Overview

Dataset statistics

Number of variables47
Number of observations166
Missing cells1797
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.8 KiB
Average record size in memory405.8 B

Variable types

Categorical22
Text7
DateTime2
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19970/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신일자 is highly imbalanced (63.3%)Imbalance
업태구분명 is highly imbalanced (57.6%)Imbalance
사용시작지상층 is highly imbalanced (54.7%)Imbalance
사용끝지하층 is highly imbalanced (55.4%)Imbalance
여성종사자수 is highly imbalanced (81.8%)Imbalance
남성종사자수 is highly imbalanced (82.5%)Imbalance
침대수 is highly imbalanced (50.5%)Imbalance
다중이용업소여부 is highly imbalanced (89.9%)Imbalance
인허가취소일자 has 166 (100.0%) missing valuesMissing
폐업일자 has 36 (21.7%) missing valuesMissing
휴업시작일자 has 166 (100.0%) missing valuesMissing
휴업종료일자 has 166 (100.0%) missing valuesMissing
재개업일자 has 166 (100.0%) missing valuesMissing
전화번호 has 15 (9.0%) missing valuesMissing
도로명주소 has 91 (54.8%) missing valuesMissing
도로명우편번호 has 98 (59.0%) missing valuesMissing
좌표정보(X) has 6 (3.6%) missing valuesMissing
좌표정보(Y) has 6 (3.6%) missing valuesMissing
건물지상층수 has 104 (62.7%) missing valuesMissing
건물지하층수 has 105 (63.3%) missing valuesMissing
사용끝지상층 has 146 (88.0%) missing valuesMissing
발한실여부 has 13 (7.8%) missing valuesMissing
조건부허가신고사유 has 166 (100.0%) missing valuesMissing
조건부허가시작일자 has 166 (100.0%) missing valuesMissing
조건부허가종료일자 has 166 (100.0%) missing valuesMissing
다중이용업소여부 has 13 (7.8%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 38 (22.9%) zerosZeros
건물지하층수 has 39 (23.5%) zerosZeros
사용끝지상층 has 11 (6.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:33:01.028261
Analysis finished2024-05-11 06:33:01.968274
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3180000
166 

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 166
100.0%

Length

2024-05-11T15:33:02.073540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:02.259056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 166
100.0%

관리번호
Text

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:33:02.501092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3652
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

Unique166 ?
Unique (%)100.0%

Sample

1st row3180000-202-1970-00412
2nd row3180000-202-1973-00388
3rd row3180000-202-1976-00426
4th row3180000-202-1976-00432
5th row3180000-202-1977-00400
ValueCountFrequency (%)
3180000-202-1970-00412 1
 
0.6%
3180000-202-2003-00006 1
 
0.6%
3180000-202-2003-00008 1
 
0.6%
3180000-202-2003-00009 1
 
0.6%
3180000-202-2003-00010 1
 
0.6%
3180000-202-2003-00011 1
 
0.6%
3180000-202-2003-00012 1
 
0.6%
3180000-202-2003-00013 1
 
0.6%
3180000-202-2003-00014 1
 
0.6%
3180000-202-2003-00015 1
 
0.6%
Other values (156) 156
94.0%
2024-05-11T15:33:03.048518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1516
41.5%
- 498
 
13.6%
2 478
 
13.1%
1 321
 
8.8%
8 237
 
6.5%
3 224
 
6.1%
9 149
 
4.1%
4 105
 
2.9%
7 45
 
1.2%
5 42
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3154
86.4%
Dash Punctuation 498
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1516
48.1%
2 478
 
15.2%
1 321
 
10.2%
8 237
 
7.5%
3 224
 
7.1%
9 149
 
4.7%
4 105
 
3.3%
7 45
 
1.4%
5 42
 
1.3%
6 37
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 498
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1516
41.5%
- 498
 
13.6%
2 478
 
13.1%
1 321
 
8.8%
8 237
 
6.5%
3 224
 
6.1%
9 149
 
4.1%
4 105
 
2.9%
7 45
 
1.2%
5 42
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1516
41.5%
- 498
 
13.6%
2 478
 
13.1%
1 321
 
8.8%
8 237
 
6.5%
3 224
 
6.1%
9 149
 
4.1%
4 105
 
2.9%
7 45
 
1.2%
5 42
 
1.2%
Distinct151
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1970-08-26 00:00:00
Maximum2021-11-19 00:00:00
2024-05-11T15:33:03.326259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:33:03.545143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB
Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
130 
1
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 130
78.3%
1 36
 
21.7%

Length

2024-05-11T15:33:03.755803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:03.898220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 130
78.3%
1 36
 
21.7%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
130 
영업/정상
36 

Length

Max length5
Median length2
Mean length2.6506024
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 130
78.3%
영업/정상 36
 
21.7%

Length

2024-05-11T15:33:04.051682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:04.196473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 130
78.3%
영업/정상 36
 
21.7%
Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
130 
1
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 130
78.3%
1 36
 
21.7%

Length

2024-05-11T15:33:04.333861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:04.461651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 130
78.3%
1 36
 
21.7%
Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
130 
영업
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 130
78.3%
영업 36
 
21.7%

Length

2024-05-11T15:33:04.605267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:04.726297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 130
78.3%
영업 36
 
21.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct111
Distinct (%)85.4%
Missing36
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean20083257
Minimum19930428
Maximum20230120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:04.865413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930428
5-th percentile19961052
Q120040634
median20080455
Q320130305
95-th percentile20206184
Maximum20230120
Range299692
Interquartile range (IQR)89671.25

Descriptive statistics

Standard deviation71711.02
Coefficient of variation (CV)0.0035706868
Kurtosis-0.55583348
Mean20083257
Median Absolute Deviation (MAD)40367
Skewness0.027198141
Sum2.6108234 × 109
Variance5.1424703 × 109
MonotonicityNot monotonic
2024-05-11T15:33:05.074435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171026 5
 
3.0%
20060227 5
 
3.0%
20090817 4
 
2.4%
20050531 3
 
1.8%
20000101 2
 
1.2%
20070402 2
 
1.2%
20100712 2
 
1.2%
20030808 2
 
1.2%
20080402 2
 
1.2%
20001010 2
 
1.2%
Other values (101) 101
60.8%
(Missing) 36
 
21.7%
ValueCountFrequency (%)
19930428 1
0.6%
19930713 1
0.6%
19941104 1
0.6%
19950202 1
0.6%
19960729 1
0.6%
19960816 1
0.6%
19960924 1
0.6%
19961209 1
0.6%
19970111 1
0.6%
19970516 1
0.6%
ValueCountFrequency (%)
20230120 1
0.6%
20221215 1
0.6%
20221130 1
0.6%
20220902 1
0.6%
20220422 1
0.6%
20211020 1
0.6%
20210409 1
0.6%
20201020 1
0.6%
20200918 1
0.6%
20191217 1
0.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB

전화번호
Text

MISSING 

Distinct150
Distinct (%)99.3%
Missing15
Missing (%)9.0%
Memory size1.4 KiB
2024-05-11T15:33:05.372231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9271523
Min length2

Characters and Unicode

Total characters1499
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

Unique149 ?
Unique (%)98.7%

Sample

1st row0226331578
2nd row0226344007
3rd row02
4th row0208332314
5th row0226354508
ValueCountFrequency (%)
02 72
31.7%
8452065 2
 
0.9%
2789 1
 
0.4%
0226755700 1
 
0.4%
8315117 1
 
0.4%
8434199 1
 
0.4%
0226713801 1
 
0.4%
026726900 1
 
0.4%
7850110 1
 
0.4%
0226378869 1
 
0.4%
Other values (145) 145
63.9%
2024-05-11T15:33:05.825030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 283
18.9%
0 261
17.4%
3 157
10.5%
8 148
9.9%
6 128
8.5%
7 118
7.9%
4 105
 
7.0%
1 87
 
5.8%
81
 
5.4%
5 79
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1418
94.6%
Space Separator 81
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 283
20.0%
0 261
18.4%
3 157
11.1%
8 148
10.4%
6 128
9.0%
7 118
8.3%
4 105
 
7.4%
1 87
 
6.1%
5 79
 
5.6%
9 52
 
3.7%
Space Separator
ValueCountFrequency (%)
81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1499
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 283
18.9%
0 261
17.4%
3 157
10.5%
8 148
9.9%
6 128
8.5%
7 118
7.9%
4 105
 
7.0%
1 87
 
5.8%
81
 
5.4%
5 79
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 283
18.9%
0 261
17.4%
3 157
10.5%
8 148
9.9%
6 128
8.5%
7 118
7.9%
4 105
 
7.0%
1 87
 
5.8%
81
 
5.4%
5 79
 
5.3%
Distinct147
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:33:06.203115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.1807229
Min length3

Characters and Unicode

Total characters1026
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)84.9%

Sample

1st row254.10
2nd row528.48
3rd row.00
4th row.00
5th row210.00
ValueCountFrequency (%)
00 15
 
9.0%
434.24 2
 
1.2%
809.19 2
 
1.2%
450.00 2
 
1.2%
220.00 2
 
1.2%
716.21 2
 
1.2%
1,285.95 1
 
0.6%
589.89 1
 
0.6%
250.12 1
 
0.6%
786.44 1
 
0.6%
Other values (137) 137
82.5%
2024-05-11T15:33:06.844691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 211
20.6%
. 166
16.2%
1 104
10.1%
2 87
8.5%
4 78
 
7.6%
6 70
 
6.8%
5 69
 
6.7%
3 60
 
5.8%
7 54
 
5.3%
8 54
 
5.3%
Other values (2) 73
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 825
80.4%
Other Punctuation 201
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 211
25.6%
1 104
12.6%
2 87
10.5%
4 78
 
9.5%
6 70
 
8.5%
5 69
 
8.4%
3 60
 
7.3%
7 54
 
6.5%
8 54
 
6.5%
9 38
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 166
82.6%
, 35
 
17.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 211
20.6%
. 166
16.2%
1 104
10.1%
2 87
8.5%
4 78
 
7.6%
6 70
 
6.8%
5 69
 
6.7%
3 60
 
5.8%
7 54
 
5.3%
8 54
 
5.3%
Other values (2) 73
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 211
20.6%
. 166
16.2%
1 104
10.1%
2 87
8.5%
4 78
 
7.6%
6 70
 
6.8%
5 69
 
6.7%
3 60
 
5.8%
7 54
 
5.3%
8 54
 
5.3%
Other values (2) 73
 
7.1%
Distinct79
Distinct (%)47.9%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2024-05-11T15:33:07.225062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.030303
Min length6

Characters and Unicode

Total characters995
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

Unique35 ?
Unique (%)21.2%

Sample

1st row150866
2nd row150903
3rd row150841
4th row150858
5th row150800
ValueCountFrequency (%)
150841 11
 
6.7%
150095 5
 
3.0%
150896 5
 
3.0%
150040 5
 
3.0%
150035 4
 
2.4%
150033 4
 
2.4%
150901 4
 
2.4%
150814 4
 
2.4%
150820 4
 
2.4%
150829 3
 
1.8%
Other values (69) 116
70.3%
2024-05-11T15:33:07.794748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 258
25.9%
1 209
21.0%
5 207
20.8%
8 120
12.1%
3 53
 
5.3%
4 39
 
3.9%
9 39
 
3.9%
2 23
 
2.3%
7 23
 
2.3%
6 19
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 990
99.5%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 258
26.1%
1 209
21.1%
5 207
20.9%
8 120
12.1%
3 53
 
5.4%
4 39
 
3.9%
9 39
 
3.9%
2 23
 
2.3%
7 23
 
2.3%
6 19
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 258
25.9%
1 209
21.0%
5 207
20.8%
8 120
12.1%
3 53
 
5.3%
4 39
 
3.9%
9 39
 
3.9%
2 23
 
2.3%
7 23
 
2.3%
6 19
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 258
25.9%
1 209
21.0%
5 207
20.8%
8 120
12.1%
3 53
 
5.3%
4 39
 
3.9%
9 39
 
3.9%
2 23
 
2.3%
7 23
 
2.3%
6 19
 
1.9%
Distinct155
Distinct (%)93.9%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2024-05-11T15:33:08.182360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length26.951515
Min length19

Characters and Unicode

Total characters4447
Distinct characters132
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

Unique146 ?
Unique (%)88.5%

Sample

1st row서울특별시 영등포구 양평동4가 71-1번지
2nd row서울특별시 영등포구 영등포동2가 328-11번지
3rd row서울특별시 영등포구 신길동 276-1번지
4th row서울특별시 영등포구 신길동 3813-0번지
5th row서울특별시 영등포구 당산동1가 256-122번지
ValueCountFrequency (%)
서울특별시 165
21.4%
영등포구 165
21.4%
신길동 42
 
5.5%
여의도동 25
 
3.2%
대림동 18
 
2.3%
지하 8
 
1.0%
도림동 8
 
1.0%
지하1층 7
 
0.9%
영등포동5가 6
 
0.8%
영등포동2가 6
 
0.8%
Other values (242) 320
41.6%
2024-05-11T15:33:08.965572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
754
 
17.0%
196
 
4.4%
195
 
4.4%
194
 
4.4%
175
 
3.9%
1 174
 
3.9%
171
 
3.8%
167
 
3.8%
165
 
3.7%
165
 
3.7%
Other values (122) 2091
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2740
61.6%
Decimal Number 779
 
17.5%
Space Separator 754
 
17.0%
Dash Punctuation 134
 
3.0%
Uppercase Letter 21
 
0.5%
Other Punctuation 15
 
0.3%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
196
 
7.2%
195
 
7.1%
194
 
7.1%
175
 
6.4%
171
 
6.2%
167
 
6.1%
165
 
6.0%
165
 
6.0%
165
 
6.0%
165
 
6.0%
Other values (98) 982
35.8%
Decimal Number
ValueCountFrequency (%)
1 174
22.3%
3 112
14.4%
2 105
13.5%
4 88
11.3%
5 79
10.1%
0 50
 
6.4%
6 50
 
6.4%
9 49
 
6.3%
7 39
 
5.0%
8 33
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 8
38.1%
T 3
 
14.3%
P 3
 
14.3%
A 3
 
14.3%
E 1
 
4.8%
R 1
 
4.8%
H 1
 
4.8%
K 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 14
93.3%
/ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
754
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2740
61.6%
Common 1686
37.9%
Latin 21
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
196
 
7.2%
195
 
7.1%
194
 
7.1%
175
 
6.4%
171
 
6.2%
167
 
6.1%
165
 
6.0%
165
 
6.0%
165
 
6.0%
165
 
6.0%
Other values (98) 982
35.8%
Common
ValueCountFrequency (%)
754
44.7%
1 174
 
10.3%
- 134
 
7.9%
3 112
 
6.6%
2 105
 
6.2%
4 88
 
5.2%
5 79
 
4.7%
0 50
 
3.0%
6 50
 
3.0%
9 49
 
2.9%
Other values (6) 91
 
5.4%
Latin
ValueCountFrequency (%)
B 8
38.1%
T 3
 
14.3%
P 3
 
14.3%
A 3
 
14.3%
E 1
 
4.8%
R 1
 
4.8%
H 1
 
4.8%
K 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2740
61.6%
ASCII 1707
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
754
44.2%
1 174
 
10.2%
- 134
 
7.9%
3 112
 
6.6%
2 105
 
6.2%
4 88
 
5.2%
5 79
 
4.6%
0 50
 
2.9%
6 50
 
2.9%
9 49
 
2.9%
Other values (14) 112
 
6.6%
Hangul
ValueCountFrequency (%)
196
 
7.2%
195
 
7.1%
194
 
7.1%
175
 
6.4%
171
 
6.2%
167
 
6.1%
165
 
6.0%
165
 
6.0%
165
 
6.0%
165
 
6.0%
Other values (98) 982
35.8%

도로명주소
Text

MISSING 

Distinct75
Distinct (%)100.0%
Missing91
Missing (%)54.8%
Memory size1.4 KiB
2024-05-11T15:33:09.270919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length42
Mean length32.2
Min length23

Characters and Unicode

Total characters2415
Distinct characters137
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

Unique75 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 영중로14길 36 (영등포동2가)
2nd row서울특별시 영등포구 당산로16길 26 (당산동1가)
3rd row서울특별시 영등포구 신길로8길 8 (신길동)
4th row서울특별시 영등포구 국회대로76길 16 (여의도동,맨하탄호텔 지하)
5th row서울특별시 영등포구 영중로8길 7 (영등포동3가)
ValueCountFrequency (%)
서울특별시 75
 
17.2%
영등포구 75
 
17.2%
신길동 17
 
3.9%
대림동 10
 
2.3%
지하1층 7
 
1.6%
선유로 5
 
1.1%
여의도동 5
 
1.1%
63로 4
 
0.9%
7 4
 
0.9%
지하 4
 
0.9%
Other values (183) 229
52.6%
2024-05-11T15:33:09.831457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
 
14.9%
103
 
4.3%
97
 
4.0%
96
 
4.0%
81
 
3.4%
( 79
 
3.3%
) 79
 
3.3%
78
 
3.2%
76
 
3.1%
75
 
3.1%
Other values (127) 1291
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1507
62.4%
Space Separator 360
 
14.9%
Decimal Number 320
 
13.3%
Open Punctuation 79
 
3.3%
Close Punctuation 79
 
3.3%
Other Punctuation 50
 
2.1%
Uppercase Letter 14
 
0.6%
Dash Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
103
 
6.8%
97
 
6.4%
96
 
6.4%
81
 
5.4%
78
 
5.2%
76
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
Other values (103) 676
44.9%
Decimal Number
ValueCountFrequency (%)
1 64
20.0%
3 46
14.4%
2 38
11.9%
5 35
10.9%
6 29
9.1%
0 25
 
7.8%
4 25
 
7.8%
7 23
 
7.2%
8 22
 
6.9%
9 13
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
A 2
 
14.3%
R 1
 
7.1%
P 1
 
7.1%
E 1
 
7.1%
H 1
 
7.1%
T 1
 
7.1%
K 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 49
98.0%
/ 1
 
2.0%
Space Separator
ValueCountFrequency (%)
360
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1507
62.4%
Common 894
37.0%
Latin 14
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
103
 
6.8%
97
 
6.4%
96
 
6.4%
81
 
5.4%
78
 
5.2%
76
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
Other values (103) 676
44.9%
Common
ValueCountFrequency (%)
360
40.3%
( 79
 
8.8%
) 79
 
8.8%
1 64
 
7.2%
, 49
 
5.5%
3 46
 
5.1%
2 38
 
4.3%
5 35
 
3.9%
6 29
 
3.2%
0 25
 
2.8%
Other values (6) 90
 
10.1%
Latin
ValueCountFrequency (%)
B 6
42.9%
A 2
 
14.3%
R 1
 
7.1%
P 1
 
7.1%
E 1
 
7.1%
H 1
 
7.1%
T 1
 
7.1%
K 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1507
62.4%
ASCII 908
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
39.6%
( 79
 
8.7%
) 79
 
8.7%
1 64
 
7.0%
, 49
 
5.4%
3 46
 
5.1%
2 38
 
4.2%
5 35
 
3.9%
6 29
 
3.2%
0 25
 
2.8%
Other values (14) 104
 
11.5%
Hangul
ValueCountFrequency (%)
103
 
6.8%
97
 
6.4%
96
 
6.4%
81
 
5.4%
78
 
5.2%
76
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
75
 
5.0%
Other values (103) 676
44.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)80.9%
Missing98
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean7319.7059
Minimum7204
Maximum7445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:10.067272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7204
5-th percentile7216.15
Q17254.25
median7319.5
Q37370.5
95-th percentile7437.65
Maximum7445
Range241
Interquartile range (IQR)116.25

Descriptive statistics

Standard deviation68.207554
Coefficient of variation (CV)0.0093183463
Kurtosis-1.0316517
Mean7319.7059
Median Absolute Deviation (MAD)59.5
Skewness0.12222665
Sum497740
Variance4652.2704
MonotonicityNot monotonic
2024-05-11T15:33:10.270827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7250 4
 
2.4%
7345 3
 
1.8%
7417 2
 
1.2%
7306 2
 
1.2%
7261 2
 
1.2%
7333 2
 
1.2%
7348 2
 
1.2%
7285 2
 
1.2%
7304 2
 
1.2%
7238 2
 
1.2%
Other values (45) 45
27.1%
(Missing) 98
59.0%
ValueCountFrequency (%)
7204 1
0.6%
7211 1
0.6%
7212 1
0.6%
7213 1
0.6%
7222 1
0.6%
7226 1
0.6%
7227 1
0.6%
7237 1
0.6%
7238 2
1.2%
7248 1
0.6%
ValueCountFrequency (%)
7445 1
0.6%
7442 1
0.6%
7440 1
0.6%
7438 1
0.6%
7437 1
0.6%
7417 2
1.2%
7413 1
0.6%
7409 1
0.6%
7408 1
0.6%
7403 1
0.6%
Distinct154
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:33:10.640358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length5.8674699
Min length2

Characters and Unicode

Total characters974
Distinct characters194
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

Unique143 ?
Unique (%)86.1%

Sample

1st row삼정목욕탕
2nd row천일온탕
3rd row삼일목욕탕
4th row수정
5th row새말목욕탕
ValueCountFrequency (%)
사우나 6
 
3.2%
청수목욕탕 3
 
1.6%
천지연사우나 2
 
1.1%
우리불한증사우나 2
 
1.1%
삼일목욕탕 2
 
1.1%
해천사우나 2
 
1.1%
옥수 2
 
1.1%
여의도 2
 
1.1%
성보목욕탕 2
 
1.1%
도림탕 2
 
1.1%
Other values (162) 165
86.8%
2024-05-11T15:33:11.251693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
6.7%
63
 
6.5%
60
 
6.2%
60
 
6.2%
52
 
5.3%
51
 
5.2%
27
 
2.8%
24
 
2.5%
18
 
1.8%
17
 
1.7%
Other values (184) 537
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 917
94.1%
Space Separator 24
 
2.5%
Decimal Number 10
 
1.0%
Uppercase Letter 9
 
0.9%
Open Punctuation 6
 
0.6%
Close Punctuation 6
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
65
 
7.1%
63
 
6.9%
60
 
6.5%
60
 
6.5%
52
 
5.7%
51
 
5.6%
27
 
2.9%
18
 
2.0%
17
 
1.9%
17
 
1.9%
Other values (169) 487
53.1%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
4 3
30.0%
3 1
 
10.0%
5 1
 
10.0%
6 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
A 2
22.2%
N 2
22.2%
O 2
22.2%
G 1
11.1%
Other Punctuation
ValueCountFrequency (%)
? 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 917
94.1%
Common 48
 
4.9%
Latin 9
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
65
 
7.1%
63
 
6.9%
60
 
6.5%
60
 
6.5%
52
 
5.7%
51
 
5.6%
27
 
2.9%
18
 
2.0%
17
 
1.9%
17
 
1.9%
Other values (169) 487
53.1%
Common
ValueCountFrequency (%)
24
50.0%
( 6
 
12.5%
) 6
 
12.5%
2 4
 
8.3%
4 3
 
6.2%
? 1
 
2.1%
. 1
 
2.1%
3 1
 
2.1%
5 1
 
2.1%
6 1
 
2.1%
Latin
ValueCountFrequency (%)
M 2
22.2%
A 2
22.2%
N 2
22.2%
O 2
22.2%
G 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 917
94.1%
ASCII 57
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
65
 
7.1%
63
 
6.9%
60
 
6.5%
60
 
6.5%
52
 
5.7%
51
 
5.6%
27
 
2.9%
18
 
2.0%
17
 
1.9%
17
 
1.9%
Other values (169) 487
53.1%
ASCII
ValueCountFrequency (%)
24
42.1%
( 6
 
10.5%
) 6
 
10.5%
2 4
 
7.0%
4 3
 
5.3%
M 2
 
3.5%
A 2
 
3.5%
N 2
 
3.5%
O 2
 
3.5%
? 1
 
1.8%
Other values (5) 5
 
8.8%
Distinct115
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2000-10-12 00:00:00
Maximum2024-05-01 14:07:43
2024-05-11T15:33:11.447138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:33:11.991691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
130 
U
36 

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 130
78.3%
U 36
 
21.7%

Length

2024-05-11T15:33:12.206999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:12.350777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 130
78.3%
u 36
 
21.7%

데이터갱신일자
Categorical

IMBALANCE 

Distinct38
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2018-08-31 23:59:59.0
129 
2021-05-02 02:40:00.0
 
1
2021-12-09 00:04:00.0
 
1
2021-12-03 22:04:00.0
 
1
2019-09-04 02:40:00.0
 
1
Other values (33)
33 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique37 ?
Unique (%)22.3%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 129
77.7%
2021-05-02 02:40:00.0 1
 
0.6%
2021-12-09 00:04:00.0 1
 
0.6%
2021-12-03 22:04:00.0 1
 
0.6%
2019-09-04 02:40:00.0 1
 
0.6%
2019-12-04 02:40:00.0 1
 
0.6%
2022-11-30 22:02:00.0 1
 
0.6%
2023-12-05 00:03:00.0 1
 
0.6%
2019-04-13 02:40:00.0 1
 
0.6%
2020-09-20 02:40:00.0 1
 
0.6%
Other values (28) 28
 
16.9%

Length

2024-05-11T15:33:12.515109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 129
38.9%
23:59:59.0 129
38.9%
02:40:00.0 23
 
6.9%
22:00:00.0 2
 
0.6%
2022-11-30 2
 
0.6%
22:02:00.0 2
 
0.6%
2019-12-08 1
 
0.3%
2019-02-23 1
 
0.3%
2019-05-13 1
 
0.3%
2022-01-15 1
 
0.3%
Other values (41) 41
 
12.3%

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
공동탕업
133 
공동탕업+찜질시설서비스영업
23 
한증막업
 
5
찜질시설서비스영업
 
3
목욕장업 기타
 
2

Length

Max length14
Median length4
Mean length5.5120482
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 133
80.1%
공동탕업+찜질시설서비스영업 23
 
13.9%
한증막업 5
 
3.0%
찜질시설서비스영업 3
 
1.8%
목욕장업 기타 2
 
1.2%

Length

2024-05-11T15:33:12.693319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:12.856331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 133
79.2%
공동탕업+찜질시설서비스영업 23
 
13.7%
한증막업 5
 
3.0%
찜질시설서비스영업 3
 
1.8%
목욕장업 2
 
1.2%
기타 2
 
1.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)81.9%
Missing6
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean191815.61
Minimum189602.77
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:13.036031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189602.77
5-th percentile190033.89
Q1191043.59
median191714.93
Q3192471.63
95-th percentile193840.88
Maximum194632.53
Range5029.7588
Interquartile range (IQR)1428.0382

Descriptive statistics

Standard deviation1098.9147
Coefficient of variation (CV)0.0057290162
Kurtosis-0.0559198
Mean191815.61
Median Absolute Deviation (MAD)720.99966
Skewness0.41209931
Sum30690498
Variance1207613.6
MonotonicityNot monotonic
2024-05-11T15:33:13.219996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194504.656267957 4
 
2.4%
191908.118795329 3
 
1.8%
189877.032334127 3
 
1.8%
191937.281348398 3
 
1.8%
191683.586637281 3
 
1.8%
190034.436613508 2
 
1.2%
192165.93453037 2
 
1.2%
190394.571819262 2
 
1.2%
191558.008889229 2
 
1.2%
191800.728214995 2
 
1.2%
Other values (121) 134
80.7%
(Missing) 6
 
3.6%
ValueCountFrequency (%)
189602.767582543 1
 
0.6%
189734.544016734 1
 
0.6%
189877.032334127 3
1.8%
189923.407054333 1
 
0.6%
190023.48828661 2
1.2%
190034.436613508 2
1.2%
190174.422109333 1
 
0.6%
190292.658514827 1
 
0.6%
190364.652010662 1
 
0.6%
190394.571819262 2
1.2%
ValueCountFrequency (%)
194632.526367463 1
 
0.6%
194504.656267957 4
2.4%
194370.32715363 1
 
0.6%
193844.169062846 2
1.2%
193840.710101987 1
 
0.6%
193765.78367653 1
 
0.6%
193752.566772147 1
 
0.6%
193501.453598102 1
 
0.6%
193469.554731741 1
 
0.6%
193468.152070342 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)81.9%
Missing6
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean445976.94
Minimum442861.81
Maximum448656.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:13.393534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442861.81
5-th percentile443502.86
Q1445114.03
median446158.99
Q3446801.78
95-th percentile448064.97
Maximum448656.73
Range5794.9179
Interquartile range (IQR)1687.7493

Descriptive statistics

Standard deviation1329.7341
Coefficient of variation (CV)0.0029816207
Kurtosis-0.42454798
Mean445976.94
Median Absolute Deviation (MAD)920.54773
Skewness-0.28884137
Sum71356311
Variance1768192.8
MonotonicityNot monotonic
2024-05-11T15:33:13.578002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446355.021491973 4
 
2.4%
446086.819081927 3
 
1.8%
446801.78225662 3
 
1.8%
445500.742692663 3
 
1.8%
446668.345375487 3
 
1.8%
446093.483911313 2
 
1.2%
446508.000792709 2
 
1.2%
448656.726986041 2
 
1.2%
447593.843343674 2
 
1.2%
443809.773854649 2
 
1.2%
Other values (121) 134
80.7%
(Missing) 6
 
3.6%
ValueCountFrequency (%)
442861.809050257 1
0.6%
443096.527391865 1
0.6%
443105.538726652 1
0.6%
443207.77252958 1
0.6%
443235.434086404 1
0.6%
443282.540835865 1
0.6%
443417.54856347 1
0.6%
443444.22840271 1
0.6%
443505.951042562 1
0.6%
443632.592211895 1
0.6%
ValueCountFrequency (%)
448656.726986041 2
1.2%
448525.658592957 1
0.6%
448350.61743141 1
0.6%
448291.624665575 1
0.6%
448283.533040285 1
0.6%
448191.644571742 1
0.6%
448079.622534069 1
0.6%
448064.203408309 1
0.6%
448060.438258654 1
0.6%
447969.888804341 1
0.6%

위생업태명
Categorical

Distinct6
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
공동탕업
124 
공동탕업+찜질시설서비스영업
19 
<NA>
13 
한증막업
 
5
찜질시설서비스영업
 
3

Length

Max length14
Median length4
Mean length5.2710843
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 124
74.7%
공동탕업+찜질시설서비스영업 19
 
11.4%
<NA> 13
 
7.8%
한증막업 5
 
3.0%
찜질시설서비스영업 3
 
1.8%
목욕장업 기타 2
 
1.2%

Length

2024-05-11T15:33:13.746681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:13.918987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 124
73.8%
공동탕업+찜질시설서비스영업 19
 
11.3%
na 13
 
7.7%
한증막업 5
 
3.0%
찜질시설서비스영업 3
 
1.8%
목욕장업 2
 
1.2%
기타 2
 
1.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)22.6%
Missing104
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean3.3387097
Minimum0
Maximum40
Zeros38
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:14.108453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile14
Maximum40
Range40
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.6232169
Coefficient of variation (CV)1.9837654
Kurtosis15.138589
Mean3.3387097
Median Absolute Deviation (MAD)0
Skewness3.4080006
Sum207
Variance43.867002
MonotonicityNot monotonic
2024-05-11T15:33:14.313454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 38
 
22.9%
3 5
 
3.0%
4 4
 
2.4%
5 3
 
1.8%
12 2
 
1.2%
14 2
 
1.2%
6 1
 
0.6%
7 1
 
0.6%
19 1
 
0.6%
8 1
 
0.6%
Other values (4) 4
 
2.4%
(Missing) 104
62.7%
ValueCountFrequency (%)
0 38
22.9%
2 1
 
0.6%
3 5
 
3.0%
4 4
 
2.4%
5 3
 
1.8%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
10 1
 
0.6%
12 2
 
1.2%
ValueCountFrequency (%)
40 1
 
0.6%
19 1
 
0.6%
17 1
 
0.6%
14 2
1.2%
12 2
1.2%
10 1
 
0.6%
8 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%
5 3
1.8%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)9.8%
Missing105
Missing (%)63.3%
Infinite0
Infinite (%)0.0%
Mean0.78688525
Minimum0
Maximum7
Zeros39
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:14.527179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3918184
Coefficient of variation (CV)1.7687692
Kurtosis6.2081698
Mean0.78688525
Median Absolute Deviation (MAD)0
Skewness2.3129634
Sum48
Variance1.9371585
MonotonicityNot monotonic
2024-05-11T15:33:14.686772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 39
 
23.5%
1 10
 
6.0%
2 5
 
3.0%
4 3
 
1.8%
3 3
 
1.8%
7 1
 
0.6%
(Missing) 105
63.3%
ValueCountFrequency (%)
0 39
23.5%
1 10
 
6.0%
2 5
 
3.0%
3 3
 
1.8%
4 3
 
1.8%
7 1
 
0.6%
ValueCountFrequency (%)
7 1
 
0.6%
4 3
 
1.8%
3 3
 
1.8%
2 5
 
3.0%
1 10
 
6.0%
0 39
23.5%

사용시작지상층
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
121 
0
34 
2
 
6
1
 
2
4
 
2

Length

Max length4
Median length4
Mean length3.186747
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
72.9%
0 34
 
20.5%
2 6
 
3.6%
1 2
 
1.2%
4 2
 
1.2%
3 1
 
0.6%

Length

2024-05-11T15:33:14.867360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:15.042287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
72.9%
0 34
 
20.5%
2 6
 
3.6%
1 2
 
1.2%
4 2
 
1.2%
3 1
 
0.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)35.0%
Missing146
Missing (%)88.0%
Infinite0
Infinite (%)0.0%
Mean1.45
Minimum0
Maximum6
Zeros11
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:33:15.207830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.25
95-th percentile5.05
Maximum6
Range6
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation1.9594575
Coefficient of variation (CV)1.35135
Kurtosis0.021873252
Mean1.45
Median Absolute Deviation (MAD)0
Skewness1.1091878
Sum29
Variance3.8394737
MonotonicityNot monotonic
2024-05-11T15:33:15.359098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 11
 
6.6%
2 3
 
1.8%
4 2
 
1.2%
6 1
 
0.6%
5 1
 
0.6%
3 1
 
0.6%
1 1
 
0.6%
(Missing) 146
88.0%
ValueCountFrequency (%)
0 11
6.6%
1 1
 
0.6%
2 3
 
1.8%
3 1
 
0.6%
4 2
 
1.2%
5 1
 
0.6%
6 1
 
0.6%
ValueCountFrequency (%)
6 1
 
0.6%
5 1
 
0.6%
4 2
 
1.2%
3 1
 
0.6%
2 3
 
1.8%
1 1
 
0.6%
0 11
6.6%
Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
109 
0
28 
1
22 
2
 
6
3
 
1

Length

Max length4
Median length4
Mean length2.9698795
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 109
65.7%
0 28
 
16.9%
1 22
 
13.3%
2 6
 
3.6%
3 1
 
0.6%

Length

2024-05-11T15:33:15.532558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:15.695894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 109
65.7%
0 28
 
16.9%
1 22
 
13.3%
2 6
 
3.6%
3 1
 
0.6%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
134 
1
16 
2
 
7
0
 
7
3
 
2

Length

Max length4
Median length4
Mean length3.4216867
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> 134
80.7%
1 16
 
9.6%
2 7
 
4.2%
0 7
 
4.2%
3 2
 
1.2%

Length

2024-05-11T15:33:15.880416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:16.052049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
80.7%
1 16
 
9.6%
2 7
 
4.2%
0 7
 
4.2%
3 2
 
1.2%

한실수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
113 
0
53 

Length

Max length4
Median length4
Mean length3.0421687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 113
68.1%
0 53
31.9%

Length

2024-05-11T15:33:16.242846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:16.453290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
68.1%
0 53
31.9%

양실수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
113 
0
53 

Length

Max length4
Median length4
Mean length3.0421687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 113
68.1%
0 53
31.9%

Length

2024-05-11T15:33:16.635468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:16.841695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
68.1%
0 53
31.9%

욕실수
Categorical

Distinct6
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
98 
0
33 
2
28 
1
 
3
4
 
3

Length

Max length4
Median length4
Mean length2.7710843
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 98
59.0%
0 33
 
19.9%
2 28
 
16.9%
1 3
 
1.8%
4 3
 
1.8%
7 1
 
0.6%

Length

2024-05-11T15:33:16.975327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:17.120414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
59.0%
0 33
 
19.9%
2 28
 
16.9%
1 3
 
1.8%
4 3
 
1.8%
7 1
 
0.6%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.3%
Missing13
Missing (%)7.8%
Memory size464.0 B
False
122 
True
31 
(Missing)
13 
ValueCountFrequency (%)
False 122
73.5%
True 31
 
18.7%
(Missing) 13
 
7.8%
2024-05-11T15:33:17.238203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
113 
0
53 

Length

Max length4
Median length4
Mean length3.0421687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 113
68.1%
0 53
31.9%

Length

2024-05-11T15:33:17.365870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:17.505342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
68.1%
0 53
31.9%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing166
Missing (%)100.0%
Memory size1.6 KiB
Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
133 
임대
24 
자가
 
9

Length

Max length4
Median length4
Mean length3.6024096
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 133
80.1%
임대 24
 
14.5%
자가 9
 
5.4%

Length

2024-05-11T15:33:17.663038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:17.835524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 133
80.1%
임대 24
 
14.5%
자가 9
 
5.4%

세탁기수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
136 
0
30 

Length

Max length4
Median length4
Mean length3.4578313
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> 136
81.9%
0 30
 
18.1%

Length

2024-05-11T15:33:17.985445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:18.123946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
81.9%
0 30
 
18.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
159 
0
 
5
2
 
2

Length

Max length4
Median length4
Mean length3.873494
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> 159
95.8%
0 5
 
3.0%
2 2
 
1.2%

Length

2024-05-11T15:33:18.269382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:18.389280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 159
95.8%
0 5
 
3.0%
2 2
 
1.2%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
159 
0
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.873494
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
95.8%
0 6
 
3.6%
2 1
 
0.6%

Length

2024-05-11T15:33:18.504177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:18.628890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 159
95.8%
0 6
 
3.6%
2 1
 
0.6%

회수건조수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
145 
0
21 

Length

Max length4
Median length4
Mean length3.6204819
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> 145
87.3%
0 21
 
12.7%

Length

2024-05-11T15:33:18.779756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:18.901531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
87.3%
0 21
 
12.7%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
148 
0
18 

Length

Max length4
Median length4
Mean length3.6746988
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> 148
89.2%
0 18
 
10.8%

Length

2024-05-11T15:33:19.045775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:33:19.161431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
89.2%
0 18
 
10.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.3%
Missing13
Missing (%)7.8%
Memory size464.0 B
False
151 
True
 
2
(Missing)
 
13
ValueCountFrequency (%)
False 151
91.0%
True 2
 
1.2%
(Missing) 13
 
7.8%
2024-05-11T15:33:19.253577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031800003180000-202-1970-0041219700826<NA>3폐업2폐업20110118<NA><NA><NA>0226331578254.10150866서울특별시 영등포구 양평동4가 71-1번지<NA><NA>삼정목욕탕2004-11-12 00:00:00I2018-08-31 23:59:59.0공동탕업190712.518988448283.53304공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131800003180000-202-1973-0038819730829<NA>3폐업2폐업20140303<NA><NA><NA>0226344007528.48150903서울특별시 영등포구 영등포동2가 328-11번지서울특별시 영등포구 영중로14길 36 (영등포동2가)<NA>천일온탕2012-02-29 10:32:28I2018-08-31 23:59:59.0공동탕업191893.26571446366.651805공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231800003180000-202-1976-0042619760701<NA>3폐업2폐업20000101<NA><NA><NA>02.00150841서울특별시 영등포구 신길동 276-1번지<NA><NA>삼일목욕탕2003-02-06 00:00:00I2018-08-31 23:59:59.0공동탕업191913.022489445157.953708공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331800003180000-202-1976-0043219760705<NA>3폐업2폐업20000803<NA><NA><NA>0208332314.00150858서울특별시 영등포구 신길동 3813-0번지<NA><NA>수정2003-02-06 00:00:00I2018-08-31 23:59:59.0공동탕업192158.756509444192.034459공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431800003180000-202-1977-0040019770504<NA>3폐업2폐업20120515<NA><NA><NA>0226354508210.00150800서울특별시 영등포구 당산동1가 256-122번지서울특별시 영등포구 당산로16길 26 (당산동1가)7266새말목욕탕2004-11-12 00:00:00I2018-08-31 23:59:59.0공동탕업191048.10289446983.043776공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531800003180000-202-1979-0039919790810<NA>3폐업2폐업20061030<NA><NA><NA>0226346605330.00150804서울특별시 영등포구 당산동3가 558-5번지<NA><NA>평화목욕탕2004-11-12 00:00:00I2018-08-31 23:59:59.0공동탕업190537.195263447165.962852공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631800003180000-202-1982-0038719821223<NA>3폐업2폐업20000101<NA><NA><NA>0206787247364.61150033서울특별시 영등포구 영등포동3가 24-0번지<NA><NA>옥수2003-02-06 00:00:00I2018-08-31 23:59:59.0공동탕업191808.025363446252.586272공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731800003180000-202-1982-0040319820927<NA>3폐업2폐업19960816<NA><NA><NA>0206347585.00150040서울특별시 영등포구 당산동 171-18번지<NA><NA>청수목욕탕2003-02-06 00:00:00I2018-08-31 23:59:59.0공동탕업191711.708138447341.746311공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831800003180000-202-1982-0043319820108<NA>3폐업2폐업20210409<NA><NA><NA>02 8321332332.00150860서울특별시 영등포구 신길동 4668-4서울특별시 영등포구 신길로8길 8 (신길동)7437우진목욕탕2021-04-09 15:19:21U2021-04-11 02:40:00.0공동탕업191934.397851443714.340369공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931800003180000-202-1982-0049619821221<NA>3폐업2폐업20220422<NA><NA><NA>02 78408321,155.00150870서울특별시 영등포구 여의도동 13-3 맨하탄호텔 지하서울특별시 영등포구 국회대로76길 16 (여의도동,맨하탄호텔 지하)7238맨하탄호텔사우나2022-04-22 16:13:35U2021-12-03 22:04:00.0공동탕업193019.645823447560.16231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
15631800003180000-202-2015-0000120150415<NA>3폐업2폐업20221130<NA><NA><NA><NA>263.75150045서울특별시 영등포구 당산동5가 9-1 88빌딩 지하1층서울특별시 영등포구 당산로45길 7, 지하1층 (당산동5가, 88빌딩 )7213웰빙 사우나2022-11-30 13:16:33U2021-11-02 00:02:00.0공동탕업191143.816124447937.935881<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15731800003180000-202-2015-0000220150429<NA>1영업/정상1영업<NA><NA><NA><NA>02 833 2789201.76150833서울특별시 영등포구 도림동 268-3 정남빌딩 4층서울특별시 영등포구 도영로 23, 4층 (도림동, 정남빌딩)7372고마온GOMAON2020-07-16 11:02:31U2020-07-18 02:40:00.0찜질시설서비스영업190722.547985445163.691376찜질시설서비스영업0044<NA><NA>000Y0<NA><NA><NA>임대00000Y
15831800003180000-202-2015-0000320150901<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1,002.40150849서울특별시 영등포구 신길동 364번지 건영아파트 상가 지층서울특별시 영등포구 도림로 313 (신길동, 건영아파트 상가 지층)7380건영스파2019-06-13 18:00:10U2019-06-15 02:40:00.0공동탕업+찜질시설서비스영업191202.282286444841.059497공동탕업+찜질시설서비스영업31<NA><NA>1<NA>002Y0<NA><NA><NA><NA>02200N
15931800003180000-202-2015-000042015-11-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>975.00150-035서울특별시 영등포구 영등포동5가 24서울특별시 영등포구 영등포로37길 4 (영등포동5가)7250동남사우나2024-02-27 13:40:35U2023-12-01 22:09:00.0공동탕업+찜질시설서비스영업191590.878296446489.419538<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16031800003180000-202-2016-0000120161207<NA>3폐업2폐업20201020<NA><NA><NA><NA>115.06<NA><NA>서울특별시 영등포구 대림로8가길 1 (대림동)7442신기한 토르마린(찜질방)2020-10-20 11:48:22U2020-10-22 02:40:00.0찜질시설서비스영업191531.775751443105.538727찜질시설서비스영업002<NA><NA><NA>000N0<NA><NA><NA><NA>02000N
16131800003180000-202-2017-0000120170725<NA>3폐업2폐업20191217<NA><NA><NA><NA>286,431.00150033서울특별시 영등포구 영등포동3가 9-13번지 에쉐르쇼핑몰 3,4 층서울특별시 영등포구 영중로 12 (영등포동3가, 에쉐르쇼핑몰 3,4 층)7304에쉐르 스파랜드2019-12-17 14:20:05U2019-12-19 02:40:00.0공동탕업+찜질시설서비스영업191664.796066446160.543792공동탕업+찜질시설서비스영업304<NA><NA><NA>002N0<NA><NA><NA><NA>00000N
16231800003180000-202-2019-0000120190212<NA>1영업/정상1영업<NA><NA><NA><NA>028332474220.60150841서울특별시 영등포구 신길동 220-12서울특별시 영등포구 신길로 220, 양우빌딩 지하1층 (신길동)7313면역공방?가위바위보2021-06-11 13:11:50U2021-06-13 02:40:00.0찜질시설서비스영업191998.784153445502.339792찜질시설서비스영업00<NA><NA><NA><NA>000Y0<NA><NA><NA><NA>00000Y
16331800003180000-202-2020-000012020-01-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 211113422763.54150-033서울특별시 영등포구 영등포동3가 9-13 에쉐르아이 시네마 쇼핑몰서울특별시 영등포구 영중로 12, 에쉐르아이 시네마 쇼핑몰 지상3,4층 (영등포동3가)7304천지힐링스파 황토 불가마 사우나2023-02-17 13:15:33U2022-12-01 23:09:00.0공동탕업+찜질시설서비스영업191664.796066446160.543792<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16431800003180000-202-2021-000012021-03-19<NA>1영업/정상1영업<NA><NA><NA><NA>02209080231348.00150-881서울특별시 영등포구 여의도동 28-3 여의도파크센터서울특별시 영등포구 여의대로 8, 여의도파크센터 B2층 (여의도동)7320여의도 메리어트 호텔 수피트니스 앤 스파2023-12-18 14:39:14U2022-11-01 22:00:00.0공동탕업+찜질시설서비스영업192739.314354446552.469846<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16531800003180000-202-2021-0000220211119<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,744.14150804서울특별시 영등포구 당산동3가 558-3 THE PARK 365서울특별시 영등포구 선유동1로 50, THE PARK 365 지하1층 (당산동3가)7261더파크 엠 사우나2021-11-19 11:17:18I2021-11-21 00:22:44.0공동탕업+찜질시설서비스영업190487.784358447142.741733공동탕업+찜질시설서비스영업000010002Y0<NA><NA><NA>임대00000N