Overview

Dataset statistics

Number of variables47
Number of observations1020
Missing cells11570
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory403.5 KiB
Average record size in memory405.1 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric9
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-17949/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (56.0%)Imbalance
업태구분명 is highly imbalanced (98.0%)Imbalance
위생업태명 is highly imbalanced (82.3%)Imbalance
사용끝지하층 is highly imbalanced (56.7%)Imbalance
발한실여부 is highly imbalanced (97.9%)Imbalance
건물소유구분명 is highly imbalanced (71.4%)Imbalance
여성종사자수 is highly imbalanced (57.3%)Imbalance
남성종사자수 is highly imbalanced (72.2%)Imbalance
침대수 is highly imbalanced (71.3%)Imbalance
인허가취소일자 has 1020 (100.0%) missing valuesMissing
폐업일자 has 116 (11.4%) missing valuesMissing
휴업시작일자 has 1020 (100.0%) missing valuesMissing
휴업종료일자 has 1020 (100.0%) missing valuesMissing
재개업일자 has 1020 (100.0%) missing valuesMissing
전화번호 has 220 (21.6%) missing valuesMissing
도로명주소 has 743 (72.8%) missing valuesMissing
도로명우편번호 has 749 (73.4%) missing valuesMissing
좌표정보(X) has 42 (4.1%) missing valuesMissing
좌표정보(Y) has 42 (4.1%) missing valuesMissing
건물지상층수 has 424 (41.6%) missing valuesMissing
건물지하층수 has 384 (37.6%) missing valuesMissing
사용시작지상층 has 644 (63.1%) missing valuesMissing
사용끝지상층 has 868 (85.1%) missing valuesMissing
발한실여부 has 47 (4.6%) missing valuesMissing
좌석수 has 106 (10.4%) missing valuesMissing
조건부허가신고사유 has 1020 (100.0%) missing valuesMissing
조건부허가시작일자 has 1020 (100.0%) missing valuesMissing
조건부허가종료일자 has 1020 (100.0%) missing valuesMissing
다중이용업소여부 has 45 (4.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 46 (4.5%) zerosZeros
건물지상층수 has 454 (44.5%) zerosZeros
건물지하층수 has 454 (44.5%) zerosZeros
사용시작지상층 has 320 (31.4%) zerosZeros
사용끝지상층 has 22 (2.2%) zerosZeros
좌석수 has 34 (3.3%) zerosZeros

Reproduction

Analysis started2024-05-11 08:20:38.139665
Analysis finished2024-05-11 08:20:40.036027
Duration1.9 second
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
3220000
1020 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 1020
100.0%

Length

2024-05-11T08:20:40.232907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:20:40.559879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 1020
100.0%

관리번호
Text

UNIQUE 

Distinct1020
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T08:20:40.949944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22440
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

Unique1020 ?
Unique (%)100.0%

Sample

1st row3220000-203-1976-00001
2nd row3220000-203-1977-00394
3rd row3220000-203-1977-00399
4th row3220000-203-1977-00401
5th row3220000-203-1977-00403
ValueCountFrequency (%)
3220000-203-1976-00001 1
 
0.1%
3220000-203-2002-00010 1
 
0.1%
3220000-203-2002-00012 1
 
0.1%
3220000-203-2001-00057 1
 
0.1%
3220000-203-2001-00062 1
 
0.1%
3220000-203-2001-00063 1
 
0.1%
3220000-203-2001-00064 1
 
0.1%
3220000-203-2001-00065 1
 
0.1%
3220000-203-2002-00001 1
 
0.1%
3220000-203-2002-00002 1
 
0.1%
Other values (1010) 1010
99.0%
2024-05-11T08:20:41.867449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8278
36.9%
2 4340
19.3%
- 3060
 
13.6%
3 2468
 
11.0%
9 1366
 
6.1%
1 1322
 
5.9%
8 465
 
2.1%
4 315
 
1.4%
5 298
 
1.3%
7 268
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19380
86.4%
Dash Punctuation 3060
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8278
42.7%
2 4340
22.4%
3 2468
 
12.7%
9 1366
 
7.0%
1 1322
 
6.8%
8 465
 
2.4%
4 315
 
1.6%
5 298
 
1.5%
7 268
 
1.4%
6 260
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 3060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8278
36.9%
2 4340
19.3%
- 3060
 
13.6%
3 2468
 
11.0%
9 1366
 
6.1%
1 1322
 
5.9%
8 465
 
2.1%
4 315
 
1.4%
5 298
 
1.3%
7 268
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8278
36.9%
2 4340
19.3%
- 3060
 
13.6%
3 2468
 
11.0%
9 1366
 
6.1%
1 1322
 
5.9%
8 465
 
2.1%
4 315
 
1.4%
5 298
 
1.3%
7 268
 
1.2%
Distinct885
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1976-03-02 00:00:00
Maximum2024-04-08 00:00:00
2024-05-11T08:20:42.273829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:20:42.737620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
3
904 
1
116 

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 (%)
3 904
88.6%
1 116
 
11.4%

Length

2024-05-11T08:20:43.162269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:20:43.450363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 904
88.6%
1 116
 
11.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
904 
영업/정상
116 

Length

Max length5
Median length2
Mean length2.3411765
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 904
88.6%
영업/정상 116
 
11.4%

Length

2024-05-11T08:20:43.795757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:20:44.124396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 904
88.6%
영업/정상 116
 
11.4%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2
904 
1
116 

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 (%)
2 904
88.6%
1 116
 
11.4%

Length

2024-05-11T08:20:44.513511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:20:44.809479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 904
88.6%
1 116
 
11.4%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
904 
영업
116 

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 904
88.6%
영업 116
 
11.4%

Length

2024-05-11T08:20:45.144390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:20:45.475932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 904
88.6%
영업 116
 
11.4%

폐업일자
Date

MISSING 

Distinct697
Distinct (%)77.1%
Missing116
Missing (%)11.4%
Memory size8.1 KiB
Minimum1991-04-03 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T08:20:45.863925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:20:46.368741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

전화번호
Text

MISSING 

Distinct704
Distinct (%)88.0%
Missing220
Missing (%)21.6%
Memory size8.1 KiB
2024-05-11T08:20:47.071186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.825
Min length2

Characters and Unicode

Total characters7860
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

Unique662 ?
Unique (%)82.8%

Sample

1st row02 22703130
2nd row02 5658818
3rd row02 5575121
4th row02 4075767
5th row0222264090
ValueCountFrequency (%)
02 595
41.9%
00000 22
 
1.6%
0200000000 17
 
1.2%
5144712 4
 
0.3%
5687843 4
 
0.3%
0 4
 
0.3%
566 3
 
0.2%
5643946 3
 
0.2%
5144185 3
 
0.2%
0234521821 3
 
0.2%
Other values (713) 761
53.6%
2024-05-11T08:20:48.683954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1462
18.6%
2 1227
15.6%
5 1112
14.1%
708
9.0%
4 665
8.5%
6 568
 
7.2%
1 468
 
6.0%
7 466
 
5.9%
3 464
 
5.9%
8 401
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7152
91.0%
Space Separator 708
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1462
20.4%
2 1227
17.2%
5 1112
15.5%
4 665
9.3%
6 568
 
7.9%
1 468
 
6.5%
7 466
 
6.5%
3 464
 
6.5%
8 401
 
5.6%
9 319
 
4.5%
Space Separator
ValueCountFrequency (%)
708
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1462
18.6%
2 1227
15.6%
5 1112
14.1%
708
9.0%
4 665
8.5%
6 568
 
7.2%
1 468
 
6.0%
7 466
 
5.9%
3 464
 
5.9%
8 401
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1462
18.6%
2 1227
15.6%
5 1112
14.1%
708
9.0%
4 665
8.5%
6 568
 
7.2%
1 468
 
6.0%
7 466
 
5.9%
3 464
 
5.9%
8 401
 
5.1%

소재지면적
Real number (ℝ)

ZEROS 

Distinct637
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.456304
Minimum0
Maximum545
Zeros46
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:20:49.137500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.285
Q115
median34.695
Q377.325
95-th percentile132
Maximum545
Range545
Interquartile range (IQR)62.325

Descriptive statistics

Standard deviation47.985177
Coefficient of variation (CV)0.95102442
Kurtosis14.574261
Mean50.456304
Median Absolute Deviation (MAD)24.615
Skewness2.4420732
Sum51465.43
Variance2302.5772
MonotonicityNot monotonic
2024-05-11T08:20:49.596707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 46
 
4.5%
99.0 18
 
1.8%
6.6 15
 
1.5%
132.0 15
 
1.5%
10.0 14
 
1.4%
9.9 13
 
1.3%
15.0 13
 
1.3%
33.0 12
 
1.2%
66.0 11
 
1.1%
16.5 9
 
0.9%
Other values (627) 854
83.7%
ValueCountFrequency (%)
0.0 46
4.5%
3.25 1
 
0.1%
3.3 3
 
0.3%
4.0 1
 
0.1%
4.3 1
 
0.1%
4.41 1
 
0.1%
4.5 1
 
0.1%
4.8 1
 
0.1%
4.9 1
 
0.1%
4.95 4
 
0.4%
ValueCountFrequency (%)
545.0 1
0.1%
380.0 1
0.1%
358.7 1
0.1%
239.4 1
0.1%
224.4 1
0.1%
211.89 1
0.1%
201.5 1
0.1%
198.34 1
0.1%
198.0 1
0.1%
196.08 1
0.1%
Distinct196
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T08:20:50.338780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0245098
Min length6

Characters and Unicode

Total characters6145
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

Unique50 ?
Unique (%)4.9%

Sample

1st row135907
2nd row135925
3rd row135878
4th row135880
5th row135220
ValueCountFrequency (%)
135907 20
 
2.0%
135894 19
 
1.9%
135928 17
 
1.7%
135936 15
 
1.5%
135513 15
 
1.5%
135935 15
 
1.5%
135995 15
 
1.5%
135812 15
 
1.5%
135897 14
 
1.4%
135840 14
 
1.4%
Other values (186) 861
84.4%
2024-05-11T08:20:51.784316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1308
21.3%
1 1275
20.7%
3 1210
19.7%
8 673
11.0%
9 595
9.7%
0 255
 
4.1%
2 238
 
3.9%
4 215
 
3.5%
7 199
 
3.2%
6 152
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6120
99.6%
Dash Punctuation 25
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1308
21.4%
1 1275
20.8%
3 1210
19.8%
8 673
11.0%
9 595
9.7%
0 255
 
4.2%
2 238
 
3.9%
4 215
 
3.5%
7 199
 
3.3%
6 152
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6145
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1308
21.3%
1 1275
20.7%
3 1210
19.7%
8 673
11.0%
9 595
9.7%
0 255
 
4.1%
2 238
 
3.9%
4 215
 
3.5%
7 199
 
3.2%
6 152
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1308
21.3%
1 1275
20.7%
3 1210
19.7%
8 673
11.0%
9 595
9.7%
0 255
 
4.1%
2 238
 
3.9%
4 215
 
3.5%
7 199
 
3.2%
6 152
 
2.5%
Distinct957
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T08:20:52.563146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length25.55098
Min length17

Characters and Unicode

Total characters26062
Distinct characters248
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

Unique900 ?
Unique (%)88.2%

Sample

1st row서울특별시 강남구 역삼동 603 노보텔 앰배서더 강남 서울
2nd row서울특별시 강남구 역삼동 752-41번지 2층 201호
3rd row서울특별시 강남구 삼성동 150-21번지
4th row서울특별시 강남구 삼성동 158-11번지
5th row서울특별시 강남구 수서동 646번지
ValueCountFrequency (%)
서울특별시 1020
21.2%
강남구 1020
21.2%
역삼동 242
 
5.0%
지하1층 203
 
4.2%
논현동 169
 
3.5%
대치동 134
 
2.8%
삼성동 125
 
2.6%
신사동 113
 
2.4%
개포동 65
 
1.4%
청담동 64
 
1.3%
Other values (1131) 1649
34.3%
2024-05-11T08:20:54.108487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4747
18.2%
1281
 
4.9%
1 1118
 
4.3%
1055
 
4.0%
1046
 
4.0%
1028
 
3.9%
1028
 
3.9%
1027
 
3.9%
1027
 
3.9%
1023
 
3.9%
Other values (238) 11682
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15367
59.0%
Decimal Number 4801
 
18.4%
Space Separator 4747
 
18.2%
Dash Punctuation 897
 
3.4%
Close Punctuation 85
 
0.3%
Open Punctuation 85
 
0.3%
Other Punctuation 42
 
0.2%
Uppercase Letter 20
 
0.1%
Math Symbol 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1281
 
8.3%
1055
 
6.9%
1046
 
6.8%
1028
 
6.7%
1028
 
6.7%
1027
 
6.7%
1027
 
6.7%
1023
 
6.7%
1022
 
6.7%
1020
 
6.6%
Other values (213) 4810
31.3%
Decimal Number
ValueCountFrequency (%)
1 1118
23.3%
2 649
13.5%
6 494
10.3%
7 381
 
7.9%
4 373
 
7.8%
0 371
 
7.7%
5 368
 
7.7%
3 363
 
7.6%
9 346
 
7.2%
8 338
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
40.0%
D 5
25.0%
A 4
20.0%
K 1
 
5.0%
S 1
 
5.0%
I 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 20
47.6%
. 19
45.2%
/ 3
 
7.1%
Math Symbol
ValueCountFrequency (%)
< 9
50.0%
> 9
50.0%
Space Separator
ValueCountFrequency (%)
4747
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 897
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15367
59.0%
Common 10675
41.0%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1281
 
8.3%
1055
 
6.9%
1046
 
6.8%
1028
 
6.7%
1028
 
6.7%
1027
 
6.7%
1027
 
6.7%
1023
 
6.7%
1022
 
6.7%
1020
 
6.6%
Other values (213) 4810
31.3%
Common
ValueCountFrequency (%)
4747
44.5%
1 1118
 
10.5%
- 897
 
8.4%
2 649
 
6.1%
6 494
 
4.6%
7 381
 
3.6%
4 373
 
3.5%
0 371
 
3.5%
5 368
 
3.4%
3 363
 
3.4%
Other values (9) 914
 
8.6%
Latin
ValueCountFrequency (%)
B 8
40.0%
D 5
25.0%
A 4
20.0%
K 1
 
5.0%
S 1
 
5.0%
I 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15367
59.0%
ASCII 10695
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4747
44.4%
1 1118
 
10.5%
- 897
 
8.4%
2 649
 
6.1%
6 494
 
4.6%
7 381
 
3.6%
4 373
 
3.5%
0 371
 
3.5%
5 368
 
3.4%
3 363
 
3.4%
Other values (15) 934
 
8.7%
Hangul
ValueCountFrequency (%)
1281
 
8.3%
1055
 
6.9%
1046
 
6.8%
1028
 
6.7%
1028
 
6.7%
1027
 
6.7%
1027
 
6.7%
1023
 
6.7%
1022
 
6.7%
1020
 
6.6%
Other values (213) 4810
31.3%

도로명주소
Text

MISSING 

Distinct269
Distinct (%)97.1%
Missing743
Missing (%)72.8%
Memory size8.1 KiB
2024-05-11T08:20:54.882939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length34.212996
Min length21

Characters and Unicode

Total characters9477
Distinct characters218
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

Unique261 ?
Unique (%)94.2%

Sample

1st row서울특별시 강남구 봉은사로 130, 노보텔 앰배서더 강남 서울 지하2층 (역삼동)
2nd row서울특별시 강남구 역삼로 133, 2층 201호 (역삼동)
3rd row서울특별시 강남구 삼성로104길 7 (삼성동)
4th row서울특별시 강남구 밤고개로34길 4, 지상1층 16호 (세곡동)
5th row서울특별시 강남구 선릉로 654 (삼성동)
ValueCountFrequency (%)
서울특별시 277
 
15.5%
강남구 277
 
15.5%
지하1층 64
 
3.6%
지상1층 41
 
2.3%
역삼동 33
 
1.8%
대치동 28
 
1.6%
삼성동 25
 
1.4%
언주로 24
 
1.3%
신사동 23
 
1.3%
논현동 22
 
1.2%
Other values (509) 972
54.4%
2024-05-11T08:20:56.254795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1509
 
15.9%
1 468
 
4.9%
316
 
3.3%
305
 
3.2%
, 296
 
3.1%
295
 
3.1%
293
 
3.1%
293
 
3.1%
) 287
 
3.0%
( 287
 
3.0%
Other values (208) 5128
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5571
58.8%
Space Separator 1509
 
15.9%
Decimal Number 1493
 
15.8%
Other Punctuation 297
 
3.1%
Close Punctuation 287
 
3.0%
Open Punctuation 287
 
3.0%
Dash Punctuation 18
 
0.2%
Uppercase Letter 13
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
316
 
5.7%
305
 
5.5%
295
 
5.3%
293
 
5.3%
293
 
5.3%
284
 
5.1%
282
 
5.1%
280
 
5.0%
277
 
5.0%
277
 
5.0%
Other values (184) 2669
47.9%
Decimal Number
ValueCountFrequency (%)
1 468
31.3%
2 264
17.7%
3 160
 
10.7%
0 128
 
8.6%
4 119
 
8.0%
5 85
 
5.7%
6 77
 
5.2%
8 74
 
5.0%
7 72
 
4.8%
9 46
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 7
53.8%
M 2
 
15.4%
W 1
 
7.7%
K 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 296
99.7%
. 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
1509
100.0%
Close Punctuation
ValueCountFrequency (%)
) 287
100.0%
Open Punctuation
ValueCountFrequency (%)
( 287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5571
58.8%
Common 3893
41.1%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
316
 
5.7%
305
 
5.5%
295
 
5.3%
293
 
5.3%
293
 
5.3%
284
 
5.1%
282
 
5.1%
280
 
5.0%
277
 
5.0%
277
 
5.0%
Other values (184) 2669
47.9%
Common
ValueCountFrequency (%)
1509
38.8%
1 468
 
12.0%
, 296
 
7.6%
) 287
 
7.4%
( 287
 
7.4%
2 264
 
6.8%
3 160
 
4.1%
0 128
 
3.3%
4 119
 
3.1%
5 85
 
2.2%
Other values (8) 290
 
7.4%
Latin
ValueCountFrequency (%)
B 7
53.8%
M 2
 
15.4%
W 1
 
7.7%
K 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5571
58.8%
ASCII 3906
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1509
38.6%
1 468
 
12.0%
, 296
 
7.6%
) 287
 
7.3%
( 287
 
7.3%
2 264
 
6.8%
3 160
 
4.1%
0 128
 
3.3%
4 119
 
3.0%
5 85
 
2.2%
Other values (14) 303
 
7.8%
Hangul
ValueCountFrequency (%)
316
 
5.7%
305
 
5.5%
295
 
5.3%
293
 
5.3%
293
 
5.3%
284
 
5.1%
282
 
5.1%
280
 
5.0%
277
 
5.0%
277
 
5.0%
Other values (184) 2669
47.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct156
Distinct (%)57.6%
Missing749
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean6181.5424
Minimum6000
Maximum6378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:20:56.711735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile6019
Q16074.5
median6176
Q36279.5
95-th percentile6343
Maximum6378
Range378
Interquartile range (IQR)205

Descriptive statistics

Standard deviation109.78105
Coefficient of variation (CV)0.017759491
Kurtosis-1.2897593
Mean6181.5424
Median Absolute Deviation (MAD)104
Skewness-0.011216618
Sum1675198
Variance12051.879
MonotonicityNot monotonic
2024-05-11T08:20:57.303233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6164 10
 
1.0%
6329 7
 
0.7%
6050 7
 
0.7%
6124 7
 
0.7%
6225 5
 
0.5%
6343 5
 
0.5%
6262 5
 
0.5%
6280 4
 
0.4%
6094 4
 
0.4%
6022 3
 
0.3%
Other values (146) 214
 
21.0%
(Missing) 749
73.4%
ValueCountFrequency (%)
6000 1
 
0.1%
6010 1
 
0.1%
6012 2
0.2%
6014 3
0.3%
6015 1
 
0.1%
6017 2
0.2%
6018 3
0.3%
6019 2
0.2%
6021 1
 
0.1%
6022 3
0.3%
ValueCountFrequency (%)
6378 1
 
0.1%
6377 2
 
0.2%
6373 1
 
0.1%
6367 1
 
0.1%
6365 1
 
0.1%
6354 3
0.3%
6352 1
 
0.1%
6349 1
 
0.1%
6347 1
 
0.1%
6343 5
0.5%
Distinct859
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T08:20:58.058054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length4.6480392
Min length1

Characters and Unicode

Total characters4741
Distinct characters432
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

Unique748 ?
Unique (%)73.3%

Sample

1st row노보텔앰배서더 강남
2nd row일성이발관
3rd row성진
4th row삼성
5th row왕북
ValueCountFrequency (%)
이용원 27
 
2.4%
현대 10
 
0.9%
바버샵 10
 
0.9%
명성 6
 
0.5%
삼성 6
 
0.5%
barbershop 6
 
0.5%
코엑스 5
 
0.4%
이발 5
 
0.4%
광주 5
 
0.4%
태양 5
 
0.4%
Other values (879) 1051
92.5%
2024-05-11T08:20:59.250131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
450
 
9.5%
278
 
5.9%
252
 
5.3%
137
 
2.9%
117
 
2.5%
116
 
2.4%
115
 
2.4%
101
 
2.1%
89
 
1.9%
83
 
1.8%
Other values (422) 3003
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4307
90.8%
Uppercase Letter 124
 
2.6%
Space Separator 116
 
2.4%
Lowercase Letter 112
 
2.4%
Open Punctuation 29
 
0.6%
Close Punctuation 29
 
0.6%
Other Punctuation 13
 
0.3%
Decimal Number 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
450
 
10.4%
278
 
6.5%
252
 
5.9%
137
 
3.2%
117
 
2.7%
115
 
2.7%
101
 
2.3%
89
 
2.1%
83
 
1.9%
67
 
1.6%
Other values (369) 2618
60.8%
Uppercase Letter
ValueCountFrequency (%)
B 21
16.9%
O 10
 
8.1%
A 10
 
8.1%
E 10
 
8.1%
R 9
 
7.3%
L 7
 
5.6%
S 7
 
5.6%
H 7
 
5.6%
M 6
 
4.8%
P 6
 
4.8%
Other values (14) 31
25.0%
Lowercase Letter
ValueCountFrequency (%)
r 18
16.1%
e 13
11.6%
o 11
9.8%
b 10
8.9%
a 9
8.0%
p 9
8.0%
s 9
8.0%
h 9
8.0%
i 5
 
4.5%
u 4
 
3.6%
Other values (9) 15
13.4%
Decimal Number
ValueCountFrequency (%)
3 4
36.4%
2 3
27.3%
1 3
27.3%
0 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 10
76.9%
? 2
 
15.4%
& 1
 
7.7%
Space Separator
ValueCountFrequency (%)
116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4307
90.8%
Latin 236
 
5.0%
Common 198
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
450
 
10.4%
278
 
6.5%
252
 
5.9%
137
 
3.2%
117
 
2.7%
115
 
2.7%
101
 
2.3%
89
 
2.1%
83
 
1.9%
67
 
1.6%
Other values (369) 2618
60.8%
Latin
ValueCountFrequency (%)
B 21
 
8.9%
r 18
 
7.6%
e 13
 
5.5%
o 11
 
4.7%
b 10
 
4.2%
O 10
 
4.2%
A 10
 
4.2%
E 10
 
4.2%
a 9
 
3.8%
p 9
 
3.8%
Other values (33) 115
48.7%
Common
ValueCountFrequency (%)
116
58.6%
( 29
 
14.6%
) 29
 
14.6%
. 10
 
5.1%
3 4
 
2.0%
2 3
 
1.5%
1 3
 
1.5%
? 2
 
1.0%
0 1
 
0.5%
& 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4307
90.8%
ASCII 434
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
450
 
10.4%
278
 
6.5%
252
 
5.9%
137
 
3.2%
117
 
2.7%
115
 
2.7%
101
 
2.3%
89
 
2.1%
83
 
1.9%
67
 
1.6%
Other values (369) 2618
60.8%
ASCII
ValueCountFrequency (%)
116
26.7%
( 29
 
6.7%
) 29
 
6.7%
B 21
 
4.8%
r 18
 
4.1%
e 13
 
3.0%
o 11
 
2.5%
b 10
 
2.3%
. 10
 
2.3%
O 10
 
2.3%
Other values (43) 167
38.5%
Distinct534
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1999-01-19 00:00:00
Maximum2024-05-07 13:34:03
2024-05-11T08:20:59.682610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:21:00.192960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
I
927 
U
93 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 927
90.9%
U 93
 
9.1%

Length

2024-05-11T08:21:00.639339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:00.947860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 927
90.9%
u 93
 
9.1%
Distinct128
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:21:01.297287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:21:01.749648image/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
일반이용업
1018 
이용업 기타
 
2

Length

Max length6
Median length5
Mean length5.0019608
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 1018
99.8%
이용업 기타 2
 
0.2%

Length

2024-05-11T08:21:02.190960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:02.512671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 1018
99.6%
이용업 2
 
0.2%
기타 2
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct725
Distinct (%)74.1%
Missing42
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean203902.82
Minimum201621.77
Maximum209628.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:02.933705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201621.77
5-th percentile202061.54
Q1202842.39
median203583.67
Q3204769.39
95-th percentile206581.79
Maximum209628.77
Range8007.006
Interquartile range (IQR)1927.0043

Descriptive statistics

Standard deviation1442.6432
Coefficient of variation (CV)0.0070751511
Kurtosis1.586037
Mean203902.82
Median Absolute Deviation (MAD)936.9364
Skewness1.0755299
Sum1.9941695 × 108
Variance2081219.5
MonotonicityNot monotonic
2024-05-11T08:21:03.417952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205130.591678902 7
 
0.7%
202396.738264143 6
 
0.6%
202482.701418444 6
 
0.6%
202108.433846703 5
 
0.5%
205707.089399978 5
 
0.5%
204705.273047989 5
 
0.5%
203504.279001895 5
 
0.5%
203467.506368803 5
 
0.5%
205340.631121567 4
 
0.4%
203125.055 4
 
0.4%
Other values (715) 926
90.8%
(Missing) 42
 
4.1%
ValueCountFrequency (%)
201621.76711437 2
0.2%
201657.313312924 1
0.1%
201667.786866215 1
0.1%
201695.800640834 1
0.1%
201718.922834407 1
0.1%
201733.702293954 1
0.1%
201749.456413619 1
0.1%
201753.375869612 1
0.1%
201757.494098748 1
0.1%
201766.531228331 1
0.1%
ValueCountFrequency (%)
209628.773156947 1
 
0.1%
209472.0 1
 
0.1%
209423.649311203 1
 
0.1%
209260.799930773 3
0.3%
209201.961413428 1
 
0.1%
209052.072465426 2
0.2%
208937.760652081 2
0.2%
208857.805045671 2
0.2%
208636.679822655 3
0.3%
207914.471699463 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct725
Distinct (%)74.1%
Missing42
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean444845.33
Minimum440208.56
Maximum447864.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:03.853280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440208.56
5-th percentile442477.8
Q1443773.13
median444845.88
Q3446097.11
95-th percentile447041.86
Maximum447864.76
Range7656.2053
Interquartile range (IQR)2323.9753

Descriptive statistics

Standard deviation1452.2777
Coefficient of variation (CV)0.00326468
Kurtosis-0.50792666
Mean444845.33
Median Absolute Deviation (MAD)1137.6226
Skewness-0.26116991
Sum4.3505874 × 108
Variance2109110.4
MonotonicityNot monotonic
2024-05-11T08:21:04.342491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445590.096837802 7
 
0.7%
446331.822616635 6
 
0.6%
444787.812950605 6
 
0.6%
446160.618240423 5
 
0.5%
443914.194133105 5
 
0.5%
444831.426571868 5
 
0.5%
443769.38050993 5
 
0.5%
443139.661679032 5
 
0.5%
445354.571117445 4
 
0.4%
446027.47 4
 
0.4%
Other values (715) 926
90.8%
(Missing) 42
 
4.1%
ValueCountFrequency (%)
440208.558412381 1
 
0.1%
440361.989121116 1
 
0.1%
440934.812128081 3
0.3%
441287.0 1
 
0.1%
441296.14728247 1
 
0.1%
441325.94 1
 
0.1%
441344.950914234 1
 
0.1%
441358.738688555 1
 
0.1%
441399.856009506 1
 
0.1%
441440.715082403 1
 
0.1%
ValueCountFrequency (%)
447864.763737276 1
 
0.1%
447400.303560123 2
0.2%
447393.51192286 1
 
0.1%
447382.746953318 1
 
0.1%
447371.866295615 3
0.3%
447366.539357322 2
0.2%
447361.253545418 1
 
0.1%
447329.953691113 1
 
0.1%
447321.457699177 1
 
0.1%
447313.362226154 4
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
일반이용업
973 
<NA>
 
45
이용업 기타
 
2

Length

Max length6
Median length5
Mean length4.9578431
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 973
95.4%
<NA> 45
 
4.4%
이용업 기타 2
 
0.2%

Length

2024-05-11T08:21:04.852972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:05.204821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 973
95.2%
na 45
 
4.4%
이용업 2
 
0.2%
기타 2
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.2%
Missing424
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean1.204698
Minimum0
Maximum54
Zeros454
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:05.525991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.25
Maximum54
Range54
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.915285
Coefficient of variation (CV)3.2500138
Kurtosis67.248487
Mean1.204698
Median Absolute Deviation (MAD)0
Skewness6.8338551
Sum718
Variance15.329457
MonotonicityNot monotonic
2024-05-11T08:21:06.056168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 454
44.5%
1 35
 
3.4%
2 32
 
3.1%
3 18
 
1.8%
5 14
 
1.4%
4 7
 
0.7%
7 7
 
0.7%
6 6
 
0.6%
8 4
 
0.4%
17 4
 
0.4%
Other values (9) 15
 
1.5%
(Missing) 424
41.6%
ValueCountFrequency (%)
0 454
44.5%
1 35
 
3.4%
2 32
 
3.1%
3 18
 
1.8%
4 7
 
0.7%
5 14
 
1.4%
6 6
 
0.6%
7 7
 
0.7%
8 4
 
0.4%
9 3
 
0.3%
ValueCountFrequency (%)
54 1
 
0.1%
26 3
0.3%
24 1
 
0.1%
20 1
 
0.1%
17 4
0.4%
16 1
 
0.1%
14 3
0.3%
11 1
 
0.1%
10 1
 
0.1%
9 3
0.3%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.6%
Missing384
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean0.47012579
Minimum0
Maximum18
Zeros454
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:06.414200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2091725
Coefficient of variation (CV)2.5720192
Kurtosis77.919036
Mean0.47012579
Median Absolute Deviation (MAD)0
Skewness6.9890474
Sum299
Variance1.4620983
MonotonicityNot monotonic
2024-05-11T08:21:06.822972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 454
44.5%
1 134
 
13.1%
2 29
 
2.8%
3 7
 
0.7%
6 5
 
0.5%
7 3
 
0.3%
18 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
8 1
 
0.1%
(Missing) 384
37.6%
ValueCountFrequency (%)
0 454
44.5%
1 134
 
13.1%
2 29
 
2.8%
3 7
 
0.7%
4 1
 
0.1%
5 1
 
0.1%
6 5
 
0.5%
7 3
 
0.3%
8 1
 
0.1%
18 1
 
0.1%
ValueCountFrequency (%)
18 1
 
0.1%
8 1
 
0.1%
7 3
 
0.3%
6 5
 
0.5%
5 1
 
0.1%
4 1
 
0.1%
3 7
 
0.7%
2 29
 
2.8%
1 134
 
13.1%
0 454
44.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.1%
Missing644
Missing (%)63.1%
Infinite0
Infinite (%)0.0%
Mean0.30851064
Minimum0
Maximum7
Zeros320
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:07.185399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.90068532
Coefficient of variation (CV)2.9194628
Kurtosis17.090013
Mean0.30851064
Median Absolute Deviation (MAD)0
Skewness3.7990425
Sum116
Variance0.81123404
MonotonicityNot monotonic
2024-05-11T08:21:07.559016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 320
31.4%
1 25
 
2.5%
2 15
 
1.5%
3 9
 
0.9%
4 4
 
0.4%
5 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
(Missing) 644
63.1%
ValueCountFrequency (%)
0 320
31.4%
1 25
 
2.5%
2 15
 
1.5%
3 9
 
0.9%
4 4
 
0.4%
5 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 4
 
0.4%
3 9
 
0.9%
2 15
 
1.5%
1 25
 
2.5%
0 320
31.4%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)5.9%
Missing868
Missing (%)85.1%
Infinite0
Infinite (%)0.0%
Mean1.6710526
Minimum0
Maximum9
Zeros22
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:07.968402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3211289
Coefficient of variation (CV)0.79059684
Kurtosis7.2879857
Mean1.6710526
Median Absolute Deviation (MAD)1
Skewness1.9193376
Sum254
Variance1.7453817
MonotonicityNot monotonic
2024-05-11T08:21:08.342485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 53
 
5.2%
2 51
 
5.0%
0 22
 
2.2%
3 16
 
1.6%
4 6
 
0.6%
9 1
 
0.1%
5 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
(Missing) 868
85.1%
ValueCountFrequency (%)
0 22
2.2%
1 53
5.2%
2 51
5.0%
3 16
 
1.6%
4 6
 
0.6%
5 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
9 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 6
 
0.6%
3 16
 
1.6%
2 51
5.0%
1 53
5.2%
0 22
2.2%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
636 
0
320 
1
 
45
2
 
18
3
 
1

Length

Max length4
Median length4
Mean length2.8705882
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 636
62.4%
0 320
31.4%
1 45
 
4.4%
2 18
 
1.8%
3 1
 
0.1%

Length

2024-05-11T08:21:08.843062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:09.212364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 636
62.4%
0 320
31.4%
1 45
 
4.4%
2 18
 
1.8%
3 1
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
793 
1
170 
2
 
36
0
 
20
3
 
1

Length

Max length4
Median length4
Mean length3.3323529
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 793
77.7%
1 170
 
16.7%
2 36
 
3.5%
0 20
 
2.0%
3 1
 
0.1%

Length

2024-05-11T08:21:09.614129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:09.997192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 793
77.7%
1 170
 
16.7%
2 36
 
3.5%
0 20
 
2.0%
3 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
548 
0
472 

Length

Max length4
Median length4
Mean length2.6117647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 548
53.7%
0 472
46.3%

Length

2024-05-11T08:21:10.546383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:10.985868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 548
53.7%
0 472
46.3%

양실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
548 
0
472 

Length

Max length4
Median length4
Mean length2.6117647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 548
53.7%
0 472
46.3%

Length

2024-05-11T08:21:11.422057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:11.804575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 548
53.7%
0 472
46.3%

욕실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
548 
0
472 

Length

Max length4
Median length4
Mean length2.6117647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 548
53.7%
0 472
46.3%

Length

2024-05-11T08:21:12.212348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:12.707907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 548
53.7%
0 472
46.3%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing47
Missing (%)4.6%
Memory size2.1 KiB
False
971 
True
 
2
(Missing)
 
47
ValueCountFrequency (%)
False 971
95.2%
True 2
 
0.2%
(Missing) 47
 
4.6%
2024-05-11T08:21:13.057213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)1.5%
Missing106
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean5.3862144
Minimum0
Maximum13
Zeros34
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T08:21:13.352935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q38
95-th percentile10.35
Maximum13
Range13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2305813
Coefficient of variation (CV)0.59978697
Kurtosis-1.1171669
Mean5.3862144
Median Absolute Deviation (MAD)3
Skewness0.28812626
Sum4923
Variance10.436655
MonotonicityNot monotonic
2024-05-11T08:21:13.797479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 157
15.4%
3 155
15.2%
8 84
8.2%
4 80
7.8%
10 80
7.8%
9 78
7.6%
7 76
7.5%
6 55
 
5.4%
5 47
 
4.6%
0 34
 
3.3%
Other values (4) 68
6.7%
(Missing) 106
10.4%
ValueCountFrequency (%)
0 34
 
3.3%
1 22
 
2.2%
2 157
15.4%
3 155
15.2%
4 80
7.8%
5 47
 
4.6%
6 55
 
5.4%
7 76
7.5%
8 84
8.2%
9 78
7.6%
ValueCountFrequency (%)
13 3
 
0.3%
12 19
 
1.9%
11 24
 
2.4%
10 80
7.8%
9 78
7.6%
8 84
8.2%
7 76
7.5%
6 55
5.4%
5 47
4.6%
4 80
7.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1020
Missing (%)100.0%
Memory size9.1 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
927 
임대
 
91
자가
 
2

Length

Max length4
Median length4
Mean length3.8176471
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> 927
90.9%
임대 91
 
8.9%
자가 2
 
0.2%

Length

2024-05-11T08:21:14.262314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:14.670878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 927
90.9%
임대 91
 
8.9%
자가 2
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
845 
0
175 

Length

Max length4
Median length4
Mean length3.4852941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 845
82.8%
0 175
 
17.2%

Length

2024-05-11T08:21:15.148763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:15.535934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 845
82.8%
0 175
 
17.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
931 
0
 
89

Length

Max length4
Median length4
Mean length3.7382353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 931
91.3%
0 89
 
8.7%

Length

2024-05-11T08:21:15.957819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:16.427859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 931
91.3%
0 89
 
8.7%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
931 
0
 
87
1
 
2

Length

Max length4
Median length4
Mean length3.7382353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 931
91.3%
0 87
 
8.5%
1 2
 
0.2%

Length

2024-05-11T08:21:17.202665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:17.576818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 931
91.3%
0 87
 
8.5%
1 2
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
860 
0
160 

Length

Max length4
Median length4
Mean length3.5294118
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 860
84.3%
0 160
 
15.7%

Length

2024-05-11T08:21:18.002275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:18.377580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 860
84.3%
0 160
 
15.7%

침대수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
860 
0
155 
1
 
2
2
 
2
6
 
1

Length

Max length4
Median length4
Mean length3.5294118
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 860
84.3%
0 155
 
15.2%
1 2
 
0.2%
2 2
 
0.2%
6 1
 
0.1%

Length

2024-05-11T08:21:18.941793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:19.431838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 860
84.3%
0 155
 
15.2%
1 2
 
0.2%
2 2
 
0.2%
6 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing45
Missing (%)4.4%
Memory size2.1 KiB
False
975 
(Missing)
 
45
ValueCountFrequency (%)
False 975
95.6%
(Missing) 45
 
4.4%
2024-05-11T08:21:19.779428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032200003220000-203-1976-0000119760302<NA>3폐업2폐업20220105<NA><NA><NA>02 2270313070.9135907서울특별시 강남구 역삼동 603 노보텔 앰배서더 강남 서울서울특별시 강남구 봉은사로 130, 노보텔 앰배서더 강남 서울 지하2층 (역삼동)6124노보텔앰배서더 강남2022-01-05 15:25:41U2022-01-07 02:40:00.0일반이용업202482.701418444787.812951일반이용업000022000N6<NA><NA><NA><NA>00000N
132200003220000-203-1977-0039419771016<NA>3폐업2폐업20141216<NA><NA><NA><NA>59.83135925서울특별시 강남구 역삼동 752-41번지 2층 201호서울특별시 강남구 역삼로 133, 2층 201호 (역삼동)6244일성이발관2014-06-02 09:18:45I2018-08-31 23:59:59.0일반이용업202954.797197443586.401425일반이용업1<NA><NA>1<NA><NA><NA><NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232200003220000-203-1977-0039919771016<NA>3폐업2폐업20131114<NA><NA><NA>02 565881819.8135878서울특별시 강남구 삼성동 150-21번지서울특별시 강남구 삼성로104길 7 (삼성동)6165성진2003-07-22 00:00:00I2018-08-31 23:59:59.0일반이용업204811.79271445410.951112일반이용업<NA>1<NA><NA><NA>1<NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332200003220000-203-1977-0040119771016<NA>3폐업2폐업19961205<NA><NA><NA>02 557512123.1135880서울특별시 강남구 삼성동 158-11번지<NA><NA>삼성2001-08-03 00:00:00I2018-08-31 23:59:59.0일반이용업205089.784538445151.814121일반이용업000<NA>0<NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432200003220000-203-1977-0040319771016<NA>3폐업2폐업20030225<NA><NA><NA>02 407576717.17135220서울특별시 강남구 수서동 646번지<NA><NA>왕북2003-02-27 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532200003220000-203-1977-0040419771016<NA>1영업/정상1영업<NA><NA><NA><NA>022226409041.29135190서울특별시 강남구 세곡동 124-2서울특별시 강남구 밤고개로34길 4, 지상1층 16호 (세곡동)6365조일이용원2022-02-10 11:39:57U2022-02-12 02:40:00.0일반이용업209423.649311440208.558412일반이용업1<NA><NA>1<NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632200003220000-203-1978-0039619780410<NA>3폐업2폐업20030207<NA><NA><NA>02 0000025.83135816서울특별시 강남구 논현동 65번지<NA><NA>대진2003-02-26 00:00:00I2018-08-31 23:59:59.0일반이용업202548.349223446323.537756일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732200003220000-203-1978-0039719780927<NA>3폐업2폐업19990817<NA><NA><NA>02 567667245.54135509서울특별시 강남구 삼성동 117-0번지<NA><NA>계림2001-08-03 00:00:00I2018-08-31 23:59:59.0일반이용업204512.650008445567.168344일반이용업000<NA>0<NA>000N7<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832200003220000-203-1978-0040519780615<NA>3폐업2폐업19940516<NA><NA><NA>02 555908237.1135927서울특별시 강남구 역삼동 765-2번지<NA><NA>백림2001-08-03 00:00:00I2018-08-31 23:59:59.0일반이용업204479.130897443880.723159일반이용업000<NA>0<NA>000N8<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932200003220000-203-1979-0039819790616<NA>3폐업2폐업19931012<NA><NA><NA>020548613427.0135830서울특별시 강남구 논현동 242-29번지<NA><NA>김인선이용원2001-08-03 00:00:00I2018-08-31 23:59:59.0일반이용업203584.665152446005.056082일반이용업000<NA>0<NA>000N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
101032200003220000-203-2023-000022023-02-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.88135-509서울특별시 강남구 삼성동 118-8서울특별시 강남구 삼성로107길 18, 지상1층 102호 (삼성동)6154칸바버샵 삼성중앙역점2023-02-15 14:06:51I2022-12-01 23:07:00.0일반이용업204561.851681445454.785937<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101132200003220000-203-2023-000032023-02-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.5135-864서울특별시 강남구 삼성동 24-7서울특별시 강남구 봉은사로73길 48, 지상1층 103호 (삼성동)6094더 샤갈(THE CHAGAL)2023-03-06 18:00:52U2022-12-03 00:08:00.0일반이용업204323.965946445918.650625<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101232200003220000-203-2023-000042023-03-21<NA>3폐업2폐업2024-05-07<NA><NA><NA><NA>4.95135-776서울특별시 강남구 대치동 66 쌍용아파트서울특별시 강남구 영동대로 210, 상가동 지하2층 (대치동, 쌍용아파트)6286현대2024-05-07 13:34:03U2023-12-05 00:09:00.0일반이용업206228.074633443988.38641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101332200003220000-203-2023-000052023-08-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.38135-200서울특별시 강남구 자곡동 658 강남힐스테이트에코서울특별시 강남구 자곡로 202, 강남힐스테이트에코 지상1층 118호 (자곡동)6373블루클럽 자곡점2023-08-31 17:09:16I2022-12-09 00:02:00.0일반이용업209201.961413441399.85601<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101432200003220000-203-2023-000062023-09-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.5135-921서울특별시 강남구 역삼동 730-4서울특별시 강남구 언주로 407, 지상2층 202호 (역삼동)6225모범이용원2023-09-15 09:50:25I2022-12-08 23:07:00.0일반이용업203811.525606444135.909946<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101532200003220000-203-2024-000012024-01-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.5135-555서울특별시 강남구 도곡동 467-24 우성캐릭터199서울특별시 강남구 언주로 118, 지하1층 스포라인호 (도곡동, 우성캐릭터199)6295자마이카이용원2024-01-04 14:49:30I2023-12-01 00:06:00.0일반이용업204518.87998442703.584824<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101632200003220000-203-2024-000022024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.2135-516서울특별시 강남구 일원동 677-2서울특별시 강남구 일원로3길 28, 지상1층 (일원동)6343올라 아미고 바버샵2024-03-05 15:27:04I2023-12-03 00:07:00.0일반이용업207247.201588443288.522439<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101732200003220000-203-2024-000032024-03-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.7135-997서울특별시 강남구 대치동 912-11서울특별시 강남구 역삼로 456-1, 지상1층 101호 (대치동)6202바버리그(BARBER LEAGUE)2024-03-15 12:14:37I2023-12-02 23:07:00.0일반이용업205014.674862444460.9198<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101832200003220000-203-2024-000042024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0135-954서울특별시 강남구 청담동 83-7서울특별시 강남구 도산대로55길 40, 지상3층 (청담동)6014H스타일(에비뉴청담점)2024-04-03 17:52:30I2023-12-04 00:05:00.0일반이용업203560.930552447096.203799<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101932200003220000-203-2024-000052024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.9135-894서울특별시 강남구 신사동 617-2 대웅빌딩서울특별시 강남구 압구정로 228, 대웅빌딩 지상1층 106호 (신사동)6023쿠프(coupe)2024-04-08 12:30:25I2023-12-03 23:00:00.0일반이용업202829.555274447382.746953<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>