Overview

Dataset statistics

Number of variables47
Number of observations234
Missing cells2449
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory92.4 KiB
Average record size in memory404.6 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-19287/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (96.0%)Imbalance
인허가취소일자 has 234 (100.0%) missing valuesMissing
폐업일자 has 80 (34.2%) missing valuesMissing
휴업시작일자 has 234 (100.0%) missing valuesMissing
휴업종료일자 has 234 (100.0%) missing valuesMissing
재개업일자 has 234 (100.0%) missing valuesMissing
전화번호 has 78 (33.3%) missing valuesMissing
도로명주소 has 63 (26.9%) missing valuesMissing
도로명우편번호 has 63 (26.9%) missing valuesMissing
좌표정보(X) has 8 (3.4%) missing valuesMissing
좌표정보(Y) has 8 (3.4%) missing valuesMissing
건물지상층수 has 102 (43.6%) missing valuesMissing
사용시작지상층 has 146 (62.4%) missing valuesMissing
사용끝지상층 has 150 (64.1%) missing valuesMissing
발한실여부 has 60 (25.6%) missing valuesMissing
조건부허가신고사유 has 234 (100.0%) missing valuesMissing
조건부허가시작일자 has 234 (100.0%) missing valuesMissing
조건부허가종료일자 has 234 (100.0%) missing valuesMissing
다중이용업소여부 has 53 (22.6%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 108 (46.2%) zerosZeros
사용시작지상층 has 34 (14.5%) zerosZeros
사용끝지상층 has 34 (14.5%) zerosZeros

Reproduction

Analysis started2024-04-29 19:52:48.164569
Analysis finished2024-04-29 19:52:49.112270
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3100000
234 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 234
100.0%

Length

2024-04-30T04:52:49.172648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:49.242691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 234
100.0%

관리번호
Text

UNIQUE 

Distinct234
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:52:49.383349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5148
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

Unique234 ?
Unique (%)100.0%

Sample

1st row3100000-206-1993-01569
2nd row3100000-206-1993-01570
3rd row3100000-206-1993-01571
4th row3100000-206-1997-01578
5th row3100000-206-1997-01579
ValueCountFrequency (%)
3100000-206-1993-01569 1
 
0.4%
3100000-206-2015-00008 1
 
0.4%
3100000-206-2014-00009 1
 
0.4%
3100000-206-2017-00005 1
 
0.4%
3100000-206-2014-00010 1
 
0.4%
3100000-206-2014-00011 1
 
0.4%
3100000-206-2014-00012 1
 
0.4%
3100000-206-2015-00001 1
 
0.4%
3100000-206-2015-00002 1
 
0.4%
3100000-206-2015-00003 1
 
0.4%
Other values (224) 224
95.7%
2024-04-30T04:52:49.658301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2621
50.9%
- 702
 
13.6%
2 548
 
10.6%
1 438
 
8.5%
3 296
 
5.7%
6 274
 
5.3%
9 64
 
1.2%
5 56
 
1.1%
7 54
 
1.0%
4 53
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4446
86.4%
Dash Punctuation 702
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2621
59.0%
2 548
 
12.3%
1 438
 
9.9%
3 296
 
6.7%
6 274
 
6.2%
9 64
 
1.4%
5 56
 
1.3%
7 54
 
1.2%
4 53
 
1.2%
8 42
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2621
50.9%
- 702
 
13.6%
2 548
 
10.6%
1 438
 
8.5%
3 296
 
5.7%
6 274
 
5.3%
9 64
 
1.2%
5 56
 
1.1%
7 54
 
1.0%
4 53
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2621
50.9%
- 702
 
13.6%
2 548
 
10.6%
1 438
 
8.5%
3 296
 
5.7%
6 274
 
5.3%
9 64
 
1.2%
5 56
 
1.1%
7 54
 
1.0%
4 53
 
1.0%
Distinct228
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1993-03-17 00:00:00
Maximum2024-03-22 00:00:00
2024-04-30T04:52:49.788379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:49.901303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
154 
1
80 

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 (%)
3 154
65.8%
1 80
34.2%

Length

2024-04-30T04:52:50.001286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:50.073258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 154
65.8%
1 80
34.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
154 
영업/정상
80 

Length

Max length5
Median length2
Mean length3.025641
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 154
65.8%
영업/정상 80
34.2%

Length

2024-04-30T04:52:50.161193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:50.236264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 154
65.8%
영업/정상 80
34.2%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2
154 
1
80 

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 (%)
2 154
65.8%
1 80
34.2%

Length

2024-04-30T04:52:50.317914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:50.398801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 154
65.8%
1 80
34.2%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
154 
영업
80 

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 154
65.8%
영업 80
34.2%

Length

2024-04-30T04:52:50.485411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:50.560638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 154
65.8%
영업 80
34.2%

폐업일자
Date

MISSING 

Distinct144
Distinct (%)93.5%
Missing80
Missing (%)34.2%
Memory size2.0 KiB
Minimum1998-10-09 00:00:00
Maximum2024-04-11 00:00:00
2024-04-30T04:52:50.650465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:50.777936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct148
Distinct (%)94.9%
Missing78
Missing (%)33.3%
Memory size2.0 KiB
2024-04-30T04:52:51.021871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.711538
Min length7

Characters and Unicode

Total characters1671
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

Unique142 ?
Unique (%)91.0%

Sample

1st row02 9521206
2nd row02 9729037
3rd row02 9485555
4th row02 9393538
5th row02 9771313
ValueCountFrequency (%)
02 120
36.7%
9480545 4
 
1.2%
933 3
 
0.9%
951 3
 
0.9%
6594 3
 
0.9%
070 3
 
0.9%
939 3
 
0.9%
8880 2
 
0.6%
976 2
 
0.6%
930 2
 
0.6%
Other values (174) 182
55.7%
2024-04-30T04:52:51.357522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 267
16.0%
2 222
13.3%
222
13.3%
9 210
12.6%
3 166
9.9%
7 113
6.8%
4 105
 
6.3%
5 103
 
6.2%
1 103
 
6.2%
8 93
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1449
86.7%
Space Separator 222
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 267
18.4%
2 222
15.3%
9 210
14.5%
3 166
11.5%
7 113
7.8%
4 105
 
7.2%
5 103
 
7.1%
1 103
 
7.1%
8 93
 
6.4%
6 67
 
4.6%
Space Separator
ValueCountFrequency (%)
222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 267
16.0%
2 222
13.3%
222
13.3%
9 210
12.6%
3 166
9.9%
7 113
6.8%
4 105
 
6.3%
5 103
 
6.2%
1 103
 
6.2%
8 93
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 267
16.0%
2 222
13.3%
222
13.3%
9 210
12.6%
3 166
9.9%
7 113
6.8%
4 105
 
6.3%
5 103
 
6.2%
1 103
 
6.2%
8 93
 
5.6%
Distinct171
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:52:51.673340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8632479
Min length3

Characters and Unicode

Total characters1138
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)62.4%

Sample

1st row.00
2nd row.00
3rd row.00
4th row5,272.54
5th row1,581.30
ValueCountFrequency (%)
00 25
 
10.7%
33.00 4
 
1.7%
24.00 4
 
1.7%
20.00 4
 
1.7%
30.00 4
 
1.7%
39.29 3
 
1.3%
34.00 3
 
1.3%
10.00 3
 
1.3%
82.32 3
 
1.3%
3.30 3
 
1.3%
Other values (161) 178
76.1%
2024-04-30T04:52:52.092782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 273
24.0%
. 234
20.6%
3 101
 
8.9%
1 94
 
8.3%
2 92
 
8.1%
6 74
 
6.5%
4 66
 
5.8%
8 63
 
5.5%
5 58
 
5.1%
7 42
 
3.7%
Other values (2) 41
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 902
79.3%
Other Punctuation 236
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 273
30.3%
3 101
 
11.2%
1 94
 
10.4%
2 92
 
10.2%
6 74
 
8.2%
4 66
 
7.3%
8 63
 
7.0%
5 58
 
6.4%
7 42
 
4.7%
9 39
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 234
99.2%
, 2
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1138
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 273
24.0%
. 234
20.6%
3 101
 
8.9%
1 94
 
8.3%
2 92
 
8.1%
6 74
 
6.5%
4 66
 
5.8%
8 63
 
5.5%
5 58
 
5.1%
7 42
 
3.7%
Other values (2) 41
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1138
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 273
24.0%
. 234
20.6%
3 101
 
8.9%
1 94
 
8.3%
2 92
 
8.1%
6 74
 
6.5%
4 66
 
5.8%
8 63
 
5.5%
5 58
 
5.1%
7 42
 
3.7%
Other values (2) 41
 
3.6%
Distinct76
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:52:52.312819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1452991
Min length6

Characters and Unicode

Total characters1438
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

Unique35 ?
Unique (%)15.0%

Sample

1st row139809
2nd row139804
3rd row139230
4th row139817
5th row139859
ValueCountFrequency (%)
139240 29
 
12.4%
139837 17
 
7.3%
139816 10
 
4.3%
139838 10
 
4.3%
139808 9
 
3.8%
139810 9
 
3.8%
139-240 9
 
3.8%
139871 8
 
3.4%
139942 8
 
3.4%
139820 7
 
3.0%
Other values (66) 118
50.4%
2024-04-30T04:52:52.658740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 297
20.7%
3 286
19.9%
9 259
18.0%
8 193
13.4%
0 108
 
7.5%
2 83
 
5.8%
4 70
 
4.9%
7 52
 
3.6%
6 34
 
2.4%
- 34
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1404
97.6%
Dash Punctuation 34
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 297
21.2%
3 286
20.4%
9 259
18.4%
8 193
13.7%
0 108
 
7.7%
2 83
 
5.9%
4 70
 
5.0%
7 52
 
3.7%
6 34
 
2.4%
5 22
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1438
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 297
20.7%
3 286
19.9%
9 259
18.0%
8 193
13.4%
0 108
 
7.5%
2 83
 
5.8%
4 70
 
4.9%
7 52
 
3.6%
6 34
 
2.4%
- 34
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 297
20.7%
3 286
19.9%
9 259
18.0%
8 193
13.4%
0 108
 
7.5%
2 83
 
5.8%
4 70
 
4.9%
7 52
 
3.6%
6 34
 
2.4%
- 34
 
2.4%
Distinct230
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:52:52.944725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length26.74359
Min length17

Characters and Unicode

Total characters6258
Distinct characters173
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

Unique226 ?
Unique (%)96.6%

Sample

1st row서울특별시 노원구 상계동 47-1
2nd row서울특별시 노원구 공릉동 408-4
3rd row서울특별시 노원구 하계동 산 158-4
4th row서울특별시 노원구 상계동 328-0 동부빌딩 2,3층
5th row서울특별시 노원구 중계동 435-1 현대상가 지하12호
ValueCountFrequency (%)
서울특별시 234
18.9%
노원구 234
18.9%
상계동 117
 
9.5%
공릉동 63
 
5.1%
중계동 24
 
1.9%
1층 18
 
1.5%
월계동 15
 
1.2%
하계동 15
 
1.2%
2층 11
 
0.9%
지하1층 7
 
0.6%
Other values (364) 499
40.3%
2024-04-30T04:52:53.321833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1152
18.4%
1 310
 
5.0%
246
 
3.9%
244
 
3.9%
244
 
3.9%
240
 
3.8%
238
 
3.8%
236
 
3.8%
235
 
3.8%
234
 
3.7%
Other values (163) 2879
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3471
55.5%
Decimal Number 1381
 
22.1%
Space Separator 1152
 
18.4%
Dash Punctuation 185
 
3.0%
Other Punctuation 23
 
0.4%
Uppercase Letter 18
 
0.3%
Close Punctuation 12
 
0.2%
Open Punctuation 12
 
0.2%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
246
 
7.1%
244
 
7.0%
244
 
7.0%
240
 
6.9%
238
 
6.9%
236
 
6.8%
235
 
6.8%
234
 
6.7%
234
 
6.7%
175
 
5.0%
Other values (137) 1145
33.0%
Decimal Number
ValueCountFrequency (%)
1 310
22.4%
2 187
13.5%
3 151
10.9%
0 151
10.9%
4 124
 
9.0%
7 115
 
8.3%
5 111
 
8.0%
6 92
 
6.7%
9 78
 
5.6%
8 62
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 11
61.1%
D 3
 
16.7%
P 1
 
5.6%
K 1
 
5.6%
I 1
 
5.6%
C 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 16
69.6%
@ 4
 
17.4%
/ 3
 
13.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
l 1
25.0%
z 1
25.0%
Space Separator
ValueCountFrequency (%)
1152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3471
55.5%
Common 2765
44.2%
Latin 22
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
246
 
7.1%
244
 
7.0%
244
 
7.0%
240
 
6.9%
238
 
6.9%
236
 
6.8%
235
 
6.8%
234
 
6.7%
234
 
6.7%
175
 
5.0%
Other values (137) 1145
33.0%
Common
ValueCountFrequency (%)
1152
41.7%
1 310
 
11.2%
2 187
 
6.8%
- 185
 
6.7%
3 151
 
5.5%
0 151
 
5.5%
4 124
 
4.5%
7 115
 
4.2%
5 111
 
4.0%
6 92
 
3.3%
Other values (7) 187
 
6.8%
Latin
ValueCountFrequency (%)
B 11
50.0%
D 3
 
13.6%
a 2
 
9.1%
l 1
 
4.5%
P 1
 
4.5%
K 1
 
4.5%
I 1
 
4.5%
z 1
 
4.5%
C 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3471
55.5%
ASCII 2787
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1152
41.3%
1 310
 
11.1%
2 187
 
6.7%
- 185
 
6.6%
3 151
 
5.4%
0 151
 
5.4%
4 124
 
4.4%
7 115
 
4.1%
5 111
 
4.0%
6 92
 
3.3%
Other values (16) 209
 
7.5%
Hangul
ValueCountFrequency (%)
246
 
7.1%
244
 
7.0%
244
 
7.0%
240
 
6.9%
238
 
6.9%
236
 
6.8%
235
 
6.8%
234
 
6.7%
234
 
6.7%
175
 
5.0%
Other values (137) 1145
33.0%

도로명주소
Text

MISSING 

Distinct171
Distinct (%)100.0%
Missing63
Missing (%)26.9%
Memory size2.0 KiB
2024-04-30T04:52:53.569999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length37.362573
Min length22

Characters and Unicode

Total characters6389
Distinct characters180
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

Unique171 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 덕릉로 862 (상계동)
2nd row서울특별시 노원구 노원로1바길 1 (공릉동)
3rd row서울특별시 노원구 덕릉로 804 (상계동, 6구역 51블럭 1롯트 대림프라자 204호)
4th row서울특별시 노원구 동일로 1130 (공릉동,삼익(아) 단지상가 105호)
5th row서울특별시 노원구 노원로 246 (하계동,욱현하이브 B/D 903호)
ValueCountFrequency (%)
서울특별시 171
 
14.3%
노원구 171
 
14.3%
상계동 78
 
6.5%
공릉동 42
 
3.5%
1층 18
 
1.5%
2층 18
 
1.5%
동일로 18
 
1.5%
중계동 16
 
1.3%
3층 12
 
1.0%
하계동 11
 
0.9%
Other values (398) 642
53.6%
2024-04-30T04:52:53.946945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1030
 
16.1%
1 279
 
4.4%
254
 
4.0%
, 221
 
3.5%
201
 
3.1%
190
 
3.0%
( 180
 
2.8%
) 180
 
2.8%
175
 
2.7%
175
 
2.7%
Other values (170) 3504
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3465
54.2%
Decimal Number 1241
 
19.4%
Space Separator 1030
 
16.1%
Other Punctuation 225
 
3.5%
Open Punctuation 180
 
2.8%
Close Punctuation 180
 
2.8%
Dash Punctuation 46
 
0.7%
Uppercase Letter 18
 
0.3%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
254
 
7.3%
201
 
5.8%
190
 
5.5%
175
 
5.1%
175
 
5.1%
173
 
5.0%
172
 
5.0%
172
 
5.0%
171
 
4.9%
171
 
4.9%
Other values (143) 1611
46.5%
Decimal Number
ValueCountFrequency (%)
1 279
22.5%
2 172
13.9%
3 149
12.0%
4 137
11.0%
0 132
10.6%
7 89
 
7.2%
5 82
 
6.6%
8 74
 
6.0%
6 68
 
5.5%
9 59
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 11
61.1%
E 2
 
11.1%
K 1
 
5.6%
P 1
 
5.6%
I 1
 
5.6%
D 1
 
5.6%
C 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 221
98.2%
@ 3
 
1.3%
/ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
l 1
25.0%
z 1
25.0%
Space Separator
ValueCountFrequency (%)
1030
100.0%
Open Punctuation
ValueCountFrequency (%)
( 180
100.0%
Close Punctuation
ValueCountFrequency (%)
) 180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3465
54.2%
Common 2902
45.4%
Latin 22
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
254
 
7.3%
201
 
5.8%
190
 
5.5%
175
 
5.1%
175
 
5.1%
173
 
5.0%
172
 
5.0%
172
 
5.0%
171
 
4.9%
171
 
4.9%
Other values (143) 1611
46.5%
Common
ValueCountFrequency (%)
1030
35.5%
1 279
 
9.6%
, 221
 
7.6%
( 180
 
6.2%
) 180
 
6.2%
2 172
 
5.9%
3 149
 
5.1%
4 137
 
4.7%
0 132
 
4.5%
7 89
 
3.1%
Other values (7) 333
 
11.5%
Latin
ValueCountFrequency (%)
B 11
50.0%
E 2
 
9.1%
a 2
 
9.1%
K 1
 
4.5%
P 1
 
4.5%
l 1
 
4.5%
I 1
 
4.5%
z 1
 
4.5%
D 1
 
4.5%
C 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3465
54.2%
ASCII 2924
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1030
35.2%
1 279
 
9.5%
, 221
 
7.6%
( 180
 
6.2%
) 180
 
6.2%
2 172
 
5.9%
3 149
 
5.1%
4 137
 
4.7%
0 132
 
4.5%
7 89
 
3.0%
Other values (17) 355
 
12.1%
Hangul
ValueCountFrequency (%)
254
 
7.3%
201
 
5.8%
190
 
5.5%
175
 
5.1%
175
 
5.1%
173
 
5.0%
172
 
5.0%
172
 
5.0%
171
 
4.9%
171
 
4.9%
Other values (143) 1611
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)51.5%
Missing63
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean1740.0058
Minimum1604
Maximum1914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:54.073143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1604
5-th percentile1606
Q11657
median1720
Q31843
95-th percentile1867
Maximum1914
Range310
Interquartile range (IQR)186

Descriptive statistics

Standard deviation94.334417
Coefficient of variation (CV)0.054215
Kurtosis-1.4901804
Mean1740.0058
Median Absolute Deviation (MAD)89
Skewness0.12045065
Sum297541
Variance8898.9823
MonotonicityNot monotonic
2024-04-30T04:52:54.193034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1689 9
 
3.8%
1809 7
 
3.0%
1646 6
 
2.6%
1604 6
 
2.6%
1844 6
 
2.6%
1856 5
 
2.1%
1849 4
 
1.7%
1666 4
 
1.7%
1663 4
 
1.7%
1684 3
 
1.3%
Other values (78) 117
50.0%
(Missing) 63
26.9%
ValueCountFrequency (%)
1604 6
2.6%
1605 2
 
0.9%
1606 2
 
0.9%
1607 1
 
0.4%
1608 2
 
0.9%
1610 1
 
0.4%
1612 1
 
0.4%
1613 1
 
0.4%
1620 1
 
0.4%
1624 1
 
0.4%
ValueCountFrequency (%)
1914 1
0.4%
1905 1
0.4%
1904 1
0.4%
1902 1
0.4%
1899 1
0.4%
1896 1
0.4%
1873 1
0.4%
1872 1
0.4%
1870 1
0.4%
1864 1
0.4%
Distinct228
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:52:54.366678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.5982906
Min length2

Characters and Unicode

Total characters1778
Distinct characters270
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

Unique222 ?
Unique (%)94.9%

Sample

1st row표석산업(주)
2nd row인종개발(주)
3rd row청지기용역
4th row(주)늘푸른환경
5th row서진환경
ValueCountFrequency (%)
주식회사 20
 
7.5%
주)대영환경 2
 
0.7%
신화비엠씨 2
 
0.7%
제니스 2
 
0.7%
신화환경개발 2
 
0.7%
주)토마토세븐 2
 
0.7%
삼성크린 2
 
0.7%
매니지먼트 2
 
0.7%
주)21세기토탈관리 1
 
0.4%
주)만도엔지니어링 1
 
0.4%
Other values (231) 231
86.5%
2024-04-30T04:52:54.678730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
7.1%
( 102
 
5.7%
) 102
 
5.7%
62
 
3.5%
38
 
2.1%
37
 
2.1%
35
 
2.0%
33
 
1.9%
32
 
1.8%
30
 
1.7%
Other values (260) 1181
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1505
84.6%
Open Punctuation 102
 
5.7%
Close Punctuation 102
 
5.7%
Space Separator 33
 
1.9%
Decimal Number 23
 
1.3%
Uppercase Letter 12
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
126
 
8.4%
62
 
4.1%
38
 
2.5%
37
 
2.5%
35
 
2.3%
32
 
2.1%
30
 
2.0%
30
 
2.0%
28
 
1.9%
27
 
1.8%
Other values (242) 1060
70.4%
Decimal Number
ValueCountFrequency (%)
1 7
30.4%
2 7
30.4%
3 2
 
8.7%
5 2
 
8.7%
9 2
 
8.7%
6 2
 
8.7%
0 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
D 2
16.7%
I 2
16.7%
C 2
16.7%
K 1
 
8.3%
O 1
 
8.3%
N 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 102
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1505
84.6%
Common 261
 
14.7%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
126
 
8.4%
62
 
4.1%
38
 
2.5%
37
 
2.5%
35
 
2.3%
32
 
2.1%
30
 
2.0%
30
 
2.0%
28
 
1.9%
27
 
1.8%
Other values (242) 1060
70.4%
Common
ValueCountFrequency (%)
( 102
39.1%
) 102
39.1%
33
 
12.6%
1 7
 
2.7%
2 7
 
2.7%
3 2
 
0.8%
5 2
 
0.8%
9 2
 
0.8%
6 2
 
0.8%
0 1
 
0.4%
Latin
ValueCountFrequency (%)
S 3
25.0%
D 2
16.7%
I 2
16.7%
C 2
16.7%
K 1
 
8.3%
O 1
 
8.3%
N 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1505
84.6%
ASCII 273
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
126
 
8.4%
62
 
4.1%
38
 
2.5%
37
 
2.5%
35
 
2.3%
32
 
2.1%
30
 
2.0%
30
 
2.0%
28
 
1.9%
27
 
1.8%
Other values (242) 1060
70.4%
ASCII
ValueCountFrequency (%)
( 102
37.4%
) 102
37.4%
33
 
12.1%
1 7
 
2.6%
2 7
 
2.6%
S 3
 
1.1%
3 2
 
0.7%
D 2
 
0.7%
I 2
 
0.7%
5 2
 
0.7%
Other values (8) 11
 
4.0%
Distinct223
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1999-05-24 00:00:00
Maximum2024-04-16 14:07:33
2024-04-30T04:52:54.796883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:55.095680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
I
120 
U
114 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 120
51.3%
U 114
48.7%

Length

2024-04-30T04:52:55.229604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:55.325452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 120
51.3%
u 114
48.7%
Distinct113
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-04-30T04:52:55.435081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:55.541705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
건물위생관리업
233 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length7.0128205
Min length7

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 233
99.6%
건물위생관리업 기타 1
 
0.4%

Length

2024-04-30T04:52:55.649453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:55.729474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 234
99.6%
기타 1
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct167
Distinct (%)73.9%
Missing8
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean206034
Minimum203719.16
Maximum207749.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:55.832933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203719.16
5-th percentile204582.4
Q1205358.67
median206272.08
Q3206626.62
95-th percentile207108.08
Maximum207749.31
Range4030.1459
Interquartile range (IQR)1267.9435

Descriptive statistics

Standard deviation827.18818
Coefficient of variation (CV)0.004014814
Kurtosis-0.52969229
Mean206034
Median Absolute Deviation (MAD)523.99855
Skewness-0.47101968
Sum46563683
Variance684240.28
MonotonicityNot monotonic
2024-04-30T04:52:55.960965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204772.367380466 6
 
2.6%
205218.739538073 4
 
1.7%
207008.092994104 4
 
1.7%
205978.185783794 4
 
1.7%
206485.004963921 3
 
1.3%
206415.545086691 3
 
1.3%
205792.929986628 3
 
1.3%
205358.673911961 3
 
1.3%
205645.891969072 3
 
1.3%
205982.668835484 3
 
1.3%
Other values (157) 190
81.2%
(Missing) 8
 
3.4%
ValueCountFrequency (%)
203719.161728968 1
0.4%
203839.989956111 1
0.4%
203982.774049825 1
0.4%
204470.586550382 1
0.4%
204518.141437282 1
0.4%
204522.744591198 1
0.4%
204525.903979787 1
0.4%
204549.346104353 2
0.9%
204553.255966506 2
0.9%
204581.162799411 1
0.4%
ValueCountFrequency (%)
207749.307579592 2
0.9%
207577.515810212 1
0.4%
207557.422364404 1
0.4%
207311.442536626 1
0.4%
207301.617322514 2
0.9%
207265.771476959 1
0.4%
207225.811432656 1
0.4%
207218.30541018 1
0.4%
207196.57377733 1
0.4%
207109.026244202 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct167
Distinct (%)73.9%
Missing8
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean460580.75
Minimum456921.61
Maximum464199.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:56.078772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456921.61
5-th percentile457477.15
Q1458083.99
median461249.84
Q3462489.71
95-th percentile463937.76
Maximum464199.05
Range7277.4389
Interquartile range (IQR)4405.7155

Descriptive statistics

Standard deviation2268.1529
Coefficient of variation (CV)0.00492455
Kurtosis-1.4549819
Mean460580.75
Median Absolute Deviation (MAD)2037.7466
Skewness-0.057633894
Sum1.0409125 × 108
Variance5144517.8
MonotonicityNot monotonic
2024-04-30T04:52:56.190648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464080.593904719 6
 
2.6%
461346.263821387 4
 
1.7%
462930.041768876 4
 
1.7%
462367.006783272 4
 
1.7%
457830.050221614 3
 
1.3%
461546.032265974 3
 
1.3%
462489.709453263 3
 
1.3%
463606.782949743 3
 
1.3%
459609.012509743 3
 
1.3%
461485.134186269 3
 
1.3%
Other values (157) 190
81.2%
(Missing) 8
 
3.4%
ValueCountFrequency (%)
456921.609527521 1
0.4%
457100.481909569 1
0.4%
457179.79322197 1
0.4%
457234.284798584 1
0.4%
457259.900809468 1
0.4%
457286.421350285 1
0.4%
457314.629851578 1
0.4%
457367.50332357 1
0.4%
457374.575999081 1
0.4%
457387.61498402 1
0.4%
ValueCountFrequency (%)
464199.048415229 1
 
0.4%
464133.975605555 2
 
0.9%
464080.593904719 6
2.6%
464016.499736548 2
 
0.9%
463940.976727043 1
 
0.4%
463928.107318353 1
 
0.4%
463887.942604325 1
 
0.4%
463781.320660902 1
 
0.4%
463778.901178769 1
 
0.4%
463777.629639984 1
 
0.4%

위생업태명
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
건물위생관리업
180 
<NA>
53 
건물위생관리업 기타
 
1

Length

Max length10
Median length7
Mean length6.3333333
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 180
76.9%
<NA> 53
 
22.6%
건물위생관리업 기타 1
 
0.4%

Length

2024-04-30T04:52:56.314563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:56.393131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 181
77.0%
na 53
 
22.6%
기타 1
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)6.8%
Missing102
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean0.68939394
Minimum0
Maximum14
Zeros108
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:56.467117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8906462
Coefficient of variation (CV)2.7424758
Kurtosis20.288511
Mean0.68939394
Median Absolute Deviation (MAD)0
Skewness3.9537275
Sum91
Variance3.5745431
MonotonicityNot monotonic
2024-04-30T04:52:56.576632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 108
46.2%
2 6
 
2.6%
5 5
 
2.1%
4 4
 
1.7%
1 4
 
1.7%
3 2
 
0.9%
8 1
 
0.4%
6 1
 
0.4%
14 1
 
0.4%
(Missing) 102
43.6%
ValueCountFrequency (%)
0 108
46.2%
1 4
 
1.7%
2 6
 
2.6%
3 2
 
0.9%
4 4
 
1.7%
5 5
 
2.1%
6 1
 
0.4%
8 1
 
0.4%
14 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
8 1
 
0.4%
6 1
 
0.4%
5 5
 
2.1%
4 4
 
1.7%
3 2
 
0.9%
2 6
 
2.6%
1 4
 
1.7%
0 108
46.2%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
120 
<NA>
105 
1
 
8
2
 
1

Length

Max length4
Median length1
Mean length2.3461538
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 120
51.3%
<NA> 105
44.9%
1 8
 
3.4%
2 1
 
0.4%

Length

2024-04-30T04:52:56.699990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:56.783121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 120
51.3%
na 105
44.9%
1 8
 
3.4%
2 1
 
0.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)9.1%
Missing146
Missing (%)62.4%
Infinite0
Infinite (%)0.0%
Mean1.5340909
Minimum0
Maximum11
Zeros34
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:56.865870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8566368
Coefficient of variation (CV)1.2102522
Kurtosis7.7717706
Mean1.5340909
Median Absolute Deviation (MAD)1
Skewness2.1888865
Sum135
Variance3.4471003
MonotonicityNot monotonic
2024-04-30T04:52:56.949433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 34
 
14.5%
2 17
 
7.3%
1 16
 
6.8%
3 12
 
5.1%
4 5
 
2.1%
5 2
 
0.9%
8 1
 
0.4%
11 1
 
0.4%
(Missing) 146
62.4%
ValueCountFrequency (%)
0 34
14.5%
1 16
6.8%
2 17
7.3%
3 12
 
5.1%
4 5
 
2.1%
5 2
 
0.9%
8 1
 
0.4%
11 1
 
0.4%
ValueCountFrequency (%)
11 1
 
0.4%
8 1
 
0.4%
5 2
 
0.9%
4 5
 
2.1%
3 12
 
5.1%
2 17
7.3%
1 16
6.8%
0 34
14.5%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)9.5%
Missing150
Missing (%)64.1%
Infinite0
Infinite (%)0.0%
Mean1.5714286
Minimum0
Maximum11
Zeros34
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:52:57.040031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9156031
Coefficient of variation (CV)1.2190202
Kurtosis6.8482135
Mean1.5714286
Median Absolute Deviation (MAD)1
Skewness2.0581355
Sum132
Variance3.6695353
MonotonicityNot monotonic
2024-04-30T04:52:57.121247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 34
 
14.5%
2 15
 
6.4%
1 13
 
5.6%
3 12
 
5.1%
4 6
 
2.6%
5 2
 
0.9%
8 1
 
0.4%
11 1
 
0.4%
(Missing) 150
64.1%
ValueCountFrequency (%)
0 34
14.5%
1 13
 
5.6%
2 15
6.4%
3 12
 
5.1%
4 6
 
2.6%
5 2
 
0.9%
8 1
 
0.4%
11 1
 
0.4%
ValueCountFrequency (%)
11 1
 
0.4%
8 1
 
0.4%
5 2
 
0.9%
4 6
 
2.6%
3 12
 
5.1%
2 15
6.4%
1 13
 
5.6%
0 34
14.5%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
173 
0
48 
1
 
12
3
 
1

Length

Max length4
Median length4
Mean length3.2179487
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 173
73.9%
0 48
 
20.5%
1 12
 
5.1%
3 1
 
0.4%

Length

2024-04-30T04:52:57.223193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:57.305740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 173
73.9%
0 48
 
20.5%
1 12
 
5.1%
3 1
 
0.4%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
176 
0
45 
1
 
12
3
 
1

Length

Max length4
Median length4
Mean length3.2564103
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
75.2%
0 45
 
19.2%
1 12
 
5.1%
3 1
 
0.4%

Length

2024-04-30T04:52:57.406365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:57.514665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
75.2%
0 45
 
19.2%
1 12
 
5.1%
3 1
 
0.4%

한실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
125 
<NA>
109 

Length

Max length4
Median length1
Mean length2.3974359
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 125
53.4%
<NA> 109
46.6%

Length

2024-04-30T04:52:57.616918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:57.700970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 125
53.4%
na 109
46.6%

양실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
125 
<NA>
109 

Length

Max length4
Median length1
Mean length2.3974359
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 125
53.4%
<NA> 109
46.6%

Length

2024-04-30T04:52:57.794467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:57.882478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 125
53.4%
na 109
46.6%

욕실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
125 
<NA>
109 

Length

Max length4
Median length1
Mean length2.3974359
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 125
53.4%
<NA> 109
46.6%

Length

2024-04-30T04:52:57.979665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:58.059489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 125
53.4%
na 109
46.6%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing60
Missing (%)25.6%
Memory size600.0 B
False
174 
(Missing)
60 
ValueCountFrequency (%)
False 174
74.4%
(Missing) 60
 
25.6%
2024-04-30T04:52:58.128012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
125 
<NA>
109 

Length

Max length4
Median length1
Mean length2.3974359
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 125
53.4%
<NA> 109
46.6%

Length

2024-04-30T04:52:58.212605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:58.308241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 125
53.4%
na 109
46.6%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing234
Missing (%)100.0%
Memory size2.2 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
202 
임대
32 

Length

Max length4
Median length4
Mean length3.7264957
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 202
86.3%
임대 32
 
13.7%

Length

2024-04-30T04:52:58.409009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:58.488589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
86.3%
임대 32
 
13.7%

세탁기수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
122 
<NA>
112 

Length

Max length4
Median length1
Mean length2.4358974
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 122
52.1%
<NA> 112
47.9%

Length

2024-04-30T04:52:58.576508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:58.660967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 122
52.1%
na 112
47.9%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
159 
0
73 
1
 
2

Length

Max length4
Median length4
Mean length3.0384615
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
67.9%
0 73
31.2%
1 2
 
0.9%

Length

2024-04-30T04:52:58.757240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:58.848606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 159
67.9%
0 73
31.2%
1 2
 
0.9%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
159 
0
73 
1
 
2

Length

Max length4
Median length4
Mean length3.0384615
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
67.9%
0 73
31.2%
1 2
 
0.9%

Length

2024-04-30T04:52:58.939313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:59.028237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 159
67.9%
0 73
31.2%
1 2
 
0.9%

회수건조수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
119 
0
115 

Length

Max length4
Median length4
Mean length2.525641
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 119
50.9%
0 115
49.1%

Length

2024-04-30T04:52:59.120886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:59.199608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 119
50.9%
0 115
49.1%

침대수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
122 
0
112 

Length

Max length4
Median length4
Mean length2.5641026
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 122
52.1%
0 112
47.9%

Length

2024-04-30T04:52:59.285249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:59.368714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 122
52.1%
0 112
47.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing53
Missing (%)22.6%
Memory size600.0 B
False
181 
(Missing)
53 
ValueCountFrequency (%)
False 181
77.4%
(Missing) 53
 
22.6%
2024-04-30T04:52:59.433738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031000003100000-206-1993-0156919930317<NA>1영업/정상1영업<NA><NA><NA><NA>02 9521206.00139809서울특별시 노원구 상계동 47-1서울특별시 노원구 덕릉로 862 (상계동)1641표석산업(주)2021-11-08 10:40:49U2021-11-10 02:40:00.0건물위생관리업207311.442537463369.008536건물위생관리업000000000N0<NA><NA><NA><NA>00000N
131000003100000-206-1993-0157019930726<NA>3폐업2폐업19990520<NA><NA><NA>02 9729037.00139804서울특별시 노원구 공릉동 408-4<NA><NA>인종개발(주)1999-05-24 00:00:00I2018-08-31 23:59:59.0건물위생관리업206895.205501458235.622434건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231000003100000-206-1993-0157119931119<NA>3폐업2폐업19981009<NA><NA><NA>02 9485555.00139230서울특별시 노원구 하계동 산 158-4<NA><NA>청지기용역2001-09-29 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331000003100000-206-1997-0157819970603<NA>3폐업2폐업19991221<NA><NA><NA>02 93935385,272.54139817서울특별시 노원구 상계동 328-0 동부빌딩 2,3층<NA><NA>(주)늘푸른환경1999-12-21 00:00:00I2018-08-31 23:59:59.0건물위생관리업<NA><NA>건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
431000003100000-206-1997-0157919970820<NA>3폐업2폐업20100429<NA><NA><NA>02 97713131,581.30139859서울특별시 노원구 중계동 435-1 현대상가 지하12호<NA><NA>서진환경2006-11-30 00:00:00I2018-08-31 23:59:59.0건물위생관리업206459.913629461503.621431건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531000003100000-206-1997-0158019971119<NA>1영업/정상1영업<NA><NA><NA><NA>02 9766282.00139800서울특별시 노원구 공릉동 271서울특별시 노원구 노원로1바길 1 (공릉동)1825지원산업(주)2021-11-08 10:34:21U2021-11-10 02:40:00.0건물위생관리업207039.860838457580.026243건물위생관리업000000000N0<NA><NA><NA><NA>00000N
631000003100000-206-1997-0158119971215<NA>1영업/정상1영업<NA><NA><NA><NA>02 931033640.96139810서울특별시 노원구 상계동 77-51 6구역 51블럭 1롯트 대림프라자 204호서울특별시 노원구 덕릉로 804 (상계동, 6구역 51블럭 1롯트 대림프라자 204호)1646가나안환경2021-12-23 09:44:45U2021-12-25 02:40:00.0건물위생관리업207008.092994462930.041769건물위생관리업000000000N0<NA><NA><NA><NA>00000N
731000003100000-206-1999-0158719990520<NA>3폐업2폐업20071129<NA><NA><NA>02 936533864.67139816서울특별시 노원구 상계동 387-113 지층<NA><NA>인동산업공사2005-12-15 00:00:00I2018-08-31 23:59:59.0건물위생관리업206133.719428461655.413213건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831000003100000-206-1999-0158819990726<NA>3폐업2폐업20081208<NA><NA><NA>02 938340510.80139816서울특별시 노원구 상계동 181-23 2층<NA><NA>신세기환경2005-11-16 00:00:00I2018-08-31 23:59:59.0건물위생관리업206172.996407461438.773254건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931000003100000-206-1999-0158919990520<NA>3폐업2폐업20050201<NA><NA><NA>02 9334007.00139814서울특별시 노원구 상계동 140-231 1층<NA><NA>동명실업2005-01-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업206415.14435462389.37092건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
22431000003100000-206-2023-000042023-08-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30139-240서울특별시 노원구 공릉동 513-48 주인맨션서울특별시 노원구 동일로184길 35, B1층 E-27호 (공릉동, 주인맨션)1844개미군단2023-08-16 15:38:09I2022-12-07 23:08:00.0건물위생관리업206594.474352458013.11984<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22531000003100000-206-2023-000052023-08-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.00139-938서울특별시 노원구 중계동 509-1 씨앤미복합빌딩서울특별시 노원구 동일로204가길 34, 씨앤미복합빌딩 916호 (중계동)1783올다종합시설관리2023-08-29 15:36:13I2022-12-07 21:01:00.0건물위생관리업205953.043736459822.608945<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22631000003100000-206-2023-000062023-10-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 984144240.00139-872서울특별시 노원구 하계동 276-6 유토피아빌딩서울특별시 노원구 공릉로63길 13, 유토피아빌딩 3층 311호 (하계동)1830창진공영(주)2023-10-16 15:02:37I2022-10-30 23:08:00.0건물위생관리업206156.733065459169.464921<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22731000003100000-206-2023-000072023-11-08<NA>3폐업2폐업2024-01-22<NA><NA><NA>02 3296605753.00139-872서울특별시 노원구 하계동 276-6 유토피아빌딩 206호서울특별시 노원구 공릉로63길 13, 유토피아빌딩 2층 206호 (하계동)1830(주)에스지공영2024-01-22 14:19:36U2023-11-30 22:04:00.0건물위생관리업206156.733065459169.464921<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22831000003100000-206-2023-000082023-06-22<NA>1영업/정상1영업<NA><NA><NA><NA>02 9789010130.16139-240서울특별시 노원구 공릉동 404-5 진서빌딩서울특별시 노원구 동일로173가길 133, 4층 (공릉동, 진서빌딩)1856주식회사 라인탑2024-04-16 14:07:33I2023-12-03 23:08:00.0건물위생관리업206255.363772457979.754321<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22931000003100000-206-2024-000012024-01-04<NA>1영업/정상1영업<NA><NA><NA><NA>0233995200433.00139-709서울특별시 노원구 중계동 506-1 건영옴니백화점서울특별시 노원구 섬밭로 258, 건영옴니백화점 B3층 4코아호 (중계동)1779모든서비스2024-01-04 13:37:26I2023-12-01 00:06:00.0건물위생관리업205645.891969459609.01251<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23031000003100000-206-2024-000022024-01-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.50139-739서울특별시 노원구 공릉동 742 효성아파트서울특별시 노원구 화랑로 556, 상가동 지하층 004호 (공릉동, 효성아파트)1804202브랜드2024-01-05 15:41:40I2023-12-01 00:07:00.0건물위생관리업207749.30758457640.840195<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23131000003100000-206-2024-000032024-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>44.00139-823서울특별시 노원구 상계동 651-7 합동빌딩서울특별시 노원구 동일로 1529, 합동빌딩 지1층 27호 (상계동)1620에코클린2024-01-10 14:14:07I2023-11-30 23:02:00.0건물위생관리업204986.23123462524.481662<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23231000003100000-206-2024-000042024-02-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.85139-813서울특별시 노원구 상계동 136-56서울특별시 노원구 한글비석로24라길 78, 1층 101호 (상계동)1657그린종합청소2024-02-13 15:42:53I2023-12-01 23:05:00.0건물위생관리업206116.892036462570.310952<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23331000003100000-206-2024-000052024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.86139-831서울특별시 노원구 상계동 764-1 하라프라자센타서울특별시 노원구 동일로 1323, 하라프라자센타 1층 109-1호 (상계동)1767제이에스2024-03-22 11:26:22I2023-12-02 22:04:00.0건물위생관리업205457.289886460487.443376<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>