Overview

Dataset statistics

Number of variables47
Number of observations315
Missing cells3642
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory124.4 KiB
Average record size in memory404.4 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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-19277/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (90.2%)Imbalance
위생업태명 is highly imbalanced (62.9%)Imbalance
사용시작지하층 is highly imbalanced (52.7%)Imbalance
사용끝지하층 is highly imbalanced (66.8%)Imbalance
발한실여부 is highly imbalanced (93.7%)Imbalance
여성종사자수 is highly imbalanced (73.6%)Imbalance
인허가취소일자 has 315 (100.0%) missing valuesMissing
폐업일자 has 60 (19.0%) missing valuesMissing
휴업시작일자 has 315 (100.0%) missing valuesMissing
휴업종료일자 has 315 (100.0%) missing valuesMissing
재개업일자 has 315 (100.0%) missing valuesMissing
전화번호 has 50 (15.9%) missing valuesMissing
소재지우편번호 has 8 (2.5%) missing valuesMissing
지번주소 has 8 (2.5%) missing valuesMissing
도로명주소 has 163 (51.7%) missing valuesMissing
도로명우편번호 has 164 (52.1%) missing valuesMissing
좌표정보(X) has 14 (4.4%) missing valuesMissing
좌표정보(Y) has 14 (4.4%) missing valuesMissing
건물지상층수 has 134 (42.5%) missing valuesMissing
건물지하층수 has 155 (49.2%) missing valuesMissing
사용시작지상층 has 158 (50.2%) missing valuesMissing
사용끝지상층 has 156 (49.5%) missing valuesMissing
발한실여부 has 43 (13.7%) missing valuesMissing
조건부허가신고사유 has 315 (100.0%) missing valuesMissing
조건부허가시작일자 has 315 (100.0%) missing valuesMissing
조건부허가종료일자 has 315 (100.0%) missing valuesMissing
남성종사자수 has 274 (87.0%) missing valuesMissing
다중이용업소여부 has 36 (11.4%) 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 99 (31.4%) zerosZeros
건물지하층수 has 115 (36.5%) zerosZeros
사용시작지상층 has 45 (14.3%) zerosZeros
사용끝지상층 has 12 (3.8%) zerosZeros
남성종사자수 has 33 (10.5%) zerosZeros

Reproduction

Analysis started2024-05-11 08:52:58.561394
Analysis finished2024-05-11 08:53:00.779230
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3000000
315 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 315
100.0%

Length

2024-05-11T08:53:00.965394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:01.264231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 315
100.0%

관리번호
Text

UNIQUE 

Distinct315
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T08:53:01.637634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6930
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

Unique315 ?
Unique (%)100.0%

Sample

1st row3000000-206-1987-01670
2nd row3000000-206-1987-01671
3rd row3000000-206-1987-01672
4th row3000000-206-1987-01673
5th row3000000-206-1987-01674
ValueCountFrequency (%)
3000000-206-1987-01670 1
 
0.3%
3000000-206-2010-00004 1
 
0.3%
3000000-206-2010-00011 1
 
0.3%
3000000-206-2010-00010 1
 
0.3%
3000000-206-2010-00009 1
 
0.3%
3000000-206-2010-00008 1
 
0.3%
3000000-206-2010-00007 1
 
0.3%
3000000-206-2010-00006 1
 
0.3%
3000000-206-2010-00017 1
 
0.3%
3000000-206-2010-00003 1
 
0.3%
Other values (305) 305
96.8%
2024-05-11T08:53:02.525020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3552
51.3%
- 945
 
13.6%
2 651
 
9.4%
6 408
 
5.9%
1 406
 
5.9%
3 401
 
5.8%
9 213
 
3.1%
7 125
 
1.8%
8 85
 
1.2%
4 78
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5985
86.4%
Dash Punctuation 945
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3552
59.3%
2 651
 
10.9%
6 408
 
6.8%
1 406
 
6.8%
3 401
 
6.7%
9 213
 
3.6%
7 125
 
2.1%
8 85
 
1.4%
4 78
 
1.3%
5 66
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3552
51.3%
- 945
 
13.6%
2 651
 
9.4%
6 408
 
5.9%
1 406
 
5.9%
3 401
 
5.8%
9 213
 
3.1%
7 125
 
1.8%
8 85
 
1.2%
4 78
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3552
51.3%
- 945
 
13.6%
2 651
 
9.4%
6 408
 
5.9%
1 406
 
5.9%
3 401
 
5.8%
9 213
 
3.1%
7 125
 
1.8%
8 85
 
1.2%
4 78
 
1.1%
Distinct300
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1987-05-09 00:00:00
Maximum2024-03-14 00:00:00
2024-05-11T08:53:02.930883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:03.607363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3
255 
1
60 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 255
81.0%
1 60
 
19.0%

Length

2024-05-11T08:53:04.039880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:04.334117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 255
81.0%
1 60
 
19.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
255 
영업/정상
60 

Length

Max length5
Median length2
Mean length2.5714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 255
81.0%
영업/정상 60
 
19.0%

Length

2024-05-11T08:53:04.624981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:04.991796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 255
81.0%
영업/정상 60
 
19.0%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2
255 
1
60 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 255
81.0%
1 60
 
19.0%

Length

2024-05-11T08:53:05.362445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:05.792327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 255
81.0%
1 60
 
19.0%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
255 
영업
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 255
81.0%
영업 60
 
19.0%

Length

2024-05-11T08:53:06.215311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:06.514638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 255
81.0%
영업 60
 
19.0%

폐업일자
Date

MISSING 

Distinct206
Distinct (%)80.8%
Missing60
Missing (%)19.0%
Memory size2.6 KiB
Minimum1992-06-02 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T08:53:06.912450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:07.346000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct245
Distinct (%)92.5%
Missing50
Missing (%)15.9%
Memory size2.6 KiB
2024-05-11T08:53:08.145270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.539623
Min length2

Characters and Unicode

Total characters2793
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

Unique232 ?
Unique (%)87.5%

Sample

1st row02 7329676
2nd row0202738544
3rd row02 7378822
4th row02 7222323
5th row02 7647276
ValueCountFrequency (%)
02 195
37.5%
0200000000 7
 
1.3%
730 5
 
1.0%
723 5
 
1.0%
733 4
 
0.8%
031 4
 
0.8%
00000 4
 
0.8%
577 3
 
0.6%
739 3
 
0.6%
070 3
 
0.6%
Other values (274) 287
55.2%
2024-05-11T08:53:09.520161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 523
18.7%
2 502
18.0%
350
12.5%
7 299
10.7%
3 250
9.0%
5 173
 
6.2%
1 148
 
5.3%
6 144
 
5.2%
4 142
 
5.1%
8 141
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2443
87.5%
Space Separator 350
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 523
21.4%
2 502
20.5%
7 299
12.2%
3 250
10.2%
5 173
 
7.1%
1 148
 
6.1%
6 144
 
5.9%
4 142
 
5.8%
8 141
 
5.8%
9 121
 
5.0%
Space Separator
ValueCountFrequency (%)
350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 523
18.7%
2 502
18.0%
350
12.5%
7 299
10.7%
3 250
9.0%
5 173
 
6.2%
1 148
 
5.3%
6 144
 
5.2%
4 142
 
5.1%
8 141
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 523
18.7%
2 502
18.0%
350
12.5%
7 299
10.7%
3 250
9.0%
5 173
 
6.2%
1 148
 
5.3%
6 144
 
5.2%
4 142
 
5.1%
8 141
 
5.0%
Distinct227
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T08:53:10.372663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.984127
Min length3

Characters and Unicode

Total characters1570
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

Unique199 ?
Unique (%)63.2%

Sample

1st row485.00
2nd row.00
3rd row313.00
4th row61.82
5th row.00
ValueCountFrequency (%)
00 49
 
15.6%
15.00 7
 
2.2%
33.00 6
 
1.9%
32.00 3
 
1.0%
36.00 3
 
1.0%
92.00 3
 
1.0%
19.80 3
 
1.0%
52.50 2
 
0.6%
49.50 2
 
0.6%
10.00 2
 
0.6%
Other values (217) 235
74.6%
2024-05-11T08:53:11.728828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 384
24.5%
. 315
20.1%
1 134
 
8.5%
2 114
 
7.3%
3 110
 
7.0%
5 104
 
6.6%
6 97
 
6.2%
4 84
 
5.4%
8 79
 
5.0%
7 69
 
4.4%
Other values (2) 80
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1243
79.2%
Other Punctuation 327
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 384
30.9%
1 134
 
10.8%
2 114
 
9.2%
3 110
 
8.8%
5 104
 
8.4%
6 97
 
7.8%
4 84
 
6.8%
8 79
 
6.4%
7 69
 
5.6%
9 68
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 315
96.3%
, 12
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 384
24.5%
. 315
20.1%
1 134
 
8.5%
2 114
 
7.3%
3 110
 
7.0%
5 104
 
6.6%
6 97
 
6.2%
4 84
 
5.4%
8 79
 
5.0%
7 69
 
4.4%
Other values (2) 80
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 384
24.5%
. 315
20.1%
1 134
 
8.5%
2 114
 
7.3%
3 110
 
7.0%
5 104
 
6.6%
6 97
 
6.2%
4 84
 
5.4%
8 79
 
5.0%
7 69
 
4.4%
Other values (2) 80
 
5.1%

소재지우편번호
Text

MISSING 

Distinct123
Distinct (%)40.1%
Missing8
Missing (%)2.5%
Memory size2.6 KiB
2024-05-11T08:53:12.620711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0749186
Min length6

Characters and Unicode

Total characters1865
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

Unique62 ?
Unique (%)20.2%

Sample

1st row110756
2nd row110430
3rd row110053
4th row110121
5th row110450
ValueCountFrequency (%)
110111 11
 
3.6%
110061 10
 
3.3%
110320 9
 
2.9%
110826 9
 
2.9%
110410 8
 
2.6%
110825 8
 
2.6%
110420 8
 
2.6%
110121 8
 
2.6%
110828 8
 
2.6%
110071 7
 
2.3%
Other values (113) 221
72.0%
2024-05-11T08:53:13.675780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 759
40.7%
0 496
26.6%
2 118
 
6.3%
8 113
 
6.1%
4 77
 
4.1%
5 68
 
3.6%
7 64
 
3.4%
3 57
 
3.1%
6 53
 
2.8%
9 37
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1842
98.8%
Dash Punctuation 23
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 759
41.2%
0 496
26.9%
2 118
 
6.4%
8 113
 
6.1%
4 77
 
4.2%
5 68
 
3.7%
7 64
 
3.5%
3 57
 
3.1%
6 53
 
2.9%
9 37
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1865
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 759
40.7%
0 496
26.6%
2 118
 
6.3%
8 113
 
6.1%
4 77
 
4.1%
5 68
 
3.6%
7 64
 
3.4%
3 57
 
3.1%
6 53
 
2.8%
9 37
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 759
40.7%
0 496
26.6%
2 118
 
6.3%
8 113
 
6.1%
4 77
 
4.1%
5 68
 
3.6%
7 64
 
3.4%
3 57
 
3.1%
6 53
 
2.8%
9 37
 
2.0%

지번주소
Text

MISSING 

Distinct290
Distinct (%)94.5%
Missing8
Missing (%)2.5%
Memory size2.6 KiB
2024-05-11T08:53:14.395413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length25.247557
Min length16

Characters and Unicode

Total characters7751
Distinct characters228
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

Unique275 ?
Unique (%)89.6%

Sample

1st row서울특별시 종로구 적선동 80 적선현대빌딩 907호
2nd row서울특별시 종로구 장사동 8 2층
3rd row서울특별시 종로구 내자동 167-2
4th row서울특별시 종로구 종로1가 136-0
5th row서울특별시 종로구 원남동 194 창곡빌딩307호
ValueCountFrequency (%)
서울특별시 307
 
19.6%
종로구 307
 
19.6%
숭인동 40
 
2.6%
신문로1가 17
 
1.1%
창신동 12
 
0.8%
2층 12
 
0.8%
적선동 12
 
0.8%
관철동 11
 
0.7%
수송동 11
 
0.7%
인의동 11
 
0.7%
Other values (500) 825
52.7%
2024-05-11T08:53:15.696680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1485
19.2%
1 391
 
5.0%
371
 
4.8%
341
 
4.4%
321
 
4.1%
313
 
4.0%
312
 
4.0%
308
 
4.0%
307
 
4.0%
307
 
4.0%
Other values (218) 3295
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4522
58.3%
Decimal Number 1508
 
19.5%
Space Separator 1485
 
19.2%
Dash Punctuation 183
 
2.4%
Uppercase Letter 18
 
0.2%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Other Punctuation 9
 
0.1%
Lowercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
371
 
8.2%
341
 
7.5%
321
 
7.1%
313
 
6.9%
312
 
6.9%
308
 
6.8%
307
 
6.8%
307
 
6.8%
280
 
6.2%
116
 
2.6%
Other values (188) 1546
34.2%
Decimal Number
ValueCountFrequency (%)
1 391
25.9%
2 233
15.5%
0 185
12.3%
3 150
 
9.9%
6 106
 
7.0%
4 105
 
7.0%
5 99
 
6.6%
8 93
 
6.2%
7 76
 
5.0%
9 70
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
16.7%
G 3
16.7%
L 3
16.7%
K 2
11.1%
A 2
11.1%
T 1
 
5.6%
W 1
 
5.6%
Q 1
 
5.6%
H 1
 
5.6%
S 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
s 3
37.5%
t 2
25.0%
c 2
25.0%
e 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
. 2
 
22.2%
Space Separator
ValueCountFrequency (%)
1485
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4522
58.3%
Common 3203
41.3%
Latin 26
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
371
 
8.2%
341
 
7.5%
321
 
7.1%
313
 
6.9%
312
 
6.9%
308
 
6.8%
307
 
6.8%
307
 
6.8%
280
 
6.2%
116
 
2.6%
Other values (188) 1546
34.2%
Common
ValueCountFrequency (%)
1485
46.4%
1 391
 
12.2%
2 233
 
7.3%
0 185
 
5.8%
- 183
 
5.7%
3 150
 
4.7%
6 106
 
3.3%
4 105
 
3.3%
5 99
 
3.1%
8 93
 
2.9%
Other values (6) 173
 
5.4%
Latin
ValueCountFrequency (%)
B 3
11.5%
s 3
11.5%
G 3
11.5%
L 3
11.5%
K 2
7.7%
A 2
7.7%
t 2
7.7%
c 2
7.7%
T 1
 
3.8%
W 1
 
3.8%
Other values (4) 4
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4522
58.3%
ASCII 3229
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1485
46.0%
1 391
 
12.1%
2 233
 
7.2%
0 185
 
5.7%
- 183
 
5.7%
3 150
 
4.6%
6 106
 
3.3%
4 105
 
3.3%
5 99
 
3.1%
8 93
 
2.9%
Other values (20) 199
 
6.2%
Hangul
ValueCountFrequency (%)
371
 
8.2%
341
 
7.5%
321
 
7.1%
313
 
6.9%
312
 
6.9%
308
 
6.8%
307
 
6.8%
307
 
6.8%
280
 
6.2%
116
 
2.6%
Other values (188) 1546
34.2%

도로명주소
Text

MISSING 

Distinct149
Distinct (%)98.0%
Missing163
Missing (%)51.7%
Memory size2.6 KiB
2024-05-11T08:53:16.569071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40.5
Mean length34.078947
Min length21

Characters and Unicode

Total characters5180
Distinct characters224
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)96.1%

Sample

1st row서울특별시 종로구 사직로 130, 907호 (적선동)
2nd row서울특별시 종로구 사직로10길 17 (내자동)
3rd row서울특별시 종로구 돈화문로11길 29, 701호 (돈의동, 낙원오피스텔)
4th row서울특별시 종로구 종로5길 58 (수송동,석탄회관 3층)
5th row서울특별시 종로구 난계로 247 (숭인동,서진빌딩309호)
ValueCountFrequency (%)
서울특별시 152
 
15.0%
종로구 152
 
15.0%
숭인동 20
 
2.0%
종로 13
 
1.3%
2층 12
 
1.2%
새문안로 12
 
1.2%
청계천로 9
 
0.9%
5층 9
 
0.9%
신문로1가 9
 
0.9%
4층 9
 
0.9%
Other values (380) 617
60.8%
2024-05-11T08:53:17.733838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
862
 
16.6%
326
 
6.3%
196
 
3.8%
1 188
 
3.6%
, 169
 
3.3%
162
 
3.1%
) 156
 
3.0%
156
 
3.0%
( 155
 
3.0%
155
 
3.0%
Other values (214) 2655
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2965
57.2%
Space Separator 862
 
16.6%
Decimal Number 829
 
16.0%
Other Punctuation 169
 
3.3%
Close Punctuation 156
 
3.0%
Open Punctuation 155
 
3.0%
Uppercase Letter 20
 
0.4%
Dash Punctuation 15
 
0.3%
Lowercase Letter 8
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
326
 
11.0%
196
 
6.6%
162
 
5.5%
156
 
5.3%
155
 
5.2%
153
 
5.2%
152
 
5.1%
152
 
5.1%
152
 
5.1%
87
 
2.9%
Other values (182) 1274
43.0%
Uppercase Letter
ValueCountFrequency (%)
L 3
15.0%
G 3
15.0%
K 3
15.0%
B 3
15.0%
H 1
 
5.0%
T 1
 
5.0%
W 1
 
5.0%
Q 1
 
5.0%
O 1
 
5.0%
N 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
1 188
22.7%
2 132
15.9%
0 95
11.5%
3 82
9.9%
5 76
9.2%
6 58
 
7.0%
9 55
 
6.6%
4 55
 
6.6%
7 50
 
6.0%
8 38
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
s 3
37.5%
c 2
25.0%
t 2
25.0%
e 1
 
12.5%
Space Separator
ValueCountFrequency (%)
862
100.0%
Other Punctuation
ValueCountFrequency (%)
, 169
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2965
57.2%
Common 2187
42.2%
Latin 28
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
326
 
11.0%
196
 
6.6%
162
 
5.5%
156
 
5.3%
155
 
5.2%
153
 
5.2%
152
 
5.1%
152
 
5.1%
152
 
5.1%
87
 
2.9%
Other values (182) 1274
43.0%
Common
ValueCountFrequency (%)
862
39.4%
1 188
 
8.6%
, 169
 
7.7%
) 156
 
7.1%
( 155
 
7.1%
2 132
 
6.0%
0 95
 
4.3%
3 82
 
3.7%
5 76
 
3.5%
6 58
 
2.7%
Other values (6) 214
 
9.8%
Latin
ValueCountFrequency (%)
L 3
10.7%
G 3
10.7%
s 3
10.7%
K 3
10.7%
B 3
10.7%
c 2
 
7.1%
t 2
 
7.1%
H 1
 
3.6%
T 1
 
3.6%
W 1
 
3.6%
Other values (6) 6
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2965
57.2%
ASCII 2215
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
862
38.9%
1 188
 
8.5%
, 169
 
7.6%
) 156
 
7.0%
( 155
 
7.0%
2 132
 
6.0%
0 95
 
4.3%
3 82
 
3.7%
5 76
 
3.4%
6 58
 
2.6%
Other values (22) 242
 
10.9%
Hangul
ValueCountFrequency (%)
326
 
11.0%
196
 
6.6%
162
 
5.5%
156
 
5.3%
155
 
5.2%
153
 
5.2%
152
 
5.1%
152
 
5.1%
152
 
5.1%
87
 
2.9%
Other values (182) 1274
43.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)48.3%
Missing164
Missing (%)52.1%
Infinite0
Infinite (%)0.0%
Mean3139.5762
Minimum3011
Maximum3197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:18.161533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3011
5-th percentile3057.5
Q13116
median3139
Q33174.5
95-th percentile3191
Maximum3197
Range186
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation42.401484
Coefficient of variation (CV)0.01350548
Kurtosis0.6373801
Mean3139.5762
Median Absolute Deviation (MAD)29
Skewness-0.88696455
Sum474076
Variance1797.8858
MonotonicityNot monotonic
2024-05-11T08:53:18.762919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3116 10
 
3.2%
3115 7
 
2.2%
3182 6
 
1.9%
3191 6
 
1.9%
3127 6
 
1.9%
3170 5
 
1.6%
3157 4
 
1.3%
3130 4
 
1.3%
3173 4
 
1.3%
3192 4
 
1.3%
Other values (63) 95
30.2%
(Missing) 164
52.1%
ValueCountFrequency (%)
3011 1
0.3%
3012 1
0.3%
3021 1
0.3%
3025 1
0.3%
3029 1
0.3%
3040 1
0.3%
3044 1
0.3%
3057 1
0.3%
3058 1
0.3%
3059 1
0.3%
ValueCountFrequency (%)
3197 1
 
0.3%
3195 1
 
0.3%
3193 1
 
0.3%
3192 4
1.3%
3191 6
1.9%
3190 2
 
0.6%
3189 1
 
0.3%
3188 2
 
0.6%
3187 1
 
0.3%
3186 3
1.0%
Distinct309
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T08:53:19.307852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length18
Mean length8.0793651
Min length3

Characters and Unicode

Total characters2545
Distinct characters322
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

Unique303 ?
Unique (%)96.2%

Sample

1st row주식회사 씨앤에스 자산관리
2nd row거산다역
3rd row우지기업(주)
4th row(주)동양상사
5th row삼진성흥(주)
ValueCountFrequency (%)
주식회사 29
 
7.9%
3
 
0.8%
주)대신관리 2
 
0.5%
유한회사 2
 
0.5%
삼진성흥(주 2
 
0.5%
주)삼화사 2
 
0.5%
주)한정씨앤지 2
 
0.5%
주)늘푸른도시 2
 
0.5%
대왕실업 2
 
0.5%
씨앤에스 1
 
0.3%
Other values (321) 321
87.2%
2024-05-11T08:53:20.244936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
 
9.5%
) 196
 
7.7%
( 194
 
7.6%
80
 
3.1%
70
 
2.8%
61
 
2.4%
56
 
2.2%
55
 
2.2%
53
 
2.1%
49
 
1.9%
Other values (312) 1489
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2054
80.7%
Close Punctuation 196
 
7.7%
Open Punctuation 194
 
7.6%
Space Separator 55
 
2.2%
Uppercase Letter 25
 
1.0%
Decimal Number 10
 
0.4%
Other Punctuation 5
 
0.2%
Lowercase Letter 4
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
242
 
11.8%
80
 
3.9%
70
 
3.4%
61
 
3.0%
56
 
2.7%
53
 
2.6%
49
 
2.4%
47
 
2.3%
45
 
2.2%
31
 
1.5%
Other values (284) 1320
64.3%
Uppercase Letter
ValueCountFrequency (%)
F 4
16.0%
N 2
 
8.0%
G 2
 
8.0%
U 2
 
8.0%
A 2
 
8.0%
Y 2
 
8.0%
M 2
 
8.0%
E 1
 
4.0%
O 1
 
4.0%
S 1
 
4.0%
Other values (6) 6
24.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
x 1
25.0%
i 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
4 3
30.0%
9 3
30.0%
Close Punctuation
ValueCountFrequency (%)
) 196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2054
80.7%
Common 462
 
18.2%
Latin 29
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
242
 
11.8%
80
 
3.9%
70
 
3.4%
61
 
3.0%
56
 
2.7%
53
 
2.6%
49
 
2.4%
47
 
2.3%
45
 
2.2%
31
 
1.5%
Other values (284) 1320
64.3%
Latin
ValueCountFrequency (%)
F 4
 
13.8%
N 2
 
6.9%
G 2
 
6.9%
U 2
 
6.9%
A 2
 
6.9%
Y 2
 
6.9%
M 2
 
6.9%
E 1
 
3.4%
O 1
 
3.4%
r 1
 
3.4%
Other values (10) 10
34.5%
Common
ValueCountFrequency (%)
) 196
42.4%
( 194
42.0%
55
 
11.9%
. 5
 
1.1%
1 4
 
0.9%
4 3
 
0.6%
9 3
 
0.6%
- 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2054
80.7%
ASCII 491
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
242
 
11.8%
80
 
3.9%
70
 
3.4%
61
 
3.0%
56
 
2.7%
53
 
2.6%
49
 
2.4%
47
 
2.3%
45
 
2.2%
31
 
1.5%
Other values (284) 1320
64.3%
ASCII
ValueCountFrequency (%)
) 196
39.9%
( 194
39.5%
55
 
11.2%
. 5
 
1.0%
F 4
 
0.8%
1 4
 
0.8%
4 3
 
0.6%
9 3
 
0.6%
N 2
 
0.4%
G 2
 
0.4%
Other values (18) 23
 
4.7%
Distinct258
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1999-04-09 00:00:00
Maximum2024-04-25 16:17:47
2024-05-11T08:53:20.664667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:21.207718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
240 
U
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 240
76.2%
U 75
 
23.8%

Length

2024-05-11T08:53:21.754665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:22.119785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 240
76.2%
u 75
 
23.8%
Distinct87
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-05-11T08:53:22.677602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:23.159727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
건물위생관리업
311 
건물위생관리업 기타
 
4

Length

Max length10
Median length7
Mean length7.0380952
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 311
98.7%
건물위생관리업 기타 4
 
1.3%

Length

2024-05-11T08:53:23.675497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:24.079871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 315
98.7%
기타 4
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)67.1%
Missing14
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean198956.01
Minimum196079.54
Maximum202026.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:24.737109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196079.54
5-th percentile196772.58
Q1197595.16
median198697.71
Q3199976.77
95-th percentile201875.67
Maximum202026.36
Range5946.8171
Interquartile range (IQR)2381.6042

Descriptive statistics

Standard deviation1577.3196
Coefficient of variation (CV)0.0079279817
Kurtosis-0.75398406
Mean198956.01
Median Absolute Deviation (MAD)1129.7687
Skewness0.46850355
Sum59885760
Variance2487937.2
MonotonicityNot monotonic
2024-05-11T08:53:25.390277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197541.418168655 6
 
1.9%
197567.849954354 6
 
1.9%
197595.161312175 5
 
1.6%
198643.543485167 5
 
1.6%
197076.316936233 5
 
1.6%
198970.736456772 5
 
1.6%
199605.49511328 4
 
1.3%
199045.043602772 4
 
1.3%
198150.300374121 4
 
1.3%
197673.919714838 4
 
1.3%
Other values (192) 253
80.3%
(Missing) 14
 
4.4%
ValueCountFrequency (%)
196079.544115659 1
0.3%
196092.743907822 2
0.6%
196349.709808129 1
0.3%
196382.344952237 1
0.3%
196384.538014661 1
0.3%
196470.449471829 1
0.3%
196481.380928093 1
0.3%
196484.581910994 1
0.3%
196518.949797615 1
0.3%
196523.091380111 1
0.3%
ValueCountFrequency (%)
202026.361176 1
 
0.3%
201966.262330671 3
1.0%
201962.62904341 3
1.0%
201960.951300031 2
0.6%
201949.270716491 1
 
0.3%
201946.86632604 1
 
0.3%
201911.136750205 1
 
0.3%
201910.647689061 1
 
0.3%
201907.246775887 1
 
0.3%
201905.282909761 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)67.1%
Missing14
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean452398.07
Minimum451580.2
Maximum456896.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:26.016645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451580.2
5-th percentile451816.04
Q1452091.98
median452291.86
Q3452516.95
95-th percentile453141.02
Maximum456896.76
Range5316.5612
Interquartile range (IQR)424.96958

Descriptive statistics

Standard deviation674.54534
Coefficient of variation (CV)0.0014910438
Kurtosis20.271292
Mean452398.07
Median Absolute Deviation (MAD)220.94839
Skewness4.0288078
Sum1.3617182 × 108
Variance455011.42
MonotonicityNot monotonic
2024-05-11T08:53:26.766641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452115.300046799 6
 
1.9%
452567.159554494 6
 
1.9%
452460.054621887 5
 
1.6%
452199.798612424 5
 
1.6%
451690.586861352 5
 
1.6%
452534.45478172 5
 
1.6%
452588.063130721 4
 
1.3%
451939.677286976 4
 
1.3%
452019.212642931 4
 
1.3%
452123.434528869 4
 
1.3%
Other values (192) 253
80.3%
(Missing) 14
 
4.4%
ValueCountFrequency (%)
451580.195594285 1
 
0.3%
451596.900364676 1
 
0.3%
451663.113055146 2
 
0.6%
451690.586861352 5
1.6%
451787.140320003 1
 
0.3%
451796.743700691 1
 
0.3%
451798.274459999 3
1.0%
451816.038182067 2
 
0.6%
451849.916935436 1
 
0.3%
451851.930284896 1
 
0.3%
ValueCountFrequency (%)
456896.756785212 1
0.3%
456198.595931715 2
0.6%
456030.708285329 1
0.3%
456004.476561751 1
0.3%
455970.888515918 1
0.3%
455192.896141084 1
0.3%
454013.33417032 1
0.3%
453645.757969136 1
0.3%
453577.361028716 1
0.3%
453487.534406085 1
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
건물위생관리업
276 
<NA>
36 
건물위생관리업 기타
 
3

Length

Max length10
Median length7
Mean length6.6857143
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 276
87.6%
<NA> 36
 
11.4%
건물위생관리업 기타 3
 
1.0%

Length

2024-05-11T08:53:27.413376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:27.955049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 279
87.7%
na 36
 
11.3%
기타 3
 
0.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)12.2%
Missing134
Missing (%)42.5%
Infinite0
Infinite (%)0.0%
Mean3.4475138
Minimum0
Maximum24
Zeros99
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:28.449083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile15
Maximum24
Range24
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.399975
Coefficient of variation (CV)1.5663389
Kurtosis3.4605142
Mean3.4475138
Median Absolute Deviation (MAD)0
Skewness1.9315099
Sum624
Variance29.15973
MonotonicityNot monotonic
2024-05-11T08:53:29.174107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 99
31.4%
4 17
 
5.4%
5 16
 
5.1%
10 8
 
2.5%
3 7
 
2.2%
2 7
 
2.2%
12 4
 
1.3%
11 3
 
1.0%
6 2
 
0.6%
15 2
 
0.6%
Other values (12) 16
 
5.1%
(Missing) 134
42.5%
ValueCountFrequency (%)
0 99
31.4%
1 2
 
0.6%
2 7
 
2.2%
3 7
 
2.2%
4 17
 
5.4%
5 16
 
5.1%
6 2
 
0.6%
7 1
 
0.3%
8 1
 
0.3%
10 8
 
2.5%
ValueCountFrequency (%)
24 2
0.6%
23 1
0.3%
22 1
0.3%
20 1
0.3%
19 1
0.3%
17 1
0.3%
16 2
0.6%
15 2
0.6%
14 1
0.3%
13 2
0.6%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)5.0%
Missing155
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean0.6875
Minimum0
Maximum7
Zeros115
Zeros (%)36.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:29.987995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4588162
Coefficient of variation (CV)2.1219144
Kurtosis5.4405139
Mean0.6875
Median Absolute Deviation (MAD)0
Skewness2.466085
Sum110
Variance2.1281447
MonotonicityNot monotonic
2024-05-11T08:53:30.553356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 115
36.5%
1 23
 
7.3%
5 6
 
1.9%
2 5
 
1.6%
4 4
 
1.3%
3 4
 
1.3%
6 2
 
0.6%
7 1
 
0.3%
(Missing) 155
49.2%
ValueCountFrequency (%)
0 115
36.5%
1 23
 
7.3%
2 5
 
1.6%
3 4
 
1.3%
4 4
 
1.3%
5 6
 
1.9%
6 2
 
0.6%
7 1
 
0.3%
ValueCountFrequency (%)
7 1
 
0.3%
6 2
 
0.6%
5 6
 
1.9%
4 4
 
1.3%
3 4
 
1.3%
2 5
 
1.6%
1 23
 
7.3%
0 115
36.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)10.8%
Missing158
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean3.4203822
Minimum0
Maximum21
Zeros45
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:31.050265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile12
Maximum21
Range21
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0842527
Coefficient of variation (CV)1.1940925
Kurtosis3.9929332
Mean3.4203822
Median Absolute Deviation (MAD)2
Skewness1.8698892
Sum537
Variance16.68112
MonotonicityNot monotonic
2024-05-11T08:53:31.513494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 45
 
14.3%
2 27
 
8.6%
4 19
 
6.0%
3 15
 
4.8%
1 14
 
4.4%
10 8
 
2.5%
5 7
 
2.2%
9 4
 
1.3%
6 4
 
1.3%
12 3
 
1.0%
Other values (7) 11
 
3.5%
(Missing) 158
50.2%
ValueCountFrequency (%)
0 45
14.3%
1 14
 
4.4%
2 27
8.6%
3 15
 
4.8%
4 19
6.0%
5 7
 
2.2%
6 4
 
1.3%
7 3
 
1.0%
8 2
 
0.6%
9 4
 
1.3%
ValueCountFrequency (%)
21 1
 
0.3%
20 1
 
0.3%
18 1
 
0.3%
15 1
 
0.3%
13 2
 
0.6%
12 3
 
1.0%
10 8
2.5%
9 4
1.3%
8 2
 
0.6%
7 3
 
1.0%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)10.7%
Missing156
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean3.9245283
Minimum0
Maximum21
Zeros12
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:31.911212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile12
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.6222714
Coefficient of variation (CV)0.92298262
Kurtosis6.4195854
Mean3.9245283
Median Absolute Deviation (MAD)1
Skewness2.3225608
Sum624
Variance13.12085
MonotonicityNot monotonic
2024-05-11T08:53:32.308624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3 53
 
16.8%
2 33
 
10.5%
4 17
 
5.4%
0 12
 
3.8%
1 10
 
3.2%
5 8
 
2.5%
10 6
 
1.9%
9 4
 
1.3%
12 3
 
1.0%
7 3
 
1.0%
Other values (7) 10
 
3.2%
(Missing) 156
49.5%
ValueCountFrequency (%)
0 12
 
3.8%
1 10
 
3.2%
2 33
10.5%
3 53
16.8%
4 17
 
5.4%
5 8
 
2.5%
6 2
 
0.6%
7 3
 
1.0%
8 2
 
0.6%
9 4
 
1.3%
ValueCountFrequency (%)
21 1
 
0.3%
20 1
 
0.3%
18 1
 
0.3%
15 1
 
0.3%
13 2
 
0.6%
12 3
1.0%
10 6
1.9%
9 4
1.3%
8 2
 
0.6%
7 3
1.0%

사용시작지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
246 
0
53 
1
 
15
6
 
1

Length

Max length4
Median length4
Mean length3.3428571
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 246
78.1%
0 53
 
16.8%
1 15
 
4.8%
6 1
 
0.3%

Length

2024-05-11T08:53:32.826828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:33.250464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
78.1%
0 53
 
16.8%
1 15
 
4.8%
6 1
 
0.3%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
270 
1
 
23
0
 
20
6
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 270
85.7%
1 23
 
7.3%
0 20
 
6.3%
6 1
 
0.3%
2 1
 
0.3%

Length

2024-05-11T08:53:33.652849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:33.997532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 270
85.7%
1 23
 
7.3%
0 20
 
6.3%
6 1
 
0.3%
2 1
 
0.3%

한실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
178 
0
137 

Length

Max length4
Median length4
Mean length2.6952381
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 178
56.5%
0 137
43.5%

Length

2024-05-11T08:53:34.507055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:34.957746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
56.5%
0 137
43.5%

양실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
178 
0
137 

Length

Max length4
Median length4
Mean length2.6952381
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 178
56.5%
0 137
43.5%

Length

2024-05-11T08:53:35.333041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:35.699017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
56.5%
0 137
43.5%

욕실수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
178 
0
137 

Length

Max length4
Median length4
Mean length2.6952381
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 178
56.5%
0 137
43.5%

Length

2024-05-11T08:53:36.102228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:36.476186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
56.5%
0 137
43.5%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.7%
Missing43
Missing (%)13.7%
Memory size762.0 B
False
270 
True
 
2
(Missing)
43 
ValueCountFrequency (%)
False 270
85.7%
True 2
 
0.6%
(Missing) 43
 
13.7%
2024-05-11T08:53:36.768942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
177 
0
137 
3
 
1

Length

Max length4
Median length4
Mean length2.6857143
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 177
56.2%
0 137
43.5%
3 1
 
0.3%

Length

2024-05-11T08:53:37.164883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:37.630997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
56.2%
0 137
43.5%
3 1
 
0.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB
Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
239 
임대
75 
자가
 
1

Length

Max length4
Median length4
Mean length3.5174603
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 239
75.9%
임대 75
 
23.8%
자가 1
 
0.3%

Length

2024-05-11T08:53:38.113490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:38.466260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
75.9%
임대 75
 
23.8%
자가 1
 
0.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
211 
0
104 

Length

Max length4
Median length4
Mean length3.0095238
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> 211
67.0%
0 104
33.0%

Length

2024-05-11T08:53:38.844134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:39.423283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 211
67.0%
0 104
33.0%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
275 
0
37 
20
 
1
9
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.6222222
Min length1

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
87.3%
0 37
 
11.7%
20 1
 
0.3%
9 1
 
0.3%
2 1
 
0.3%

Length

2024-05-11T08:53:39.915208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:40.411775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
87.3%
0 37
 
11.7%
20 1
 
0.3%
9 1
 
0.3%
2 1
 
0.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)14.6%
Missing274
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean1.3170732
Minimum0
Maximum26
Zeros33
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T08:53:41.012582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.4913195
Coefficient of variation (CV)3.4100759
Kurtosis24.036404
Mean1.3170732
Median Absolute Deviation (MAD)0
Skewness4.6908561
Sum54
Variance20.171951
MonotonicityNot monotonic
2024-05-11T08:53:41.533776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 33
 
10.5%
2 4
 
1.3%
26 1
 
0.3%
1 1
 
0.3%
8 1
 
0.3%
11 1
 
0.3%
(Missing) 274
87.0%
ValueCountFrequency (%)
0 33
10.5%
1 1
 
0.3%
2 4
 
1.3%
8 1
 
0.3%
11 1
 
0.3%
26 1
 
0.3%
ValueCountFrequency (%)
26 1
 
0.3%
11 1
 
0.3%
8 1
 
0.3%
2 4
 
1.3%
1 1
 
0.3%
0 33
10.5%

회수건조수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
222 
0
93 

Length

Max length4
Median length4
Mean length3.1142857
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> 222
70.5%
0 93
29.5%

Length

2024-05-11T08:53:41.925204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:42.296349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
70.5%
0 93
29.5%

침대수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
229 
0
86 

Length

Max length4
Median length4
Mean length3.1809524
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> 229
72.7%
0 86
 
27.3%

Length

2024-05-11T08:53:42.616498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:43.021068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 229
72.7%
0 86
 
27.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing36
Missing (%)11.4%
Memory size762.0 B
False
279 
(Missing)
36 
ValueCountFrequency (%)
False 279
88.6%
(Missing) 36
 
11.4%
2024-05-11T08:53:43.468965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030000003000000-206-1987-0167019870512<NA>1영업/정상1영업<NA><NA><NA><NA>02 7329676485.00110756서울특별시 종로구 적선동 80 적선현대빌딩 907호서울특별시 종로구 사직로 130, 907호 (적선동)3170주식회사 씨앤에스 자산관리2020-09-11 14:06:56U2020-09-13 02:40:00.0건물위생관리업197567.849954452567.159554건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130000003000000-206-1987-0167119870512<NA>3폐업2폐업20040109<NA><NA><NA>0202738544.00110430서울특별시 종로구 장사동 8 2층<NA><NA>거산다역2003-03-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업199264.864268451927.319853건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230000003000000-206-1987-0167219870509<NA>1영업/정상1영업<NA><NA><NA><NA>02 7378822313.00110053서울특별시 종로구 내자동 167-2서울특별시 종로구 사직로10길 17 (내자동)3169우지기업(주)2018-06-04 11:18:21I2018-08-31 23:59:59.0건물위생관리업197336.583985452534.336254건물위생관리업3<NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330000003000000-206-1987-0167319870528<NA>3폐업2폐업19960418<NA><NA><NA>02 722232361.82110121서울특별시 종로구 종로1가 136-0<NA><NA>(주)동양상사2001-11-20 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
430000003000000-206-1987-0167419870619<NA>3폐업2폐업20090902<NA><NA><NA>02 7647276.00110450서울특별시 종로구 원남동 194 창곡빌딩307호<NA><NA>삼진성흥(주)2003-03-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업199605.495113452588.063131건물위생관리업<NA><NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530000003000000-206-1987-0167519870509<NA>1영업/정상1영업<NA><NA><NA><NA>02 7631038.00110807서울특별시 종로구 돈의동 39-2 대성빌딩 201호서울특별시 종로구 돈화문로11길 29, 701호 (돈의동, 낙원오피스텔)3139영진비엠에스(주)2017-11-07 17:28:08I2018-08-31 23:59:59.0건물위생관리업199035.365798452223.875441건물위생관리업<NA><NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630000003000000-206-1987-0167719870710<NA>3폐업2폐업19940806<NA><NA><NA>0207337550120.00110290서울특별시 종로구 인사동 194-4<NA><NA>동서기연(주)2001-11-20 00:00:00I2018-08-31 23:59:59.0건물위생관리업198643.543485452199.798612건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730000003000000-206-1987-0167819870808<NA>3폐업2폐업20030707<NA><NA><NA>02 74415362,397.00110829서울특별시 종로구 숭인동 1422<NA><NA>주식회사건도2003-03-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업201966.262331452287.609465건물위생관리업<NA><NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830000003000000-206-1987-0167919870831<NA>3폐업2폐업20130412<NA><NA><NA>02 737647259.40110140서울특별시 종로구 수송동 146-1<NA><NA>대정실업2003-03-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업198076.878951452402.19527건물위생관리업<NA><NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930000003000000-206-1988-0167619880710<NA>3폐업2폐업20121217<NA><NA><NA>02 7420932855.00110320서울특별시 종로구 낙원동 90<NA><NA>(주)산정양행2006-02-15 00:00:00I2018-08-31 23:59:59.0건물위생관리업198934.124836452289.680019건물위생관리업<NA><NA><NA>2<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
30530000003000000-206-2021-000032021-03-29<NA>3폐업2폐업2023-11-09<NA><NA><NA>02722101143.47110-052서울특별시 종로구 적선동 156 광화문 플래티넘서울특별시 종로구 새문안로5가길 28, 광화문 플래티넘 810호 (적선동)3170(주)맨인씨앤에스2023-11-09 11:30:56U2022-10-31 23:01:00.0건물위생관리업197595.161312452460.054622<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30630000003000000-206-2021-0000420211116<NA>1영업/정상1영업<NA><NA><NA><NA>02 730 667715.00110121서울특별시 종로구 종로1가 24 르메이에르종로타운1서울특별시 종로구 종로 19, 르메이에르종로타운1 9층 942호 (종로1가)3157(주)에이원티엠에스2021-11-16 09:33:38I2021-11-18 00:22:44.0건물위생관리업198150.300374452019.212643건물위생관리업000000000N0<NA><NA><NA><NA>00000N
30730000003000000-206-2021-000052021-06-02<NA>3폐업2폐업2024-04-17<NA><NA><NA>031 248 937743.46110-999서울특별시 종로구 신문로1가 163 광화문오피시아빌딩서울특별시 종로구 새문안로 92, 광화문오피시아빌딩 15층 1510호 (신문로1가)3186평산앤종합관리2024-04-17 17:03:04U2023-12-03 23:09:00.0건물위생관리업197713.264844451938.037703<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30830000003000000-206-2022-0000120220817<NA>1영업/정상1영업<NA><NA><NA><NA>022149377749.00110754서울특별시 종로구 연지동 1-7 현대그룹빌딩 서관서울특별시 종로구 율곡로 194, 현대그룹빌딩 서관 B2층 (연지동)3127유한책임회사 티지아이코리아2022-08-17 14:45:41I2021-12-07 23:09:00.0건물위생관리업199976.765493452526.527263<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30930000003000000-206-2022-000022022-08-17<NA>1영업/정상1영업<NA><NA><NA><NA>0264043331119.45110-826서울특별시 종로구 숭인동 298-1서울특별시 종로구 종로 350, 5층 (숭인동)3114뉴던 주식회사2024-01-04 14:42:42U2023-12-01 00:06:00.0건물위생관리업201380.152505452291.85697<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31030000003000000-206-2022-0000320221025<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.00110863서울특별시 종로구 숭인동 178-81 운영빌딩 비01호서울특별시 종로구 종로65길 21, 운영빌딩 비01호 (숭인동)3112주식회사 로운트리2022-10-25 11:26:04I2021-10-30 22:07:00.0건물위생관리업201670.858168452572.102189<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31130000003000000-206-2022-0000420221219<NA>3폐업2폐업20230117<NA><NA><NA><NA>15.00110110서울특별시 종로구 서린동 159-1 동아일보사 6층서울특별시 종로구 청계천로 1, 동아일보사 6층 (서린동)3187(주)동아프린테크2023-01-17 11:27:14U2022-11-30 23:09:00.0건물위생관리업197993.004036451917.062538<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31230000003000000-206-2023-000012023-10-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30110-809서울특별시 종로구 동숭동 1-88 계우빌딩서울특별시 종로구 대학로12길 61, 계우빌딩 5층 501호 K606호 (동숭동)3086주식회사 웰컴클린2023-10-27 15:49:49I2022-10-30 22:09:00.0건물위생관리업200284.07971453238.540021<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31330000003000000-206-2023-000022023-12-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.17110-841서울특별시 종로구 창신동 408-7서울특별시 종로구 종로54길 45-13, 지하1층 (창신동)3120꼼꼬미청소2023-12-08 15:01:12I2022-11-01 23:00:00.0건물위생관리업201235.045032452029.072977<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31430000003000000-206-2024-000012024-03-14<NA>1영업/정상1영업<NA><NA><NA><NA>02 36709885265.00110-250서울특별시 종로구 재동 84-2 보헌빌딩서울특별시 종로구 계동길 31, 보헌빌딩 (재동)3059(주)삼양인터내셔날2024-03-14 16:29:45I2023-12-02 23:06:00.0건물위생관리업198730.4227452928.204611<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>