Overview

Dataset statistics

Number of variables47
Number of observations125
Missing cells1287
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.6 KiB
Average record size in memory406.1 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-19958/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신일자 is highly imbalanced (62.9%)Imbalance
업태구분명 is highly imbalanced (60.9%)Imbalance
위생업태명 is highly imbalanced (57.3%)Imbalance
사용끝지하층 is highly imbalanced (63.3%)Imbalance
발한실여부 is highly imbalanced (74.9%)Imbalance
건물소유구분명 is highly imbalanced (80.5%)Imbalance
여성종사자수 is highly imbalanced (83.7%)Imbalance
남성종사자수 is highly imbalanced (83.7%)Imbalance
회수건조수 is highly imbalanced (62.7%)Imbalance
침대수 is highly imbalanced (65.7%)Imbalance
인허가취소일자 has 125 (100.0%) missing valuesMissing
폐업일자 has 19 (15.2%) missing valuesMissing
휴업시작일자 has 125 (100.0%) missing valuesMissing
휴업종료일자 has 125 (100.0%) missing valuesMissing
재개업일자 has 125 (100.0%) missing valuesMissing
전화번호 has 4 (3.2%) missing valuesMissing
도로명주소 has 88 (70.4%) missing valuesMissing
도로명우편번호 has 89 (71.2%) missing valuesMissing
좌표정보(X) has 8 (6.4%) missing valuesMissing
좌표정보(Y) has 8 (6.4%) missing valuesMissing
건물지상층수 has 39 (31.2%) missing valuesMissing
사용시작지상층 has 43 (34.4%) missing valuesMissing
사용끝지상층 has 102 (81.6%) missing valuesMissing
발한실여부 has 6 (4.8%) missing valuesMissing
조건부허가신고사유 has 125 (100.0%) missing valuesMissing
조건부허가시작일자 has 125 (100.0%) missing valuesMissing
조건부허가종료일자 has 125 (100.0%) missing valuesMissing
다중이용업소여부 has 6 (4.8%) 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 79 (63.2%) zerosZeros
사용시작지상층 has 67 (53.6%) zerosZeros
사용끝지상층 has 8 (6.4%) zerosZeros

Reproduction

Analysis started2024-04-29 20:03:57.623910
Analysis finished2024-04-29 20:03:58.384148
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3060000
125 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 125
100.0%

Length

2024-04-30T05:03:58.444430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:58.519293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 125
100.0%

관리번호
Text

UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-30T05:03:58.659466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2750
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

Unique125 ?
Unique (%)100.0%

Sample

1st row3060000-202-1969-00227
2nd row3060000-202-1969-00228
3rd row3060000-202-1970-00203
4th row3060000-202-1970-00267
5th row3060000-202-1971-00196
ValueCountFrequency (%)
3060000-202-1969-00227 1
 
0.8%
3060000-202-1988-00266 1
 
0.8%
3060000-202-1997-00281 1
 
0.8%
3060000-202-1997-00280 1
 
0.8%
3060000-202-1997-00279 1
 
0.8%
3060000-202-1996-00279 1
 
0.8%
3060000-202-1996-00278 1
 
0.8%
3060000-202-1996-00276 1
 
0.8%
3060000-202-1996-00271 1
 
0.8%
3060000-202-1996-00234 1
 
0.8%
Other values (115) 115
92.0%
2024-04-30T05:03:58.931263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1122
40.8%
2 414
 
15.1%
- 375
 
13.6%
3 168
 
6.1%
6 159
 
5.8%
1 158
 
5.7%
9 155
 
5.6%
8 77
 
2.8%
7 54
 
2.0%
4 41
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2375
86.4%
Dash Punctuation 375
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1122
47.2%
2 414
 
17.4%
3 168
 
7.1%
6 159
 
6.7%
1 158
 
6.7%
9 155
 
6.5%
8 77
 
3.2%
7 54
 
2.3%
4 41
 
1.7%
5 27
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 375
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2750
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1122
40.8%
2 414
 
15.1%
- 375
 
13.6%
3 168
 
6.1%
6 159
 
5.8%
1 158
 
5.7%
9 155
 
5.6%
8 77
 
2.8%
7 54
 
2.0%
4 41
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1122
40.8%
2 414
 
15.1%
- 375
 
13.6%
3 168
 
6.1%
6 159
 
5.8%
1 158
 
5.7%
9 155
 
5.6%
8 77
 
2.8%
7 54
 
2.0%
4 41
 
1.5%
Distinct117
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1969-12-05 00:00:00
Maximum2018-03-05 00:00:00
2024-04-30T05:03:59.057910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:03:59.175544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB
Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
106 
1
19 

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 (%)
3 106
84.8%
1 19
 
15.2%

Length

2024-04-30T05:03:59.296431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:59.388791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 106
84.8%
1 19
 
15.2%

영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
106 
영업/정상
19 

Length

Max length5
Median length2
Mean length2.456
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 106
84.8%
영업/정상 19
 
15.2%

Length

2024-04-30T05:03:59.483141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:59.563022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 106
84.8%
영업/정상 19
 
15.2%
Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2
106 
1
19 

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 (%)
2 106
84.8%
1 19
 
15.2%

Length

2024-04-30T05:03:59.663636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:59.735716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 106
84.8%
1 19
 
15.2%
Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
106 
영업
19 

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 106
84.8%
영업 19
 
15.2%

Length

2024-04-30T05:03:59.810264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:03:59.889747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 106
84.8%
영업 19
 
15.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)95.3%
Missing19
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean20052705
Minimum19940111
Maximum20221020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:03:59.984492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940111
5-th percentile19950385
Q120000539
median20040266
Q320091209
95-th percentile20198296
Maximum20221020
Range280909
Interquartile range (IQR)90669.5

Descriptive statistics

Standard deviation76549.991
Coefficient of variation (CV)0.0038174397
Kurtosis-0.56224834
Mean20052705
Median Absolute Deviation (MAD)50250
Skewness0.61485986
Sum2.1255867 × 109
Variance5.8599012 × 109
MonotonicityNot monotonic
2024-04-30T05:04:00.116313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021209 2
 
1.6%
19940510 2
 
1.6%
20000630 2
 
1.6%
20030130 2
 
1.6%
19970603 2
 
1.6%
19970410 1
 
0.8%
20070530 1
 
0.8%
20020430 1
 
0.8%
20130620 1
 
0.8%
20150826 1
 
0.8%
Other values (91) 91
72.8%
(Missing) 19
 
15.2%
ValueCountFrequency (%)
19940111 1
0.8%
19940411 1
0.8%
19940425 1
0.8%
19940510 2
1.6%
19950313 1
0.8%
19950602 1
0.8%
19960318 1
0.8%
19960319 1
0.8%
19960514 1
0.8%
19970224 1
0.8%
ValueCountFrequency (%)
20221020 1
0.8%
20211224 1
0.8%
20211014 1
0.8%
20210222 1
0.8%
20201012 1
0.8%
20200722 1
0.8%
20191017 1
0.8%
20190630 1
0.8%
20190617 1
0.8%
20190502 1
0.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

전화번호
Text

MISSING 

Distinct113
Distinct (%)93.4%
Missing4
Missing (%)3.2%
Memory size1.1 KiB
2024-04-30T05:04:00.316499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8099174
Min length2

Characters and Unicode

Total characters1187
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

Unique105 ?
Unique (%)86.8%

Sample

1st row02
2nd row02 4347825
3rd row02 4340205
4th row0204344456
5th row02 4348573
ValueCountFrequency (%)
02 63
33.7%
0204956999 2
 
1.1%
4333841 2
 
1.1%
0204355346 2
 
1.1%
4362020 2
 
1.1%
4924727 2
 
1.1%
0204944571 2
 
1.1%
4950588 2
 
1.1%
02433 1
 
0.5%
0204325142 1
 
0.5%
Other values (108) 108
57.8%
2024-04-30T05:04:00.642106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
18.9%
2 200
16.8%
4 170
14.3%
3 119
10.0%
9 90
7.6%
5 74
 
6.2%
68
 
5.7%
7 65
 
5.5%
8 63
 
5.3%
1 60
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1119
94.3%
Space Separator 68
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
20.0%
2 200
17.9%
4 170
15.2%
3 119
10.6%
9 90
8.0%
5 74
 
6.6%
7 65
 
5.8%
8 63
 
5.6%
1 60
 
5.4%
6 54
 
4.8%
Space Separator
ValueCountFrequency (%)
68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
18.9%
2 200
16.8%
4 170
14.3%
3 119
10.0%
9 90
7.6%
5 74
 
6.2%
68
 
5.7%
7 65
 
5.5%
8 63
 
5.3%
1 60
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
18.9%
2 200
16.8%
4 170
14.3%
3 119
10.0%
9 90
7.6%
5 74
 
6.2%
68
 
5.7%
7 65
 
5.5%
8 63
 
5.3%
1 60
 
5.1%
Distinct122
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-30T05:04:00.917803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.232
Min length3

Characters and Unicode

Total characters779
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

Unique119 ?
Unique (%)95.2%

Sample

1st row176.94
2nd row181.79
3rd row140.62
4th row332.68
5th row220.72
ValueCountFrequency (%)
336.75 2
 
1.6%
1,573.56 2
 
1.6%
1,150.47 2
 
1.6%
231.00 1
 
0.8%
206.32 1
 
0.8%
740.85 1
 
0.8%
365.43 1
 
0.8%
709.05 1
 
0.8%
564.08 1
 
0.8%
495.69 1
 
0.8%
Other values (112) 112
89.6%
2024-04-30T05:04:01.297951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 125
16.0%
0 92
11.8%
1 79
10.1%
2 77
9.9%
3 67
8.6%
5 64
8.2%
4 64
8.2%
6 63
8.1%
8 47
 
6.0%
7 45
 
5.8%
Other values (2) 56
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 638
81.9%
Other Punctuation 141
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
14.4%
1 79
12.4%
2 77
12.1%
3 67
10.5%
5 64
10.0%
4 64
10.0%
6 63
9.9%
8 47
7.4%
7 45
7.1%
9 40
6.3%
Other Punctuation
ValueCountFrequency (%)
. 125
88.7%
, 16
 
11.3%

Most occurring scripts

ValueCountFrequency (%)
Common 779
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 125
16.0%
0 92
11.8%
1 79
10.1%
2 77
9.9%
3 67
8.6%
5 64
8.2%
4 64
8.2%
6 63
8.1%
8 47
 
6.0%
7 45
 
5.8%
Other values (2) 56
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 779
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 125
16.0%
0 92
11.8%
1 79
10.1%
2 77
9.9%
3 67
8.6%
5 64
8.2%
4 64
8.2%
6 63
8.1%
8 47
 
6.0%
7 45
 
5.8%
Other values (2) 56
7.2%
Distinct60
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-30T05:04:01.506294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.016
Min length6

Characters and Unicode

Total characters752
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

Unique27 ?
Unique (%)21.6%

Sample

1st row131859
2nd row131860
3rd row131816
4th row131809
5th row131824
ValueCountFrequency (%)
131809 6
 
4.8%
131878 5
 
4.0%
131802 5
 
4.0%
131848 5
 
4.0%
131859 4
 
3.2%
131877 4
 
3.2%
131831 4
 
3.2%
131860 4
 
3.2%
131815 4
 
3.2%
131852 3
 
2.4%
Other values (50) 81
64.8%
2024-04-30T05:04:01.825094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 289
38.4%
8 144
19.1%
3 140
18.6%
0 37
 
4.9%
2 31
 
4.1%
7 28
 
3.7%
6 28
 
3.7%
5 23
 
3.1%
4 16
 
2.1%
9 14
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
99.7%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 289
38.5%
8 144
19.2%
3 140
18.7%
0 37
 
4.9%
2 31
 
4.1%
7 28
 
3.7%
6 28
 
3.7%
5 23
 
3.1%
4 16
 
2.1%
9 14
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 289
38.4%
8 144
19.1%
3 140
18.6%
0 37
 
4.9%
2 31
 
4.1%
7 28
 
3.7%
6 28
 
3.7%
5 23
 
3.1%
4 16
 
2.1%
9 14
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 289
38.4%
8 144
19.1%
3 140
18.6%
0 37
 
4.9%
2 31
 
4.1%
7 28
 
3.7%
6 28
 
3.7%
5 23
 
3.1%
4 16
 
2.1%
9 14
 
1.9%
Distinct118
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-30T05:04:02.050206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length33
Mean length22.784
Min length17

Characters and Unicode

Total characters2848
Distinct characters63
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)89.6%

Sample

1st row서울특별시 중랑구 상봉동 104-2번지
2nd row서울특별시 중랑구 상봉동 118-1번지
3rd row서울특별시 중랑구 면목동 101-12번지
4th row서울특별시 중랑구 망우동 494-2번지
5th row서울특별시 중랑구 면목동 191-78번지
ValueCountFrequency (%)
서울특별시 125
24.0%
중랑구 125
24.0%
면목동 44
 
8.4%
망우동 22
 
4.2%
중화동 17
 
3.3%
묵동 17
 
3.3%
상봉동 14
 
2.7%
신내동 11
 
2.1%
292-3번지 3
 
0.6%
지하1층 3
 
0.6%
Other values (134) 140
26.9%
2024-04-30T05:04:02.412596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
514
18.0%
142
 
5.0%
130
 
4.6%
125
 
4.4%
125
 
4.4%
125
 
4.4%
125
 
4.4%
125
 
4.4%
125
 
4.4%
125
 
4.4%
Other values (53) 1187
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1637
57.5%
Decimal Number 570
 
20.0%
Space Separator 514
 
18.0%
Dash Punctuation 114
 
4.0%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
142
 
8.7%
130
 
7.9%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
114
 
7.0%
Other values (36) 376
23.0%
Decimal Number
ValueCountFrequency (%)
1 117
20.5%
2 75
13.2%
3 62
10.9%
4 54
9.5%
5 50
8.8%
0 47
8.2%
7 45
 
7.9%
6 44
 
7.7%
8 43
 
7.5%
9 33
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
514
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1637
57.5%
Common 1211
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
142
 
8.7%
130
 
7.9%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
114
 
7.0%
Other values (36) 376
23.0%
Common
ValueCountFrequency (%)
514
42.4%
1 117
 
9.7%
- 114
 
9.4%
2 75
 
6.2%
3 62
 
5.1%
4 54
 
4.5%
5 50
 
4.1%
0 47
 
3.9%
7 45
 
3.7%
6 44
 
3.6%
Other values (7) 89
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1637
57.5%
ASCII 1211
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
514
42.4%
1 117
 
9.7%
- 114
 
9.4%
2 75
 
6.2%
3 62
 
5.1%
4 54
 
4.5%
5 50
 
4.1%
0 47
 
3.9%
7 45
 
3.7%
6 44
 
3.6%
Other values (7) 89
 
7.3%
Hangul
ValueCountFrequency (%)
142
 
8.7%
130
 
7.9%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
125
 
7.6%
114
 
7.0%
Other values (36) 376
23.0%

도로명주소
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing88
Missing (%)70.4%
Memory size1.1 KiB
2024-04-30T05:04:02.632506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length26.945946
Min length21

Characters and Unicode

Total characters997
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row서울특별시 중랑구 봉화산로3길 14 (중화동)
2nd row서울특별시 중랑구 중랑역로 192 (묵동)
3rd row서울특별시 중랑구 망우로 477 (망우동)
4th row서울특별시 중랑구 면목로64길 45 (면목동)
5th row서울특별시 중랑구 동일로 643 (면목동)
ValueCountFrequency (%)
서울특별시 37
19.0%
중랑구 37
19.0%
면목동 12
 
6.2%
중화동 6
 
3.1%
망우동 5
 
2.6%
중랑역로 4
 
2.1%
묵동 3
 
1.5%
신내동 3
 
1.5%
동일로 3
 
1.5%
상봉동 3
 
1.5%
Other values (75) 82
42.1%
2024-04-30T05:04:02.974890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
 
15.8%
52
 
5.2%
44
 
4.4%
43
 
4.3%
( 38
 
3.8%
) 38
 
3.8%
37
 
3.7%
37
 
3.7%
37
 
3.7%
37
 
3.7%
Other values (60) 476
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 611
61.3%
Space Separator 158
 
15.8%
Decimal Number 138
 
13.8%
Open Punctuation 38
 
3.8%
Close Punctuation 38
 
3.8%
Other Punctuation 13
 
1.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
8.5%
44
 
7.2%
43
 
7.0%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
Other values (44) 213
34.9%
Decimal Number
ValueCountFrequency (%)
1 33
23.9%
2 19
13.8%
3 16
11.6%
4 15
10.9%
0 12
 
8.7%
6 11
 
8.0%
5 9
 
6.5%
8 8
 
5.8%
7 8
 
5.8%
9 7
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 12
92.3%
. 1
 
7.7%
Space Separator
ValueCountFrequency (%)
158
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 611
61.3%
Common 386
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
8.5%
44
 
7.2%
43
 
7.0%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
Other values (44) 213
34.9%
Common
ValueCountFrequency (%)
158
40.9%
( 38
 
9.8%
) 38
 
9.8%
1 33
 
8.5%
2 19
 
4.9%
3 16
 
4.1%
4 15
 
3.9%
, 12
 
3.1%
0 12
 
3.1%
6 11
 
2.8%
Other values (6) 34
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 611
61.3%
ASCII 386
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
40.9%
( 38
 
9.8%
) 38
 
9.8%
1 33
 
8.5%
2 19
 
4.9%
3 16
 
4.1%
4 15
 
3.9%
, 12
 
3.1%
0 12
 
3.1%
6 11
 
2.8%
Other values (6) 34
 
8.8%
Hangul
ValueCountFrequency (%)
52
 
8.5%
44
 
7.2%
43
 
7.0%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
37
 
6.1%
Other values (44) 213
34.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)100.0%
Missing89
Missing (%)71.2%
Infinite0
Infinite (%)0.0%
Mean2114.0278
Minimum2006
Maximum2249
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:03.092877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2013
Q12065.5
median2115
Q32167.5
95-th percentile2237.75
Maximum2249
Range243
Interquartile range (IQR)102

Descriptive statistics

Standard deviation70.202355
Coefficient of variation (CV)0.033207868
Kurtosis-0.89453507
Mean2114.0278
Median Absolute Deviation (MAD)51.5
Skewness0.22854145
Sum76105
Variance4928.3706
MonotonicityNot monotonic
2024-04-30T05:04:03.205055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2240 1
 
0.8%
2091 1
 
0.8%
2162 1
 
0.8%
2119 1
 
0.8%
2203 1
 
0.8%
2176 1
 
0.8%
2117 1
 
0.8%
2068 1
 
0.8%
2167 1
 
0.8%
2169 1
 
0.8%
Other values (26) 26
 
20.8%
(Missing) 89
71.2%
ValueCountFrequency (%)
2006 1
0.8%
2010 1
0.8%
2014 1
0.8%
2016 1
0.8%
2024 1
0.8%
2033 1
0.8%
2036 1
0.8%
2051 1
0.8%
2064 1
0.8%
2066 1
0.8%
ValueCountFrequency (%)
2249 1
0.8%
2240 1
0.8%
2237 1
0.8%
2214 1
0.8%
2203 1
0.8%
2189 1
0.8%
2185 1
0.8%
2176 1
0.8%
2169 1
0.8%
2167 1
0.8%
Distinct115
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-30T05:04:03.488498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.144
Min length2

Characters and Unicode

Total characters518
Distinct characters116
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)84.0%

Sample

1st row성호탕
2nd row봉황탕
3rd row동천탕
4th row천우탕
5th row영진탕
ValueCountFrequency (%)
약수탕 2
 
1.6%
대도탕 2
 
1.6%
수정탕 2
 
1.6%
화원탕 2
 
1.6%
극동탕 2
 
1.6%
장미탕 2
 
1.6%
은성탕 2
 
1.6%
봉화산사우나 2
 
1.6%
상일탕 2
 
1.6%
양지탕 2
 
1.6%
Other values (105) 105
84.0%
2024-04-30T05:04:03.848378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
16.6%
31
 
6.0%
23
 
4.4%
22
 
4.2%
16
 
3.1%
16
 
3.1%
14
 
2.7%
12
 
2.3%
11
 
2.1%
10
 
1.9%
Other values (106) 277
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
99.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
16.7%
31
 
6.0%
23
 
4.5%
22
 
4.3%
16
 
3.1%
16
 
3.1%
14
 
2.7%
12
 
2.3%
11
 
2.1%
10
 
1.9%
Other values (104) 275
53.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
99.6%
Common 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
16.7%
31
 
6.0%
23
 
4.5%
22
 
4.3%
16
 
3.1%
16
 
3.1%
14
 
2.7%
12
 
2.3%
11
 
2.1%
10
 
1.9%
Other values (104) 275
53.3%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
99.6%
ASCII 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
86
 
16.7%
31
 
6.0%
23
 
4.5%
22
 
4.3%
16
 
3.1%
16
 
3.1%
14
 
2.7%
12
 
2.3%
11
 
2.1%
10
 
1.9%
Other values (104) 275
53.3%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%
Distinct91
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2000-09-20 00:00:00
Maximum2023-11-30 11:34:19
2024-04-30T05:04:03.964570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:04:04.090435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
I
98 
U
27 

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 98
78.4%
U 27
 
21.6%

Length

2024-04-30T05:04:04.203489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:04.292747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 98
78.4%
u 27
 
21.6%

데이터갱신일자
Categorical

IMBALANCE 

Distinct24
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2018-08-31 23:59:59.0
98 
2021-01-09 02:40:00.0
 
4
2021-01-22 02:40:00.0
 
2
2019-10-19 02:40:00.0
 
1
2021-12-04 22:05:00.0
 
1
Other values (19)
19 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique21 ?
Unique (%)16.8%

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 98
78.4%
2021-01-09 02:40:00.0 4
 
3.2%
2021-01-22 02:40:00.0 2
 
1.6%
2019-10-19 02:40:00.0 1
 
0.8%
2021-12-04 22:05:00.0 1
 
0.8%
2019-05-13 02:40:00.0 1
 
0.8%
2021-10-16 02:40:00.0 1
 
0.8%
2020-01-31 02:40:00.0 1
 
0.8%
2021-07-02 02:40:00.0 1
 
0.8%
2021-12-05 23:00:00.0 1
 
0.8%
Other values (14) 14
 
11.2%

Length

2024-04-30T05:04:04.382027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 98
39.2%
23:59:59.0 98
39.2%
02:40:00.0 21
 
8.4%
2021-01-09 4
 
1.6%
2021-01-22 2
 
0.8%
2021-11-01 1
 
0.4%
2021-10-30 1
 
0.4%
22:02:00.0 1
 
0.4%
2018-11-30 1
 
0.4%
2021-02-24 1
 
0.4%
Other values (22) 22
 
8.8%

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공동탕업
101 
공동탕업+찜질시설서비스영업
19 
목욕장업 기타
 
2
한증막업
 
2
찜질시설서비스영업
 
1

Length

Max length14
Median length4
Mean length5.608
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 101
80.8%
공동탕업+찜질시설서비스영업 19
 
15.2%
목욕장업 기타 2
 
1.6%
한증막업 2
 
1.6%
찜질시설서비스영업 1
 
0.8%

Length

2024-04-30T05:04:04.655013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:04.734563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 101
79.5%
공동탕업+찜질시설서비스영업 19
 
15.0%
목욕장업 2
 
1.6%
기타 2
 
1.6%
한증막업 2
 
1.6%
찜질시설서비스영업 1
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct102
Distinct (%)87.2%
Missing8
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean207631.02
Minimum206411.12
Maximum210012.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:04.848819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206411.12
5-th percentile206551.29
Q1206966.08
median207631.37
Q3208263.09
95-th percentile208949.7
Maximum210012.43
Range3601.309
Interquartile range (IQR)1297.0051

Descriptive statistics

Standard deviation798.63714
Coefficient of variation (CV)0.0038464249
Kurtosis-0.59721001
Mean207631.02
Median Absolute Deviation (MAD)663.72844
Skewness0.43836789
Sum24292830
Variance637821.27
MonotonicityNot monotonic
2024-04-30T05:04:04.965118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207136.222443825 3
 
2.4%
206764.330728385 2
 
1.6%
207116.730373469 2
 
1.6%
208949.703327608 2
 
1.6%
206814.61345332 2
 
1.6%
206492.087474895 2
 
1.6%
206966.083443672 2
 
1.6%
207464.387434306 2
 
1.6%
208243.910432602 2
 
1.6%
208112.860200669 2
 
1.6%
Other values (92) 96
76.8%
(Missing) 8
 
6.4%
ValueCountFrequency (%)
206411.123593498 2
1.6%
206463.443740034 1
0.8%
206492.087474895 2
1.6%
206495.0669016 1
0.8%
206565.340851053 1
0.8%
206595.707775401 1
0.8%
206643.557292629 1
0.8%
206655.021274777 1
0.8%
206661.03364855 1
0.8%
206665.562124786 1
0.8%
ValueCountFrequency (%)
210012.432600907 1
0.8%
209434.936710026 1
0.8%
209217.316962415 1
0.8%
209144.172317054 1
0.8%
209046.874952547 1
0.8%
208949.703327608 2
1.6%
208878.45773824 1
0.8%
208826.080479215 1
0.8%
208797.57815483 1
0.8%
208719.253338273 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct102
Distinct (%)87.2%
Missing8
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean454840.31
Minimum452403.93
Maximum457134.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:05.071574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452403.93
5-th percentile452944.13
Q1454120.41
median454810.44
Q3455546.12
95-th percentile456887.92
Maximum457134.65
Range4730.7267
Interquartile range (IQR)1425.7053

Descriptive statistics

Standard deviation1158.7106
Coefficient of variation (CV)0.0025475108
Kurtosis-0.53896533
Mean454840.31
Median Absolute Deviation (MAD)735.68124
Skewness0.024729216
Sum53216316
Variance1342610.2
MonotonicityNot monotonic
2024-04-30T05:04:05.178856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455229.538936769 3
 
2.4%
454711.739232552 2
 
1.6%
452792.451348479 2
 
1.6%
454810.437265163 2
 
1.6%
456135.882474094 2
 
1.6%
454508.605124002 2
 
1.6%
456693.746141199 2
 
1.6%
452980.036913527 2
 
1.6%
453913.946459696 2
 
1.6%
457113.638411288 2
 
1.6%
Other values (92) 96
76.8%
(Missing) 8
 
6.4%
ValueCountFrequency (%)
452403.92559767 1
0.8%
452413.605073678 1
0.8%
452646.861470708 1
0.8%
452792.451348479 2
1.6%
452896.697726472 1
0.8%
452955.98208017 1
0.8%
452980.036913527 2
1.6%
453059.327474458 1
0.8%
453155.928929722 2
1.6%
453196.34209616 1
0.8%
ValueCountFrequency (%)
457134.652291135 1
0.8%
457113.638411288 2
1.6%
457070.631526277 1
0.8%
457011.632629502 1
0.8%
457004.445188958 1
0.8%
456858.787878919 1
0.8%
456855.134478693 1
0.8%
456693.746141199 2
1.6%
456472.216329929 1
0.8%
456466.302841444 1
0.8%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공동탕업
97 
공동탕업+찜질시설서비스영업
18 
<NA>
 
6
한증막업
 
2
목욕장업 기타
 
1

Length

Max length14
Median length4
Mean length5.504
Min length4

Unique

Unique2 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 97
77.6%
공동탕업+찜질시설서비스영업 18
 
14.4%
<NA> 6
 
4.8%
한증막업 2
 
1.6%
목욕장업 기타 1
 
0.8%
찜질시설서비스영업 1
 
0.8%

Length

2024-04-30T05:04:05.354510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:05.494766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 97
77.0%
공동탕업+찜질시설서비스영업 18
 
14.3%
na 6
 
4.8%
한증막업 2
 
1.6%
목욕장업 1
 
0.8%
기타 1
 
0.8%
찜질시설서비스영업 1
 
0.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)8.1%
Missing39
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean0.60465116
Minimum0
Maximum18
Zeros79
Zeros (%)63.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:05.636055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.5
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5124587
Coefficient of variation (CV)4.1552202
Kurtosis30.197512
Mean0.60465116
Median Absolute Deviation (MAD)0
Skewness5.2050913
Sum52
Variance6.3124487
MonotonicityNot monotonic
2024-04-30T05:04:05.768951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 79
63.2%
5 2
 
1.6%
3 1
 
0.8%
2 1
 
0.8%
9 1
 
0.8%
10 1
 
0.8%
18 1
 
0.8%
(Missing) 39
31.2%
ValueCountFrequency (%)
0 79
63.2%
2 1
 
0.8%
3 1
 
0.8%
5 2
 
1.6%
9 1
 
0.8%
10 1
 
0.8%
18 1
 
0.8%
ValueCountFrequency (%)
18 1
 
0.8%
10 1
 
0.8%
9 1
 
0.8%
5 2
 
1.6%
3 1
 
0.8%
2 1
 
0.8%
0 79
63.2%
Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
76 
<NA>
39 
1
 
5
3
 
3
2
 
1

Length

Max length4
Median length1
Mean length1.936
Min length1

Unique

Unique2 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 76
60.8%
<NA> 39
31.2%
1 5
 
4.0%
3 3
 
2.4%
2 1
 
0.8%
4 1
 
0.8%

Length

2024-04-30T05:04:05.927443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:06.019464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 76
60.8%
na 39
31.2%
1 5
 
4.0%
3 3
 
2.4%
2 1
 
0.8%
4 1
 
0.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.3%
Missing43
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean0.5
Minimum0
Maximum10
Zeros67
Zeros (%)53.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:06.103269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4337209
Coefficient of variation (CV)2.8674418
Kurtosis24.254483
Mean0.5
Median Absolute Deviation (MAD)0
Skewness4.3925898
Sum41
Variance2.0555556
MonotonicityNot monotonic
2024-04-30T05:04:06.199030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 67
53.6%
1 5
 
4.0%
2 4
 
3.2%
4 3
 
2.4%
3 2
 
1.6%
10 1
 
0.8%
(Missing) 43
34.4%
ValueCountFrequency (%)
0 67
53.6%
1 5
 
4.0%
2 4
 
3.2%
3 2
 
1.6%
4 3
 
2.4%
10 1
 
0.8%
ValueCountFrequency (%)
10 1
 
0.8%
4 3
 
2.4%
3 2
 
1.6%
2 4
 
3.2%
1 5
 
4.0%
0 67
53.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)34.8%
Missing102
Missing (%)81.6%
Infinite0
Infinite (%)0.0%
Mean2.4347826
Minimum0
Maximum11
Zeros8
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-30T05:04:06.297200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33.5
95-th percentile5.9
Maximum11
Range11
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.6255058
Coefficient of variation (CV)1.0783327
Kurtosis3.9491988
Mean2.4347826
Median Absolute Deviation (MAD)2
Skewness1.6072544
Sum56
Variance6.8932806
MonotonicityNot monotonic
2024-04-30T05:04:06.390661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 8
 
6.4%
3 5
 
4.0%
4 3
 
2.4%
2 3
 
2.4%
5 1
 
0.8%
11 1
 
0.8%
6 1
 
0.8%
1 1
 
0.8%
(Missing) 102
81.6%
ValueCountFrequency (%)
0 8
6.4%
1 1
 
0.8%
2 3
 
2.4%
3 5
4.0%
4 3
 
2.4%
5 1
 
0.8%
6 1
 
0.8%
11 1
 
0.8%
ValueCountFrequency (%)
11 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
4 3
 
2.4%
3 5
4.0%
2 3
 
2.4%
1 1
 
0.8%
0 8
6.4%
Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
60 
<NA>
42 
1
22 
2
 
1

Length

Max length4
Median length1
Mean length2.008
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 60
48.0%
<NA> 42
33.6%
1 22
 
17.6%
2 1
 
0.8%

Length

2024-04-30T05:04:06.505836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:06.608911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 60
48.0%
na 42
33.6%
1 22
 
17.6%
2 1
 
0.8%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
101 
1
18 
2
 
3
0
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.44
Min length1

Unique

Unique3 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 101
80.8%
1 18
 
14.4%
2 3
 
2.4%
0 1
 
0.8%
3 1
 
0.8%
101 1
 
0.8%

Length

2024-04-30T05:04:06.709650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:06.809831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 101
80.8%
1 18
 
14.4%
2 3
 
2.4%
0 1
 
0.8%
3 1
 
0.8%
101 1
 
0.8%

한실수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
82 
<NA>
43 

Length

Max length4
Median length1
Mean length2.032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 82
65.6%
<NA> 43
34.4%

Length

2024-04-30T05:04:06.918351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.007766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 82
65.6%
na 43
34.4%

양실수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
82 
<NA>
43 

Length

Max length4
Median length1
Mean length2.032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 82
65.6%
<NA> 43
34.4%

Length

2024-04-30T05:04:07.090656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.171180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 82
65.6%
na 43
34.4%

욕실수
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
77 
<NA>
39 
2
 
6
1
 
3

Length

Max length4
Median length1
Mean length1.936
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 77
61.6%
<NA> 39
31.2%
2 6
 
4.8%
1 3
 
2.4%

Length

2024-04-30T05:04:07.261778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.362629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 77
61.6%
na 39
31.2%
2 6
 
4.8%
1 3
 
2.4%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.7%
Missing6
Missing (%)4.8%
Memory size382.0 B
False
114 
True
 
5
(Missing)
 
6
ValueCountFrequency (%)
False 114
91.2%
True 5
 
4.0%
(Missing) 6
 
4.8%
2024-04-30T05:04:07.445773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
82 
<NA>
43 

Length

Max length4
Median length1
Mean length2.032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 82
65.6%
<NA> 43
34.4%

Length

2024-04-30T05:04:07.529541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.610197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 82
65.6%
na 43
34.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing125
Missing (%)100.0%
Memory size1.2 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
119 
자가
 
5
임대
 
1

Length

Max length4
Median length4
Mean length3.904
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 119
95.2%
자가 5
 
4.0%
임대 1
 
0.8%

Length

2024-04-30T05:04:07.705828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.816709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 119
95.2%
자가 5
 
4.0%
임대 1
 
0.8%

세탁기수
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
98 
0
27 

Length

Max length4
Median length4
Mean length3.352
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> 98
78.4%
0 27
 
21.6%

Length

2024-04-30T05:04:07.908678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:07.991050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
78.4%
0 27
 
21.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
122 
0
 
3

Length

Max length4
Median length4
Mean length3.928
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> 122
97.6%
0 3
 
2.4%

Length

2024-04-30T05:04:08.082104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:08.181072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 122
97.6%
0 3
 
2.4%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
122 
0
 
3

Length

Max length4
Median length4
Mean length3.928
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> 122
97.6%
0 3
 
2.4%

Length

2024-04-30T05:04:08.269668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:08.365681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 122
97.6%
0 3
 
2.4%

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
116 
0
 
9

Length

Max length4
Median length4
Mean length3.784
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> 116
92.8%
0 9
 
7.2%

Length

2024-04-30T05:04:08.460320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:08.551438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 116
92.8%
0 9
 
7.2%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
117 
0
 
8

Length

Max length4
Median length4
Mean length3.808
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> 117
93.6%
0 8
 
6.4%

Length

2024-04-30T05:04:08.644698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:04:08.732777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
93.6%
0 8
 
6.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing6
Missing (%)4.8%
Memory size382.0 B
False
119 
(Missing)
 
6
ValueCountFrequency (%)
False 119
95.2%
(Missing) 6
 
4.8%
2024-04-30T05:04:08.796649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030600003060000-202-1969-0022719691205<NA>3폐업2폐업19990122<NA><NA><NA>02176.94131859서울특별시 중랑구 상봉동 104-2번지<NA><NA>성호탕2001-09-28 00:00:00I2018-08-31 23:59:59.0공동탕업207679.059029454769.274104공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130600003060000-202-1969-0022819691222<NA>3폐업2폐업19971013<NA><NA><NA>02 4347825181.79131860서울특별시 중랑구 상봉동 118-1번지<NA><NA>봉황탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업207235.533859454752.984582공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230600003060000-202-1970-0020319700821<NA>3폐업2폐업19960318<NA><NA><NA>02 4340205140.62131816서울특별시 중랑구 면목동 101-12번지<NA><NA>동천탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업207731.413062454120.413257공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330600003060000-202-1970-0026719700919<NA>3폐업2폐업20040610<NA><NA><NA>0204344456332.68131809서울특별시 중랑구 망우동 494-2번지<NA><NA>천우탕2004-06-10 00:00:00I2018-08-31 23:59:59.0공동탕업208362.862427455035.333237공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430600003060000-202-1971-0019619710809<NA>3폐업2폐업19970603<NA><NA><NA>02 4348573220.72131824서울특별시 중랑구 면목동 191-78번지<NA><NA>영진탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업206495.066902454142.433367공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530600003060000-202-1971-0024219711021<NA>3폐업2폐업20191017<NA><NA><NA>0204333885157.92131881서울특별시 중랑구 중화동 311-58번지서울특별시 중랑구 봉화산로3길 14 (중화동)2016대호탕2019-10-17 09:58:47U2019-10-19 02:40:00.0공동탕업206655.021275455546.118509공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
630600003060000-202-1972-0019419720921<NA>3폐업2폐업20160303<NA><NA><NA><NA>151.11131817서울특별시 중랑구 면목동 90-69번지<NA><NA>혜원탕2014-03-25 13:12:35I2018-08-31 23:59:59.0공동탕업207987.608799454570.904363공동탕업00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>0<NA><NA><NA><NA>N
730600003060000-202-1972-0024519720218<NA>3폐업2폐업20000420<NA><NA><NA>02 9734444213.26131850서울특별시 중랑구 묵동 188-5번지<NA><NA>덕원탕2000-09-20 00:00:00I2018-08-31 23:59:59.0공동탕업206898.416758455994.683562공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830600003060000-202-1973-0019219731207<NA>3폐업2폐업19970813<NA><NA><NA>02 4350746186.16131818서울특별시 중랑구 면목동 504-10번지<NA><NA>용강탕2001-10-04 00:00:00I2018-08-31 23:59:59.0공동탕업207691.56065453797.216875공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930600003060000-202-1973-0019319730925<NA>3폐업2폐업20031229<NA><NA><NA><NA>170.20131817서울특별시 중랑구 면목동 86-32번지<NA><NA>동원대중사우나2003-12-30 00:00:00I2018-08-31 23:59:59.0공동탕업208114.025699454228.239001공동탕업<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
11530600003060000-202-2005-0000120050129<NA>1영업/정상1영업<NA><NA><NA><NA>02 49182852,284.00131809서울특별시 중랑구 망우동 572번지 용마프라자2.3층서울특별시 중랑구 봉우재로71길 18 (망우동,용마프라자2.3층)2167우림해수찜사우나2017-03-27 14:55:29I2018-08-31 23:59:59.0공동탕업+찜질시설서비스영업208658.077733454894.79022공동탕업+찜질시설서비스영업<NA><NA>23<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11630600003060000-202-2005-0000220050414<NA>3폐업2폐업20061128<NA><NA><NA>02 4340430264.00131828서울특별시 중랑구 면목동 632-4번지<NA><NA>천호찜질방2006-09-13 00:00:00I2018-08-31 23:59:59.0찜질시설서비스영업<NA><NA>찜질시설서비스영업<NA><NA>33<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11730600003060000-202-2005-0000320050720<NA>1영업/정상1영업<NA><NA><NA><NA>02220985881,562.74131809서울특별시 중랑구 망우동 508-14 비01,비02서울특별시 중랑구 망우로58길 33-6 (망우동)2169해오름사우나2021-01-20 10:29:44U2021-01-22 02:40:00.0공동탕업+찜질시설서비스영업208262.201081454926.231547공동탕업+찜질시설서비스영업104<NA><NA>12<NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11830600003060000-202-2007-0000120070420<NA>1영업/정상1영업<NA><NA><NA><NA>02 9751783400.58131849서울특별시 중랑구 묵동 121-25번지서울특별시 중랑구 공릉로2나길 10 (묵동)2036장미탕2018-07-19 09:58:05I2018-08-31 23:59:59.0공동탕업206966.083444456693.746141공동탕업<NA><NA>1111<NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11930600003060000-202-2007-0000220071113<NA>3폐업2폐업20150803<NA><NA><NA>02 22080101440.65131814서울특별시 중랑구 면목동 62-4,5번지 지하1층<NA><NA>영스포츠클럽2012-10-25 09:56:40I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업01<NA><NA><NA><NA>002Y0<NA><NA><NA>자가0<NA><NA><NA><NA>N
12030600003060000-202-2008-0000120080528<NA>1영업/정상1영업<NA><NA><NA><NA>9772048543.10131853서울특별시 중랑구 묵동 245-4 지하1층서울특별시 중랑구 동일로 865 (묵동,지하1층)2010솔잎여성전용한증막2021-01-20 13:26:39U2021-01-22 02:40:00.0한증막업206814.613453456135.882474한증막업00<NA><NA>11001Y0<NA><NA><NA>임대0<NA><NA><NA><NA>N
12130600003060000-202-2008-0000220081121<NA>3폐업2폐업20211224<NA><NA><NA>02 342197781,150.47131872서울특별시 중랑구 신내동 646서울특별시 중랑구 신내로 211 (신내동)2024봉화산사우나2021-12-24 11:54:20U2021-12-26 02:40:00.0공동탕업+찜질시설서비스영업208112.860201457113.638411공동탕업+찜질시설서비스영업000011002Y0<NA><NA><NA><NA>00000N
12230600003060000-202-2010-0000120101102<NA>1영업/정상1영업<NA><NA><NA><NA>342124871,573.56131781서울특별시 중랑구 신내동 797 동성아파트 701동 지101호서울특별시 중랑구 신내로14길 21, 701동 지101호 (신내동,동성아파트)2067춘천옥사우나2021-01-07 13:57:56U2021-01-09 02:40:00.0공동탕업+찜질시설서비스영업208508.13674455974.025798공동탕업+찜질시설서비스영업183001101000N0<NA><NA><NA>자가0<NA><NA>00N
12330600003060000-202-2012-0000120120309<NA>3폐업2폐업20190630<NA><NA><NA>02495 0588183.25131877서울특별시 중랑구 중화동 292-3번지서울특별시 중랑구 봉화산로20길 48 (중화동)2094중화여성전용사우나2019-07-11 17:10:44U2019-07-13 02:40:00.0공동탕업207136.222444455229.538937공동탕업0012<NA><NA>002N0<NA><NA><NA>자가0<NA><NA>00N
12430600003060000-202-2018-000012018-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>189.00131-876서울특별시 중랑구 중화동 286-25 대신빌딩서울특별시 중랑구 동일로 802, 대신빌딩 지하1층 (중화동)2051스파카인드2023-09-13 13:36:06U2022-12-08 23:05:00.0목욕장업 기타206971.00348455523.908863<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>