Overview

Dataset statistics

Number of variables47
Number of observations876
Missing cells8152
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory346.6 KiB
Average record size in memory405.2 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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-17945/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (52.2%)Imbalance
업태구분명 is highly imbalanced (92.5%)Imbalance
위생업태명 is highly imbalanced (74.8%)Imbalance
사용시작지하층 is highly imbalanced (63.8%)Imbalance
사용끝지하층 is highly imbalanced (69.3%)Imbalance
한실수 is highly imbalanced (67.5%)Imbalance
양실수 is highly imbalanced (67.5%)Imbalance
욕실수 is highly imbalanced (67.5%)Imbalance
건물소유구분명 is highly imbalanced (70.9%)Imbalance
세탁기수 is highly imbalanced (67.5%)Imbalance
여성종사자수 is highly imbalanced (77.4%)Imbalance
남성종사자수 is highly imbalanced (73.4%)Imbalance
회수건조수 is highly imbalanced (67.5%)Imbalance
침대수 is highly imbalanced (67.5%)Imbalance
인허가취소일자 has 876 (100.0%) missing valuesMissing
폐업일자 has 133 (15.2%) missing valuesMissing
휴업시작일자 has 876 (100.0%) missing valuesMissing
휴업종료일자 has 876 (100.0%) missing valuesMissing
재개업일자 has 876 (100.0%) missing valuesMissing
전화번호 has 205 (23.4%) missing valuesMissing
도로명주소 has 584 (66.7%) missing valuesMissing
도로명우편번호 has 595 (67.9%) missing valuesMissing
좌표정보(X) has 59 (6.7%) missing valuesMissing
좌표정보(Y) has 59 (6.7%) missing valuesMissing
건물지상층수 has 52 (5.9%) missing valuesMissing
건물지하층수 has 52 (5.9%) missing valuesMissing
사용시작지상층 has 52 (5.9%) missing valuesMissing
사용끝지상층 has 52 (5.9%) missing valuesMissing
발한실여부 has 68 (7.8%) missing valuesMissing
좌석수 has 52 (5.9%) missing valuesMissing
조건부허가신고사유 has 876 (100.0%) missing valuesMissing
조건부허가시작일자 has 876 (100.0%) missing valuesMissing
조건부허가종료일자 has 876 (100.0%) missing valuesMissing
다중이용업소여부 has 52 (5.9%) missing valuesMissing
사용끝지상층 is highly skewed (γ1 = 27.70923617)Skewed
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 92 (10.5%) zerosZeros
건물지상층수 has 768 (87.7%) zerosZeros
건물지하층수 has 780 (89.0%) zerosZeros
사용시작지상층 has 758 (86.5%) zerosZeros
사용끝지상층 has 778 (88.8%) zerosZeros
좌석수 has 92 (10.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:43:07.291375
Analysis finished2024-05-11 05:43:09.217092
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
3180000
876 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 876
100.0%

Length

2024-05-11T05:43:09.619374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:09.929706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 876
100.0%

관리번호
Text

UNIQUE 

Distinct876
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T05:43:10.466311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters19272
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

Unique876 ?
Unique (%)100.0%

Sample

1st row3180000-203-1963-01516
2nd row3180000-203-1963-01680
3rd row3180000-203-1963-01684
4th row3180000-203-1966-01717
5th row3180000-203-1967-01718
ValueCountFrequency (%)
3180000-203-1963-01516 1
 
0.1%
3180000-203-2003-00098 1
 
0.1%
3180000-203-2003-00088 1
 
0.1%
3180000-203-2004-00013 1
 
0.1%
3180000-203-2003-00089 1
 
0.1%
3180000-203-2003-00090 1
 
0.1%
3180000-203-2003-00091 1
 
0.1%
3180000-203-2003-00092 1
 
0.1%
3180000-203-2003-00093 1
 
0.1%
3180000-203-2003-00094 1
 
0.1%
Other values (866) 866
98.9%
2024-05-11T05:43:11.771621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7128
37.0%
- 2628
 
13.6%
1 2265
 
11.8%
3 2081
 
10.8%
2 1598
 
8.3%
8 1294
 
6.7%
9 837
 
4.3%
6 401
 
2.1%
7 367
 
1.9%
5 353
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16644
86.4%
Dash Punctuation 2628
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7128
42.8%
1 2265
 
13.6%
3 2081
 
12.5%
2 1598
 
9.6%
8 1294
 
7.8%
9 837
 
5.0%
6 401
 
2.4%
7 367
 
2.2%
5 353
 
2.1%
4 320
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 2628
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7128
37.0%
- 2628
 
13.6%
1 2265
 
11.8%
3 2081
 
10.8%
2 1598
 
8.3%
8 1294
 
6.7%
9 837
 
4.3%
6 401
 
2.1%
7 367
 
1.9%
5 353
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7128
37.0%
- 2628
 
13.6%
1 2265
 
11.8%
3 2081
 
10.8%
2 1598
 
8.3%
8 1294
 
6.7%
9 837
 
4.3%
6 401
 
2.1%
7 367
 
1.9%
5 353
 
1.8%

인허가일자
Date

Distinct733
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum1963-03-11 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T05:43:12.346591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:43:12.935082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
3
743 
1
133 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 743
84.8%
1 133
 
15.2%

Length

2024-05-11T05:43:13.511746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:13.845155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 743
84.8%
1 133
 
15.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
폐업
743 
영업/정상
133 

Length

Max length5
Median length2
Mean length2.4554795
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 743
84.8%
영업/정상 133
 
15.2%

Length

2024-05-11T05:43:14.362701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:14.799975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 743
84.8%
영업/정상 133
 
15.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2
743 
1
133 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 743
84.8%
1 133
 
15.2%

Length

2024-05-11T05:43:15.331201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:15.772940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 743
84.8%
1 133
 
15.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
폐업
743 
영업
133 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 743
84.8%
영업 133
 
15.2%

Length

2024-05-11T05:43:16.214520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:16.568421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 743
84.8%
영업 133
 
15.2%

폐업일자
Date

MISSING 

Distinct520
Distinct (%)70.0%
Missing133
Missing (%)15.2%
Memory size7.0 KiB
Minimum1993-01-29 00:00:00
Maximum2024-04-19 00:00:00
2024-05-11T05:43:17.146179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:43:17.679231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

전화번호
Text

MISSING 

Distinct503
Distinct (%)75.0%
Missing205
Missing (%)23.4%
Memory size7.0 KiB
2024-05-11T05:43:18.406023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.4232489
Min length2

Characters and Unicode

Total characters5652
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique470 ?
Unique (%)70.0%

Sample

1st row02
2nd row02 8329173
3rd row02 8456369
4th row02 8416759
5th row02 8432003
ValueCountFrequency (%)
02 480
46.2%
846 3
 
0.3%
8474423 3
 
0.3%
8325136 3
 
0.3%
7851290 2
 
0.2%
0220692851 2
 
0.2%
0226783708 2
 
0.2%
8497063 2
 
0.2%
8480598 2
 
0.2%
8339891 2
 
0.2%
Other values (509) 538
51.8%
2024-05-11T05:43:19.718622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1153
20.4%
0 900
15.9%
8 577
10.2%
6 488
8.6%
7 466
8.2%
3 453
 
8.0%
4 420
 
7.4%
392
 
6.9%
1 303
 
5.4%
5 283
 
5.0%
Other values (2) 217
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5259
93.0%
Space Separator 392
 
6.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1153
21.9%
0 900
17.1%
8 577
11.0%
6 488
9.3%
7 466
8.9%
3 453
 
8.6%
4 420
 
8.0%
1 303
 
5.8%
5 283
 
5.4%
9 216
 
4.1%
Space Separator
ValueCountFrequency (%)
392
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1153
20.4%
0 900
15.9%
8 577
10.2%
6 488
8.6%
7 466
8.2%
3 453
 
8.0%
4 420
 
7.4%
392
 
6.9%
1 303
 
5.4%
5 283
 
5.0%
Other values (2) 217
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1153
20.4%
0 900
15.9%
8 577
10.2%
6 488
8.6%
7 466
8.2%
3 453
 
8.0%
4 420
 
7.4%
392
 
6.9%
1 303
 
5.4%
5 283
 
5.0%
Other values (2) 217
 
3.8%

소재지면적
Real number (ℝ)

ZEROS 

Distinct468
Distinct (%)53.5%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean28.378651
Minimum0
Maximum210
Zeros92
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:20.324522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.05
median19.37
Q338.18
95-th percentile82.15
Maximum210
Range210
Interquartile range (IQR)27.13

Descriptive statistics

Standard deviation27.575008
Coefficient of variation (CV)0.97168141
Kurtosis6.8264397
Mean28.378651
Median Absolute Deviation (MAD)10.63
Skewness2.1344957
Sum24831.32
Variance760.38107
MonotonicityNot monotonic
2024-05-11T05:43:20.987934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 92
 
10.5%
10.0 26
 
3.0%
12.0 20
 
2.3%
33.0 15
 
1.7%
20.0 13
 
1.5%
16.5 12
 
1.4%
60.0 11
 
1.3%
9.9 11
 
1.3%
15.0 11
 
1.3%
6.6 10
 
1.1%
Other values (458) 654
74.7%
ValueCountFrequency (%)
0.0 92
10.5%
2.5 1
 
0.1%
3.0 2
 
0.2%
3.3 1
 
0.1%
4.5 1
 
0.1%
4.9 1
 
0.1%
4.95 1
 
0.1%
5.0 2
 
0.2%
6.0 9
 
1.0%
6.6 10
 
1.1%
ValueCountFrequency (%)
210.0 2
0.2%
167.6 1
 
0.1%
159.67 1
 
0.1%
150.0 1
 
0.1%
143.0 1
 
0.1%
132.79 1
 
0.1%
120.0 4
0.5%
118.81 1
 
0.1%
118.39 1
 
0.1%
114.84 1
 
0.1%

소재지우편번호
Text

Distinct151
Distinct (%)17.3%
Missing2
Missing (%)0.2%
Memory size7.0 KiB
2024-05-11T05:43:21.819950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0331808
Min length6

Characters and Unicode

Total characters5273
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

Unique42 ?
Unique (%)4.8%

Sample

1st row150834
2nd row150840
3rd row150840
4th row150853
5th row150839
ValueCountFrequency (%)
150841 38
 
4.3%
150033 27
 
3.1%
150813 21
 
2.4%
150815 21
 
2.4%
150800 21
 
2.4%
150035 21
 
2.4%
150814 20
 
2.3%
150037 20
 
2.3%
150890 19
 
2.2%
150840 19
 
2.2%
Other values (141) 647
74.0%
2024-05-11T05:43:23.326300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1357
25.7%
1 1101
20.9%
5 1030
19.5%
8 674
12.8%
3 289
 
5.5%
4 196
 
3.7%
9 193
 
3.7%
2 143
 
2.7%
7 137
 
2.6%
6 124
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5244
99.5%
Dash Punctuation 29
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1357
25.9%
1 1101
21.0%
5 1030
19.6%
8 674
12.9%
3 289
 
5.5%
4 196
 
3.7%
9 193
 
3.7%
2 143
 
2.7%
7 137
 
2.6%
6 124
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5273
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1357
25.7%
1 1101
20.9%
5 1030
19.5%
8 674
12.8%
3 289
 
5.5%
4 196
 
3.7%
9 193
 
3.7%
2 143
 
2.7%
7 137
 
2.6%
6 124
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1357
25.7%
1 1101
20.9%
5 1030
19.5%
8 674
12.8%
3 289
 
5.5%
4 196
 
3.7%
9 193
 
3.7%
2 143
 
2.7%
7 137
 
2.6%
6 124
 
2.4%

지번주소
Text

Distinct789
Distinct (%)90.3%
Missing2
Missing (%)0.2%
Memory size7.0 KiB
2024-05-11T05:43:24.182326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length26.120137
Min length18

Characters and Unicode

Total characters22829
Distinct characters232
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

Unique715 ?
Unique (%)81.8%

Sample

1st row서울특별시 영등포구 문래동3가 16-0번지
2nd row서울특별시 영등포구 신길동 151-43번지
3rd row서울특별시 영등포구 신길동 192-2번지
4th row서울특별시 영등포구 신길동 457-4번지
5th row서울특별시 영등포구 신길동 95-201번지
ValueCountFrequency (%)
서울특별시 874
22.4%
영등포구 873
22.4%
신길동 162
 
4.2%
대림동 148
 
3.8%
여의도동 132
 
3.4%
도림동 35
 
0.9%
영등포동2가 30
 
0.8%
영등포동3가 27
 
0.7%
당산동1가 26
 
0.7%
지하 26
 
0.7%
Other values (933) 1569
40.2%
2024-05-11T05:43:25.832022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3825
 
16.8%
영 1041
 
4.6%
등 1035
 
4.5%
포 1035
 
4.5%
동 907
 
4.0%
지 891
 
3.9%
서 883
 
3.9%
시 882
 
3.9%
구 881
 
3.9%
울 875
 
3.8%
Other values (222) 10574
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14119
61.8%
Decimal Number 4051
 
17.7%
Space Separator 3825
 
16.8%
Dash Punctuation 760
 
3.3%
Uppercase Letter 32
 
0.1%
Other Punctuation 16
 
0.1%
Open Punctuation 13
 
0.1%
Close Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1041
 
7.4%
등 1035
 
7.3%
포 1035
 
7.3%
동 907
 
6.4%
지 891
 
6.3%
서 883
 
6.3%
시 882
 
6.2%
구 881
 
6.2%
울 875
 
6.2%
특 874
 
6.2%
Other values (193) 4815
34.1%
Uppercase Letter
ValueCountFrequency (%)
B 11
34.4%
M 4
 
12.5%
C 4
 
12.5%
K 2
 
6.2%
G 2
 
6.2%
L 2
 
6.2%
H 1
 
3.1%
T 1
 
3.1%
E 1
 
3.1%
S 1
 
3.1%
Other values (3) 3
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 825
20.4%
2 571
14.1%
3 494
12.2%
4 449
11.1%
5 351
8.7%
0 347
8.6%
6 317
 
7.8%
7 262
 
6.5%
9 222
 
5.5%
8 213
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 10
62.5%
. 6
37.5%
Space Separator
ValueCountFrequency (%)
3825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 760
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14119
61.8%
Common 8678
38.0%
Latin 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1041
 
7.4%
등 1035
 
7.3%
포 1035
 
7.3%
동 907
 
6.4%
지 891
 
6.3%
서 883
 
6.3%
시 882
 
6.2%
구 881
 
6.2%
울 875
 
6.2%
특 874
 
6.2%
Other values (193) 4815
34.1%
Common
ValueCountFrequency (%)
3825
44.1%
1 825
 
9.5%
- 760
 
8.8%
2 571
 
6.6%
3 494
 
5.7%
4 449
 
5.2%
5 351
 
4.0%
0 347
 
4.0%
6 317
 
3.7%
7 262
 
3.0%
Other values (6) 477
 
5.5%
Latin
ValueCountFrequency (%)
B 11
34.4%
M 4
 
12.5%
C 4
 
12.5%
K 2
 
6.2%
G 2
 
6.2%
L 2
 
6.2%
H 1
 
3.1%
T 1
 
3.1%
E 1
 
3.1%
S 1
 
3.1%
Other values (3) 3
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14119
61.8%
ASCII 8710
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3825
43.9%
1 825
 
9.5%
- 760
 
8.7%
2 571
 
6.6%
3 494
 
5.7%
4 449
 
5.2%
5 351
 
4.0%
0 347
 
4.0%
6 317
 
3.6%
7 262
 
3.0%
Other values (19) 509
 
5.8%
Hangul
ValueCountFrequency (%)
영 1041
 
7.4%
등 1035
 
7.3%
포 1035
 
7.3%
동 907
 
6.4%
지 891
 
6.3%
서 883
 
6.3%
시 882
 
6.2%
구 881
 
6.2%
울 875
 
6.2%
특 874
 
6.2%
Other values (193) 4815
34.1%

도로명주소
Text

MISSING 

Distinct283
Distinct (%)96.9%
Missing584
Missing (%)66.7%
Memory size7.0 KiB
2024-05-11T05:43:26.621123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length31.726027
Min length23

Characters and Unicode

Total characters9264
Distinct characters196
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

Unique275 ?
Unique (%)94.2%

Sample

1st row서울특별시 영등포구 도신로56길 17-1 (신길동)
2nd row서울특별시 영등포구 도림로53길 8 (대림동)
3rd row서울특별시 영등포구 여의대방로35길 3 (신길동)
4th row서울특별시 영등포구 가마산로61나길 13 (신길동)
5th row서울특별시 영등포구 도림로141다길 9 (문래동4가)
ValueCountFrequency (%)
서울특별시 292
 
17.2%
영등포구 292
 
17.2%
대림동 47
 
2.8%
신길동 47
 
2.8%
1층 42
 
2.5%
여의도동 36
 
2.1%
지하1층 15
 
0.9%
도림동 15
 
0.9%
2층 14
 
0.8%
도림로 13
 
0.8%
Other values (460) 888
52.2%
2024-05-11T05:43:28.298433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1409
 
15.2%
영 388
 
4.2%
포 366
 
4.0%
등 366
 
4.0%
1 353
 
3.8%
동 318
 
3.4%
서 299
 
3.2%
시 299
 
3.2%
) 297
 
3.2%
( 297
 
3.2%
Other values (186) 4872
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5675
61.3%
Space Separator 1409
 
15.2%
Decimal Number 1319
 
14.2%
Close Punctuation 297
 
3.2%
Open Punctuation 297
 
3.2%
Other Punctuation 188
 
2.0%
Dash Punctuation 46
 
0.5%
Uppercase Letter 33
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 388
 
6.8%
포 366
 
6.4%
등 366
 
6.4%
동 318
 
5.6%
서 299
 
5.3%
시 299
 
5.3%
구 296
 
5.2%
울 293
 
5.2%
로 293
 
5.2%
별 292
 
5.1%
Other values (157) 2465
43.4%
Uppercase Letter
ValueCountFrequency (%)
B 9
27.3%
C 4
12.1%
M 4
12.1%
L 3
 
9.1%
G 3
 
9.1%
K 2
 
6.1%
A 2
 
6.1%
T 1
 
3.0%
H 1
 
3.0%
R 1
 
3.0%
Other values (3) 3
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 353
26.8%
2 198
15.0%
3 152
11.5%
4 114
 
8.6%
5 110
 
8.3%
6 89
 
6.7%
7 88
 
6.7%
8 78
 
5.9%
0 78
 
5.9%
9 59
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 182
96.8%
. 6
 
3.2%
Space Separator
ValueCountFrequency (%)
1409
100.0%
Close Punctuation
ValueCountFrequency (%)
) 297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5675
61.3%
Common 3556
38.4%
Latin 33
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 388
 
6.8%
포 366
 
6.4%
등 366
 
6.4%
동 318
 
5.6%
서 299
 
5.3%
시 299
 
5.3%
구 296
 
5.2%
울 293
 
5.2%
로 293
 
5.2%
별 292
 
5.1%
Other values (157) 2465
43.4%
Common
ValueCountFrequency (%)
1409
39.6%
1 353
 
9.9%
) 297
 
8.4%
( 297
 
8.4%
2 198
 
5.6%
, 182
 
5.1%
3 152
 
4.3%
4 114
 
3.2%
5 110
 
3.1%
6 89
 
2.5%
Other values (6) 355
 
10.0%
Latin
ValueCountFrequency (%)
B 9
27.3%
C 4
12.1%
M 4
12.1%
L 3
 
9.1%
G 3
 
9.1%
K 2
 
6.1%
A 2
 
6.1%
T 1
 
3.0%
H 1
 
3.0%
R 1
 
3.0%
Other values (3) 3
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5675
61.3%
ASCII 3589
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1409
39.3%
1 353
 
9.8%
) 297
 
8.3%
( 297
 
8.3%
2 198
 
5.5%
, 182
 
5.1%
3 152
 
4.2%
4 114
 
3.2%
5 110
 
3.1%
6 89
 
2.5%
Other values (19) 388
 
10.8%
Hangul
ValueCountFrequency (%)
영 388
 
6.8%
포 366
 
6.4%
등 366
 
6.4%
동 318
 
5.6%
서 299
 
5.3%
시 299
 
5.3%
구 296
 
5.2%
울 293
 
5.2%
로 293
 
5.2%
별 292
 
5.1%
Other values (157) 2465
43.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)48.0%
Missing595
Missing (%)67.9%
Infinite0
Infinite (%)0.0%
Mean7323.8114
Minimum7201
Maximum7448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:29.110803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7201
5-th percentile7222
Q17259
median7331
Q37380
95-th percentile7432
Maximum7448
Range247
Interquartile range (IQR)121

Descriptive statistics

Standard deviation69.907567
Coefficient of variation (CV)0.009545244
Kurtosis-1.2729935
Mean7323.8114
Median Absolute Deviation (MAD)67
Skewness0.057169652
Sum2057991
Variance4887.0679
MonotonicityNot monotonic
2024-05-11T05:43:30.195868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7250 12
 
1.4%
7237 8
 
0.9%
7333 7
 
0.8%
7374 6
 
0.7%
7345 6
 
0.7%
7362 6
 
0.7%
7238 6
 
0.7%
7266 6
 
0.7%
7213 5
 
0.6%
7259 5
 
0.6%
Other values (125) 214
 
24.4%
(Missing) 595
67.9%
ValueCountFrequency (%)
7201 1
 
0.1%
7204 1
 
0.1%
7206 2
 
0.2%
7211 2
 
0.2%
7212 1
 
0.1%
7213 5
0.6%
7220 2
 
0.2%
7222 1
 
0.1%
7223 2
 
0.2%
7225 1
 
0.1%
ValueCountFrequency (%)
7448 1
 
0.1%
7446 1
 
0.1%
7445 1
 
0.1%
7443 1
 
0.1%
7442 1
 
0.1%
7440 4
0.5%
7439 1
 
0.1%
7438 2
0.2%
7437 1
 
0.1%
7434 1
 
0.1%

사업장명
Text

Distinct670
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T05:43:30.982136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length4.1175799
Min length1

Characters and Unicode

Total characters3607
Distinct characters350
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

Unique550 ?
Unique (%)62.8%

Sample

1st row충남
2nd row형제
3rd row신일
4th row미광
5th row동원
ValueCountFrequency (%)
이용원 27
 
2.7%
내 12
 
1.2%
현대 11
 
1.1%
바버샵 8
 
0.8%
현대이용원 7
 
0.7%
대성 7
 
0.7%
이발실 6
 
0.6%
은하 6
 
0.6%
평화 6
 
0.6%
이발 6
 
0.6%
Other values (683) 887
90.2%
2024-05-11T05:43:32.640197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 295
 
8.2%
용 208
 
5.8%
원 204
 
5.7%
107
 
3.0%
우 103
 
2.9%
대 81
 
2.2%
사 81
 
2.2%
성 80
 
2.2%
나 79
 
2.2%
발 74
 
2.1%
Other values (340) 2295
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3353
93.0%
Space Separator 107
 
3.0%
Uppercase Letter 65
 
1.8%
Lowercase Letter 28
 
0.8%
Close Punctuation 18
 
0.5%
Open Punctuation 18
 
0.5%
Decimal Number 14
 
0.4%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 295
 
8.8%
용 208
 
6.2%
원 204
 
6.1%
우 103
 
3.1%
대 81
 
2.4%
사 81
 
2.4%
성 80
 
2.4%
나 79
 
2.4%
발 74
 
2.2%
내 62
 
1.8%
Other values (294) 2086
62.2%
Uppercase Letter
ValueCountFrequency (%)
B 8
12.3%
E 7
10.8%
S 7
10.8%
A 6
 
9.2%
C 5
 
7.7%
R 5
 
7.7%
O 3
 
4.6%
H 3
 
4.6%
T 3
 
4.6%
Q 2
 
3.1%
Other values (10) 16
24.6%
Lowercase Letter
ValueCountFrequency (%)
t 5
17.9%
c 3
10.7%
o 3
10.7%
u 3
10.7%
s 2
 
7.1%
j 2
 
7.1%
d 2
 
7.1%
h 2
 
7.1%
r 1
 
3.6%
x 1
 
3.6%
Other values (4) 4
14.3%
Decimal Number
ValueCountFrequency (%)
0 3
21.4%
2 3
21.4%
6 2
14.3%
4 2
14.3%
7 2
14.3%
1 1
 
7.1%
3 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
? 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3353
93.0%
Common 161
 
4.5%
Latin 93
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 295
 
8.8%
용 208
 
6.2%
원 204
 
6.1%
우 103
 
3.1%
대 81
 
2.4%
사 81
 
2.4%
성 80
 
2.4%
나 79
 
2.4%
발 74
 
2.2%
내 62
 
1.8%
Other values (294) 2086
62.2%
Latin
ValueCountFrequency (%)
B 8
 
8.6%
E 7
 
7.5%
S 7
 
7.5%
A 6
 
6.5%
C 5
 
5.4%
t 5
 
5.4%
R 5
 
5.4%
c 3
 
3.2%
o 3
 
3.2%
O 3
 
3.2%
Other values (24) 41
44.1%
Common
ValueCountFrequency (%)
107
66.5%
) 18
 
11.2%
( 18
 
11.2%
0 3
 
1.9%
? 3
 
1.9%
2 3
 
1.9%
6 2
 
1.2%
4 2
 
1.2%
7 2
 
1.2%
1 1
 
0.6%
Other values (2) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3353
93.0%
ASCII 254
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 295
 
8.8%
용 208
 
6.2%
원 204
 
6.1%
우 103
 
3.1%
대 81
 
2.4%
사 81
 
2.4%
성 80
 
2.4%
나 79
 
2.4%
발 74
 
2.2%
내 62
 
1.8%
Other values (294) 2086
62.2%
ASCII
ValueCountFrequency (%)
107
42.1%
) 18
 
7.1%
( 18
 
7.1%
B 8
 
3.1%
E 7
 
2.8%
S 7
 
2.8%
A 6
 
2.4%
C 5
 
2.0%
t 5
 
2.0%
R 5
 
2.0%
Other values (36) 68
26.8%

최종수정일자
Date

Distinct475
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum1999-01-29 00:00:00
Maximum2024-04-26 15:14:22
2024-05-11T05:43:33.203339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:43:33.821987image/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 size7.0 KiB
I
786 
U
90 

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 786
89.7%
U 90
 
10.3%

Length

2024-05-11T05:43:34.312648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:34.697397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 786
89.7%
u 90
 
10.3%

데이터갱신일자
Date

Distinct103
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:08:00
2024-05-11T05:43:35.114681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:43:35.763184image/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 size7.0 KiB
일반이용업
868 
이용업 기타
 
8

Length

Max length6
Median length5
Mean length5.0091324
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 868
99.1%
이용업 기타 8
 
0.9%

Length

2024-05-11T05:43:36.218941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:36.620467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 868
98.2%
이용업 8
 
0.9%
기타 8
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct595
Distinct (%)72.8%
Missing59
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean191708.29
Minimum189602.34
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:37.010743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189602.34
5-th percentile190174.42
Q1190969.75
median191559.74
Q3192375.73
95-th percentile193727.15
Maximum194632.53
Range5030.1892
Interquartile range (IQR)1405.9799

Descriptive statistics

Standard deviation1052.4362
Coefficient of variation (CV)0.0054897793
Kurtosis-0.24888914
Mean191708.29
Median Absolute Deviation (MAD)647.68845
Skewness0.54651202
Sum1.5662567 × 108
Variance1107621.9
MonotonicityNot monotonic
2024-05-11T05:43:37.563797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190969.754112801 8
 
0.9%
193844.169062846 6
 
0.7%
191800.728214995 6
 
0.7%
192785.997964211 6
 
0.7%
191039.739317388 5
 
0.6%
190394.571819262 5
 
0.6%
191979.46040147 5
 
0.6%
190292.658514827 5
 
0.6%
190517.88054611 5
 
0.6%
189900.439154034 5
 
0.6%
Other values (585) 761
86.9%
(Missing) 59
 
6.7%
ValueCountFrequency (%)
189602.337205545 1
 
0.1%
189679.286130733 2
 
0.2%
189682.022243843 2
 
0.2%
189727.962773728 1
 
0.1%
189732.390590096 1
 
0.1%
189745.178404513 2
 
0.2%
189773.106823997 1
 
0.1%
189828.295895973 1
 
0.1%
189877.032334127 3
0.3%
189900.439154034 5
0.6%
ValueCountFrequency (%)
194632.526367463 4
0.5%
194504.656267957 4
0.5%
194370.32715363 3
0.3%
194324.398950764 1
 
0.1%
194015.180457719 1
 
0.1%
193989.272586157 1
 
0.1%
193915.13139016 2
 
0.2%
193870.812916718 1
 
0.1%
193847.088620039 1
 
0.1%
193844.169062846 6
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct595
Distinct (%)72.8%
Missing59
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean445861.55
Minimum442782.83
Maximum449096.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:38.126999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442782.83
5-th percentile443334.29
Q1444796.37
median446252.59
Q3446801.98
95-th percentile448064.2
Maximum449096.51
Range6313.6763
Interquartile range (IQR)2005.6121

Descriptive statistics

Standard deviation1430.919
Coefficient of variation (CV)0.0032093349
Kurtosis-0.77306762
Mean445861.55
Median Absolute Deviation (MAD)928.1218
Skewness-0.30176043
Sum3.6426889 × 108
Variance2047529.3
MonotonicityNot monotonic
2024-05-11T05:43:38.757412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443505.951042562 8
 
0.9%
446511.783285705 6
 
0.7%
443809.773854649 6
 
0.7%
447523.1165117 6
 
0.7%
443638.704942648 5
 
0.6%
448656.726986041 5
 
0.6%
446740.301257223 5
 
0.6%
448525.658592957 5
 
0.6%
447739.172359225 5
 
0.6%
446663.521261847 5
 
0.6%
Other values (585) 761
86.9%
(Missing) 59
 
6.7%
ValueCountFrequency (%)
442782.832508026 1
0.1%
442861.809050257 1
0.1%
442867.24381127 1
0.1%
442869.887891747 1
0.1%
442877.855856471 1
0.1%
442905.116903156 1
0.1%
442919.355163851 1
0.1%
442957.706072228 1
0.1%
442963.261559408 1
0.1%
442972.238395 1
0.1%
ValueCountFrequency (%)
449096.508811899 1
 
0.1%
448953.434292828 1
 
0.1%
448808.445544904 1
 
0.1%
448656.726986041 5
0.6%
448525.658592957 5
0.6%
448434.679777957 1
 
0.1%
448409.083430107 1
 
0.1%
448368.494370526 1
 
0.1%
448352.38169269 3
0.3%
448345.756184783 1
 
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
일반이용업
816 
<NA>
 
52
이용업 기타
 
8

Length

Max length6
Median length5
Mean length4.9497717
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 816
93.2%
<NA> 52
 
5.9%
이용업 기타 8
 
0.9%

Length

2024-05-11T05:43:39.375322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:39.996596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 816
92.3%
na 52
 
5.9%
이용업 8
 
0.9%
기타 8
 
0.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)1.6%
Missing52
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean0.33373786
Minimum0
Maximum63
Zeros768
Zeros (%)87.7%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:40.709746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum63
Range63
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5086054
Coefficient of variation (CV)7.5166939
Kurtosis476.72768
Mean0.33373786
Median Absolute Deviation (MAD)0
Skewness19.74671
Sum275
Variance6.293101
MonotonicityNot monotonic
2024-05-11T05:43:41.490451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 768
87.7%
1 12
 
1.4%
4 11
 
1.3%
3 10
 
1.1%
2 8
 
0.9%
5 5
 
0.6%
12 2
 
0.2%
9 2
 
0.2%
6 2
 
0.2%
10 1
 
0.1%
Other values (3) 3
 
0.3%
(Missing) 52
 
5.9%
ValueCountFrequency (%)
0 768
87.7%
1 12
 
1.4%
2 8
 
0.9%
3 10
 
1.1%
4 11
 
1.3%
5 5
 
0.6%
6 2
 
0.2%
7 1
 
0.1%
9 2
 
0.2%
10 1
 
0.1%
ValueCountFrequency (%)
63 1
 
0.1%
14 1
 
0.1%
12 2
 
0.2%
10 1
 
0.1%
9 2
 
0.2%
7 1
 
0.1%
6 2
 
0.2%
5 5
0.6%
4 11
1.3%
3 10
1.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing52
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean0.074029126
Minimum0
Maximum5
Zeros780
Zeros (%)89.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:42.095298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.36969697
Coefficient of variation (CV)4.9939394
Kurtosis67.787143
Mean0.074029126
Median Absolute Deviation (MAD)0
Skewness7.2240708
Sum61
Variance0.13667585
MonotonicityNot monotonic
2024-05-11T05:43:42.481125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 780
89.0%
1 34
 
3.9%
2 6
 
0.7%
3 2
 
0.2%
5 1
 
0.1%
4 1
 
0.1%
(Missing) 52
 
5.9%
ValueCountFrequency (%)
0 780
89.0%
1 34
 
3.9%
2 6
 
0.7%
3 2
 
0.2%
4 1
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 1
 
0.1%
3 2
 
0.2%
2 6
 
0.7%
1 34
 
3.9%
0 780
89.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.8%
Missing52
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean0.14320388
Minimum0
Maximum7
Zeros758
Zeros (%)86.5%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:42.928032image/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 deviation0.62657039
Coefficient of variation (CV)4.3753729
Kurtosis57.753961
Mean0.14320388
Median Absolute Deviation (MAD)0
Skewness6.7776166
Sum118
Variance0.39259045
MonotonicityNot monotonic
2024-05-11T05:43:43.593738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 758
86.5%
1 39
 
4.5%
2 18
 
2.1%
3 3
 
0.3%
7 2
 
0.2%
6 2
 
0.2%
4 2
 
0.2%
(Missing) 52
 
5.9%
ValueCountFrequency (%)
0 758
86.5%
1 39
 
4.5%
2 18
 
2.1%
3 3
 
0.3%
4 2
 
0.2%
6 2
 
0.2%
7 2
 
0.2%
ValueCountFrequency (%)
7 2
 
0.2%
6 2
 
0.2%
4 2
 
0.2%
3 3
 
0.3%
2 18
 
2.1%
1 39
 
4.5%
0 758
86.5%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.8%
Missing52
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean0.22451456
Minimum0
Maximum102
Zeros778
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:44.233090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum102
Range102
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5931393
Coefficient of variation (CV)16.004037
Kurtosis784.88695
Mean0.22451456
Median Absolute Deviation (MAD)0
Skewness27.709236
Sum185
Variance12.91065
MonotonicityNot monotonic
2024-05-11T05:43:44.720959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 778
88.8%
1 27
 
3.1%
2 12
 
1.4%
7 2
 
0.2%
6 2
 
0.2%
3 2
 
0.2%
102 1
 
0.1%
(Missing) 52
 
5.9%
ValueCountFrequency (%)
0 778
88.8%
1 27
 
3.1%
2 12
 
1.4%
3 2
 
0.2%
6 2
 
0.2%
7 2
 
0.2%
102 1
 
0.1%
ValueCountFrequency (%)
102 1
 
0.1%
7 2
 
0.2%
6 2
 
0.2%
3 2
 
0.2%
2 12
 
1.4%
1 27
 
3.1%
0 778
88.8%

사용시작지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
761 
1
 
57
<NA>
 
52
2
 
6

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 761
86.9%
1 57
 
6.5%
<NA> 52
 
5.9%
2 6
 
0.7%

Length

2024-05-11T05:43:45.211092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:45.728024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 761
86.9%
1 57
 
6.5%
na 52
 
5.9%
2 6
 
0.7%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
783 
<NA>
 
52
1
 
37
2
 
4

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 783
89.4%
<NA> 52
 
5.9%
1 37
 
4.2%
2 4
 
0.5%

Length

2024-05-11T05:43:46.167000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:46.651914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 783
89.4%
na 52
 
5.9%
1 37
 
4.2%
2 4
 
0.5%

한실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:47.280028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:47.773800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

양실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:48.152181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:48.476732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

욕실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:48.907846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:49.395393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing68
Missing (%)7.8%
Memory size1.8 KiB
False
808 
(Missing)
 
68
ValueCountFrequency (%)
False 808
92.2%
(Missing) 68
 
7.8%
2024-05-11T05:43:49.797825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)1.7%
Missing52
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean3.690534
Minimum0
Maximum15
Zeros92
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T05:43:50.108603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile9
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6150527
Coefficient of variation (CV)0.70858384
Kurtosis0.34148587
Mean3.690534
Median Absolute Deviation (MAD)1
Skewness0.84896533
Sum3041
Variance6.8385008
MonotonicityNot monotonic
2024-05-11T05:43:50.598018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 196
22.4%
3 191
21.8%
0 92
10.5%
4 89
10.2%
7 57
 
6.5%
5 52
 
5.9%
6 41
 
4.7%
8 34
 
3.9%
9 27
 
3.1%
10 20
 
2.3%
Other values (4) 25
 
2.9%
(Missing) 52
 
5.9%
ValueCountFrequency (%)
0 92
10.5%
1 18
 
2.1%
2 196
22.4%
3 191
21.8%
4 89
10.2%
5 52
 
5.9%
6 41
 
4.7%
7 57
 
6.5%
8 34
 
3.9%
9 27
 
3.1%
ValueCountFrequency (%)
15 1
 
0.1%
12 1
 
0.1%
11 5
 
0.6%
10 20
 
2.3%
9 27
 
3.1%
8 34
 
3.9%
7 57
6.5%
6 41
4.7%
5 52
5.9%
4 89
10.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing876
Missing (%)100.0%
Memory size7.8 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
793 
임대
82 
자가
 
1

Length

Max length4
Median length4
Mean length3.8105023
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 793
90.5%
임대 82
 
9.4%
자가 1
 
0.1%

Length

2024-05-11T05:43:51.036014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:51.402288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 793
90.5%
임대 82
 
9.4%
자가 1
 
0.1%

세탁기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:51.921992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:52.254022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
821 
<NA>
 
52
1
 
3

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 821
93.7%
<NA> 52
 
5.9%
1 3
 
0.3%

Length

2024-05-11T05:43:52.872554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:53.215862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 821
93.7%
na 52
 
5.9%
1 3
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
813 
<NA>
 
52
1
 
11

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 813
92.8%
<NA> 52
 
5.9%
1 11
 
1.3%

Length

2024-05-11T05:43:53.610419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:53.959677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 813
92.8%
na 52
 
5.9%
1 11
 
1.3%

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:54.328050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:54.685449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
824 
<NA>
 
52

Length

Max length4
Median length1
Mean length1.1780822
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 824
94.1%
<NA> 52
 
5.9%

Length

2024-05-11T05:43:55.090550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:43:55.539391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 824
94.1%
na 52
 
5.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing52
Missing (%)5.9%
Memory size1.8 KiB
False
824 
(Missing)
 
52
ValueCountFrequency (%)
False 824
94.1%
(Missing) 52
 
5.9%
2024-05-11T05:43:55.851190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031800003180000-203-1963-0151619630722<NA>3폐업2폐업19930129<NA><NA><NA>0219.6150834서울특별시 영등포구 문래동3가 16-0번지<NA><NA>충남2003-07-01 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N0<NA><NA><NA><NA>00000N
131800003180000-203-1963-0168019630311<NA>1영업/정상1영업<NA><NA><NA><NA>02 832917319.8150840서울특별시 영등포구 신길동 151-43번지서울특별시 영등포구 도신로56길 17-1 (신길동)7349형제2018-02-20 15:41:56I2018-08-31 23:59:59.0일반이용업192516.067143445344.80592일반이용업000000000N1<NA><NA><NA>임대00000N
231800003180000-203-1963-0168419630611<NA>3폐업2폐업19971029<NA><NA><NA>02 845636931.68150840서울특별시 영등포구 신길동 192-2번지<NA><NA>신일2001-08-02 00:00:00I2018-08-31 23:59:59.0일반이용업192235.432282445492.32917일반이용업000000000N7<NA><NA><NA><NA>00000N
331800003180000-203-1966-0171719660404<NA>3폐업2폐업20030225<NA><NA><NA>02 841675921.73150853서울특별시 영등포구 신길동 457-4번지<NA><NA>미광2003-06-11 00:00:00I2018-08-31 23:59:59.0일반이용업193004.111136445136.627718일반이용업000000000N4<NA><NA><NA><NA>00000N
431800003180000-203-1967-0171819671115<NA>3폐업2폐업20030225<NA><NA><NA>02 843200321.45150839서울특별시 영등포구 신길동 95-201번지<NA><NA>동원2003-06-11 00:00:00I2018-08-31 23:59:59.0일반이용업192896.71822445577.964173일반이용업000000000N4<NA><NA><NA><NA>00000N
531800003180000-203-1968-0165819681025<NA>3폐업2폐업20030225<NA><NA><NA>0210.92150840서울특별시 영등포구 신길동 144-0번지<NA><NA>협성2003-03-13 00:00:00I2018-08-31 23:59:59.0일반이용업192579.210617445073.817262일반이용업000000000N2<NA><NA><NA><NA>00000N
631800003180000-203-1968-0167619680824<NA>3폐업2폐업20110801<NA><NA><NA>02 848830717.34150842서울특별시 영등포구 신길동 2018-0번지<NA><NA>신천지2009-06-01 14:13:25I2018-08-31 23:59:59.0일반이용업192276.153039444381.219999일반이용업000000000N3<NA><NA><NA><NA>00000N
731800003180000-203-1968-0176819681021<NA>3폐업2폐업19941110<NA><NA><NA>02 845129113.6150898서울특별시 영등포구 영등포동 577-4번지<NA><NA>대성2001-08-02 00:00:00I2018-08-31 23:59:59.0일반이용업192254.639418445925.545948일반이용업000000000N2<NA><NA><NA><NA>00000N
831800003180000-203-1968-0176919681021<NA>3폐업2폐업20030225<NA><NA><NA>02 845129113.6150898서울특별시 영등포구 영등포동 577-4번지<NA><NA>대성2003-06-11 00:00:00I2018-08-31 23:59:59.0일반이용업192254.639418445925.545948일반이용업000000000N2<NA><NA><NA><NA>00000N
931800003180000-203-1968-0177119680921<NA>3폐업2폐업20030207<NA><NA><NA>0218.79150030서울특별시 영등포구 영등포동 산 1-0번지<NA><NA>미진1999-04-29 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000000000N3<NA><NA><NA><NA>00000N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
86631800003180000-203-2023-000072023-09-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.0150-042서울특별시 영등포구 당산동2가 47-4서울특별시 영등포구 양산로 96, A41호 (당산동2가)7264밸티드바버샵(VALTED BARBERSHOP)2024-04-18 15:37:11U2023-12-03 22:00:00.0일반이용업190522.614008446846.651846<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86731800003180000-203-2023-000082023-09-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0150-896서울특별시 영등포구 여의도동 61-5 리버타워서울특별시 영등포구 63로 36, 지층 (여의도동, 리버타워)7345월드사우나 내 이발실2023-09-19 11:51:31I2022-12-08 22:01:00.0일반이용업194504.656268446355.021492<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86831800003180000-203-2023-000092023-11-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.83150-803서울특별시 영등포구 당산동3가 300 102호서울특별시 영등포구 당산로26길 5, 1층 2호 (당산동3가)7259페트리코 바버샵2023-11-06 14:48:46I2022-11-01 00:08:00.0일반이용업190822.799143446928.848983<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86931800003180000-203-2023-000102023-11-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.8150-906서울특별시 영등포구 대림동 1018-23서울특별시 영등포구 대림로 100, 1층 (대림동)7438공원이용원2023-11-21 10:38:18I2022-10-31 22:03:00.0일반이용업191405.996311443167.880244<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87031800003180000-203-2023-000112023-12-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.14150-092서울특별시 영등포구 문래동2가 35 남성맨션아파트 상가동 4-2호서울특별시 영등포구 경인로77길 21, 상가동 1층 4-2호 (문래동2가, 남성맨션아파트)7289미소 남성컷 헤어2023-12-26 11:33:44I2022-11-01 22:08:00.0일반이용업190346.55231445601.663339<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87131800003180000-203-2024-000012024-01-08<NA>3폐업2폐업2024-04-19<NA><NA><NA><NA>13.2150-857서울특별시 영등포구 신길동 4936서울특별시 영등포구 가마산로79길 46, 1층 (신길동)7350푸른숲 헬스 사우나내(이발)2024-04-19 15:02:52U2023-12-03 22:01:00.0일반이용업192702.306288445115.514647<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87231800003180000-203-2024-000022024-01-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.05150-040서울특별시 영등포구 당산동 121-130 리버뷰 B101호서울특별시 영등포구 버드나루로 97, 리버뷰 지1층 B101호 (당산동)7229멘헤즈 당산점2024-01-29 13:10:19I2023-11-30 21:01:00.0일반이용업191827.828153447186.296743<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87331800003180000-203-2024-000032024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0150-841서울특별시 영등포구 신길동 214-5서울특별시 영등포구 도신로 188, 1층 (신길동)7347신길 남성컷트2024-02-27 13:18:10I2023-12-01 22:09:00.0일반이용업192168.628687445407.778168<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87431800003180000-203-2024-000042024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.0150-800서울특별시 영등포구 당산동1가 256-93 101호서울특별시 영등포구 영등포로25길 9-1, 1층 101호 (당산동1가)7266리얼라이즈 바버샵(REALIZE BARBERSHOP)2024-03-29 13:31:03I2023-12-02 21:01:00.0일반이용업190903.435362446644.302438<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
87531800003180000-203-2024-000052024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.5150-857서울특별시 영등포구 신길동 4936서울특별시 영등포구 가마산로79길 46, 1층 (신길동)7350푸른숲헬스사우나 내 이발2024-04-26 15:14:22I2023-12-03 22:08:00.0일반이용업192702.306288445115.514647<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>