Overview

Dataset statistics

Number of variables47
Number of observations390
Missing cells4145
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory154.4 KiB
Average record size in memory405.3 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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-17944/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (93.5%)Imbalance
위생업태명 is highly imbalanced (77.4%)Imbalance
사용끝지하층 is highly imbalanced (67.8%)Imbalance
건물소유구분명 is highly imbalanced (66.0%)Imbalance
여성종사자수 is highly imbalanced (81.8%)Imbalance
남성종사자수 is highly imbalanced (74.4%)Imbalance
다중이용업소여부 is highly imbalanced (97.3%)Imbalance
인허가취소일자 has 390 (100.0%) missing valuesMissing
폐업일자 has 76 (19.5%) missing valuesMissing
휴업시작일자 has 390 (100.0%) missing valuesMissing
휴업종료일자 has 390 (100.0%) missing valuesMissing
재개업일자 has 390 (100.0%) missing valuesMissing
전화번호 has 68 (17.4%) missing valuesMissing
도로명주소 has 257 (65.9%) missing valuesMissing
도로명우편번호 has 258 (66.2%) missing valuesMissing
좌표정보(X) has 13 (3.3%) missing valuesMissing
좌표정보(Y) has 13 (3.3%) missing valuesMissing
건물지상층수 has 164 (42.1%) missing valuesMissing
사용시작지상층 has 165 (42.3%) missing valuesMissing
사용끝지상층 has 315 (80.8%) missing valuesMissing
발한실여부 has 25 (6.4%) missing valuesMissing
좌석수 has 39 (10.0%) missing valuesMissing
조건부허가신고사유 has 390 (100.0%) missing valuesMissing
조건부허가시작일자 has 390 (100.0%) missing valuesMissing
조건부허가종료일자 has 390 (100.0%) missing valuesMissing
다중이용업소여부 has 22 (5.6%) 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 46 (11.8%) zerosZeros
건물지상층수 has 169 (43.3%) zerosZeros
사용시작지상층 has 156 (40.0%) zerosZeros
사용끝지상층 has 23 (5.9%) zerosZeros
좌석수 has 18 (4.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:06:27.298878
Analysis finished2024-05-11 06:06:28.521929
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3170000
390 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 390
100.0%

Length

2024-05-11T15:06:28.643242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:28.823655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 390
100.0%

관리번호
Text

UNIQUE 

Distinct390
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:06:29.197782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8580
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

Unique390 ?
Unique (%)100.0%

Sample

1st row3170000-203-1976-01103
2nd row3170000-203-1977-01104
3rd row3170000-203-1977-01120
4th row3170000-203-1978-01105
5th row3170000-203-1978-01106
ValueCountFrequency (%)
3170000-203-1976-01103 1
 
0.3%
3170000-203-1999-01260 1
 
0.3%
3170000-203-2001-01319 1
 
0.3%
3170000-203-2001-01317 1
 
0.3%
3170000-203-2001-01309 1
 
0.3%
3170000-203-2001-01295 1
 
0.3%
3170000-203-2001-01294 1
 
0.3%
3170000-203-2001-01290 1
 
0.3%
3170000-203-2001-01288 1
 
0.3%
3170000-203-2001-01278 1
 
0.3%
Other values (380) 380
97.4%
2024-05-11T15:06:29.773443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3128
36.5%
- 1170
 
13.6%
1 1143
 
13.3%
3 896
 
10.4%
2 729
 
8.5%
7 518
 
6.0%
9 474
 
5.5%
8 222
 
2.6%
5 109
 
1.3%
4 99
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7410
86.4%
Dash Punctuation 1170
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3128
42.2%
1 1143
 
15.4%
3 896
 
12.1%
2 729
 
9.8%
7 518
 
7.0%
9 474
 
6.4%
8 222
 
3.0%
5 109
 
1.5%
4 99
 
1.3%
6 92
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3128
36.5%
- 1170
 
13.6%
1 1143
 
13.3%
3 896
 
10.4%
2 729
 
8.5%
7 518
 
6.0%
9 474
 
5.5%
8 222
 
2.6%
5 109
 
1.3%
4 99
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3128
36.5%
- 1170
 
13.6%
1 1143
 
13.3%
3 896
 
10.4%
2 729
 
8.5%
7 518
 
6.0%
9 474
 
5.5%
8 222
 
2.6%
5 109
 
1.3%
4 99
 
1.2%

인허가일자
Date

Distinct341
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1976-12-01 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T15:06:30.395323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:30.641229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3
314 
1
76 

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 (%)
3 314
80.5%
1 76
 
19.5%

Length

2024-05-11T15:06:30.874288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:31.048293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 314
80.5%
1 76
 
19.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
314 
영업/정상
76 

Length

Max length5
Median length2
Mean length2.5846154
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 314
80.5%
영업/정상 76
 
19.5%

Length

2024-05-11T15:06:31.237260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:31.427316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 314
80.5%
영업/정상 76
 
19.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2
314 
1
76 

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 (%)
2 314
80.5%
1 76
 
19.5%

Length

2024-05-11T15:06:31.633386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:31.798021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 314
80.5%
1 76
 
19.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
314 
영업
76 

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 314
80.5%
영업 76
 
19.5%

Length

2024-05-11T15:06:31.937652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:32.104828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 314
80.5%
영업 76
 
19.5%

폐업일자
Date

MISSING 

Distinct257
Distinct (%)81.8%
Missing76
Missing (%)19.5%
Memory size3.2 KiB
Minimum1994-08-05 00:00:00
Maximum2024-04-23 00:00:00
2024-05-11T15:06:32.285180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:32.487717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

전화번호
Text

MISSING 

Distinct281
Distinct (%)87.3%
Missing68
Missing (%)17.4%
Memory size3.2 KiB
2024-05-11T15:06:32.940678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.826087
Min length2

Characters and Unicode

Total characters3164
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

Unique269 ?
Unique (%)83.5%

Sample

1st row02 8025075
2nd row02 8026955
3rd row02 8031680
4th row0208052378
5th row0200000000
ValueCountFrequency (%)
02 266
44.7%
0200000000 15
 
2.5%
0 10
 
1.7%
00000 7
 
1.2%
8539082 2
 
0.3%
806 2
 
0.3%
808 2
 
0.3%
8048924 2
 
0.3%
8080111 2
 
0.3%
8569669 2
 
0.3%
Other values (280) 285
47.9%
2024-05-11T15:06:33.610807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 754
23.8%
2 472
14.9%
8 423
13.4%
319
10.1%
5 223
 
7.0%
6 193
 
6.1%
9 188
 
5.9%
3 160
 
5.1%
4 159
 
5.0%
1 138
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2845
89.9%
Space Separator 319
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 754
26.5%
2 472
16.6%
8 423
14.9%
5 223
 
7.8%
6 193
 
6.8%
9 188
 
6.6%
3 160
 
5.6%
4 159
 
5.6%
1 138
 
4.9%
7 135
 
4.7%
Space Separator
ValueCountFrequency (%)
319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 754
23.8%
2 472
14.9%
8 423
13.4%
319
10.1%
5 223
 
7.0%
6 193
 
6.1%
9 188
 
5.9%
3 160
 
5.1%
4 159
 
5.0%
1 138
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 754
23.8%
2 472
14.9%
8 423
13.4%
319
10.1%
5 223
 
7.0%
6 193
 
6.1%
9 188
 
5.9%
3 160
 
5.1%
4 159
 
5.0%
1 138
 
4.4%

소재지면적
Real number (ℝ)

ZEROS 

Distinct276
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.306128
Minimum0
Maximum165
Zeros46
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:33.903467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.04
median19.245
Q330.615
95-th percentile67.856
Maximum165
Range165
Interquartile range (IQR)18.575

Descriptive statistics

Standard deviation21.516829
Coefficient of variation (CV)0.88524298
Kurtosis7.8196738
Mean24.306128
Median Absolute Deviation (MAD)8.575
Skewness2.2504007
Sum9479.39
Variance462.97394
MonotonicityNot monotonic
2024-05-11T15:06:34.158932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 46
 
11.8%
19.8 5
 
1.3%
10.0 5
 
1.3%
20.0 5
 
1.3%
12.0 5
 
1.3%
23.0 4
 
1.0%
8.25 4
 
1.0%
16.5 4
 
1.0%
16.32 3
 
0.8%
33.0 3
 
0.8%
Other values (266) 306
78.5%
ValueCountFrequency (%)
0.0 46
11.8%
4.0 1
 
0.3%
4.32 1
 
0.3%
6.0 1
 
0.3%
6.6 2
 
0.5%
7.0 2
 
0.5%
8.0 1
 
0.3%
8.2 1
 
0.3%
8.25 4
 
1.0%
8.28 1
 
0.3%
ValueCountFrequency (%)
165.0 1
0.3%
128.69 1
0.3%
115.21 1
0.3%
105.52 1
0.3%
98.0 1
0.3%
95.76 1
0.3%
90.92 1
0.3%
90.0 1
0.3%
89.0 1
0.3%
88.55 1
0.3%

소재지우편번호
Text

Distinct66
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:06:34.552600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0358974
Min length6

Characters and Unicode

Total characters2354
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

Unique21 ?
Unique (%)5.4%

Sample

1st row153858
2nd row153858
3rd row153842
4th row153844
5th row153030
ValueCountFrequency (%)
153801 37
 
9.5%
153823 19
 
4.9%
153825 19
 
4.9%
153857 17
 
4.4%
153858 16
 
4.1%
153806 16
 
4.1%
153841 15
 
3.8%
153864 15
 
3.8%
153820 14
 
3.6%
153863 13
 
3.3%
Other values (56) 209
53.6%
2024-05-11T15:06:35.254906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 499
21.2%
5 493
20.9%
3 491
20.9%
8 404
17.2%
0 122
 
5.2%
2 95
 
4.0%
6 91
 
3.9%
4 66
 
2.8%
7 46
 
2.0%
9 33
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2340
99.4%
Dash Punctuation 14
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 499
21.3%
5 493
21.1%
3 491
21.0%
8 404
17.3%
0 122
 
5.2%
2 95
 
4.1%
6 91
 
3.9%
4 66
 
2.8%
7 46
 
2.0%
9 33
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 499
21.2%
5 493
20.9%
3 491
20.9%
8 404
17.2%
0 122
 
5.2%
2 95
 
4.0%
6 91
 
3.9%
4 66
 
2.8%
7 46
 
2.0%
9 33
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 499
21.2%
5 493
20.9%
3 491
20.9%
8 404
17.2%
0 122
 
5.2%
2 95
 
4.0%
6 91
 
3.9%
4 66
 
2.8%
7 46
 
2.0%
9 33
 
1.4%

지번주소
Text

Distinct364
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:06:35.768923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length52
Mean length25.45641
Min length18

Characters and Unicode

Total characters9928
Distinct characters170
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

Unique339 ?
Unique (%)86.9%

Sample

1st row서울특별시 금천구 시흥동 890-15번지
2nd row서울특별시 금천구 시흥동 894-6번지
3rd row서울특별시 금천구 시흥동 239-1번지 [탑골길 68-1]
4th row서울특별시 금천구 시흥동 266-1845번지
5th row서울특별시 금천구 시흥동 91-0번지
ValueCountFrequency (%)
서울특별시 390
21.6%
금천구 390
21.6%
독산동 176
 
9.8%
시흥동 162
 
9.0%
가산동 52
 
2.9%
시흥대로 15
 
0.8%
1층 13
 
0.7%
독산동길 6
 
0.3%
2층 5
 
0.3%
967-12번지 5
 
0.3%
Other values (491) 588
32.6%
2024-05-11T15:06:36.931589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1766
17.8%
시 573
 
5.8%
동 413
 
4.2%
1 413
 
4.2%
금 394
 
4.0%
구 394
 
4.0%
천 393
 
4.0%
서 391
 
3.9%
울 391
 
3.9%
특 390
 
3.9%
Other values (160) 4410
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5565
56.1%
Decimal Number 2080
 
21.0%
Space Separator 1766
 
17.8%
Dash Punctuation 366
 
3.7%
Open Punctuation 65
 
0.7%
Close Punctuation 65
 
0.7%
Uppercase Letter 19
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 573
 
10.3%
동 413
 
7.4%
금 394
 
7.1%
구 394
 
7.1%
천 393
 
7.1%
서 391
 
7.0%
울 391
 
7.0%
특 390
 
7.0%
별 390
 
7.0%
지 362
 
6.5%
Other values (138) 1474
26.5%
Decimal Number
ValueCountFrequency (%)
1 413
19.9%
9 275
13.2%
2 227
10.9%
0 205
9.9%
8 197
9.5%
3 192
9.2%
4 167
8.0%
5 165
 
7.9%
7 139
 
6.7%
6 100
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 14
73.7%
A 3
 
15.8%
J 1
 
5.3%
S 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
[ 58
89.2%
( 7
 
10.8%
Close Punctuation
ValueCountFrequency (%)
] 58
89.2%
) 7
 
10.8%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
: 1
50.0%
Space Separator
ValueCountFrequency (%)
1766
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5565
56.1%
Common 4344
43.8%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 573
 
10.3%
동 413
 
7.4%
금 394
 
7.1%
구 394
 
7.1%
천 393
 
7.1%
서 391
 
7.0%
울 391
 
7.0%
특 390
 
7.0%
별 390
 
7.0%
지 362
 
6.5%
Other values (138) 1474
26.5%
Common
ValueCountFrequency (%)
1766
40.7%
1 413
 
9.5%
- 366
 
8.4%
9 275
 
6.3%
2 227
 
5.2%
0 205
 
4.7%
8 197
 
4.5%
3 192
 
4.4%
4 167
 
3.8%
5 165
 
3.8%
Other values (8) 371
 
8.5%
Latin
ValueCountFrequency (%)
B 14
73.7%
A 3
 
15.8%
J 1
 
5.3%
S 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5565
56.1%
ASCII 4363
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1766
40.5%
1 413
 
9.5%
- 366
 
8.4%
9 275
 
6.3%
2 227
 
5.2%
0 205
 
4.7%
8 197
 
4.5%
3 192
 
4.4%
4 167
 
3.8%
5 165
 
3.8%
Other values (12) 390
 
8.9%
Hangul
ValueCountFrequency (%)
시 573
 
10.3%
동 413
 
7.4%
금 394
 
7.1%
구 394
 
7.1%
천 393
 
7.1%
서 391
 
7.0%
울 391
 
7.0%
특 390
 
7.0%
별 390
 
7.0%
지 362
 
6.5%
Other values (138) 1474
26.5%

도로명주소
Text

MISSING 

Distinct130
Distinct (%)97.7%
Missing257
Missing (%)65.9%
Memory size3.2 KiB
2024-05-11T15:06:37.545693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length29.015038
Min length22

Characters and Unicode

Total characters3859
Distinct characters125
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

Unique127 ?
Unique (%)95.5%

Sample

1st row서울특별시 금천구 금하로16길 17 (시흥동)
2nd row서울특별시 금천구 탑골로 46-1 (시흥동,[탑골길 68-1])
3rd row서울특별시 금천구 독산로47길 29 (시흥동)
4th row서울특별시 금천구 범안로17길 12, 상가동 15호 (독산동, 독산현대아파트)
5th row서울특별시 금천구 범안로12가길 51 (독산동)
ValueCountFrequency (%)
서울특별시 133
17.6%
금천구 133
17.6%
시흥동 55
 
7.3%
독산동 54
 
7.1%
1층 23
 
3.0%
가산동 18
 
2.4%
시흥대로 8
 
1.1%
22 7
 
0.9%
5 5
 
0.7%
독산로 5
 
0.7%
Other values (226) 315
41.7%
2024-05-11T15:06:38.425151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
 
16.1%
시 238
 
6.2%
1 164
 
4.2%
금 146
 
3.8%
동 142
 
3.7%
울 134
 
3.5%
( 133
 
3.4%
) 133
 
3.4%
산 133
 
3.4%
서 133
 
3.4%
Other values (115) 1880
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2267
58.7%
Space Separator 623
 
16.1%
Decimal Number 613
 
15.9%
Open Punctuation 137
 
3.6%
Close Punctuation 137
 
3.6%
Other Punctuation 54
 
1.4%
Dash Punctuation 16
 
0.4%
Uppercase Letter 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 238
 
10.5%
금 146
 
6.4%
동 142
 
6.3%
울 134
 
5.9%
산 133
 
5.9%
서 133
 
5.9%
천 133
 
5.9%
구 133
 
5.9%
특 133
 
5.9%
별 133
 
5.9%
Other values (96) 809
35.7%
Decimal Number
ValueCountFrequency (%)
1 164
26.8%
2 96
15.7%
3 60
 
9.8%
4 57
 
9.3%
0 48
 
7.8%
5 43
 
7.0%
6 39
 
6.4%
8 38
 
6.2%
7 34
 
5.5%
9 34
 
5.5%
Open Punctuation
ValueCountFrequency (%)
( 133
97.1%
[ 4
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 133
97.1%
] 4
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
B 10
83.3%
A 2
 
16.7%
Space Separator
ValueCountFrequency (%)
623
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2267
58.7%
Common 1580
40.9%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 238
 
10.5%
금 146
 
6.4%
동 142
 
6.3%
울 134
 
5.9%
산 133
 
5.9%
서 133
 
5.9%
천 133
 
5.9%
구 133
 
5.9%
특 133
 
5.9%
별 133
 
5.9%
Other values (96) 809
35.7%
Common
ValueCountFrequency (%)
623
39.4%
1 164
 
10.4%
( 133
 
8.4%
) 133
 
8.4%
2 96
 
6.1%
3 60
 
3.8%
4 57
 
3.6%
, 54
 
3.4%
0 48
 
3.0%
5 43
 
2.7%
Other values (7) 169
 
10.7%
Latin
ValueCountFrequency (%)
B 10
83.3%
A 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2267
58.7%
ASCII 1592
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
39.1%
1 164
 
10.3%
( 133
 
8.4%
) 133
 
8.4%
2 96
 
6.0%
3 60
 
3.8%
4 57
 
3.6%
, 54
 
3.4%
0 48
 
3.0%
5 43
 
2.7%
Other values (9) 181
 
11.4%
Hangul
ValueCountFrequency (%)
시 238
 
10.5%
금 146
 
6.4%
동 142
 
6.3%
울 134
 
5.9%
산 133
 
5.9%
서 133
 
5.9%
천 133
 
5.9%
구 133
 
5.9%
특 133
 
5.9%
별 133
 
5.9%
Other values (96) 809
35.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)56.1%
Missing258
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean8584.3485
Minimum8505
Maximum8656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:38.801615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8505
5-th percentile8516.2
Q18546.75
median8576
Q38624.25
95-th percentile8652
Maximum8656
Range151
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation44.607702
Coefficient of variation (CV)0.0051963993
Kurtosis-1.2785255
Mean8584.3485
Median Absolute Deviation (MAD)42.5
Skewness-0.00067589837
Sum1133134
Variance1989.8471
MonotonicityNot monotonic
2024-05-11T15:06:39.121522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8618 5
 
1.3%
8532 5
 
1.3%
8548 4
 
1.0%
8585 4
 
1.0%
8639 4
 
1.0%
8656 4
 
1.0%
8507 4
 
1.0%
8574 4
 
1.0%
8528 3
 
0.8%
8625 3
 
0.8%
Other values (64) 92
 
23.6%
(Missing) 258
66.2%
ValueCountFrequency (%)
8505 1
 
0.3%
8507 4
1.0%
8511 1
 
0.3%
8514 1
 
0.3%
8518 1
 
0.3%
8519 1
 
0.3%
8520 1
 
0.3%
8524 1
 
0.3%
8528 3
0.8%
8529 1
 
0.3%
ValueCountFrequency (%)
8656 4
1.0%
8655 1
 
0.3%
8654 1
 
0.3%
8652 2
0.5%
8651 1
 
0.3%
8649 2
0.5%
8647 2
0.5%
8643 2
0.5%
8639 4
1.0%
8638 1
 
0.3%

사업장명
Text

Distinct303
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:06:39.756716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length3.0358974
Min length1

Characters and Unicode

Total characters1184
Distinct characters228
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)64.6%

Sample

1st row정성
2nd row공원
3rd row탑동
4th row우리
5th row서울
ValueCountFrequency (%)
현대 6
 
1.5%
모범 5
 
1.2%
소망 5
 
1.2%
우리 5
 
1.2%
대성 4
 
1.0%
반도 4
 
1.0%
중앙 4
 
1.0%
명동 4
 
1.0%
독산 4
 
1.0%
대우 3
 
0.7%
Other values (307) 362
89.2%
2024-05-11T15:06:40.582454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 73
 
6.2%
용 43
 
3.6%
원 42
 
3.5%
성 42
 
3.5%
대 39
 
3.3%
발 24
 
2.0%
우 22
 
1.9%
수 22
 
1.9%
리 20
 
1.7%
지 18
 
1.5%
Other values (218) 839
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1165
98.4%
Space Separator 16
 
1.4%
Decimal Number 2
 
0.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 73
 
6.3%
용 43
 
3.7%
원 42
 
3.6%
성 42
 
3.6%
대 39
 
3.3%
발 24
 
2.1%
우 22
 
1.9%
수 22
 
1.9%
리 20
 
1.7%
지 18
 
1.5%
Other values (214) 820
70.4%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1165
98.4%
Common 18
 
1.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 73
 
6.3%
용 43
 
3.7%
원 42
 
3.6%
성 42
 
3.6%
대 39
 
3.3%
발 24
 
2.1%
우 22
 
1.9%
수 22
 
1.9%
리 20
 
1.7%
지 18
 
1.5%
Other values (214) 820
70.4%
Common
ValueCountFrequency (%)
16
88.9%
3 1
 
5.6%
6 1
 
5.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1165
98.4%
ASCII 19
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 73
 
6.3%
용 43
 
3.7%
원 42
 
3.6%
성 42
 
3.6%
대 39
 
3.3%
발 24
 
2.1%
우 22
 
1.9%
수 22
 
1.9%
리 20
 
1.7%
지 18
 
1.5%
Other values (214) 820
70.4%
ASCII
ValueCountFrequency (%)
16
84.2%
3 1
 
5.3%
6 1
 
5.3%
A 1
 
5.3%

최종수정일자
Date

Distinct288
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1999-01-27 00:00:00
Maximum2024-04-30 09:38:35
2024-05-11T15:06:40.886233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:41.285286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
I
296 
U
94 

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 296
75.9%
U 94
 
24.1%

Length

2024-05-11T15:06:41.575456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:41.739171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 296
75.9%
u 94
 
24.1%

데이터갱신일자
Date

Distinct58
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T15:06:41.922543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:42.227665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
일반이용업
387 
이용업 기타
 
3

Length

Max length6
Median length5
Mean length5.0076923
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 387
99.2%
이용업 기타 3
 
0.8%

Length

2024-05-11T15:06:42.430010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:42.632593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 387
98.5%
이용업 3
 
0.8%
기타 3
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct297
Distinct (%)78.8%
Missing13
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean191160.51
Minimum189282.64
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:42.834962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189282.64
5-th percentile190091.74
Q1190918.24
median191226.29
Q3191513.65
95-th percentile191924.22
Maximum192754.35
Range3471.704
Interquartile range (IQR)595.41884

Descriptive statistics

Standard deviation585.00685
Coefficient of variation (CV)0.0030602913
Kurtosis0.98161415
Mean191160.51
Median Absolute Deviation (MAD)287.9392
Skewness-0.64507133
Sum72067514
Variance342233.01
MonotonicityNot monotonic
2024-05-11T15:06:43.096747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191226.287379467 6
 
1.5%
191132.625751785 5
 
1.3%
190996.914193444 5
 
1.3%
191399.035388034 3
 
0.8%
192754.34619252 3
 
0.8%
190944.565006493 3
 
0.8%
191203.899276547 3
 
0.8%
190023.426907798 3
 
0.8%
190241.176536786 3
 
0.8%
190527.918536528 3
 
0.8%
Other values (287) 340
87.2%
(Missing) 13
 
3.3%
ValueCountFrequency (%)
189282.642165078 1
0.3%
189369.53962474 2
0.5%
189504.258704224 1
0.3%
189538.020935968 2
0.5%
189603.222916543 2
0.5%
189616.142056546 1
0.3%
189685.516219475 2
0.5%
189691.858978981 1
0.3%
189722.178532426 1
0.3%
189767.989093933 1
0.3%
ValueCountFrequency (%)
192754.34619252 3
0.8%
192653.790840875 1
 
0.3%
192368.43764933 1
 
0.3%
192343.982564036 2
0.5%
192193.026208196 1
 
0.3%
192098.393803231 1
 
0.3%
192074.372702969 2
0.5%
192048.416690547 1
 
0.3%
191994.597811022 1
 
0.3%
191991.918911557 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct297
Distinct (%)78.8%
Missing13
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean440232.8
Minimum436909.87
Maximum442354.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:43.507865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436909.87
5-th percentile437933.87
Q1439073.57
median440327.81
Q3441484.87
95-th percentile441918.31
Maximum442354.3
Range5444.4342
Interquartile range (IQR)2411.2991

Descriptive statistics

Standard deviation1295.3882
Coefficient of variation (CV)0.0029425074
Kurtosis-1.0837889
Mean440232.8
Median Absolute Deviation (MAD)1209.1506
Skewness-0.28308361
Sum1.6596776 × 108
Variance1678030.7
MonotonicityNot monotonic
2024-05-11T15:06:43.805808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
437914.06299827 6
 
1.5%
441825.157273149 5
 
1.3%
441563.015154086 5
 
1.3%
441861.4629578 3
 
0.8%
438827.143732711 3
 
0.8%
439580.401737633 3
 
0.8%
439248.909749975 3
 
0.8%
439379.272866954 3
 
0.8%
440453.915574498 3
 
0.8%
441484.865931033 3
 
0.8%
Other values (287) 340
87.2%
(Missing) 13
 
3.3%
ValueCountFrequency (%)
436909.870493711 1
0.3%
436991.446935421 1
0.3%
437199.30787957 1
0.3%
437353.689417366 1
0.3%
437571.204954672 1
0.3%
437656.844199862 1
0.3%
437663.852858361 1
0.3%
437749.431223746 1
0.3%
437773.987067282 1
0.3%
437777.824339474 1
0.3%
ValueCountFrequency (%)
442354.304734197 1
0.3%
442245.138038493 1
0.3%
442201.740263751 1
0.3%
442043.878227727 1
0.3%
442027.464190371 1
0.3%
442026.468974479 2
0.5%
442021.668538685 1
0.3%
441995.873207136 1
0.3%
441982.427934953 2
0.5%
441967.460780947 2
0.5%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
일반이용업
366 
<NA>
 
22
이용업 기타
 
2

Length

Max length6
Median length5
Mean length4.9487179
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 366
93.8%
<NA> 22
 
5.6%
이용업 기타 2
 
0.5%

Length

2024-05-11T15:06:44.088146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:44.294823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 366
93.4%
na 22
 
5.6%
이용업 2
 
0.5%
기타 2
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)5.3%
Missing164
Missing (%)42.1%
Infinite0
Infinite (%)0.0%
Mean1.0575221
Minimum0
Maximum15
Zeros169
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:44.861043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.75
95-th percentile5.75
Maximum15
Range15
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation2.5718581
Coefficient of variation (CV)2.4319663
Kurtosis13.711042
Mean1.0575221
Median Absolute Deviation (MAD)0
Skewness3.4847591
Sum239
Variance6.6144543
MonotonicityNot monotonic
2024-05-11T15:06:45.075354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 169
43.3%
3 13
 
3.3%
1 11
 
2.8%
4 10
 
2.6%
2 9
 
2.3%
7 3
 
0.8%
6 2
 
0.5%
9 2
 
0.5%
5 2
 
0.5%
14 2
 
0.5%
Other values (2) 3
 
0.8%
(Missing) 164
42.1%
ValueCountFrequency (%)
0 169
43.3%
1 11
 
2.8%
2 9
 
2.3%
3 13
 
3.3%
4 10
 
2.6%
5 2
 
0.5%
6 2
 
0.5%
7 3
 
0.8%
9 2
 
0.5%
12 1
 
0.3%
ValueCountFrequency (%)
15 2
 
0.5%
14 2
 
0.5%
12 1
 
0.3%
9 2
 
0.5%
7 3
 
0.8%
6 2
 
0.5%
5 2
 
0.5%
4 10
2.6%
3 13
3.3%
2 9
2.3%

건물지하층수
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
183 
<NA>
171 
1
25 
2
 
4
3
 
4

Length

Max length4
Median length1
Mean length2.3153846
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 183
46.9%
<NA> 171
43.8%
1 25
 
6.4%
2 4
 
1.0%
3 4
 
1.0%
4 3
 
0.8%

Length

2024-05-11T15:06:45.340679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:45.538295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 183
46.9%
na 171
43.8%
1 25
 
6.4%
2 4
 
1.0%
3 4
 
1.0%
4 3
 
0.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.7%
Missing165
Missing (%)42.3%
Infinite0
Infinite (%)0.0%
Mean0.49333333
Minimum0
Maximum7
Zeros156
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:45.728506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.98705912
Coefficient of variation (CV)2.0007955
Kurtosis16.816344
Mean0.49333333
Median Absolute Deviation (MAD)0
Skewness3.4331921
Sum111
Variance0.97428571
MonotonicityNot monotonic
2024-05-11T15:06:45.967790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 156
40.0%
1 44
 
11.3%
2 18
 
4.6%
3 3
 
0.8%
7 2
 
0.5%
4 2
 
0.5%
(Missing) 165
42.3%
ValueCountFrequency (%)
0 156
40.0%
1 44
 
11.3%
2 18
 
4.6%
3 3
 
0.8%
4 2
 
0.5%
7 2
 
0.5%
ValueCountFrequency (%)
7 2
 
0.5%
4 2
 
0.5%
3 3
 
0.8%
2 18
 
4.6%
1 44
 
11.3%
0 156
40.0%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)8.0%
Missing315
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean1.1866667
Minimum0
Maximum7
Zeros23
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:46.171584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3.3
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3526084
Coefficient of variation (CV)1.1398386
Kurtosis7.7904494
Mean1.1866667
Median Absolute Deviation (MAD)1
Skewness2.3770834
Sum89
Variance1.8295495
MonotonicityNot monotonic
2024-05-11T15:06:46.324169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 32
 
8.2%
0 23
 
5.9%
2 13
 
3.3%
3 3
 
0.8%
7 2
 
0.5%
4 2
 
0.5%
(Missing) 315
80.8%
ValueCountFrequency (%)
0 23
5.9%
1 32
8.2%
2 13
3.3%
3 3
 
0.8%
4 2
 
0.5%
7 2
 
0.5%
ValueCountFrequency (%)
7 2
 
0.5%
4 2
 
0.5%
3 3
 
0.8%
2 13
3.3%
1 32
8.2%
0 23
5.9%

사용시작지하층
Categorical

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
202 
0
159 
1
25 
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length2.5538462
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 202
51.8%
0 159
40.8%
1 25
 
6.4%
2 3
 
0.8%
3 1
 
0.3%

Length

2024-05-11T15:06:46.532376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:46.715316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
51.8%
0 159
40.8%
1 25
 
6.4%
2 3
 
0.8%
3 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
338 
0
 
28
1
 
20
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.6
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 338
86.7%
0 28
 
7.2%
1 20
 
5.1%
2 3
 
0.8%
3 1
 
0.3%

Length

2024-05-11T15:06:46.944623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:47.125076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 338
86.7%
0 28
 
7.2%
1 20
 
5.1%
2 3
 
0.8%
3 1
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
200 
<NA>
190 

Length

Max length4
Median length1
Mean length2.4615385
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 200
51.3%
<NA> 190
48.7%

Length

2024-05-11T15:06:47.311196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:47.485431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 200
51.3%
na 190
48.7%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
200 
<NA>
190 

Length

Max length4
Median length1
Mean length2.4615385
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 200
51.3%
<NA> 190
48.7%

Length

2024-05-11T15:06:47.682968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:47.881116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 200
51.3%
na 190
48.7%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
200 
<NA>
190 

Length

Max length4
Median length1
Mean length2.4615385
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 200
51.3%
<NA> 190
48.7%

Length

2024-05-11T15:06:48.087318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:48.309748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 200
51.3%
na 190
48.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing25
Missing (%)6.4%
Memory size912.0 B
False
365 
(Missing)
 
25
ValueCountFrequency (%)
False 365
93.6%
(Missing) 25
 
6.4%
2024-05-11T15:06:48.480746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)4.0%
Missing39
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean3.9088319
Minimum0
Maximum35
Zeros18
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:48.627619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q12
median3
Q35
95-th percentile8.5
Maximum35
Range35
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.8229076
Coefficient of variation (CV)0.72218701
Kurtosis41.461308
Mean3.9088319
Median Absolute Deviation (MAD)1
Skewness4.3164416
Sum1372
Variance7.9688075
MonotonicityNot monotonic
2024-05-11T15:06:48.886996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3 115
29.5%
2 70
17.9%
4 46
 
11.8%
7 29
 
7.4%
5 21
 
5.4%
0 18
 
4.6%
6 17
 
4.4%
8 11
 
2.8%
9 11
 
2.8%
1 6
 
1.5%
Other values (4) 7
 
1.8%
(Missing) 39
 
10.0%
ValueCountFrequency (%)
0 18
 
4.6%
1 6
 
1.5%
2 70
17.9%
3 115
29.5%
4 46
 
11.8%
5 21
 
5.4%
6 17
 
4.4%
7 29
 
7.4%
8 11
 
2.8%
9 11
 
2.8%
ValueCountFrequency (%)
35 1
 
0.3%
14 1
 
0.3%
11 1
 
0.3%
10 4
 
1.0%
9 11
 
2.8%
8 11
 
2.8%
7 29
7.4%
6 17
 
4.4%
5 21
5.4%
4 46
11.8%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing390
Missing (%)100.0%
Memory size3.6 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
346 
임대
42 
자가
 
2

Length

Max length4
Median length4
Mean length3.774359
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> 346
88.7%
임대 42
 
10.8%
자가 2
 
0.5%

Length

2024-05-11T15:06:49.196415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:49.413566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
88.7%
임대 42
 
10.8%
자가 2
 
0.5%

세탁기수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
325 
0
65 

Length

Max length4
Median length4
Mean length3.5
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> 325
83.3%
0 65
 
16.7%

Length

2024-05-11T15:06:49.644247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:49.830478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 325
83.3%
0 65
 
16.7%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
367 
0
 
20
2
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.8230769
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
94.1%
0 20
 
5.1%
2 2
 
0.5%
1 1
 
0.3%

Length

2024-05-11T15:06:50.031390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:50.218382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
94.1%
0 20
 
5.1%
2 2
 
0.5%
1 1
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
365 
0
 
15
1
 
10

Length

Max length4
Median length4
Mean length3.8076923
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> 365
93.6%
0 15
 
3.8%
1 10
 
2.6%

Length

2024-05-11T15:06:50.420592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:50.674807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 365
93.6%
0 15
 
3.8%
1 10
 
2.6%

회수건조수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
332 
0
58 

Length

Max length4
Median length4
Mean length3.5538462
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> 332
85.1%
0 58
 
14.9%

Length

2024-05-11T15:06:50.876174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:51.090646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 332
85.1%
0 58
 
14.9%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
335 
0
55 

Length

Max length4
Median length4
Mean length3.5769231
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> 335
85.9%
0 55
 
14.1%

Length

2024-05-11T15:06:51.378829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:51.579462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 335
85.9%
0 55
 
14.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing22
Missing (%)5.6%
Memory size912.0 B
False
367 
True
 
1
(Missing)
 
22
ValueCountFrequency (%)
False 367
94.1%
True 1
 
0.3%
(Missing) 22
 
5.6%
2024-05-11T15:06:51.753707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031700003170000-203-1976-0110319761201<NA>3폐업2폐업19990203<NA><NA><NA>02 802507519.25153858서울특별시 금천구 시흥동 890-15번지<NA><NA>정성1999-02-05 00:00:00I2018-08-31 23:59:59.0일반이용업191308.017269438814.976751일반이용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131700003170000-203-1977-0110419770920<NA>1영업/정상1영업<NA><NA><NA><NA>02 802695511.78153858서울특별시 금천구 시흥동 894-6번지서울특별시 금천구 금하로16길 17 (시흥동)8629공원2019-10-22 17:05:42U2019-10-24 02:40:00.0일반이용업191465.836682438903.978839일반이용업000000000N2<NA><NA><NA><NA>0<NA><NA>0<NA>N
231700003170000-203-1977-0112019770411<NA>3폐업2폐업20140227<NA><NA><NA>02 803168016.79153842서울특별시 금천구 시흥동 239-1번지 [탑골길 68-1]서울특별시 금천구 탑골로 46-1 (시흥동,[탑골길 68-1])8656탑동2007-10-05 16:54:36I2018-08-31 23:59:59.0일반이용업192343.982564438860.742532일반이용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331700003170000-203-1978-0110519780503<NA>3폐업2폐업20030225<NA><NA><NA>020805237813.52153844서울특별시 금천구 시흥동 266-1845번지<NA><NA>우리2003-02-25 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431700003170000-203-1978-0110619780605<NA>3폐업2폐업19981128<NA><NA><NA>020000000024.74153030서울특별시 금천구 시흥동 91-0번지<NA><NA>서울2002-01-13 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531700003170000-203-1978-0112319780126<NA>3폐업2폐업19971216<NA><NA><NA>02 805532418.24153010서울특별시 금천구 독산동 399-5번지<NA><NA>경일2002-01-13 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631700003170000-203-1978-0112719781108<NA>3폐업2폐업19970312<NA><NA><NA>02 80258760.0153831서울특별시 금천구 독산동 1041-39번지<NA><NA>지하2002-01-13 00:00:00I2018-08-31 23:59:59.0일반이용업191336.707921440303.141196일반이용업000<NA>0<NA>000N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731700003170000-203-1979-0106919790627<NA>3폐업2폐업20020730<NA><NA><NA>02 863240323.76153801서울특별시 금천구 가산동 237-123번지<NA><NA>여주2002-12-30 00:00:00I2018-08-31 23:59:59.0일반이용업190251.023016441258.597463일반이용업000<NA>0<NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831700003170000-203-1979-0112919791109<NA>3폐업2폐업20020207<NA><NA><NA>02 863261112.0153823서울특별시 금천구 독산동 965-26번지<NA><NA>대우2002-12-30 00:00:00I2018-08-31 23:59:59.0일반이용업191093.134282441522.344996일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931700003170000-203-1979-0127519790307<NA>1영업/정상1영업<NA><NA><NA><NA>02 803991635.0153857서울특별시 금천구 시흥동 861번지서울특별시 금천구 독산로47길 29 (시흥동)8621중앙2019-10-22 17:06:05U2019-10-24 02:40:00.0일반이용업191319.553816440001.166903일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
38031700003170000-203-2022-0000120220126<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.6153854서울특별시 금천구 시흥동 800-18 1층서울특별시 금천구 독산로40길 37, 1층 (시흥동)8568착한이발소2022-01-26 17:14:09I2022-01-28 00:22:39.0일반이용업191660.095101439844.396275일반이용업001100000N2<NA><NA><NA><NA>00100N
38131700003170000-203-2022-000022022-02-18<NA>1영업/정상1영업<NA><NA><NA><NA>02 892906640.43153-863서울특별시 금천구 시흥동 985 한영상가 나동 14호서울특별시 금천구 시흥대로39길 16, 한영상가 나동 1층 14호 (시흥동)8638태후사랑2023-11-13 10:59:22U2022-10-31 23:05:00.0일반이용업191266.732178438395.806834<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38231700003170000-203-2022-000032022-04-05<NA>3폐업2폐업2023-12-31<NA><NA><NA><NA>14.2153-804서울특별시 금천구 가산동 772 주상복합두산아파트서울특별시 금천구 가산로 106, B1층 (가산동, 주상복합두산아파트)8532뉴 그린 이용원2024-01-03 10:46:54U2023-12-01 00:05:00.0일반이용업190527.918537441484.865931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38331700003170000-203-2022-0000420220706<NA>1영업/정상1영업<NA><NA><NA><NA><NA>56.63153801서울특별시 금천구 가산동 60-15 삼성리더스타워 B121호서울특별시 금천구 벚꽃로 286, 삼성리더스타워 지하1층 B121호 (가산동)8511골든벅 바버샵2022-07-06 13:22:46I2021-12-07 00:08:00.0일반이용업189685.516219442026.468974<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38431700003170000-203-2022-0000520220830<NA>1영업/정상1영업<NA><NA><NA><NA><NA>55.0153801서울특별시 금천구 가산동 60-8 현대시티아울렛 가산점서울특별시 금천구 디지털로10길 9, 현대시티아울렛 가산점 4층 402호 (가산동)8514웸블리바버샵2022-08-30 15:03:45I2021-12-09 00:01:00.0일반이용업190119.463376441716.684586<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38531700003170000-203-2022-000062022-09-27<NA>3폐업2폐업2023-05-02<NA><NA><NA><NA>10.0153-803서울특별시 금천구 가산동 371-57 가산 더스카이밸리 1차서울특별시 금천구 가산디지털1로 142, 가산 더스카이밸리 1차 118호 (가산동)8507마르코에스코바르 가디점2023-05-02 11:24:52U2022-12-05 00:04:00.0일반이용업189603.222917441801.135064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38631700003170000-203-2022-0000720221213<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0153856서울특별시 금천구 시흥동 847-1 일부호서울특별시 금천구 독산로33길 5, 1층 일부호 (시흥동)8625평화2022-12-13 10:51:15I2021-11-01 23:05:00.0일반이용업191531.671278439439.978281<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38731700003170000-203-2023-000012023-05-02<NA>1영업/정상1영업<NA><NA><NA><NA>05071330107934.5153-803서울특별시 금천구 가산동 371-57 가산 더스카이밸리 1차서울특별시 금천구 가산디지털1로 142, 가산 더스카이밸리 1차 1층 118호 (가산동)8507마르코에스코바르 가디점2023-05-02 14:53:32I2022-12-05 00:04:00.0일반이용업189603.222917441801.135064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38831700003170000-203-2024-000012024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.44153-819서울특별시 금천구 독산동 884-1서울특별시 금천구 문성로5길 22, 1층 (독산동)8550대명이발관2024-04-23 16:11:42I2023-12-03 22:05:00.0일반이용업191542.932686441747.715521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38931700003170000-203-2024-000022024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0153-803서울특별시 금천구 가산동 549-1서울특별시 금천구 가산디지털2로 101, 204호 (가산동)8505더 맨바버샵2024-04-26 10:55:28I2023-12-03 22:08:00.0일반이용업189282.642165441654.484591<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>