Overview

Dataset statistics

Number of variables47
Number of observations421
Missing cells4426
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory166.6 KiB
Average record size in memory405.3 B

Variable types

Categorical20
Text6
DateTime4
Unsupported7
Numeric8
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-19301/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (95.6%)Imbalance
사용시작지하층 is highly imbalanced (59.2%)Imbalance
사용끝지하층 is highly imbalanced (64.3%)Imbalance
여성종사자수 is highly imbalanced (52.3%)Imbalance
남성종사자수 is highly imbalanced (61.9%)Imbalance
인허가취소일자 has 421 (100.0%) missing valuesMissing
폐업일자 has 131 (31.1%) missing valuesMissing
휴업시작일자 has 421 (100.0%) missing valuesMissing
휴업종료일자 has 421 (100.0%) missing valuesMissing
재개업일자 has 421 (100.0%) missing valuesMissing
전화번호 has 130 (30.9%) missing valuesMissing
도로명주소 has 120 (28.5%) missing valuesMissing
도로명우편번호 has 121 (28.7%) missing valuesMissing
건물지상층수 has 151 (35.9%) missing valuesMissing
건물지하층수 has 172 (40.9%) missing valuesMissing
사용시작지상층 has 192 (45.6%) missing valuesMissing
사용끝지상층 has 227 (53.9%) missing valuesMissing
발한실여부 has 122 (29.0%) missing valuesMissing
조건부허가신고사유 has 421 (100.0%) missing valuesMissing
조건부허가시작일자 has 421 (100.0%) missing valuesMissing
조건부허가종료일자 has 421 (100.0%) missing valuesMissing
다중이용업소여부 has 108 (25.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 11 (2.6%) zerosZeros
건물지상층수 has 178 (42.3%) zerosZeros
건물지하층수 has 207 (49.2%) zerosZeros
사용시작지상층 has 43 (10.2%) zerosZeros
사용끝지상층 has 25 (5.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:53:20.072789
Analysis finished2024-04-29 19:53:21.046919
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
3240000
421 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 421
100.0%

Length

2024-04-30T04:53:21.119015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:21.200766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 421
100.0%

관리번호
Text

UNIQUE 

Distinct421
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-30T04:53:21.342004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9262
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

Unique421 ?
Unique (%)100.0%

Sample

1st row3240000-206-1988-02410
2nd row3240000-206-1988-02411
3rd row3240000-206-1989-02411
4th row3240000-206-1990-02412
5th row3240000-206-1990-02413
ValueCountFrequency (%)
3240000-206-1988-02410 1
 
0.2%
3240000-206-2010-00025 1
 
0.2%
3240000-206-2014-00014 1
 
0.2%
3240000-206-2014-00013 1
 
0.2%
3240000-206-2014-00012 1
 
0.2%
3240000-206-2014-00011 1
 
0.2%
3240000-206-2014-00010 1
 
0.2%
3240000-206-2014-00009 1
 
0.2%
3240000-206-2014-00008 1
 
0.2%
3240000-206-2014-00007 1
 
0.2%
Other values (411) 411
97.6%
2024-04-30T04:53:21.622885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4052
43.7%
2 1449
 
15.6%
- 1263
 
13.6%
4 575
 
6.2%
3 532
 
5.7%
6 505
 
5.5%
1 468
 
5.1%
9 177
 
1.9%
5 91
 
1.0%
8 83
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7999
86.4%
Dash Punctuation 1263
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4052
50.7%
2 1449
 
18.1%
4 575
 
7.2%
3 532
 
6.7%
6 505
 
6.3%
1 468
 
5.9%
9 177
 
2.2%
5 91
 
1.1%
8 83
 
1.0%
7 67
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1263
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4052
43.7%
2 1449
 
15.6%
- 1263
 
13.6%
4 575
 
6.2%
3 532
 
5.7%
6 505
 
5.5%
1 468
 
5.1%
9 177
 
1.9%
5 91
 
1.0%
8 83
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4052
43.7%
2 1449
 
15.6%
- 1263
 
13.6%
4 575
 
6.2%
3 532
 
5.7%
6 505
 
5.5%
1 468
 
5.1%
9 177
 
1.9%
5 91
 
1.0%
8 83
 
0.9%

인허가일자
Date

Distinct394
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum1988-01-14 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:53:21.754267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:21.860032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
3
290 
1
131 

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 (%)
3 290
68.9%
1 131
31.1%

Length

2024-04-30T04:53:21.971442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:22.055687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 290
68.9%
1 131
31.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
폐업
290 
영업/정상
131 

Length

Max length5
Median length2
Mean length2.9334917
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 290
68.9%
영업/정상 131
31.1%

Length

2024-04-30T04:53:22.158551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:22.254848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 290
68.9%
영업/정상 131
31.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2
290 
1
131 

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 (%)
2 290
68.9%
1 131
31.1%

Length

2024-04-30T04:53:22.340044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:22.419200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 290
68.9%
1 131
31.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
폐업
290 
영업
131 

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 290
68.9%
영업 131
31.1%

Length

2024-04-30T04:53:22.509083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:22.596192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 290
68.9%
영업 131
31.1%

폐업일자
Date

MISSING 

Distinct234
Distinct (%)80.7%
Missing131
Missing (%)31.1%
Memory size3.4 KiB
Minimum1990-03-29 00:00:00
Maximum2024-02-16 00:00:00
2024-04-30T04:53:22.691011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:22.819058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

전화번호
Text

MISSING 

Distinct274
Distinct (%)94.2%
Missing130
Missing (%)30.9%
Memory size3.4 KiB
2024-04-30T04:53:23.082786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.965636
Min length2

Characters and Unicode

Total characters3191
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

Unique261 ?
Unique (%)89.7%

Sample

1st row02 0 000
2nd row02 5719590
3rd row02 4722963
4th row02 4784055
5th row02 4854611
ValueCountFrequency (%)
02 242
36.4%
070 16
 
2.4%
477 7
 
1.1%
481 7
 
1.1%
471 6
 
0.9%
478 6
 
0.9%
031 5
 
0.8%
474 5
 
0.8%
482 4
 
0.6%
427 4
 
0.6%
Other values (316) 363
54.6%
2024-04-30T04:53:23.489100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 537
16.8%
522
16.4%
2 490
15.4%
4 379
11.9%
7 275
8.6%
8 207
 
6.5%
1 201
 
6.3%
3 150
 
4.7%
5 149
 
4.7%
6 145
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2669
83.6%
Space Separator 522
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 537
20.1%
2 490
18.4%
4 379
14.2%
7 275
10.3%
8 207
 
7.8%
1 201
 
7.5%
3 150
 
5.6%
5 149
 
5.6%
6 145
 
5.4%
9 136
 
5.1%
Space Separator
ValueCountFrequency (%)
522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3191
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 537
16.8%
522
16.4%
2 490
15.4%
4 379
11.9%
7 275
8.6%
8 207
 
6.5%
1 201
 
6.3%
3 150
 
4.7%
5 149
 
4.7%
6 145
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 537
16.8%
522
16.4%
2 490
15.4%
4 379
11.9%
7 275
8.6%
8 207
 
6.5%
1 201
 
6.3%
3 150
 
4.7%
5 149
 
4.7%
6 145
 
4.5%

소재지면적
Real number (ℝ)

ZEROS 

Distinct291
Distinct (%)69.3%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean70.694143
Minimum0
Maximum991.81
Zeros11
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:23.622731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.3315
Q126.4
median47.735
Q384.735
95-th percentile172.591
Maximum991.81
Range991.81
Interquartile range (IQR)58.335

Descriptive statistics

Standard deviation100.61077
Coefficient of variation (CV)1.423184
Kurtosis44.627967
Mean70.694143
Median Absolute Deviation (MAD)25.605
Skewness5.9194477
Sum29691.54
Variance10122.527
MonotonicityNot monotonic
2024-04-30T04:53:23.746910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 17
 
4.0%
30.0 13
 
3.1%
66.0 13
 
3.1%
0.0 11
 
2.6%
82.5 5
 
1.2%
3.0 4
 
1.0%
10.0 4
 
1.0%
23.1 4
 
1.0%
15.0 4
 
1.0%
24.0 4
 
1.0%
Other values (281) 341
81.0%
ValueCountFrequency (%)
0.0 11
2.6%
3.0 4
 
1.0%
3.3 3
 
0.7%
5.6 1
 
0.2%
6.82 1
 
0.2%
6.84 1
 
0.2%
8.41 1
 
0.2%
9.0 2
 
0.5%
9.9 3
 
0.7%
10.0 4
 
1.0%
ValueCountFrequency (%)
991.81 1
0.2%
941.97 1
0.2%
910.54 1
0.2%
635.87 1
0.2%
544.5 1
0.2%
509.38 1
0.2%
399.0 1
0.2%
380.17 1
0.2%
340.3 1
0.2%
263.64 1
0.2%

소재지우편번호
Text

Distinct92
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-30T04:53:23.969981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.111639
Min length6

Characters and Unicode

Total characters2573
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

Unique32 ?
Unique (%)7.6%

Sample

1st row134811
2nd row134880
3rd row134873
4th row134841
5th row134861
ValueCountFrequency (%)
134851 25
 
5.9%
134864 23
 
5.5%
134841 19
 
4.5%
134814 19
 
4.5%
134830 17
 
4.0%
134838 13
 
3.1%
134850 12
 
2.9%
134867 12
 
2.9%
134874 12
 
2.9%
134880 11
 
2.6%
Other values (82) 258
61.3%
2024-04-30T04:53:24.305040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 572
22.2%
4 562
21.8%
8 479
18.6%
3 477
18.5%
0 118
 
4.6%
6 93
 
3.6%
5 91
 
3.5%
7 69
 
2.7%
- 47
 
1.8%
2 37
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2526
98.2%
Dash Punctuation 47
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 572
22.6%
4 562
22.2%
8 479
19.0%
3 477
18.9%
0 118
 
4.7%
6 93
 
3.7%
5 91
 
3.6%
7 69
 
2.7%
2 37
 
1.5%
9 28
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2573
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 572
22.2%
4 562
21.8%
8 479
18.6%
3 477
18.5%
0 118
 
4.6%
6 93
 
3.6%
5 91
 
3.5%
7 69
 
2.7%
- 47
 
1.8%
2 37
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 572
22.2%
4 562
21.8%
8 479
18.6%
3 477
18.5%
0 118
 
4.6%
6 93
 
3.6%
5 91
 
3.5%
7 69
 
2.7%
- 47
 
1.8%
2 37
 
1.4%

지번주소
Text

Distinct400
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-30T04:53:24.573433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length25.432304
Min length17

Characters and Unicode

Total characters10707
Distinct characters216
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique385 ?
Unique (%)91.4%

Sample

1st row서울특별시 강동구 길동 348-3
2nd row서울특별시 강동구 길동 404-14 재성빌딩 201호
3rd row서울특별시 강동구 천호동 421-10 농협천호지점3층
4th row서울특별시 강동구 성내동 111-23
5th row서울특별시 강동구 천호동 40-45
ValueCountFrequency (%)
서울특별시 421
19.5%
강동구 421
19.5%
성내동 121
 
5.6%
천호동 103
 
4.8%
길동 76
 
3.5%
암사동 31
 
1.4%
명일동 29
 
1.3%
2층 26
 
1.2%
상일동 21
 
1.0%
1층 18
 
0.8%
Other values (604) 895
41.4%
2024-04-30T04:53:24.958305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1983
18.5%
동 886
 
8.3%
1 464
 
4.3%
강 449
 
4.2%
서 426
 
4.0%
구 425
 
4.0%
시 423
 
4.0%
울 422
 
3.9%
특 421
 
3.9%
별 421
 
3.9%
Other values (206) 4387
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5865
54.8%
Decimal Number 2432
22.7%
Space Separator 1983
 
18.5%
Dash Punctuation 379
 
3.5%
Close Punctuation 13
 
0.1%
Open Punctuation 13
 
0.1%
Uppercase Letter 13
 
0.1%
Other Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 886
15.1%
강 449
 
7.7%
서 426
 
7.3%
구 425
 
7.2%
시 423
 
7.2%
울 422
 
7.2%
특 421
 
7.2%
별 421
 
7.2%
호 278
 
4.7%
성 135
 
2.3%
Other values (180) 1579
26.9%
Decimal Number
ValueCountFrequency (%)
1 464
19.1%
4 366
15.0%
3 325
13.4%
2 314
12.9%
0 270
11.1%
5 242
10.0%
6 123
 
5.1%
9 122
 
5.0%
8 105
 
4.3%
7 101
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
R 2
15.4%
B 2
15.4%
A 2
15.4%
H 1
7.7%
T 1
7.7%
Y 1
7.7%
O 1
7.7%
C 1
7.7%
W 1
7.7%
E 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
. 2
 
22.2%
Space Separator
ValueCountFrequency (%)
1983
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 379
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5865
54.8%
Common 4829
45.1%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 886
15.1%
강 449
 
7.7%
서 426
 
7.3%
구 425
 
7.2%
시 423
 
7.2%
울 422
 
7.2%
특 421
 
7.2%
별 421
 
7.2%
호 278
 
4.7%
성 135
 
2.3%
Other values (180) 1579
26.9%
Common
ValueCountFrequency (%)
1983
41.1%
1 464
 
9.6%
- 379
 
7.8%
4 366
 
7.6%
3 325
 
6.7%
2 314
 
6.5%
0 270
 
5.6%
5 242
 
5.0%
6 123
 
2.5%
9 122
 
2.5%
Other values (6) 241
 
5.0%
Latin
ValueCountFrequency (%)
R 2
15.4%
B 2
15.4%
A 2
15.4%
H 1
7.7%
T 1
7.7%
Y 1
7.7%
O 1
7.7%
C 1
7.7%
W 1
7.7%
E 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5865
54.8%
ASCII 4842
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1983
41.0%
1 464
 
9.6%
- 379
 
7.8%
4 366
 
7.6%
3 325
 
6.7%
2 314
 
6.5%
0 270
 
5.6%
5 242
 
5.0%
6 123
 
2.5%
9 122
 
2.5%
Other values (16) 254
 
5.2%
Hangul
ValueCountFrequency (%)
동 886
15.1%
강 449
 
7.7%
서 426
 
7.3%
구 425
 
7.2%
시 423
 
7.2%
울 422
 
7.2%
특 421
 
7.2%
별 421
 
7.2%
호 278
 
4.7%
성 135
 
2.3%
Other values (180) 1579
26.9%

도로명주소
Text

MISSING 

Distinct298
Distinct (%)99.0%
Missing120
Missing (%)28.5%
Memory size3.4 KiB
2024-04-30T04:53:25.182328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length34.136213
Min length22

Characters and Unicode

Total characters10275
Distinct characters215
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)98.0%

Sample

1st row서울특별시 강동구 천호대로187길 38, 201호 (길동, 재성빌딩)
2nd row서울특별시 강동구 천중로39길 87 (천호동)
3rd row서울특별시 강동구 천호옛길 16 (성내동)
4th row서울특별시 강동구 양재대로89길 24 (성내동,2층)
5th row서울특별시 강동구 성내로8길 9 (성내동,초성빌딩 203호)
ValueCountFrequency (%)
서울특별시 301
 
15.2%
강동구 301
 
15.2%
성내동 66
 
3.3%
천호동 65
 
3.3%
길동 42
 
2.1%
1층 34
 
1.7%
3층 31
 
1.6%
2층 29
 
1.5%
양재대로 28
 
1.4%
천호대로 26
 
1.3%
Other values (551) 1061
53.5%
2024-04-30T04:53:25.536030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1683
 
16.4%
동 655
 
6.4%
1 478
 
4.7%
, 342
 
3.3%
호 330
 
3.2%
강 330
 
3.2%
구 320
 
3.1%
서 306
 
3.0%
( 306
 
3.0%
) 306
 
3.0%
Other values (205) 5219
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5679
55.3%
Decimal Number 1891
 
18.4%
Space Separator 1683
 
16.4%
Other Punctuation 344
 
3.3%
Open Punctuation 306
 
3.0%
Close Punctuation 306
 
3.0%
Dash Punctuation 48
 
0.5%
Uppercase Letter 18
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 655
 
11.5%
호 330
 
5.8%
강 330
 
5.8%
구 320
 
5.6%
서 306
 
5.4%
시 304
 
5.4%
울 302
 
5.3%
별 301
 
5.3%
특 301
 
5.3%
로 298
 
5.2%
Other values (177) 2232
39.3%
Uppercase Letter
ValueCountFrequency (%)
B 5
27.8%
R 2
 
11.1%
A 2
 
11.1%
S 1
 
5.6%
K 1
 
5.6%
O 1
 
5.6%
C 1
 
5.6%
H 1
 
5.6%
Y 1
 
5.6%
T 1
 
5.6%
Other values (2) 2
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 478
25.3%
2 263
13.9%
0 224
11.8%
3 216
11.4%
4 162
 
8.6%
5 132
 
7.0%
7 120
 
6.3%
6 106
 
5.6%
8 105
 
5.6%
9 85
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 342
99.4%
. 2
 
0.6%
Space Separator
ValueCountFrequency (%)
1683
100.0%
Open Punctuation
ValueCountFrequency (%)
( 306
100.0%
Close Punctuation
ValueCountFrequency (%)
) 306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5679
55.3%
Common 4578
44.6%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 655
 
11.5%
호 330
 
5.8%
강 330
 
5.8%
구 320
 
5.6%
서 306
 
5.4%
시 304
 
5.4%
울 302
 
5.3%
별 301
 
5.3%
특 301
 
5.3%
로 298
 
5.2%
Other values (177) 2232
39.3%
Common
ValueCountFrequency (%)
1683
36.8%
1 478
 
10.4%
, 342
 
7.5%
( 306
 
6.7%
) 306
 
6.7%
2 263
 
5.7%
0 224
 
4.9%
3 216
 
4.7%
4 162
 
3.5%
5 132
 
2.9%
Other values (6) 466
 
10.2%
Latin
ValueCountFrequency (%)
B 5
27.8%
R 2
 
11.1%
A 2
 
11.1%
S 1
 
5.6%
K 1
 
5.6%
O 1
 
5.6%
C 1
 
5.6%
H 1
 
5.6%
Y 1
 
5.6%
T 1
 
5.6%
Other values (2) 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5679
55.3%
ASCII 4596
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1683
36.6%
1 478
 
10.4%
, 342
 
7.4%
( 306
 
6.7%
) 306
 
6.7%
2 263
 
5.7%
0 224
 
4.9%
3 216
 
4.7%
4 162
 
3.5%
5 132
 
2.9%
Other values (18) 484
 
10.5%
Hangul
ValueCountFrequency (%)
동 655
 
11.5%
호 330
 
5.8%
강 330
 
5.8%
구 320
 
5.6%
서 306
 
5.4%
시 304
 
5.4%
울 302
 
5.3%
별 301
 
5.3%
특 301
 
5.3%
로 298
 
5.2%
Other values (177) 2232
39.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)36.0%
Missing121
Missing (%)28.7%
Infinite0
Infinite (%)0.0%
Mean5323.3533
Minimum5202
Maximum5408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:25.675221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5202
5-th percentile5226
Q15282.75
median5336
Q35374
95-th percentile5399
Maximum5408
Range206
Interquartile range (IQR)91.25

Descriptive statistics

Standard deviation57.116924
Coefficient of variation (CV)0.010729501
Kurtosis-1.0273609
Mean5323.3533
Median Absolute Deviation (MAD)46
Skewness-0.36126773
Sum1597006
Variance3262.343
MonotonicityNot monotonic
2024-04-30T04:53:25.794249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5399 10
 
2.4%
5295 9
 
2.1%
5353 9
 
2.1%
5340 8
 
1.9%
5248 7
 
1.7%
5398 7
 
1.7%
5283 7
 
1.7%
5211 7
 
1.7%
5336 7
 
1.7%
5355 7
 
1.7%
Other values (98) 222
52.7%
(Missing) 121
28.7%
ValueCountFrequency (%)
5202 1
 
0.2%
5203 1
 
0.2%
5211 7
1.7%
5221 1
 
0.2%
5222 4
1.0%
5226 2
 
0.5%
5227 5
1.2%
5232 1
 
0.2%
5236 1
 
0.2%
5237 1
 
0.2%
ValueCountFrequency (%)
5408 1
 
0.2%
5404 3
 
0.7%
5403 4
 
1.0%
5402 2
 
0.5%
5400 3
 
0.7%
5399 10
2.4%
5398 7
1.7%
5396 6
1.4%
5394 1
 
0.2%
5393 1
 
0.2%

사업장명
Text

Distinct413
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-30T04:53:26.006397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length14
Mean length7.8574822
Min length2

Characters and Unicode

Total characters3308
Distinct characters339
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique405 ?
Unique (%)96.2%

Sample

1st row식원기업
2nd row(주)오뚜기토탈시스템
3rd row사단법인 축협동우회
4th row향경종합방역공사
5th row식원기업주식회사
ValueCountFrequency (%)
주식회사 54
 
11.0%
사회적협동조합 3
 
0.6%
남원산업 3
 
0.6%
사회복지법인 3
 
0.6%
주)미래프로세스 2
 
0.4%
주 2
 
0.4%
천호종합관리 2
 
0.4%
늘푸른교역 2
 
0.4%
주)내외공영 2
 
0.4%
성원 2
 
0.4%
Other values (415) 418
84.8%
2024-04-30T04:53:26.343741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 295
 
8.9%
) 235
 
7.1%
( 230
 
7.0%
스 123
 
3.7%
사 81
 
2.4%
회 77
 
2.3%
에 72
 
2.2%
72
 
2.2%
식 65
 
2.0%
이 64
 
1.9%
Other values (329) 1994
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2724
82.3%
Close Punctuation 235
 
7.1%
Open Punctuation 230
 
7.0%
Space Separator 72
 
2.2%
Uppercase Letter 28
 
0.8%
Other Punctuation 8
 
0.2%
Decimal Number 6
 
0.2%
Lowercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 295
 
10.8%
스 123
 
4.5%
사 81
 
3.0%
회 77
 
2.8%
에 72
 
2.6%
식 65
 
2.4%
이 64
 
2.3%
리 59
 
2.2%
비 45
 
1.7%
합 41
 
1.5%
Other values (303) 1802
66.2%
Uppercase Letter
ValueCountFrequency (%)
S 5
17.9%
O 3
10.7%
E 3
10.7%
D 3
10.7%
C 3
10.7%
H 3
10.7%
G 2
 
7.1%
K 2
 
7.1%
T 1
 
3.6%
L 1
 
3.6%
Other values (2) 2
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
b 1
20.0%
i 1
20.0%
o 1
20.0%
z 1
20.0%
a 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
& 2
 
25.0%
? 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
1 2
33.3%
2 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 230
100.0%
Space Separator
ValueCountFrequency (%)
72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2724
82.3%
Common 551
 
16.7%
Latin 33
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 295
 
10.8%
스 123
 
4.5%
사 81
 
3.0%
회 77
 
2.8%
에 72
 
2.6%
식 65
 
2.4%
이 64
 
2.3%
리 59
 
2.2%
비 45
 
1.7%
합 41
 
1.5%
Other values (303) 1802
66.2%
Latin
ValueCountFrequency (%)
S 5
15.2%
O 3
9.1%
E 3
9.1%
D 3
9.1%
C 3
9.1%
H 3
9.1%
G 2
 
6.1%
K 2
 
6.1%
b 1
 
3.0%
i 1
 
3.0%
Other values (7) 7
21.2%
Common
ValueCountFrequency (%)
) 235
42.6%
( 230
41.7%
72
 
13.1%
. 5
 
0.9%
0 3
 
0.5%
1 2
 
0.4%
& 2
 
0.4%
? 1
 
0.2%
2 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2724
82.3%
ASCII 584
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 295
 
10.8%
스 123
 
4.5%
사 81
 
3.0%
회 77
 
2.8%
에 72
 
2.6%
식 65
 
2.4%
이 64
 
2.3%
리 59
 
2.2%
비 45
 
1.7%
합 41
 
1.5%
Other values (303) 1802
66.2%
ASCII
ValueCountFrequency (%)
) 235
40.2%
( 230
39.4%
72
 
12.3%
. 5
 
0.9%
S 5
 
0.9%
O 3
 
0.5%
E 3
 
0.5%
D 3
 
0.5%
0 3
 
0.5%
C 3
 
0.5%
Other values (16) 22
 
3.8%

최종수정일자
Date

Distinct386
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2002-06-06 00:00:00
Maximum2024-04-24 14:24:41
2024-04-30T04:53:26.462437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:26.782378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
I
262 
U
159 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 262
62.2%
U 159
37.8%

Length

2024-04-30T04:53:26.901523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:26.983178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 262
62.2%
u 159
37.8%

데이터갱신일자
Date

Distinct152
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-04-30T04:53:27.075707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:53:27.190406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
건물위생관리업
419 
건물위생관리업 기타
 
2

Length

Max length10
Median length7
Mean length7.0142518
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 419
99.5%
건물위생관리업 기타 2
 
0.5%

Length

2024-04-30T04:53:27.313542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:27.395853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 421
99.5%
기타 2
 
0.5%

좌표정보(X)
Real number (ℝ)

Distinct307
Distinct (%)73.3%
Missing2
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean212056.9
Minimum210558.1
Maximum215474.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:27.489040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210558.1
5-th percentile210726.81
Q1211232.4
median211799.89
Q3212555.28
95-th percentile215027.55
Maximum215474.51
Range4916.4179
Interquartile range (IQR)1322.8751

Descriptive statistics

Standard deviation1171.2789
Coefficient of variation (CV)0.0055234181
Kurtosis1.3431619
Mean212056.9
Median Absolute Deviation (MAD)660.05827
Skewness1.3130451
Sum88851842
Variance1371894.3
MonotonicityNot monotonic
2024-04-30T04:53:27.611744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211542.314116941 12
 
2.9%
212706.795162194 7
 
1.7%
211458.648093395 6
 
1.4%
210931.005191598 6
 
1.4%
210839.281153832 5
 
1.2%
212251.603548884 5
 
1.2%
211279.030241561 4
 
1.0%
213070.495037105 4
 
1.0%
215212.625424847 4
 
1.0%
211367.91579687 4
 
1.0%
Other values (297) 362
86.0%
ValueCountFrequency (%)
210558.095600946 1
0.2%
210566.875626134 1
0.2%
210567.072509045 1
0.2%
210587.488645319 1
0.2%
210607.529826692 1
0.2%
210613.801723814 1
0.2%
210622.73929089 1
0.2%
210626.58631048 2
0.5%
210630.209443525 2
0.5%
210664.882366319 1
0.2%
ValueCountFrequency (%)
215474.513482379 1
 
0.2%
215339.644961398 1
 
0.2%
215327.573332527 1
 
0.2%
215313.230134197 1
 
0.2%
215289.815449411 2
0.5%
215254.0 3
0.7%
215231.341426541 1
 
0.2%
215212.625424847 4
1.0%
215201.290186508 1
 
0.2%
215189.45156682 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct307
Distinct (%)73.3%
Missing2
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean448698.42
Minimum446824.91
Maximum451689.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:27.745113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446824.91
5-th percentile447293.16
Q1447976.82
median448505.09
Q3449429.71
95-th percentile450752.14
Maximum451689.51
Range4864.6024
Interquartile range (IQR)1452.8906

Descriptive statistics

Standard deviation1037.2004
Coefficient of variation (CV)0.0023115757
Kurtosis-0.14654405
Mean448698.42
Median Absolute Deviation (MAD)783.94457
Skewness0.58786721
Sum1.8800464 × 108
Variance1075784.6
MonotonicityNot monotonic
2024-04-30T04:53:27.866636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448273.114107211 12
 
2.9%
449694.965400189 7
 
1.7%
450316.255472825 6
 
1.4%
448917.62261412 6
 
1.4%
447458.387605645 5
 
1.2%
448345.727351302 5
 
1.2%
448548.819716671 4
 
1.0%
448552.7479101 4
 
1.0%
449468.899712593 4
 
1.0%
447225.778131525 4
 
1.0%
Other values (297) 362
86.0%
ValueCountFrequency (%)
446824.910976521 1
0.2%
446921.590368548 1
0.2%
446926.627141526 1
0.2%
447021.970958815 1
0.2%
447051.00353677 1
0.2%
447120.009771995 1
0.2%
447125.42728615 1
0.2%
447191.452672555 2
0.5%
447195.676766748 1
0.2%
447205.139674886 1
0.2%
ValueCountFrequency (%)
451689.513375361 1
 
0.2%
451573.12221291 1
 
0.2%
451519.404046335 2
0.5%
451507.371460994 1
 
0.2%
451469.210879017 1
 
0.2%
451457.0 3
0.7%
451115.733950248 1
 
0.2%
450984.376735084 1
 
0.2%
450963.783553916 1
 
0.2%
450919.0652351 2
0.5%

위생업태명
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
건물위생관리업
312 
<NA>
108 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.2375297
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 312
74.1%
<NA> 108
 
25.7%
건물위생관리업 기타 1
 
0.2%

Length

2024-04-30T04:53:28.004634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:28.100187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 313
74.2%
na 108
 
25.6%
기타 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)4.4%
Missing151
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean1.2962963
Minimum0
Maximum18
Zeros178
Zeros (%)42.3%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:28.178363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.75
95-th percentile5
Maximum18
Range18
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation2.4130194
Coefficient of variation (CV)1.8614721
Kurtosis14.729766
Mean1.2962963
Median Absolute Deviation (MAD)0
Skewness3.1525232
Sum350
Variance5.8226628
MonotonicityNot monotonic
2024-04-30T04:53:28.269241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 178
42.3%
3 28
 
6.7%
4 18
 
4.3%
2 14
 
3.3%
5 13
 
3.1%
1 10
 
2.4%
6 4
 
1.0%
18 1
 
0.2%
16 1
 
0.2%
12 1
 
0.2%
Other values (2) 2
 
0.5%
(Missing) 151
35.9%
ValueCountFrequency (%)
0 178
42.3%
1 10
 
2.4%
2 14
 
3.3%
3 28
 
6.7%
4 18
 
4.3%
5 13
 
3.1%
6 4
 
1.0%
10 1
 
0.2%
11 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
18 1
 
0.2%
16 1
 
0.2%
12 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
6 4
 
1.0%
5 13
3.1%
4 18
4.3%
3 28
6.7%
2 14
3.3%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.4%
Missing172
Missing (%)40.9%
Infinite0
Infinite (%)0.0%
Mean0.24497992
Minimum0
Maximum5
Zeros207
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:28.357581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.66616447
Coefficient of variation (CV)2.7192615
Kurtosis18.85617
Mean0.24497992
Median Absolute Deviation (MAD)0
Skewness3.8837801
Sum61
Variance0.4437751
MonotonicityNot monotonic
2024-04-30T04:53:28.447413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 207
49.2%
1 31
 
7.4%
2 7
 
1.7%
4 2
 
0.5%
5 1
 
0.2%
3 1
 
0.2%
(Missing) 172
40.9%
ValueCountFrequency (%)
0 207
49.2%
1 31
 
7.4%
2 7
 
1.7%
3 1
 
0.2%
4 2
 
0.5%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 2
 
0.5%
3 1
 
0.2%
2 7
 
1.7%
1 31
 
7.4%
0 207
49.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)6.6%
Missing192
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean2.5240175
Minimum0
Maximum15
Zeros43
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:28.531638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile7.6
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4576393
Coefficient of variation (CV)0.97370137
Kurtosis5.4773206
Mean2.5240175
Median Absolute Deviation (MAD)1
Skewness1.9899688
Sum578
Variance6.0399908
MonotonicityNot monotonic
2024-04-30T04:53:28.628649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 60
 
14.3%
0 43
 
10.2%
3 39
 
9.3%
1 37
 
8.8%
4 19
 
4.5%
5 13
 
3.1%
9 4
 
1.0%
7 4
 
1.0%
6 2
 
0.5%
10 2
 
0.5%
Other values (5) 6
 
1.4%
(Missing) 192
45.6%
ValueCountFrequency (%)
0 43
10.2%
1 37
8.8%
2 60
14.3%
3 39
9.3%
4 19
 
4.5%
5 13
 
3.1%
6 2
 
0.5%
7 4
 
1.0%
8 2
 
0.5%
9 4
 
1.0%
ValueCountFrequency (%)
15 1
 
0.2%
13 1
 
0.2%
12 1
 
0.2%
11 1
 
0.2%
10 2
 
0.5%
9 4
 
1.0%
8 2
 
0.5%
7 4
 
1.0%
6 2
 
0.5%
5 13
3.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)7.7%
Missing227
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean2.7268041
Minimum0
Maximum15
Zeros25
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-04-30T04:53:28.741004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile8.35
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4752878
Coefficient of variation (CV)0.90776151
Kurtosis5.7468063
Mean2.7268041
Median Absolute Deviation (MAD)1
Skewness2.0719145
Sum529
Variance6.1270498
MonotonicityNot monotonic
2024-04-30T04:53:28.847702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 58
 
13.8%
3 35
 
8.3%
1 31
 
7.4%
0 25
 
5.9%
4 16
 
3.8%
5 13
 
3.1%
9 4
 
1.0%
7 3
 
0.7%
6 2
 
0.5%
10 2
 
0.5%
Other values (5) 5
 
1.2%
(Missing) 227
53.9%
ValueCountFrequency (%)
0 25
5.9%
1 31
7.4%
2 58
13.8%
3 35
8.3%
4 16
 
3.8%
5 13
 
3.1%
6 2
 
0.5%
7 3
 
0.7%
8 1
 
0.2%
9 4
 
1.0%
ValueCountFrequency (%)
15 1
 
0.2%
13 1
 
0.2%
12 1
 
0.2%
11 1
 
0.2%
10 2
 
0.5%
9 4
 
1.0%
8 1
 
0.2%
7 3
 
0.7%
6 2
 
0.5%
5 13
3.1%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
331 
0
68 
1
 
20
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.3586698
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
78.6%
0 68
 
16.2%
1 20
 
4.8%
5 1
 
0.2%
2 1
 
0.2%

Length

2024-04-30T04:53:28.953948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:29.053396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
78.6%
0 68
 
16.2%
1 20
 
4.8%
5 1
 
0.2%
2 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
351 
0
47 
1
 
21
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.5011876
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
83.4%
0 47
 
11.2%
1 21
 
5.0%
5 1
 
0.2%
2 1
 
0.2%

Length

2024-04-30T04:53:29.157820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:29.260702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
83.4%
0 47
 
11.2%
1 21
 
5.0%
5 1
 
0.2%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
0
224 
<NA>
197 

Length

Max length4
Median length1
Mean length2.4038005
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 224
53.2%
<NA> 197
46.8%

Length

2024-04-30T04:53:29.357124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:29.446630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 224
53.2%
na 197
46.8%

양실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
0
224 
<NA>
197 

Length

Max length4
Median length1
Mean length2.4038005
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 224
53.2%
<NA> 197
46.8%

Length

2024-04-30T04:53:29.530575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:29.612937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 224
53.2%
na 197
46.8%

욕실수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
0
224 
<NA>
197 

Length

Max length4
Median length1
Mean length2.4038005
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 224
53.2%
<NA> 197
46.8%

Length

2024-04-30T04:53:29.717068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:29.803840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 224
53.2%
na 197
46.8%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing122
Missing (%)29.0%
Memory size974.0 B
False
299 
(Missing)
122 
ValueCountFrequency (%)
False 299
71.0%
(Missing) 122
29.0%
2024-04-30T04:53:29.876783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
0
224 
<NA>
196 
2
 
1

Length

Max length4
Median length1
Mean length2.3966746
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 224
53.2%
<NA> 196
46.6%
2 1
 
0.2%

Length

2024-04-30T04:53:29.965420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:30.066288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 224
53.2%
na 196
46.6%
2 1
 
0.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing421
Missing (%)100.0%
Memory size3.8 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
254 
임대
159 
자가
 
8

Length

Max length4
Median length4
Mean length3.2066508
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 254
60.3%
임대 159
37.8%
자가 8
 
1.9%

Length

2024-04-30T04:53:30.165701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:30.267400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 254
60.3%
임대 159
37.8%
자가 8
 
1.9%

세탁기수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
218 
0
203 

Length

Max length4
Median length4
Mean length2.5534442
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 218
51.8%
0 203
48.2%

Length

2024-04-30T04:53:30.362615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:30.447008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 218
51.8%
0 203
48.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
339 
0
79 
1
 
3

Length

Max length4
Median length4
Mean length3.415677
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> 339
80.5%
0 79
 
18.8%
1 3
 
0.7%

Length

2024-04-30T04:53:30.540524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:30.634167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 339
80.5%
0 79
 
18.8%
1 3
 
0.7%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
339 
0
79 
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.415677
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 339
80.5%
0 79
 
18.8%
1 2
 
0.5%
3 1
 
0.2%

Length

2024-04-30T04:53:30.730714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:30.822663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 339
80.5%
0 79
 
18.8%
1 2
 
0.5%
3 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
240 
0
181 

Length

Max length4
Median length4
Mean length2.7102138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
57.0%
0 181
43.0%

Length

2024-04-30T04:53:30.921714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:31.005418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
57.0%
0 181
43.0%

침대수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
249 
0
172 

Length

Max length4
Median length4
Mean length2.7743468
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
59.1%
0 172
40.9%

Length

2024-04-30T04:53:31.112589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:53:31.194981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
59.1%
0 172
40.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing108
Missing (%)25.7%
Memory size974.0 B
False
313 
(Missing)
108 
ValueCountFrequency (%)
False 313
74.3%
(Missing) 108
 
25.7%
2024-04-30T04:53:31.265370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032400003240000-206-1988-0241019880927<NA>3폐업2폐업19900329<NA><NA><NA>02 0 00063.92134811서울특별시 강동구 길동 348-3<NA><NA>식원기업2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업212455.130492448730.679231건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132400003240000-206-1988-0241119880114<NA>3폐업2폐업20200603<NA><NA><NA>02 571959066.0134880서울특별시 강동구 길동 404-14 재성빌딩 201호서울특별시 강동구 천호대로187길 38, 201호 (길동, 재성빌딩)5350(주)오뚜기토탈시스템2020-06-03 16:43:53U2020-06-05 02:40:00.0건물위생관리업212557.771715448197.912561건물위생관리업000000000N0<NA><NA><NA><NA>0<NA><NA>00N
232400003240000-206-1989-0241119890908<NA>3폐업2폐업20101229<NA><NA><NA>02 472296387.68134873서울특별시 강동구 천호동 421-10 농협천호지점3층<NA><NA>사단법인 축협동우회2010-12-16 16:01:55I2018-08-31 23:59:59.0건물위생관리업211190.44264448657.80622건물위생관리업3<NA>33<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
332400003240000-206-1990-0241219900104<NA>3폐업2폐업19931217<NA><NA><NA>02 478405567.76134841서울특별시 강동구 성내동 111-23<NA><NA>향경종합방역공사2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업210728.46502448001.873197건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432400003240000-206-1990-0241319900531<NA>3폐업2폐업20150619<NA><NA><NA>02 485461192.4134861서울특별시 강동구 천호동 40-45서울특별시 강동구 천중로39길 87 (천호동)5313식원기업주식회사2011-12-07 12:00:29I2018-08-31 23:59:59.0건물위생관리업212326.363888449196.906575건물위생관리업303300000N0<NA><NA><NA>임대0<NA><NA>00N
532400003240000-206-1990-0241419901213<NA>3폐업2폐업19960311<NA><NA><NA>02 471012573.15134812서울특별시 강동구 길동 352-9<NA><NA>(주)금익종합개발2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업212798.998651448713.988817건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632400003240000-206-1991-0241519910129<NA>3폐업2폐업19931217<NA><NA><NA>02 487631189.54134890서울특별시 강동구 성내동 427-19<NA><NA>(주)내외공영2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업211789.003857447191.452673건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
732400003240000-206-1992-0241619920728<NA>3폐업2폐업19931116<NA><NA><NA>02 485089149.0134848서울특별시 강동구 성내동 455-8<NA><NA>쌍마무역(주)2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업210626.58631447414.913781건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
832400003240000-206-1992-0241719920925<NA>3폐업2폐업19921123<NA><NA><NA>02 064.73134850서울특별시 강동구 성내동 542-3<NA><NA>지홍개발(주)2002-06-06 00:00:00I2018-08-31 23:59:59.0건물위생관리업211233.066679447308.975224건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
932400003240000-206-1992-0241819921204<NA>3폐업2폐업20141229<NA><NA><NA>02 489234066.0134851서울특별시 강동구 성내동 320-9서울특별시 강동구 천호옛길 16 (성내동)5392동양환경엔지니어링(주)2004-04-16 00:00:00I2018-08-31 23:59:59.0건물위생관리업210677.372119447641.132017건물위생관리업3<NA>22<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
41132400003240000-206-2023-000082023-10-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.0134-841서울특별시 강동구 성내동 163-16 경남빌딩서울특별시 강동구 천호대로 1082, 경남빌딩 304-4호 (성내동)5380주식회사 케이건물관리2024-04-22 16:08:36U2023-12-03 22:04:00.0건물위생관리업211573.770265448168.954893<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41232400003240000-206-2023-000092023-10-20<NA>1영업/정상1영업<NA><NA><NA><NA>031 48185623.0134-855서울특별시 강동구 암사동 441-10 정산아파트서울특별시 강동구 고덕로 47, 3층 303-16호 (암사동, 정산아파트)5238트레비종합관리 주식회사2024-03-15 14:17:16U2023-12-02 23:07:00.0건물위생관리업211458.648093450316.255473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41332400003240000-206-2023-000102023-11-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.0134-809서울특별시 강동구 길동 106-6 그린하우스서울특별시 강동구 명일로 228, 그린하우스 301호 (길동)5345(주)바이제로텍2023-11-23 11:12:21I2022-10-31 22:05:00.0건물위생관리업212889.562218448529.733176<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41432400003240000-206-2023-000112023-12-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.0134-868서울특별시 강동구 천호동 335-14 아성뜨란채서울특별시 강동구 구천면로17길 43, 1층 101호 (천호동, 아성뜨란채)5245나경에듀12023-12-12 09:18:42I2022-11-01 23:04:00.0건물위생관리업210901.165321449047.250267<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41532400003240000-206-2024-000012024-01-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>47.0134-850서울특별시 강동구 성내동 533-1 호성빌딩서울특별시 강동구 성내로3가길 49, 호성빌딩 1층 (성내동)5393(주)가꾸다2024-01-08 13:12:58I2023-11-30 23:00:00.0건물위생관리업211009.888662447534.760999<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41632400003240000-206-2024-000022024-01-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.0134-855서울특별시 강동구 암사동 441-10 정산아파트서울특별시 강동구 고덕로 47, 3층 301-71호 (암사동, 정산아파트)5238프로퍼솔루션2024-01-11 10:57:41I2023-11-30 23:03:00.0건물위생관리업211458.648093450316.255473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41732400003240000-206-2024-000032024-02-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.12134-830서울특별시 강동구 명일동 306-7 대은상가서울특별시 강동구 양재대로 1657-11, 대은상가 1층 7호 (명일동)5257(주) 본케어시스템2024-02-14 13:43:37I2023-12-01 23:06:00.0건물위생관리업212603.194993450135.008703<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41832400003240000-206-2024-000042024-02-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 442 774933.62134-864서울특별시 강동구 천호동 450-40서울특별시 강동구 천호대로163길 21, 302호 (천호동)5336푸른솔 주식회사2024-02-16 11:04:26I2023-12-01 23:08:00.0건물위생관리업211506.286057448387.518588<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41932400003240000-206-2024-000052024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0134-855서울특별시 강동구 암사동 441-10 정산아파트서울특별시 강동구 고덕로 47, 3층 303-73호 (암사동, 정산아파트)5238스마일토탈케어2024-03-05 13:29:34I2023-12-03 00:07:00.0건물위생관리업211458.648093450316.255473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42032400003240000-206-2024-000062024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA>02 566 019130.0134-100서울특별시 강동구 강일동 676 강일프라자서울특별시 강동구 아리수로93길 33-9, 강일프라자 902호 (강일동)5211엘림종합건설(주)2024-04-24 14:24:41I2023-12-03 22:06:00.0건물위생관리업215231.341427451507.371461<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>