Overview

Dataset statistics

Number of variables47
Number of observations131
Missing cells1393
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.9 KiB
Average record size in memory406.0 B

Variable types

Categorical20
Text7
DateTime3
Unsupported7
Numeric8
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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-19968/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (73.9%)Imbalance
위생업태명 is highly imbalanced (64.9%)Imbalance
세탁기수 is highly imbalanced (55.8%)Imbalance
여성종사자수 is highly imbalanced (80.3%)Imbalance
남성종사자수 is highly imbalanced (80.3%)Imbalance
회수건조수 is highly imbalanced (61.1%)Imbalance
침대수 is highly imbalanced (61.1%)Imbalance
인허가취소일자 has 131 (100.0%) missing valuesMissing
폐업일자 has 22 (16.8%) missing valuesMissing
휴업시작일자 has 131 (100.0%) missing valuesMissing
휴업종료일자 has 131 (100.0%) missing valuesMissing
재개업일자 has 131 (100.0%) missing valuesMissing
전화번호 has 4 (3.1%) missing valuesMissing
소재지우편번호 has 2 (1.5%) missing valuesMissing
지번주소 has 2 (1.5%) missing valuesMissing
도로명주소 has 82 (62.6%) missing valuesMissing
도로명우편번호 has 82 (62.6%) missing valuesMissing
좌표정보(X) has 5 (3.8%) missing valuesMissing
좌표정보(Y) has 5 (3.8%) missing valuesMissing
건물지상층수 has 33 (25.2%) missing valuesMissing
건물지하층수 has 43 (32.8%) missing valuesMissing
사용시작지상층 has 72 (55.0%) missing valuesMissing
사용끝지상층 has 100 (76.3%) missing valuesMissing
발한실여부 has 12 (9.2%) missing valuesMissing
조건부허가신고사유 has 131 (100.0%) missing valuesMissing
조건부허가시작일자 has 131 (100.0%) missing valuesMissing
조건부허가종료일자 has 131 (100.0%) missing valuesMissing
다중이용업소여부 has 12 (9.2%) 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 34 (26.0%) zerosZeros
건물지하층수 has 34 (26.0%) zerosZeros
사용시작지상층 has 31 (23.7%) zerosZeros
사용끝지상층 has 4 (3.1%) zerosZeros

Reproduction

Analysis started2024-04-06 11:04:58.916109
Analysis finished2024-04-06 11:04:59.975212
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3160000
131 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 131
100.0%

Length

2024-04-06T20:05:00.087555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:00.258636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 131
100.0%

관리번호
Text

UNIQUE 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T20:05:00.560569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2882
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

Unique131 ?
Unique (%)100.0%

Sample

1st row3160000-202-1969-00225
2nd row3160000-202-1972-00226
3rd row3160000-202-1972-00227
4th row3160000-202-1981-00292
5th row3160000-202-1982-00237
ValueCountFrequency (%)
3160000-202-1969-00225 1
 
0.8%
3160000-202-1993-00278 1
 
0.8%
3160000-202-2002-00002 1
 
0.8%
3160000-202-2002-00001 1
 
0.8%
3160000-202-2001-00004 1
 
0.8%
3160000-202-2001-00003 1
 
0.8%
3160000-202-2001-00002 1
 
0.8%
3160000-202-2001-00001 1
 
0.8%
3160000-202-2000-00002 1
 
0.8%
3160000-202-2000-00001 1
 
0.8%
Other values (121) 121
92.4%
2024-04-06T20:05:01.107165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1104
38.3%
2 413
 
14.3%
- 393
 
13.6%
1 267
 
9.3%
3 186
 
6.5%
6 171
 
5.9%
9 146
 
5.1%
8 87
 
3.0%
4 42
 
1.5%
7 41
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2489
86.4%
Dash Punctuation 393
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1104
44.4%
2 413
 
16.6%
1 267
 
10.7%
3 186
 
7.5%
6 171
 
6.9%
9 146
 
5.9%
8 87
 
3.5%
4 42
 
1.7%
7 41
 
1.6%
5 32
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2882
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1104
38.3%
2 413
 
14.3%
- 393
 
13.6%
1 267
 
9.3%
3 186
 
6.5%
6 171
 
5.9%
9 146
 
5.1%
8 87
 
3.0%
4 42
 
1.5%
7 41
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1104
38.3%
2 413
 
14.3%
- 393
 
13.6%
1 267
 
9.3%
3 186
 
6.5%
6 171
 
5.9%
9 146
 
5.1%
8 87
 
3.0%
4 42
 
1.5%
7 41
 
1.4%
Distinct129
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1969-04-14 00:00:00
Maximum2020-11-10 00:00:00
2024-04-06T20:05:01.392292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:01.648792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB
Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
109 
1
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 109
83.2%
1 22
 
16.8%

Length

2024-04-06T20:05:01.905156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:02.066575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 109
83.2%
1 22
 
16.8%

영업상태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
109 
영업/정상
22 

Length

Max length5
Median length2
Mean length2.5038168
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 109
83.2%
영업/정상 22
 
16.8%

Length

2024-04-06T20:05:02.244844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:02.424237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 109
83.2%
영업/정상 22
 
16.8%
Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2
109 
1
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 109
83.2%
1 22
 
16.8%

Length

2024-04-06T20:05:02.605141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:02.805742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 109
83.2%
1 22
 
16.8%
Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
109 
영업
22 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 109
83.2%
영업 22
 
16.8%

Length

2024-04-06T20:05:03.008680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:03.154535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 109
83.2%
영업 22
 
16.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct98
Distinct (%)89.9%
Missing22
Missing (%)16.8%
Infinite0
Infinite (%)0.0%
Mean20074178
Minimum19920409
Maximum20221201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:03.316038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19920409
5-th percentile19954840
Q120020410
median20060411
Q320130726
95-th percentile20216449
Maximum20221201
Range300792
Interquartile range (IQR)110316

Descriptive statistics

Standard deviation82257.945
Coefficient of variation (CV)0.0040976993
Kurtosis-0.90015998
Mean20074178
Median Absolute Deviation (MAD)59490
Skewness0.32778324
Sum2.1880854 × 109
Variance6.7663695 × 109
MonotonicityNot monotonic
2024-04-06T20:05:03.538527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030212 9
 
6.9%
20060411 3
 
2.3%
20201224 2
 
1.5%
19940714 1
 
0.8%
20140618 1
 
0.8%
20060630 1
 
0.8%
20100209 1
 
0.8%
20060223 1
 
0.8%
20040804 1
 
0.8%
20030407 1
 
0.8%
Other values (88) 88
67.2%
(Missing) 22
 
16.8%
ValueCountFrequency (%)
19920409 1
0.8%
19930610 1
0.8%
19930707 1
0.8%
19940714 1
0.8%
19950616 1
0.8%
19951128 1
0.8%
19960408 1
0.8%
19961105 1
0.8%
19970303 1
0.8%
19970509 1
0.8%
ValueCountFrequency (%)
20221201 1
0.8%
20221129 1
0.8%
20220914 1
0.8%
20220628 1
0.8%
20220405 1
0.8%
20220208 1
0.8%
20210810 1
0.8%
20201224 2
1.5%
20201110 1
0.8%
20201106 1
0.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Text

MISSING 

Distinct122
Distinct (%)96.1%
Missing4
Missing (%)3.1%
Memory size1.2 KiB
2024-04-06T20:05:03.918643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.102362
Min length6

Characters and Unicode

Total characters1283
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

Unique118 ?
Unique (%)92.9%

Sample

1st row0208542161
2nd row02 6125771
3rd row0226121713
4th row0206846202
5th row02 6830214
ValueCountFrequency (%)
02 73
35.3%
0 3
 
1.4%
6143617 2
 
1.0%
8690997 2
 
1.0%
0226315888 2
 
1.0%
6186333 1
 
0.5%
0226173019 1
 
0.5%
0226192177 1
 
0.5%
0226893335 1
 
0.5%
0226114338 1
 
0.5%
Other values (120) 120
58.0%
2024-04-06T20:05:04.544819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 233
18.2%
0 211
16.4%
6 158
12.3%
8 138
10.8%
98
7.6%
1 95
7.4%
5 94
7.3%
7 78
 
6.1%
3 74
 
5.8%
9 54
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1185
92.4%
Space Separator 98
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 233
19.7%
0 211
17.8%
6 158
13.3%
8 138
11.6%
1 95
8.0%
5 94
7.9%
7 78
 
6.6%
3 74
 
6.2%
9 54
 
4.6%
4 50
 
4.2%
Space Separator
ValueCountFrequency (%)
98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1283
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 233
18.2%
0 211
16.4%
6 158
12.3%
8 138
10.8%
98
7.6%
1 95
7.4%
5 94
7.3%
7 78
 
6.1%
3 74
 
5.8%
9 54
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1283
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 233
18.2%
0 211
16.4%
6 158
12.3%
8 138
10.8%
98
7.6%
1 95
7.4%
5 94
7.3%
7 78
 
6.1%
3 74
 
5.8%
9 54
 
4.2%
Distinct127
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T20:05:05.073430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.3129771
Min length3

Characters and Unicode

Total characters827
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

Unique124 ?
Unique (%)94.7%

Sample

1st row148.87
2nd row118.86
3rd row209.94
4th row166.08
5th row287.20
ValueCountFrequency (%)
330.00 3
 
2.3%
735.08 2
 
1.5%
429.00 2
 
1.5%
710.20 1
 
0.8%
148.87 1
 
0.8%
973.50 1
 
0.8%
900.00 1
 
0.8%
891.00 1
 
0.8%
462.00 1
 
0.8%
1,221.00 1
 
0.8%
Other values (117) 117
89.3%
2024-04-06T20:05:05.830335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 131
15.8%
0 117
14.1%
2 96
11.6%
1 82
9.9%
3 62
7.5%
4 62
7.5%
5 56
6.8%
6 55
6.7%
9 52
 
6.3%
8 47
 
5.7%
Other values (2) 67
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 675
81.6%
Other Punctuation 152
 
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
17.3%
2 96
14.2%
1 82
12.1%
3 62
9.2%
4 62
9.2%
5 56
8.3%
6 55
8.1%
9 52
7.7%
8 47
7.0%
7 46
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 131
86.2%
, 21
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 827
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 131
15.8%
0 117
14.1%
2 96
11.6%
1 82
9.9%
3 62
7.5%
4 62
7.5%
5 56
6.8%
6 55
6.7%
9 52
 
6.3%
8 47
 
5.7%
Other values (2) 67
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 131
15.8%
0 117
14.1%
2 96
11.6%
1 82
9.9%
3 62
7.5%
4 62
7.5%
5 56
6.8%
6 55
6.7%
9 52
 
6.3%
8 47
 
5.7%
Other values (2) 67
8.1%

소재지우편번호
Text

MISSING 

Distinct68
Distinct (%)52.7%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2024-04-06T20:05:06.307543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0387597
Min length6

Characters and Unicode

Total characters779
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

Unique33 ?
Unique (%)25.6%

Sample

1st row152872
2nd row152815
3rd row152834
4th row152809
5th row152836
ValueCountFrequency (%)
152815 7
 
5.4%
152850 4
 
3.1%
152865 4
 
3.1%
152872 4
 
3.1%
152838 4
 
3.1%
152857 3
 
2.3%
152823 3
 
2.3%
152837 3
 
2.3%
152090 3
 
2.3%
152826 3
 
2.3%
Other values (58) 91
70.5%
2024-04-06T20:05:07.287367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 162
20.8%
1 153
19.6%
2 150
19.3%
8 144
18.5%
0 45
 
5.8%
4 30
 
3.9%
6 24
 
3.1%
7 24
 
3.1%
9 22
 
2.8%
3 20
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 774
99.4%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 162
20.9%
1 153
19.8%
2 150
19.4%
8 144
18.6%
0 45
 
5.8%
4 30
 
3.9%
6 24
 
3.1%
7 24
 
3.1%
9 22
 
2.8%
3 20
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 779
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 162
20.8%
1 153
19.6%
2 150
19.3%
8 144
18.5%
0 45
 
5.8%
4 30
 
3.9%
6 24
 
3.1%
7 24
 
3.1%
9 22
 
2.8%
3 20
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 779
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 162
20.8%
1 153
19.6%
2 150
19.3%
8 144
18.5%
0 45
 
5.8%
4 30
 
3.9%
6 24
 
3.1%
7 24
 
3.1%
9 22
 
2.8%
3 20
 
2.6%

지번주소
Text

MISSING 

Distinct124
Distinct (%)96.1%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2024-04-06T20:05:07.840424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length41
Mean length25.062016
Min length17

Characters and Unicode

Total characters3233
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)92.2%

Sample

1st row서울특별시 구로구 구로동 738-67번지
2nd row서울특별시 구로구 개봉동 349-5번지
3rd row서울특별시 구로구 고척동 253-14번지
4th row서울특별시 구로구 개봉동 202-6
5th row서울특별시 구로구 고척동 312-13번지
ValueCountFrequency (%)
서울특별시 129
22.0%
구로구 129
22.0%
구로동 56
 
9.6%
개봉동 30
 
5.1%
고척동 16
 
2.7%
오류동 13
 
2.2%
가리봉동 5
 
0.9%
신도림동 5
 
0.9%
지하동 3
 
0.5%
궁동 2
 
0.3%
Other values (178) 198
33.8%
2024-04-06T20:05:08.567246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
568
17.6%
317
 
9.8%
188
 
5.8%
1 158
 
4.9%
140
 
4.3%
130
 
4.0%
130
 
4.0%
129
 
4.0%
129
 
4.0%
129
 
4.0%
Other values (90) 1215
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1868
57.8%
Decimal Number 646
 
20.0%
Space Separator 568
 
17.6%
Dash Punctuation 119
 
3.7%
Other Punctuation 15
 
0.5%
Uppercase Letter 11
 
0.3%
Math Symbol 2
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
317
17.0%
188
10.1%
140
7.5%
130
 
7.0%
130
 
7.0%
129
 
6.9%
129
 
6.9%
129
 
6.9%
123
 
6.6%
104
 
5.6%
Other values (71) 349
18.7%
Decimal Number
ValueCountFrequency (%)
1 158
24.5%
2 83
12.8%
3 76
11.8%
4 62
 
9.6%
7 50
 
7.7%
0 49
 
7.6%
6 48
 
7.4%
5 48
 
7.4%
8 41
 
6.3%
9 31
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
. 2
 
13.3%
Uppercase Letter
ValueCountFrequency (%)
B 10
90.9%
A 1
 
9.1%
Space Separator
ValueCountFrequency (%)
568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1868
57.8%
Common 1354
41.9%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
317
17.0%
188
10.1%
140
7.5%
130
 
7.0%
130
 
7.0%
129
 
6.9%
129
 
6.9%
129
 
6.9%
123
 
6.6%
104
 
5.6%
Other values (71) 349
18.7%
Common
ValueCountFrequency (%)
568
41.9%
1 158
 
11.7%
- 119
 
8.8%
2 83
 
6.1%
3 76
 
5.6%
4 62
 
4.6%
7 50
 
3.7%
0 49
 
3.6%
6 48
 
3.5%
5 48
 
3.5%
Other values (7) 93
 
6.9%
Latin
ValueCountFrequency (%)
B 10
90.9%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1868
57.8%
ASCII 1365
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
568
41.6%
1 158
 
11.6%
- 119
 
8.7%
2 83
 
6.1%
3 76
 
5.6%
4 62
 
4.5%
7 50
 
3.7%
0 49
 
3.6%
6 48
 
3.5%
5 48
 
3.5%
Other values (9) 104
 
7.6%
Hangul
ValueCountFrequency (%)
317
17.0%
188
10.1%
140
7.5%
130
 
7.0%
130
 
7.0%
129
 
6.9%
129
 
6.9%
129
 
6.9%
123
 
6.6%
104
 
5.6%
Other values (71) 349
18.7%

도로명주소
Text

MISSING 

Distinct49
Distinct (%)100.0%
Missing82
Missing (%)62.6%
Memory size1.2 KiB
2024-04-06T20:05:09.041980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length42
Mean length32.183673
Min length22

Characters and Unicode

Total characters1577
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row서울특별시 구로구 고척로32길 11 (고척동)
2nd row서울특별시 구로구 경인로35길 86 (고척동)
3rd row서울특별시 구로구 우마1가길 19 (가리봉동)
4th row서울특별시 구로구 구로동로38길 32 (구로동)
5th row서울특별시 구로구 구로동로26길 73 (구로동)
ValueCountFrequency (%)
서울특별시 49
 
17.0%
구로구 49
 
17.0%
개봉동 9
 
3.1%
구로동 9
 
3.1%
고척동 6
 
2.1%
오류동 4
 
1.4%
8 4
 
1.4%
공원로 3
 
1.0%
63 3
 
1.0%
4 3
 
1.0%
Other values (129) 150
51.9%
2024-04-06T20:05:09.722786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
240
 
15.2%
129
 
8.2%
126
 
8.0%
63
 
4.0%
1 62
 
3.9%
) 51
 
3.2%
( 51
 
3.2%
50
 
3.2%
49
 
3.1%
49
 
3.1%
Other values (90) 707
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 928
58.8%
Decimal Number 246
 
15.6%
Space Separator 240
 
15.2%
Close Punctuation 51
 
3.2%
Open Punctuation 51
 
3.2%
Other Punctuation 46
 
2.9%
Uppercase Letter 9
 
0.6%
Dash Punctuation 4
 
0.3%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
129
13.9%
126
13.6%
63
 
6.8%
50
 
5.4%
49
 
5.3%
49
 
5.3%
49
 
5.3%
49
 
5.3%
35
 
3.8%
23
 
2.5%
Other values (72) 306
33.0%
Decimal Number
ValueCountFrequency (%)
1 62
25.2%
2 42
17.1%
3 32
13.0%
5 21
 
8.5%
0 21
 
8.5%
8 17
 
6.9%
7 16
 
6.5%
4 15
 
6.1%
6 12
 
4.9%
9 8
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 8
88.9%
A 1
 
11.1%
Space Separator
ValueCountFrequency (%)
240
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 928
58.8%
Common 640
40.6%
Latin 9
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
129
13.9%
126
13.6%
63
 
6.8%
50
 
5.4%
49
 
5.3%
49
 
5.3%
49
 
5.3%
49
 
5.3%
35
 
3.8%
23
 
2.5%
Other values (72) 306
33.0%
Common
ValueCountFrequency (%)
240
37.5%
1 62
 
9.7%
) 51
 
8.0%
( 51
 
8.0%
, 46
 
7.2%
2 42
 
6.6%
3 32
 
5.0%
5 21
 
3.3%
0 21
 
3.3%
8 17
 
2.7%
Other values (6) 57
 
8.9%
Latin
ValueCountFrequency (%)
B 8
88.9%
A 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 928
58.8%
ASCII 649
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
240
37.0%
1 62
 
9.6%
) 51
 
7.9%
( 51
 
7.9%
, 46
 
7.1%
2 42
 
6.5%
3 32
 
4.9%
5 21
 
3.2%
0 21
 
3.2%
8 17
 
2.6%
Other values (8) 66
 
10.2%
Hangul
ValueCountFrequency (%)
129
13.9%
126
13.6%
63
 
6.8%
50
 
5.4%
49
 
5.3%
49
 
5.3%
49
 
5.3%
49
 
5.3%
35
 
3.8%
23
 
2.5%
Other values (72) 306
33.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)83.7%
Missing82
Missing (%)62.6%
Infinite0
Infinite (%)0.0%
Mean8288.1837
Minimum8210
Maximum8395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:09.977919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8210
5-th percentile8215.4
Q18243
median8282
Q38328
95-th percentile8381
Maximum8395
Range185
Interquartile range (IQR)85

Descriptive statistics

Standard deviation54.344071
Coefficient of variation (CV)0.0065568131
Kurtosis-1.0229923
Mean8288.1837
Median Absolute Deviation (MAD)46
Skewness0.31257055
Sum406121
Variance2953.2781
MonotonicityNot monotonic
2024-04-06T20:05:10.245659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
8251 2
 
1.5%
8378 2
 
1.5%
8210 2
 
1.5%
8282 2
 
1.5%
8228 2
 
1.5%
8243 2
 
1.5%
8311 2
 
1.5%
8295 2
 
1.5%
8263 1
 
0.8%
8285 1
 
0.8%
Other values (31) 31
 
23.7%
(Missing) 82
62.6%
ValueCountFrequency (%)
8210 2
1.5%
8215 1
0.8%
8216 1
0.8%
8218 1
0.8%
8220 1
0.8%
8227 1
0.8%
8228 2
1.5%
8229 1
0.8%
8233 1
0.8%
8235 1
0.8%
ValueCountFrequency (%)
8395 1
0.8%
8385 1
0.8%
8383 1
0.8%
8378 2
1.5%
8363 1
0.8%
8354 1
0.8%
8353 1
0.8%
8349 1
0.8%
8348 1
0.8%
8341 1
0.8%
Distinct123
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T20:05:10.649884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length4.9083969
Min length2

Characters and Unicode

Total characters643
Distinct characters151
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

Unique116 ?
Unique (%)88.5%

Sample

1st row시온탕
2nd row온양탕
3rd row영진탕
4th row대원장
5th row온정탕
ValueCountFrequency (%)
대성탕 3
 
2.1%
스파 2
 
1.4%
하얀탕 2
 
1.4%
신도탕 2
 
1.4%
제일탕 2
 
1.4%
구로동불가마사우나 2
 
1.4%
로얄사우나 2
 
1.4%
영진탕 2
 
1.4%
사우나 2
 
1.4%
찜질방 2
 
1.4%
Other values (124) 124
85.5%
2024-04-06T20:05:11.376734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
10.4%
43
 
6.7%
40
 
6.2%
35
 
5.4%
20
 
3.1%
14
 
2.2%
13
 
2.0%
11
 
1.7%
11
 
1.7%
10
 
1.6%
Other values (141) 379
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 613
95.3%
Space Separator 14
 
2.2%
Decimal Number 10
 
1.6%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Other Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
67
 
10.9%
43
 
7.0%
40
 
6.5%
35
 
5.7%
20
 
3.3%
13
 
2.1%
11
 
1.8%
11
 
1.8%
10
 
1.6%
10
 
1.6%
Other values (134) 353
57.6%
Decimal Number
ValueCountFrequency (%)
2 5
50.0%
4 5
50.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 613
95.3%
Common 30
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
67
 
10.9%
43
 
7.0%
40
 
6.5%
35
 
5.7%
20
 
3.3%
13
 
2.1%
11
 
1.8%
11
 
1.8%
10
 
1.6%
10
 
1.6%
Other values (134) 353
57.6%
Common
ValueCountFrequency (%)
14
46.7%
2 5
 
16.7%
4 5
 
16.7%
( 2
 
6.7%
) 2
 
6.7%
& 1
 
3.3%
- 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 613
95.3%
ASCII 30
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
67
 
10.9%
43
 
7.0%
40
 
6.5%
35
 
5.7%
20
 
3.3%
13
 
2.1%
11
 
1.8%
11
 
1.8%
10
 
1.6%
10
 
1.6%
Other values (134) 353
57.6%
ASCII
ValueCountFrequency (%)
14
46.7%
2 5
 
16.7%
4 5
 
16.7%
( 2
 
6.7%
) 2
 
6.7%
& 1
 
3.3%
- 1
 
3.3%
Distinct94
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1999-03-24 00:00:00
Maximum2024-01-02 17:03:05
2024-04-06T20:05:11.618244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:11.931913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
92 
U
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 92
70.2%
U 39
29.8%

Length

2024-04-06T20:05:12.197504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:12.384866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 92
70.2%
u 39
29.8%
Distinct31
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-01 00:04:00
2024-04-06T20:05:12.553975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:12.787016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
공동탕업
119 
공동탕업+찜질시설서비스영업
 
6
목욕장업 기타
 
2
한증막업
 
2
찜질시설서비스영업
 
2

Length

Max length14
Median length4
Mean length4.5801527
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 119
90.8%
공동탕업+찜질시설서비스영업 6
 
4.6%
목욕장업 기타 2
 
1.5%
한증막업 2
 
1.5%
찜질시설서비스영업 2
 
1.5%

Length

2024-04-06T20:05:13.013829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:13.198237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 119
89.5%
공동탕업+찜질시설서비스영업 6
 
4.5%
목욕장업 2
 
1.5%
기타 2
 
1.5%
한증막업 2
 
1.5%
찜질시설서비스영업 2
 
1.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)84.1%
Missing5
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean188381.08
Minimum184200.66
Maximum191205.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:13.404876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184200.66
5-th percentile185775.1
Q1186951.7
median189006.06
Q3189967.82
95-th percentile190541.56
Maximum191205.79
Range7005.1299
Interquartile range (IQR)3016.1208

Descriptive statistics

Standard deviation1743.7089
Coefficient of variation (CV)0.0092562846
Kurtosis-1.0993173
Mean188381.08
Median Absolute Deviation (MAD)1376.0115
Skewness-0.27919438
Sum23736016
Variance3040520.7
MonotonicityNot monotonic
2024-04-06T20:05:13.726386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189038.460268375 3
 
2.3%
186835.172300314 3
 
2.3%
189618.752905327 2
 
1.5%
189530.280204564 2
 
1.5%
187870.470839962 2
 
1.5%
190101.571803215 2
 
1.5%
189432.385517396 2
 
1.5%
190352.405595566 2
 
1.5%
187173.725729414 2
 
1.5%
186282.360333502 2
 
1.5%
Other values (96) 104
79.4%
(Missing) 5
 
3.8%
ValueCountFrequency (%)
184200.661623067 1
0.8%
184457.791730837 1
0.8%
184861.891003458 1
0.8%
184941.706201411 1
0.8%
185557.827666309 1
0.8%
185678.165074992 1
0.8%
185741.502547322 1
0.8%
185875.875759586 1
0.8%
185900.76304245 1
0.8%
185993.519856833 1
0.8%
ValueCountFrequency (%)
191205.791543965 1
0.8%
191191.131566069 1
0.8%
191126.922861445 1
0.8%
191020.264430044 1
0.8%
191002.243483409 1
0.8%
190759.48539169 1
0.8%
190541.558271971 2
1.5%
190406.417331687 1
0.8%
190395.221939679 1
0.8%
190394.394227379 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)84.1%
Missing5
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean443669.9
Minimum441915.95
Maximum445279.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:13.996162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441915.95
5-th percentile442479.48
Q1443043.56
median443626.65
Q3444331.58
95-th percentile444915.25
Maximum445279.56
Range3363.6134
Interquartile range (IQR)1288.0258

Descriptive statistics

Standard deviation810.59591
Coefficient of variation (CV)0.0018270248
Kurtosis-0.96604256
Mean443669.9
Median Absolute Deviation (MAD)670.79468
Skewness-0.0080296499
Sum55902408
Variance657065.73
MonotonicityNot monotonic
2024-04-06T20:05:14.215209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444478.759955186 3
 
2.3%
442508.979734929 3
 
2.3%
444921.078748984 2
 
1.5%
443626.645892719 2
 
1.5%
444127.308633809 2
 
1.5%
444426.01649216 2
 
1.5%
444019.253245838 2
 
1.5%
444253.918572529 2
 
1.5%
442678.332549373 2
 
1.5%
444482.054741506 2
 
1.5%
Other values (96) 104
79.4%
(Missing) 5
 
3.8%
ValueCountFrequency (%)
441915.949256826 1
0.8%
442152.778031612 1
0.8%
442247.539159585 1
0.8%
442287.430313169 1
0.8%
442398.056827727 1
0.8%
442460.919021593 1
0.8%
442476.539315903 1
0.8%
442488.299498464 1
0.8%
442491.81823395 1
0.8%
442493.802438612 1
0.8%
ValueCountFrequency (%)
445279.562650792 1
0.8%
445268.38516364 1
0.8%
445258.462014386 1
0.8%
444964.893802424 1
0.8%
444942.306774479 1
0.8%
444921.078748984 2
1.5%
444897.757615026 1
0.8%
444886.798172714 1
0.8%
444861.540913438 1
0.8%
444836.673561831 1
0.8%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
공동탕업
110 
<NA>
12 
공동탕업+찜질시설서비스영업
 
5
찜질시설서비스영업
 
2
목욕장업 기타
 
1

Length

Max length14
Median length4
Mean length4.480916
Min length4

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 110
84.0%
<NA> 12
 
9.2%
공동탕업+찜질시설서비스영업 5
 
3.8%
찜질시설서비스영업 2
 
1.5%
목욕장업 기타 1
 
0.8%
한증막업 1
 
0.8%

Length

2024-04-06T20:05:14.461242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:14.678681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 110
83.3%
na 12
 
9.1%
공동탕업+찜질시설서비스영업 5
 
3.8%
찜질시설서비스영업 2
 
1.5%
목욕장업 1
 
0.8%
기타 1
 
0.8%
한증막업 1
 
0.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)15.3%
Missing33
Missing (%)25.2%
Infinite0
Infinite (%)0.0%
Mean4.0204082
Minimum0
Maximum24
Zeros34
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:14.852805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q34.75
95-th percentile15.3
Maximum24
Range24
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation4.9824012
Coefficient of variation (CV)1.2392774
Kurtosis4.6660826
Mean4.0204082
Median Absolute Deviation (MAD)3
Skewness2.0700635
Sum394
Variance24.824321
MonotonicityNot monotonic
2024-04-06T20:05:15.047284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 34
26.0%
4 20
15.3%
3 16
12.2%
8 6
 
4.6%
5 5
 
3.8%
2 3
 
2.3%
6 3
 
2.3%
15 2
 
1.5%
7 2
 
1.5%
17 2
 
1.5%
Other values (5) 5
 
3.8%
(Missing) 33
25.2%
ValueCountFrequency (%)
0 34
26.0%
2 3
 
2.3%
3 16
12.2%
4 20
15.3%
5 5
 
3.8%
6 3
 
2.3%
7 2
 
1.5%
8 6
 
4.6%
12 1
 
0.8%
13 1
 
0.8%
ValueCountFrequency (%)
24 1
 
0.8%
22 1
 
0.8%
20 1
 
0.8%
17 2
 
1.5%
15 2
 
1.5%
13 1
 
0.8%
12 1
 
0.8%
8 6
4.6%
7 2
 
1.5%
6 3
2.3%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)6.8%
Missing43
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean1.1022727
Minimum0
Maximum6
Zeros34
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:15.203734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3.65
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2321346
Coefficient of variation (CV)1.1178128
Kurtosis2.2077858
Mean1.1022727
Median Absolute Deviation (MAD)1
Skewness1.3856883
Sum97
Variance1.5181557
MonotonicityNot monotonic
2024-04-06T20:05:15.354757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 34
26.0%
1 29
22.1%
2 14
 
10.7%
3 6
 
4.6%
4 4
 
3.1%
6 1
 
0.8%
(Missing) 43
32.8%
ValueCountFrequency (%)
0 34
26.0%
1 29
22.1%
2 14
10.7%
3 6
 
4.6%
4 4
 
3.1%
6 1
 
0.8%
ValueCountFrequency (%)
6 1
 
0.8%
4 4
 
3.1%
3 6
 
4.6%
2 14
10.7%
1 29
22.1%
0 34
26.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)11.9%
Missing72
Missing (%)55.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum0
Maximum8
Zeros31
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:15.599067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3.2
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.62947
Coefficient of variation (CV)1.62947
Kurtosis7.8337368
Mean1
Median Absolute Deviation (MAD)0
Skewness2.5986669
Sum59
Variance2.6551724
MonotonicityNot monotonic
2024-04-06T20:05:15.773397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 31
23.7%
1 15
 
11.5%
2 6
 
4.6%
3 4
 
3.1%
5 1
 
0.8%
8 1
 
0.8%
7 1
 
0.8%
(Missing) 72
55.0%
ValueCountFrequency (%)
0 31
23.7%
1 15
11.5%
2 6
 
4.6%
3 4
 
3.1%
5 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
ValueCountFrequency (%)
8 1
 
0.8%
7 1
 
0.8%
5 1
 
0.8%
3 4
 
3.1%
2 6
 
4.6%
1 15
11.5%
0 31
23.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)25.8%
Missing100
Missing (%)76.3%
Infinite0
Infinite (%)0.0%
Mean2.5483871
Minimum0
Maximum8
Zeros4
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-06T20:05:15.946063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6.5
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.01393
Coefficient of variation (CV)0.79027632
Kurtosis0.94480103
Mean2.5483871
Median Absolute Deviation (MAD)1
Skewness1.0892885
Sum79
Variance4.055914
MonotonicityNot monotonic
2024-04-06T20:05:16.121274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 10
 
7.6%
3 6
 
4.6%
1 5
 
3.8%
0 4
 
3.1%
5 3
 
2.3%
6 1
 
0.8%
8 1
 
0.8%
7 1
 
0.8%
(Missing) 100
76.3%
ValueCountFrequency (%)
0 4
 
3.1%
1 5
3.8%
2 10
7.6%
3 6
4.6%
5 3
 
2.3%
6 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
ValueCountFrequency (%)
8 1
 
0.8%
7 1
 
0.8%
6 1
 
0.8%
5 3
 
2.3%
3 6
4.6%
2 10
7.6%
1 5
3.8%
0 4
 
3.1%
Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
66 
1
32 
0
29 
2
 
4

Length

Max length4
Median length4
Mean length2.5114504
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
50.4%
1 32
24.4%
0 29
22.1%
2 4
 
3.1%

Length

2024-04-06T20:05:16.387884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:16.553797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
50.4%
1 32
24.4%
0 29
22.1%
2 4
 
3.1%
Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
94 
1
23 
2
11 
0
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.1526718
Min length1

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> 94
71.8%
1 23
 
17.6%
2 11
 
8.4%
0 2
 
1.5%
3 1
 
0.8%

Length

2024-04-06T20:05:16.728843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:16.907807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
71.8%
1 23
 
17.6%
2 11
 
8.4%
0 2
 
1.5%
3 1
 
0.8%

한실수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
92 
0
39 

Length

Max length4
Median length4
Mean length3.1068702
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
70.2%
0 39
29.8%

Length

2024-04-06T20:05:17.140413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:17.354655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
70.2%
0 39
29.8%

양실수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
92 
0
39 

Length

Max length4
Median length4
Mean length3.1068702
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
70.2%
0 39
29.8%

Length

2024-04-06T20:05:17.553975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:17.726207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
70.2%
0 39
29.8%

욕실수
Categorical

Distinct6
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
77 
0
33 
2
18 
1
 
1
7
 
1

Length

Max length4
Median length4
Mean length2.7633588
Min length1

Unique

Unique3 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 77
58.8%
0 33
25.2%
2 18
 
13.7%
1 1
 
0.8%
7 1
 
0.8%
3 1
 
0.8%

Length

2024-04-06T20:05:17.926950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:18.109082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
58.8%
0 33
25.2%
2 18
 
13.7%
1 1
 
0.8%
7 1
 
0.8%
3 1
 
0.8%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)1.7%
Missing12
Missing (%)9.2%
Memory size394.0 B
False
103 
True
16 
(Missing)
12 
ValueCountFrequency (%)
False 103
78.6%
True 16
 
12.2%
(Missing) 12
 
9.2%
2024-04-06T20:05:18.276537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
92 
0
39 

Length

Max length4
Median length4
Mean length3.1068702
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
70.2%
0 39
29.8%

Length

2024-04-06T20:05:18.481523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:18.670768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
70.2%
0 39
29.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB
Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
72 
임대
31 
자가
28 

Length

Max length4
Median length4
Mean length3.0992366
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 72
55.0%
임대 31
23.7%
자가 28
 
21.4%

Length

2024-04-06T20:05:18.907057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:19.094135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 72
55.0%
임대 31
23.7%
자가 28
 
21.4%

세탁기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
119 
0
12 

Length

Max length4
Median length4
Mean length3.7251908
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> 119
90.8%
0 12
 
9.2%

Length

2024-04-06T20:05:19.676926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:19.876240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 119
90.8%
0 12
 
9.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
127 
0
 
4

Length

Max length4
Median length4
Mean length3.9083969
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> 127
96.9%
0 4
 
3.1%

Length

2024-04-06T20:05:20.046334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:20.274118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
96.9%
0 4
 
3.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
127 
0
 
4

Length

Max length4
Median length4
Mean length3.9083969
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> 127
96.9%
0 4
 
3.1%

Length

2024-04-06T20:05:20.491045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:20.754658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
96.9%
0 4
 
3.1%

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
121 
0
 
10

Length

Max length4
Median length4
Mean length3.7709924
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> 121
92.4%
0 10
 
7.6%

Length

2024-04-06T20:05:20.921786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:21.090556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
92.4%
0 10
 
7.6%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
121 
0
 
10

Length

Max length4
Median length4
Mean length3.7709924
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> 121
92.4%
0 10
 
7.6%

Length

2024-04-06T20:05:21.293859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:21.589514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
92.4%
0 10
 
7.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing12
Missing (%)9.2%
Memory size394.0 B
False
119 
(Missing)
12 
ValueCountFrequency (%)
False 119
90.8%
(Missing) 12
 
9.2%
2024-04-06T20:05:21.706860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031600003160000-202-1969-0022519690414<NA>3폐업2폐업20030212<NA><NA><NA>0208542161148.87152872서울특별시 구로구 구로동 738-67번지<NA><NA>시온탕2003-02-12 00:00:00I2018-08-31 23:59:59.0공동탕업189798.281145442779.352076공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131600003160000-202-1972-0022619721020<NA>3폐업2폐업19990903<NA><NA><NA>02 6125771118.86152815서울특별시 구로구 개봉동 349-5번지<NA><NA>온양탕2000-07-12 00:00:00I2018-08-31 23:59:59.0공동탕업187138.643002442838.479701공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231600003160000-202-1972-0022719721018<NA>1영업/정상1영업<NA><NA><NA><NA>0226121713209.94152834서울특별시 구로구 고척동 253-14번지서울특별시 구로구 고척로32길 11 (고척동)8235영진탕2018-12-20 11:30:21U2018-12-22 02:40:00.0공동탕업186636.978328444456.446712공동탕업3111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
331600003160000-202-1981-0029219811106<NA>3폐업2폐업19940714<NA><NA><NA>0206846202166.08152809서울특별시 구로구 개봉동 202-6<NA><NA>대원장2020-12-17 10:44:19U2020-12-19 02:40:00.0공동탕업187474.51321443527.929805공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431600003160000-202-1982-0023719821103<NA>1영업/정상1영업<NA><NA><NA><NA>02 6830214287.20152836서울특별시 구로구 고척동 312-13번지서울특별시 구로구 경인로35길 86 (고척동)8229온정탕2020-01-31 17:46:46U2020-02-02 02:40:00.0공동탕업186899.308976444239.550542공동탕업2<NA>12<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531600003160000-202-1982-0028619821202<NA>3폐업2폐업20030212<NA><NA><NA>0206135346192.91152814서울특별시 구로구 개봉동 308-13번지<NA><NA>고성2003-02-12 00:00:00I2018-08-31 23:59:59.0공동탕업186757.069207443544.930636공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631600003160000-202-1982-0030019821211<NA>3폐업2폐업20020212<NA><NA><NA>0200000000246.92152862서울특별시 구로구 구로동 557-24번지<NA><NA>삼흥탕2003-02-12 00:00:00I2018-08-31 23:59:59.0공동탕업189924.531804444680.46885공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731600003160000-202-1982-0030119821213<NA>3폐업2폐업20030212<NA><NA><NA>0206823684229.91152810서울특별시 구로구 개봉동 261-7번지<NA><NA>이화탕2003-02-12 00:00:00I2018-08-31 23:59:59.0공동탕업187248.200046443175.354576공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831600003160000-202-1983-0022919830927<NA>3폐업2폐업19961105<NA><NA><NA>02 6123451213.60152893서울특별시 구로구 오류동 38-1번지<NA><NA>오류탕2001-09-26 00:00:00I2018-08-31 23:59:59.0공동탕업186143.039451443851.276038공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931600003160000-202-1983-0023319830427<NA>3폐업2폐업20020410<NA><NA><NA>02 8626155123.72152801서울특별시 구로구 가리봉동 133-51번지<NA><NA>우성탕2003-02-12 00:00:00I2018-08-31 23:59:59.0공동탕업190298.795845442152.778032공동탕업<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
12131600003160000-202-2011-0000120110823<NA>3폐업2폐업20200117<NA><NA><NA><NA>735.08152838서울특별시 구로구 구로동 46-5번지 한스타워 B -101호, 201호서울특별시 구로구 공원로 34 (구로동,한스타워 B -101호, 201호)8297한스사우나2020-01-17 17:36:58U2020-01-19 02:40:00.0공동탕업190352.405596444253.918573공동탕업00<NA><NA><NA><NA>002N0<NA><NA><NA><NA>0<NA><NA>00N
12231600003160000-202-2011-0000220111031<NA>3폐업2폐업20201224<NA><NA><NA><NA>445.80152865서울특별시 구로구 구로동 610-17 신구로상가서울특별시 구로구 경인로55길 31, 신구로상가 지하호 (구로동)8215로얄사우나2020-12-24 15:15:56U2020-12-26 02:40:00.0공동탕업189038.460268444478.759955공동탕업00<NA><NA>1<NA>003Y0<NA><NA><NA><NA>0<NA><NA>00N
12331600003160000-202-2012-000012012-01-18<NA>1영업/정상1영업<NA><NA><NA><NA>0236663668951.66152-090서울특별시 구로구 개봉동 478 개봉한진아파트 상가1동 지하1층서울특별시 구로구 개봉로3길 87 (개봉동,개봉한진아파트 상가1동 지하1층)8354한진힐링사우나2023-03-22 11:36:11U2022-12-02 22:04:00.0목욕장업 기타186835.1723442508.979735<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12431600003160000-202-2014-0000120140226<NA>1영업/정상1영업<NA><NA><NA><NA>0226135000921.49152825서울특별시 구로구 고척동 60-34 제니스 스포츠클럽 지1층서울특별시 구로구 안양천로539길 11 (고척동)8220제니스 스포츠 주식회사(사우나)2023-01-19 10:35:38U2022-11-30 22:01:00.0공동탕업188459.808425444722.121127<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12531600003160000-202-2014-0000220140415<NA>3폐업2폐업20190904<NA><NA><NA>02261927772,084.00152892서울특별시 구로구 오류동 31-280번지 참좋은 스파 찜질방 2 ~ 5층서울특별시 구로구 경인로 233 (오류동)8267참좋은 스파 찜질방2019-09-04 17:11:40U2019-09-06 02:40:00.0공동탕업+찜질시설서비스영업186343.11549443954.03571공동탕업+찜질시설서비스영업0025<NA><NA>000N0<NA><NA><NA>자가0<NA><NA>00N
12631600003160000-202-2014-000032014-04-22<NA>1영업/정상1영업<NA><NA><NA><NA>02328177702241.60152-844서울특별시 구로구 구로동 110-1 희훈타워빌 지2층, 지3층서울특별시 구로구 공원로 63 (구로동, 희훈타워빌 지2층, 지3층)8295해양 24시 불가마사우나2023-11-29 14:32:04U2022-11-02 00:01:00.0공동탕업+찜질시설서비스영업190101.571803444426.016492<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12731600003160000-202-2014-0000420141126<NA>3폐업2폐업20220208<NA><NA><NA>0226160921854.00152900서울특별시 구로구 오류동 213-1 2층,지1~지2층서울특별시 구로구 오리로7길 4, 2층,지1~지2층 (오류동)8363천왕대중사우나2022-02-08 11:42:10U2022-02-10 02:40:00.0공동탕업185557.827666442841.709836공동탕업422212000N0<NA><NA><NA><NA>00000N
12831600003160000-202-2014-0000520141201<NA>3폐업2폐업20170829<NA><NA><NA>0226315888710.20<NA><NA>서울특별시 구로구 경인로59길 8, 7층 713호 (신도림동, 태영프라자)8210태영 신통방통 찜질방2017-08-29 13:39:32I2018-08-31 23:59:59.0찜질시설서비스영업189618.752905444921.078749찜질시설서비스영업0077<NA><NA>000N0<NA><NA><NA><NA>00000N
12931600003160000-202-2015-0000120150424<NA>1영업/정상1영업<NA><NA><NA><NA>0226898052410.00152802서울특별시 구로구 개봉동 33-163번지서울특별시 구로구 고척로21가길 4, 지상 2 ~ 3층 (개봉동)8251천지연녹주찜질방2018-02-09 12:18:28I2018-08-31 23:59:59.0찜질시설서비스영업186282.360334444482.054742찜질시설서비스영업4123<NA><NA>000N0<NA><NA><NA><NA>00000N
13031600003160000-202-2020-0000120201110<NA>3폐업2폐업20220914<NA><NA><NA><NA>2,332.00152857서울특별시 구로구 구로동 461-3 경남빌딩서울특별시 구로구 구로동로 183, 경남빌딩 지하1층 (구로동)8282구로동불가마사우나2022-09-14 11:09:41U2021-12-08 23:06:00.0공동탕업189530.280205443626.645893<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>