988-02100
4th row3210000-206-1988-02101
5th row3210000-206-1988-02102
ValueCountFrequency (%)
3210000-206-1987-02096 1
 
0.1%
3210000-206-2009-00053 1
 
0.1%
3210000-206-2012-00042 1
 
0.1%
3210000-206-2012-00029 1
 
0.1%
3210000-206-2012-00030 1
 
0.1%
3210000-206-2012-00031 1
 
0.1%
3210000-206-2012-00032 1
 
0.1%
3210000-206-2012-00033 1
 
0.1%
3210000-206-2012-00034 1
 
0.1%
3210000-206-2012-00035 1
 
0.1%
Other values (1015) 1015
99.0%
2024-05-11T04:01:56.434983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9750
43.2%
2 3566
 
15.8%
- 3075
 
13.6%
1 2040
 
9.0%
3 1410
 
6.3%
6 1243
 
5.5%
9 477
 
2.1%
4 317
 
1.4%
5 249
 
1.1%
7 217
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19475
86.4%
Dash Punctuation 3075
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9750
50.1%
2 3566
 
18.3%
1 2040
 
10.5%
3 1410
 
7.2%
6 1243
 
6.4%
9 477
 
2.4%
4 317
 
1.6%
5 249
 
1.3%
7 217
 
1.1%
8 206
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 3075
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9750
43.2%
2 3566
 
15.8%
- 3075
 
13.6%
1 2040
 
9.0%
3 1410
 
6.3%
6 1243
 
5.5%
9 477
 
2.1%
4 317
 
1.4%
5 249
 
1.1%
7 217
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9750
43.2%
2 3566
 
15.8%
- 3075
 
13.6%
1 2040
 
9.0%
3 1410
 
6.3%
6 1243
 
5.5%
9 477
 
2.1%
4 317
 
1.4%
5 249
 
1.1%
7 217
 
1.0%
Distinct905
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1987-05-15 00:00:00
Maximum2024-04-19 00:00:00
2024-05-11T04:01:56.872992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:01:57.320778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
3
762 
1
263 

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 (%)
3 762
74.3%
1 263
 
25.7%

Length

2024-05-11T04:01:57.738587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:58.044531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 762
74.3%
1 263
 
25.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
762 
영업/정상
263 

Length

Max length5
Median length2
Mean length2.7697561
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 762
74.3%
영업/정상 263
 
25.7%

Length

2024-05-11T04:01:58.407218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:58.878613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 762
74.3%
영업/정상 263
 
25.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2
762 
1
263 

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 (%)
2 762
74.3%
1 263
 
25.7%

Length

2024-05-11T04:01:59.186760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:01:59.475184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 762
74.3%
1 263
 
25.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
762 
영업
263 

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 762
74.3%
영업 263
 
25.7%

Length

2024-05-11T04:01:59.814265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:00.858981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 762
74.3%
영업 263
 
25.7%

폐업일자
Date

MISSING 

Distinct563
Distinct (%)73.9%
Missing263
Missing (%)25.7%
Memory size8.1 KiB
Minimum1995-07-11 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T04:02:01.220368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:01.649625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB

전화번호
Text

MISSING 

Distinct732
Distinct (%)95.7%
Missing260
Missing (%)25.4%
Memory size8.1 KiB
2024-05-11T04:02:02.495116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.252288
Min length2

Characters and Unicode

Total characters7843
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

Unique704 ?
Unique (%)92.0%

Sample

1st row02 5330860
2nd row02 5934957
3rd row02
4th row0234827004
5th row0234813755
ValueCountFrequency (%)
02 442
30.4%
070 13
 
0.9%
521 12
 
0.8%
529 8
 
0.6%
523 7
 
0.5%
522 7
 
0.5%
537 6
 
0.4%
587 6
 
0.4%
0 6
 
0.4%
581 5
 
0.3%
Other values (838) 941
64.8%
2024-05-11T04:02:04.204056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1220
15.6%
2 1168
14.9%
953
12.2%
5 874
11.1%
7 618
7.9%
3 614
7.8%
4 540
6.9%
1 527
6.7%
8 523
6.7%
6 422
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6890
87.8%
Space Separator 953
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1220
17.7%
2 1168
17.0%
5 874
12.7%
7 618
9.0%
3 614
8.9%
4 540
7.8%
1 527
7.6%
8 523
7.6%
6 422
 
6.1%
9 384
 
5.6%
Space Separator
ValueCountFrequency (%)
953
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7843
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1220
15.6%
2 1168
14.9%
953
12.2%
5 874
11.1%
7 618
7.9%
3 614
7.8%
4 540
6.9%
1 527
6.7%
8 523
6.7%
6 422
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1220
15.6%
2 1168
14.9%
953
12.2%
5 874
11.1%
7 618
7.9%
3 614
7.8%
4 540
6.9%
1 527
6.7%
8 523
6.7%
6 422
 
5.4%
Distinct613
Distinct (%)60.0%
Missing4
Missing (%)0.4%
Memory size8.1 KiB
2024-05-11T04:02:05.276385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0411361
Min length3

Characters and Unicode

Total characters5147
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

Unique502 ?
Unique (%)49.2%

Sample

1st row33.25
2nd row.00
3rd row.00
4th row44.60
5th row.00
ValueCountFrequency (%)
00 98
 
9.6%
33.00 26
 
2.5%
30.00 18
 
1.8%
60.00 15
 
1.5%
50.00 14
 
1.4%
66.00 14
 
1.4%
3.30 14
 
1.4%
10.00 11
 
1.1%
90.00 11
 
1.1%
20.00 9
 
0.9%
Other values (603) 791
77.5%
2024-05-11T04:02:06.745791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1344
26.1%
. 1021
19.8%
1 423
 
8.2%
2 359
 
7.0%
3 349
 
6.8%
6 313
 
6.1%
5 309
 
6.0%
4 303
 
5.9%
8 265
 
5.1%
9 259
 
5.0%
Other values (2) 202
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4120
80.0%
Other Punctuation 1027
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1344
32.6%
1 423
 
10.3%
2 359
 
8.7%
3 349
 
8.5%
6 313
 
7.6%
5 309
 
7.5%
4 303
 
7.4%
8 265
 
6.4%
9 259
 
6.3%
7 196
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 1021
99.4%
, 6
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 5147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1344
26.1%
. 1021
19.8%
1 423
 
8.2%
2 359
 
7.0%
3 349
 
6.8%
6 313
 
6.1%
5 309
 
6.0%
4 303
 
5.9%
8 265
 
5.1%
9 259
 
5.0%
Other values (2) 202
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1344
26.1%
. 1021
19.8%
1 423
 
8.2%
2 359
 
7.0%
3 349
 
6.8%
6 313
 
6.1%
5 309
 
6.0%
4 303
 
5.9%
8 265
 
5.1%
9 259
 
5.0%
Other values (2) 202
 
3.9%
Distinct168
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T04:02:07.782733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0878049
Min length6

Characters and Unicode

Total characters6240
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

Unique40 ?
Unique (%)3.9%

Sample

1st row137907
2nd row137829
3rd row137862
4th row137855
5th row137855
ValueCountFrequency (%)
137876 44
 
4.3%
137860 31
 
3.0%
137862 29
 
2.8%
137130 24
 
2.3%
137818 23
 
2.2%
137894 22
 
2.1%
137891 20
 
2.0%
137895 19
 
1.9%
137875 17
 
1.7%
137872 16
 
1.6%
Other values (158) 780
76.1%
2024-05-11T04:02:09.164371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1297
20.8%
3 1211
19.4%
1 1206
19.3%
8 1069
17.1%
9 316
 
5.1%
0 311
 
5.0%
6 253
 
4.1%
4 172
 
2.8%
5 167
 
2.7%
2 148
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6150
98.6%
Dash Punctuation 90
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1297
21.1%
3 1211
19.7%
1 1206
19.6%
8 1069
17.4%
9 316
 
5.1%
0 311
 
5.1%
6 253
 
4.1%
4 172
 
2.8%
5 167
 
2.7%
2 148
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1297
20.8%
3 1211
19.4%
1 1206
19.3%
8 1069
17.1%
9 316
 
5.1%
0 311
 
5.0%
6 253
 
4.1%
4 172
 
2.8%
5 167
 
2.7%
2 148
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1297
20.8%
3 1211
19.4%
1 1206
19.3%
8 1069
17.1%
9 316
 
5.1%
0 311
 
5.0%
6 253
 
4.1%
4 172
 
2.8%
5 167
 
2.7%
2 148
 
2.4%
Distinct998
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T04:02:09.986683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length27.764878
Min length18

Characters and Unicode

Total characters28459
Distinct characters326
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique971 ?
Unique (%)94.7%

Sample

1st row서울특별시 서초구 잠원동 64-4
2nd row서울특별시 서초구 방배동 782-1
3rd row서울특별시 서초구 서초동 1355-8 중앙로얄 1701
4th row서울특별시 서초구 서초동 1303-16
5th row서울특별시 서초구 서초동 1303-16 제일생명빌딩 신관6층
ValueCountFrequency (%)
서울특별시 1025
18.0%
서초구 1025
18.0%
서초동 425
 
7.5%
양재동 232
 
4.1%
방배동 229
 
4.0%
2층 102
 
1.8%
3층 69
 
1.2%
잠원동 65
 
1.1%
4층 65
 
1.1%
반포동 56
 
1.0%
Other values (1465) 2387
42.0%
2024-05-11T04:02:11.476367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5307
18.6%
2537
 
8.9%
1 1495
 
5.3%
1483
 
5.2%
1097
 
3.9%
1038
 
3.6%
1033
 
3.6%
1027
 
3.6%
1025
 
3.6%
1025
 
3.6%
Other values (316) 11392
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15035
52.8%
Decimal Number 6861
24.1%
Space Separator 5307
 
18.6%
Dash Punctuation 1000
 
3.5%
Uppercase Letter 95
 
0.3%
Other Punctuation 57
 
0.2%
Close Punctuation 47
 
0.2%
Open Punctuation 47
 
0.2%
Math Symbol 8
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2537
16.9%
1483
 
9.9%
1097
 
7.3%
1038
 
6.9%
1033
 
6.9%
1027
 
6.8%
1025
 
6.8%
1025
 
6.8%
561
 
3.7%
458
 
3.0%
Other values (278) 3751
24.9%
Uppercase Letter
ValueCountFrequency (%)
B 35
36.8%
D 9
 
9.5%
K 8
 
8.4%
A 8
 
8.4%
C 6
 
6.3%
G 5
 
5.3%
L 5
 
5.3%
F 3
 
3.2%
T 3
 
3.2%
H 2
 
2.1%
Other values (7) 11
 
11.6%
Decimal Number
ValueCountFrequency (%)
1 1495
21.8%
2 931
13.6%
3 805
11.7%
0 738
10.8%
5 658
9.6%
4 591
 
8.6%
6 457
 
6.7%
7 426
 
6.2%
8 401
 
5.8%
9 359
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 48
84.2%
/ 8
 
14.0%
& 1
 
1.8%
Math Symbol
ValueCountFrequency (%)
~ 7
87.5%
1
 
12.5%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
5307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15035
52.8%
Common 13327
46.8%
Latin 97
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2537
16.9%
1483
 
9.9%
1097
 
7.3%
1038
 
6.9%
1033
 
6.9%
1027
 
6.8%
1025
 
6.8%
1025
 
6.8%
561
 
3.7%
458
 
3.0%
Other values (278) 3751
24.9%
Common
ValueCountFrequency (%)
5307
39.8%
1 1495
 
11.2%
- 1000
 
7.5%
2 931
 
7.0%
3 805
 
6.0%
0 738
 
5.5%
5 658
 
4.9%
4 591
 
4.4%
6 457
 
3.4%
7 426
 
3.2%
Other values (9) 919
 
6.9%
Latin
ValueCountFrequency (%)
B 35
36.1%
D 9
 
9.3%
K 8
 
8.2%
A 8
 
8.2%
C 6
 
6.2%
G 5
 
5.2%
L 5
 
5.2%
F 3
 
3.1%
T 3
 
3.1%
H 2
 
2.1%
Other values (9) 13
 
13.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15035
52.8%
ASCII 13421
47.2%
Number Forms 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5307
39.5%
1 1495
 
11.1%
- 1000
 
7.5%
2 931
 
6.9%
3 805
 
6.0%
0 738
 
5.5%
5 658
 
4.9%
4 591
 
4.4%
6 457
 
3.4%
7 426
 
3.2%
Other values (25) 1013
 
7.5%
Hangul
ValueCountFrequency (%)
2537
16.9%
1483
 
9.9%
1097
 
7.3%
1038
 
6.9%
1033
 
6.9%
1027
 
6.8%
1025
 
6.8%
1025
 
6.8%
561
 
3.7%
458
 
3.0%
Other values (278) 3751
24.9%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct726
Distinct (%)97.4%
Missing280
Missing (%)27.3%
Memory size8.1 KiB
2024-05-11T04:02:12.381579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length46
Mean length34.832215
Min length22

Characters and Unicode

Total characters25950
Distinct characters325
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique707 ?
Unique (%)94.9%

Sample

1st row서울특별시 서초구 동작대로 194 (방배동)
2nd row서울특별시 서초구 논현로 87, 1306호 (양재동)
3rd row서울특별시 서초구 반포대로 59 (서초동,선흥빌딩 4층)
4th row서울특별시 서초구 반포대로 59 (서초동,선흥빌딩 4층)
5th row서울특별시 서초구 강남대로43길 14-1, 4층, 5층 (서초동, 서초빌딩)
ValueCountFrequency (%)
서울특별시 745
 
15.1%
서초구 745
 
15.1%
서초동 237
 
4.8%
양재동 140
 
2.8%
방배동 131
 
2.7%
2층 81
 
1.6%
4층 67
 
1.4%
3층 62
 
1.3%
5층 41
 
0.8%
1층 36
 
0.7%
Other values (1180) 2648
53.7%
2024-05-11T04:02:13.921466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4190
 
16.1%
2021
 
7.8%
1224
 
4.7%
, 973
 
3.7%
1 897
 
3.5%
843
 
3.2%
( 765
 
2.9%
) 765
 
2.9%
757
 
2.9%
749
 
2.9%
Other values (315) 12766
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14736
56.8%
Decimal Number 4335
 
16.7%
Space Separator 4190
 
16.1%
Other Punctuation 978
 
3.8%
Open Punctuation 765
 
2.9%
Close Punctuation 765
 
2.9%
Dash Punctuation 114
 
0.4%
Uppercase Letter 66
 
0.3%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2021
 
13.7%
1224
 
8.3%
843
 
5.7%
757
 
5.1%
749
 
5.1%
748
 
5.1%
745
 
5.1%
745
 
5.1%
724
 
4.9%
441
 
3.0%
Other values (282) 5739
38.9%
Uppercase Letter
ValueCountFrequency (%)
B 24
36.4%
A 7
 
10.6%
K 7
 
10.6%
D 5
 
7.6%
C 5
 
7.6%
S 3
 
4.5%
T 3
 
4.5%
G 3
 
4.5%
L 3
 
4.5%
H 1
 
1.5%
Other values (5) 5
 
7.6%
Decimal Number
ValueCountFrequency (%)
1 897
20.7%
2 678
15.6%
3 559
12.9%
0 513
11.8%
4 411
9.5%
5 332
 
7.7%
7 273
 
6.3%
6 248
 
5.7%
9 215
 
5.0%
8 209
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 973
99.5%
/ 4
 
0.4%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 765
100.0%
Close Punctuation
ValueCountFrequency (%)
) 765
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14736
56.8%
Common 11147
43.0%
Latin 67
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2021
 
13.7%
1224
 
8.3%
843
 
5.7%
757
 
5.1%
749
 
5.1%
748
 
5.1%
745
 
5.1%
745
 
5.1%
724
 
4.9%
441
 
3.0%
Other values (282) 5739
38.9%
Common
ValueCountFrequency (%)
4190
37.6%
, 973
 
8.7%
1 897
 
8.0%
( 765
 
6.9%
) 765
 
6.9%
2 678
 
6.1%
3 559
 
5.0%
0 513
 
4.6%
4 411
 
3.7%
5 332
 
3.0%
Other values (7) 1064
 
9.5%
Latin
ValueCountFrequency (%)
B 24
35.8%
A 7
 
10.4%
K 7
 
10.4%
D 5
 
7.5%
C 5
 
7.5%
S 3
 
4.5%
T 3
 
4.5%
G 3
 
4.5%
L 3
 
4.5%
H 1
 
1.5%
Other values (6) 6
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14736
56.8%
ASCII 11213
43.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4190
37.4%
, 973
 
8.7%
1 897
 
8.0%
( 765
 
6.8%
) 765
 
6.8%
2 678
 
6.0%
3 559
 
5.0%
0 513
 
4.6%
4 411
 
3.7%
5 332
 
3.0%
Other values (22) 1130
 
10.1%
Hangul
ValueCountFrequency (%)
2021
 
13.7%
1224
 
8.3%
843
 
5.7%
757
 
5.1%
749
 
5.1%
748
 
5.1%
745
 
5.1%
745
 
5.1%
724
 
4.9%
441
 
3.0%
Other values (282) 5739
38.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)25.7%
Missing283
Missing (%)27.6%
Infinite0
Infinite (%)0.0%
Mean6669.9973
Minimum6502
Maximum6806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:14.463132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6502
5-th percentile6531
Q16616
median6664
Q36739
95-th percentile6784
Maximum6806
Range304
Interquartile range (IQR)123

Descriptive statistics

Standard deviation79.356334
Coefficient of variation (CV)0.011897506
Kurtosis-1.0011851
Mean6669.9973
Median Absolute Deviation (MAD)68
Skewness-0.19238193
Sum4949138
Variance6297.4278
MonotonicityNot monotonic
2024-05-11T04:02:14.901200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6775 32
 
3.1%
6653 17
 
1.7%
6654 14
 
1.4%
6651 14
 
1.4%
6628 13
 
1.3%
6784 11
 
1.1%
6643 11
 
1.1%
6776 10
 
1.0%
6627 10
 
1.0%
6649 10
 
1.0%
Other values (181) 600
58.5%
(Missing) 283
27.6%
ValueCountFrequency (%)
6502 4
0.4%
6512 7
0.7%
6520 1
 
0.1%
6522 1
 
0.1%
6524 6
0.6%
6526 3
0.3%
6527 6
0.6%
6529 1
 
0.1%
6530 6
0.6%
6531 4
0.4%
ValueCountFrequency (%)
6806 2
0.2%
6804 3
0.3%
6802 1
 
0.1%
6797 1
 
0.1%
6796 1
 
0.1%
6794 2
0.2%
6793 1
 
0.1%
6791 4
0.4%
6788 3
0.3%
6787 4
0.4%
Distinct999
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T04:02:15.621876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length8.1697561
Min length2

Characters and Unicode

Total characters8374
Distinct characters427
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

Unique974 ?
Unique (%)95.0%

Sample

1st row주)풍원용역
2nd row새재기업(주)
3rd row국제흥업(주)
4th row한동용역
5th row명신방호실업(주)
ValueCountFrequency (%)
주식회사 110
 
9.2%
29
 
2.4%
주)동양상사 3
 
0.3%
크린 3
 
0.3%
클린 3
 
0.3%
올댓모델 3
 
0.3%
석정지엠 2
 
0.2%
주)티비엠씨 2
 
0.2%
주)시티온 2
 
0.2%
주)맥풍 2
 
0.2%
Other values (1010) 1031
86.6%
2024-05-11T04:02:16.762884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
867
 
10.4%
) 730
 
8.7%
( 720
 
8.6%
343
 
4.1%
258
 
3.1%
221
 
2.6%
167
 
2.0%
152
 
1.8%
151
 
1.8%
129
 
1.5%
Other values (417) 4636
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6673
79.7%
Close Punctuation 730
 
8.7%
Open Punctuation 720
 
8.6%
Space Separator 167
 
2.0%
Uppercase Letter 48
 
0.6%
Dash Punctuation 11
 
0.1%
Lowercase Letter 11
 
0.1%
Decimal Number 8
 
0.1%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
867
 
13.0%
343
 
5.1%
258
 
3.9%
221
 
3.3%
152
 
2.3%
151
 
2.3%
129
 
1.9%
127
 
1.9%
122
 
1.8%
113
 
1.7%
Other values (379) 4190
62.8%
Uppercase Letter
ValueCountFrequency (%)
C 8
16.7%
S 7
14.6%
B 5
10.4%
M 5
10.4%
N 3
 
6.2%
G 3
 
6.2%
U 2
 
4.2%
L 2
 
4.2%
R 2
 
4.2%
E 2
 
4.2%
Other values (9) 9
18.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
y 1
 
9.1%
o 1
 
9.1%
n 1
 
9.1%
d 1
 
9.1%
r 1
 
9.1%
v 1
 
9.1%
i 1
 
9.1%
c 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 3
37.5%
4 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
& 2
33.3%
/ 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 730
100.0%
Open Punctuation
ValueCountFrequency (%)
( 720
100.0%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6673
79.7%
Common 1642
 
19.6%
Latin 59
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
867
 
13.0%
343
 
5.1%
258
 
3.9%
221
 
3.3%
152
 
2.3%
151
 
2.3%
129
 
1.9%
127
 
1.9%
122
 
1.8%
113
 
1.7%
Other values (379) 4190
62.8%
Latin
ValueCountFrequency (%)
C 8
13.6%
S 7
 
11.9%
B 5
 
8.5%
M 5
 
8.5%
N 3
 
5.1%
G 3
 
5.1%
e 3
 
5.1%
U 2
 
3.4%
L 2
 
3.4%
R 2
 
3.4%
Other values (18) 19
32.2%
Common
ValueCountFrequency (%)
) 730
44.5%
( 720
43.8%
167
 
10.2%
- 11
 
0.7%
1 4
 
0.2%
. 3
 
0.2%
2 3
 
0.2%
& 2
 
0.1%
/ 1
 
0.1%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6673
79.7%
ASCII 1701
 
20.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
867
 
13.0%
343
 
5.1%
258
 
3.9%
221
 
3.3%
152
 
2.3%
151
 
2.3%
129
 
1.9%
127
 
1.9%
122
 
1.8%
113
 
1.7%
Other values (379) 4190
62.8%
ASCII
ValueCountFrequency (%)
) 730
42.9%
( 720
42.3%
167
 
9.8%
- 11
 
0.6%
C 8
 
0.5%
S 7
 
0.4%
B 5
 
0.3%
M 5
 
0.3%
1 4
 
0.2%
N 3
 
0.2%
Other values (28) 41
 
2.4%
Distinct943
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1998-12-30 00:00:00
Maximum2024-05-09 10:44:39
2024-05-11T04:02:17.283723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:17.879289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
I
736 
U
289 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 736
71.8%
U 289
 
28.2%

Length

2024-05-11T04:02:18.436211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:18.834579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 736
71.8%
u 289
 
28.2%
Distinct291
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T04:02:19.503486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:02:20.035168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
건물위생관리업
1022 
건물위생관리업 기타
 
3

Length

Max length10
Median length7
Mean length7.0087805
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 1022
99.7%
건물위생관리업 기타 3
 
0.3%

Length

2024-05-11T04:02:20.569537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:20.936332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 1025
99.7%
기타 3
 
0.3%

좌표정보(X)
Real number (ℝ)

Distinct706
Distinct (%)69.4%
Missing8
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean201460.81
Minimum198357.32
Maximum208072.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:21.402731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198357.32
5-th percentile198589.72
Q1200347.59
median201483.61
Q3202661.25
95-th percentile203869
Maximum208072.63
Range9715.3067
Interquartile range (IQR)2313.6577

Descriptive statistics

Standard deviation1683.3809
Coefficient of variation (CV)0.0083558725
Kurtosis-0.72481665
Mean201460.81
Median Absolute Deviation (MAD)1155.3391
Skewness-0.12498351
Sum2.0488564 × 108
Variance2833771.1
MonotonicityNot monotonic
2024-05-11T04:02:21.931447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202481.661169413 10
 
1.0%
201213.64069933 8
 
0.8%
202638.948768564 8
 
0.8%
203847.029537103 8
 
0.8%
201501.672660443 8
 
0.8%
203891.041008756 7
 
0.7%
202623.297219041 7
 
0.7%
202508.646065919 6
 
0.6%
201153.543582527 5
 
0.5%
203848.094015013 5
 
0.5%
Other values (696) 945
92.2%
(Missing) 8
 
0.8%
ValueCountFrequency (%)
198357.319178572 1
 
0.1%
198362.476944652 2
0.2%
198364.994691704 1
 
0.1%
198368.472159079 1
 
0.1%
198371.633126437 1
 
0.1%
198387.623421253 1
 
0.1%
198397.235721331 1
 
0.1%
198409.68236069 1
 
0.1%
198432.354182494 4
0.4%
198433.751911823 1
 
0.1%
ValueCountFrequency (%)
208072.625904312 1
0.1%
205670.786257176 2
0.2%
204958.894510233 1
0.1%
204949.585384898 1
0.1%
204859.624669529 1
0.1%
204418.836684211 1
0.1%
204347.957205681 1
0.1%
204333.831655277 1
0.1%
204318.138260863 1
0.1%
204258.061998707 1
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct706
Distinct (%)69.4%
Missing8
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean442752.27
Minimum437942.63
Maximum446331.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:22.610380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437942.63
5-th percentile440791.19
Q1441943.5
median442654.58
Q3443361.67
95-th percentile445354.36
Maximum446331.38
Range8388.755
Interquartile range (IQR)1418.1772

Descriptive statistics

Standard deviation1274.4961
Coefficient of variation (CV)0.0028785762
Kurtosis0.78563102
Mean442752.27
Median Absolute Deviation (MAD)709.08292
Skewness0.27861922
Sum4.5027905 × 108
Variance1624340.4
MonotonicityNot monotonic
2024-05-11T04:02:23.257688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442563.269271521 10
 
1.0%
442739.647017252 8
 
0.8%
443109.509930091 8
 
0.8%
441707.819305687 8
 
0.8%
442505.573142545 8
 
0.8%
441636.969240722 7
 
0.7%
443154.964346798 7
 
0.7%
442625.413940559 6
 
0.6%
442643.280772 5
 
0.5%
441601.513809347 5
 
0.5%
Other values (696) 945
92.2%
(Missing) 8
 
0.8%
ValueCountFrequency (%)
437942.625019913 1
 
0.1%
437968.892025771 1
 
0.1%
438324.966150657 1
 
0.1%
439328.894560548 2
0.2%
439564.755203245 1
 
0.1%
439620.265870293 3
0.3%
439730.929547293 1
 
0.1%
439810.25559883 1
 
0.1%
439881.740443559 1
 
0.1%
439958.443578701 1
 
0.1%
ValueCountFrequency (%)
446331.380046658 1
0.1%
446205.939573861 1
0.1%
446155.716601327 2
0.2%
446150.216745339 2
0.2%
446144.110278895 1
0.1%
446130.47997888 1
0.1%
446041.940329826 1
0.1%
445977.856273032 2
0.2%
445894.878452956 1
0.1%
445892.414984064 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
건물위생관리업
871 
<NA>
151 
건물위생관리업 기타
 
3

Length

Max length10
Median length7
Mean length6.5668293
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 871
85.0%
<NA> 151
 
14.7%
건물위생관리업 기타 3
 
0.3%

Length

2024-05-11T04:02:23.775176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:24.148350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 874
85.0%
na 151
 
14.7%
기타 3
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.1%
Missing407
Missing (%)39.7%
Infinite0
Infinite (%)0.0%
Mean0.81229773
Minimum0
Maximum46
Zeros557
Zeros (%)54.3%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:24.577956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.3412666
Coefficient of variation (CV)4.1133521
Kurtosis68.665686
Mean0.81229773
Median Absolute Deviation (MAD)0
Skewness7.0409081
Sum502
Variance11.164062
MonotonicityNot monotonic
2024-05-11T04:02:25.037575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 557
54.3%
5 18
 
1.8%
4 10
 
1.0%
6 6
 
0.6%
7 4
 
0.4%
8 4
 
0.4%
15 3
 
0.3%
20 3
 
0.3%
2 2
 
0.2%
9 2
 
0.2%
Other values (9) 9
 
0.9%
(Missing) 407
39.7%
ValueCountFrequency (%)
0 557
54.3%
1 1
 
0.1%
2 2
 
0.2%
3 1
 
0.1%
4 10
 
1.0%
5 18
 
1.8%
6 6
 
0.6%
7 4
 
0.4%
8 4
 
0.4%
9 2
 
0.2%
ValueCountFrequency (%)
46 1
 
0.1%
25 1
 
0.1%
24 1
 
0.1%
20 3
0.3%
16 1
 
0.1%
15 3
0.3%
13 1
 
0.1%
11 1
 
0.1%
10 1
 
0.1%
9 2
0.2%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.3%
Missing408
Missing (%)39.8%
Infinite0
Infinite (%)0.0%
Mean0.19773096
Minimum0
Maximum7
Zeros560
Zeros (%)54.6%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:25.527575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.81968162
Coefficient of variation (CV)4.145439
Kurtosis35.869666
Mean0.19773096
Median Absolute Deviation (MAD)0
Skewness5.6535121
Sum122
Variance0.67187796
MonotonicityNot monotonic
2024-05-11T04:02:25.917437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 560
54.6%
1 34
 
3.3%
2 7
 
0.7%
3 5
 
0.5%
5 4
 
0.4%
7 3
 
0.3%
4 3
 
0.3%
6 1
 
0.1%
(Missing) 408
39.8%
ValueCountFrequency (%)
0 560
54.6%
1 34
 
3.3%
2 7
 
0.7%
3 5
 
0.5%
4 3
 
0.3%
5 4
 
0.4%
6 1
 
0.1%
7 3
 
0.3%
ValueCountFrequency (%)
7 3
 
0.3%
6 1
 
0.1%
5 4
 
0.4%
4 3
 
0.3%
3 5
 
0.5%
2 7
 
0.7%
1 34
 
3.3%
0 560
54.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)3.3%
Missing364
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean3.7004539
Minimum0
Maximum22
Zeros91
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:26.280880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile10
Maximum22
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4519845
Coefficient of variation (CV)0.93285435
Kurtosis6.0312441
Mean3.7004539
Median Absolute Deviation (MAD)1
Skewness2.1151969
Sum2446
Variance11.916197
MonotonicityNot monotonic
2024-05-11T04:02:26.779768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3 124
 
12.1%
2 122
 
11.9%
0 91
 
8.9%
4 91
 
8.9%
5 68
 
6.6%
1 54
 
5.3%
6 26
 
2.5%
7 19
 
1.9%
9 15
 
1.5%
10 15
 
1.5%
Other values (12) 36
 
3.5%
(Missing) 364
35.5%
ValueCountFrequency (%)
0 91
8.9%
1 54
5.3%
2 122
11.9%
3 124
12.1%
4 91
8.9%
5 68
6.6%
6 26
 
2.5%
7 19
 
1.9%
8 9
 
0.9%
9 15
 
1.5%
ValueCountFrequency (%)
22 1
 
0.1%
20 1
 
0.1%
19 3
0.3%
18 5
0.5%
17 1
 
0.1%
16 4
0.4%
15 2
 
0.2%
14 1
 
0.1%
13 5
0.5%
12 3
0.3%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)3.6%
Missing411
Missing (%)40.1%
Infinite0
Infinite (%)0.0%
Mean3.9739414
Minimum0
Maximum22
Zeros48
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:27.626354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile10
Maximum22
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4280255
Coefficient of variation (CV)0.86262609
Kurtosis6.1691281
Mean3.9739414
Median Absolute Deviation (MAD)1
Skewness2.1751833
Sum2440
Variance11.751359
MonotonicityNot monotonic
2024-05-11T04:02:28.035213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3 124
 
12.1%
2 122
 
11.9%
4 87
 
8.5%
5 72
 
7.0%
1 51
 
5.0%
0 48
 
4.7%
6 26
 
2.5%
7 18
 
1.8%
9 15
 
1.5%
10 15
 
1.5%
Other values (12) 36
 
3.5%
(Missing) 411
40.1%
ValueCountFrequency (%)
0 48
 
4.7%
1 51
5.0%
2 122
11.9%
3 124
12.1%
4 87
8.5%
5 72
7.0%
6 26
 
2.5%
7 18
 
1.8%
8 9
 
0.9%
9 15
 
1.5%
ValueCountFrequency (%)
22 1
 
0.1%
20 1
 
0.1%
19 3
0.3%
18 5
0.5%
17 1
 
0.1%
16 4
0.4%
15 2
 
0.2%
14 1
 
0.1%
13 5
0.5%
12 3
0.3%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.7%
Missing679
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean0.24855491
Minimum0
Maximum6
Zeros283
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:28.449744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.66946718
Coefficient of variation (CV)2.6934377
Kurtosis24.967721
Mean0.24855491
Median Absolute Deviation (MAD)0
Skewness4.3276313
Sum86
Variance0.44818631
MonotonicityNot monotonic
2024-05-11T04:02:28.806534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 283
27.6%
1 53
 
5.2%
4 3
 
0.3%
3 3
 
0.3%
2 3
 
0.3%
6 1
 
0.1%
(Missing) 679
66.2%
ValueCountFrequency (%)
0 283
27.6%
1 53
 
5.2%
2 3
 
0.3%
3 3
 
0.3%
4 3
 
0.3%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 3
 
0.3%
3 3
 
0.3%
2 3
 
0.3%
1 53
 
5.2%
0 283
27.6%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.0%
Missing721
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean0.28289474
Minimum0
Maximum6
Zeros241
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:29.224721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.70750585
Coefficient of variation (CV)2.5009509
Kurtosis21.773688
Mean0.28289474
Median Absolute Deviation (MAD)0
Skewness4.0374093
Sum86
Variance0.50056453
MonotonicityNot monotonic
2024-05-11T04:02:29.620898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 241
 
23.5%
1 53
 
5.2%
4 3
 
0.3%
3 3
 
0.3%
2 3
 
0.3%
6 1
 
0.1%
(Missing) 721
70.3%
ValueCountFrequency (%)
0 241
23.5%
1 53
 
5.2%
2 3
 
0.3%
3 3
 
0.3%
4 3
 
0.3%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 3
 
0.3%
3 3
 
0.3%
2 3
 
0.3%
1 53
 
5.2%
0 241
23.5%

한실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
0
655 
<NA>
370 

Length

Max length4
Median length1
Mean length2.0829268
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 655
63.9%
<NA> 370
36.1%

Length

2024-05-11T04:02:30.157816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:30.572695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 655
63.9%
na 370
36.1%

양실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
0
655 
<NA>
370 

Length

Max length4
Median length1
Mean length2.0829268
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 655
63.9%
<NA> 370
36.1%

Length

2024-05-11T04:02:31.072599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:31.468972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 655
63.9%
na 370
36.1%

욕실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
0
655 
<NA>
370 

Length

Max length4
Median length1
Mean length2.0829268
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 655
63.9%
<NA> 370
36.1%

Length

2024-05-11T04:02:32.012029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:32.411368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 655
63.9%
na 370
36.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing180
Missing (%)17.6%
Memory size2.1 KiB
False
845 
(Missing)
180 
ValueCountFrequency (%)
False 845
82.4%
(Missing) 180
 
17.6%
2024-05-11T04:02:32.782876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
0
613 
<NA>
412 

Length

Max length4
Median length1
Mean length2.2058537
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 613
59.8%
<NA> 412
40.2%

Length

2024-05-11T04:02:33.307434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:33.733554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 613
59.8%
na 412
40.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1025
Missing (%)100.0%
Memory size9.1 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
568 
임대
445 
자가
 
12

Length

Max length4
Median length4
Mean length3.1082927
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> 568
55.4%
임대 445
43.4%
자가 12
 
1.2%

Length

2024-05-11T04:02:34.318350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:34.824892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 568
55.4%
임대 445
43.4%
자가 12
 
1.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
0
571 
<NA>
454 

Length

Max length4
Median length1
Mean length2.3287805
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 (%)
0 571
55.7%
<NA> 454
44.3%

Length

2024-05-11T04:02:35.271474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:35.644374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 571
55.7%
na 454
44.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct39
Distinct (%)15.5%
Missing774
Missing (%)75.5%
Infinite0
Infinite (%)0.0%
Mean31.223108
Minimum0
Maximum4379
Zeros67
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:36.206176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile97.5
Maximum4379
Range4379
Interquartile range (IQR)5

Descriptive statistics

Standard deviation278.31179
Coefficient of variation (CV)8.9136481
Kurtosis240.99382
Mean31.223108
Median Absolute Deviation (MAD)1
Skewness15.382135
Sum7837
Variance77457.454
MonotonicityNot monotonic
2024-05-11T04:02:36.816171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 67
 
6.5%
1 59
 
5.8%
2 25
 
2.4%
5 16
 
1.6%
3 12
 
1.2%
4 10
 
1.0%
10 7
 
0.7%
6 7
 
0.7%
30 5
 
0.5%
15 4
 
0.4%
Other values (29) 39
 
3.8%
(Missing) 774
75.5%
ValueCountFrequency (%)
0 67
6.5%
1 59
5.8%
2 25
 
2.4%
3 12
 
1.2%
4 10
 
1.0%
5 16
 
1.6%
6 7
 
0.7%
8 1
 
0.1%
9 2
 
0.2%
10 7
 
0.7%
ValueCountFrequency (%)
4379 1
0.1%
350 1
0.1%
250 1
0.1%
200 1
0.1%
150 1
0.1%
142 1
0.1%
141 1
0.1%
139 1
0.1%
137 1
0.1%
130 1
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)14.2%
Missing772
Missing (%)75.3%
Infinite0
Infinite (%)0.0%
Mean19.003953
Minimum0
Maximum2073
Zeros30
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T04:02:37.369732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile50
Maximum2073
Range2073
Interquartile range (IQR)6

Descriptive statistics

Standard deviation132.60696
Coefficient of variation (CV)6.9778623
Kurtosis230.9358
Mean19.003953
Median Absolute Deviation (MAD)2
Skewness14.900724
Sum4808
Variance17584.607
MonotonicityNot monotonic
2024-05-11T04:02:37.892089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 66
 
6.4%
2 34
 
3.3%
0 30
 
2.9%
3 25
 
2.4%
4 16
 
1.6%
5 13
 
1.3%
7 10
 
1.0%
10 9
 
0.9%
20 6
 
0.6%
30 4
 
0.4%
Other values (26) 40
 
3.9%
(Missing) 772
75.3%
ValueCountFrequency (%)
0 30
2.9%
1 66
6.4%
2 34
3.3%
3 25
 
2.4%
4 16
 
1.6%
5 13
 
1.3%
6 4
 
0.4%
7 10
 
1.0%
8 3
 
0.3%
9 3
 
0.3%
ValueCountFrequency (%)
2073 1
0.1%
228 1
0.1%
200 1
0.1%
140 1
0.1%
130 1
0.1%
120 2
0.2%
110 1
0.1%
90 1
0.1%
87 1
0.1%
80 1
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
518 
0
507 

Length

Max length4
Median length4
Mean length2.5160976
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> 518
50.5%
0 507
49.5%

Length

2024-05-11T04:02:38.520702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:38.938578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 518
50.5%
0 507
49.5%

침대수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
534 
0
491 

Length

Max length4
Median length4
Mean length2.5629268
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> 534
52.1%
0 491
47.9%

Length

2024-05-11T04:02:39.477077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:02:39.834712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 534
52.1%
0 491
47.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing151
Missing (%)14.7%
Memory size2.1 KiB
False
874 
(Missing)
151 
ValueCountFrequency (%)
False 874
85.3%
(Missing) 151
 
14.7%
2024-05-11T04:02:40.160394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032100003210000-206-1987-0209619870515<NA>3폐업2폐업19970925<NA><NA><NA>02 533086033.25137907서울특별시 서초구 잠원동 64-4<NA><NA>주)풍원용역2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132100003210000-206-1987-0209819870716<NA>3폐업2폐업20150331<NA><NA><NA>02 5934957.00137829서울특별시 서초구 방배동 782-1서울특별시 서초구 동작대로 194 (방배동)6559새재기업(주)2003-03-14 00:00:00I2018-08-31 23:59:59.0건물위생관리업198437.442761443516.483654건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232100003210000-206-1988-0210019880627<NA>3폐업2폐업19990513<NA><NA><NA>02.00137862서울특별시 서초구 서초동 1355-8 중앙로얄 1701<NA><NA>국제흥업(주)2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업202481.661169442563.269272건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332100003210000-206-1988-0210119880725<NA>3폐업2폐업20090818<NA><NA><NA>023482700444.60137855서울특별시 서초구 서초동 1303-16<NA><NA>한동용역2008-06-30 09:22:18I2018-08-31 23:59:59.0건물위생관리업202044.629094444504.112782건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432100003210000-206-1988-0210219880326<NA>3폐업2폐업20050316<NA><NA><NA>0234813755.00137855서울특별시 서초구 서초동 1303-16 제일생명빌딩 신관6층<NA><NA>명신방호실업(주)2003-03-24 00:00:00I2018-08-31 23:59:59.0건물위생관리업202044.629094444504.112782건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532100003210000-206-1989-0210219890429<NA>3폐업2폐업19971120<NA><NA><NA>020566526335.82137860서울특별시 서초구 서초동 1337-8<NA><NA>주)석정상사2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업202536.876907443239.168513건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632100003210000-206-1990-0210319900517<NA>3폐업2폐업20060731<NA><NA><NA>02 5460481102.51137817서울특별시 서초구 방배동 438-15<NA><NA>(주)유일건영2004-12-13 00:00:00I2018-08-31 23:59:59.0건물위생관리업198368.472159442306.22841건물위생관리업<NA><NA><NA><NA><NA><NA>000N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732100003210000-206-1990-0210419901116<NA>3폐업2폐업19970303<NA><NA><NA>02 568179386.48137864서울특별시 서초구 서초동 1425-1<NA><NA>경원산업관리(주)2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업201610.997509442284.81729건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832100003210000-206-1991-0210519910328<NA>3폐업2폐업19990624<NA><NA><NA>0237.60137803서울특별시 서초구 반포동 58-14<NA><NA>신화종합관리(주)2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업200802.087785444557.9179건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932100003210000-206-1991-0210619910508<NA>3폐업2폐업20091221<NA><NA><NA>02 586294154.49137879서울특별시 서초구 서초동 1631-1 3층<NA><NA>(주)서래기업2008-06-30 10:10:06I2018-08-31 23:59:59.0건물위생관리업201808.286684443101.599671건물위생관리업<NA><NA><NA><NA><NA><NA>000N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
101532100003210000-206-2023-000112023-08-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30137-875서울특별시 서초구 서초동 1579-6서울특별시 서초구 사임당로 27, 4층 4C34호 (서초동)6650클리닝에프엠2023-08-07 15:39:40I2022-12-08 00:09:00.0건물위생관리업201094.337058442884.744432<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101632100003210000-206-2023-000122023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30137-878서울특별시 서초구 서초동 1625-10 4층 402호 K547호서울특별시 서초구 사임당로8길 13, 4층 402호 K547호 (서초동)6640재원크린 주식회사2023-10-20 16:13:01I2022-10-30 22:02:00.0건물위생관리업201314.245104442859.398474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101732100003210000-206-2023-000132023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30137-878서울특별시 서초구 서초동 1625-10 4층 402호 K474호서울특별시 서초구 사임당로8길 13, 4층 402호 K474호 (서초동)6640상현종합관리 주식회사2023-10-20 16:25:14I2022-10-30 22:02:00.0건물위생관리업201314.245104442859.398474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101832100003210000-206-2023-000142023-11-03<NA>1영업/정상1영업<NA><NA><NA><NA>02 5842430169.45137-863서울특별시 서초구 서초동 1360-14 파인빌딩서울특별시 서초구 강남대로39길 6-21, 파인빌딩 4층 (서초동)6730(주)파인스태프2023-11-03 14:19:11I2022-11-01 00:05:00.0건물위생관리업202752.158359442755.197041<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101932100003210000-206-2023-000152023-11-10<NA>1영업/정상1영업<NA><NA><NA><NA>02154401123.00137-900서울특별시 서초구 우면동 66-2 우면종합상가서울특별시 서초구 바우뫼로7길 8, 우면종합상가 801호 (우면동)6762주식회사 어드밴티지2023-11-10 13:36:36I2022-10-31 23:02:00.0건물위생관리업202175.011113440963.759051<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102032100003210000-206-2023-000162023-12-13<NA>1영업/정상1영업<NA><NA><NA><NA>02 924 33333.30137-878서울특별시 서초구 서초동 1625-10 제일빌딩 4층 402호 K73호서울특별시 서초구 사임당로8길 13, 제일빌딩 4층 402호 K73호 (서초동)6640주식회사 에스앤지엠2023-12-13 12:55:41I2022-11-01 23:05:00.0건물위생관리업201314.245104442859.398474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102132100003210000-206-2024-000012024-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.00137-860서울특별시 서초구 서초동 1338-12 718호서울특별시 서초구 강남대로 311, 718호 (서초동)6628주식회사 열한시2024-03-06 11:17:51I2023-12-03 00:08:00.0건물위생관리업202605.525331443189.699751<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102232100003210000-206-2024-000022024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA>021555159315.00137-858서울특별시 서초구 서초동 1328-11 대우도씨에빛2 16층 1615호서울특별시 서초구 강남대로 359, 대우도씨에빛2 16층 11615호 (서초동)6621강건클린2024-04-02 15:38:45I2023-12-04 00:04:00.0건물위생관리업202459.257859443620.263219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102332100003210000-206-2024-000032024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30137-878서울특별시 서초구 서초동 1625-10 제일빌딩 4층 402-J84호서울특별시 서초구 사임당로8길 13, 제일빌딩 4층 402-J84호 (서초동)6640드림컴퍼니2024-04-17 15:39:33I2023-12-03 23:09:00.0건물위생관리업201314.245104442859.398474<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102432100003210000-206-2024-000042024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00137-902서울특별시 서초구 잠원동 13-11 2층서울특별시 서초구 강남대로101안길 5, 2층 (잠원동)6524(주)아트플랜2024-04-19 10:52:27I2023-12-03 22:01:00.0건물위생관리업201547.008449446041.94033<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>