Overview

Dataset statistics

Number of variables47
Number of observations176
Missing cells1645
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory69.7 KiB
Average record size in memory405.8 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-19286/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
사용끝지하층 is highly imbalanced (51.9%)Imbalance
여성종사자수 is highly imbalanced (54.5%)Imbalance
남성종사자수 is highly imbalanced (62.2%)Imbalance
인허가취소일자 has 176 (100.0%) missing valuesMissing
폐업일자 has 48 (27.3%) missing valuesMissing
휴업시작일자 has 176 (100.0%) missing valuesMissing
휴업종료일자 has 176 (100.0%) missing valuesMissing
재개업일자 has 176 (100.0%) missing valuesMissing
전화번호 has 52 (29.5%) missing valuesMissing
도로명주소 has 47 (26.7%) missing valuesMissing
도로명우편번호 has 47 (26.7%) missing valuesMissing
건물지상층수 has 53 (30.1%) missing valuesMissing
사용시작지상층 has 46 (26.1%) missing valuesMissing
사용끝지상층 has 69 (39.2%) missing valuesMissing
발한실여부 has 29 (16.5%) missing valuesMissing
조건부허가신고사유 has 176 (100.0%) missing valuesMissing
조건부허가시작일자 has 176 (100.0%) missing valuesMissing
조건부허가종료일자 has 176 (100.0%) missing valuesMissing
다중이용업소여부 has 22 (12.5%) 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
소재지면적 has 4 (2.3%) zerosZeros
건물지상층수 has 100 (56.8%) zerosZeros
사용시작지상층 has 11 (6.2%) zerosZeros
사용끝지상층 has 6 (3.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:49:01.840050
Analysis finished2024-05-11 05:49:02.824543
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3090000
176 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 176
100.0%

Length

2024-05-11T14:49:02.918754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:03.072823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 176
100.0%

관리번호
Text

UNIQUE 

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T14:49:03.441018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3872
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

Unique176 ?
Unique (%)100.0%

Sample

1st row3090000-206-1993-01461
2nd row3090000-206-1994-01462
3rd row3090000-206-1994-01463
4th row3090000-206-1994-01464
5th row3090000-206-1994-01465
ValueCountFrequency (%)
3090000-206-1993-01461 1
 
0.6%
3090000-206-1994-01462 1
 
0.6%
3090000-206-2013-00007 1
 
0.6%
3090000-206-2012-00006 1
 
0.6%
3090000-206-2012-00007 1
 
0.6%
3090000-206-2013-00001 1
 
0.6%
3090000-206-2013-00002 1
 
0.6%
3090000-206-2013-00003 1
 
0.6%
3090000-206-2013-00004 1
 
0.6%
3090000-206-2013-00005 1
 
0.6%
Other values (166) 166
94.3%
2024-05-11T14:49:04.095614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1926
49.7%
- 528
 
13.6%
2 387
 
10.0%
9 232
 
6.0%
6 225
 
5.8%
3 222
 
5.7%
1 184
 
4.8%
4 58
 
1.5%
5 40
 
1.0%
8 36
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3344
86.4%
Dash Punctuation 528
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1926
57.6%
2 387
 
11.6%
9 232
 
6.9%
6 225
 
6.7%
3 222
 
6.6%
1 184
 
5.5%
4 58
 
1.7%
5 40
 
1.2%
8 36
 
1.1%
7 34
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 528
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1926
49.7%
- 528
 
13.6%
2 387
 
10.0%
9 232
 
6.0%
6 225
 
5.8%
3 222
 
5.7%
1 184
 
4.8%
4 58
 
1.5%
5 40
 
1.0%
8 36
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1926
49.7%
- 528
 
13.6%
2 387
 
10.0%
9 232
 
6.0%
6 225
 
5.8%
3 222
 
5.7%
1 184
 
4.8%
4 58
 
1.5%
5 40
 
1.0%
8 36
 
0.9%

인허가일자
Date

Distinct166
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1993-11-06 00:00:00
Maximum2023-12-11 00:00:00
2024-05-11T14:49:04.363860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:04.634206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
128 
1
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 128
72.7%
1 48
 
27.3%

Length

2024-05-11T14:49:04.847808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:05.040754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 128
72.7%
1 48
 
27.3%

영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
128 
영업/정상
48 

Length

Max length5
Median length2
Mean length2.8181818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 128
72.7%
영업/정상 48
 
27.3%

Length

2024-05-11T14:49:05.270417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:05.483497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 128
72.7%
영업/정상 48
 
27.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2
128 
1
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 128
72.7%
1 48
 
27.3%

Length

2024-05-11T14:49:05.698386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:05.919800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 128
72.7%
1 48
 
27.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
128 
영업
48 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 128
72.7%
영업 48
 
27.3%

Length

2024-05-11T14:49:06.103848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:06.237104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 128
72.7%
영업 48
 
27.3%

폐업일자
Date

MISSING 

Distinct114
Distinct (%)89.1%
Missing48
Missing (%)27.3%
Memory size1.5 KiB
Minimum1996-09-20 00:00:00
Maximum2024-01-03 00:00:00
2024-05-11T14:49:06.412483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:06.610889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct117
Distinct (%)94.4%
Missing52
Missing (%)29.5%
Memory size1.5 KiB
2024-05-11T14:49:07.008848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.08871
Min length6

Characters and Unicode

Total characters1251
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

Unique111 ?
Unique (%)89.5%

Sample

1st row02 9557870
2nd row02 9913873
3rd row02 9902967
4th row02 9993141
5th row02 9991341
ValueCountFrequency (%)
02 83
34.2%
993 4
 
1.6%
938 3
 
1.2%
9902967 3
 
1.2%
031 3
 
1.2%
903 3
 
1.2%
956 3
 
1.2%
955 3
 
1.2%
976 2
 
0.8%
9998100 2
 
0.8%
Other values (130) 134
55.1%
2024-05-11T14:49:07.695618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 218
17.4%
9 196
15.7%
2 163
13.0%
158
12.6%
3 93
7.4%
7 90
7.2%
1 77
 
6.2%
5 77
 
6.2%
4 67
 
5.4%
8 58
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1093
87.4%
Space Separator 158
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218
19.9%
9 196
17.9%
2 163
14.9%
3 93
8.5%
7 90
8.2%
1 77
 
7.0%
5 77
 
7.0%
4 67
 
6.1%
8 58
 
5.3%
6 54
 
4.9%
Space Separator
ValueCountFrequency (%)
158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 218
17.4%
9 196
15.7%
2 163
13.0%
158
12.6%
3 93
7.4%
7 90
7.2%
1 77
 
6.2%
5 77
 
6.2%
4 67
 
5.4%
8 58
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 218
17.4%
9 196
15.7%
2 163
13.0%
158
12.6%
3 93
7.4%
7 90
7.2%
1 77
 
6.2%
5 77
 
6.2%
4 67
 
5.4%
8 58
 
4.6%

소재지면적
Real number (ℝ)

ZEROS 

Distinct136
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.031648
Minimum0
Maximum367.61
Zeros4
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:07.917399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q122.84
median37.5
Q367.57
95-th percentile133.5
Maximum367.61
Range367.61
Interquartile range (IQR)44.73

Descriptive statistics

Standard deviation46.265112
Coefficient of variation (CV)0.88917252
Kurtosis13.26038
Mean52.031648
Median Absolute Deviation (MAD)21.195
Skewness2.7605114
Sum9157.57
Variance2140.4605
MonotonicityNot monotonic
2024-05-11T14:49:08.182386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 7
 
4.0%
33.0 5
 
2.8%
10.0 5
 
2.8%
23.0 4
 
2.3%
0.0 4
 
2.3%
65.0 3
 
1.7%
25.53 3
 
1.7%
14.0 3
 
1.7%
56.0 2
 
1.1%
25.0 2
 
1.1%
Other values (126) 138
78.4%
ValueCountFrequency (%)
0.0 4
2.3%
3.3 1
 
0.6%
4.65 1
 
0.6%
8.1 1
 
0.6%
9.9 1
 
0.6%
10.0 5
2.8%
10.68 1
 
0.6%
11.0 1
 
0.6%
11.21 1
 
0.6%
12.0 1
 
0.6%
ValueCountFrequency (%)
367.61 1
0.6%
249.16 1
0.6%
178.05 1
0.6%
168.0 1
0.6%
165.0 1
0.6%
149.04 1
0.6%
144.57 1
0.6%
141.75 1
0.6%
138.0 1
0.6%
132.0 1
0.6%

소재지우편번호
Text

Distinct74
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T14:49:08.580233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0340909
Min length6

Characters and Unicode

Total characters1062
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

Unique34 ?
Unique (%)19.3%

Sample

1st row132819
2nd row132841
3rd row132898
4th row132819
5th row132908
ValueCountFrequency (%)
132898 17
 
9.7%
132800 9
 
5.1%
132819 6
 
3.4%
132822 6
 
3.4%
132821 6
 
3.4%
132850 6
 
3.4%
132924 6
 
3.4%
132893 4
 
2.3%
132851 4
 
2.3%
132854 4
 
2.3%
Other values (64) 108
61.4%
2024-05-11T14:49:09.163735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 227
21.4%
1 225
21.2%
3 193
18.2%
8 161
15.2%
9 83
 
7.8%
0 59
 
5.6%
4 34
 
3.2%
5 30
 
2.8%
6 26
 
2.4%
7 18
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1056
99.4%
Dash Punctuation 6
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 227
21.5%
1 225
21.3%
3 193
18.3%
8 161
15.2%
9 83
 
7.9%
0 59
 
5.6%
4 34
 
3.2%
5 30
 
2.8%
6 26
 
2.5%
7 18
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1062
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 227
21.4%
1 225
21.2%
3 193
18.2%
8 161
15.2%
9 83
 
7.8%
0 59
 
5.6%
4 34
 
3.2%
5 30
 
2.8%
6 26
 
2.4%
7 18
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 227
21.4%
1 225
21.2%
3 193
18.2%
8 161
15.2%
9 83
 
7.8%
0 59
 
5.6%
4 34
 
3.2%
5 30
 
2.8%
6 26
 
2.4%
7 18
 
1.7%

지번주소
Text

Distinct171
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T14:49:09.659772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length26.539773
Min length17

Characters and Unicode

Total characters4671
Distinct characters133
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

Unique166 ?
Unique (%)94.3%

Sample

1st row서울특별시 도봉구 도봉동 600-19
2nd row서울특별시 도봉구 방학동 630-17
3rd row서울특별시 도봉구 창동 6-0
4th row서울특별시 도봉구 도봉동 602-31
5th row서울특별시 도봉구 창동 333-2
ValueCountFrequency (%)
서울특별시 176
19.0%
도봉구 176
19.0%
창동 59
 
6.4%
도봉동 52
 
5.6%
방학동 33
 
3.6%
쌍문동 32
 
3.5%
지상3층 16
 
1.7%
지상1층 11
 
1.2%
지상2층 9
 
1.0%
3층 9
 
1.0%
Other values (262) 354
38.2%
2024-05-11T14:49:10.328451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
885
18.9%
도 234
 
5.0%
봉 234
 
5.0%
1 206
 
4.4%
동 192
 
4.1%
시 182
 
3.9%
서 178
 
3.8%
특 176
 
3.8%
별 176
 
3.8%
구 176
 
3.8%
Other values (123) 2032
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2526
54.1%
Decimal Number 1067
22.8%
Space Separator 885
 
18.9%
Dash Punctuation 149
 
3.2%
Uppercase Letter 15
 
0.3%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%
Other Punctuation 8
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 234
 
9.3%
봉 234
 
9.3%
동 192
 
7.6%
시 182
 
7.2%
서 178
 
7.0%
특 176
 
7.0%
별 176
 
7.0%
구 176
 
7.0%
울 176
 
7.0%
층 97
 
3.8%
Other values (97) 705
27.9%
Decimal Number
ValueCountFrequency (%)
1 206
19.3%
2 153
14.3%
3 143
13.4%
6 132
12.4%
0 107
10.0%
4 90
8.4%
5 86
8.1%
7 55
 
5.2%
8 52
 
4.9%
9 43
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 7
46.7%
G 2
 
13.3%
D 1
 
6.7%
H 1
 
6.7%
A 1
 
6.7%
K 1
 
6.7%
I 1
 
6.7%
N 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
/ 1
 
12.5%
@ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2526
54.1%
Common 2130
45.6%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 234
 
9.3%
봉 234
 
9.3%
동 192
 
7.6%
시 182
 
7.2%
서 178
 
7.0%
특 176
 
7.0%
별 176
 
7.0%
구 176
 
7.0%
울 176
 
7.0%
층 97
 
3.8%
Other values (97) 705
27.9%
Common
ValueCountFrequency (%)
885
41.5%
1 206
 
9.7%
2 153
 
7.2%
- 149
 
7.0%
3 143
 
6.7%
6 132
 
6.2%
0 107
 
5.0%
4 90
 
4.2%
5 86
 
4.0%
7 55
 
2.6%
Other values (8) 124
 
5.8%
Latin
ValueCountFrequency (%)
B 7
46.7%
G 2
 
13.3%
D 1
 
6.7%
H 1
 
6.7%
A 1
 
6.7%
K 1
 
6.7%
I 1
 
6.7%
N 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2526
54.1%
ASCII 2145
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
885
41.3%
1 206
 
9.6%
2 153
 
7.1%
- 149
 
6.9%
3 143
 
6.7%
6 132
 
6.2%
0 107
 
5.0%
4 90
 
4.2%
5 86
 
4.0%
7 55
 
2.6%
Other values (16) 139
 
6.5%
Hangul
ValueCountFrequency (%)
도 234
 
9.3%
봉 234
 
9.3%
동 192
 
7.6%
시 182
 
7.2%
서 178
 
7.0%
특 176
 
7.0%
별 176
 
7.0%
구 176
 
7.0%
울 176
 
7.0%
층 97
 
3.8%
Other values (97) 705
27.9%

도로명주소
Text

MISSING 

Distinct126
Distinct (%)97.7%
Missing47
Missing (%)26.7%
Memory size1.5 KiB
2024-05-11T14:49:10.844781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length43
Mean length34.589147
Min length25

Characters and Unicode

Total characters4462
Distinct characters127
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

Unique123 ?
Unique (%)95.3%

Sample

1st row서울특별시 도봉구 도봉로169나길 67 (도봉동)
2nd row서울특별시 도봉구 도봉로 575 (쌍문동,삼환프라자601호)
3rd row서울특별시 도봉구 도봉로146길 21, 우림빌딩(201호) 지상2층 (방학동)
4th row서울특별시 도봉구 덕릉로57길 30, 3층 2호 (창동)
5th row서울특별시 도봉구 도봉로180나길 41, 상가1동 322호 (도봉동)
ValueCountFrequency (%)
서울특별시 129
 
15.7%
도봉구 129
 
15.7%
도봉동 38
 
4.6%
창동 23
 
2.8%
방학동 21
 
2.5%
쌍문동 19
 
2.3%
지상3층 13
 
1.6%
지상2층 12
 
1.5%
도봉로 10
 
1.2%
마들로 9
 
1.1%
Other values (260) 421
51.1%
2024-05-11T14:49:11.555596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
695
 
15.6%
도 247
 
5.5%
봉 247
 
5.5%
1 213
 
4.8%
동 148
 
3.3%
, 148
 
3.3%
시 141
 
3.2%
) 137
 
3.1%
( 137
 
3.1%
서 131
 
2.9%
Other values (117) 2218
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2445
54.8%
Decimal Number 863
 
19.3%
Space Separator 695
 
15.6%
Other Punctuation 148
 
3.3%
Close Punctuation 137
 
3.1%
Open Punctuation 137
 
3.1%
Dash Punctuation 26
 
0.6%
Uppercase Letter 10
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 247
 
10.1%
봉 247
 
10.1%
동 148
 
6.1%
시 141
 
5.8%
서 131
 
5.4%
구 129
 
5.3%
별 129
 
5.3%
울 129
 
5.3%
특 129
 
5.3%
로 128
 
5.2%
Other values (95) 887
36.3%
Decimal Number
ValueCountFrequency (%)
1 213
24.7%
2 119
13.8%
3 96
11.1%
0 93
10.8%
6 84
 
9.7%
5 74
 
8.6%
4 65
 
7.5%
7 51
 
5.9%
9 37
 
4.3%
8 31
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
50.0%
K 1
 
10.0%
I 1
 
10.0%
N 1
 
10.0%
G 1
 
10.0%
A 1
 
10.0%
Space Separator
ValueCountFrequency (%)
695
100.0%
Other Punctuation
ValueCountFrequency (%)
, 148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2445
54.8%
Common 2007
45.0%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 247
 
10.1%
봉 247
 
10.1%
동 148
 
6.1%
시 141
 
5.8%
서 131
 
5.4%
구 129
 
5.3%
별 129
 
5.3%
울 129
 
5.3%
특 129
 
5.3%
로 128
 
5.2%
Other values (95) 887
36.3%
Common
ValueCountFrequency (%)
695
34.6%
1 213
 
10.6%
, 148
 
7.4%
) 137
 
6.8%
( 137
 
6.8%
2 119
 
5.9%
3 96
 
4.8%
0 93
 
4.6%
6 84
 
4.2%
5 74
 
3.7%
Other values (6) 211
 
10.5%
Latin
ValueCountFrequency (%)
B 5
50.0%
K 1
 
10.0%
I 1
 
10.0%
N 1
 
10.0%
G 1
 
10.0%
A 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2445
54.8%
ASCII 2017
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
695
34.5%
1 213
 
10.6%
, 148
 
7.3%
) 137
 
6.8%
( 137
 
6.8%
2 119
 
5.9%
3 96
 
4.8%
0 93
 
4.6%
6 84
 
4.2%
5 74
 
3.7%
Other values (12) 221
 
11.0%
Hangul
ValueCountFrequency (%)
도 247
 
10.1%
봉 247
 
10.1%
동 148
 
6.1%
시 141
 
5.8%
서 131
 
5.4%
구 129
 
5.3%
별 129
 
5.3%
울 129
 
5.3%
특 129
 
5.3%
로 128
 
5.2%
Other values (95) 887
36.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)49.6%
Missing47
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean1376.5814
Minimum1303
Maximum1480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:11.831793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1303
5-th percentile1306.4
Q11323
median1357
Q31432
95-th percentile1466
Maximum1480
Range177
Interquartile range (IQR)109

Descriptive statistics

Standard deviation55.969257
Coefficient of variation (CV)0.040658153
Kurtosis-1.4684334
Mean1376.5814
Median Absolute Deviation (MAD)48
Skewness0.24983552
Sum177579
Variance3132.5578
MonotonicityNot monotonic
2024-05-11T14:49:12.089944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1414 12
 
6.8%
1318 8
 
4.5%
1432 5
 
2.8%
1436 4
 
2.3%
1306 4
 
2.3%
1347 3
 
1.7%
1320 3
 
1.7%
1324 3
 
1.7%
1322 3
 
1.7%
1357 3
 
1.7%
Other values (54) 81
46.0%
(Missing) 47
26.7%
ValueCountFrequency (%)
1303 1
 
0.6%
1304 1
 
0.6%
1305 1
 
0.6%
1306 4
2.3%
1307 3
1.7%
1308 2
1.1%
1309 1
 
0.6%
1310 1
 
0.6%
1314 1
 
0.6%
1315 1
 
0.6%
ValueCountFrequency (%)
1480 1
 
0.6%
1477 1
 
0.6%
1475 2
1.1%
1471 1
 
0.6%
1470 2
1.1%
1460 2
1.1%
1454 3
1.7%
1453 2
1.1%
1452 1
 
0.6%
1448 1
 
0.6%

사업장명
Text

Distinct171
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T14:49:12.490552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length7.3693182
Min length2

Characters and Unicode

Total characters1297
Distinct characters226
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)94.3%

Sample

1st row송일산업개발(주)
2nd row재원용역
3rd row코암산업(주)
4th row금호환경개발
5th row미래정수
ValueCountFrequency (%)
주식회사 22
 
10.2%
주 3
 
1.4%
코리아종합관리(주 2
 
0.9%
정수산업 2
 
0.9%
월드환경 2
 
0.9%
재원용역 2
 
0.9%
진성관리 2
 
0.9%
행복한크린세상 1
 
0.5%
태영건물종합관리주식회사 1
 
0.5%
용문 1
 
0.5%
Other values (178) 178
82.4%
2024-05-11T14:49:13.165424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 97
 
7.5%
) 69
 
5.3%
( 68
 
5.2%
40
 
3.1%
사 37
 
2.9%
스 36
 
2.8%
리 33
 
2.5%
회 32
 
2.5%
경 31
 
2.4%
식 30
 
2.3%
Other values (216) 824
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1083
83.5%
Close Punctuation 69
 
5.3%
Open Punctuation 68
 
5.2%
Space Separator 40
 
3.1%
Lowercase Letter 19
 
1.5%
Uppercase Letter 16
 
1.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 97
 
9.0%
사 37
 
3.4%
스 36
 
3.3%
리 33
 
3.0%
회 32
 
3.0%
경 31
 
2.9%
식 30
 
2.8%
환 28
 
2.6%
이 22
 
2.0%
관 21
 
1.9%
Other values (190) 716
66.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
21.1%
o 3
15.8%
s 2
10.5%
r 2
10.5%
a 1
 
5.3%
p 1
 
5.3%
w 1
 
5.3%
l 1
 
5.3%
h 1
 
5.3%
c 1
 
5.3%
Other values (2) 2
10.5%
Uppercase Letter
ValueCountFrequency (%)
K 4
25.0%
Y 2
12.5%
S 2
12.5%
A 2
12.5%
H 1
 
6.2%
B 1
 
6.2%
G 1
 
6.2%
M 1
 
6.2%
C 1
 
6.2%
D 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1083
83.5%
Common 179
 
13.8%
Latin 35
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 97
 
9.0%
사 37
 
3.4%
스 36
 
3.3%
리 33
 
3.0%
회 32
 
3.0%
경 31
 
2.9%
식 30
 
2.8%
환 28
 
2.6%
이 22
 
2.0%
관 21
 
1.9%
Other values (190) 716
66.1%
Latin
ValueCountFrequency (%)
K 4
 
11.4%
e 4
 
11.4%
o 3
 
8.6%
Y 2
 
5.7%
S 2
 
5.7%
s 2
 
5.7%
r 2
 
5.7%
A 2
 
5.7%
H 1
 
2.9%
a 1
 
2.9%
Other values (12) 12
34.3%
Common
ValueCountFrequency (%)
) 69
38.5%
( 68
38.0%
40
22.3%
& 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1083
83.5%
ASCII 214
 
16.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 97
 
9.0%
사 37
 
3.4%
스 36
 
3.3%
리 33
 
3.0%
회 32
 
3.0%
경 31
 
2.9%
식 30
 
2.8%
환 28
 
2.6%
이 22
 
2.0%
관 21
 
1.9%
Other values (190) 716
66.1%
ASCII
ValueCountFrequency (%)
) 69
32.2%
( 68
31.8%
40
18.7%
K 4
 
1.9%
e 4
 
1.9%
o 3
 
1.4%
& 2
 
0.9%
Y 2
 
0.9%
S 2
 
0.9%
s 2
 
0.9%
Other values (16) 18
 
8.4%

최종수정일자
Date

Distinct171
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2000-02-07 00:00:00
Maximum2024-01-03 13:18:29
2024-05-11T14:49:13.440911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:13.724035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
I
122 
U
54 

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 122
69.3%
U 54
30.7%

Length

2024-05-11T14:49:13.964896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:14.114318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 122
69.3%
u 54
30.7%

데이터갱신일자
Date

Distinct60
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-01 00:05:00
2024-05-11T14:49:14.627940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:14.847555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
건물위생관리업
176 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 176
100.0%

Length

2024-05-11T14:49:15.079624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:15.264635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 176
100.0%

좌표정보(X)
Real number (ℝ)

Distinct129
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203576.35
Minimum201177.74
Maximum204506.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:15.426329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201177.74
5-th percentile202737.56
Q1203118.39
median203637.34
Q3204040.75
95-th percentile204357.13
Maximum204506.92
Range3329.1779
Interquartile range (IQR)922.3637

Descriptive statistics

Standard deviation595.0091
Coefficient of variation (CV)0.0029227811
Kurtosis1.5275298
Mean203576.35
Median Absolute Deviation (MAD)450.02326
Skewness-0.84482107
Sum35829438
Variance354035.83
MonotonicityNot monotonic
2024-05-11T14:49:15.658774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204335.057042232 6
 
3.4%
204169.847670316 5
 
2.8%
204035.063229754 4
 
2.3%
203348.210556651 4
 
2.3%
204397.004135761 3
 
1.7%
203984.137173444 3
 
1.7%
204506.921108086 3
 
1.7%
204172.527806715 3
 
1.7%
203071.568977276 2
 
1.1%
204081.386150138 2
 
1.1%
Other values (119) 141
80.1%
ValueCountFrequency (%)
201177.743198866 1
0.6%
201180.316997451 1
0.6%
202230.909568087 1
0.6%
202338.176087569 2
1.1%
202356.839977265 1
0.6%
202449.231621477 1
0.6%
202677.943933184 1
0.6%
202719.074278396 1
0.6%
202743.722437757 1
0.6%
202791.379926876 1
0.6%
ValueCountFrequency (%)
204506.921108086 3
1.7%
204488.650732578 1
 
0.6%
204428.262955437 1
 
0.6%
204397.004135761 3
1.7%
204365.037901995 1
 
0.6%
204354.5 1
 
0.6%
204345.826664906 1
 
0.6%
204335.057042232 6
3.4%
204292.478413536 1
 
0.6%
204286.797406657 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

Distinct129
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean462151.64
Minimum459047.54
Maximum465042.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:15.862978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum459047.54
5-th percentile459746.92
Q1461124.3
median461963.12
Q3463365.59
95-th percentile464814.72
Maximum465042.49
Range5994.9579
Interquartile range (IQR)2241.2827

Descriptive statistics

Standard deviation1475.1472
Coefficient of variation (CV)0.0031919116
Kurtosis-0.80940153
Mean462151.64
Median Absolute Deviation (MAD)1013.0707
Skewness0.21841107
Sum81338689
Variance2176059.2
MonotonicityNot monotonic
2024-05-11T14:49:16.098763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461157.210858518 6
 
3.4%
464814.717432497 5
 
2.8%
465042.493324016 4
 
2.3%
461557.310544671 4
 
2.3%
461175.40204195 3
 
1.7%
461008.914009807 3
 
1.7%
461239.917552563 3
 
1.7%
463449.540298026 3
 
1.7%
461437.490682857 2
 
1.1%
464472.810888981 2
 
1.1%
Other values (119) 141
80.1%
ValueCountFrequency (%)
459047.53542317 1
0.6%
459141.573121253 1
0.6%
459467.444022286 1
0.6%
459569.169181429 1
0.6%
459614.063091496 1
0.6%
459659.745086451 1
0.6%
459660.983890238 2
1.1%
459746.924430501 2
1.1%
459891.795182137 1
0.6%
460133.149907308 1
0.6%
ValueCountFrequency (%)
465042.493324016 4
2.3%
464978.535 1
 
0.6%
464828.911640695 1
 
0.6%
464814.717432497 5
2.8%
464768.43323261 1
 
0.6%
464725.202550965 1
 
0.6%
464621.491955908 1
 
0.6%
464472.810888981 2
 
1.1%
464295.628375287 1
 
0.6%
464212.297931928 1
 
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
건물위생관리업
154 
<NA>
22 

Length

Max length7
Median length7
Mean length6.625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 154
87.5%
<NA> 22
 
12.5%

Length

2024-05-11T14:49:16.305321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:16.482238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 154
87.5%
na 22
 
12.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)8.1%
Missing53
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean0.95121951
Minimum0
Maximum19
Zeros100
Zeros (%)56.8%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:16.643618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6141283
Coefficient of variation (CV)2.7481861
Kurtosis22.912328
Mean0.95121951
Median Absolute Deviation (MAD)0
Skewness4.26031
Sum117
Variance6.8336665
MonotonicityNot monotonic
2024-05-11T14:49:16.830418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 100
56.8%
4 6
 
3.4%
5 5
 
2.8%
3 5
 
2.8%
2 2
 
1.1%
1 1
 
0.6%
7 1
 
0.6%
14 1
 
0.6%
19 1
 
0.6%
8 1
 
0.6%
(Missing) 53
30.1%
ValueCountFrequency (%)
0 100
56.8%
1 1
 
0.6%
2 2
 
1.1%
3 5
 
2.8%
4 6
 
3.4%
5 5
 
2.8%
7 1
 
0.6%
8 1
 
0.6%
14 1
 
0.6%
19 1
 
0.6%
ValueCountFrequency (%)
19 1
 
0.6%
14 1
 
0.6%
8 1
 
0.6%
7 1
 
0.6%
5 5
 
2.8%
4 6
 
3.4%
3 5
 
2.8%
2 2
 
1.1%
1 1
 
0.6%
0 100
56.8%

건물지하층수
Categorical

Distinct6
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
103 
<NA>
51 
1
17 
2
 
3
4
 
1

Length

Max length4
Median length1
Mean length1.8693182
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 103
58.5%
<NA> 51
29.0%
1 17
 
9.7%
2 3
 
1.7%
4 1
 
0.6%
6 1
 
0.6%

Length

2024-05-11T14:49:17.056958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:17.273451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 103
58.5%
na 51
29.0%
1 17
 
9.7%
2 3
 
1.7%
4 1
 
0.6%
6 1
 
0.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)10.8%
Missing46
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean3.0769231
Minimum0
Maximum18
Zeros11
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:17.536923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile8.55
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9691316
Coefficient of variation (CV)0.96496777
Kurtosis6.962858
Mean3.0769231
Median Absolute Deviation (MAD)2
Skewness2.3170937
Sum400
Variance8.8157424
MonotonicityNot monotonic
2024-05-11T14:49:17.747561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 33
18.8%
3 32
18.2%
2 20
11.4%
0 11
 
6.2%
4 10
 
5.7%
6 6
 
3.4%
5 6
 
3.4%
7 4
 
2.3%
11 2
 
1.1%
13 2
 
1.1%
Other values (4) 4
 
2.3%
(Missing) 46
26.1%
ValueCountFrequency (%)
0 11
 
6.2%
1 33
18.8%
2 20
11.4%
3 32
18.2%
4 10
 
5.7%
5 6
 
3.4%
6 6
 
3.4%
7 4
 
2.3%
8 1
 
0.6%
9 1
 
0.6%
ValueCountFrequency (%)
18 1
 
0.6%
14 1
 
0.6%
13 2
 
1.1%
11 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%
7 4
 
2.3%
6 6
3.4%
5 6
3.4%
4 10
5.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)13.1%
Missing69
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean3.1588785
Minimum0
Maximum18
Zeros6
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T14:49:18.015461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q11
median3
Q34
95-th percentile8.7
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9688621
Coefficient of variation (CV)0.93984688
Kurtosis7.6076075
Mean3.1588785
Median Absolute Deviation (MAD)2
Skewness2.4148977
Sum338
Variance8.8141421
MonotonicityNot monotonic
2024-05-11T14:49:18.225870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 29
16.5%
3 28
15.9%
2 15
 
8.5%
4 9
 
5.1%
0 6
 
3.4%
5 6
 
3.4%
6 4
 
2.3%
7 3
 
1.7%
11 2
 
1.1%
9 1
 
0.6%
Other values (4) 4
 
2.3%
(Missing) 69
39.2%
ValueCountFrequency (%)
0 6
 
3.4%
1 29
16.5%
2 15
8.5%
3 28
15.9%
4 9
 
5.1%
5 6
 
3.4%
6 4
 
2.3%
7 3
 
1.7%
8 1
 
0.6%
9 1
 
0.6%
ValueCountFrequency (%)
18 1
 
0.6%
14 1
 
0.6%
13 1
 
0.6%
11 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%
7 3
 
1.7%
6 4
2.3%
5 6
3.4%
4 9
5.1%

사용시작지하층
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
125 
0
41 
1
 
9
2
 
1

Length

Max length4
Median length4
Mean length3.1306818
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 125
71.0%
0 41
 
23.3%
1 9
 
5.1%
2 1
 
0.6%

Length

2024-05-11T14:49:18.456841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:18.640692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
71.0%
0 41
 
23.3%
1 9
 
5.1%
2 1
 
0.6%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
136 
0
32 
1
 
7
2
 
1

Length

Max length4
Median length4
Mean length3.3181818
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 136
77.3%
0 32
 
18.2%
1 7
 
4.0%
2 1
 
0.6%

Length

2024-05-11T14:49:18.835945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:19.074121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
77.3%
0 32
 
18.2%
1 7
 
4.0%
2 1
 
0.6%

한실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
114 
<NA>
62 

Length

Max length4
Median length1
Mean length2.0568182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
64.8%
<NA> 62
35.2%

Length

2024-05-11T14:49:19.295142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:19.512630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
64.8%
na 62
35.2%

양실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
114 
<NA>
62 

Length

Max length4
Median length1
Mean length2.0568182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
64.8%
<NA> 62
35.2%

Length

2024-05-11T14:49:19.716064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:20.071253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
64.8%
na 62
35.2%

욕실수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
114 
<NA>
62 

Length

Max length4
Median length1
Mean length2.0568182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
64.8%
<NA> 62
35.2%

Length

2024-05-11T14:49:20.338404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:20.526983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
64.8%
na 62
35.2%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing29
Missing (%)16.5%
Memory size484.0 B
False
147 
(Missing)
29 
ValueCountFrequency (%)
False 147
83.5%
(Missing) 29
 
16.5%
2024-05-11T14:49:20.683791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
114 
<NA>
62 

Length

Max length4
Median length1
Mean length2.0568182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
64.8%
<NA> 62
35.2%

Length

2024-05-11T14:49:20.863251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:21.039627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
64.8%
na 62
35.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
124 
임대
49 
자가
 
3

Length

Max length4
Median length4
Mean length3.4090909
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 124
70.5%
임대 49
 
27.8%
자가 3
 
1.7%

Length

2024-05-11T14:49:21.248677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:21.485656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
70.5%
임대 49
 
27.8%
자가 3
 
1.7%

세탁기수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
105 
<NA>
71 

Length

Max length4
Median length1
Mean length2.2102273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 105
59.7%
<NA> 71
40.3%

Length

2024-05-11T14:49:21.692256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:21.887331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 105
59.7%
na 71
40.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
144 
0
31 
1
 
1

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 144
81.8%
0 31
 
17.6%
1 1
 
0.6%

Length

2024-05-11T14:49:22.110252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:22.444579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
81.8%
0 31
 
17.6%
1 1
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
144 
0
30 
3
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 144
81.8%
0 30
 
17.0%
3 1
 
0.6%
1 1
 
0.6%

Length

2024-05-11T14:49:22.716963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:22.932755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
81.8%
0 30
 
17.0%
3 1
 
0.6%
1 1
 
0.6%

회수건조수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
91 
0
85 

Length

Max length4
Median length4
Mean length2.5511364
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> 91
51.7%
0 85
48.3%

Length

2024-05-11T14:49:23.143999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:23.316496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
51.7%
0 85
48.3%

침대수
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
91 
0
85 

Length

Max length4
Median length4
Mean length2.5511364
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> 91
51.7%
0 85
48.3%

Length

2024-05-11T14:49:23.521511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:23.716231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
51.7%
0 85
48.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing22
Missing (%)12.5%
Memory size484.0 B
False
154 
(Missing)
22 
ValueCountFrequency (%)
False 154
87.5%
(Missing) 22
 
12.5%
2024-05-11T14:49:23.877400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030900003090000-206-1993-0146119931106<NA>1영업/정상1영업<NA><NA><NA><NA>02 9557870144.57132819서울특별시 도봉구 도봉동 600-19서울특별시 도봉구 도봉로169나길 67 (도봉동)1307송일산업개발(주)2012-11-28 15:04:53I2018-08-31 23:59:59.0건물위생관리업203796.632977463804.941164건물위생관리업41<NA><NA>11<NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
130900003090000-206-1994-0146219940412<NA>3폐업2폐업20000419<NA><NA><NA>02 991387350.66132841서울특별시 도봉구 방학동 630-17<NA><NA>재원용역2000-05-25 00:00:00I2018-08-31 23:59:59.0건물위생관리업202913.837444462705.364669건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230900003090000-206-1994-0146319940608<NA>3폐업2폐업19960920<NA><NA><NA>02 990296795.45132898서울특별시 도봉구 창동 6-0<NA><NA>코암산업(주)2002-01-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업204279.415461140.88건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330900003090000-206-1994-0146419940707<NA>3폐업2폐업20020103<NA><NA><NA>02 999314152.38132819서울특별시 도봉구 도봉동 602-31<NA><NA>금호환경개발2002-05-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업203745.387821463567.923415건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430900003090000-206-1994-0146519941018<NA>3폐업2폐업19960920<NA><NA><NA>02 999134179.3132908서울특별시 도봉구 창동 333-2<NA><NA>미래정수2002-01-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업204004.945535461048.885009건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530900003090000-206-1995-0145919950620<NA>3폐업2폐업19960920<NA><NA><NA>02 955184760.9132821서울특별시 도봉구 도봉동 622-17<NA><NA>동원실업2002-01-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업203875.874892463190.652831건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630900003090000-206-1995-0146019950710<NA>3폐업2폐업19960920<NA><NA><NA>02 990296760.04132898서울특별시 도봉구 창동 3-3<NA><NA>코암크린산업2002-01-18 00:00:00I2018-08-31 23:59:59.0건물위생관리업204263.706546461207.24473건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730900003090000-206-1995-0146619950120<NA>3폐업2폐업20060627<NA><NA><NA>3491911393.78132850서울특별시 도봉구 방학동 685-3<NA><NA>승진개발2005-08-19 00:00:00I2018-08-31 23:59:59.0건물위생관리업203402.944063462539.193652건물위생관리업<NA><NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830900003090000-206-1996-0146819960619<NA>3폐업2폐업20050115<NA><NA><NA><NA>149.04132809서울특별시 도봉구 도봉동 447-2<NA><NA>성일위생2005-01-15 00:00:00I2018-08-31 23:59:59.0건물위생관리업203444.92051463402.087663건물위생관리업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930900003090000-206-1996-0146919961115<NA>3폐업2폐업20000207<NA><NA><NA>02 992131353.92132896서울특별시 도봉구 쌍문동 711-21 제일시장 201호<NA><NA>성우기업2000-02-07 00:00:00I2018-08-31 23:59:59.0건물위생관리업203289.775603462040.427791건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
16630900003090000-206-2020-0000220200916<NA>1영업/정상1영업<NA><NA><NA><NA>02 9907901141.75132815서울특별시 도봉구 도봉동 569 3층서울특별시 도봉구 도봉산3길 45, 3층 (도봉동)1303(주)소유파트너스2020-09-16 14:07:43I2020-09-18 00:23:12.0건물위생관리업203800.36311464768.433233건물위생관리업0033<NA><NA>000N0<NA><NA><NA><NA>00000N
16730900003090000-206-2020-000032020-01-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0132-951서울특별시 도봉구 쌍문동 342-3서울특별시 도봉구 노해로 162, 2층 (쌍문동)1446한국위생방역협동조합2023-12-01 10:58:34I2022-11-02 00:03:00.0건물위생관리업202338.176088460715.069435<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16830900003090000-206-2022-0000120220414<NA>1영업/정상1영업<NA><NA><NA><NA>02 955777189.0132851서울특별시 도봉구 방학동 691-1 1층서울특별시 도봉구 방학로8길 4, 1층 (방학동)1343지와이건설 주식회사(GY)2022-04-14 15:49:33I2021-12-03 23:06:00.0건물위생관리업203123.055393462295.515028<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16930900003090000-206-2022-0000220220729<NA>1영업/정상1영업<NA><NA><NA><NA><NA>51.08132863서울특별시 도봉구 쌍문동 85-16 지하1층서울특별시 도봉구 도봉로121가길 27, 지하1층 (쌍문동)1440사단법인 한국장애인농축산기술협회국토환경기술사업단2022-08-01 09:26:18U2021-12-08 00:03:00.0건물위생관리업202959.17683461041.762718<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17030900003090000-206-2022-000032022-08-10<NA>3폐업2폐업2024-01-03<NA><NA><NA><NA>67.32132-916서울특별시 도봉구 창동 492-33 1층서울특별시 도봉구 덕릉로60길 157, 1층 (창동)1480제로제로환경2024-01-03 13:18:29U2023-12-01 00:05:00.0건물위생관리업203755.716812459047.535423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17130900003090000-206-2022-0000420221020<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.43132866서울특별시 도봉구 쌍문동 88-29 1층서울특별시 도봉구 노해로60길 67-3, 1층 (쌍문동)1443클리닝오케이 샤코리아(SYA Korea)2022-12-29 15:25:24U2021-11-01 21:01:00.0건물위생관리업202910.608343460667.628202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17230900003090000-206-2022-0000520221021<NA>1영업/정상1영업<NA><NA><NA><NA>02 955899324.1132850서울특별시 도봉구 방학동 684-54 1층서울특별시 도봉구 방학로2길 65, 1층 (방학동)1341푸르른환경주식회사2022-10-21 11:30:29I2021-10-30 22:03:00.0건물위생관리업203530.877333462608.329959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17330900003090000-206-2022-0000620220308<NA>1영업/정상1영업<NA><NA><NA><NA>02 956 325624.86132758서울특별시 도봉구 도봉동 641 서원아파트서울특별시 도봉구 마들로 684-9, 서원아파트 상가동 304호 (도봉동)1324주식회사 대온종합관리2023-01-02 17:31:19I2022-12-01 00:04:00.0건물위생관리업204172.527807463449.540298<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17430900003090000-206-2023-000012023-09-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.66132-801서울특별시 도봉구 도봉동 62-3 도봉투웨니퍼스트1단지 102동 702호서울특별시 도봉구 도봉로180길 20, 도봉투웨니퍼스트1단지 102동 702호 (도봉동)1320(주)미래휴넷시스템2023-09-20 15:12:34U2022-12-08 22:02:00.0건물위생관리업204081.38615464472.810889<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17530900003090000-206-2023-000022023-12-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>86.52132-030서울특별시 도봉구 쌍문동 644 ,3층서울특별시 도봉구 해등로17길 12 (쌍문동)1432월드환경2023-12-11 15:06:27I2022-11-01 23:03:00.0건물위생관리업203306.556907461561.615484<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>