Overview

Dataset statistics

Number of variables47
Number of observations892
Missing cells11133
Missing cells (%)26.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory352.1 KiB
Average record size in memory404.1 B

Variable types

Categorical18
Text7
DateTime4
Unsupported7
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-19300/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (95.0%)Imbalance
사용시작지하층 is highly imbalanced (66.1%)Imbalance
사용끝지하층 is highly imbalanced (70.9%)Imbalance
다중이용업소여부 is highly imbalanced (98.3%)Imbalance
인허가취소일자 has 892 (100.0%) missing valuesMissing
폐업일자 has 323 (36.2%) missing valuesMissing
휴업시작일자 has 892 (100.0%) missing valuesMissing
휴업종료일자 has 892 (100.0%) missing valuesMissing
재개업일자 has 892 (100.0%) missing valuesMissing
전화번호 has 387 (43.4%) missing valuesMissing
도로명주소 has 186 (20.9%) missing valuesMissing
도로명우편번호 has 195 (21.9%) missing valuesMissing
좌표정보(X) has 57 (6.4%) missing valuesMissing
좌표정보(Y) has 57 (6.4%) missing valuesMissing
건물지상층수 has 384 (43.0%) missing valuesMissing
건물지하층수 has 418 (46.9%) missing valuesMissing
사용시작지상층 has 464 (52.0%) missing valuesMissing
사용끝지상층 has 504 (56.5%) missing valuesMissing
발한실여부 has 255 (28.6%) missing valuesMissing
조건부허가신고사유 has 892 (100.0%) missing valuesMissing
조건부허가시작일자 has 892 (100.0%) missing valuesMissing
조건부허가종료일자 has 892 (100.0%) missing valuesMissing
여성종사자수 has 708 (79.4%) missing valuesMissing
남성종사자수 has 702 (78.7%) missing valuesMissing
다중이용업소여부 has 245 (27.5%) 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 388 (43.5%) zerosZeros
건물지하층수 has 424 (47.5%) zerosZeros
사용시작지상층 has 66 (7.4%) zerosZeros
사용끝지상층 has 34 (3.8%) zerosZeros
여성종사자수 has 155 (17.4%) zerosZeros
남성종사자수 has 131 (14.7%) zerosZeros

Reproduction

Analysis started2024-05-11 07:10:25.281771
Analysis finished2024-05-11 07:10:26.232268
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3230000
892 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 892
100.0%

Length

2024-05-11T16:10:26.288346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:26.396631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 892
100.0%

관리번호
Text

UNIQUE 

Distinct892
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-11T16:10:26.563593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters19624
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

Unique892 ?
Unique (%)100.0%

Sample

1st row3230000-206-1976-03184
2nd row3230000-206-1992-03128
3rd row3230000-206-1992-03129
4th row3230000-206-1992-03130
5th row3230000-206-1992-03131
ValueCountFrequency (%)
3230000-206-1976-03184 1
 
0.1%
3230000-206-2014-00035 1
 
0.1%
3230000-206-2014-00037 1
 
0.1%
3230000-206-2014-00025 1
 
0.1%
3230000-206-2014-00026 1
 
0.1%
3230000-206-2014-00027 1
 
0.1%
3230000-206-2014-00028 1
 
0.1%
3230000-206-2014-00029 1
 
0.1%
3230000-206-2014-00030 1
 
0.1%
3230000-206-2014-00031 1
 
0.1%
Other values (882) 882
98.9%
2024-05-11T16:10:26.900892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8474
43.2%
2 3102
 
15.8%
- 2676
 
13.6%
3 2212
 
11.3%
6 1097
 
5.6%
1 957
 
4.9%
9 347
 
1.8%
4 233
 
1.2%
5 194
 
1.0%
7 181
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16948
86.4%
Dash Punctuation 2676
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8474
50.0%
2 3102
 
18.3%
3 2212
 
13.1%
6 1097
 
6.5%
1 957
 
5.6%
9 347
 
2.0%
4 233
 
1.4%
5 194
 
1.1%
7 181
 
1.1%
8 151
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 2676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8474
43.2%
2 3102
 
15.8%
- 2676
 
13.6%
3 2212
 
11.3%
6 1097
 
5.6%
1 957
 
4.9%
9 347
 
1.8%
4 233
 
1.2%
5 194
 
1.0%
7 181
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8474
43.2%
2 3102
 
15.8%
- 2676
 
13.6%
3 2212
 
11.3%
6 1097
 
5.6%
1 957
 
4.9%
9 347
 
1.8%
4 233
 
1.2%
5 194
 
1.0%
7 181
 
0.9%
Distinct713
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum1976-10-07 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T16:10:27.325656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:10:27.466327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3
569 
1
323 

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 (%)
3 569
63.8%
1 323
36.2%

Length

2024-05-11T16:10:27.621825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:27.716083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 569
63.8%
1 323
36.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
569 
영업/정상
323 

Length

Max length5
Median length2
Mean length3.0863229
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 569
63.8%
영업/정상 323
36.2%

Length

2024-05-11T16:10:27.831520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:27.945214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 569
63.8%
영업/정상 323
36.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2
569 
1
323 

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 (%)
2 569
63.8%
1 323
36.2%

Length

2024-05-11T16:10:28.048599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:28.145324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 569
63.8%
1 323
36.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
569 
영업
323 

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 569
63.8%
영업 323
36.2%

Length

2024-05-11T16:10:28.242403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:28.332663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 569
63.8%
영업 323
36.2%

폐업일자
Date

MISSING 

Distinct446
Distinct (%)78.4%
Missing323
Missing (%)36.2%
Memory size7.1 KiB
Minimum1995-11-23 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T16:10:28.449693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:10:28.583803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB

전화번호
Text

MISSING 

Distinct487
Distinct (%)96.4%
Missing387
Missing (%)43.4%
Memory size7.1 KiB
2024-05-11T16:10:28.873320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.968317
Min length7

Characters and Unicode

Total characters5539
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

Unique473 ?
Unique (%)93.7%

Sample

1st row0234022567
2nd row02 4183536
3rd row02 4211203
4th row02 4487704
5th row02 4894997
ValueCountFrequency (%)
02 391
34.9%
070 19
 
1.7%
031 15
 
1.3%
400 8
 
0.7%
418 8
 
0.7%
420 7
 
0.6%
415 7
 
0.6%
430 6
 
0.5%
423 6
 
0.5%
407 6
 
0.5%
Other values (564) 648
57.8%
2024-05-11T16:10:29.389728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
18.1%
859
15.5%
2 856
15.5%
4 598
10.8%
1 427
7.7%
3 388
 
7.0%
7 318
 
5.7%
5 312
 
5.6%
8 303
 
5.5%
9 248
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4680
84.5%
Space Separator 859
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
21.4%
2 856
18.3%
4 598
12.8%
1 427
9.1%
3 388
 
8.3%
7 318
 
6.8%
5 312
 
6.7%
8 303
 
6.5%
9 248
 
5.3%
6 230
 
4.9%
Space Separator
ValueCountFrequency (%)
859
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5539
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
18.1%
859
15.5%
2 856
15.5%
4 598
10.8%
1 427
7.7%
3 388
 
7.0%
7 318
 
5.7%
5 312
 
5.6%
8 303
 
5.5%
9 248
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
18.1%
859
15.5%
2 856
15.5%
4 598
10.8%
1 427
7.7%
3 388
 
7.0%
7 318
 
5.7%
5 312
 
5.6%
8 303
 
5.5%
9 248
 
4.5%
Distinct499
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-11T16:10:29.779681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9820628
Min length3

Characters and Unicode

Total characters4444
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

Unique402 ?
Unique (%)45.1%

Sample

1st row3,972.37
2nd row47.60
3rd row54.35
4th row149.82
5th row.00
ValueCountFrequency (%)
00 78
 
8.7%
50.00 24
 
2.7%
66.00 23
 
2.6%
33.00 23
 
2.6%
30.00 16
 
1.8%
0.00 14
 
1.6%
20.00 14
 
1.6%
15.00 13
 
1.5%
22.68 11
 
1.2%
40.00 11
 
1.2%
Other values (489) 665
74.6%
2024-05-11T16:10:30.248494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1298
29.2%
. 892
20.1%
1 310
 
7.0%
2 309
 
7.0%
5 275
 
6.2%
3 275
 
6.2%
6 267
 
6.0%
4 234
 
5.3%
8 210
 
4.7%
9 196
 
4.4%
Other values (2) 178
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3541
79.7%
Other Punctuation 903
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1298
36.7%
1 310
 
8.8%
2 309
 
8.7%
5 275
 
7.8%
3 275
 
7.8%
6 267
 
7.5%
4 234
 
6.6%
8 210
 
5.9%
9 196
 
5.5%
7 167
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 892
98.8%
, 11
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1298
29.2%
. 892
20.1%
1 310
 
7.0%
2 309
 
7.0%
5 275
 
6.2%
3 275
 
6.2%
6 267
 
6.0%
4 234
 
5.3%
8 210
 
4.7%
9 196
 
4.4%
Other values (2) 178
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1298
29.2%
. 892
20.1%
1 310
 
7.0%
2 309
 
7.0%
5 275
 
6.2%
3 275
 
6.2%
6 267
 
6.0%
4 234
 
5.3%
8 210
 
4.7%
9 196
 
4.4%
Other values (2) 178
 
4.0%
Distinct166
Distinct (%)18.7%
Missing2
Missing (%)0.2%
Memory size7.1 KiB
2024-05-11T16:10:30.535524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1988764
Min length6

Characters and Unicode

Total characters5517
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

Unique45 ?
Unique (%)5.1%

Sample

1st row138885
2nd row138838
3rd row138210
4th row138210
5th row138210
ValueCountFrequency (%)
138888 50
 
5.6%
138828 31
 
3.5%
138200 27
 
3.0%
138210 26
 
2.9%
138960 21
 
2.4%
138934 20
 
2.2%
138850 17
 
1.9%
138827 17
 
1.9%
138-888 16
 
1.8%
138861 16
 
1.8%
Other values (156) 649
72.9%
2024-05-11T16:10:30.951666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1847
33.5%
1 1097
19.9%
3 1053
19.1%
0 311
 
5.6%
2 253
 
4.6%
4 191
 
3.5%
5 177
 
3.2%
- 177
 
3.2%
6 148
 
2.7%
7 137
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5340
96.8%
Dash Punctuation 177
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1847
34.6%
1 1097
20.5%
3 1053
19.7%
0 311
 
5.8%
2 253
 
4.7%
4 191
 
3.6%
5 177
 
3.3%
6 148
 
2.8%
7 137
 
2.6%
9 126
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1847
33.5%
1 1097
19.9%
3 1053
19.1%
0 311
 
5.6%
2 253
 
4.6%
4 191
 
3.5%
5 177
 
3.2%
- 177
 
3.2%
6 148
 
2.7%
7 137
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1847
33.5%
1 1097
19.9%
3 1053
19.1%
0 311
 
5.6%
2 253
 
4.6%
4 191
 
3.5%
5 177
 
3.2%
- 177
 
3.2%
6 148
 
2.7%
7 137
 
2.5%
Distinct792
Distinct (%)89.0%
Missing2
Missing (%)0.2%
Memory size7.1 KiB
2024-05-11T16:10:31.208019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length24.41573
Min length16

Characters and Unicode

Total characters21730
Distinct characters275
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

Unique735 ?
Unique (%)82.6%

Sample

1st row서울특별시 송파구 문정동 150-4
2nd row서울특별시 송파구 삼전동 48-10
3rd row서울특별시 송파구 장지동 산 391-5 대원빌딩 7층동
4th row서울특별시 송파구 장지동 산 37-7
5th row서울특별시 송파구 장지동 산 250-1
ValueCountFrequency (%)
서울특별시 890
20.1%
송파구 890
20.1%
문정동 183
 
4.1%
가락동 150
 
3.4%
방이동 118
 
2.7%
송파동 73
 
1.6%
잠실동 69
 
1.6%
오금동 57
 
1.3%
석촌동 53
 
1.2%
거여동 38
 
0.9%
Other values (1008) 1913
43.1%
2024-05-11T16:10:31.621795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4118
19.0%
1035
 
4.8%
979
 
4.5%
1 942
 
4.3%
925
 
4.3%
904
 
4.2%
897
 
4.1%
892
 
4.1%
890
 
4.1%
890
 
4.1%
Other values (265) 9258
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12621
58.1%
Space Separator 4118
 
19.0%
Decimal Number 4107
 
18.9%
Dash Punctuation 746
 
3.4%
Uppercase Letter 82
 
0.4%
Close Punctuation 21
 
0.1%
Open Punctuation 20
 
0.1%
Other Punctuation 14
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1035
 
8.2%
979
 
7.8%
925
 
7.3%
904
 
7.2%
897
 
7.1%
892
 
7.1%
890
 
7.1%
890
 
7.1%
890
 
7.1%
228
 
1.8%
Other values (225) 4091
32.4%
Uppercase Letter
ValueCountFrequency (%)
B 14
17.1%
T 7
 
8.5%
A 7
 
8.5%
S 7
 
8.5%
N 6
 
7.3%
D 5
 
6.1%
I 5
 
6.1%
U 4
 
4.9%
L 4
 
4.9%
K 3
 
3.7%
Other values (11) 20
24.4%
Decimal Number
ValueCountFrequency (%)
1 942
22.9%
2 591
14.4%
3 465
11.3%
0 386
9.4%
4 363
 
8.8%
6 330
 
8.0%
5 305
 
7.4%
9 255
 
6.2%
7 251
 
6.1%
8 219
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 6
42.9%
/ 5
35.7%
? 2
 
14.3%
& 1
 
7.1%
Space Separator
ValueCountFrequency (%)
4118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 746
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12621
58.1%
Common 9026
41.5%
Latin 83
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1035
 
8.2%
979
 
7.8%
925
 
7.3%
904
 
7.2%
897
 
7.1%
892
 
7.1%
890
 
7.1%
890
 
7.1%
890
 
7.1%
228
 
1.8%
Other values (225) 4091
32.4%
Latin
ValueCountFrequency (%)
B 14
16.9%
T 7
 
8.4%
A 7
 
8.4%
S 7
 
8.4%
N 6
 
7.2%
D 5
 
6.0%
I 5
 
6.0%
U 4
 
4.8%
L 4
 
4.8%
K 3
 
3.6%
Other values (12) 21
25.3%
Common
ValueCountFrequency (%)
4118
45.6%
1 942
 
10.4%
- 746
 
8.3%
2 591
 
6.5%
3 465
 
5.2%
0 386
 
4.3%
4 363
 
4.0%
6 330
 
3.7%
5 305
 
3.4%
9 255
 
2.8%
Other values (8) 525
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12621
58.1%
ASCII 9109
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4118
45.2%
1 942
 
10.3%
- 746
 
8.2%
2 591
 
6.5%
3 465
 
5.1%
0 386
 
4.2%
4 363
 
4.0%
6 330
 
3.6%
5 305
 
3.3%
9 255
 
2.8%
Other values (30) 608
 
6.7%
Hangul
ValueCountFrequency (%)
1035
 
8.2%
979
 
7.8%
925
 
7.3%
904
 
7.2%
897
 
7.1%
892
 
7.1%
890
 
7.1%
890
 
7.1%
890
 
7.1%
228
 
1.8%
Other values (225) 4091
32.4%

도로명주소
Text

MISSING 

Distinct695
Distinct (%)98.4%
Missing186
Missing (%)20.9%
Memory size7.1 KiB
2024-05-11T16:10:31.920006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length35.375354
Min length22

Characters and Unicode

Total characters24975
Distinct characters283
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

Unique684 ?
Unique (%)96.9%

Sample

1st row서울특별시 송파구 백제고분로40길 31, 3층 (석촌동)
2nd row서울특별시 송파구 양재대로 932 (가락동,( 서문 ))
3rd row서울특별시 송파구 강동대로 61-4 (풍납동)
4th row서울특별시 송파구 법원로 128, 문정에스케이브이원지엘메트로시티 C동 G114-A124호 (문정동)
5th row서울특별시 송파구 올림픽로30길 5, 2층 (방이동)
ValueCountFrequency (%)
서울특별시 706
 
14.8%
송파구 706
 
14.8%
문정동 153
 
3.2%
가락동 110
 
2.3%
방이동 78
 
1.6%
2층 69
 
1.4%
3층 61
 
1.3%
잠실동 46
 
1.0%
송파동 45
 
0.9%
충민로 41
 
0.9%
Other values (1066) 2762
57.8%
2024-05-11T16:10:32.343565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4072
 
16.3%
1 932
 
3.7%
920
 
3.7%
878
 
3.5%
, 832
 
3.3%
829
 
3.3%
722
 
2.9%
) 721
 
2.9%
( 721
 
2.9%
711
 
2.8%
Other values (273) 13637
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14111
56.5%
Decimal Number 4228
 
16.9%
Space Separator 4072
 
16.3%
Other Punctuation 836
 
3.3%
Close Punctuation 721
 
2.9%
Open Punctuation 721
 
2.9%
Dash Punctuation 150
 
0.6%
Uppercase Letter 134
 
0.5%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
920
 
6.5%
878
 
6.2%
829
 
5.9%
722
 
5.1%
711
 
5.0%
708
 
5.0%
707
 
5.0%
706
 
5.0%
706
 
5.0%
705
 
5.0%
Other values (233) 6519
46.2%
Uppercase Letter
ValueCountFrequency (%)
B 33
24.6%
C 17
12.7%
A 16
11.9%
T 13
 
9.7%
Y 8
 
6.0%
F 7
 
5.2%
L 6
 
4.5%
S 5
 
3.7%
K 4
 
3.0%
J 4
 
3.0%
Other values (12) 21
15.7%
Decimal Number
ValueCountFrequency (%)
1 932
22.0%
2 681
16.1%
0 529
12.5%
3 499
11.8%
4 363
 
8.6%
6 316
 
7.5%
5 288
 
6.8%
8 231
 
5.5%
7 207
 
4.9%
9 182
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 832
99.5%
/ 4
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
4072
100.0%
Close Punctuation
ValueCountFrequency (%)
) 721
100.0%
Open Punctuation
ValueCountFrequency (%)
( 721
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14111
56.5%
Common 10728
43.0%
Latin 136
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
920
 
6.5%
878
 
6.2%
829
 
5.9%
722
 
5.1%
711
 
5.0%
708
 
5.0%
707
 
5.0%
706
 
5.0%
706
 
5.0%
705
 
5.0%
Other values (233) 6519
46.2%
Latin
ValueCountFrequency (%)
B 33
24.3%
C 17
12.5%
A 16
11.8%
T 13
 
9.6%
Y 8
 
5.9%
F 7
 
5.1%
L 6
 
4.4%
S 5
 
3.7%
K 4
 
2.9%
J 4
 
2.9%
Other values (14) 23
16.9%
Common
ValueCountFrequency (%)
4072
38.0%
1 932
 
8.7%
, 832
 
7.8%
) 721
 
6.7%
( 721
 
6.7%
2 681
 
6.3%
0 529
 
4.9%
3 499
 
4.7%
4 363
 
3.4%
6 316
 
2.9%
Other values (6) 1062
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14111
56.5%
ASCII 10864
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4072
37.5%
1 932
 
8.6%
, 832
 
7.7%
) 721
 
6.6%
( 721
 
6.6%
2 681
 
6.3%
0 529
 
4.9%
3 499
 
4.6%
4 363
 
3.3%
6 316
 
2.9%
Other values (30) 1198
 
11.0%
Hangul
ValueCountFrequency (%)
920
 
6.5%
878
 
6.2%
829
 
5.9%
722
 
5.1%
711
 
5.0%
708
 
5.0%
707
 
5.0%
706
 
5.0%
706
 
5.0%
705
 
5.0%
Other values (233) 6519
46.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct214
Distinct (%)30.7%
Missing195
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean5693.8264
Minimum5502
Maximum5855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:32.489182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5502
5-th percentile5530
Q15588
median5704
Q35801
95-th percentile5838
Maximum5855
Range353
Interquartile range (IQR)213

Descriptive statistics

Standard deviation109.11421
Coefficient of variation (CV)0.0191636
Kurtosis-1.3084575
Mean5693.8264
Median Absolute Deviation (MAD)101
Skewness-0.12435679
Sum3968597
Variance11905.911
MonotonicityNot monotonic
2024-05-11T16:10:32.642706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5838 36
 
4.0%
5836 26
 
2.9%
5719 22
 
2.5%
5548 18
 
2.0%
5510 17
 
1.9%
5854 14
 
1.6%
5545 14
 
1.6%
5556 14
 
1.6%
5855 13
 
1.5%
5542 10
 
1.1%
Other values (204) 513
57.5%
(Missing) 195
 
21.9%
ValueCountFrequency (%)
5502 2
 
0.2%
5504 1
 
0.1%
5505 1
 
0.1%
5510 17
1.9%
5513 1
 
0.1%
5514 1
 
0.1%
5517 1
 
0.1%
5518 2
 
0.2%
5519 2
 
0.2%
5525 2
 
0.2%
ValueCountFrequency (%)
5855 13
 
1.5%
5854 14
 
1.6%
5849 1
 
0.1%
5841 2
 
0.2%
5840 4
 
0.4%
5838 36
4.0%
5837 4
 
0.4%
5836 26
2.9%
5835 1
 
0.1%
5832 3
 
0.3%
Distinct873
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-11T16:10:32.864674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length7.8464126
Min length2

Characters and Unicode

Total characters6999
Distinct characters434
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

Unique855 ?
Unique (%)95.9%

Sample

1st row신한동종합관리(주)
2nd row동방환경(주)
3rd row한영크린써비스(주)
4th row해동상사
5th row동일코리아
ValueCountFrequency (%)
주식회사 61
 
5.9%
19
 
1.8%
사회복지법인 5
 
0.5%
유한회사 4
 
0.4%
하우스 4
 
0.4%
크린 3
 
0.3%
주)한국에스웨이 3
 
0.3%
주)해강이엔씨 2
 
0.2%
케이비 2
 
0.2%
주)대호아이비에스 2
 
0.2%
Other values (908) 930
89.9%
2024-05-11T16:10:33.244475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
650
 
9.3%
) 574
 
8.2%
( 571
 
8.2%
263
 
3.8%
198
 
2.8%
163
 
2.3%
143
 
2.0%
138
 
2.0%
113
 
1.6%
100
 
1.4%
Other values (424) 4086
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5619
80.3%
Close Punctuation 574
 
8.2%
Open Punctuation 571
 
8.2%
Space Separator 143
 
2.0%
Uppercase Letter 65
 
0.9%
Lowercase Letter 13
 
0.2%
Other Punctuation 10
 
0.1%
Decimal Number 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
650
 
11.6%
263
 
4.7%
198
 
3.5%
163
 
2.9%
138
 
2.5%
113
 
2.0%
100
 
1.8%
95
 
1.7%
83
 
1.5%
81
 
1.4%
Other values (388) 3735
66.5%
Uppercase Letter
ValueCountFrequency (%)
S 11
16.9%
C 10
15.4%
I 5
 
7.7%
E 5
 
7.7%
O 5
 
7.7%
N 4
 
6.2%
M 4
 
6.2%
K 3
 
4.6%
G 3
 
4.6%
P 2
 
3.1%
Other values (9) 13
20.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
15.4%
l 2
15.4%
i 2
15.4%
c 2
15.4%
t 1
7.7%
m 1
7.7%
s 1
7.7%
o 1
7.7%
n 1
7.7%
Other Punctuation
ValueCountFrequency (%)
. 8
80.0%
& 2
 
20.0%
Decimal Number
ValueCountFrequency (%)
9 2
66.7%
3 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 574
100.0%
Open Punctuation
ValueCountFrequency (%)
( 571
100.0%
Space Separator
ValueCountFrequency (%)
143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5619
80.3%
Common 1302
 
18.6%
Latin 78
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
650
 
11.6%
263
 
4.7%
198
 
3.5%
163
 
2.9%
138
 
2.5%
113
 
2.0%
100
 
1.8%
95
 
1.7%
83
 
1.5%
81
 
1.4%
Other values (388) 3735
66.5%
Latin
ValueCountFrequency (%)
S 11
14.1%
C 10
 
12.8%
I 5
 
6.4%
E 5
 
6.4%
O 5
 
6.4%
N 4
 
5.1%
M 4
 
5.1%
K 3
 
3.8%
G 3
 
3.8%
e 2
 
2.6%
Other values (18) 26
33.3%
Common
ValueCountFrequency (%)
) 574
44.1%
( 571
43.9%
143
 
11.0%
. 8
 
0.6%
& 2
 
0.2%
9 2
 
0.2%
- 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5619
80.3%
ASCII 1380
 
19.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
650
 
11.6%
263
 
4.7%
198
 
3.5%
163
 
2.9%
138
 
2.5%
113
 
2.0%
100
 
1.8%
95
 
1.7%
83
 
1.5%
81
 
1.4%
Other values (388) 3735
66.5%
ASCII
ValueCountFrequency (%)
) 574
41.6%
( 571
41.4%
143
 
10.4%
S 11
 
0.8%
C 10
 
0.7%
. 8
 
0.6%
I 5
 
0.4%
E 5
 
0.4%
O 5
 
0.4%
N 4
 
0.3%
Other values (26) 44
 
3.2%
Distinct800
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum1999-03-23 00:00:00
Maximum2024-05-08 10:13:20
2024-05-11T16:10:33.423644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:10:33.586186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
I
531 
U
361 

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 531
59.5%
U 361
40.5%

Length

2024-05-11T16:10:33.746648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:33.865843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 531
59.5%
u 361
40.5%
Distinct322
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T16:10:34.002815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:10:34.137078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
건물위생관리업
887 
건물위생관리업 기타
 
5

Length

Max length10
Median length7
Mean length7.0168161
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 887
99.4%
건물위생관리업 기타 5
 
0.6%

Length

2024-05-11T16:10:34.259571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:34.345750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 892
99.4%
기타 5
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct554
Distinct (%)66.3%
Missing57
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean210269.05
Minimum206397.35
Maximum213830.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:34.453288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206397.35
5-th percentile207263.11
Q1209464.45
median210476
Q3211088.79
95-th percentile212660.33
Maximum213830.47
Range7433.121
Interquartile range (IQR)1624.3483

Descriptive statistics

Standard deviation1458.4789
Coefficient of variation (CV)0.0069362512
Kurtosis0.059726207
Mean210269.05
Median Absolute Deviation (MAD)807.803
Skewness-0.35025985
Sum1.7557465 × 108
Variance2127160.8
MonotonicityNot monotonic
2024-05-11T16:10:34.593529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210986.460698452 28
 
3.1%
209416.462512974 9
 
1.0%
211382.424686224 9
 
1.0%
209790.959909032 8
 
0.9%
210431.832858016 8
 
0.9%
211053.119518 7
 
0.8%
210289.0 6
 
0.7%
210591.787825479 6
 
0.7%
209427.410217251 6
 
0.7%
209140.885315651 6
 
0.7%
Other values (544) 742
83.2%
(Missing) 57
 
6.4%
ValueCountFrequency (%)
206397.34797252 1
 
0.1%
206900.84547168 1
 
0.1%
206908.348523164 2
 
0.2%
206914.005245094 2
 
0.2%
206916.75835 3
0.3%
206919.478094926 1
 
0.1%
206932.357872339 5
0.6%
206945.449731532 1
 
0.1%
206956.849156975 1
 
0.1%
206960.853941553 1
 
0.1%
ValueCountFrequency (%)
213830.468958047 1
0.1%
213803.219673517 1
0.1%
213712.175713909 1
0.1%
213577.946731813 1
0.1%
213575.844348959 1
0.1%
213468.096258992 1
0.1%
213465.861165698 1
0.1%
213447.204339171 1
0.1%
213352.825103698 1
0.1%
213333.804421171 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct554
Distinct (%)66.3%
Missing57
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean444349.06
Minimum441112.93
Maximum448601.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:34.739435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441112.93
5-th percentile442044.86
Q1443469.06
median444393.47
Q3445301.06
95-th percentile446055.9
Maximum448601.32
Range7488.3968
Interquartile range (IQR)1832.0014

Descriptive statistics

Standard deviation1342.3194
Coefficient of variation (CV)0.0030208671
Kurtosis0.16207122
Mean444349.06
Median Absolute Deviation (MAD)912.26007
Skewness0.15334993
Sum3.7103146 × 108
Variance1801821.5
MonotonicityNot monotonic
2024-05-11T16:10:34.868208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441725.293491662 28
 
3.1%
444307.531173705 9
 
1.0%
445029.112139333 9
 
1.0%
443481.212174317 8
 
0.9%
443465.4592322 8
 
0.9%
442026.988783 7
 
0.8%
442448.0 6
 
0.7%
443574.427660288 6
 
0.7%
445829.725943441 6
 
0.7%
446042.592367722 6
 
0.7%
Other values (544) 742
83.2%
(Missing) 57
 
6.4%
ValueCountFrequency (%)
441112.927797859 1
 
0.1%
441594.11003888 1
 
0.1%
441725.293491662 28
3.1%
441833.16323518 2
 
0.2%
441953.803802768 1
 
0.1%
441996.227705236 1
 
0.1%
442026.988783 7
 
0.8%
442034.053754612 1
 
0.1%
442049.488916525 2
 
0.2%
442053.227933005 4
 
0.4%
ValueCountFrequency (%)
448601.324644324 1
0.1%
448544.828218852 1
0.1%
448443.321572646 1
0.1%
448299.18801552 1
0.1%
448294.869037663 1
0.1%
448276.580577065 1
0.1%
448167.313880614 1
0.1%
448114.284328398 1
0.1%
447987.10147332 1
0.1%
447968.027991844 2
0.2%

위생업태명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
건물위생관리업
643 
<NA>
245 
건물위생관리업 기타
 
4

Length

Max length10
Median length7
Mean length6.1894619
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 643
72.1%
<NA> 245
 
27.5%
건물위생관리업 기타 4
 
0.4%

Length

2024-05-11T16:10:34.997221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:35.098614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 647
72.2%
na 245
 
27.3%
기타 4
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)3.0%
Missing384
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean1.1791339
Minimum0
Maximum20
Zeros388
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:35.195186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7687673
Coefficient of variation (CV)2.3481366
Kurtosis16.495865
Mean1.1791339
Median Absolute Deviation (MAD)0
Skewness3.5760213
Sum599
Variance7.6660726
MonotonicityNot monotonic
2024-05-11T16:10:35.308271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 388
43.5%
4 29
 
3.3%
3 28
 
3.1%
5 20
 
2.2%
6 12
 
1.3%
1 8
 
0.9%
2 7
 
0.8%
9 3
 
0.3%
16 3
 
0.3%
12 2
 
0.2%
Other values (5) 8
 
0.9%
(Missing) 384
43.0%
ValueCountFrequency (%)
0 388
43.5%
1 8
 
0.9%
2 7
 
0.8%
3 28
 
3.1%
4 29
 
3.3%
5 20
 
2.2%
6 12
 
1.3%
8 2
 
0.2%
9 3
 
0.3%
10 2
 
0.2%
ValueCountFrequency (%)
20 2
 
0.2%
19 1
 
0.1%
16 3
 
0.3%
12 2
 
0.2%
11 1
 
0.1%
10 2
 
0.2%
9 3
 
0.3%
8 2
 
0.2%
6 12
1.3%
5 20
2.2%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.5%
Missing418
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean0.15189873
Minimum0
Maximum7
Zeros424
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:35.411007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.57256386
Coefficient of variation (CV)3.7693787
Kurtosis59.515956
Mean0.15189873
Median Absolute Deviation (MAD)0
Skewness6.5793848
Sum72
Variance0.32782937
MonotonicityNot monotonic
2024-05-11T16:10:35.796243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 424
47.5%
1 39
 
4.4%
2 7
 
0.8%
5 1
 
0.1%
7 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
(Missing) 418
46.9%
ValueCountFrequency (%)
0 424
47.5%
1 39
 
4.4%
2 7
 
0.8%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 7
 
0.8%
1 39
 
4.4%
0 424
47.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)4.4%
Missing464
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean3.1191589
Minimum0
Maximum20
Zeros66
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:35.910615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile9
Maximum20
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0256216
Coefficient of variation (CV)0.97001202
Kurtosis5.6155803
Mean3.1191589
Median Absolute Deviation (MAD)1
Skewness2.0385346
Sum1335
Variance9.1543862
MonotonicityNot monotonic
2024-05-11T16:10:36.022264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2 92
 
10.3%
3 75
 
8.4%
0 66
 
7.4%
1 60
 
6.7%
4 50
 
5.6%
5 30
 
3.4%
6 13
 
1.5%
9 8
 
0.9%
12 7
 
0.8%
8 7
 
0.8%
Other values (9) 20
 
2.2%
(Missing) 464
52.0%
ValueCountFrequency (%)
0 66
7.4%
1 60
6.7%
2 92
10.3%
3 75
8.4%
4 50
5.6%
5 30
 
3.4%
6 13
 
1.5%
7 6
 
0.7%
8 7
 
0.8%
9 8
 
0.9%
ValueCountFrequency (%)
20 1
 
0.1%
17 1
 
0.1%
16 2
 
0.2%
15 1
 
0.1%
14 1
 
0.1%
13 1
 
0.1%
12 7
0.8%
11 3
 
0.3%
10 4
0.4%
9 8
0.9%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)5.2%
Missing504
Missing (%)56.5%
Infinite0
Infinite (%)0.0%
Mean3.4046392
Minimum0
Maximum20
Zeros34
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:36.150637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile10
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1316801
Coefficient of variation (CV)0.91982731
Kurtosis6.1605656
Mean3.4046392
Median Absolute Deviation (MAD)1
Skewness2.1874037
Sum1321
Variance9.8074203
MonotonicityNot monotonic
2024-05-11T16:10:36.254025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 90
 
10.1%
3 73
 
8.2%
1 59
 
6.6%
4 49
 
5.5%
0 34
 
3.8%
5 29
 
3.3%
6 12
 
1.3%
12 8
 
0.9%
8 7
 
0.8%
9 7
 
0.8%
Other values (10) 20
 
2.2%
(Missing) 504
56.5%
ValueCountFrequency (%)
0 34
 
3.8%
1 59
6.6%
2 90
10.1%
3 73
8.2%
4 49
5.5%
5 29
 
3.3%
6 12
 
1.3%
7 6
 
0.7%
8 7
 
0.8%
9 7
 
0.8%
ValueCountFrequency (%)
20 1
 
0.1%
19 1
 
0.1%
17 1
 
0.1%
16 2
 
0.2%
15 1
 
0.1%
14 1
 
0.1%
13 1
 
0.1%
12 8
0.9%
11 3
 
0.3%
10 3
 
0.3%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
733 
0
111 
1
 
41
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length3.4663677
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 733
82.2%
0 111
 
12.4%
1 41
 
4.6%
2 4
 
0.4%
3 2
 
0.2%
13 1
 
0.1%

Length

2024-05-11T16:10:36.373278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:36.480716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 733
82.2%
0 111
 
12.4%
1 41
 
4.6%
2 4
 
0.4%
3 2
 
0.2%
13 1
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
768 
0
78 
1
 
40
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.5840807
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 768
86.1%
0 78
 
8.7%
1 40
 
4.5%
2 4
 
0.4%
3 1
 
0.1%
13 1
 
0.1%

Length

2024-05-11T16:10:36.597918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:36.700949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 768
86.1%
0 78
 
8.7%
1 40
 
4.5%
2 4
 
0.4%
3 1
 
0.1%
13 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
454 
0
438 

Length

Max length4
Median length4
Mean length2.5269058
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 454
50.9%
0 438
49.1%

Length

2024-05-11T16:10:36.829965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:36.941326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 454
50.9%
0 438
49.1%

양실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
454 
0
438 

Length

Max length4
Median length4
Mean length2.5269058
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 454
50.9%
0 438
49.1%

Length

2024-05-11T16:10:37.068837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:37.176636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 454
50.9%
0 438
49.1%

욕실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
454 
0
438 

Length

Max length4
Median length4
Mean length2.5269058
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 454
50.9%
0 438
49.1%

Length

2024-05-11T16:10:37.295350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:37.402889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 454
50.9%
0 438
49.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing255
Missing (%)28.6%
Memory size1.9 KiB
False
637 
(Missing)
255 
ValueCountFrequency (%)
False 637
71.4%
(Missing) 255
28.6%
2024-05-11T16:10:37.484601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
453 
0
438 
3
 
1

Length

Max length4
Median length4
Mean length2.5235426
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 453
50.8%
0 438
49.1%
3 1
 
0.1%

Length

2024-05-11T16:10:37.583409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:37.689530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 453
50.8%
0 438
49.1%
3 1
 
0.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing892
Missing (%)100.0%
Memory size8.0 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
688 
임대
202 
자가
 
2

Length

Max length4
Median length4
Mean length3.5426009
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> 688
77.1%
임대 202
 
22.6%
자가 2
 
0.2%

Length

2024-05-11T16:10:37.811998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:37.926538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 688
77.1%
임대 202
 
22.6%
자가 2
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
488 
0
404 

Length

Max length4
Median length4
Mean length2.6412556
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> 488
54.7%
0 404
45.3%

Length

2024-05-11T16:10:38.051417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:38.184599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 488
54.7%
0 404
45.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.8%
Missing708
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean0.39130435
Minimum0
Maximum7
Zeros155
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:38.289792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.85
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1777214
Coefficient of variation (CV)3.0097326
Kurtosis14.825913
Mean0.39130435
Median Absolute Deviation (MAD)0
Skewness3.7641331
Sum72
Variance1.3870278
MonotonicityNot monotonic
2024-05-11T16:10:38.394231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 155
 
17.4%
1 14
 
1.6%
2 5
 
0.6%
5 4
 
0.4%
4 2
 
0.2%
3 2
 
0.2%
7 2
 
0.2%
(Missing) 708
79.4%
ValueCountFrequency (%)
0 155
17.4%
1 14
 
1.6%
2 5
 
0.6%
3 2
 
0.2%
4 2
 
0.2%
5 4
 
0.4%
7 2
 
0.2%
ValueCountFrequency (%)
7 2
 
0.2%
5 4
 
0.4%
4 2
 
0.2%
3 2
 
0.2%
2 5
 
0.6%
1 14
 
1.6%
0 155
17.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)5.8%
Missing702
Missing (%)78.7%
Infinite0
Infinite (%)0.0%
Mean1.3210526
Minimum0
Maximum26
Zeros131
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2024-05-11T16:10:38.501135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum26
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.3942184
Coefficient of variation (CV)2.5693287
Kurtosis22.38695
Mean1.3210526
Median Absolute Deviation (MAD)0
Skewness4.3243892
Sum251
Variance11.520718
MonotonicityNot monotonic
2024-05-11T16:10:38.607167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 131
 
14.7%
1 17
 
1.9%
2 12
 
1.3%
3 12
 
1.3%
5 5
 
0.6%
6 4
 
0.4%
10 3
 
0.3%
15 3
 
0.3%
26 1
 
0.1%
20 1
 
0.1%
(Missing) 702
78.7%
ValueCountFrequency (%)
0 131
14.7%
1 17
 
1.9%
2 12
 
1.3%
3 12
 
1.3%
4 1
 
0.1%
5 5
 
0.6%
6 4
 
0.4%
10 3
 
0.3%
15 3
 
0.3%
20 1
 
0.1%
ValueCountFrequency (%)
26 1
 
0.1%
20 1
 
0.1%
15 3
 
0.3%
10 3
 
0.3%
6 4
 
0.4%
5 5
 
0.6%
4 1
 
0.1%
3 12
1.3%
2 12
1.3%
1 17
1.9%

회수건조수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
511 
0
381 

Length

Max length4
Median length4
Mean length2.7186099
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> 511
57.3%
0 381
42.7%

Length

2024-05-11T16:10:38.731659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:38.839103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 511
57.3%
0 381
42.7%

침대수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
543 
0
349 

Length

Max length4
Median length4
Mean length2.8262332
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> 543
60.9%
0 349
39.1%

Length

2024-05-11T16:10:38.943460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:10:39.034084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 543
60.9%
0 349
39.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing245
Missing (%)27.5%
Memory size1.9 KiB
False
646 
True
 
1
(Missing)
245 
ValueCountFrequency (%)
False 646
72.4%
True 1
 
0.1%
(Missing) 245
 
27.5%
2024-05-11T16:10:39.111711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032300003230000-206-1976-0318419761007<NA>3폐업2폐업20020731<NA><NA><NA>02340225673,972.37138885서울특별시 송파구 문정동 150-4<NA><NA>신한동종합관리(주)2003-01-07 00:00:00I2018-08-31 23:59:59.0건물위생관리업210112.318379443221.728318건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132300003230000-206-1992-0312820030227<NA>3폐업2폐업20070731<NA><NA><NA>02 418353647.60138838서울특별시 송파구 삼전동 48-10<NA><NA>동방환경(주)2006-08-02 00:00:00I2018-08-31 23:59:59.0건물위생관리업207914.78619444584.647018건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232300003230000-206-1992-0312919920618<NA>3폐업2폐업19980707<NA><NA><NA>02 421120354.35138210서울특별시 송파구 장지동 산 391-5 대원빌딩 7층동<NA><NA>한영크린써비스(주)2002-09-04 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
332300003230000-206-1992-0313019920703<NA>3폐업2폐업19960123<NA><NA><NA>02 4487704149.82138210서울특별시 송파구 장지동 산 37-7<NA><NA>해동상사2002-09-04 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
432300003230000-206-1992-0313119921102<NA>3폐업2폐업19990312<NA><NA><NA>02 4894997.00138210서울특별시 송파구 장지동 산 250-1<NA><NA>동일코리아1999-03-23 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
532300003230000-206-1992-0313219921230<NA>3폐업2폐업19980507<NA><NA><NA>02 4254051798.40138836서울특별시 송파구 방이동 226-3<NA><NA>서울건물관리(주)2003-01-07 00:00:00I2018-08-31 23:59:59.0건물위생관리업210608.020069444943.016705건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632300003230000-206-1993-0313419930911<NA>3폐업2폐업19960123<NA><NA><NA>02 4213790561.94138210서울특별시 송파구 장지동 산 157-0<NA><NA>하영실업2002-09-04 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
732300003230000-206-1993-0313620030227<NA>1영업/정상1영업<NA><NA><NA><NA>02 412991245.49138847서울특별시 송파구 석촌동 294-5 3층서울특별시 송파구 백제고분로40길 31, 3층 (석촌동)5687대원나노 하이테크2014-04-02 15:14:17I2018-08-31 23:59:59.0건물위생관리업209477.553111444430.025102건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832300003230000-206-1993-0313820030227<NA>3폐업2폐업20040527<NA><NA><NA>02 4093361700.84138200서울특별시 송파구 문정동 100-6 삼봉빌딩301호<NA><NA>기린환경주식회사2003-06-10 00:00:00I2018-08-31 23:59:59.0건물위생관리업211458.631668442499.919987건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932300003230000-206-1993-0313919930710<NA>3폐업2폐업19991126<NA><NA><NA>02 409791985.14138210서울특별시 송파구 장지동 산 114-12<NA><NA>영원실업(주)2000-01-03 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
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
88232300003230000-206-2023-000212023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30138-800서울특별시 송파구 가락동 10-7 대명빌딩서울특별시 송파구 중대로 207, 대명빌딩 2층 201호 K475호 (가락동)5702이현종합관리 주식회사2023-10-20 14:40:58I2022-10-30 22:02:00.0건물위생관리업211108.961742444263.057029<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88332300003230000-206-2023-000222023-11-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.00138-888서울특별시 송파구 문정동 643-1 엠스테이트서울특별시 송파구 법원로 114, 엠스테이트 A동 2층 209-M155호 (문정동)5854광진종합관리2023-11-02 10:30:34I2022-11-01 00:04:00.0건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88432300003230000-206-2023-000232023-11-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.00138-888서울특별시 송파구 문정동 642 송파 테라타워2서울특별시 송파구 송파대로 201, 송파 테라타워2 B동 208-70호 (문정동)5854광호종합관리2023-11-02 10:35:38I2022-11-01 00:04:00.0건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88532300003230000-206-2023-000242023-11-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.88138-863서울특별시 송파구 잠실동 231 삼성빌라트서울특별시 송파구 올림픽로12길 45, 2층 204호 (잠실동, 삼성빌라트)5565오성 종합 청소2023-11-15 09:43:04I2022-10-31 23:07:00.0건물위생관리업207350.525096445036.880284<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88632300003230000-206-2023-000252023-12-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.80138-826서울특별시 송파구 문정동 52-16서울특별시 송파구 송파대로22길 4-19, 3층 (문정동)5806(주)숲이로움2023-12-08 16:50:53I2022-11-01 23:00:00.0건물위생관리업210811.101603442722.675736<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88732300003230000-206-2023-000262023-12-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00138-801서울특별시 송파구 가락동 35-10서울특별시 송파구 양재대로66길 44, 5층 502호 (가락동)5704(주)로이스2024-02-29 14:33:47U2023-12-03 00:02:00.0건물위생관리업211021.765869444168.205405<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88832300003230000-206-2023-000272023-12-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.00138-826서울특별시 송파구 문정동 66-5서울특별시 송파구 송파대로14길 7-10, 2층 201-293호 (문정동)5807퍼펙트스쿨2023-12-13 10:40:39I2022-11-01 23:05:00.0건물위생관리업210983.587452442438.127125<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
88932300003230000-206-2024-000012024-03-18<NA>1영업/정상1영업<NA><NA><NA><NA>02 2054811589.29138-888서울특별시 송파구 문정동 651 문정역테라타워서울특별시 송파구 송파대로 167, 문정역테라타워 B동 2층 214호 (문정동)5855명문디앤씨주식회사2024-03-18 14:05:07I2023-12-02 22:00:00.0건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89032300003230000-206-2024-000022024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1208.88138-888서울특별시 송파구 문정동 641-3 소노타워서울특별시 송파구 법원로 135, 소노타워 8층 (문정동)5836한국이콜랩2024-04-26 10:52:18I2023-12-03 22:08:00.0건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89132300003230000-206-2024-000032024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 2203273739.00138-829서울특별시 송파구 방이동 69-5 하나빌딩서울특별시 송파구 올림픽로32길 30, 하나빌딩 401호 (방이동)5548주상건설(주)2024-05-07 16:27:21I2023-12-05 00:09:00.0건물위생관리업209621.194561445701.201902<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>