Overview

Dataset statistics

Number of variables47
Number of observations444
Missing cells4003
Missing cells (%)19.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory175.3 KiB
Average record size in memory404.3 B

Variable types

Categorical21
Text7
DateTime4
Unsupported4
Numeric9
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-19293/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.2%)Imbalance
위생업태명 is highly imbalanced (55.4%)Imbalance
사용시작지하층 is highly imbalanced (54.4%)Imbalance
사용끝지하층 is highly imbalanced (61.8%)Imbalance
조건부허가시작일자 is highly imbalanced (97.7%)Imbalance
조건부허가종료일자 is highly imbalanced (97.7%)Imbalance
여성종사자수 is highly imbalanced (62.9%)Imbalance
인허가취소일자 has 444 (100.0%) missing valuesMissing
폐업일자 has 140 (31.5%) missing valuesMissing
휴업시작일자 has 444 (100.0%) missing valuesMissing
휴업종료일자 has 444 (100.0%) missing valuesMissing
재개업일자 has 444 (100.0%) missing valuesMissing
전화번호 has 119 (26.8%) missing valuesMissing
소재지우편번호 has 10 (2.3%) missing valuesMissing
지번주소 has 10 (2.3%) missing valuesMissing
도로명주소 has 154 (34.7%) missing valuesMissing
도로명우편번호 has 155 (34.9%) missing valuesMissing
좌표정보(X) has 5 (1.1%) missing valuesMissing
좌표정보(Y) has 5 (1.1%) missing valuesMissing
건물지상층수 has 126 (28.4%) missing valuesMissing
건물지하층수 has 143 (32.2%) missing valuesMissing
사용시작지상층 has 175 (39.4%) missing valuesMissing
사용끝지상층 has 245 (55.2%) missing valuesMissing
발한실여부 has 83 (18.7%) missing valuesMissing
조건부허가신고사유 has 443 (99.8%) missing valuesMissing
남성종사자수 has 340 (76.6%) missing valuesMissing
다중이용업소여부 has 74 (16.7%) 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
소재지면적 has 65 (14.6%) zerosZeros
건물지상층수 has 230 (51.8%) zerosZeros
건물지하층수 has 253 (57.0%) zerosZeros
사용시작지상층 has 66 (14.9%) zerosZeros
사용끝지상층 has 18 (4.1%) zerosZeros
남성종사자수 has 96 (21.6%) zerosZeros

Reproduction

Analysis started2024-04-29 19:53:03.674985
Analysis finished2024-04-29 19:53:04.656938
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3160000
444 

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 444
100.0%

Length

2024-04-30T04:53:04.724813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:04.802683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 444
100.0%

관리번호
Text

UNIQUE 

Distinct444
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:53:04.943749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9768
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

Unique444 ?
Unique (%)100.0%

Sample

1st row3160000-206-1991-02102
2nd row3160000-206-1993-02103
3rd row3160000-206-1993-02104
4th row3160000-206-1993-02105
5th row3160000-206-1993-02106
ValueCountFrequency (%)
3160000-206-1991-02102 1
 
0.2%
3160000-206-2014-00016 1
 
0.2%
3160000-206-2015-00009 1
 
0.2%
3160000-206-2015-00008 1
 
0.2%
3160000-206-2015-00007 1
 
0.2%
3160000-206-2015-00006 1
 
0.2%
3160000-206-2015-00004 1
 
0.2%
3160000-206-2015-00003 1
 
0.2%
3160000-206-2015-00002 1
 
0.2%
3160000-206-2015-00001 1
 
0.2%
Other values (434) 434
97.7%
2024-04-30T04:53:05.224214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4351
44.5%
- 1332
 
13.6%
2 1079
 
11.0%
6 974
 
10.0%
1 960
 
9.8%
3 561
 
5.7%
9 148
 
1.5%
4 97
 
1.0%
7 94
 
1.0%
5 90
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8436
86.4%
Dash Punctuation 1332
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4351
51.6%
2 1079
 
12.8%
6 974
 
11.5%
1 960
 
11.4%
3 561
 
6.7%
9 148
 
1.8%
4 97
 
1.1%
7 94
 
1.1%
5 90
 
1.1%
8 82
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1332
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9768
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4351
44.5%
- 1332
 
13.6%
2 1079
 
11.0%
6 974
 
10.0%
1 960
 
9.8%
3 561
 
5.7%
9 148
 
1.5%
4 97
 
1.0%
7 94
 
1.0%
5 90
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4351
44.5%
- 1332
 
13.6%
2 1079
 
11.0%
6 974
 
10.0%
1 960
 
9.8%
3 561
 
5.7%
9 148
 
1.5%
4 97
 
1.0%
7 94
 
1.0%
5 90
 
0.9%
Distinct416
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1991-04-30 00:00:00
Maximum2024-03-28 00:00:00
2024-04-30T04:53:05.367588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:05.509874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3
304 
1
140 

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 (%)
3 304
68.5%
1 140
31.5%

Length

2024-04-30T04:53:05.624123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:05.721443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 304
68.5%
1 140
31.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
304 
영업/정상
140 

Length

Max length5
Median length2
Mean length2.9459459
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 304
68.5%
영업/정상 140
31.5%

Length

2024-04-30T04:53:05.823764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:05.918800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 304
68.5%
영업/정상 140
31.5%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2
304 
1
140 

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 (%)
2 304
68.5%
1 140
31.5%

Length

2024-04-30T04:53:06.000763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:06.085833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 304
68.5%
1 140
31.5%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
304 
영업
140 

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 304
68.5%
영업 140
31.5%

Length

2024-04-30T04:53:06.181653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:06.269756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 304
68.5%
영업 140
31.5%

폐업일자
Date

MISSING 

Distinct251
Distinct (%)82.6%
Missing140
Missing (%)31.5%
Memory size3.6 KiB
Minimum1995-01-13 00:00:00
Maximum2024-03-22 00:00:00
2024-04-30T04:53:06.367919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:06.479490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

전화번호
Text

MISSING 

Distinct308
Distinct (%)94.8%
Missing119
Missing (%)26.8%
Memory size3.6 KiB
2024-04-30T04:53:06.694789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.415385
Min length6

Characters and Unicode

Total characters3385
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

Unique292 ?
Unique (%)89.8%

Sample

1st row02 00000
2nd row02 6317822
3rd row02 6165008
4th row02 6148112
5th row0208390069
ValueCountFrequency (%)
02 192
34.2%
070 4
 
0.7%
828 4
 
0.7%
8532931 3
 
0.5%
8566955 2
 
0.4%
853 2
 
0.4%
830 2
 
0.4%
031 2
 
0.4%
859 2
 
0.4%
8181312 2
 
0.4%
Other values (333) 347
61.7%
2024-04-30T04:53:07.064074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 608
18.0%
2 591
17.5%
8 326
9.6%
312
9.2%
6 302
8.9%
1 252
7.4%
3 236
 
7.0%
5 233
 
6.9%
7 182
 
5.4%
4 173
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3073
90.8%
Space Separator 312
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 608
19.8%
2 591
19.2%
8 326
10.6%
6 302
9.8%
1 252
8.2%
3 236
 
7.7%
5 233
 
7.6%
7 182
 
5.9%
4 173
 
5.6%
9 170
 
5.5%
Space Separator
ValueCountFrequency (%)
312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3385
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 608
18.0%
2 591
17.5%
8 326
9.6%
312
9.2%
6 302
8.9%
1 252
7.4%
3 236
 
7.0%
5 233
 
6.9%
7 182
 
5.4%
4 173
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 608
18.0%
2 591
17.5%
8 326
9.6%
312
9.2%
6 302
8.9%
1 252
7.4%
3 236
 
7.0%
5 233
 
6.9%
7 182
 
5.4%
4 173
 
5.1%

소재지면적
Real number (ℝ)

ZEROS 

Distinct281
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.880586
Minimum0
Maximum4364.73
Zeros65
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:07.197778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116.3
median34
Q365.4375
95-th percentile158.34
Maximum4364.73
Range4364.73
Interquartile range (IQR)49.1375

Descriptive statistics

Standard deviation215.50577
Coefficient of variation (CV)3.539811
Kurtosis361.22476
Mean60.880586
Median Absolute Deviation (MAD)23.21
Skewness18.177931
Sum27030.98
Variance46442.735
MonotonicityNot monotonic
2024-04-30T04:53:07.307308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 65
 
14.6%
16.5 8
 
1.8%
20.0 7
 
1.6%
18.0 6
 
1.4%
30.0 6
 
1.4%
15.0 6
 
1.4%
33.0 5
 
1.1%
40.0 5
 
1.1%
3.0 5
 
1.1%
36.0 5
 
1.1%
Other values (271) 326
73.4%
ValueCountFrequency (%)
0.0 65
14.6%
1.1 3
 
0.7%
1.3 1
 
0.2%
3.0 5
 
1.1%
3.3 2
 
0.5%
3.5 1
 
0.2%
4.96 1
 
0.2%
5.76 1
 
0.2%
6.0 1
 
0.2%
6.6 1
 
0.2%
ValueCountFrequency (%)
4364.73 1
0.2%
672.12 1
0.2%
555.41 1
0.2%
477.49 1
0.2%
335.8 1
0.2%
300.1 1
0.2%
288.44 1
0.2%
287.55 1
0.2%
281.5 1
0.2%
272.31 1
0.2%

소재지우편번호
Text

MISSING 

Distinct106
Distinct (%)24.4%
Missing10
Missing (%)2.3%
Memory size3.6 KiB
2024-04-30T04:53:07.544968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1221198
Min length6

Characters and Unicode

Total characters2657
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

Unique41 ?
Unique (%)9.4%

Sample

1st row152816
2nd row152080
3rd row152804
4th row152823
5th row152858
ValueCountFrequency (%)
152848 46
 
10.6%
152842 27
 
6.2%
152838 21
 
4.8%
152880 16
 
3.7%
152841 14
 
3.2%
152-848 14
 
3.2%
152858 12
 
2.8%
152865 12
 
2.8%
152828 11
 
2.5%
152800 10
 
2.3%
Other values (96) 251
57.8%
2024-04-30T04:53:07.891428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 552
20.8%
2 522
19.6%
5 515
19.4%
1 485
18.3%
4 180
 
6.8%
0 101
 
3.8%
6 85
 
3.2%
7 69
 
2.6%
- 53
 
2.0%
3 50
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2604
98.0%
Dash Punctuation 53
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 552
21.2%
2 522
20.0%
5 515
19.8%
1 485
18.6%
4 180
 
6.9%
0 101
 
3.9%
6 85
 
3.3%
7 69
 
2.6%
3 50
 
1.9%
9 45
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2657
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 552
20.8%
2 522
19.6%
5 515
19.4%
1 485
18.3%
4 180
 
6.8%
0 101
 
3.8%
6 85
 
3.2%
7 69
 
2.6%
- 53
 
2.0%
3 50
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 552
20.8%
2 522
19.6%
5 515
19.4%
1 485
18.3%
4 180
 
6.8%
0 101
 
3.8%
6 85
 
3.2%
7 69
 
2.6%
- 53
 
2.0%
3 50
 
1.9%

지번주소
Text

MISSING 

Distinct404
Distinct (%)93.1%
Missing10
Missing (%)2.3%
Memory size3.6 KiB
2024-04-30T04:53:08.122977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length40
Mean length27.610599
Min length17

Characters and Unicode

Total characters11983
Distinct characters247
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)87.8%

Sample

1st row서울특별시 구로구 개봉동 403-117
2nd row서울특별시 구로구 고척동 612-7 1 7호
3rd row서울특별시 구로구 개봉동 113-14
4th row서울특별시 구로구 고척동 50-48
5th row서울특별시 구로구 구로동 496-11
ValueCountFrequency (%)
구로구 436
18.8%
서울특별시 434
18.7%
구로동 291
 
12.6%
개봉동 36
 
1.6%
오류동 31
 
1.3%
고척동 31
 
1.3%
신도림동 15
 
0.6%
가리봉동 14
 
0.6%
2층 13
 
0.6%
3층 13
 
0.6%
Other values (644) 1002
43.3%
2024-04-30T04:53:08.503834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2140
17.9%
1191
 
9.9%
751
 
6.3%
1 609
 
5.1%
481
 
4.0%
438
 
3.7%
437
 
3.6%
436
 
3.6%
435
 
3.6%
434
 
3.6%
Other values (237) 4631
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6663
55.6%
Decimal Number 2635
 
22.0%
Space Separator 2140
 
17.9%
Dash Punctuation 403
 
3.4%
Uppercase Letter 43
 
0.4%
Close Punctuation 36
 
0.3%
Open Punctuation 36
 
0.3%
Other Punctuation 11
 
0.1%
Lowercase Letter 11
 
0.1%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1191
17.9%
751
11.3%
481
 
7.2%
438
 
6.6%
437
 
6.6%
436
 
6.5%
435
 
6.5%
434
 
6.5%
198
 
3.0%
84
 
1.3%
Other values (198) 1778
26.7%
Uppercase Letter
ValueCountFrequency (%)
A 11
25.6%
K 9
20.9%
B 6
14.0%
T 5
11.6%
S 2
 
4.7%
D 2
 
4.7%
H 2
 
4.7%
O 1
 
2.3%
W 1
 
2.3%
E 1
 
2.3%
Other values (3) 3
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 609
23.1%
0 328
12.4%
2 320
12.1%
3 266
10.1%
4 264
10.0%
7 184
 
7.0%
6 183
 
6.9%
5 180
 
6.8%
8 168
 
6.4%
9 133
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
36.4%
r 1
 
9.1%
t 1
 
9.1%
i 1
 
9.1%
b 1
 
9.1%
z 1
 
9.1%
n 1
 
9.1%
c 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
. 3
 
27.3%
Letter Number
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
2140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 403
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6663
55.6%
Common 5261
43.9%
Latin 59
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1191
17.9%
751
11.3%
481
 
7.2%
438
 
6.6%
437
 
6.6%
436
 
6.5%
435
 
6.5%
434
 
6.5%
198
 
3.0%
84
 
1.3%
Other values (198) 1778
26.7%
Latin
ValueCountFrequency (%)
A 11
18.6%
K 9
15.3%
B 6
10.2%
T 5
 
8.5%
4
 
6.8%
e 4
 
6.8%
S 2
 
3.4%
D 2
 
3.4%
H 2
 
3.4%
r 1
 
1.7%
Other values (13) 13
22.0%
Common
ValueCountFrequency (%)
2140
40.7%
1 609
 
11.6%
- 403
 
7.7%
0 328
 
6.2%
2 320
 
6.1%
3 266
 
5.1%
4 264
 
5.0%
7 184
 
3.5%
6 183
 
3.5%
5 180
 
3.4%
Other values (6) 384
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6663
55.6%
ASCII 5315
44.4%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2140
40.3%
1 609
 
11.5%
- 403
 
7.6%
0 328
 
6.2%
2 320
 
6.0%
3 266
 
5.0%
4 264
 
5.0%
7 184
 
3.5%
6 183
 
3.4%
5 180
 
3.4%
Other values (27) 438
 
8.2%
Hangul
ValueCountFrequency (%)
1191
17.9%
751
11.3%
481
 
7.2%
438
 
6.6%
437
 
6.6%
436
 
6.5%
435
 
6.5%
434
 
6.5%
198
 
3.0%
84
 
1.3%
Other values (198) 1778
26.7%
Number Forms
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

도로명주소
Text

MISSING 

Distinct277
Distinct (%)95.5%
Missing154
Missing (%)34.7%
Memory size3.6 KiB
2024-04-30T04:53:08.754026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length47
Mean length38.593103
Min length22

Characters and Unicode

Total characters11192
Distinct characters233
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)91.4%

Sample

1st row서울특별시 구로구 구로중앙로3길 14 (구로동)
2nd row서울특별시 구로구 경인로 579-1, B동 3층 4호 (신도림동, 안성빌딩)
3rd row서울특별시 구로구 구로동로 240 (구로동,세일빌딩 401호)
4th row서울특별시 구로구 디지털로26길 5, 에이스하이엔드타워1차 209호 (구로동)
5th row서울특별시 구로구 공원로 3 (구로동,선경오피스텔 1층)
ValueCountFrequency (%)
서울특별시 290
 
14.2%
구로구 290
 
14.2%
구로동 170
 
8.3%
1층 27
 
1.3%
경인로 23
 
1.1%
개봉동 23
 
1.1%
2층 22
 
1.1%
공원로 19
 
0.9%
구로중앙로 19
 
0.9%
고척동 18
 
0.9%
Other values (573) 1146
56.0%
2024-04-30T04:53:09.125774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1757
 
15.7%
853
 
7.6%
847
 
7.6%
1 430
 
3.8%
, 387
 
3.5%
373
 
3.3%
2 318
 
2.8%
( 312
 
2.8%
) 312
 
2.8%
299
 
2.7%
Other values (223) 5304
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6372
56.9%
Decimal Number 1925
 
17.2%
Space Separator 1757
 
15.7%
Other Punctuation 389
 
3.5%
Open Punctuation 312
 
2.8%
Close Punctuation 312
 
2.8%
Dash Punctuation 77
 
0.7%
Uppercase Letter 42
 
0.4%
Letter Number 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
853
 
13.4%
847
 
13.3%
373
 
5.9%
299
 
4.7%
296
 
4.6%
292
 
4.6%
291
 
4.6%
290
 
4.6%
228
 
3.6%
180
 
2.8%
Other values (190) 2423
38.0%
Uppercase Letter
ValueCountFrequency (%)
A 10
23.8%
K 7
16.7%
B 7
16.7%
T 5
11.9%
C 2
 
4.8%
R 2
 
4.8%
D 2
 
4.8%
P 1
 
2.4%
E 1
 
2.4%
J 1
 
2.4%
Other values (4) 4
 
9.5%
Decimal Number
ValueCountFrequency (%)
1 430
22.3%
2 318
16.5%
3 241
12.5%
0 232
12.1%
5 177
9.2%
4 141
 
7.3%
7 107
 
5.6%
6 102
 
5.3%
8 101
 
5.2%
9 76
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 387
99.5%
. 2
 
0.5%
Letter Number
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Space Separator
ValueCountFrequency (%)
1757
100.0%
Open Punctuation
ValueCountFrequency (%)
( 312
100.0%
Close Punctuation
ValueCountFrequency (%)
) 312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6372
56.9%
Common 4774
42.7%
Latin 46
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
853
 
13.4%
847
 
13.3%
373
 
5.9%
299
 
4.7%
296
 
4.6%
292
 
4.6%
291
 
4.6%
290
 
4.6%
228
 
3.6%
180
 
2.8%
Other values (190) 2423
38.0%
Common
ValueCountFrequency (%)
1757
36.8%
1 430
 
9.0%
, 387
 
8.1%
2 318
 
6.7%
( 312
 
6.5%
) 312
 
6.5%
3 241
 
5.0%
0 232
 
4.9%
5 177
 
3.7%
4 141
 
3.0%
Other values (7) 467
 
9.8%
Latin
ValueCountFrequency (%)
A 10
21.7%
K 7
15.2%
B 7
15.2%
T 5
10.9%
3
 
6.5%
C 2
 
4.3%
R 2
 
4.3%
D 2
 
4.3%
P 1
 
2.2%
E 1
 
2.2%
Other values (6) 6
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6372
56.9%
ASCII 4816
43.0%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1757
36.5%
1 430
 
8.9%
, 387
 
8.0%
2 318
 
6.6%
( 312
 
6.5%
) 312
 
6.5%
3 241
 
5.0%
0 232
 
4.8%
5 177
 
3.7%
4 141
 
2.9%
Other values (21) 509
 
10.6%
Hangul
ValueCountFrequency (%)
853
 
13.4%
847
 
13.3%
373
 
5.9%
299
 
4.7%
296
 
4.6%
292
 
4.6%
291
 
4.6%
290
 
4.6%
228
 
3.6%
180
 
2.8%
Other values (190) 2423
38.0%
Number Forms
ValueCountFrequency (%)
3
75.0%
1
 
25.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)34.6%
Missing155
Missing (%)34.9%
Infinite0
Infinite (%)0.0%
Mean8301.526
Minimum8200
Maximum8395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:09.257951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8200
5-th percentile8212
Q18263
median8298
Q38355
95-th percentile8390
Maximum8395
Range195
Interquartile range (IQR)92

Descriptive statistics

Standard deviation58.39711
Coefficient of variation (CV)0.0070345031
Kurtosis-1.0661264
Mean8301.526
Median Absolute Deviation (MAD)43
Skewness0.039487917
Sum2399141
Variance3410.2224
MonotonicityNot monotonic
2024-04-30T04:53:09.389400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8298 20
 
4.5%
8376 18
 
4.1%
8215 15
 
3.4%
8390 10
 
2.3%
8301 10
 
2.3%
8271 10
 
2.3%
8302 9
 
2.0%
8334 7
 
1.6%
8294 7
 
1.6%
8212 7
 
1.6%
Other values (90) 176
39.6%
(Missing) 155
34.9%
ValueCountFrequency (%)
8200 1
 
0.2%
8203 1
 
0.2%
8204 1
 
0.2%
8206 2
 
0.5%
8208 3
 
0.7%
8209 1
 
0.2%
8211 1
 
0.2%
8212 7
1.6%
8213 2
 
0.5%
8215 15
3.4%
ValueCountFrequency (%)
8395 1
 
0.2%
8394 1
 
0.2%
8393 4
 
0.9%
8392 4
 
0.9%
8391 3
 
0.7%
8390 10
2.3%
8389 5
1.1%
8385 2
 
0.5%
8384 1
 
0.2%
8382 1
 
0.2%
Distinct436
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-30T04:53:09.796287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length14
Mean length7.7972973
Min length2

Characters and Unicode

Total characters3462
Distinct characters348
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

Unique428 ?
Unique (%)96.4%

Sample

1st row휘창기업
2nd row한신공무
3rd row용운실업
4th row태일케미칼
5th row유니나환경관리
ValueCountFrequency (%)
주식회사 71
 
12.8%
사회복지법인 3
 
0.5%
3
 
0.5%
사단법인 3
 
0.5%
원크린 2
 
0.4%
멀티씨엠 2
 
0.4%
금잔디 2
 
0.4%
cs 2
 
0.4%
코리아 2
 
0.4%
세상 2
 
0.4%
Other values (452) 463
83.4%
2024-04-30T04:53:10.134573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
292
 
8.4%
) 214
 
6.2%
( 212
 
6.1%
113
 
3.3%
113
 
3.3%
100
 
2.9%
90
 
2.6%
88
 
2.5%
80
 
2.3%
67
 
1.9%
Other values (338) 2093
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2856
82.5%
Close Punctuation 214
 
6.2%
Open Punctuation 212
 
6.1%
Space Separator 113
 
3.3%
Uppercase Letter 35
 
1.0%
Lowercase Letter 27
 
0.8%
Other Punctuation 4
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
292
 
10.2%
113
 
4.0%
100
 
3.5%
90
 
3.2%
88
 
3.1%
80
 
2.8%
67
 
2.3%
65
 
2.3%
48
 
1.7%
45
 
1.6%
Other values (307) 1868
65.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
a 4
14.8%
n 3
11.1%
r 2
 
7.4%
i 2
 
7.4%
g 2
 
7.4%
m 2
 
7.4%
q 1
 
3.7%
t 1
 
3.7%
d 1
 
3.7%
Other values (5) 5
18.5%
Uppercase Letter
ValueCountFrequency (%)
S 8
22.9%
C 7
20.0%
M 6
17.1%
G 3
 
8.6%
N 3
 
8.6%
E 3
 
8.6%
J 2
 
5.7%
D 1
 
2.9%
K 1
 
2.9%
B 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
& 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 214
100.0%
Open Punctuation
ValueCountFrequency (%)
( 212
100.0%
Space Separator
ValueCountFrequency (%)
113
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2856
82.5%
Common 544
 
15.7%
Latin 62
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
292
 
10.2%
113
 
4.0%
100
 
3.5%
90
 
3.2%
88
 
3.1%
80
 
2.8%
67
 
2.3%
65
 
2.3%
48
 
1.7%
45
 
1.6%
Other values (307) 1868
65.4%
Latin
ValueCountFrequency (%)
S 8
12.9%
C 7
 
11.3%
M 6
 
9.7%
e 4
 
6.5%
a 4
 
6.5%
G 3
 
4.8%
n 3
 
4.8%
N 3
 
4.8%
E 3
 
4.8%
J 2
 
3.2%
Other values (15) 19
30.6%
Common
ValueCountFrequency (%)
) 214
39.3%
( 212
39.0%
113
20.8%
. 3
 
0.6%
& 1
 
0.2%
2 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2856
82.5%
ASCII 606
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
292
 
10.2%
113
 
4.0%
100
 
3.5%
90
 
3.2%
88
 
3.1%
80
 
2.8%
67
 
2.3%
65
 
2.3%
48
 
1.7%
45
 
1.6%
Other values (307) 1868
65.4%
ASCII
ValueCountFrequency (%)
) 214
35.3%
( 212
35.0%
113
18.6%
S 8
 
1.3%
C 7
 
1.2%
M 6
 
1.0%
e 4
 
0.7%
a 4
 
0.7%
G 3
 
0.5%
n 3
 
0.5%
Other values (21) 32
 
5.3%
Distinct395
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1999-02-24 00:00:00
Maximum2024-04-24 09:55:38
2024-04-30T04:53:10.247124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:10.385640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
I
305 
U
139 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 305
68.7%
U 139
31.3%

Length

2024-04-30T04:53:10.529554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:10.618970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 305
68.7%
u 139
31.3%
Distinct165
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T04:53:10.725773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:10.839357image/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 size3.6 KiB
건물위생관리업
441 
건물위생관리업 기타
 
3

Length

Max length10
Median length7
Mean length7.0202703
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 441
99.3%
건물위생관리업 기타 3
 
0.7%

Length

2024-04-30T04:53:10.971179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:11.062315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 444
99.3%
기타 3
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct271
Distinct (%)61.7%
Missing5
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean189128.97
Minimum183834.39
Maximum191229.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:11.166287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183834.39
5-th percentile185706.49
Q1187826.96
median189863.72
Q3190394.39
95-th percentile190825.33
Maximum191229.9
Range7395.5018
Interquartile range (IQR)2567.4346

Descriptive statistics

Standard deviation1732.4303
Coefficient of variation (CV)0.0091600472
Kurtosis0.26894138
Mean189128.97
Median Absolute Deviation (MAD)641.06289
Skewness-1.1641524
Sum83027619
Variance3001314.8
MonotonicityNot monotonic
2024-04-30T04:53:11.279833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190541.499138217 11
 
2.5%
190410.047738361 10
 
2.3%
190479.902194476 10
 
2.3%
189065.067799932 8
 
1.8%
190394.394227379 7
 
1.6%
190822.851419439 6
 
1.4%
186144.880821445 6
 
1.4%
190295.141464557 6
 
1.4%
187619.596959162 5
 
1.1%
189570.360930049 5
 
1.1%
Other values (261) 365
82.2%
ValueCountFrequency (%)
183834.394571484 1
0.2%
184228.841799469 2
0.5%
184300.395659961 2
0.5%
184405.318446064 1
0.2%
184432.142369759 1
0.2%
184573.723475124 1
0.2%
184655.927434086 1
0.2%
184725.796610134 1
0.2%
184757.189120902 1
0.2%
184842.081099299 1
0.2%
ValueCountFrequency (%)
191229.896362573 1
 
0.2%
191205.791543965 1
 
0.2%
191191.131566069 3
0.7%
191110.143101304 1
 
0.2%
191081.320138999 1
 
0.2%
191045.678761051 1
 
0.2%
191029.307108884 2
0.5%
191020.264430044 1
 
0.2%
190991.073851399 1
 
0.2%
190987.661570042 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct270
Distinct (%)61.5%
Missing5
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean443601.93
Minimum441596.48
Maximum445795.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:11.409083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441596.48
5-th percentile442253.13
Q1442751.42
median443736.09
Q3444245.56
95-th percentile444791.79
Maximum445795.07
Range4198.5846
Interquartile range (IQR)1494.1438

Descriptive statistics

Standard deviation838.654
Coefficient of variation (CV)0.0018905553
Kurtosis-0.90147649
Mean443601.93
Median Absolute Deviation (MAD)604.03509
Skewness-0.17904662
Sum1.9474125 × 108
Variance703340.53
MonotonicityNot monotonic
2024-04-30T04:53:11.522944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442708.140860448 11
 
2.5%
443953.502895004 10
 
2.3%
442751.419539641 10
 
2.3%
444456.127223357 8
 
1.8%
444191.966689461 7
 
1.6%
443706.570673762 6
 
1.4%
442253.132895893 6
 
1.4%
443841.455440573 6
 
1.4%
443850.860193572 5
 
1.1%
443952.558147738 5
 
1.1%
Other values (260) 365
82.2%
ValueCountFrequency (%)
441596.481083253 2
 
0.5%
441868.707510887 1
 
0.2%
441968.468347335 1
 
0.2%
442033.558960014 1
 
0.2%
442071.447779897 1
 
0.2%
442154.992807483 5
1.1%
442203.635214803 1
 
0.2%
442206.887162369 1
 
0.2%
442216.317475069 1
 
0.2%
442217.790627324 1
 
0.2%
ValueCountFrequency (%)
445795.065707973 1
 
0.2%
445519.342526518 1
 
0.2%
445342.593707823 1
 
0.2%
445250.538868558 3
0.7%
445159.400640086 1
 
0.2%
445157.626366229 1
 
0.2%
445062.741303 1
 
0.2%
444978.682746138 3
0.7%
444898.367647601 1
 
0.2%
444891.605594405 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
건물위생관리업
367 
<NA>
74 
건물위생관리업 기타
 
3

Length

Max length10
Median length7
Mean length6.5202703
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 367
82.7%
<NA> 74
 
16.7%
건물위생관리업 기타 3
 
0.7%

Length

2024-04-30T04:53:11.634530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:11.736140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 370
82.8%
na 74
 
16.6%
기타 3
 
0.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)5.0%
Missing126
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean1.5031447
Minimum0
Maximum17
Zeros230
Zeros (%)51.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:11.815304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8
Maximum17
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1147846
Coefficient of variation (CV)2.0721788
Kurtosis7.2242356
Mean1.5031447
Median Absolute Deviation (MAD)0
Skewness2.6089456
Sum478
Variance9.7018828
MonotonicityNot monotonic
2024-04-30T04:53:11.913986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 230
51.8%
4 22
 
5.0%
5 14
 
3.2%
3 13
 
2.9%
1 7
 
1.6%
2 6
 
1.4%
6 5
 
1.1%
10 5
 
1.1%
7 4
 
0.9%
15 4
 
0.9%
Other values (6) 8
 
1.8%
(Missing) 126
28.4%
ValueCountFrequency (%)
0 230
51.8%
1 7
 
1.6%
2 6
 
1.4%
3 13
 
2.9%
4 22
 
5.0%
5 14
 
3.2%
6 5
 
1.1%
7 4
 
0.9%
8 2
 
0.5%
10 5
 
1.1%
ValueCountFrequency (%)
17 1
 
0.2%
15 4
0.9%
14 1
 
0.2%
13 1
 
0.2%
12 1
 
0.2%
11 2
 
0.5%
10 5
1.1%
8 2
 
0.5%
7 4
0.9%
6 5
1.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.0%
Missing143
Missing (%)32.2%
Infinite0
Infinite (%)0.0%
Mean0.27574751
Minimum0
Maximum5
Zeros253
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:12.006279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.77483968
Coefficient of variation (CV)2.8099608
Kurtosis14.311629
Mean0.27574751
Median Absolute Deviation (MAD)0
Skewness3.5900379
Sum83
Variance0.60037652
MonotonicityNot monotonic
2024-04-30T04:53:12.089931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 253
57.0%
1 30
 
6.8%
2 7
 
1.6%
3 7
 
1.6%
5 2
 
0.5%
4 2
 
0.5%
(Missing) 143
32.2%
ValueCountFrequency (%)
0 253
57.0%
1 30
 
6.8%
2 7
 
1.6%
3 7
 
1.6%
4 2
 
0.5%
5 2
 
0.5%
ValueCountFrequency (%)
5 2
 
0.5%
4 2
 
0.5%
3 7
 
1.6%
2 7
 
1.6%
1 30
 
6.8%
0 253
57.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)6.3%
Missing175
Missing (%)39.4%
Infinite0
Infinite (%)0.0%
Mean3.1115242
Minimum0
Maximum17
Zeros66
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:12.182709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile10.6
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6306399
Coefficient of variation (CV)1.1668365
Kurtosis3.6482598
Mean3.1115242
Median Absolute Deviation (MAD)2
Skewness1.8739105
Sum837
Variance13.181546
MonotonicityNot monotonic
2024-04-30T04:53:12.278304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 66
 
14.9%
1 43
 
9.7%
2 42
 
9.5%
3 40
 
9.0%
4 19
 
4.3%
5 14
 
3.2%
8 8
 
1.8%
9 7
 
1.6%
7 7
 
1.6%
6 6
 
1.4%
Other values (7) 17
 
3.8%
(Missing) 175
39.4%
ValueCountFrequency (%)
0 66
14.9%
1 43
9.7%
2 42
9.5%
3 40
9.0%
4 19
 
4.3%
5 14
 
3.2%
6 6
 
1.4%
7 7
 
1.6%
8 8
 
1.8%
9 7
 
1.6%
ValueCountFrequency (%)
17 4
0.9%
16 1
 
0.2%
15 1
 
0.2%
14 4
0.9%
12 3
 
0.7%
11 1
 
0.2%
10 3
 
0.7%
9 7
1.6%
8 8
1.8%
7 7
1.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)8.5%
Missing245
Missing (%)55.2%
Infinite0
Infinite (%)0.0%
Mean4.7839196
Minimum0
Maximum203
Zeros18
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:12.383045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile14
Maximum203
Range203
Interquartile range (IQR)4

Descriptive statistics

Standard deviation14.607959
Coefficient of variation (CV)3.0535545
Kurtosis173.45319
Mean4.7839196
Median Absolute Deviation (MAD)2
Skewness12.762332
Sum952
Variance213.39247
MonotonicityNot monotonic
2024-04-30T04:53:12.487248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 38
 
8.6%
3 37
 
8.3%
2 36
 
8.1%
0 18
 
4.1%
4 17
 
3.8%
5 12
 
2.7%
8 7
 
1.6%
7 7
 
1.6%
9 6
 
1.4%
6 5
 
1.1%
Other values (7) 16
 
3.6%
(Missing) 245
55.2%
ValueCountFrequency (%)
0 18
4.1%
1 38
8.6%
2 36
8.1%
3 37
8.3%
4 17
3.8%
5 12
 
2.7%
6 5
 
1.1%
7 7
 
1.6%
8 7
 
1.6%
9 6
 
1.4%
ValueCountFrequency (%)
203 1
 
0.2%
17 4
0.9%
16 1
 
0.2%
15 1
 
0.2%
14 4
0.9%
12 3
0.7%
10 2
 
0.5%
9 6
1.4%
8 7
1.6%
7 7
1.6%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
325 
0
95 
1
 
22
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.1959459
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 325
73.2%
0 95
 
21.4%
1 22
 
5.0%
2 1
 
0.2%
4 1
 
0.2%

Length

2024-04-30T04:53:12.602363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:12.697581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 325
73.2%
0 95
 
21.4%
1 22
 
5.0%
2 1
 
0.2%
4 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
377 
0
45 
1
 
21
4
 
1

Length

Max length4
Median length4
Mean length3.5472973
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
84.9%
0 45
 
10.1%
1 21
 
4.7%
4 1
 
0.2%

Length

2024-04-30T04:53:12.805671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:12.904282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
84.9%
0 45
 
10.1%
1 21
 
4.7%
4 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
273 
<NA>
171 

Length

Max length4
Median length1
Mean length2.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 273
61.5%
<NA> 171
38.5%

Length

2024-04-30T04:53:13.008483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:13.100788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 273
61.5%
na 171
38.5%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
273 
<NA>
171 

Length

Max length4
Median length1
Mean length2.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 273
61.5%
<NA> 171
38.5%

Length

2024-04-30T04:53:13.193850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:13.279313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 273
61.5%
na 171
38.5%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
273 
<NA>
171 

Length

Max length4
Median length1
Mean length2.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 273
61.5%
<NA> 171
38.5%

Length

2024-04-30T04:53:13.366962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:13.453011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 273
61.5%
na 171
38.5%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing83
Missing (%)18.7%
Memory size1020.0 B
False
361 
(Missing)
83 
ValueCountFrequency (%)
False 361
81.3%
(Missing) 83
 
18.7%
2024-04-30T04:53:13.529471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
273 
<NA>
171 

Length

Max length4
Median length1
Mean length2.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 273
61.5%
<NA> 171
38.5%

Length

2024-04-30T04:53:13.613003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:13.694731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 273
61.5%
na 171
38.5%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing443
Missing (%)99.8%
Memory size3.6 KiB
2024-04-30T04:53:13.825041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters43
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물만 청소
ValueCountFrequency (%)
공중위생관리법시행령 1
12.5%
제3조제1호의 1
12.5%
규정에 1
12.5%
의한 1
12.5%
건축물규모 1
12.5%
이하의 1
12.5%
건축물만 1
12.5%
청소 1
12.5%
2024-04-30T04:53:14.065598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
16.3%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
1
 
2.3%
1
 
2.3%
Other values (20) 20
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34
79.1%
Space Separator 7
 
16.3%
Decimal Number 2
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17) 17
50.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34
79.1%
Common 9
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17) 17
50.0%
Common
ValueCountFrequency (%)
7
77.8%
1 1
 
11.1%
3 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34
79.1%
ASCII 9
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
77.8%
1 1
 
11.1%
3 1
 
11.1%
Hangul
ValueCountFrequency (%)
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17) 17
50.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
443 
20060410
 
1

Length

Max length8
Median length4
Mean length4.009009
Min length4

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> 443
99.8%
20060410 1
 
0.2%

Length

2024-04-30T04:53:14.186208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:14.283642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 443
99.8%
20060410 1
 
0.2%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
443 
20360410
 
1

Length

Max length8
Median length4
Mean length4.009009
Min length4

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> 443
99.8%
20360410 1
 
0.2%

Length

2024-04-30T04:53:14.382789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:14.472169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 443
99.8%
20360410 1
 
0.2%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
315 
임대
120 
자가
 
9

Length

Max length4
Median length4
Mean length3.4189189
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> 315
70.9%
임대 120
 
27.0%
자가 9
 
2.0%

Length

2024-04-30T04:53:14.787405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:14.888292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
70.9%
임대 120
 
27.0%
자가 9
 
2.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
226 
<NA>
218 

Length

Max length4
Median length1
Mean length2.472973
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 (%)
0 226
50.9%
<NA> 218
49.1%

Length

2024-04-30T04:53:14.978201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:15.060334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 226
50.9%
na 218
49.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
341 
0
98 
1
 
3
8
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.3040541
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 341
76.8%
0 98
 
22.1%
1 3
 
0.7%
8 1
 
0.2%
3 1
 
0.2%

Length

2024-04-30T04:53:15.166337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:15.266354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 341
76.8%
0 98
 
22.1%
1 3
 
0.7%
8 1
 
0.2%
3 1
 
0.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)6.7%
Missing340
Missing (%)76.6%
Infinite0
Infinite (%)0.0%
Mean0.31730769
Minimum0
Maximum12
Zeros96
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-30T04:53:15.344564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5217799
Coefficient of variation (CV)4.7959124
Kurtosis40.382348
Mean0.31730769
Median Absolute Deviation (MAD)0
Skewness6.1027201
Sum33
Variance2.315814
MonotonicityNot monotonic
2024-04-30T04:53:15.430722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 96
 
21.6%
1 3
 
0.7%
5 1
 
0.2%
3 1
 
0.2%
8 1
 
0.2%
12 1
 
0.2%
2 1
 
0.2%
(Missing) 340
76.6%
ValueCountFrequency (%)
0 96
21.6%
1 3
 
0.7%
2 1
 
0.2%
3 1
 
0.2%
5 1
 
0.2%
8 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
8 1
 
0.2%
5 1
 
0.2%
3 1
 
0.2%
2 1
 
0.2%
1 3
 
0.7%
0 96
21.6%

회수건조수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
242 
0
202 

Length

Max length4
Median length4
Mean length2.6351351
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> 242
54.5%
0 202
45.5%

Length

2024-04-30T04:53:15.532723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:15.618313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 242
54.5%
0 202
45.5%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
254 
0
190 

Length

Max length4
Median length4
Mean length2.7162162
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> 254
57.2%
0 190
42.8%

Length

2024-04-30T04:53:15.713682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:15.809889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 254
57.2%
0 190
42.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing74
Missing (%)16.7%
Memory size1020.0 B
False
370 
(Missing)
74 
ValueCountFrequency (%)
False 370
83.3%
(Missing) 74
 
16.7%
2024-04-30T04:53:15.897647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031600003160000-206-1991-0210219910430<NA>3폐업2폐업19951201<NA><NA><NA>02 000000.0152816서울특별시 구로구 개봉동 403-117<NA><NA>휘창기업2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업187186.449789443082.115598건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131600003160000-206-1993-0210319930210<NA>3폐업2폐업19960213<NA><NA><NA>02 63178220.0152080서울특별시 구로구 고척동 612-7 1 7호<NA><NA>한신공무2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231600003160000-206-1993-0210419930224<NA>3폐업2폐업20060411<NA><NA><NA>02 61650080.0152804서울특별시 구로구 개봉동 113-14<NA><NA>용운실업1999-03-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업186337.572178444757.860312건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331600003160000-206-1993-0210519930614<NA>3폐업2폐업19951212<NA><NA><NA>02 61481120.0152823서울특별시 구로구 고척동 50-48<NA><NA>태일케미칼2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업187798.869265444629.704822건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431600003160000-206-1993-0210619930806<NA>3폐업2폐업20040604<NA><NA><NA>02083900690.0152858서울특별시 구로구 구로동 496-11<NA><NA>유니나환경관리1999-03-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업189519.377782444011.786584건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531600003160000-206-1993-0210719930814<NA>3폐업2폐업20050110<NA><NA><NA>02038988410.0152855서울특별시 구로구 구로동 420-4<NA><NA>중광실업1999-03-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업189579.358513443636.776029건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631600003160000-206-1993-0210819930907<NA>1영업/정상1영업<NA><NA><NA><NA>020857904037.5152846서울특별시 구로구 구로동 142-43서울특별시 구로구 구로중앙로3길 14 (구로동)8312(주)동일실업2013-10-17 16:03:03I2018-08-31 23:59:59.0건물위생관리업190378.81895443138.776548건물위생관리업4<NA><NA>3<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731600003160000-206-1993-0210919931222<NA>3폐업2폐업19951127<NA><NA><NA>02 61970600.0152810서울특별시 구로구 개봉동 262-5<NA><NA>한강정수실업2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업187333.676062443142.090003건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831600003160000-206-1994-0211019940201<NA>3폐업2폐업20050110<NA><NA><NA>02 89669640.0152880서울특별시 구로구 구로동 1127-33<NA><NA>주영환경개발1999-03-03 00:00:00I2018-08-31 23:59:59.0건물위생관리업191029.307109442318.446583건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931600003160000-206-1994-0211219940321<NA>3폐업2폐업19950113<NA><NA><NA>02 85354330.0152705서울특별시 구로구 구로동 437-0 동남 4 9호<NA><NA>한성기업2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업189851.590964443550.958203건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
43431600003160000-206-2023-000082023-11-08<NA>1영업/정상1영업<NA><NA><NA><NA>070883060833.0152-848서울특별시 구로구 구로동 197-10 이앤씨벤처드림타워2차서울특별시 구로구 디지털로33길 55, 이앤씨벤처드림타워2차 702호 일부호 (구로동)8376주식회사 미소환경2024-01-09 14:11:54U2023-11-30 23:01:00.0건물위생관리업190479.902194442751.41954<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43531600003160000-206-2023-000092023-11-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4364.73152-887서울특별시 구로구 신도림동 337 신도림1차푸르지오서울특별시 구로구 경인로 661, 신도림1차푸르지오 101동 2301호~2314호,24층~26층 전체호 (신도림동)8208엘비유세스 주식회사2023-11-14 13:28:36I2022-10-31 23:06:00.0건물위생관리업190005.1325445250.538869<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43631600003160000-206-2023-000102023-11-15<NA>1영업/정상1영업<NA><NA><NA><NA>026953990735.0152-841서울특별시 구로구 구로동 92 하나세인스톤Ⅴ서울특별시 구로구 도림천로 336-1, 1층 102호 일부(좌측)호 (구로동, 하나세인스톤Ⅴ)8303코리아청소협동조합2023-12-01 13:17:33U2022-11-02 00:03:00.0건물위생관리업190508.096163443644.889397<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43731600003160000-206-2023-000112023-11-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.35152-760서울특별시 구로구 고척동 141-1 서울가든아파트서울특별시 구로구 중앙로5길 62, 상가동 4층 404호 (고척동, 서울가든아파트)8224주식회사 해길2023-11-17 15:59:29I2022-10-31 23:09:00.0건물위생관리업187601.409308444490.834046<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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