Overview

Dataset statistics

Number of variables47
Number of observations156
Missing cells1830
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.8 KiB
Average record size in memory405.8 B

Variable types

Categorical20
Text7
DateTime2
Unsupported7
Numeric9
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-19967/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신일자 is highly imbalanced (58.4%)Imbalance
사용끝지하층 is highly imbalanced (53.4%)Imbalance
여성종사자수 is highly imbalanced (63.2%)Imbalance
남성종사자수 is highly imbalanced (63.2%)Imbalance
인허가취소일자 has 156 (100.0%) missing valuesMissing
폐업일자 has 40 (25.6%) missing valuesMissing
휴업시작일자 has 156 (100.0%) missing valuesMissing
휴업종료일자 has 156 (100.0%) missing valuesMissing
재개업일자 has 156 (100.0%) missing valuesMissing
전화번호 has 8 (5.1%) missing valuesMissing
도로명주소 has 82 (52.6%) missing valuesMissing
도로명우편번호 has 84 (53.8%) missing valuesMissing
좌표정보(X) has 5 (3.2%) missing valuesMissing
좌표정보(Y) has 5 (3.2%) missing valuesMissing
건물지상층수 has 80 (51.3%) missing valuesMissing
건물지하층수 has 80 (51.3%) missing valuesMissing
사용시작지상층 has 102 (65.4%) missing valuesMissing
사용끝지상층 has 124 (79.5%) missing valuesMissing
욕실수 has 82 (52.6%) missing valuesMissing
발한실여부 has 23 (14.7%) missing valuesMissing
조건부허가신고사유 has 156 (100.0%) missing valuesMissing
조건부허가시작일자 has 156 (100.0%) missing valuesMissing
조건부허가종료일자 has 156 (100.0%) missing valuesMissing
다중이용업소여부 has 23 (14.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 33 (21.2%) zerosZeros
건물지하층수 has 34 (21.8%) zerosZeros
사용시작지상층 has 26 (16.7%) zerosZeros
사용끝지상층 has 6 (3.8%) zerosZeros
욕실수 has 24 (15.4%) zerosZeros

Reproduction

Analysis started2024-05-11 06:57:17.139716
Analysis finished2024-05-11 06:57:18.214893
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3150000
156 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 156
100.0%

Length

2024-05-11T15:57:18.342799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:18.515982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 156
100.0%

관리번호
Text

UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:57:18.805707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3432
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

Unique156 ?
Unique (%)100.0%

Sample

1st row3150000-202-1968-00021
2nd row3150000-202-1968-00022
3rd row3150000-202-1969-00023
4th row3150000-202-1970-00016
5th row3150000-202-1971-00029
ValueCountFrequency (%)
3150000-202-1968-00021 1
 
0.6%
3150000-202-2003-00006 1
 
0.6%
3150000-202-2005-00001 1
 
0.6%
3150000-202-2002-00006 1
 
0.6%
3150000-202-2003-00001 1
 
0.6%
3150000-202-2003-00002 1
 
0.6%
3150000-202-2003-00003 1
 
0.6%
3150000-202-2003-00004 1
 
0.6%
3150000-202-2003-00005 1
 
0.6%
3150000-202-2003-00008 1
 
0.6%
Other values (146) 146
93.6%
2024-05-11T15:57:19.318579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1537
44.8%
2 471
 
13.7%
- 468
 
13.6%
1 316
 
9.2%
3 205
 
6.0%
5 178
 
5.2%
9 143
 
4.2%
8 39
 
1.1%
4 31
 
0.9%
6 23
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2964
86.4%
Dash Punctuation 468
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1537
51.9%
2 471
 
15.9%
1 316
 
10.7%
3 205
 
6.9%
5 178
 
6.0%
9 143
 
4.8%
8 39
 
1.3%
4 31
 
1.0%
6 23
 
0.8%
7 21
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 468
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1537
44.8%
2 471
 
13.7%
- 468
 
13.6%
1 316
 
9.2%
3 205
 
6.0%
5 178
 
5.2%
9 143
 
4.2%
8 39
 
1.1%
4 31
 
0.9%
6 23
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1537
44.8%
2 471
 
13.7%
- 468
 
13.6%
1 316
 
9.2%
3 205
 
6.0%
5 178
 
5.2%
9 143
 
4.2%
8 39
 
1.1%
4 31
 
0.9%
6 23
 
0.7%

인허가일자
Date

Distinct145
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1968-11-15 00:00:00
Maximum2024-03-20 00:00:00
2024-05-11T15:57:19.536979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:19.766084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
116 
1
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 116
74.4%
1 40
 
25.6%

Length

2024-05-11T15:57:19.985712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:20.154427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 116
74.4%
1 40
 
25.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
116 
영업/정상
40 

Length

Max length5
Median length2
Mean length2.7692308
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 116
74.4%
영업/정상 40
 
25.6%

Length

2024-05-11T15:57:20.365521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:20.586818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
74.4%
영업/정상 40
 
25.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
116 
1
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 116
74.4%
1 40
 
25.6%

Length

2024-05-11T15:57:20.752425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:20.898881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 116
74.4%
1 40
 
25.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
116 
영업
40 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 116
74.4%
영업 40
 
25.6%

Length

2024-05-11T15:57:21.054384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:21.218068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
74.4%
영업 40
 
25.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)96.6%
Missing40
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean20089510
Minimum20000731
Maximum20221109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:21.739737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000731
5-th percentile20010901
Q120040604
median20070861
Q320130877
95-th percentile20210156
Maximum20221109
Range220378
Interquartile range (IQR)90272.75

Descriptive statistics

Standard deviation62304.07
Coefficient of variation (CV)0.0031013235
Kurtosis-0.64548737
Mean20089510
Median Absolute Deviation (MAD)40192.5
Skewness0.67233932
Sum2.3303832 × 109
Variance3.8817972 × 109
MonotonicityNot monotonic
2024-05-11T15:57:21.967079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080114 2
 
1.3%
20080204 2
 
1.3%
20060526 2
 
1.3%
20020318 2
 
1.3%
20020305 1
 
0.6%
20061213 1
 
0.6%
20080102 1
 
0.6%
20090922 1
 
0.6%
20040427 1
 
0.6%
20070719 1
 
0.6%
Other values (102) 102
65.4%
(Missing) 40
 
25.6%
ValueCountFrequency (%)
20000731 1
0.6%
20000816 1
0.6%
20010321 1
0.6%
20010401 1
0.6%
20010625 1
0.6%
20010830 1
0.6%
20010925 1
0.6%
20011203 1
0.6%
20011226 1
0.6%
20020305 1
0.6%
ValueCountFrequency (%)
20221109 1
0.6%
20220824 1
0.6%
20220616 1
0.6%
20220111 1
0.6%
20210607 1
0.6%
20210302 1
0.6%
20210107 1
0.6%
20201015 1
0.6%
20201012 1
0.6%
20200903 1
0.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct145
Distinct (%)98.0%
Missing8
Missing (%)5.1%
Memory size1.3 KiB
2024-05-11T15:57:22.348752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.195946
Min length10

Characters and Unicode

Total characters1509
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

Unique142 ?
Unique (%)95.9%

Sample

1st row02 6933731
2nd row0226022936
3rd row0226944096
4th row0226635775
5th row0226648119
ValueCountFrequency (%)
02 31
 
17.3%
0226916797 2
 
1.1%
0236637832 2
 
1.1%
0226622809 2
 
1.1%
0236659015 1
 
0.6%
0236620022 1
 
0.6%
36642977 1
 
0.6%
6933731 1
 
0.6%
6969325 1
 
0.6%
0236618451 1
 
0.6%
Other values (136) 136
76.0%
2024-05-11T15:57:23.009033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 333
22.1%
6 275
18.2%
0 272
18.0%
3 120
 
8.0%
5 99
 
6.6%
9 88
 
5.8%
1 76
 
5.0%
4 72
 
4.8%
7 66
 
4.4%
8 64
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1465
97.1%
Space Separator 44
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 333
22.7%
6 275
18.8%
0 272
18.6%
3 120
 
8.2%
5 99
 
6.8%
9 88
 
6.0%
1 76
 
5.2%
4 72
 
4.9%
7 66
 
4.5%
8 64
 
4.4%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1509
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 333
22.1%
6 275
18.2%
0 272
18.0%
3 120
 
8.0%
5 99
 
6.6%
9 88
 
5.8%
1 76
 
5.0%
4 72
 
4.8%
7 66
 
4.4%
8 64
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 333
22.1%
6 275
18.2%
0 272
18.0%
3 120
 
8.0%
5 99
 
6.6%
9 88
 
5.8%
1 76
 
5.0%
4 72
 
4.8%
7 66
 
4.4%
8 64
 
4.2%

소재지면적
Text

Distinct147
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:57:23.503693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.224359
Min length3

Characters and Unicode

Total characters971
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

Unique138 ?
Unique (%)88.5%

Sample

1st row68.46
2nd row56.70
3rd row173.00
4th row330.00
5th row389.00
ValueCountFrequency (%)
145.92 2
 
1.3%
1,721.00 2
 
1.3%
321.54 2
 
1.3%
990.00 2
 
1.3%
523.86 2
 
1.3%
140.47 2
 
1.3%
573.86 2
 
1.3%
425.70 2
 
1.3%
311.34 2
 
1.3%
228.33 1
 
0.6%
Other values (137) 137
87.8%
2024-05-11T15:57:24.315165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 156
16.1%
0 113
11.6%
2 103
10.6%
1 93
9.6%
6 88
9.1%
3 79
8.1%
8 69
7.1%
5 65
6.7%
4 63
6.5%
9 61
 
6.3%
Other values (2) 81
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 794
81.8%
Other Punctuation 177
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 113
14.2%
2 103
13.0%
1 93
11.7%
6 88
11.1%
3 79
9.9%
8 69
8.7%
5 65
8.2%
4 63
7.9%
9 61
7.7%
7 60
7.6%
Other Punctuation
ValueCountFrequency (%)
. 156
88.1%
, 21
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Common 971
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 156
16.1%
0 113
11.6%
2 103
10.6%
1 93
9.6%
6 88
9.1%
3 79
8.1%
8 69
7.1%
5 65
6.7%
4 63
6.5%
9 61
 
6.3%
Other values (2) 81
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 971
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 156
16.1%
0 113
11.6%
2 103
10.6%
1 93
9.6%
6 88
9.1%
3 79
8.1%
8 69
7.1%
5 65
6.7%
4 63
6.5%
9 61
 
6.3%
Other values (2) 81
8.3%

소재지우편번호
Text

Distinct77
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:57:24.732497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0897436
Min length6

Characters and Unicode

Total characters950
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 (%)22.4%

Sample

1st row157866
2nd row157872
3rd row157-884
4th row157240
5th row157852
ValueCountFrequency (%)
157930 8
 
5.1%
157928 5
 
3.2%
157910 5
 
3.2%
157862 5
 
3.2%
157904 4
 
2.6%
157-210 4
 
2.6%
157853 4
 
2.6%
157846 4
 
2.6%
157863 4
 
2.6%
157847 4
 
2.6%
Other values (67) 109
69.9%
2024-05-11T15:57:25.368541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 206
21.7%
5 182
19.2%
7 178
18.7%
8 118
12.4%
9 61
 
6.4%
0 61
 
6.4%
2 39
 
4.1%
3 36
 
3.8%
6 31
 
3.3%
4 24
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
98.5%
Dash Punctuation 14
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 206
22.0%
5 182
19.4%
7 178
19.0%
8 118
12.6%
9 61
 
6.5%
0 61
 
6.5%
2 39
 
4.2%
3 36
 
3.8%
6 31
 
3.3%
4 24
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 206
21.7%
5 182
19.2%
7 178
18.7%
8 118
12.4%
9 61
 
6.4%
0 61
 
6.4%
2 39
 
4.1%
3 36
 
3.8%
6 31
 
3.3%
4 24
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 950
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 206
21.7%
5 182
19.2%
7 178
18.7%
8 118
12.4%
9 61
 
6.4%
0 61
 
6.4%
2 39
 
4.1%
3 36
 
3.8%
6 31
 
3.3%
4 24
 
2.5%

지번주소
Text

Distinct147
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:57:25.778877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length25.230769
Min length18

Characters and Unicode

Total characters3936
Distinct characters121
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)89.1%

Sample

1st row서울특별시 강서구 화곡동 24-242번지
2nd row서울특별시 강서구 화곡동 105-54번지
3rd row서울특별시 강서구 화곡동 362-44
4th row서울특별시 강서구 공항동 52-5번지 ,8
5th row서울특별시 강서구 방화동 609-56
ValueCountFrequency (%)
서울특별시 156
21.8%
강서구 156
21.8%
화곡동 67
 
9.3%
방화동 22
 
3.1%
등촌동 20
 
2.8%
염창동 15
 
2.1%
가양동 10
 
1.4%
내발산동 9
 
1.3%
공항동 8
 
1.1%
지하1층 8
 
1.1%
Other values (209) 246
34.3%
2024-05-11T15:57:26.423597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
691
17.6%
서 314
 
8.0%
1 178
 
4.5%
강 159
 
4.0%
동 158
 
4.0%
구 156
 
4.0%
울 156
 
4.0%
시 156
 
4.0%
특 156
 
4.0%
별 156
 
4.0%
Other values (111) 1656
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2240
56.9%
Decimal Number 818
 
20.8%
Space Separator 691
 
17.6%
Dash Punctuation 140
 
3.6%
Other Punctuation 21
 
0.5%
Close Punctuation 7
 
0.2%
Open Punctuation 7
 
0.2%
Uppercase Letter 6
 
0.2%
Letter Number 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 314
14.0%
강 159
 
7.1%
동 158
 
7.1%
구 156
 
7.0%
울 156
 
7.0%
시 156
 
7.0%
특 156
 
7.0%
별 156
 
7.0%
지 149
 
6.7%
번 119
 
5.3%
Other values (88) 561
25.0%
Decimal Number
ValueCountFrequency (%)
1 178
21.8%
2 105
12.8%
0 85
10.4%
3 76
9.3%
6 65
 
7.9%
4 64
 
7.8%
7 64
 
7.8%
9 61
 
7.5%
5 60
 
7.3%
8 60
 
7.3%
Other Punctuation
ValueCountFrequency (%)
, 15
71.4%
. 4
 
19.0%
@ 1
 
4.8%
/ 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
D 2
33.3%
Space Separator
ValueCountFrequency (%)
691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2240
56.9%
Common 1686
42.8%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 314
14.0%
강 159
 
7.1%
동 158
 
7.1%
구 156
 
7.0%
울 156
 
7.0%
시 156
 
7.0%
특 156
 
7.0%
별 156
 
7.0%
지 149
 
6.7%
번 119
 
5.3%
Other values (88) 561
25.0%
Common
ValueCountFrequency (%)
691
41.0%
1 178
 
10.6%
- 140
 
8.3%
2 105
 
6.2%
0 85
 
5.0%
3 76
 
4.5%
6 65
 
3.9%
4 64
 
3.8%
7 64
 
3.8%
9 61
 
3.6%
Other values (9) 157
 
9.3%
Latin
ValueCountFrequency (%)
B 4
40.0%
Ⅱ 2
20.0%
D 2
20.0%
a 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2240
56.9%
ASCII 1694
43.0%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
691
40.8%
1 178
 
10.5%
- 140
 
8.3%
2 105
 
6.2%
0 85
 
5.0%
3 76
 
4.5%
6 65
 
3.8%
4 64
 
3.8%
7 64
 
3.8%
9 61
 
3.6%
Other values (12) 165
 
9.7%
Hangul
ValueCountFrequency (%)
서 314
14.0%
강 159
 
7.1%
동 158
 
7.1%
구 156
 
7.0%
울 156
 
7.0%
시 156
 
7.0%
특 156
 
7.0%
별 156
 
7.0%
지 149
 
6.7%
번 119
 
5.3%
Other values (88) 561
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명주소
Text

MISSING 

Distinct74
Distinct (%)100.0%
Missing82
Missing (%)52.6%
Memory size1.3 KiB
2024-05-11T15:57:26.766429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length31.810811
Min length22

Characters and Unicode

Total characters2354
Distinct characters143
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row서울특별시 강서구 월정로30길 50, 1층 (화곡동)
2nd row서울특별시 강서구 방화대로21길 91 (방화동)
3rd row서울특별시 강서구 화곡로20길 33-3 (화곡동)
4th row서울특별시 강서구 방화동로 103 (방화동)
5th row서울특별시 강서구 강서로45나길 39 (내발산동)
ValueCountFrequency (%)
서울특별시 74
 
16.9%
강서구 74
 
16.9%
화곡동 21
 
4.8%
양천로 11
 
2.5%
방화동 11
 
2.5%
지하1층 9
 
2.1%
화곡로 7
 
1.6%
등촌동 7
 
1.6%
마곡동 5
 
1.1%
강서로 5
 
1.1%
Other values (180) 215
49.0%
2024-05-11T15:57:27.417752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
365
 
15.5%
서 161
 
6.8%
강 87
 
3.7%
1 84
 
3.6%
동 83
 
3.5%
( 78
 
3.3%
) 78
 
3.3%
시 74
 
3.1%
별 74
 
3.1%
울 74
 
3.1%
Other values (133) 1196
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1350
57.3%
Decimal Number 387
 
16.4%
Space Separator 365
 
15.5%
Open Punctuation 78
 
3.3%
Close Punctuation 78
 
3.3%
Other Punctuation 71
 
3.0%
Dash Punctuation 11
 
0.5%
Uppercase Letter 7
 
0.3%
Math Symbol 3
 
0.1%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 161
 
11.9%
강 87
 
6.4%
동 83
 
6.1%
시 74
 
5.5%
별 74
 
5.5%
울 74
 
5.5%
구 74
 
5.5%
특 74
 
5.5%
로 73
 
5.4%
화 66
 
4.9%
Other values (111) 510
37.8%
Decimal Number
ValueCountFrequency (%)
1 84
21.7%
3 61
15.8%
4 46
11.9%
2 46
11.9%
0 37
9.6%
5 32
 
8.3%
7 27
 
7.0%
9 21
 
5.4%
6 20
 
5.2%
8 13
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 69
97.2%
. 1
 
1.4%
/ 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
71.4%
D 2
 
28.6%
Space Separator
ValueCountFrequency (%)
365
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1350
57.3%
Common 993
42.2%
Latin 11
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 161
 
11.9%
강 87
 
6.4%
동 83
 
6.1%
시 74
 
5.5%
별 74
 
5.5%
울 74
 
5.5%
구 74
 
5.5%
특 74
 
5.5%
로 73
 
5.4%
화 66
 
4.9%
Other values (111) 510
37.8%
Common
ValueCountFrequency (%)
365
36.8%
1 84
 
8.5%
( 78
 
7.9%
) 78
 
7.9%
, 69
 
6.9%
3 61
 
6.1%
4 46
 
4.6%
2 46
 
4.6%
0 37
 
3.7%
5 32
 
3.2%
Other values (8) 97
 
9.8%
Latin
ValueCountFrequency (%)
B 5
45.5%
D 2
 
18.2%
Ⅱ 2
 
18.2%
a 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1350
57.3%
ASCII 1002
42.6%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
365
36.4%
1 84
 
8.4%
( 78
 
7.8%
) 78
 
7.8%
, 69
 
6.9%
3 61
 
6.1%
4 46
 
4.6%
2 46
 
4.6%
0 37
 
3.7%
5 32
 
3.2%
Other values (11) 106
 
10.6%
Hangul
ValueCountFrequency (%)
서 161
 
11.9%
강 87
 
6.4%
동 83
 
6.1%
시 74
 
5.5%
별 74
 
5.5%
울 74
 
5.5%
구 74
 
5.5%
특 74
 
5.5%
로 73
 
5.4%
화 66
 
4.9%
Other values (111) 510
37.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)79.2%
Missing84
Missing (%)53.8%
Infinite0
Infinite (%)0.0%
Mean7645.5972
Minimum7505
Maximum7807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:27.671250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7505
5-th percentile7524.65
Q17573
median7647.5
Q37711.25
95-th percentile7792.5
Maximum7807
Range302
Interquartile range (IQR)138.25

Descriptive statistics

Standard deviation86.78136
Coefficient of variation (CV)0.011350501
Kurtosis-1.0094569
Mean7645.5972
Median Absolute Deviation (MAD)70
Skewness0.23988767
Sum550483
Variance7531.0045
MonotonicityNot monotonic
2024-05-11T15:57:27.923048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7663 4
 
2.6%
7539 4
 
2.6%
7604 3
 
1.9%
7694 2
 
1.3%
7777 2
 
1.3%
7573 2
 
1.3%
7649 2
 
1.3%
7590 2
 
1.3%
7621 2
 
1.3%
7653 2
 
1.3%
Other values (47) 47
30.1%
(Missing) 84
53.8%
ValueCountFrequency (%)
7505 1
 
0.6%
7511 1
 
0.6%
7516 1
 
0.6%
7523 1
 
0.6%
7526 1
 
0.6%
7528 1
 
0.6%
7531 1
 
0.6%
7539 4
2.6%
7542 1
 
0.6%
7549 1
 
0.6%
ValueCountFrequency (%)
7807 1
0.6%
7803 1
0.6%
7802 1
0.6%
7798 1
0.6%
7788 1
0.6%
7787 1
0.6%
7777 2
1.3%
7776 1
0.6%
7767 1
0.6%
7765 1
0.6%

사업장명
Text

Distinct145
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T15:57:28.456037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.1666667
Min length2

Characters and Unicode

Total characters806
Distinct characters192
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

Unique136 ?
Unique (%)87.2%

Sample

1st row금천탕
2nd row화곡탕
3rd row대호
4th row송정
5th row국제
ValueCountFrequency (%)
사우나 5
 
2.8%
수정 4
 
2.2%
천지연사우나 2
 
1.1%
빠제로 2
 
1.1%
세신샵 2
 
1.1%
스파 2
 
1.1%
신라 2
 
1.1%
쇼골프 2
 
1.1%
세종목욕탕 2
 
1.1%
삼성 2
 
1.1%
Other values (149) 153
86.0%
2024-05-11T15:57:29.138420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 53
 
6.6%
사 51
 
6.3%
우 50
 
6.2%
탕 26
 
3.2%
22
 
2.7%
대 21
 
2.6%
성 18
 
2.2%
수 16
 
2.0%
가 16
 
2.0%
스 16
 
2.0%
Other values (182) 517
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 746
92.6%
Space Separator 22
 
2.7%
Decimal Number 13
 
1.6%
Uppercase Letter 12
 
1.5%
Other Punctuation 7
 
0.9%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 53
 
7.1%
사 51
 
6.8%
우 50
 
6.7%
탕 26
 
3.5%
대 21
 
2.8%
성 18
 
2.4%
수 16
 
2.1%
가 16
 
2.1%
스 16
 
2.1%
욕 15
 
2.0%
Other values (163) 464
62.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
16.7%
M 2
16.7%
N 1
8.3%
K 1
8.3%
S 1
8.3%
E 1
8.3%
O 1
8.3%
H 1
8.3%
P 1
8.3%
V 1
8.3%
Decimal Number
ValueCountFrequency (%)
4 5
38.5%
2 5
38.5%
5 2
 
15.4%
9 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
& 3
42.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 746
92.6%
Common 48
 
6.0%
Latin 12
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 53
 
7.1%
사 51
 
6.8%
우 50
 
6.7%
탕 26
 
3.5%
대 21
 
2.8%
성 18
 
2.4%
수 16
 
2.1%
가 16
 
2.1%
스 16
 
2.1%
욕 15
 
2.0%
Other values (163) 464
62.2%
Latin
ValueCountFrequency (%)
I 2
16.7%
M 2
16.7%
N 1
8.3%
K 1
8.3%
S 1
8.3%
E 1
8.3%
O 1
8.3%
H 1
8.3%
P 1
8.3%
V 1
8.3%
Common
ValueCountFrequency (%)
22
45.8%
4 5
 
10.4%
2 5
 
10.4%
. 4
 
8.3%
& 3
 
6.2%
) 3
 
6.2%
( 3
 
6.2%
5 2
 
4.2%
9 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 746
92.6%
ASCII 60
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 53
 
7.1%
사 51
 
6.8%
우 50
 
6.7%
탕 26
 
3.5%
대 21
 
2.8%
성 18
 
2.4%
수 16
 
2.1%
가 16
 
2.1%
스 16
 
2.1%
욕 15
 
2.0%
Other values (163) 464
62.2%
ASCII
ValueCountFrequency (%)
22
36.7%
4 5
 
8.3%
2 5
 
8.3%
. 4
 
6.7%
& 3
 
5.0%
) 3
 
5.0%
( 3
 
5.0%
I 2
 
3.3%
M 2
 
3.3%
5 2
 
3.3%
Other values (9) 9
15.0%

최종수정일자
Date

Distinct117
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2001-01-09 00:00:00
Maximum2024-04-15 17:13:04
2024-05-11T15:57:29.352594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:29.601254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
121 
U
35 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 121
77.6%
U 35
 
22.4%

Length

2024-05-11T15:57:29.847955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:29.998302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 121
77.6%
u 35
 
22.4%

데이터갱신일자
Categorical

IMBALANCE 

Distinct40
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2018-08-31 23:59:59.0
115 
2022-12-08 00:02:00.0
 
2
2021-10-31 23:07:00.0
 
2
2022-11-02 00:02:00.0
 
1
2022-01-13 02:40:00.0
 
1
Other values (35)
35 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique37 ?
Unique (%)23.7%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2022-12-08 00:02:00.0
4th row2018-08-31 23:59:59.0
5th row2020-10-14 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 115
73.7%
2022-12-08 00:02:00.0 2
 
1.3%
2021-10-31 23:07:00.0 2
 
1.3%
2022-11-02 00:02:00.0 1
 
0.6%
2022-01-13 02:40:00.0 1
 
0.6%
2022-10-31 22:02:00.0 1
 
0.6%
2021-12-05 23:08:00.0 1
 
0.6%
2020-10-14 02:40:00.0 1
 
0.6%
2020-06-27 02:40:00.0 1
 
0.6%
2022-01-05 02:40:00.0 1
 
0.6%
Other values (30) 30
 
19.2%

Length

2024-05-11T15:57:30.148825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 115
36.9%
23:59:59.0 115
36.9%
02:40:00.0 16
 
5.1%
00:02:00.0 5
 
1.6%
2021-10-31 4
 
1.3%
23:07:00.0 4
 
1.3%
23:00:00.0 2
 
0.6%
2022-12-05 2
 
0.6%
23:08:00.0 2
 
0.6%
2022-10-31 2
 
0.6%
Other values (42) 45
 
14.4%

업태구분명
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동탕업
112 
공동탕업+찜질시설서비스영업
30 
목욕장업 기타
 
6
한증막업
 
6
찜질시설서비스영업
 
2

Length

Max length14
Median length4
Mean length6.1025641
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 112
71.8%
공동탕업+찜질시설서비스영업 30
 
19.2%
목욕장업 기타 6
 
3.8%
한증막업 6
 
3.8%
찜질시설서비스영업 2
 
1.3%

Length

2024-05-11T15:57:30.336936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:30.494869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 112
69.1%
공동탕업+찜질시설서비스영업 30
 
18.5%
목욕장업 6
 
3.7%
기타 6
 
3.7%
한증막업 6
 
3.7%
찜질시설서비스영업 2
 
1.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct130
Distinct (%)86.1%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean185995.25
Minimum182895.67
Maximum189200.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:30.651842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182895.67
5-th percentile183242.41
Q1185356.78
median186249.44
Q3186886.56
95-th percentile188689.64
Maximum189200.15
Range6304.4792
Interquartile range (IQR)1529.7803

Descriptive statistics

Standard deviation1613.02
Coefficient of variation (CV)0.0086723722
Kurtosis-0.45361786
Mean185995.25
Median Absolute Deviation (MAD)834.66782
Skewness-0.25268047
Sum28085283
Variance2601833.7
MonotonicityNot monotonic
2024-05-11T15:57:30.833319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189200.147733153 4
 
2.6%
187137.650939893 3
 
1.9%
183306.751602566 3
 
1.9%
186299.74267687 3
 
1.9%
183269.526391991 2
 
1.3%
187710.471574269 2
 
1.3%
185920.509227929 2
 
1.3%
183846.102699972 2
 
1.3%
183382.861571856 2
 
1.3%
187084.103220523 2
 
1.3%
Other values (120) 126
80.8%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
182895.668483962 1
 
0.6%
183007.220061564 1
 
0.6%
183049.525160207 1
 
0.6%
183090.805509245 1
 
0.6%
183118.598958412 1
 
0.6%
183131.028798764 2
1.3%
183215.287450855 1
 
0.6%
183269.526391991 2
1.3%
183271.311495807 1
 
0.6%
183306.751602566 3
1.9%
ValueCountFrequency (%)
189200.147733153 4
2.6%
189156.529751731 1
 
0.6%
189098.806779959 1
 
0.6%
188843.428976776 1
 
0.6%
188766.438303493 1
 
0.6%
188612.842594632 1
 
0.6%
188474.213387955 1
 
0.6%
188429.042609254 1
 
0.6%
188387.609305559 1
 
0.6%
188320.272052969 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct130
Distinct (%)86.1%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean449961.49
Minimum447381.65
Maximum452817.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:31.023418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447381.65
5-th percentile447470.97
Q1448949.04
median449948.85
Q3451024.15
95-th percentile452293.46
Maximum452817.47
Range5435.8236
Interquartile range (IQR)2075.1031

Descriptive statistics

Standard deviation1449.2928
Coefficient of variation (CV)0.0032209263
Kurtosis-0.82907008
Mean449961.49
Median Absolute Deviation (MAD)1023.6256
Skewness-0.097552406
Sum67944186
Variance2100449.6
MonotonicityNot monotonic
2024-05-11T15:57:31.198908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449654.951038959 4
 
2.6%
447456.838723466 3
 
1.9%
452339.893234091 3
 
1.9%
450792.016505679 3
 
1.9%
450656.487430219 2
 
1.3%
451087.687651536 2
 
1.3%
452044.379121132 2
 
1.3%
452293.455519022 2
 
1.3%
452713.505241493 2
 
1.3%
451262.653397625 2
 
1.3%
Other values (120) 126
80.8%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
447381.645907113 1
 
0.6%
447406.124515211 2
1.3%
447456.838723466 3
1.9%
447459.491685718 1
 
0.6%
447468.836493019 1
 
0.6%
447473.094467874 1
 
0.6%
447538.027901623 1
 
0.6%
447558.373870105 1
 
0.6%
447606.137048609 1
 
0.6%
447718.495194045 1
 
0.6%
ValueCountFrequency (%)
452817.469477897 1
 
0.6%
452713.505241493 2
1.3%
452349.671029508 1
 
0.6%
452339.893234091 3
1.9%
452293.455519022 2
1.3%
452268.261985956 1
 
0.6%
452253.772178 1
 
0.6%
452244.734781694 2
1.3%
452044.379121132 2
1.3%
451983.994387909 1
 
0.6%

위생업태명
Categorical

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동탕업
106 
<NA>
23 
공동탕업+찜질시설서비스영업
21 
한증막업
 
3
목욕장업 기타
 
2

Length

Max length14
Median length4
Mean length5.4166667
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 106
67.9%
<NA> 23
 
14.7%
공동탕업+찜질시설서비스영업 21
 
13.5%
한증막업 3
 
1.9%
목욕장업 기타 2
 
1.3%
찜질시설서비스영업 1
 
0.6%

Length

2024-05-11T15:57:31.369894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:31.542724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 106
67.1%
na 23
 
14.6%
공동탕업+찜질시설서비스영업 21
 
13.3%
한증막업 3
 
1.9%
목욕장업 2
 
1.3%
기타 2
 
1.3%
찜질시설서비스영업 1
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)17.1%
Missing80
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean3.3289474
Minimum0
Maximum14
Zeros33
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:31.716147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q36
95-th percentile10.25
Maximum14
Range14
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.8031151
Coefficient of variation (CV)1.1424377
Kurtosis0.22452902
Mean3.3289474
Median Absolute Deviation (MAD)2.5
Skewness0.99672123
Sum253
Variance14.463684
MonotonicityNot monotonic
2024-05-11T15:57:31.897619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 33
21.2%
3 7
 
4.5%
6 6
 
3.8%
4 5
 
3.2%
7 5
 
3.2%
5 5
 
3.2%
9 4
 
2.6%
2 4
 
2.6%
14 2
 
1.3%
10 2
 
1.3%
Other values (3) 3
 
1.9%
(Missing) 80
51.3%
ValueCountFrequency (%)
0 33
21.2%
1 1
 
0.6%
2 4
 
2.6%
3 7
 
4.5%
4 5
 
3.2%
5 5
 
3.2%
6 6
 
3.8%
7 5
 
3.2%
9 4
 
2.6%
10 2
 
1.3%
ValueCountFrequency (%)
14 2
 
1.3%
12 1
 
0.6%
11 1
 
0.6%
10 2
 
1.3%
9 4
2.6%
7 5
3.2%
6 6
3.8%
5 5
3.2%
4 5
3.2%
3 7
4.5%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.9%
Missing80
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean1.0263158
Minimum0
Maximum5
Zeros34
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:32.108795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3364
Coefficient of variation (CV)1.3021333
Kurtosis1.4313656
Mean1.0263158
Median Absolute Deviation (MAD)1
Skewness1.4998796
Sum78
Variance1.7859649
MonotonicityNot monotonic
2024-05-11T15:57:32.267876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 34
21.8%
1 27
 
17.3%
4 5
 
3.2%
3 5
 
3.2%
2 3
 
1.9%
5 2
 
1.3%
(Missing) 80
51.3%
ValueCountFrequency (%)
0 34
21.8%
1 27
17.3%
2 3
 
1.9%
3 5
 
3.2%
4 5
 
3.2%
5 2
 
1.3%
ValueCountFrequency (%)
5 2
 
1.3%
4 5
 
3.2%
3 5
 
3.2%
2 3
 
1.9%
1 27
17.3%
0 34
21.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)14.8%
Missing102
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean1.5555556
Minimum0
Maximum15
Zeros26
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:32.404440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5377651
Coefficient of variation (CV)1.6314204
Kurtosis14.475274
Mean1.5555556
Median Absolute Deviation (MAD)1
Skewness3.2702509
Sum84
Variance6.4402516
MonotonicityNot monotonic
2024-05-11T15:57:32.528762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 26
 
16.7%
2 10
 
6.4%
1 7
 
4.5%
3 6
 
3.8%
6 2
 
1.3%
5 1
 
0.6%
7 1
 
0.6%
15 1
 
0.6%
(Missing) 102
65.4%
ValueCountFrequency (%)
0 26
16.7%
1 7
 
4.5%
2 10
 
6.4%
3 6
 
3.8%
5 1
 
0.6%
6 2
 
1.3%
7 1
 
0.6%
15 1
 
0.6%
ValueCountFrequency (%)
15 1
 
0.6%
7 1
 
0.6%
6 2
 
1.3%
5 1
 
0.6%
3 6
 
3.8%
2 10
 
6.4%
1 7
 
4.5%
0 26
16.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)25.0%
Missing124
Missing (%)79.5%
Infinite0
Infinite (%)0.0%
Mean2.3125
Minimum0
Maximum7
Zeros6
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:32.677776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5.45
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7121482
Coefficient of variation (CV)0.74038843
Kurtosis0.87195941
Mean2.3125
Median Absolute Deviation (MAD)1
Skewness0.71179994
Sum74
Variance2.9314516
MonotonicityNot monotonic
2024-05-11T15:57:32.812677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 9
 
5.8%
3 9
 
5.8%
0 6
 
3.8%
1 3
 
1.9%
4 2
 
1.3%
6 1
 
0.6%
5 1
 
0.6%
7 1
 
0.6%
(Missing) 124
79.5%
ValueCountFrequency (%)
0 6
3.8%
1 3
 
1.9%
2 9
5.8%
3 9
5.8%
4 2
 
1.3%
5 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
ValueCountFrequency (%)
7 1
 
0.6%
6 1
 
0.6%
5 1
 
0.6%
4 2
 
1.3%
3 9
5.8%
2 9
5.8%
1 3
 
1.9%
0 6
3.8%

사용시작지하층
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
101 
1
25 
0
24 
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length2.9423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 101
64.7%
1 25
 
16.0%
0 24
 
15.4%
2 4
 
2.6%
3 2
 
1.3%

Length

2024-05-11T15:57:32.971887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:33.109185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 101
64.7%
1 25
 
16.0%
0 24
 
15.4%
2 4
 
2.6%
3 2
 
1.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
123 
1
19 
0
 
7
2
 
5
3
 
2

Length

Max length4
Median length4
Mean length3.3653846
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> 123
78.8%
1 19
 
12.2%
0 7
 
4.5%
2 5
 
3.2%
3 2
 
1.3%

Length

2024-05-11T15:57:33.260521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:33.432110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
78.8%
1 19
 
12.2%
0 7
 
4.5%
2 5
 
3.2%
3 2
 
1.3%

한실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
111 
0
45 

Length

Max length4
Median length4
Mean length3.1346154
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 111
71.2%
0 45
28.8%

Length

2024-05-11T15:57:33.581705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:33.731119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 111
71.2%
0 45
28.8%

양실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
111 
0
45 

Length

Max length4
Median length4
Mean length3.1346154
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 111
71.2%
0 45
28.8%

Length

2024-05-11T15:57:33.877509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:34.048048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 111
71.2%
0 45
28.8%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)10.8%
Missing82
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean1.9324324
Minimum0
Maximum9
Zeros24
Zeros (%)15.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T15:57:34.183054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile8.35
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3660329
Coefficient of variation (CV)1.2243807
Kurtosis3.3261448
Mean1.9324324
Median Absolute Deviation (MAD)1
Skewness1.938677
Sum143
Variance5.5981118
MonotonicityNot monotonic
2024-05-11T15:57:34.366061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 32
 
20.5%
0 24
 
15.4%
1 8
 
5.1%
9 4
 
2.6%
6 2
 
1.3%
8 2
 
1.3%
3 1
 
0.6%
4 1
 
0.6%
(Missing) 82
52.6%
ValueCountFrequency (%)
0 24
15.4%
1 8
 
5.1%
2 32
20.5%
3 1
 
0.6%
4 1
 
0.6%
6 2
 
1.3%
8 2
 
1.3%
9 4
 
2.6%
ValueCountFrequency (%)
9 4
 
2.6%
8 2
 
1.3%
6 2
 
1.3%
4 1
 
0.6%
3 1
 
0.6%
2 32
20.5%
1 8
 
5.1%
0 24
15.4%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.5%
Missing23
Missing (%)14.7%
Memory size444.0 B
False
97 
True
36 
(Missing)
23 
ValueCountFrequency (%)
False 97
62.2%
True 36
 
23.1%
(Missing) 23
 
14.7%
2024-05-11T15:57:34.851883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
111 
0
45 

Length

Max length4
Median length4
Mean length3.1346154
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 111
71.2%
0 45
28.8%

Length

2024-05-11T15:57:35.000515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:35.141152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 111
71.2%
0 45
28.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
126 
임대
21 
자가
 
9

Length

Max length4
Median length4
Mean length3.6153846
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> 126
80.8%
임대 21
 
13.5%
자가 9
 
5.8%

Length

2024-05-11T15:57:35.300744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:35.459851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 126
80.8%
임대 21
 
13.5%
자가 9
 
5.8%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
131 
0
25 

Length

Max length4
Median length4
Mean length3.5192308
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> 131
84.0%
0 25
 
16.0%

Length

2024-05-11T15:57:35.605647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:35.759014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
84.0%
0 25
 
16.0%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
145 
0
 
11

Length

Max length4
Median length4
Mean length3.7884615
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
92.9%
0 11
 
7.1%

Length

2024-05-11T15:57:35.922179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:36.062508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
92.9%
0 11
 
7.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
145 
0
 
11

Length

Max length4
Median length4
Mean length3.7884615
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
92.9%
0 11
 
7.1%

Length

2024-05-11T15:57:36.216671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:36.362258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
92.9%
0 11
 
7.1%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
135 
0
21 

Length

Max length4
Median length4
Mean length3.5961538
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> 135
86.5%
0 21
 
13.5%

Length

2024-05-11T15:57:36.569838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:36.720318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 135
86.5%
0 21
 
13.5%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
137 
0
19 

Length

Max length4
Median length4
Mean length3.6346154
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> 137
87.8%
0 19
 
12.2%

Length

2024-05-11T15:57:36.872379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:37.039021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
87.8%
0 19
 
12.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing23
Missing (%)14.7%
Memory size444.0 B
False
133 
(Missing)
23 
ValueCountFrequency (%)
False 133
85.3%
(Missing) 23
 
14.7%
2024-05-11T15:57:37.163515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031500003150000-202-1968-0002119681126<NA>3폐업2폐업20020318<NA><NA><NA>02 693373168.46157866서울특별시 강서구 화곡동 24-242번지<NA><NA>금천탕2002-11-11 00:00:00I2018-08-31 23:59:59.0공동탕업186195.782437449145.546164공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131500003150000-202-1968-0002219681115<NA>3폐업2폐업20000731<NA><NA><NA>022602293656.70157872서울특별시 강서구 화곡동 105-54번지<NA><NA>화곡탕2001-01-09 00:00:00I2018-08-31 23:59:59.0공동탕업186113.318148448876.381049공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231500003150000-202-1969-000231969-09-29<NA>1영업/정상1영업<NA><NA><NA><NA>0226944096173.00157-884서울특별시 강서구 화곡동 362-44서울특별시 강서구 월정로30길 50, 1층 (화곡동)7767대호2023-07-31 17:07:02U2022-12-08 00:02:00.0공동탕업185672.108166448044.750632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331500003150000-202-1970-0001619701023<NA>3폐업2폐업20040427<NA><NA><NA>0226635775330.00157240서울특별시 강서구 공항동 52-5번지 ,8<NA><NA>송정2003-10-13 00:00:00I2018-08-31 23:59:59.0공동탕업183118.598958450884.384415공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431500003150000-202-1971-0002919710504<NA>3폐업2폐업20201012<NA><NA><NA>0226648119389.00157852서울특별시 강서구 방화동 609-56서울특별시 강서구 방화대로21길 91 (방화동)<NA>국제2020-10-12 18:25:37U2020-10-14 02:40:00.0공동탕업183271.311496451337.028488공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531500003150000-202-1974-0000119740115<NA>3폐업2폐업20120312<NA><NA><NA>0226026400314.44157925서울특별시 강서구 화곡동 1083-34번지서울특별시 강서구 화곡로20길 33-3 (화곡동)7717선화2004-11-26 00:00:00I2018-08-31 23:59:59.0공동탕업185501.937522448553.628789공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631500003150000-202-1975-0000119751231<NA>3폐업2폐업20020305<NA><NA><NA>0226052542152.42157928서울특별시 강서구 화곡동 1120-12번지<NA><NA>고운2002-06-12 00:00:00I2018-08-31 23:59:59.0공동탕업186844.416777450007.416348공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731500003150000-202-1976-0000119760525<NA>3폐업2폐업20140623<NA><NA><NA>0226645108329.67157851서울특별시 강서구 방화동 580-132번지서울특별시 강서구 방화동로 103 (방화동)<NA>동원목욕탕2010-12-15 11:23:15I2018-08-31 23:59:59.0공동탕업183439.032634452253.772178공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831500003150000-202-1979-0000119791001<NA>3폐업2폐업20010830<NA><NA><NA>0226020931186.26157886서울특별시 강서구 화곡동 398-19번지<NA><NA>수정2002-06-12 00:00:00I2018-08-31 23:59:59.0공동탕업186476.764914448046.544417공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931500003150000-202-1980-0001919801205<NA>3폐업2폐업20040420<NA><NA><NA>0226543422261.16157897서울특별시 강서구 화곡동 773-1번지<NA><NA>서울2004-02-06 00:00:00I2018-08-31 23:59:59.0공동탕업187789.193573448139.970458공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14631500003150000-202-2020-0000320200624<NA>3폐업2폐업20201015<NA><NA><NA><NA>145.92157853서울특별시 강서구 방화동 614-120 옥수탕서울특별시 강서구 개화동로25길 73, 옥수탕 1층 (방화동)7621옥수탕2020-10-15 17:09:14U2020-10-18 02:40:00.0공동탕업183131.028799451431.601811공동탕업3111<NA><NA>000N0<NA><NA><NA>자가00000N
14731500003150000-202-2020-0000420200907<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1,767.79157040서울특별시 강서구 염창동 310 아네스트염창 지하 3동 101,201호서울특별시 강서구 공항대로 593, 3동 지하층 101,101-1,201호 (염창동, 아네스트염창)7559무한사우나2020-09-17 17:07:49U2020-09-19 02:40:00.0공동탕업+찜질시설서비스영업<NA><NA>공동탕업+찜질시설서비스영업00<NA><NA>12002N0<NA><NA><NA><NA>00000N
14831500003150000-202-2021-0000120210325<NA>1영업/정상1영업<NA><NA><NA><NA>0236637832425.70157862서울특별시 강서구 염창동 259-2 나이아가라관광호텔 지하2층서울특별시 강서구 양천로 743, 나이아가라관광호텔 지하2층 (염창동)7539ONE(원)2022-11-07 16:28:25U2021-11-01 00:09:00.0공동탕업189200.147733449654.951039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14931500003150000-202-2021-0000220211019<NA>3폐업2폐업20220824<NA><NA><NA>0236659015428.10157210서울특별시 강서구 마곡동 794-1 우성에스비타워서울특별시 강서구 강서로 385, 우성에스비타워 1108~1110호 (마곡동)7803엠스타사우나2022-08-24 16:46:20U2021-12-07 22:06:00.0공동탕업+찜질시설서비스영업185660.0450884.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15031500003150000-202-2022-0000120220426<NA>1영업/정상1영업<NA><NA><NA><NA><NA>82.28157915서울특별시 강서구 화곡동 980-21 강서아이파크 312호서울특별시 강서구 화곡로 296, 3층 312호 (화곡동, 강서아이파크)7663세신샵 결2022-04-26 15:31:56I2021-12-03 22:08:00.0목욕장업 기타186594.265613449819.183931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15131500003150000-202-2023-000012023-06-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>67.41157-210서울특별시 강서구 마곡동 757-2 마곡나루역프라이빗타워Ⅱ 312호서울특별시 강서구 마곡중앙로 171, 마곡나루역프라이빗타워Ⅱ 3층 312호 (마곡동)7788스파 산2023-06-09 09:35:02I2022-12-05 23:01:00.0목욕장업 기타184715.451782451876.480698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15231500003150000-202-2023-000022023-07-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.20157-210서울특별시 강서구 마곡동 798-6 류마타워Ⅱ, 308, 309호서울특별시 강서구 마곡중앙로 59-17, 류마타워Ⅱ 3층 308, 309호 (마곡동)7807세신샵 더퓨어2024-01-30 11:29:36U2023-12-02 00:02:00.0목욕장업 기타184448.542297450753.134593<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15331500003150000-202-2023-000032023-11-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>138.14157-915서울특별시 강서구 화곡동 982-3서울특별시 강서구 화곡로44가길 39, 지하1층 (화곡동)7663밀다2023-11-27 14:43:37I2022-10-31 22:09:00.0목욕장업 기타186522.329925449713.968972<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15431500003150000-202-2024-000012024-01-08<NA>1영업/정상1영업<NA><NA><NA><NA>0226660054746.86157-210서울특별시 강서구 마곡동 743-4 마곡엠밸리7단지서울특별시 강서구 마곡서로 133, 704동 101-1,101-2호 (마곡동, 마곡엠밸리7단지)7798엠스타2024-01-08 17:31:49I2023-11-30 23:00:00.0한증막업184333.032124451471.100985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15531500003150000-202-2024-000022024-03-20<NA>1영업/정상1영업<NA><NA><NA><NA>07043672908344.00157-937서울특별시 강서구 내발산동 750-9 웨스트엔드문화센터 901호서울특별시 강서구 수명로 68-27, 웨스트엔드문화센터 901호 (내발산동)7635에이블짐 휘트니스2024-04-03 14:30:24U2023-12-04 00:05:00.0찜질시설서비스영업184615.262499450059.812591<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>