Overview

Dataset statistics

Number of variables47
Number of observations632
Missing cells6841
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory249.5 KiB
Average record size in memory404.2 B

Variable types

Categorical19
Text7
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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-17943/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신구분 is highly imbalanced (59.0%)Imbalance
업태구분명 is highly imbalanced (94.5%)Imbalance
위생업태명 is highly imbalanced (80.8%)Imbalance
사용끝지하층 is highly imbalanced (51.8%)Imbalance
발한실여부 is highly imbalanced (98.2%)Imbalance
건물소유구분명 is highly imbalanced (59.2%)Imbalance
여성종사자수 is highly imbalanced (77.8%)Imbalance
남성종사자수 is highly imbalanced (76.2%)Imbalance
다중이용업소여부 is highly imbalanced (98.2%)Imbalance
인허가취소일자 has 632 (100.0%) missing valuesMissing
폐업일자 has 91 (14.4%) missing valuesMissing
휴업시작일자 has 632 (100.0%) missing valuesMissing
휴업종료일자 has 632 (100.0%) missing valuesMissing
재개업일자 has 632 (100.0%) missing valuesMissing
전화번호 has 160 (25.3%) missing valuesMissing
도로명주소 has 445 (70.4%) missing valuesMissing
도로명우편번호 has 445 (70.4%) missing valuesMissing
좌표정보(X) has 46 (7.3%) missing valuesMissing
좌표정보(Y) has 46 (7.3%) missing valuesMissing
건물지상층수 has 158 (25.0%) missing valuesMissing
건물지하층수 has 228 (36.1%) missing valuesMissing
사용시작지상층 has 257 (40.7%) missing valuesMissing
사용끝지상층 has 415 (65.7%) missing valuesMissing
발한실여부 has 49 (7.8%) missing valuesMissing
좌석수 has 44 (7.0%) missing valuesMissing
조건부허가신고사유 has 632 (100.0%) missing valuesMissing
조건부허가시작일자 has 632 (100.0%) missing valuesMissing
조건부허가종료일자 has 632 (100.0%) missing valuesMissing
다중이용업소여부 has 28 (4.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 235 (37.2%) zerosZeros
건물지하층수 has 242 (38.3%) zerosZeros
사용시작지상층 has 162 (25.6%) zerosZeros
사용끝지상층 has 21 (3.3%) zerosZeros

Reproduction

Analysis started2024-05-11 08:51:38.970971
Analysis finished2024-05-11 08:51:40.922106
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3160000
632 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3160000 632
100.0%

Length

2024-05-11T08:51:41.244776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:41.671211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 632
100.0%

관리번호
Text

UNIQUE 

Distinct632
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T08:51:42.224188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13904
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

Unique632 ?
Unique (%)100.0%

Sample

1st row3160000-203-1966-00317
2nd row3160000-203-1970-00541
3rd row3160000-203-1971-00340
4th row3160000-203-1973-00542
5th row3160000-203-1974-00330
ValueCountFrequency (%)
3160000-203-1966-00317 1
 
0.2%
3160000-203-2003-00004 1
 
0.2%
3160000-203-2003-00006 1
 
0.2%
3160000-203-2002-00016 1
 
0.2%
3160000-203-2002-00017 1
 
0.2%
3160000-203-2002-00018 1
 
0.2%
3160000-203-2003-00001 1
 
0.2%
3160000-203-2003-00002 1
 
0.2%
3160000-203-2003-00003 1
 
0.2%
3160000-203-2002-00014 1
 
0.2%
Other values (622) 622
98.4%
2024-05-11T08:51:43.849410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5372
38.6%
- 1896
 
13.6%
3 1517
 
10.9%
1 1376
 
9.9%
2 1104
 
7.9%
6 884
 
6.4%
9 686
 
4.9%
8 329
 
2.4%
5 282
 
2.0%
4 265
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12008
86.4%
Dash Punctuation 1896
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5372
44.7%
3 1517
 
12.6%
1 1376
 
11.5%
2 1104
 
9.2%
6 884
 
7.4%
9 686
 
5.7%
8 329
 
2.7%
5 282
 
2.3%
4 265
 
2.2%
7 193
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1896
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13904
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5372
38.6%
- 1896
 
13.6%
3 1517
 
10.9%
1 1376
 
9.9%
2 1104
 
7.9%
6 884
 
6.4%
9 686
 
4.9%
8 329
 
2.4%
5 282
 
2.0%
4 265
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5372
38.6%
- 1896
 
13.6%
3 1517
 
10.9%
1 1376
 
9.9%
2 1104
 
7.9%
6 884
 
6.4%
9 686
 
4.9%
8 329
 
2.4%
5 282
 
2.0%
4 265
 
1.9%
Distinct574
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1966-08-13 00:00:00
Maximum2024-04-23 00:00:00
2024-05-11T08:51:44.734848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:45.339638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3
541 
1
91 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 541
85.6%
1 91
 
14.4%

Length

2024-05-11T08:51:46.162259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:46.988967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 541
85.6%
1 91
 
14.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
541 
영업/정상
91 

Length

Max length5
Median length2
Mean length2.431962
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 541
85.6%
영업/정상 91
 
14.4%

Length

2024-05-11T08:51:47.604443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:48.007559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 541
85.6%
영업/정상 91
 
14.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2
541 
1
91 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 541
85.6%
1 91
 
14.4%

Length

2024-05-11T08:51:48.525676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:48.932193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 541
85.6%
1 91
 
14.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
폐업
541 
영업
91 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 541
85.6%
영업 91
 
14.4%

Length

2024-05-11T08:51:49.370226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:49.802390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 541
85.6%
영업 91
 
14.4%

폐업일자
Date

MISSING 

Distinct441
Distinct (%)81.5%
Missing91
Missing (%)14.4%
Memory size5.1 KiB
Minimum1987-09-09 00:00:00
Maximum2024-02-05 00:00:00
2024-05-11T08:51:50.219438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:50.825630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

전화번호
Text

MISSING 

Distinct383
Distinct (%)81.1%
Missing160
Missing (%)25.3%
Memory size5.1 KiB
2024-05-11T08:51:51.681585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.7902542
Min length2

Characters and Unicode

Total characters4621
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)76.7%

Sample

1st row02 8551795
2nd row02 00000
3rd row02 8542785
4th row02 00000
5th row0200000000
ValueCountFrequency (%)
02 271
36.1%
00000 35
 
4.7%
0 27
 
3.6%
0200000000 14
 
1.9%
8555040 2
 
0.3%
8566969 2
 
0.3%
0226789472 2
 
0.3%
6844062 2
 
0.3%
6879518 2
 
0.3%
0226137945 2
 
0.3%
Other values (378) 391
52.1%
2024-05-11T08:51:52.928996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 996
21.6%
2 831
18.0%
6 519
11.2%
8 505
10.9%
411
8.9%
5 306
 
6.6%
1 229
 
5.0%
7 222
 
4.8%
3 216
 
4.7%
9 193
 
4.2%
Other values (2) 193
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4209
91.1%
Space Separator 411
 
8.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 996
23.7%
2 831
19.7%
6 519
12.3%
8 505
12.0%
5 306
 
7.3%
1 229
 
5.4%
7 222
 
5.3%
3 216
 
5.1%
9 193
 
4.6%
4 192
 
4.6%
Space Separator
ValueCountFrequency (%)
411
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4621
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 996
21.6%
2 831
18.0%
6 519
11.2%
8 505
10.9%
411
8.9%
5 306
 
6.6%
1 229
 
5.0%
7 222
 
4.8%
3 216
 
4.7%
9 193
 
4.2%
Other values (2) 193
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4621
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 996
21.6%
2 831
18.0%
6 519
11.2%
8 505
10.9%
411
8.9%
5 306
 
6.6%
1 229
 
5.0%
7 222
 
4.8%
3 216
 
4.7%
9 193
 
4.2%
Other values (2) 193
 
4.2%
Distinct419
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T08:51:53.574309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.835443
Min length3

Characters and Unicode

Total characters3056
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)51.9%

Sample

1st row22.50
2nd row20.49
3rd row44.64
4th row14.42
5th row34.09
ValueCountFrequency (%)
00 37
 
5.9%
9.90 14
 
2.2%
16.00 10
 
1.6%
19.80 8
 
1.3%
10.00 7
 
1.1%
33.00 6
 
0.9%
18.00 6
 
0.9%
16.50 6
 
0.9%
25.00 5
 
0.8%
66.00 5
 
0.8%
Other values (409) 528
83.5%
2024-05-11T08:51:54.941877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 632
20.7%
0 591
19.3%
1 364
11.9%
2 327
10.7%
4 189
 
6.2%
5 182
 
6.0%
3 169
 
5.5%
8 164
 
5.4%
6 160
 
5.2%
9 152
 
5.0%
Other values (2) 126
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2422
79.3%
Other Punctuation 634
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 591
24.4%
1 364
15.0%
2 327
13.5%
4 189
 
7.8%
5 182
 
7.5%
3 169
 
7.0%
8 164
 
6.8%
6 160
 
6.6%
9 152
 
6.3%
7 124
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 632
99.7%
, 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3056
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 632
20.7%
0 591
19.3%
1 364
11.9%
2 327
10.7%
4 189
 
6.2%
5 182
 
6.0%
3 169
 
5.5%
8 164
 
5.4%
6 160
 
5.2%
9 152
 
5.0%
Other values (2) 126
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 632
20.7%
0 591
19.3%
1 364
11.9%
2 327
10.7%
4 189
 
6.2%
5 182
 
6.0%
3 169
 
5.5%
8 164
 
5.4%
6 160
 
5.2%
9 152
 
5.0%
Other values (2) 126
 
4.1%
Distinct112
Distinct (%)17.8%
Missing3
Missing (%)0.5%
Memory size5.1 KiB
2024-05-11T08:51:55.596039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0286169
Min length6

Characters and Unicode

Total characters3792
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

Unique30 ?
Unique (%)4.8%

Sample

1st row152872
2nd row152871
3rd row152815
4th row152887
5th row152855
ValueCountFrequency (%)
152800 28
 
4.5%
152815 26
 
4.1%
152880 17
 
2.7%
152871 16
 
2.5%
152801 16
 
2.5%
152872 16
 
2.5%
152845 15
 
2.4%
152840 15
 
2.4%
152888 13
 
2.1%
152838 13
 
2.1%
Other values (102) 454
72.2%
2024-05-11T08:51:56.664917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 765
20.2%
2 744
19.6%
1 742
19.6%
8 720
19.0%
0 234
 
6.2%
4 152
 
4.0%
6 121
 
3.2%
7 104
 
2.7%
3 98
 
2.6%
9 94
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3774
99.5%
Dash Punctuation 18
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 765
20.3%
2 744
19.7%
1 742
19.7%
8 720
19.1%
0 234
 
6.2%
4 152
 
4.0%
6 121
 
3.2%
7 104
 
2.8%
3 98
 
2.6%
9 94
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3792
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 765
20.2%
2 744
19.6%
1 742
19.6%
8 720
19.0%
0 234
 
6.2%
4 152
 
4.0%
6 121
 
3.2%
7 104
 
2.7%
3 98
 
2.6%
9 94
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 765
20.2%
2 744
19.6%
1 742
19.6%
8 720
19.0%
0 234
 
6.2%
4 152
 
4.0%
6 121
 
3.2%
7 104
 
2.7%
3 98
 
2.6%
9 94
 
2.5%
Distinct571
Distinct (%)90.6%
Missing2
Missing (%)0.3%
Memory size5.1 KiB
2024-05-11T08:51:57.504901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length25.34127
Min length17

Characters and Unicode

Total characters15965
Distinct characters197
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique521 ?
Unique (%)82.7%

Sample

1st row서울특별시 구로구 구로동 748-2번지
2nd row서울특별시 구로구 119-2번지
3rd row서울특별시 구로구 구로동 722-7번지
4th row서울특별시 구로구 개봉동 349-5번지
5th row서울특별시 구로구 신도림동 365번지
ValueCountFrequency (%)
구로구 635
21.8%
서울특별시 630
21.7%
구로동 264
 
9.1%
개봉동 121
 
4.2%
고척동 82
 
2.8%
오류동 59
 
2.0%
가리봉동 46
 
1.6%
신도림동 34
 
1.2%
온수동 11
 
0.4%
1층 11
 
0.4%
Other values (745) 1016
34.9%
2024-05-11T08:51:59.535088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2842
17.8%
1549
 
9.7%
916
 
5.7%
1 725
 
4.5%
682
 
4.3%
634
 
4.0%
633
 
4.0%
630
 
3.9%
630
 
3.9%
630
 
3.9%
Other values (187) 6094
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9201
57.6%
Decimal Number 3186
 
20.0%
Space Separator 2842
 
17.8%
Dash Punctuation 589
 
3.7%
Open Punctuation 60
 
0.4%
Close Punctuation 60
 
0.4%
Uppercase Letter 15
 
0.1%
Other Punctuation 10
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1549
16.8%
916
10.0%
682
 
7.4%
634
 
6.9%
633
 
6.9%
630
 
6.8%
630
 
6.8%
630
 
6.8%
599
 
6.5%
535
 
5.8%
Other values (167) 1763
19.2%
Decimal Number
ValueCountFrequency (%)
1 725
22.8%
2 415
13.0%
3 355
11.1%
4 302
9.5%
5 293
9.2%
0 272
 
8.5%
6 258
 
8.1%
7 231
 
7.3%
8 176
 
5.5%
9 159
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 14
93.3%
A 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
. 3
30.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
2842
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 589
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9201
57.6%
Common 6747
42.3%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1549
16.8%
916
10.0%
682
 
7.4%
634
 
6.9%
633
 
6.9%
630
 
6.8%
630
 
6.8%
630
 
6.8%
599
 
6.5%
535
 
5.8%
Other values (167) 1763
19.2%
Common
ValueCountFrequency (%)
2842
42.1%
1 725
 
10.7%
- 589
 
8.7%
2 415
 
6.2%
3 355
 
5.3%
4 302
 
4.5%
5 293
 
4.3%
0 272
 
4.0%
6 258
 
3.8%
7 231
 
3.4%
Other values (6) 465
 
6.9%
Latin
ValueCountFrequency (%)
B 14
82.4%
e 1
 
5.9%
A 1
 
5.9%
b 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9201
57.6%
ASCII 6764
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2842
42.0%
1 725
 
10.7%
- 589
 
8.7%
2 415
 
6.1%
3 355
 
5.2%
4 302
 
4.5%
5 293
 
4.3%
0 272
 
4.0%
6 258
 
3.8%
7 231
 
3.4%
Other values (10) 482
 
7.1%
Hangul
ValueCountFrequency (%)
1549
16.8%
916
10.0%
682
 
7.4%
634
 
6.9%
633
 
6.9%
630
 
6.8%
630
 
6.8%
630
 
6.8%
599
 
6.5%
535
 
5.8%
Other values (167) 1763
19.2%

도로명주소
Text

MISSING 

Distinct183
Distinct (%)97.9%
Missing445
Missing (%)70.4%
Memory size5.1 KiB
2024-05-11T08:52:00.579745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48
Mean length31.203209
Min length22

Characters and Unicode

Total characters5835
Distinct characters170
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)95.7%

Sample

1st row서울특별시 구로구 경인로47길 67 (고척동)
2nd row서울특별시 구로구 경인로47길 91 (고척동)
3rd row서울특별시 구로구 벚꽃로68길 31 (구로동)
4th row서울특별시 구로구 고척로3길 20 (오류동)
5th row서울특별시 구로구 구로동로22길 78-2 (구로동)
ValueCountFrequency (%)
서울특별시 187
 
17.0%
구로구 187
 
17.0%
구로동 63
 
5.7%
개봉동 26
 
2.4%
1층 25
 
2.3%
오류동 20
 
1.8%
고척동 19
 
1.7%
경인로 12
 
1.1%
신도림동 10
 
0.9%
가리봉동 10
 
0.9%
Other values (358) 543
49.3%
2024-05-11T08:52:02.164779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
918
 
15.7%
503
 
8.6%
495
 
8.5%
1 263
 
4.5%
245
 
4.2%
) 199
 
3.4%
( 199
 
3.4%
193
 
3.3%
190
 
3.3%
187
 
3.2%
Other values (160) 2443
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3449
59.1%
Space Separator 918
 
15.7%
Decimal Number 913
 
15.6%
Close Punctuation 199
 
3.4%
Open Punctuation 199
 
3.4%
Other Punctuation 116
 
2.0%
Dash Punctuation 32
 
0.5%
Uppercase Letter 7
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
503
14.6%
495
14.4%
245
 
7.1%
193
 
5.6%
190
 
5.5%
187
 
5.4%
187
 
5.4%
187
 
5.4%
149
 
4.3%
64
 
1.9%
Other values (141) 1049
30.4%
Decimal Number
ValueCountFrequency (%)
1 263
28.8%
2 150
16.4%
3 106
11.6%
5 68
 
7.4%
0 66
 
7.2%
8 64
 
7.0%
4 54
 
5.9%
6 54
 
5.9%
7 54
 
5.9%
9 34
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
85.7%
A 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
918
100.0%
Close Punctuation
ValueCountFrequency (%)
) 199
100.0%
Open Punctuation
ValueCountFrequency (%)
( 199
100.0%
Other Punctuation
ValueCountFrequency (%)
, 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3449
59.1%
Common 2377
40.7%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
503
14.6%
495
14.4%
245
 
7.1%
193
 
5.6%
190
 
5.5%
187
 
5.4%
187
 
5.4%
187
 
5.4%
149
 
4.3%
64
 
1.9%
Other values (141) 1049
30.4%
Common
ValueCountFrequency (%)
918
38.6%
1 263
 
11.1%
) 199
 
8.4%
( 199
 
8.4%
2 150
 
6.3%
, 116
 
4.9%
3 106
 
4.5%
5 68
 
2.9%
0 66
 
2.8%
8 64
 
2.7%
Other values (5) 228
 
9.6%
Latin
ValueCountFrequency (%)
B 6
66.7%
b 1
 
11.1%
A 1
 
11.1%
e 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3449
59.1%
ASCII 2386
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
918
38.5%
1 263
 
11.0%
) 199
 
8.3%
( 199
 
8.3%
2 150
 
6.3%
, 116
 
4.9%
3 106
 
4.4%
5 68
 
2.8%
0 66
 
2.8%
8 64
 
2.7%
Other values (9) 237
 
9.9%
Hangul
ValueCountFrequency (%)
503
14.6%
495
14.4%
245
 
7.1%
193
 
5.6%
190
 
5.5%
187
 
5.4%
187
 
5.4%
187
 
5.4%
149
 
4.3%
64
 
1.9%
Other values (141) 1049
30.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)57.8%
Missing445
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean8290.2941
Minimum8202
Maximum8395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:02.597549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8202
5-th percentile8209.3
Q18243
median8290
Q38330.5
95-th percentile8383.7
Maximum8395
Range193
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation53.79885
Coefficient of variation (CV)0.0064893777
Kurtosis-1.0054754
Mean8290.2941
Median Absolute Deviation (MAD)44
Skewness0.1463774
Sum1550285
Variance2894.3163
MonotonicityNot monotonic
2024-05-11T08:52:03.164984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8251 4
 
0.6%
8304 4
 
0.6%
8353 4
 
0.6%
8374 4
 
0.6%
8315 4
 
0.6%
8289 4
 
0.6%
8384 3
 
0.5%
8243 3
 
0.5%
8348 3
 
0.5%
8318 3
 
0.5%
Other values (98) 151
 
23.9%
(Missing) 445
70.4%
ValueCountFrequency (%)
8202 1
 
0.2%
8203 3
0.5%
8205 1
 
0.2%
8206 1
 
0.2%
8207 2
0.3%
8208 1
 
0.2%
8209 1
 
0.2%
8210 2
0.3%
8212 1
 
0.2%
8213 1
 
0.2%
ValueCountFrequency (%)
8395 3
0.5%
8393 1
 
0.2%
8391 1
 
0.2%
8387 1
 
0.2%
8386 1
 
0.2%
8384 3
0.5%
8383 1
 
0.2%
8378 3
0.5%
8374 4
0.6%
8372 1
 
0.2%
Distinct488
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-11T08:52:03.759721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length2
Mean length3.8322785
Min length1

Characters and Unicode

Total characters2422
Distinct characters291
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

Unique399 ?
Unique (%)63.1%

Sample

1st row희망
2nd row항동
3rd row일광
4th row온양
5th row한국타이어구내
ValueCountFrequency (%)
이용원 29
 
4.1%
11
 
1.6%
현대 8
 
1.1%
유정 5
 
0.7%
황금 5
 
0.7%
행운 5
 
0.7%
은성 4
 
0.6%
이발관 4
 
0.6%
광명 4
 
0.6%
한스이용원 4
 
0.6%
Other values (495) 624
88.8%
2024-05-11T08:52:04.712194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
201
 
8.3%
159
 
6.6%
150
 
6.2%
71
 
2.9%
65
 
2.7%
58
 
2.4%
50
 
2.1%
45
 
1.9%
43
 
1.8%
41
 
1.7%
Other values (281) 1539
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2322
95.9%
Space Separator 71
 
2.9%
Lowercase Letter 12
 
0.5%
Decimal Number 7
 
0.3%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
201
 
8.7%
159
 
6.8%
150
 
6.5%
65
 
2.8%
58
 
2.5%
50
 
2.2%
45
 
1.9%
43
 
1.9%
41
 
1.8%
39
 
1.7%
Other values (260) 1471
63.4%
Lowercase Letter
ValueCountFrequency (%)
b 2
16.7%
r 2
16.7%
a 2
16.7%
e 2
16.7%
p 1
8.3%
o 1
8.3%
s 1
8.3%
h 1
8.3%
Decimal Number
ValueCountFrequency (%)
7 2
28.6%
2 1
14.3%
4 1
14.3%
3 1
14.3%
6 1
14.3%
1 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2322
95.9%
Common 85
 
3.5%
Latin 15
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
201
 
8.7%
159
 
6.8%
150
 
6.5%
65
 
2.8%
58
 
2.5%
50
 
2.2%
45
 
1.9%
43
 
1.9%
41
 
1.8%
39
 
1.7%
Other values (260) 1471
63.4%
Latin
ValueCountFrequency (%)
b 2
13.3%
r 2
13.3%
a 2
13.3%
e 2
13.3%
p 1
6.7%
o 1
6.7%
S 1
6.7%
s 1
6.7%
h 1
6.7%
G 1
6.7%
Common
ValueCountFrequency (%)
71
83.5%
( 3
 
3.5%
) 3
 
3.5%
7 2
 
2.4%
2 1
 
1.2%
4 1
 
1.2%
3 1
 
1.2%
? 1
 
1.2%
6 1
 
1.2%
1 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2322
95.9%
ASCII 100
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
201
 
8.7%
159
 
6.8%
150
 
6.5%
65
 
2.8%
58
 
2.5%
50
 
2.2%
45
 
1.9%
43
 
1.9%
41
 
1.8%
39
 
1.7%
Other values (260) 1471
63.4%
ASCII
ValueCountFrequency (%)
71
71.0%
( 3
 
3.0%
) 3
 
3.0%
b 2
 
2.0%
r 2
 
2.0%
a 2
 
2.0%
e 2
 
2.0%
7 2
 
2.0%
2 1
 
1.0%
4 1
 
1.0%
Other values (11) 11
 
11.0%
Distinct397
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum1999-01-04 00:00:00
Maximum2024-04-23 10:22:36
2024-05-11T08:52:05.109346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:52:05.605724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
I
530 
U
101 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
I 530
83.9%
U 101
 
16.0%
D 1
 
0.2%

Length

2024-05-11T08:52:06.035314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:06.581055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 530
83.9%
u 101
 
16.0%
d 1
 
0.2%
Distinct65
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:05:00
2024-05-11T08:52:06.904365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:52:07.415477image/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 size5.1 KiB
일반이용업
628 
이용업 기타
 
4

Length

Max length6
Median length5
Mean length5.0063291
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 628
99.4%
이용업 기타 4
 
0.6%

Length

2024-05-11T08:52:07.889575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:08.234353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 628
98.7%
이용업 4
 
0.6%
기타 4
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct425
Distinct (%)72.5%
Missing46
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean188460.82
Minimum184007.01
Maximum191209.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:08.590268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184007.01
5-th percentile185847.58
Q1186974.77
median189133.97
Q3190018.68
95-th percentile190541.56
Maximum191209.11
Range7202.1002
Interquartile range (IQR)3043.9075

Descriptive statistics

Standard deviation1754.592
Coefficient of variation (CV)0.0093101153
Kurtosis-1.0977615
Mean188460.82
Median Absolute Deviation (MAD)1243.9614
Skewness-0.39162209
Sum1.1043804 × 108
Variance3078593
MonotonicityNot monotonic
2024-05-11T08:52:09.078007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190541.558271971 8
 
1.3%
186212.084054908 6
 
0.9%
190352.405595566 5
 
0.8%
189432.385517396 5
 
0.8%
187918.667297764 5
 
0.8%
186143.039450549 5
 
0.8%
187798.86926511 5
 
0.8%
190143.595205387 5
 
0.8%
190349.885855531 4
 
0.6%
189047.773084017 4
 
0.6%
Other values (415) 534
84.5%
(Missing) 46
 
7.3%
ValueCountFrequency (%)
184007.005868999 1
0.2%
184019.610971952 2
0.3%
184401.204537439 1
0.2%
184404.38198014 1
0.2%
184406.083962228 1
0.2%
184432.049843714 1
0.2%
184435.943272169 1
0.2%
184457.791730837 2
0.3%
184490.087831918 1
0.2%
184861.891003458 1
0.2%
ValueCountFrequency (%)
191209.106092001 1
 
0.2%
191205.791543965 1
 
0.2%
191191.131566069 1
 
0.2%
191189.171149286 1
 
0.2%
191177.269899076 3
0.5%
191173.834097241 1
 
0.2%
191162.946632749 1
 
0.2%
191126.922861445 1
 
0.2%
191112.163912258 1
 
0.2%
191104.056779696 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct425
Distinct (%)72.5%
Missing46
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean443673.62
Minimum441868.93
Maximum445517.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:09.528162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441868.93
5-th percentile442286.31
Q1443069.83
median443702.01
Q3444353.9
95-th percentile444942.31
Maximum445517.26
Range3648.3264
Interquartile range (IQR)1284.0715

Descriptive statistics

Standard deviation835.38266
Coefficient of variation (CV)0.0018828766
Kurtosis-0.82354745
Mean443673.62
Median Absolute Deviation (MAD)648.28709
Skewness-0.11919405
Sum2.5999274 × 108
Variance697864.19
MonotonicityNot monotonic
2024-05-11T08:52:10.054677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443547.821727301 8
 
1.3%
443782.555826869 6
 
0.9%
444253.918572529 5
 
0.8%
444019.253245838 5
 
0.8%
444244.808913646 5
 
0.8%
443851.276037986 5
 
0.8%
444629.704821749 5
 
0.8%
442247.539159585 5
 
0.8%
444836.673561831 4
 
0.6%
444715.218537294 4
 
0.6%
Other values (415) 534
84.5%
(Missing) 46
 
7.3%
ValueCountFrequency (%)
441868.929927785 1
 
0.2%
441915.949256826 3
0.5%
441950.431750327 3
0.5%
441953.67598425 1
 
0.2%
441968.468347335 1
 
0.2%
441970.427503288 2
0.3%
441993.104862582 1
 
0.2%
441995.724053949 1
 
0.2%
442002.997913478 1
 
0.2%
442029.838784371 1
 
0.2%
ValueCountFrequency (%)
445517.256341461 1
0.2%
445430.97917589 1
0.2%
445381.540711693 1
0.2%
445369.517787461 1
0.2%
445331.670217458 1
0.2%
445295.068906157 1
0.2%
445294.073591369 1
0.2%
445279.562650792 1
0.2%
445278.145916981 1
0.2%
445274.192767605 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
일반이용업
601 
<NA>
 
28
이용업 기타
 
3

Length

Max length6
Median length5
Mean length4.960443
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 601
95.1%
<NA> 28
 
4.4%
이용업 기타 3
 
0.5%

Length

2024-05-11T08:52:10.727184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:11.120094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 601
94.6%
na 28
 
4.4%
이용업 3
 
0.5%
기타 3
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)3.8%
Missing158
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean1.8544304
Minimum0
Maximum24
Zeros235
Zeros (%)37.2%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:11.508914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.74919
Coefficient of variation (CV)1.4824984
Kurtosis17.374834
Mean1.8544304
Median Absolute Deviation (MAD)1
Skewness3.2664198
Sum879
Variance7.5580459
MonotonicityNot monotonic
2024-05-11T08:52:12.027312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 235
37.2%
3 79
 
12.5%
4 51
 
8.1%
2 48
 
7.6%
1 22
 
3.5%
5 16
 
2.5%
8 5
 
0.8%
6 5
 
0.8%
7 3
 
0.5%
15 2
 
0.3%
Other values (8) 8
 
1.3%
(Missing) 158
25.0%
ValueCountFrequency (%)
0 235
37.2%
1 22
 
3.5%
2 48
 
7.6%
3 79
 
12.5%
4 51
 
8.1%
5 16
 
2.5%
6 5
 
0.8%
7 3
 
0.5%
8 5
 
0.8%
9 1
 
0.2%
ValueCountFrequency (%)
24 1
 
0.2%
20 1
 
0.2%
18 1
 
0.2%
15 2
 
0.3%
14 1
 
0.2%
13 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
8 5
0.8%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.5%
Missing228
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean0.49752475
Minimum0
Maximum5
Zeros242
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:12.381074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.75051269
Coefficient of variation (CV)1.5084932
Kurtosis8.4733958
Mean0.49752475
Median Absolute Deviation (MAD)0
Skewness2.3267638
Sum201
Variance0.56326929
MonotonicityNot monotonic
2024-05-11T08:52:12.858051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 242
38.3%
1 139
22.0%
2 13
 
2.1%
3 6
 
0.9%
4 2
 
0.3%
5 2
 
0.3%
(Missing) 228
36.1%
ValueCountFrequency (%)
0 242
38.3%
1 139
22.0%
2 13
 
2.1%
3 6
 
0.9%
4 2
 
0.3%
5 2
 
0.3%
ValueCountFrequency (%)
5 2
 
0.3%
4 2
 
0.3%
3 6
 
0.9%
2 13
 
2.1%
1 139
22.0%
0 242
38.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.1%
Missing257
Missing (%)40.7%
Infinite0
Infinite (%)0.0%
Mean0.93066667
Minimum0
Maximum28
Zeros162
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:13.363209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum28
Range28
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7597683
Coefficient of variation (CV)1.8908685
Kurtosis150.61696
Mean0.93066667
Median Absolute Deviation (MAD)1
Skewness10.248678
Sum349
Variance3.0967843
MonotonicityNot monotonic
2024-05-11T08:52:13.732999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 162
25.6%
1 144
22.8%
2 46
 
7.3%
3 15
 
2.4%
5 4
 
0.6%
6 2
 
0.3%
8 1
 
0.2%
28 1
 
0.2%
(Missing) 257
40.7%
ValueCountFrequency (%)
0 162
25.6%
1 144
22.8%
2 46
 
7.3%
3 15
 
2.4%
5 4
 
0.6%
6 2
 
0.3%
8 1
 
0.2%
28 1
 
0.2%
ValueCountFrequency (%)
28 1
 
0.2%
8 1
 
0.2%
6 2
 
0.3%
5 4
 
0.6%
3 15
 
2.4%
2 46
 
7.3%
1 144
22.8%
0 162
25.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.7%
Missing415
Missing (%)65.7%
Infinite0
Infinite (%)0.0%
Mean1.4746544
Minimum0
Maximum28
Zeros21
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:14.227409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum28
Range28
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.081789
Coefficient of variation (CV)1.4117132
Kurtosis123.1878
Mean1.4746544
Median Absolute Deviation (MAD)0
Skewness9.9350389
Sum320
Variance4.3338454
MonotonicityNot monotonic
2024-05-11T08:52:14.642463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 134
 
21.2%
2 41
 
6.5%
0 21
 
3.3%
3 14
 
2.2%
5 4
 
0.6%
6 1
 
0.2%
8 1
 
0.2%
28 1
 
0.2%
(Missing) 415
65.7%
ValueCountFrequency (%)
0 21
 
3.3%
1 134
21.2%
2 41
 
6.5%
3 14
 
2.2%
5 4
 
0.6%
6 1
 
0.2%
8 1
 
0.2%
28 1
 
0.2%
ValueCountFrequency (%)
28 1
 
0.2%
8 1
 
0.2%
6 1
 
0.2%
5 4
 
0.6%
3 14
 
2.2%
2 41
 
6.5%
1 134
21.2%
0 21
 
3.3%
Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
337 
0
161 
1
122 
2
 
12

Length

Max length4
Median length4
Mean length2.5996835
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
53.3%
0 161
25.5%
1 122
 
19.3%
2 12
 
1.9%

Length

2024-05-11T08:52:15.214239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:15.792017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
53.3%
0 161
25.5%
1 122
 
19.3%
2 12
 
1.9%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
491 
1
113 
0
 
20
2
 
8

Length

Max length4
Median length4
Mean length3.3306962
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> 491
77.7%
1 113
 
17.9%
0 20
 
3.2%
2 8
 
1.3%

Length

2024-05-11T08:52:16.358349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:16.832219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 491
77.7%
1 113
 
17.9%
0 20
 
3.2%
2 8
 
1.3%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
371 
0
261 

Length

Max length4
Median length4
Mean length2.7610759
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
58.7%
0 261
41.3%

Length

2024-05-11T08:52:17.482674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:17.889282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
58.7%
0 261
41.3%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
371 
0
261 

Length

Max length4
Median length4
Mean length2.7610759
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
58.7%
0 261
41.3%

Length

2024-05-11T08:52:18.435505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:18.983039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
58.7%
0 261
41.3%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
371 
0
261 

Length

Max length4
Median length4
Mean length2.7610759
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
58.7%
0 261
41.3%

Length

2024-05-11T08:52:19.478644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:19.868103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
58.7%
0 261
41.3%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing49
Missing (%)7.8%
Memory size1.4 KiB
False
582 
True
 
1
(Missing)
 
49
ValueCountFrequency (%)
False 582
92.1%
True 1
 
0.2%
(Missing) 49
 
7.8%
2024-05-11T08:52:20.260006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)2.2%
Missing44
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean3.9642857
Minimum0
Maximum15
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-11T08:52:20.904487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median3
Q35
95-th percentile8
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1550819
Coefficient of variation (CV)0.54362427
Kurtosis3.1080888
Mean3.9642857
Median Absolute Deviation (MAD)1
Skewness1.491147
Sum2331
Variance4.6443782
MonotonicityNot monotonic
2024-05-11T08:52:21.544595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 167
26.4%
2 142
22.5%
4 101
16.0%
5 46
 
7.3%
6 37
 
5.9%
7 31
 
4.9%
8 30
 
4.7%
9 13
 
2.1%
1 10
 
1.6%
10 5
 
0.8%
Other values (3) 6
 
0.9%
(Missing) 44
 
7.0%
ValueCountFrequency (%)
0 2
 
0.3%
1 10
 
1.6%
2 142
22.5%
3 167
26.4%
4 101
16.0%
5 46
 
7.3%
6 37
 
5.9%
7 31
 
4.9%
8 30
 
4.7%
9 13
 
2.1%
ValueCountFrequency (%)
15 3
 
0.5%
11 1
 
0.2%
10 5
 
0.8%
9 13
 
2.1%
8 30
 
4.7%
7 31
 
4.9%
6 37
 
5.9%
5 46
 
7.3%
4 101
16.0%
3 167
26.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing632
Missing (%)100.0%
Memory size5.7 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
531 
임대
100 
자가
 
1

Length

Max length4
Median length4
Mean length3.6803797
Min length2

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> 531
84.0%
임대 100
 
15.8%
자가 1
 
0.2%

Length

2024-05-11T08:52:22.235441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:22.594426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 531
84.0%
임대 100
 
15.8%
자가 1
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
514 
0
118 

Length

Max length4
Median length4
Mean length3.4398734
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> 514
81.3%
0 118
 
18.7%

Length

2024-05-11T08:52:23.031556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:23.465522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 514
81.3%
0 118
 
18.7%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
594 
0
 
35
1
 
3

Length

Max length4
Median length4
Mean length3.8196203
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> 594
94.0%
0 35
 
5.5%
1 3
 
0.5%

Length

2024-05-11T08:52:23.840985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:24.180371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 594
94.0%
0 35
 
5.5%
1 3
 
0.5%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
594 
0
 
28
1
 
10

Length

Max length4
Median length4
Mean length3.8196203
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> 594
94.0%
0 28
 
4.4%
1 10
 
1.6%

Length

2024-05-11T08:52:24.637734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:25.097997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 594
94.0%
0 28
 
4.4%
1 10
 
1.6%

회수건조수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
545 
0
87 

Length

Max length4
Median length4
Mean length3.5870253
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> 545
86.2%
0 87
 
13.8%

Length

2024-05-11T08:52:25.567811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:25.950555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 545
86.2%
0 87
 
13.8%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
<NA>
546 
0
86 

Length

Max length4
Median length4
Mean length3.5917722
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> 546
86.4%
0 86
 
13.6%

Length

2024-05-11T08:52:26.278972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:52:26.648408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 546
86.4%
0 86
 
13.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing28
Missing (%)4.4%
Memory size1.4 KiB
False
603 
True
 
1
(Missing)
 
28
ValueCountFrequency (%)
False 603
95.4%
True 1
 
0.2%
(Missing) 28
 
4.4%
2024-05-11T08:52:26.940085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031600003160000-203-1966-0031719660813<NA>3폐업2폐업20040720<NA><NA><NA>02 855179522.50152872서울특별시 구로구 구로동 748-2번지<NA><NA>희망2002-07-24 00:00:00I2018-08-31 23:59:59.0일반이용업189999.119582442773.208151일반이용업000<NA>0<NA>000N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131600003160000-203-1970-0054119700411<NA>3폐업2폐업19970709<NA><NA><NA>02 0000020.49<NA>서울특별시 구로구 119-2번지<NA><NA>항동2001-09-26 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
231600003160000-203-1971-0034019710118<NA>3폐업2폐업19950821<NA><NA><NA>02 854278544.64152871서울특별시 구로구 구로동 722-7번지<NA><NA>일광2001-09-26 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
331600003160000-203-1973-0054219730129<NA>3폐업2폐업20030225<NA><NA><NA>02 0000014.42152815서울특별시 구로구 개봉동 349-5번지<NA><NA>온양2003-02-25 00:00:00I2018-08-31 23:59:59.0일반이용업187138.643002442838.479701일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431600003160000-203-1974-0033019740411<NA>3폐업2폐업20030225<NA><NA><NA>020000000034.09152887서울특별시 구로구 신도림동 365번지<NA><NA>한국타이어구내2003-02-25 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531600003160000-203-1975-0033419750127<NA>3폐업2폐업19960131<NA><NA><NA>02 0000011.22152855서울특별시 구로구 구로동 423-21번지<NA><NA>김포2001-09-26 00:00:00I2018-08-31 23:59:59.0일반이용업189650.060005443708.419018일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631600003160000-203-1976-0032119760302<NA>3폐업2폐업20210910<NA><NA><NA>02 685978924.14152824서울특별시 구로구 고척동 52-48서울특별시 구로구 경인로47길 67 (고척동)8223고려2021-09-10 11:18:16U2021-09-12 02:40:00.0일반이용업187953.87169444408.341996일반이용업301100000N5<NA><NA><NA><NA>00000N
731600003160000-203-1976-0032219760601<NA>1영업/정상1영업<NA><NA><NA><NA>022618295017.55152823서울특별시 구로구 고척동 51-8번지서울특별시 구로구 경인로47길 91 (고척동)8223포맨클럽2018-07-31 13:58:11I2018-08-31 23:59:59.0일반이용업187896.892972444507.643051일반이용업1<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831600003160000-203-1976-0032819760825<NA>3폐업2폐업20061026<NA><NA><NA>022613111917.64152140서울특별시 구로구 항동 140-3번지<NA><NA>성진2006-10-26 00:00:00I2018-08-31 23:59:59.0일반이용업184432.049844441868.929928일반이용업1<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931600003160000-203-1976-0053519760619<NA>3폐업2폐업19990304<NA><NA><NA>02 014.40152887서울특별시 구로구 신도림동 396-79번지<NA><NA>삼성이발소2001-09-26 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
62231600003160000-203-2021-0000320210427<NA>3폐업2폐업20210902<NA><NA><NA><NA>10.00152893서울특별시 구로구 오류동 38-1 대서프라자서울특별시 구로구 경인로23길 8, 대서프라자 지하1층 (오류동)8268오류2021-09-02 13:42:47U2021-09-04 02:40:00.0일반이용업186143.039451443851.276038일반이용업000000000N2<NA><NA><NA><NA>00000N
62331600003160000-203-2021-0000420210622<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.75152845서울특별시 구로구 구로동 130-74서울특별시 구로구 구로중앙로12길 13-44, 1층 (구로동)8304기분좋은날2021-06-23 13:23:12I2021-06-24 00:22:53.0일반이용업190374.209867443466.692855일반이용업00<NA><NA><NA><NA>000N3<NA><NA><NA><NA>00000N
62431600003160000-203-2021-000052021-10-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.00152-871서울특별시 구로구 구로동 714-18 1층서울특별시 구로구 구로동로13길 23-5 (구로동)8318후니커트샵2023-05-02 17:19:45U2022-12-05 00:04:00.0일반이용업189635.682429442764.22179<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62531600003160000-203-2021-0000620211109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.90152848서울특별시 구로구 구로동 187-3 예성유토피아서울특별시 구로구 도림천로 448, 예성유토피아 201동 지하1층 101호 (구로동)8378유토피아2021-11-12 10:03:35U2021-11-14 02:40:00.0일반이용업191002.243483442614.803166일반이용업000000000N3<NA><NA><NA><NA>00000N
62631600003160000-203-2021-0000720211221<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.00152804서울특별시 구로구 개봉동 108-13 샘물빌딩서울특별시 구로구 고척로27바길 6, 샘물빌딩 (개봉동)8243금강이용원2021-12-21 09:48:44I2021-12-23 00:22:42.0일반이용업186274.371938444942.306774일반이용업000000000N2<NA><NA><NA><NA>00000N
62731600003160000-203-2022-0000120220224<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.00152870서울특별시 구로구 구로동 705-50서울특별시 구로구 구로동로25길 18, 1층 (구로동)8309큐사랑2022-02-24 11:09:02I2022-02-26 00:22:49.0일반이용업189581.416865443175.396802일반이용업000000000N1<NA><NA><NA><NA>00000N
62831600003160000-203-2022-0000220220620<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.90152888서울특별시 구로구 신도림동 645 신도림3차동아아파트 상가동 201호서울특별시 구로구 신도림로 78, 상가동 2층 201호 (신도림동, 신도림3차동아아파트)8207아름다운 선택2022-06-20 11:56:15I2021-12-05 22:02:00.0일반이용업189691.819101445265.19194<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62931600003160000-203-2023-000012023-05-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.43152-834서울특별시 구로구 고척동 253-179서울특별시 구로구 고척로 135, 지층 (고척동)8246수이발2023-05-26 14:24:04I2022-12-04 22:08:00.0일반이용업186572.46189444505.470962<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63031600003160000-203-2023-000022023-08-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.92152-873서울특별시 구로구 구로동 769-264서울특별시 구로구 도림로 45 (구로동)8314오래이발소2023-08-23 10:56:57I2022-12-07 22:05:00.0일반이용업190122.917619442898.84024<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63131600003160000-203-2024-000012024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.08152-856서울특별시 구로구 구로동 513-1서울특별시 구로구 구로중앙로 106, 1층 (구로동)8300오땡큐 구로중앙점2024-04-23 10:22:36I2023-12-03 22:05:00.0일반이용업189891.00304444029.875082<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>