Overview

Dataset statistics

Number of variables47
Number of observations396
Missing cells3951
Missing cells (%)21.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory156.8 KiB
Average record size in memory405.3 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-17939/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (95.4%)Imbalance
위생업태명 is highly imbalanced (75.1%)Imbalance
사용끝지상층 is highly imbalanced (61.2%)Imbalance
사용시작지하층 is highly imbalanced (50.4%)Imbalance
사용끝지하층 is highly imbalanced (78.1%)Imbalance
건물소유구분명 is highly imbalanced (54.9%)Imbalance
여성종사자수 is highly imbalanced (75.2%)Imbalance
남성종사자수 is highly imbalanced (62.2%)Imbalance
인허가취소일자 has 396 (100.0%) missing valuesMissing
폐업일자 has 64 (16.2%) missing valuesMissing
휴업시작일자 has 396 (100.0%) missing valuesMissing
휴업종료일자 has 396 (100.0%) missing valuesMissing
재개업일자 has 396 (100.0%) missing valuesMissing
전화번호 has 95 (24.0%) missing valuesMissing
도로명주소 has 255 (64.4%) missing valuesMissing
도로명우편번호 has 260 (65.7%) missing valuesMissing
좌표정보(X) has 48 (12.1%) missing valuesMissing
좌표정보(Y) has 48 (12.1%) missing valuesMissing
건물지상층수 has 160 (40.4%) missing valuesMissing
건물지하층수 has 163 (41.2%) missing valuesMissing
발한실여부 has 28 (7.1%) missing valuesMissing
좌석수 has 32 (8.1%) missing valuesMissing
조건부허가신고사유 has 396 (100.0%) missing valuesMissing
조건부허가시작일자 has 396 (100.0%) missing valuesMissing
조건부허가종료일자 has 396 (100.0%) missing valuesMissing
다중이용업소여부 has 26 (6.6%) 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 15 (3.8%) zerosZeros
건물지상층수 has 195 (49.2%) zerosZeros
건물지하층수 has 191 (48.2%) zerosZeros
좌석수 has 10 (2.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:33:58.353513
Analysis finished2024-05-11 05:33:59.516545
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3120000
396 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 396
100.0%

Length

2024-05-11T14:33:59.626063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:33:59.786478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 396
100.0%

관리번호
Text

UNIQUE 

Distinct396
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:34:00.171837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8712
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

Unique396 ?
Unique (%)100.0%

Sample

1st row3120000-203-1960-00233
2nd row3120000-203-1966-00155
3rd row3120000-203-1967-00198
4th row3120000-203-1967-01420
5th row3120000-203-1969-00150
ValueCountFrequency (%)
3120000-203-1960-00233 1
 
0.3%
3120000-203-2003-00005 1
 
0.3%
3120000-203-2003-00003 1
 
0.3%
3120000-203-2003-00002 1
 
0.3%
3120000-203-2002-00014 1
 
0.3%
3120000-203-2002-00013 1
 
0.3%
3120000-203-2002-00012 1
 
0.3%
3120000-203-2002-00010 1
 
0.3%
3120000-203-2002-00009 1
 
0.3%
3120000-203-2002-00008 1
 
0.3%
Other values (386) 386
97.5%
2024-05-11T14:34:00.752727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3278
37.6%
- 1188
 
13.6%
2 1176
 
13.5%
1 982
 
11.3%
3 979
 
11.2%
9 458
 
5.3%
8 186
 
2.1%
7 145
 
1.7%
4 124
 
1.4%
6 98
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7524
86.4%
Dash Punctuation 1188
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3278
43.6%
2 1176
 
15.6%
1 982
 
13.1%
3 979
 
13.0%
9 458
 
6.1%
8 186
 
2.5%
7 145
 
1.9%
4 124
 
1.6%
6 98
 
1.3%
5 98
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8712
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3278
37.6%
- 1188
 
13.6%
2 1176
 
13.5%
1 982
 
11.3%
3 979
 
11.2%
9 458
 
5.3%
8 186
 
2.1%
7 145
 
1.7%
4 124
 
1.4%
6 98
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3278
37.6%
- 1188
 
13.6%
2 1176
 
13.5%
1 982
 
11.3%
3 979
 
11.2%
9 458
 
5.3%
8 186
 
2.1%
7 145
 
1.7%
4 124
 
1.4%
6 98
 
1.1%

인허가일자
Date

Distinct360
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1960-12-29 00:00:00
Maximum2024-03-06 00:00:00
2024-05-11T14:34:01.022894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:34:01.264839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3
332 
1
64 

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 (%)
3 332
83.8%
1 64
 
16.2%

Length

2024-05-11T14:34:01.503848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:01.658936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 332
83.8%
1 64
 
16.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
332 
영업/정상
64 

Length

Max length5
Median length2
Mean length2.4848485
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 332
83.8%
영업/정상 64
 
16.2%

Length

2024-05-11T14:34:01.842788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:02.035646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 332
83.8%
영업/정상 64
 
16.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2
332 
1
64 

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 (%)
2 332
83.8%
1 64
 
16.2%

Length

2024-05-11T14:34:02.235005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:02.399417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 332
83.8%
1 64
 
16.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
332 
영업
64 

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 332
83.8%
영업 64
 
16.2%

Length

2024-05-11T14:34:02.558133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:02.716585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 332
83.8%
영업 64
 
16.2%

폐업일자
Date

MISSING 

Distinct279
Distinct (%)84.0%
Missing64
Missing (%)16.2%
Memory size3.2 KiB
Minimum1993-03-17 00:00:00
Maximum2023-10-31 00:00:00
2024-05-11T14:34:02.913050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:34:03.150056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

전화번호
Text

MISSING 

Distinct264
Distinct (%)87.7%
Missing95
Missing (%)24.0%
Memory size3.2 KiB
2024-05-11T14:34:03.478187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8006645
Min length2

Characters and Unicode

Total characters2950
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

Unique247 ?
Unique (%)82.1%

Sample

1st row0203640156
2nd row02 3929025
3rd row02 3923762
4th row0203181849
5th row0203633693
ValueCountFrequency (%)
02 212
41.3%
0 10
 
1.9%
0200000000 9
 
1.8%
00000 4
 
0.8%
3077636 3
 
0.6%
3635743 3
 
0.6%
3934403 3
 
0.6%
3728088 3
 
0.6%
3939235 2
 
0.4%
3236362 2
 
0.4%
Other values (255) 262
51.1%
2024-05-11T14:34:04.104938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 633
21.5%
2 510
17.3%
3 499
16.9%
244
 
8.3%
7 190
 
6.4%
6 170
 
5.8%
4 153
 
5.2%
9 151
 
5.1%
5 149
 
5.1%
1 140
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2706
91.7%
Space Separator 244
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 633
23.4%
2 510
18.8%
3 499
18.4%
7 190
 
7.0%
6 170
 
6.3%
4 153
 
5.7%
9 151
 
5.6%
5 149
 
5.5%
1 140
 
5.2%
8 111
 
4.1%
Space Separator
ValueCountFrequency (%)
244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 633
21.5%
2 510
17.3%
3 499
16.9%
244
 
8.3%
7 190
 
6.4%
6 170
 
5.8%
4 153
 
5.2%
9 151
 
5.1%
5 149
 
5.1%
1 140
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2950
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 633
21.5%
2 510
17.3%
3 499
16.9%
244
 
8.3%
7 190
 
6.4%
6 170
 
5.8%
4 153
 
5.2%
9 151
 
5.1%
5 149
 
5.1%
1 140
 
4.7%

소재지면적
Real number (ℝ)

ZEROS 

Distinct259
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.268737
Minimum0
Maximum115
Zeros15
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:04.448376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.075
Q111.145
median17.175
Q326.4
95-th percentile60.3975
Maximum115
Range115
Interquartile range (IQR)15.255

Descriptive statistics

Standard deviation17.995541
Coefficient of variation (CV)0.80810784
Kurtosis6.344023
Mean22.268737
Median Absolute Deviation (MAD)6.825
Skewness2.2685344
Sum8818.42
Variance323.83951
MonotonicityNot monotonic
2024-05-11T14:34:04.696845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 16
 
4.0%
0.0 15
 
3.8%
16.5 9
 
2.3%
9.9 9
 
2.3%
15.0 8
 
2.0%
18.0 6
 
1.5%
12.0 6
 
1.5%
6.6 5
 
1.3%
13.2 5
 
1.3%
17.0 4
 
1.0%
Other values (249) 313
79.0%
ValueCountFrequency (%)
0.0 15
3.8%
4.5 1
 
0.3%
4.95 2
 
0.5%
5.0 1
 
0.3%
6.0 1
 
0.3%
6.1 1
 
0.3%
6.6 5
 
1.3%
7.0 2
 
0.5%
8.0 2
 
0.5%
8.06 1
 
0.3%
ValueCountFrequency (%)
115.0 1
 
0.3%
113.58 1
 
0.3%
106.12 1
 
0.3%
94.72 1
 
0.3%
86.0 1
 
0.3%
82.5 4
1.0%
81.48 1
 
0.3%
78.75 1
 
0.3%
76.7 1
 
0.3%
76.0 1
 
0.3%

소재지우편번호
Text

Distinct81
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:34:05.010934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.020202
Min length6

Characters and Unicode

Total characters2384
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

Unique25 ?
Unique (%)6.3%

Sample

1st row120190
2nd row120040
3rd row120818
4th row120837
5th row120819
ValueCountFrequency (%)
120857 21
 
5.3%
120805 18
 
4.5%
120827 18
 
4.5%
120810 14
 
3.5%
120830 13
 
3.3%
120841 12
 
3.0%
120833 10
 
2.5%
120837 10
 
2.5%
120834 10
 
2.5%
120100 10
 
2.5%
Other values (71) 260
65.7%
2024-05-11T14:34:05.531900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 597
25.0%
1 528
22.1%
2 484
20.3%
8 360
15.1%
5 110
 
4.6%
3 94
 
3.9%
7 73
 
3.1%
4 60
 
2.5%
6 38
 
1.6%
9 32
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2376
99.7%
Dash Punctuation 8
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 597
25.1%
1 528
22.2%
2 484
20.4%
8 360
15.2%
5 110
 
4.6%
3 94
 
4.0%
7 73
 
3.1%
4 60
 
2.5%
6 38
 
1.6%
9 32
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 597
25.0%
1 528
22.1%
2 484
20.3%
8 360
15.1%
5 110
 
4.6%
3 94
 
3.9%
7 73
 
3.1%
4 60
 
2.5%
6 38
 
1.6%
9 32
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 597
25.0%
1 528
22.1%
2 484
20.3%
8 360
15.1%
5 110
 
4.6%
3 94
 
3.9%
7 73
 
3.1%
4 60
 
2.5%
6 38
 
1.6%
9 32
 
1.3%

지번주소
Text

Distinct362
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:34:05.945119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length25.896465
Min length18

Characters and Unicode

Total characters10255
Distinct characters160
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

Unique331 ?
Unique (%)83.6%

Sample

1st row서울특별시 서대문구 북아현동 176-219번지
2nd row서울특별시 서대문구 천연동 108번지
3rd row서울특별시 서대문구 북아현동 3-563번지 (구: 북아현동 산3)
4th row서울특별시 서대문구 충정로3가 3-191번지
5th row서울특별시 서대문구 북아현동 129-1번지
ValueCountFrequency (%)
서울특별시 396
22.5%
서대문구 396
22.5%
홍제동 67
 
3.8%
북가좌동 62
 
3.5%
남가좌동 62
 
3.5%
연희동 55
 
3.1%
홍은동 38
 
2.2%
북아현동 30
 
1.7%
창천동 27
 
1.5%
1층 21
 
1.2%
Other values (442) 609
34.5%
2024-05-11T14:34:06.575333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1736
 
16.9%
서 798
 
7.8%
대 411
 
4.0%
문 400
 
3.9%
시 398
 
3.9%
울 397
 
3.9%
구 397
 
3.9%
특 396
 
3.9%
별 396
 
3.9%
동 390
 
3.8%
Other values (150) 4536
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6163
60.1%
Decimal Number 1853
 
18.1%
Space Separator 1736
 
16.9%
Dash Punctuation 378
 
3.7%
Close Punctuation 53
 
0.5%
Open Punctuation 52
 
0.5%
Other Punctuation 16
 
0.2%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 798
12.9%
대 411
 
6.7%
문 400
 
6.5%
시 398
 
6.5%
울 397
 
6.4%
구 397
 
6.4%
특 396
 
6.4%
별 396
 
6.4%
동 390
 
6.3%
지 384
 
6.2%
Other values (130) 1796
29.1%
Decimal Number
ValueCountFrequency (%)
1 389
21.0%
2 279
15.1%
3 260
14.0%
4 158
8.5%
0 153
 
8.3%
5 141
 
7.6%
9 129
 
7.0%
7 127
 
6.9%
6 120
 
6.5%
8 97
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
D 1
25.0%
M 1
25.0%
C 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 14
87.5%
: 2
 
12.5%
Space Separator
ValueCountFrequency (%)
1736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6163
60.1%
Common 4088
39.9%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 798
12.9%
대 411
 
6.7%
문 400
 
6.5%
시 398
 
6.5%
울 397
 
6.4%
구 397
 
6.4%
특 396
 
6.4%
별 396
 
6.4%
동 390
 
6.3%
지 384
 
6.2%
Other values (130) 1796
29.1%
Common
ValueCountFrequency (%)
1736
42.5%
1 389
 
9.5%
- 378
 
9.2%
2 279
 
6.8%
3 260
 
6.4%
4 158
 
3.9%
0 153
 
3.7%
5 141
 
3.4%
9 129
 
3.2%
7 127
 
3.1%
Other values (6) 338
 
8.3%
Latin
ValueCountFrequency (%)
D 1
25.0%
M 1
25.0%
C 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6163
60.1%
ASCII 4092
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1736
42.4%
1 389
 
9.5%
- 378
 
9.2%
2 279
 
6.8%
3 260
 
6.4%
4 158
 
3.9%
0 153
 
3.7%
5 141
 
3.4%
9 129
 
3.2%
7 127
 
3.1%
Other values (10) 342
 
8.4%
Hangul
ValueCountFrequency (%)
서 798
12.9%
대 411
 
6.7%
문 400
 
6.5%
시 398
 
6.5%
울 397
 
6.4%
구 397
 
6.4%
특 396
 
6.4%
별 396
 
6.4%
동 390
 
6.3%
지 384
 
6.2%
Other values (130) 1796
29.1%

도로명주소
Text

MISSING 

Distinct139
Distinct (%)98.6%
Missing255
Missing (%)64.4%
Memory size3.2 KiB
2024-05-11T14:34:07.003538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length31.70922
Min length23

Characters and Unicode

Total characters4471
Distinct characters162
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

Unique137 ?
Unique (%)97.2%

Sample

1st row서울특별시 서대문구 독립문로10길 11 (천연동)
2nd row서울특별시 서대문구 경기대로7길 3 (충정로3가)
3rd row서울특별시 서대문구 통일로27길 9, 1층 일부호 (홍제동)
4th row서울특별시 서대문구 응암로 32 (북가좌동, 한양아파트상가 1층101호)
5th row서울특별시 서대문구 홍은중앙로8길 21 (홍은동)
ValueCountFrequency (%)
서울특별시 141
 
16.7%
서대문구 141
 
16.7%
홍제동 31
 
3.7%
1층 30
 
3.6%
연희동 22
 
2.6%
홍은동 13
 
1.5%
모래내로 12
 
1.4%
남가좌동 11
 
1.3%
북가좌동 9
 
1.1%
통일로 8
 
1.0%
Other values (268) 424
50.4%
2024-05-11T14:34:07.587736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
703
 
15.7%
서 290
 
6.5%
대 165
 
3.7%
) 161
 
3.6%
( 161
 
3.6%
문 151
 
3.4%
1 147
 
3.3%
울 145
 
3.2%
시 142
 
3.2%
특 141
 
3.2%
Other values (152) 2265
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2763
61.8%
Space Separator 703
 
15.7%
Decimal Number 551
 
12.3%
Close Punctuation 161
 
3.6%
Open Punctuation 161
 
3.6%
Other Punctuation 105
 
2.3%
Dash Punctuation 22
 
0.5%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 290
 
10.5%
대 165
 
6.0%
문 151
 
5.5%
울 145
 
5.2%
시 142
 
5.1%
특 141
 
5.1%
별 141
 
5.1%
구 141
 
5.1%
동 141
 
5.1%
로 128
 
4.6%
Other values (133) 1178
42.6%
Decimal Number
ValueCountFrequency (%)
1 147
26.7%
3 78
14.2%
2 75
13.6%
4 50
 
9.1%
5 41
 
7.4%
0 37
 
6.7%
7 34
 
6.2%
8 33
 
6.0%
9 28
 
5.1%
6 28
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
M 1
20.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
703
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Other Punctuation
ValueCountFrequency (%)
, 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2763
61.8%
Common 1703
38.1%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 290
 
10.5%
대 165
 
6.0%
문 151
 
5.5%
울 145
 
5.2%
시 142
 
5.1%
특 141
 
5.1%
별 141
 
5.1%
구 141
 
5.1%
동 141
 
5.1%
로 128
 
4.6%
Other values (133) 1178
42.6%
Common
ValueCountFrequency (%)
703
41.3%
) 161
 
9.5%
( 161
 
9.5%
1 147
 
8.6%
, 105
 
6.2%
3 78
 
4.6%
2 75
 
4.4%
4 50
 
2.9%
5 41
 
2.4%
0 37
 
2.2%
Other values (5) 145
 
8.5%
Latin
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
M 1
20.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2763
61.8%
ASCII 1708
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
703
41.2%
) 161
 
9.4%
( 161
 
9.4%
1 147
 
8.6%
, 105
 
6.1%
3 78
 
4.6%
2 75
 
4.4%
4 50
 
2.9%
5 41
 
2.4%
0 37
 
2.2%
Other values (9) 150
 
8.8%
Hangul
ValueCountFrequency (%)
서 290
 
10.5%
대 165
 
6.0%
문 151
 
5.5%
울 145
 
5.2%
시 142
 
5.1%
특 141
 
5.1%
별 141
 
5.1%
구 141
 
5.1%
동 141
 
5.1%
로 128
 
4.6%
Other values (133) 1178
42.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)55.9%
Missing260
Missing (%)65.7%
Infinite0
Infinite (%)0.0%
Mean3693.4632
Minimum3601
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:07.826749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3601
5-th percentile3612
Q13643
median3696
Q33734
95-th percentile3777.25
Maximum3789
Range188
Interquartile range (IQR)91

Descriptive statistics

Standard deviation52.796452
Coefficient of variation (CV)0.014294565
Kurtosis-1.1770459
Mean3693.4632
Median Absolute Deviation (MAD)48.5
Skewness-0.052546363
Sum502311
Variance2787.4653
MonotonicityNot monotonic
2024-05-11T14:34:08.048230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3628 7
 
1.8%
3766 6
 
1.5%
3646 5
 
1.3%
3712 4
 
1.0%
3717 4
 
1.0%
3637 4
 
1.0%
3692 3
 
0.8%
3724 3
 
0.8%
3757 3
 
0.8%
3650 3
 
0.8%
Other values (66) 94
 
23.7%
(Missing) 260
65.7%
ValueCountFrequency (%)
3601 1
0.3%
3604 1
0.3%
3605 2
0.5%
3606 1
0.3%
3611 1
0.3%
3612 2
0.5%
3615 1
0.3%
3616 1
0.3%
3620 1
0.3%
3622 2
0.5%
ValueCountFrequency (%)
3789 2
 
0.5%
3787 1
 
0.3%
3785 1
 
0.3%
3781 1
 
0.3%
3779 1
 
0.3%
3778 1
 
0.3%
3777 1
 
0.3%
3769 1
 
0.3%
3766 6
1.5%
3757 3
0.8%

사업장명
Text

Distinct336
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:34:08.486146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length4.0656566
Min length2

Characters and Unicode

Total characters1610
Distinct characters264
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique290 ?
Unique (%)73.2%

Sample

1st row안창
2nd row새천연
3rd row대영
4th row동아
5th row양로원후생
ValueCountFrequency (%)
유진 4
 
0.9%
중앙 4
 
0.9%
스카이빌 4
 
0.9%
이용원 4
 
0.9%
명지 3
 
0.7%
홍은 3
 
0.7%
중앙이용원 3
 
0.7%
barbershop 3
 
0.7%
가좌 3
 
0.7%
삼화 3
 
0.7%
Other values (343) 388
91.9%
2024-05-11T14:34:09.383784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 155
 
9.6%
용 106
 
6.6%
원 91
 
5.7%
우 39
 
2.4%
성 37
 
2.3%
발 37
 
2.3%
대 35
 
2.2%
26
 
1.6%
관 26
 
1.6%
나 23
 
1.4%
Other values (254) 1035
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1493
92.7%
Uppercase Letter 54
 
3.4%
Space Separator 26
 
1.6%
Lowercase Letter 19
 
1.2%
Close Punctuation 7
 
0.4%
Open Punctuation 7
 
0.4%
Decimal Number 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 155
 
10.4%
용 106
 
7.1%
원 91
 
6.1%
우 39
 
2.6%
성 37
 
2.5%
발 37
 
2.5%
대 35
 
2.3%
관 26
 
1.7%
나 23
 
1.5%
신 23
 
1.5%
Other values (223) 921
61.7%
Uppercase Letter
ValueCountFrequency (%)
R 7
13.0%
B 7
13.0%
O 6
11.1%
E 6
11.1%
H 5
9.3%
S 4
7.4%
A 3
 
5.6%
P 3
 
5.6%
T 3
 
5.6%
D 2
 
3.7%
Other values (7) 8
14.8%
Lowercase Letter
ValueCountFrequency (%)
r 4
21.1%
b 3
15.8%
a 2
10.5%
e 2
10.5%
s 2
10.5%
p 2
10.5%
h 2
10.5%
o 2
10.5%
Decimal Number
ValueCountFrequency (%)
8 2
50.0%
2 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1493
92.7%
Latin 73
 
4.5%
Common 44
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 155
 
10.4%
용 106
 
7.1%
원 91
 
6.1%
우 39
 
2.6%
성 37
 
2.5%
발 37
 
2.5%
대 35
 
2.3%
관 26
 
1.7%
나 23
 
1.5%
신 23
 
1.5%
Other values (223) 921
61.7%
Latin
ValueCountFrequency (%)
R 7
 
9.6%
B 7
 
9.6%
O 6
 
8.2%
E 6
 
8.2%
H 5
 
6.8%
S 4
 
5.5%
r 4
 
5.5%
b 3
 
4.1%
A 3
 
4.1%
P 3
 
4.1%
Other values (15) 25
34.2%
Common
ValueCountFrequency (%)
26
59.1%
) 7
 
15.9%
( 7
 
15.9%
8 2
 
4.5%
2 1
 
2.3%
4 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1493
92.7%
ASCII 117
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 155
 
10.4%
용 106
 
7.1%
원 91
 
6.1%
우 39
 
2.6%
성 37
 
2.5%
발 37
 
2.5%
대 35
 
2.3%
관 26
 
1.7%
나 23
 
1.5%
신 23
 
1.5%
Other values (223) 921
61.7%
ASCII
ValueCountFrequency (%)
26
22.2%
R 7
 
6.0%
B 7
 
6.0%
) 7
 
6.0%
( 7
 
6.0%
O 6
 
5.1%
E 6
 
5.1%
H 5
 
4.3%
S 4
 
3.4%
r 4
 
3.4%
Other values (21) 38
32.5%

최종수정일자
Date

Distinct231
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2001-10-04 00:00:00
Maximum2024-03-06 14:14:59
2024-05-11T14:34:09.601473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:34:09.784545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
I
345 
U
51 

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 345
87.1%
U 51
 
12.9%

Length

2024-05-11T14:34:10.013781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:10.187778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 345
87.1%
u 51
 
12.9%

데이터갱신일자
Date

Distinct63
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:08:00
2024-05-11T14:34:10.388680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:34:10.645046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
일반이용업
394 
이용업 기타
 
2

Length

Max length6
Median length5
Mean length5.0050505
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 394
99.5%
이용업 기타 2
 
0.5%

Length

2024-05-11T14:34:10.896515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:11.095533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 394
99.0%
이용업 2
 
0.5%
기타 2
 
0.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct269
Distinct (%)77.3%
Missing48
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean194325.05
Minimum191552.61
Maximum197061.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:11.300127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191552.61
5-th percentile192112.29
Q1193150.98
median194438.47
Q3195306.56
95-th percentile196572.72
Maximum197061.15
Range5508.5368
Interquartile range (IQR)2155.5815

Descriptive statistics

Standard deviation1397.6129
Coefficient of variation (CV)0.0071921399
Kurtosis-1.000071
Mean194325.05
Median Absolute Deviation (MAD)1055.8204
Skewness-0.034287714
Sum67625116
Variance1953321.9
MonotonicityNot monotonic
2024-05-11T14:34:11.542205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192552.192063652 5
 
1.3%
195055.550568823 5
 
1.3%
193803.424181589 4
 
1.0%
193905.343690008 3
 
0.8%
194908.961214686 3
 
0.8%
196328.539699705 3
 
0.8%
193249.597155093 3
 
0.8%
192383.59049231 3
 
0.8%
194509.296532923 3
 
0.8%
194125.738623054 3
 
0.8%
Other values (259) 313
79.0%
(Missing) 48
 
12.1%
ValueCountFrequency (%)
191552.612967645 1
 
0.3%
191604.289576468 1
 
0.3%
191615.037104598 1
 
0.3%
191834.307158224 1
 
0.3%
191836.275479334 3
0.8%
191900.345924872 1
 
0.3%
191914.747374826 1
 
0.3%
191997.083132782 1
 
0.3%
192000.945942229 3
0.8%
192008.587379083 1
 
0.3%
ValueCountFrequency (%)
197061.149730671 1
0.3%
197040.207721042 2
0.5%
197004.364341776 1
0.3%
196846.672463643 1
0.3%
196820.124190281 2
0.5%
196805.294127207 1
0.3%
196763.23582904 1
0.3%
196734.141013732 1
0.3%
196709.605559308 1
0.3%
196692.35093317 2
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct269
Distinct (%)77.3%
Missing48
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean452633.35
Minimum450422.37
Maximum455484.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:11.757863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450422.37
5-th percentile450560.74
Q1451515.82
median452724.93
Q3453613.31
95-th percentile454698.28
Maximum455484.48
Range5062.1047
Interquartile range (IQR)2097.4922

Descriptive statistics

Standard deviation1354.8116
Coefficient of variation (CV)0.0029931768
Kurtosis-1.0215137
Mean452633.35
Median Absolute Deviation (MAD)1064.0163
Skewness0.024396318
Sum1.575164 × 108
Variance1835514.5
MonotonicityNot monotonic
2024-05-11T14:34:12.024615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453030.926927651 5
 
1.3%
454355.62123459 5
 
1.3%
452723.457356207 4
 
1.0%
451537.647684662 3
 
0.8%
450597.757522205 3
 
0.8%
451322.091559666 3
 
0.8%
453284.448434146 3
 
0.8%
453612.04746201 3
 
0.8%
453448.051702994 3
 
0.8%
450504.59151374 3
 
0.8%
Other values (259) 313
79.0%
(Missing) 48
 
12.1%
ValueCountFrequency (%)
450422.374151297 2
0.5%
450425.216941786 2
0.5%
450431.225117309 2
0.5%
450450.019449555 2
0.5%
450450.682916715 2
0.5%
450453.169968033 1
 
0.3%
450491.55070752 1
 
0.3%
450504.59151374 3
0.8%
450539.519341814 1
 
0.3%
450552.13574851 1
 
0.3%
ValueCountFrequency (%)
455484.478875325 1
0.3%
455378.246569486 2
0.5%
455311.85683048 1
0.3%
455203.422749202 2
0.5%
455201.994071747 1
0.3%
455177.640801886 1
0.3%
455174.760256232 1
0.3%
455138.458761169 1
0.3%
455118.74563207 1
0.3%
455100.863150966 1
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
일반이용업
368 
<NA>
 
26
이용업 기타
 
2

Length

Max length6
Median length5
Mean length4.9393939
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 368
92.9%
<NA> 26
 
6.6%
이용업 기타 2
 
0.5%

Length

2024-05-11T14:34:12.321628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:12.591540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 368
92.5%
na 26
 
6.5%
이용업 2
 
0.5%
기타 2
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.1%
Missing160
Missing (%)40.4%
Infinite0
Infinite (%)0.0%
Mean0.8220339
Minimum0
Maximum19
Zeros195
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:12.743890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4395024
Coefficient of variation (CV)2.9676421
Kurtosis25.371983
Mean0.8220339
Median Absolute Deviation (MAD)0
Skewness4.5950192
Sum194
Variance5.951172
MonotonicityNot monotonic
2024-05-11T14:34:12.891906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 195
49.2%
3 17
 
4.3%
4 8
 
2.0%
2 4
 
1.0%
5 3
 
0.8%
7 2
 
0.5%
1 2
 
0.5%
19 1
 
0.3%
16 1
 
0.3%
15 1
 
0.3%
Other values (2) 2
 
0.5%
(Missing) 160
40.4%
ValueCountFrequency (%)
0 195
49.2%
1 2
 
0.5%
2 4
 
1.0%
3 17
 
4.3%
4 8
 
2.0%
5 3
 
0.8%
7 2
 
0.5%
10 1
 
0.3%
12 1
 
0.3%
15 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
16 1
 
0.3%
15 1
 
0.3%
12 1
 
0.3%
10 1
 
0.3%
7 2
 
0.5%
5 3
 
0.8%
4 8
2.0%
3 17
4.3%
2 4
 
1.0%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.4%
Missing163
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean0.7167382
Minimum0
Maximum101
Zeros191
Zeros (%)48.2%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:13.062201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum101
Range101
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.6518421
Coefficient of variation (CV)9.2807138
Kurtosis225.46921
Mean0.7167382
Median Absolute Deviation (MAD)0
Skewness14.9042
Sum167
Variance44.247003
MonotonicityNot monotonic
2024-05-11T14:34:13.226791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 191
48.2%
1 31
 
7.8%
2 4
 
1.0%
3 3
 
0.8%
5 1
 
0.3%
7 1
 
0.3%
101 1
 
0.3%
6 1
 
0.3%
(Missing) 163
41.2%
ValueCountFrequency (%)
0 191
48.2%
1 31
 
7.8%
2 4
 
1.0%
3 3
 
0.8%
5 1
 
0.3%
6 1
 
0.3%
7 1
 
0.3%
101 1
 
0.3%
ValueCountFrequency (%)
101 1
 
0.3%
7 1
 
0.3%
6 1
 
0.3%
5 1
 
0.3%
3 3
 
0.8%
2 4
 
1.0%
1 31
 
7.8%
0 191
48.2%

사용시작지상층
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
187 
0
146 
1
36 
2
 
15
3
 
11

Length

Max length4
Median length1
Mean length2.4166667
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 187
47.2%
0 146
36.9%
1 36
 
9.1%
2 15
 
3.8%
3 11
 
2.8%
6 1
 
0.3%

Length

2024-05-11T14:34:13.405961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:13.573917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 187
47.2%
0 146
36.9%
1 36
 
9.1%
2 15
 
3.8%
3 11
 
2.8%
6 1
 
0.3%

사용끝지상층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
327 
1
 
31
2
 
15
0
 
12
3
 
10

Length

Max length4
Median length4
Mean length3.4772727
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
82.6%
1 31
 
7.8%
2 15
 
3.8%
0 12
 
3.0%
3 10
 
2.5%
6 1
 
0.3%

Length

2024-05-11T14:34:13.792994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:13.965558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
82.6%
1 31
 
7.8%
2 15
 
3.8%
0 12
 
3.0%
3 10
 
2.5%
6 1
 
0.3%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
224 
0
151 
1
 
16
4
 
2
2
 
2

Length

Max length4
Median length4
Mean length2.6969697
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 224
56.6%
0 151
38.1%
1 16
 
4.0%
4 2
 
0.5%
2 2
 
0.5%
5 1
 
0.3%

Length

2024-05-11T14:34:14.155884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:14.346276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
56.6%
0 151
38.1%
1 16
 
4.0%
4 2
 
0.5%
2 2
 
0.5%
5 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
362 
1
 
15
0
 
14
4
 
2
2
 
2

Length

Max length4
Median length4
Mean length3.7424242
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 362
91.4%
1 15
 
3.8%
0 14
 
3.5%
4 2
 
0.5%
2 2
 
0.5%
5 1
 
0.3%

Length

2024-05-11T14:34:14.597083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:14.807425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 362
91.4%
1 15
 
3.8%
0 14
 
3.5%
4 2
 
0.5%
2 2
 
0.5%
5 1
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
207 
<NA>
189 

Length

Max length4
Median length1
Mean length2.4318182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 207
52.3%
<NA> 189
47.7%

Length

2024-05-11T14:34:14.976045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:15.157920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 207
52.3%
na 189
47.7%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
207 
<NA>
189 

Length

Max length4
Median length1
Mean length2.4318182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 207
52.3%
<NA> 189
47.7%

Length

2024-05-11T14:34:15.344599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:15.551117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 207
52.3%
na 189
47.7%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
207 
<NA>
189 

Length

Max length4
Median length1
Mean length2.4318182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 207
52.3%
<NA> 189
47.7%

Length

2024-05-11T14:34:15.754240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:15.917011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 207
52.3%
na 189
47.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing28
Missing (%)7.1%
Memory size924.0 B
False
368 
(Missing)
 
28
ValueCountFrequency (%)
False 368
92.9%
(Missing) 28
 
7.1%
2024-05-11T14:34:16.055173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)3.0%
Missing32
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean3.3269231
Minimum0
Maximum10
Zeros10
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T14:34:16.228738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile7
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8837394
Coefficient of variation (CV)0.5662107
Kurtosis1.5834782
Mean3.3269231
Median Absolute Deviation (MAD)1
Skewness1.280904
Sum1211
Variance3.5484743
MonotonicityNot monotonic
2024-05-11T14:34:16.407995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 118
29.8%
3 110
27.8%
4 47
 
11.9%
5 19
 
4.8%
6 15
 
3.8%
7 15
 
3.8%
1 12
 
3.0%
0 10
 
2.5%
9 9
 
2.3%
8 8
 
2.0%
(Missing) 32
 
8.1%
ValueCountFrequency (%)
0 10
 
2.5%
1 12
 
3.0%
2 118
29.8%
3 110
27.8%
4 47
 
11.9%
5 19
 
4.8%
6 15
 
3.8%
7 15
 
3.8%
8 8
 
2.0%
9 9
 
2.3%
ValueCountFrequency (%)
10 1
 
0.3%
9 9
 
2.3%
8 8
 
2.0%
7 15
 
3.8%
6 15
 
3.8%
5 19
 
4.8%
4 47
 
11.9%
3 110
27.8%
2 118
29.8%
1 12
 
3.0%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing396
Missing (%)100.0%
Memory size3.6 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
322 
임대
73 
자가
 
1

Length

Max length4
Median length4
Mean length3.6262626
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 322
81.3%
임대 73
 
18.4%
자가 1
 
0.3%

Length

2024-05-11T14:34:16.616132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:16.797488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 322
81.3%
임대 73
 
18.4%
자가 1
 
0.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
326 
0
70 

Length

Max length4
Median length4
Mean length3.469697
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 326
82.3%
0 70
 
17.7%

Length

2024-05-11T14:34:17.015006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:17.197930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 326
82.3%
0 70
 
17.7%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
367 
0
 
28
1
 
1

Length

Max length4
Median length4
Mean length3.780303
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
92.7%
0 28
 
7.1%
1 1
 
0.3%

Length

2024-05-11T14:34:17.370285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:17.553591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
92.7%
0 28
 
7.1%
1 1
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
367 
0
 
29

Length

Max length4
Median length4
Mean length3.780303
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
92.7%
0 29
 
7.3%

Length

2024-05-11T14:34:17.704209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:17.851722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
92.7%
0 29
 
7.3%

회수건조수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
336 
0
60 

Length

Max length4
Median length4
Mean length3.5454545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 336
84.8%
0 60
 
15.2%

Length

2024-05-11T14:34:18.027128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:18.204967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 336
84.8%
0 60
 
15.2%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
337 
0
59 

Length

Max length4
Median length4
Mean length3.5530303
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
85.1%
0 59
 
14.9%

Length

2024-05-11T14:34:18.417179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:34:18.630848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
85.1%
0 59
 
14.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing26
Missing (%)6.6%
Memory size924.0 B
False
370 
(Missing)
 
26
ValueCountFrequency (%)
False 370
93.4%
(Missing) 26
 
6.6%
2024-05-11T14:34:18.766904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031200003120000-203-1960-0023319601229<NA>3폐업2폐업20110927<NA><NA><NA>020364015618.12120190서울특별시 서대문구 북아현동 176-219번지<NA><NA>안창2003-04-09 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
131200003120000-203-1966-0015519660328<NA>1영업/정상1영업<NA><NA><NA><NA>02 392902520.5120040서울특별시 서대문구 천연동 108번지서울특별시 서대문구 독립문로10길 11 (천연동)3745새천연2014-11-28 10:19:52I2018-08-31 23:59:59.0일반이용업196517.1749451773.737869일반이용업000<NA>0<NA>000N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231200003120000-203-1967-0019819670124<NA>3폐업2폐업20090327<NA><NA><NA>02 392376215.22120818서울특별시 서대문구 북아현동 3-563번지 (구: 북아현동 산3)<NA><NA>대영2009-12-31 13:33:29I2018-08-31 23:59:59.0일반이용업196305.23002451175.821323일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331200003120000-203-1967-0142019670131<NA>3폐업2폐업20130515<NA><NA><NA>020318184914.4120837서울특별시 서대문구 충정로3가 3-191번지서울특별시 서대문구 경기대로7길 3 (충정로3가)3752동아2003-03-18 00:00:00I2018-08-31 23:59:59.0일반이용업196560.541251451198.849989일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431200003120000-203-1969-0015019690306<NA>3폐업2폐업20120409<NA><NA><NA>020363369323.32120819서울특별시 서대문구 북아현동 129-1번지<NA><NA>양로원후생2003-03-18 00:00:00I2018-08-31 23:59:59.0일반이용업196130.776896450891.993771일반이용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531200003120000-203-1969-0018919690221<NA>1영업/정상1영업<NA><NA><NA><NA>02 732952829.75120853서울특별시 서대문구 홍제동 90-20번지 1층, 일부서울특별시 서대문구 통일로27길 9, 1층 일부호 (홍제동)3730해남2018-09-20 11:35:55U2018-09-20 23:59:59.0일반이용업195417.900062453458.009063일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631200003120000-203-1969-0111919691115<NA>1영업/정상1영업<NA><NA><NA><NA>02 322797730.55120765서울특별시 서대문구 북가좌동 431번지 (한양아파트상가 1층101호)서울특별시 서대문구 응암로 32 (북가좌동, 한양아파트상가 1층101호)3709삼성이발관2014-11-13 15:43:01I2018-08-31 23:59:59.0일반이용업191900.345925452626.221252일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731200003120000-203-1969-0135819690822<NA>3폐업2폐업20050525<NA><NA><NA>02 363129023.36120020서울특별시 서대문구 미근동 165-0번지<NA><NA>서대문경찰서구내2003-05-01 00:00:00I2018-08-31 23:59:59.0일반이용업197004.364342451399.301408일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831200003120000-203-1969-0143319691127<NA>3폐업2폐업20060614<NA><NA><NA>020392170731.28120050서울특별시 서대문구 냉천동 123-5번지<NA><NA>시민2003-12-31 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
931200003120000-203-1970-0019919701219<NA>1영업/정상1영업<NA><NA><NA><NA>02 396726113.89120841서울특별시 서대문구 홍은동 9-137번지서울특별시 서대문구 홍은중앙로8길 21 (홍은동)3605신안2014-11-28 10:05:18I2018-08-31 23:59:59.0일반이용업195405.045455455177.640802일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
38631200003120000-203-2022-0000120220105<NA>3폐업2폐업20220114<NA><NA><NA><NA>10.02120863서울특별시 서대문구 홍제동 276-6 태양열목욕탕서울특별시 서대문구 세검정로 74-8, 태양열목욕탕내 (홍제동)3622태양열사우나 이용원2022-01-14 16:09:56U2022-01-16 02:40:00.0일반이용업195391.101174454649.074712일반이용업000000000N2<NA><NA><NA><NA>00000N
38731200003120000-203-2022-0000220220322<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.0120859서울특별시 서대문구 홍제동 158-33 연세24시사우나서울특별시 서대문구 통일로 413, 연세24시사우나 지하1층 (홍제동)3646연세이용원2022-03-22 10:27:59I2022-03-24 00:22:35.0일반이용업195196.693652453764.706269일반이용업000000000N2<NA><NA><NA><NA>00000N
38831200003120000-203-2022-0000320220726<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0120809서울특별시 서대문구 대현동 101-7 혜우빌딩서울특별시 서대문구 신촌역로 10, 지하2층 (대현동, 혜우빌딩)3766혜우24시사우나 이발소2022-07-26 14:10:47I2021-12-06 22:08:00.0일반이용업194908.961215450597.757522<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38931200003120000-203-2022-0000420220801<NA>3폐업2폐업20221107<NA><NA><NA><NA>13.78120808서울특별시 서대문구 대현동 37-57서울특별시 서대문구 이화여대7길 27, 1층 (대현동)3766모범2022-11-07 14:10:59U2021-11-01 00:09:00.0일반이용업194996.051811450708.329437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39031200003120000-203-2022-0000520220819<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.5120837서울특별시 서대문구 충정로3가 3-187서울특별시 서대문구 경기대로7길 2, 1층 (충정로3가)3752하우스 바버샵(HOUSE BARBERSHOP)2022-08-19 15:27:46I2021-12-07 22:01:00.0일반이용업196574.588377451207.046401<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39131200003120000-203-2022-0000620221005<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.0120807서울특별시 서대문구 남가좌동 344-33서울특별시 서대문구 증가로 140, 1층 (남가좌동)3665나이스가이 명지대점2022-10-05 11:20:22I2021-10-31 00:07:00.0일반이용업193042.66699452830.718334<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39231200003120000-203-2022-0000720221114<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.0120861서울특별시 서대문구 홍제동 361-32서울특별시 서대문구 모래내로 375, 좌측 (홍제동)3643핫독 바버샵(HOTDOG barbershop)2022-11-16 10:33:37U2021-10-31 23:08:00.0일반이용업194393.471553453403.786169<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39331200003120000-203-2023-000012023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.79120-040서울특별시 서대문구 천연동 98-31서울특별시 서대문구 독립문로8길 13, 지층 (천연동)3745오땡큐2023-03-08 11:12:57I2022-12-02 23:00:00.0일반이용업196470.535105451814.111521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39431200003120000-203-2023-000022023-05-24<NA>3폐업2폐업2023-09-12<NA><NA><NA><NA>7.0120-857서울특별시 서대문구 홍제동 266-105 서문대중탕서울특별시 서대문구 세무서5길 35, 서문대중탕 3층 (홍제동)3628유진2023-09-12 11:27:13U2022-12-08 23:04:00.0일반이용업195055.550569454355.621235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39531200003120000-203-2024-000012024-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0120-857서울특별시 서대문구 홍제동 266-105 서문대중탕서울특별시 서대문구 세무서5길 35, 서문대중탕 목욕장업소 내 일부호 (홍제동)3628유진이용실2024-03-06 14:14:59I2023-12-03 00:08:00.0일반이용업195055.550569454355.621235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>