Overview

Dataset statistics

Number of variables47
Number of observations612
Missing cells6783
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory242.2 KiB
Average record size in memory405.2 B

Variable types

Categorical20
Text6
DateTime4
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-17941/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.3%)Imbalance
위생업태명 is highly imbalanced (74.5%)Imbalance
사용끝지하층 is highly imbalanced (56.1%)Imbalance
건물소유구분명 is highly imbalanced (73.7%)Imbalance
여성종사자수 is highly imbalanced (53.7%)Imbalance
남성종사자수 is highly imbalanced (70.0%)Imbalance
인허가취소일자 has 612 (100.0%) missing valuesMissing
폐업일자 has 96 (15.7%) missing valuesMissing
휴업시작일자 has 612 (100.0%) missing valuesMissing
휴업종료일자 has 612 (100.0%) missing valuesMissing
재개업일자 has 612 (100.0%) missing valuesMissing
전화번호 has 135 (22.1%) missing valuesMissing
도로명주소 has 405 (66.2%) missing valuesMissing
도로명우편번호 has 405 (66.2%) missing valuesMissing
좌표정보(X) has 38 (6.2%) missing valuesMissing
좌표정보(Y) has 38 (6.2%) missing valuesMissing
건물지상층수 has 398 (65.0%) missing valuesMissing
사용시작지상층 has 363 (59.3%) missing valuesMissing
사용끝지상층 has 414 (67.6%) missing valuesMissing
발한실여부 has 48 (7.8%) missing valuesMissing
좌석수 has 117 (19.1%) missing valuesMissing
조건부허가신고사유 has 612 (100.0%) missing valuesMissing
조건부허가시작일자 has 612 (100.0%) missing valuesMissing
조건부허가종료일자 has 612 (100.0%) missing valuesMissing
다중이용업소여부 has 42 (6.9%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 13 (2.1%) zerosZeros
건물지상층수 has 189 (30.9%) zerosZeros
사용시작지상층 has 65 (10.6%) zerosZeros
사용끝지상층 has 18 (2.9%) zerosZeros
좌석수 has 13 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:31:05.194752
Analysis finished2024-05-11 05:31:06.827895
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3140000
612 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 612
100.0%

Length

2024-05-11T14:31:07.030251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:07.252488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 612
100.0%

관리번호
Text

UNIQUE 

Distinct612
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T14:31:07.523020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13464
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

Unique612 ?
Unique (%)100.0%

Sample

1st row3140000-203-1970-00139
2nd row3140000-203-1970-00141
3rd row3140000-203-1970-00179
4th row3140000-203-1970-00207
5th row3140000-203-1971-00144
ValueCountFrequency (%)
3140000-203-1970-00139 1
 
0.2%
3140000-203-2003-00023 1
 
0.2%
3140000-203-2003-00032 1
 
0.2%
3140000-203-2003-00016 1
 
0.2%
3140000-203-2003-00017 1
 
0.2%
3140000-203-2003-00018 1
 
0.2%
3140000-203-2003-00020 1
 
0.2%
3140000-203-2003-00021 1
 
0.2%
3140000-203-2003-00022 1
 
0.2%
3140000-203-2003-00025 1
 
0.2%
Other values (602) 602
98.4%
2024-05-11T14:31:08.067563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5281
39.2%
- 1836
 
13.6%
3 1534
 
11.4%
1 1330
 
9.9%
2 1212
 
9.0%
4 843
 
6.3%
9 635
 
4.7%
8 288
 
2.1%
5 173
 
1.3%
6 172
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11628
86.4%
Dash Punctuation 1836
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5281
45.4%
3 1534
 
13.2%
1 1330
 
11.4%
2 1212
 
10.4%
4 843
 
7.2%
9 635
 
5.5%
8 288
 
2.5%
5 173
 
1.5%
6 172
 
1.5%
7 160
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13464
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5281
39.2%
- 1836
 
13.6%
3 1534
 
11.4%
1 1330
 
9.9%
2 1212
 
9.0%
4 843
 
6.3%
9 635
 
4.7%
8 288
 
2.1%
5 173
 
1.3%
6 172
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5281
39.2%
- 1836
 
13.6%
3 1534
 
11.4%
1 1330
 
9.9%
2 1212
 
9.0%
4 843
 
6.3%
9 635
 
4.7%
8 288
 
2.1%
5 173
 
1.3%
6 172
 
1.3%

인허가일자
Date

Distinct558
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1970-03-13 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T14:31:08.325459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:08.544298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
516 
1
96 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 516
84.3%
1 96
 
15.7%

Length

2024-05-11T14:31:08.791157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:09.014234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 516
84.3%
1 96
 
15.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
516 
영업/정상
96 

Length

Max length5
Median length2
Mean length2.4705882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 516
84.3%
영업/정상 96
 
15.7%

Length

2024-05-11T14:31:09.207603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:09.423388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 516
84.3%
영업/정상 96
 
15.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2
516 
1
96 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 516
84.3%
1 96
 
15.7%

Length

2024-05-11T14:31:09.630616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:09.827846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 516
84.3%
1 96
 
15.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
516 
영업
96 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 516
84.3%
영업 96
 
15.7%

Length

2024-05-11T14:31:09.996434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:10.220788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 516
84.3%
영업 96
 
15.7%

폐업일자
Date

MISSING 

Distinct432
Distinct (%)83.7%
Missing96
Missing (%)15.7%
Memory size4.9 KiB
Minimum1994-01-13 00:00:00
Maximum2024-03-19 00:00:00
2024-05-11T14:31:10.524505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:10.756778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

전화번호
Text

MISSING 

Distinct423
Distinct (%)88.7%
Missing135
Missing (%)22.1%
Memory size4.9 KiB
2024-05-11T14:31:11.156932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8825996
Min length2

Characters and Unicode

Total characters4714
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

Unique407 ?
Unique (%)85.3%

Sample

1st row0206458487
2nd row0226524010
3rd row0206467140
4th row0206496819
5th row0206451844
ValueCountFrequency (%)
02 186
28.2%
0200000000 22
 
3.3%
00000 8
 
1.2%
0 6
 
0.9%
6458401 3
 
0.5%
6920662 2
 
0.3%
26487318 2
 
0.3%
0226427089 2
 
0.3%
0226426567 2
 
0.3%
0226457844 2
 
0.3%
Other values (418) 424
64.3%
2024-05-11T14:31:11.829736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1053
22.3%
2 905
19.2%
6 636
13.5%
9 367
 
7.8%
4 339
 
7.2%
5 283
 
6.0%
3 247
 
5.2%
7 236
 
5.0%
8 227
 
4.8%
225
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4489
95.2%
Space Separator 225
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1053
23.5%
2 905
20.2%
6 636
14.2%
9 367
 
8.2%
4 339
 
7.6%
5 283
 
6.3%
3 247
 
5.5%
7 236
 
5.3%
8 227
 
5.1%
1 196
 
4.4%
Space Separator
ValueCountFrequency (%)
225
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4714
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1053
22.3%
2 905
19.2%
6 636
13.5%
9 367
 
7.8%
4 339
 
7.2%
5 283
 
6.0%
3 247
 
5.2%
7 236
 
5.0%
8 227
 
4.8%
225
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1053
22.3%
2 905
19.2%
6 636
13.5%
9 367
 
7.8%
4 339
 
7.2%
5 283
 
6.0%
3 247
 
5.2%
7 236
 
5.0%
8 227
 
4.8%
225
 
4.8%

소재지면적
Real number (ℝ)

ZEROS 

Distinct381
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.363791
Minimum0
Maximum181.5
Zeros13
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:12.101159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6
Q113.2
median20.35
Q330
95-th percentile78.626
Maximum181.5
Range181.5
Interquartile range (IQR)16.8

Descriptive statistics

Standard deviation23.838304
Coefficient of variation (CV)0.87116232
Kurtosis7.7987981
Mean27.363791
Median Absolute Deviation (MAD)7.85
Skewness2.4427088
Sum16746.64
Variance568.26471
MonotonicityNot monotonic
2024-05-11T14:31:12.343619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 13
 
2.1%
10.0 12
 
2.0%
9.9 12
 
2.0%
26.4 10
 
1.6%
6.6 10
 
1.6%
24.0 9
 
1.5%
13.2 9
 
1.5%
19.8 8
 
1.3%
8.0 8
 
1.3%
16.5 8
 
1.3%
Other values (371) 513
83.8%
ValueCountFrequency (%)
0.0 13
2.1%
2.0 1
 
0.2%
3.0 1
 
0.2%
3.3 4
 
0.7%
3.74 1
 
0.2%
4.0 1
 
0.2%
5.0 1
 
0.2%
5.77 1
 
0.2%
6.0 2
 
0.3%
6.5 1
 
0.2%
ValueCountFrequency (%)
181.5 1
0.2%
160.0 1
0.2%
138.6 2
0.3%
132.8 1
0.2%
132.0 1
0.2%
130.0 1
0.2%
112.0 1
0.2%
110.0 1
0.2%
109.0 1
0.2%
99.0 1
0.2%

소재지우편번호
Text

Distinct92
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T14:31:12.809933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0359477
Min length6

Characters and Unicode

Total characters3694
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)4.1%

Sample

1st row158851
2nd row158851
3rd row158849
4th row158806
5th row158849
ValueCountFrequency (%)
158860 28
 
4.6%
158861 26
 
4.2%
158806 22
 
3.6%
158827 22
 
3.6%
158050 20
 
3.3%
158811 19
 
3.1%
158864 18
 
2.9%
158829 17
 
2.8%
158070 17
 
2.8%
158859 16
 
2.6%
Other values (82) 407
66.5%
2024-05-11T14:31:13.437682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1222
33.1%
1 777
21.0%
5 734
19.9%
0 195
 
5.3%
6 162
 
4.4%
2 143
 
3.9%
4 132
 
3.6%
7 113
 
3.1%
3 99
 
2.7%
9 95
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3672
99.4%
Dash Punctuation 22
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1222
33.3%
1 777
21.2%
5 734
20.0%
0 195
 
5.3%
6 162
 
4.4%
2 143
 
3.9%
4 132
 
3.6%
7 113
 
3.1%
3 99
 
2.7%
9 95
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3694
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1222
33.1%
1 777
21.0%
5 734
19.9%
0 195
 
5.3%
6 162
 
4.4%
2 143
 
3.9%
4 132
 
3.6%
7 113
 
3.1%
3 99
 
2.7%
9 95
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1222
33.1%
1 777
21.0%
5 734
19.9%
0 195
 
5.3%
6 162
 
4.4%
2 143
 
3.9%
4 132
 
3.6%
7 113
 
3.1%
3 99
 
2.7%
9 95
 
2.6%

지번주소
Text

Distinct552
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T14:31:13.969013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length24.632353
Min length18

Characters and Unicode

Total characters15075
Distinct characters177
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique501 ?
Unique (%)81.9%

Sample

1st row서울특별시 양천구 신정동 192-0번지
2nd row서울특별시 양천구 신정동 207-3번지
3rd row서울특별시 양천구 신정동 137-3번지
4th row서울특별시 양천구 목동 405-171번지
5th row서울특별시 양천구 신정동 87-2번지
ValueCountFrequency (%)
서울특별시 612
21.7%
양천구 612
21.7%
신월동 231
 
8.2%
신정동 201
 
7.1%
목동 181
 
6.4%
1층 48
 
1.7%
지하1층 33
 
1.2%
산 12
 
0.4%
내 10
 
0.4%
2층 8
 
0.3%
Other values (628) 874
31.0%
2024-05-11T14:31:14.889461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2759
18.3%
1 714
 
4.7%
동 657
 
4.4%
시 617
 
4.1%
양 614
 
4.1%
천 614
 
4.1%
서 613
 
4.1%
별 612
 
4.1%
울 612
 
4.1%
구 612
 
4.1%
Other values (167) 6651
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8678
57.6%
Decimal Number 3024
 
20.1%
Space Separator 2759
 
18.3%
Dash Punctuation 562
 
3.7%
Uppercase Letter 19
 
0.1%
Open Punctuation 16
 
0.1%
Close Punctuation 16
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 657
 
7.6%
시 617
 
7.1%
양 614
 
7.1%
천 614
 
7.1%
서 613
 
7.1%
별 612
 
7.1%
울 612
 
7.1%
구 612
 
7.1%
특 612
 
7.1%
지 578
 
6.7%
Other values (146) 2537
29.2%
Decimal Number
ValueCountFrequency (%)
1 714
23.6%
2 396
13.1%
9 290
9.6%
0 284
 
9.4%
4 245
 
8.1%
3 243
 
8.0%
7 235
 
7.8%
5 218
 
7.2%
8 205
 
6.8%
6 194
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
B 8
42.1%
S 4
21.1%
A 4
21.1%
K 1
 
5.3%
T 1
 
5.3%
W 1
 
5.3%
Space Separator
ValueCountFrequency (%)
2759
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 562
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8678
57.6%
Common 6378
42.3%
Latin 19
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 657
 
7.6%
시 617
 
7.1%
양 614
 
7.1%
천 614
 
7.1%
서 613
 
7.1%
별 612
 
7.1%
울 612
 
7.1%
구 612
 
7.1%
특 612
 
7.1%
지 578
 
6.7%
Other values (146) 2537
29.2%
Common
ValueCountFrequency (%)
2759
43.3%
1 714
 
11.2%
- 562
 
8.8%
2 396
 
6.2%
9 290
 
4.5%
0 284
 
4.5%
4 245
 
3.8%
3 243
 
3.8%
7 235
 
3.7%
5 218
 
3.4%
Other values (5) 432
 
6.8%
Latin
ValueCountFrequency (%)
B 8
42.1%
S 4
21.1%
A 4
21.1%
K 1
 
5.3%
T 1
 
5.3%
W 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8678
57.6%
ASCII 6397
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2759
43.1%
1 714
 
11.2%
- 562
 
8.8%
2 396
 
6.2%
9 290
 
4.5%
0 284
 
4.4%
4 245
 
3.8%
3 243
 
3.8%
7 235
 
3.7%
5 218
 
3.4%
Other values (11) 451
 
7.1%
Hangul
ValueCountFrequency (%)
동 657
 
7.6%
시 617
 
7.1%
양 614
 
7.1%
천 614
 
7.1%
서 613
 
7.1%
별 612
 
7.1%
울 612
 
7.1%
구 612
 
7.1%
특 612
 
7.1%
지 578
 
6.7%
Other values (146) 2537
29.2%

도로명주소
Text

MISSING 

Distinct200
Distinct (%)96.6%
Missing405
Missing (%)66.2%
Memory size4.9 KiB
2024-05-11T14:31:15.420296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length33.289855
Min length22

Characters and Unicode

Total characters6891
Distinct characters164
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)93.7%

Sample

1st row서울특별시 양천구 목동남로4길 41 (신정동)
2nd row서울특별시 양천구 신목로2길 35-1 (신정동)
3rd row서울특별시 양천구 곰달래로 15 (신월동)
4th row서울특별시 양천구 목동중앙본로7길 42 (목동)
5th row서울특별시 양천구 가로공원로60길 12, 1층 (신월동)
ValueCountFrequency (%)
서울특별시 207
 
14.9%
양천구 207
 
14.9%
1층 95
 
6.8%
신월동 76
 
5.5%
목동 66
 
4.8%
신정동 58
 
4.2%
지하1층 21
 
1.5%
2층 18
 
1.3%
지하 13
 
0.9%
내 13
 
0.9%
Other values (332) 613
44.2%
2024-05-11T14:31:16.132308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1181
 
17.1%
동 343
 
5.0%
1 315
 
4.6%
서 221
 
3.2%
양 218
 
3.2%
, 216
 
3.1%
로 216
 
3.1%
시 211
 
3.1%
) 210
 
3.0%
( 210
 
3.0%
Other values (154) 3550
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4053
58.8%
Space Separator 1181
 
17.1%
Decimal Number 978
 
14.2%
Other Punctuation 216
 
3.1%
Close Punctuation 210
 
3.0%
Open Punctuation 210
 
3.0%
Dash Punctuation 32
 
0.5%
Uppercase Letter 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 343
 
8.5%
서 221
 
5.5%
양 218
 
5.4%
로 216
 
5.3%
시 211
 
5.2%
천 208
 
5.1%
별 207
 
5.1%
구 207
 
5.1%
울 207
 
5.1%
특 207
 
5.1%
Other values (135) 1808
44.6%
Decimal Number
ValueCountFrequency (%)
1 315
32.2%
2 144
14.7%
3 105
 
10.7%
0 88
 
9.0%
4 83
 
8.5%
5 69
 
7.1%
6 49
 
5.0%
7 43
 
4.4%
9 43
 
4.4%
8 39
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 7
63.6%
S 2
 
18.2%
A 1
 
9.1%
C 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1181
100.0%
Other Punctuation
ValueCountFrequency (%)
, 216
100.0%
Close Punctuation
ValueCountFrequency (%)
) 210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4053
58.8%
Common 2827
41.0%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 343
 
8.5%
서 221
 
5.5%
양 218
 
5.4%
로 216
 
5.3%
시 211
 
5.2%
천 208
 
5.1%
별 207
 
5.1%
구 207
 
5.1%
울 207
 
5.1%
특 207
 
5.1%
Other values (135) 1808
44.6%
Common
ValueCountFrequency (%)
1181
41.8%
1 315
 
11.1%
, 216
 
7.6%
) 210
 
7.4%
( 210
 
7.4%
2 144
 
5.1%
3 105
 
3.7%
0 88
 
3.1%
4 83
 
2.9%
5 69
 
2.4%
Other values (5) 206
 
7.3%
Latin
ValueCountFrequency (%)
B 7
63.6%
S 2
 
18.2%
A 1
 
9.1%
C 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4053
58.8%
ASCII 2838
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1181
41.6%
1 315
 
11.1%
, 216
 
7.6%
) 210
 
7.4%
( 210
 
7.4%
2 144
 
5.1%
3 105
 
3.7%
0 88
 
3.1%
4 83
 
2.9%
5 69
 
2.4%
Other values (9) 217
 
7.6%
Hangul
ValueCountFrequency (%)
동 343
 
8.5%
서 221
 
5.5%
양 218
 
5.4%
로 216
 
5.3%
시 211
 
5.2%
천 208
 
5.1%
별 207
 
5.1%
구 207
 
5.1%
울 207
 
5.1%
특 207
 
5.1%
Other values (135) 1808
44.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)48.8%
Missing405
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean7989.8019
Minimum7900
Maximum8106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:16.679162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7906
Q17936
median7983
Q38031
95-th percentile8090.5
Maximum8106
Range206
Interquartile range (IQR)95

Descriptive statistics

Standard deviation60.077817
Coefficient of variation (CV)0.0075193124
Kurtosis-1.0972083
Mean7989.8019
Median Absolute Deviation (MAD)47
Skewness0.28140792
Sum1653889
Variance3609.3441
MonotonicityNot monotonic
2024-05-11T14:31:16.927433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8007 7
 
1.1%
8022 6
 
1.0%
7904 5
 
0.8%
8086 5
 
0.8%
7961 5
 
0.8%
7906 4
 
0.7%
8042 4
 
0.7%
7983 4
 
0.7%
7928 4
 
0.7%
7920 4
 
0.7%
Other values (91) 159
 
26.0%
(Missing) 405
66.2%
ValueCountFrequency (%)
7900 2
 
0.3%
7902 1
 
0.2%
7903 1
 
0.2%
7904 5
0.8%
7906 4
0.7%
7909 1
 
0.2%
7910 1
 
0.2%
7911 1
 
0.2%
7912 3
0.5%
7913 1
 
0.2%
ValueCountFrequency (%)
8106 1
 
0.2%
8104 2
 
0.3%
8101 4
0.7%
8100 1
 
0.2%
8096 2
 
0.3%
8092 1
 
0.2%
8087 3
0.5%
8086 5
0.8%
8085 3
0.5%
8082 1
 
0.2%

사업장명
Text

Distinct489
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T14:31:17.486853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.7156863
Min length1

Characters and Unicode

Total characters2886
Distinct characters299
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique412 ?
Unique (%)67.3%

Sample

1st row고바우
2nd row신진
3rd row대구
4th row대중
5th row대중
ValueCountFrequency (%)
이용원 12
 
1.8%
오땡큐 8
 
1.2%
현대이용원 8
 
1.2%
신월 6
 
0.9%
바버샵 5
 
0.8%
양천이용원 4
 
0.6%
대우이용원 4
 
0.6%
청수이용원 4
 
0.6%
서울이용원 4
 
0.6%
새마음 4
 
0.6%
Other values (486) 595
91.0%
2024-05-11T14:31:18.279170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 357
 
12.4%
용 271
 
9.4%
원 254
 
8.8%
발 75
 
2.6%
우 74
 
2.6%
대 60
 
2.1%
사 55
 
1.9%
동 54
 
1.9%
나 52
 
1.8%
관 48
 
1.7%
Other values (289) 1586
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2799
97.0%
Space Separator 43
 
1.5%
Uppercase Letter 15
 
0.5%
Decimal Number 10
 
0.3%
Close Punctuation 9
 
0.3%
Open Punctuation 9
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 357
 
12.8%
용 271
 
9.7%
원 254
 
9.1%
발 75
 
2.7%
우 74
 
2.6%
대 60
 
2.1%
사 55
 
2.0%
동 54
 
1.9%
나 52
 
1.9%
관 48
 
1.7%
Other values (275) 1499
53.6%
Uppercase Letter
ValueCountFrequency (%)
S 6
40.0%
B 3
20.0%
I 2
 
13.3%
V 2
 
13.3%
P 2
 
13.3%
Decimal Number
ValueCountFrequency (%)
2 3
30.0%
1 2
20.0%
8 2
20.0%
3 2
20.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2799
97.0%
Common 72
 
2.5%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 357
 
12.8%
용 271
 
9.7%
원 254
 
9.1%
발 75
 
2.7%
우 74
 
2.6%
대 60
 
2.1%
사 55
 
2.0%
동 54
 
1.9%
나 52
 
1.9%
관 48
 
1.7%
Other values (275) 1499
53.6%
Common
ValueCountFrequency (%)
43
59.7%
) 9
 
12.5%
( 9
 
12.5%
2 3
 
4.2%
1 2
 
2.8%
8 2
 
2.8%
3 2
 
2.8%
7 1
 
1.4%
- 1
 
1.4%
Latin
ValueCountFrequency (%)
S 6
40.0%
B 3
20.0%
I 2
 
13.3%
V 2
 
13.3%
P 2
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2799
97.0%
ASCII 87
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 357
 
12.8%
용 271
 
9.7%
원 254
 
9.1%
발 75
 
2.7%
우 74
 
2.6%
대 60
 
2.1%
사 55
 
2.0%
동 54
 
1.9%
나 52
 
1.9%
관 48
 
1.7%
Other values (275) 1499
53.6%
ASCII
ValueCountFrequency (%)
43
49.4%
) 9
 
10.3%
( 9
 
10.3%
S 6
 
6.9%
2 3
 
3.4%
B 3
 
3.4%
I 2
 
2.3%
1 2
 
2.3%
V 2
 
2.3%
P 2
 
2.3%
Other values (4) 6
 
6.9%

최종수정일자
Date

Distinct391
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1999-01-14 00:00:00
Maximum2024-05-07 13:47:22
2024-05-11T14:31:18.530998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:18.821665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
I
478 
U
134 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 478
78.1%
U 134
 
21.9%

Length

2024-05-11T14:31:19.070978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:19.291160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 478
78.1%
u 134
 
21.9%

데이터갱신일자
Date

Distinct117
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:31:19.505377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:31:19.819980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반이용업
608 
이용업 기타
 
4

Length

Max length6
Median length5
Mean length5.0065359
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 608
99.3%
이용업 기타 4
 
0.7%

Length

2024-05-11T14:31:20.048121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:20.210592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 608
98.7%
이용업 4
 
0.6%
기타 4
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct398
Distinct (%)69.3%
Missing38
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean187044.47
Minimum184242.73
Maximum189749.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:20.370809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184242.73
5-th percentile184764.67
Q1185751.78
median187269.29
Q3188064.35
95-th percentile188983.39
Maximum189749.78
Range5507.0463
Interquartile range (IQR)2312.5662

Descriptive statistics

Standard deviation1378.1513
Coefficient of variation (CV)0.0073680407
Kurtosis-1.2069036
Mean187044.47
Median Absolute Deviation (MAD)1184.1428
Skewness-0.24378494
Sum1.0736353 × 108
Variance1899301
MonotonicityNot monotonic
2024-05-11T14:31:20.701617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189151.208015925 9
 
1.5%
185478.063988449 7
 
1.1%
189021.797866206 7
 
1.1%
187520.306766633 6
 
1.0%
186357.984760281 6
 
1.0%
184806.911534822 6
 
1.0%
187531.38903074 5
 
0.8%
188605.762730565 5
 
0.8%
187922.26264924 4
 
0.7%
187957.763929332 4
 
0.7%
Other values (388) 515
84.2%
(Missing) 38
 
6.2%
ValueCountFrequency (%)
184242.730019702 1
0.2%
184413.184233757 1
0.2%
184457.852171363 1
0.2%
184487.550160698 1
0.2%
184528.724474679 1
0.2%
184531.725955665 1
0.2%
184537.639604228 1
0.2%
184571.315447564 1
0.2%
184582.382083153 1
0.2%
184597.4496425 1
0.2%
ValueCountFrequency (%)
189749.776358917 1
 
0.2%
189423.528553032 2
 
0.3%
189280.689807363 1
 
0.2%
189151.208015925 9
1.5%
189084.800934932 1
 
0.2%
189042.496526196 3
 
0.5%
189036.127630103 1
 
0.2%
189021.797866206 7
1.1%
189004.157251782 2
 
0.3%
188992.794245115 2
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct398
Distinct (%)69.3%
Missing38
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean447308.81
Minimum444842.31
Maximum449785.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:20.961942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444842.31
5-th percentile445996.7
Q1446567.22
median447054.07
Q3448120.78
95-th percentile449342.43
Maximum449785.23
Range4942.9217
Interquartile range (IQR)1553.5592

Descriptive statistics

Standard deviation1025.6149
Coefficient of variation (CV)0.0022928566
Kurtosis-0.4176413
Mean447308.81
Median Absolute Deviation (MAD)696.77027
Skewness0.4142523
Sum2.5675525 × 108
Variance1051886
MonotonicityNot monotonic
2024-05-11T14:31:21.210208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448200.067716589 9
 
1.5%
446309.072252909 7
 
1.1%
446740.576354849 7
 
1.1%
446450.347274241 6
 
1.0%
446590.916612838 6
 
1.0%
448551.489178583 6
 
1.0%
447310.609246804 5
 
0.8%
448342.943184802 5
 
0.8%
448410.335423139 4
 
0.7%
448923.320680584 4
 
0.7%
Other values (388) 515
84.2%
(Missing) 38
 
6.2%
ValueCountFrequency (%)
444842.305705773 2
0.3%
445081.396522145 2
0.3%
445155.081213627 2
0.3%
445202.600824056 2
0.3%
445203.905798912 2
0.3%
445224.946263915 1
0.2%
445229.76179636 1
0.2%
445428.447103333 2
0.3%
445655.04439912 1
0.2%
445678.076325463 2
0.3%
ValueCountFrequency (%)
449785.227427003 2
0.3%
449728.279227887 1
 
0.2%
449683.219205227 3
0.5%
449665.710786217 1
 
0.2%
449656.729753851 1
 
0.2%
449615.339955719 1
 
0.2%
449607.118627628 2
0.3%
449588.385660235 1
 
0.2%
449507.023242441 1
 
0.2%
449502.116638432 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반이용업
567 
<NA>
 
42
이용업 기타
 
3

Length

Max length6
Median length5
Mean length4.9362745
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 567
92.6%
<NA> 42
 
6.9%
이용업 기타 3
 
0.5%

Length

2024-05-11T14:31:21.480583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:21.701725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 567
92.2%
na 42
 
6.8%
이용업 3
 
0.5%
기타 3
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.3%
Missing398
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean0.36915888
Minimum0
Maximum15
Zeros189
Zeros (%)30.9%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:21.873209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3938774
Coefficient of variation (CV)3.7758197
Kurtosis58.586821
Mean0.36915888
Median Absolute Deviation (MAD)0
Skewness6.5516569
Sum79
Variance1.9428941
MonotonicityNot monotonic
2024-05-11T14:31:22.080836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 189
30.9%
1 8
 
1.3%
4 7
 
1.1%
3 4
 
0.7%
2 3
 
0.5%
5 2
 
0.3%
15 1
 
0.2%
(Missing) 398
65.0%
ValueCountFrequency (%)
0 189
30.9%
1 8
 
1.3%
2 3
 
0.5%
3 4
 
0.7%
4 7
 
1.1%
5 2
 
0.3%
15 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
5 2
 
0.3%
4 7
 
1.1%
3 4
 
0.7%
2 3
 
0.5%
1 8
 
1.3%
0 189
30.9%

건물지하층수
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
403 
0
192 
1
 
16
3
 
1

Length

Max length4
Median length4
Mean length2.9754902
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 403
65.8%
0 192
31.4%
1 16
 
2.6%
3 1
 
0.2%

Length

2024-05-11T14:31:22.317214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:22.504004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 403
65.8%
0 192
31.4%
1 16
 
2.6%
3 1
 
0.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.8%
Missing363
Missing (%)59.3%
Infinite0
Infinite (%)0.0%
Mean1.0562249
Minimum0
Maximum7
Zeros65
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:22.679895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0262931
Coefficient of variation (CV)0.97166157
Kurtosis8.3260214
Mean1.0562249
Median Absolute Deviation (MAD)0
Skewness2.2332978
Sum263
Variance1.0532776
MonotonicityNot monotonic
2024-05-11T14:31:22.860785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 137
 
22.4%
0 65
 
10.6%
2 30
 
4.9%
3 9
 
1.5%
4 5
 
0.8%
6 2
 
0.3%
7 1
 
0.2%
(Missing) 363
59.3%
ValueCountFrequency (%)
0 65
10.6%
1 137
22.4%
2 30
 
4.9%
3 9
 
1.5%
4 5
 
0.8%
6 2
 
0.3%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
6 2
 
0.3%
4 5
 
0.8%
3 9
 
1.5%
2 30
 
4.9%
1 137
22.4%
0 65
10.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.0%
Missing414
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean1.2626263
Minimum0
Maximum6
Zeros18
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:23.081091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.89085436
Coefficient of variation (CV)0.70555665
Kurtosis8.3301022
Mean1.2626263
Median Absolute Deviation (MAD)0
Skewness2.2864172
Sum250
Variance0.79362149
MonotonicityNot monotonic
2024-05-11T14:31:23.284425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 135
 
22.1%
2 30
 
4.9%
0 18
 
2.9%
3 9
 
1.5%
4 4
 
0.7%
6 2
 
0.3%
(Missing) 414
67.6%
ValueCountFrequency (%)
0 18
 
2.9%
1 135
22.1%
2 30
 
4.9%
3 9
 
1.5%
4 4
 
0.7%
6 2
 
0.3%
ValueCountFrequency (%)
6 2
 
0.3%
4 4
 
0.7%
3 9
 
1.5%
2 30
 
4.9%
1 135
22.1%
0 18
 
2.9%

사용시작지하층
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
430 
0
103 
1
75 
2
 
3
6
 
1

Length

Max length4
Median length4
Mean length3.1078431
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 430
70.3%
0 103
 
16.8%
1 75
 
12.3%
2 3
 
0.5%
6 1
 
0.2%

Length

2024-05-11T14:31:23.541396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:23.727824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 430
70.3%
0 103
 
16.8%
1 75
 
12.3%
2 3
 
0.5%
6 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
477 
1
75 
0
56 
2
 
3
6
 
1

Length

Max length4
Median length4
Mean length3.3382353
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 477
77.9%
1 75
 
12.3%
0 56
 
9.2%
2 3
 
0.5%
6 1
 
0.2%

Length

2024-05-11T14:31:23.948674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:24.161910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 477
77.9%
1 75
 
12.3%
0 56
 
9.2%
2 3
 
0.5%
6 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
315 
0
297 

Length

Max length4
Median length4
Mean length2.5441176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 315
51.5%
0 297
48.5%

Length

2024-05-11T14:31:24.388742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:24.570043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
51.5%
0 297
48.5%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
315 
0
297 

Length

Max length4
Median length4
Mean length2.5441176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 315
51.5%
0 297
48.5%

Length

2024-05-11T14:31:24.733534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:24.918429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
51.5%
0 297
48.5%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
315 
0
297 

Length

Max length4
Median length4
Mean length2.5441176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 315
51.5%
0 297
48.5%

Length

2024-05-11T14:31:25.119591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:25.336325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
51.5%
0 297
48.5%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing48
Missing (%)7.8%
Memory size1.3 KiB
False
564 
(Missing)
 
48
ValueCountFrequency (%)
False 564
92.2%
(Missing) 48
 
7.8%
2024-05-11T14:31:25.481190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)2.4%
Missing117
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean3.5090909
Minimum0
Maximum11
Zeros13
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T14:31:25.686090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile8
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0870281
Coefficient of variation (CV)0.59474895
Kurtosis1.8569456
Mean3.5090909
Median Absolute Deviation (MAD)1
Skewness1.4252419
Sum1737
Variance4.3556864
MonotonicityNot monotonic
2024-05-11T14:31:25.899133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 170
27.8%
2 137
22.4%
4 67
 
10.9%
7 26
 
4.2%
5 20
 
3.3%
8 15
 
2.5%
1 15
 
2.5%
0 13
 
2.1%
6 11
 
1.8%
9 10
 
1.6%
Other values (2) 11
 
1.8%
(Missing) 117
19.1%
ValueCountFrequency (%)
0 13
 
2.1%
1 15
 
2.5%
2 137
22.4%
3 170
27.8%
4 67
 
10.9%
5 20
 
3.3%
6 11
 
1.8%
7 26
 
4.2%
8 15
 
2.5%
9 10
 
1.6%
ValueCountFrequency (%)
11 2
 
0.3%
10 9
 
1.5%
9 10
 
1.6%
8 15
 
2.5%
7 26
 
4.2%
6 11
 
1.8%
5 20
 
3.3%
4 67
 
10.9%
3 170
27.8%
2 137
22.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing612
Missing (%)100.0%
Memory size5.5 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
564 
임대
 
46
자가
 
2

Length

Max length4
Median length4
Mean length3.8431373
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 564
92.2%
임대 46
 
7.5%
자가 2
 
0.3%

Length

2024-05-11T14:31:26.160614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:26.373354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 564
92.2%
임대 46
 
7.5%
자가 2
 
0.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
457 
0
155 

Length

Max length4
Median length4
Mean length3.2401961
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 457
74.7%
0 155
 
25.3%

Length

2024-05-11T14:31:26.610351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:26.766869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 457
74.7%
0 155
 
25.3%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
552 
0
60 

Length

Max length4
Median length4
Mean length3.7058824
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> 552
90.2%
0 60
 
9.8%

Length

2024-05-11T14:31:26.964817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:27.496496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 552
90.2%
0 60
 
9.8%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
552 
0
59 
1
 
1

Length

Max length4
Median length4
Mean length3.7058824
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 552
90.2%
0 59
 
9.6%
1 1
 
0.2%

Length

2024-05-11T14:31:27.685043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:27.867944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 552
90.2%
0 59
 
9.6%
1 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
469 
0
143 

Length

Max length4
Median length4
Mean length3.2990196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 469
76.6%
0 143
 
23.4%

Length

2024-05-11T14:31:28.100998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:28.269853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 469
76.6%
0 143
 
23.4%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
471 
0
141 

Length

Max length4
Median length4
Mean length3.3088235
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 471
77.0%
0 141
 
23.0%

Length

2024-05-11T14:31:28.451093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:31:28.624699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 471
77.0%
0 141
 
23.0%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing42
Missing (%)6.9%
Memory size1.3 KiB
False
570 
(Missing)
 
42
ValueCountFrequency (%)
False 570
93.1%
(Missing) 42
 
6.9%
2024-05-11T14:31:28.739502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031400003140000-203-1970-0013919701026<NA>3폐업2폐업20030225<NA><NA><NA>020645848717.04158851서울특별시 양천구 신정동 192-0번지<NA><NA>고바우2003-03-19 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131400003140000-203-1970-0014119700313<NA>1영업/정상1영업<NA><NA><NA><NA>022652401015.05158851서울특별시 양천구 신정동 207-3번지서울특별시 양천구 목동남로4길 41 (신정동)8101신진2019-12-19 20:18:50U2019-12-21 02:40:00.0일반이용업188130.687257445224.946264일반이용업001100000N3<NA><NA><NA><NA>0<NA><NA>00N
231400003140000-203-1970-0017919700522<NA>3폐업2폐업20030225<NA><NA><NA>020646714025.2158849서울특별시 양천구 신정동 137-3번지<NA><NA>대구2003-03-19 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N5<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331400003140000-203-1970-0020719700603<NA>3폐업2폐업19941128<NA><NA><NA>020649681911.2158806서울특별시 양천구 목동 405-171번지<NA><NA>대중1999-01-21 00:00:00I2018-08-31 23:59:59.0일반이용업188590.49471446929.520545일반이용업<NA><NA><NA><NA><NA><NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431400003140000-203-1971-0014419710119<NA>3폐업2폐업19940125<NA><NA><NA>020645184424.0158849서울특별시 양천구 신정동 87-2번지<NA><NA>대중1999-01-21 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531400003140000-203-1971-0014719710106<NA>3폐업2폐업20170609<NA><NA><NA>022646074019.8158849서울특별시 양천구 신정동 127-18번지서울특별시 양천구 신목로2길 35-1 (신정동)8009정성이발관2017-06-09 13:57:11I2018-08-31 23:59:59.0일반이용업189036.12763446531.082453일반이용업001100000N3<NA><NA><NA><NA>0<NA><NA><NA><NA>N
631400003140000-203-1973-0019219730917<NA>3폐업2폐업20030225<NA><NA><NA>020695142515.24158811서울특별시 양천구 목동 630-12번지<NA><NA>오복2003-03-19 00:00:00I2018-08-31 23:59:59.0일반이용업188020.204308449285.730373일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731400003140000-203-1973-0024019731030<NA>3폐업2폐업20190509<NA><NA><NA>022699432414.08158827서울특별시 양천구 신월동 126-36번지서울특별시 양천구 곰달래로 15 (신월동)7921부강2019-05-09 11:37:06U2019-05-11 02:40:00.0일반이용업185285.79645447534.917611일반이용업<NA><NA>11<NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831400003140000-203-1974-0015319740418<NA>3폐업2폐업20030225<NA><NA><NA>020000000013.5158863서울특별시 양천구 신정동 1168-15번지<NA><NA>현대2003-03-19 00:00:00I2018-08-31 23:59:59.0일반이용업186792.484379446080.719947일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931400003140000-203-1975-0024119750703<NA>3폐업2폐업20041210<NA><NA><NA>020698060815.2158827서울특별시 양천구 신월동 124-1번지<NA><NA>금성2003-12-19 00:00:00I2018-08-31 23:59:59.0일반이용업185284.860102447721.611436일반이용업<NA><NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
60231400003140000-203-2022-0000520221206<NA>1영업/정상1영업<NA><NA><NA><NA>02 2699275327.0158828서울특별시 양천구 신월동 135-28서울특별시 양천구 남부순환로59길 9, 1층 (신월동)7920오땡큐2022-12-06 09:46:39I2021-11-02 00:08:00.0일반이용업185103.6109447799.921503<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60331400003140000-203-2022-000062022-12-07<NA>3폐업2폐업2024-01-10<NA><NA><NA>02 2602582826.0158-860서울특별시 양천구 신정동 990-19서울특별시 양천구 오목로48길 10, 1층 일부호 (신정동)8022바버샵 엉클부스2024-01-10 13:21:49U2023-11-30 23:03:00.0일반이용업187803.22485446983.913501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60431400003140000-203-2023-000012023-02-07<NA>3폐업2폐업2023-12-11<NA><NA><NA><NA>10.0158-877서울특별시 양천구 목동 907 현대월드타워서울특별시 양천구 목동서로 77, 현대월드타워 지하1층 B118호 (목동)7983현대월드사우나 남탕 이발소2023-12-11 11:43:29U2022-11-01 23:03:00.0일반이용업189151.208016448200.067717<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60531400003140000-203-2023-000022023-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>109.0158-050서울특별시 양천구 목동 917-6 중소기업유통센터(행복한백화점)서울특별시 양천구 목동동로 309, 중소기업유통센터(행복한백화점) 3층 301호 (목동)7997버터맨즈헤어바버샵2023-03-06 15:47:02I2022-12-03 00:08:00.0일반이용업188977.17105447466.355031<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60631400003140000-203-2023-000032023-03-13<NA>3폐업2폐업2023-04-30<NA><NA><NA><NA>23.76158-836서울특별시 양천구 신월동 463-8서울특별시 양천구 월정로8길 12, 1층 101호 (신월동)7931탑남성컷트2023-08-28 13:53:49U2022-12-07 21:00:00.0일반이용업186086.129251447014.877464<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60731400003140000-203-2023-000042023-08-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 2608102828.14158-860서울특별시 양천구 신정동 992-1 보성팰리스 212호서울특별시 양천구 오목로 232, 2층 212호 (신정동, 보성팰리스)8022레스트 바버샵2023-08-30 13:15:06I2022-12-09 00:01:00.0일반이용업187822.906667447060.377699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60831400003140000-203-2024-000012024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA>05071343582823.07158-860서울특별시 양천구 신정동 990-19 1층 일부 좌측호서울특별시 양천구 오목로48길 10, 1층 좌측호 (신정동)8022바버샵 엉클부스 목동점2024-01-12 15:14:59I2023-11-30 23:04:00.0일반이용업187803.22485446983.913501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60931400003140000-203-2024-000022024-01-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0158-877서울특별시 양천구 목동 907 현대월드타워 지하1층 118호서울특별시 양천구 목동서로 77, 현대월드타워 지하1층 118호 (목동)7983현대이용원2024-01-22 11:21:13I2023-11-30 22:04:00.0일반이용업189151.208016448200.067717<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61031400003140000-203-2024-000032024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0158-862서울특별시 양천구 신정동 1050-9 1층 일부서울특별시 양천구 중앙로36길 12-1, 1층 (신정동)8085아이언바버샵2024-04-29 15:45:45I2023-12-05 00:01:00.0일반이용업187146.855481446362.774454<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61131400003140000-203-2024-000042024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0158-846서울특별시 양천구 신월동 986-8 용민아파트 106호 일부서울특별시 양천구 지양로 25, 1층 106호 (신월동, 용민아파트)8042정정헤어2024-05-07 13:47:22I2023-12-05 00:09:00.0일반이용업185511.223568446283.271989<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>