Overview

Dataset statistics

Number of variables47
Number of observations606
Missing cells4929
Missing cells (%)17.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory239.2 KiB
Average record size in memory404.2 B

Variable types

Categorical24
Text7
DateTime4
Unsupported4
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-17964/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (89.0%)Imbalance
위생업태명 is highly imbalanced (78.7%)Imbalance
사용끝지상층 is highly imbalanced (56.8%)Imbalance
사용끝지하층 is highly imbalanced (80.3%)Imbalance
조건부허가시작일자 is highly imbalanced (98.2%)Imbalance
조건부허가종료일자 is highly imbalanced (98.2%)Imbalance
건물소유구분명 is highly imbalanced (58.2%)Imbalance
여성종사자수 is highly imbalanced (68.8%)Imbalance
남성종사자수 is highly imbalanced (79.2%)Imbalance
회수건조수 is highly imbalanced (52.4%)Imbalance
침대수 is highly imbalanced (51.9%)Imbalance
인허가취소일자 has 606 (100.0%) missing valuesMissing
폐업일자 has 97 (16.0%) missing valuesMissing
휴업시작일자 has 606 (100.0%) missing valuesMissing
휴업종료일자 has 606 (100.0%) missing valuesMissing
재개업일자 has 606 (100.0%) missing valuesMissing
전화번호 has 32 (5.3%) missing valuesMissing
도로명주소 has 367 (60.6%) missing valuesMissing
도로명우편번호 has 381 (62.9%) missing valuesMissing
좌표정보(X) has 108 (17.8%) missing valuesMissing
좌표정보(Y) has 108 (17.8%) missing valuesMissing
건물지상층수 has 216 (35.6%) missing valuesMissing
발한실여부 has 35 (5.8%) missing valuesMissing
조건부허가신고사유 has 605 (99.8%) missing valuesMissing
세탁기수 has 520 (85.8%) missing valuesMissing
다중이용업소여부 has 35 (5.8%) 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
소재지면적 has 68 (11.2%) zerosZeros
건물지상층수 has 287 (47.4%) zerosZeros
세탁기수 has 16 (2.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:19:47.510084
Analysis finished2024-05-11 06:19:48.986168
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3120000
606 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 606
100.0%

Length

2024-05-11T15:19:49.383151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:49.525468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 606
100.0%

관리번호
Text

UNIQUE 

Distinct606
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:19:49.807587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13332
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

Unique606 ?
Unique (%)100.0%

Sample

1st row3120000-205-1982-00832
2nd row3120000-205-1982-00839
3rd row3120000-205-1987-00701
4th row3120000-205-1987-00702
5th row3120000-205-1987-00703
ValueCountFrequency (%)
3120000-205-1982-00832 1
 
0.2%
3120000-205-1997-02171 1
 
0.2%
3120000-205-1997-02174 1
 
0.2%
3120000-205-1997-02175 1
 
0.2%
3120000-205-1997-02203 1
 
0.2%
3120000-205-1997-02204 1
 
0.2%
3120000-205-1998-00899 1
 
0.2%
3120000-205-1998-00901 1
 
0.2%
3120000-205-1998-00902 1
 
0.2%
3120000-205-1998-00903 1
 
0.2%
Other values (596) 596
98.3%
2024-05-11T15:19:50.402155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4714
35.4%
- 1818
 
13.6%
2 1710
 
12.8%
1 1480
 
11.1%
9 897
 
6.7%
3 763
 
5.7%
5 755
 
5.7%
8 491
 
3.7%
7 408
 
3.1%
4 167
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11514
86.4%
Dash Punctuation 1818
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4714
40.9%
2 1710
 
14.9%
1 1480
 
12.9%
9 897
 
7.8%
3 763
 
6.6%
5 755
 
6.6%
8 491
 
4.3%
7 408
 
3.5%
4 167
 
1.5%
6 129
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1818
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4714
35.4%
- 1818
 
13.6%
2 1710
 
12.8%
1 1480
 
11.1%
9 897
 
6.7%
3 763
 
5.7%
5 755
 
5.7%
8 491
 
3.7%
7 408
 
3.1%
4 167
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4714
35.4%
- 1818
 
13.6%
2 1710
 
12.8%
1 1480
 
11.1%
9 897
 
6.7%
3 763
 
5.7%
5 755
 
5.7%
8 491
 
3.7%
7 408
 
3.1%
4 167
 
1.3%

인허가일자
Date

Distinct376
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1982-05-07 00:00:00
Maximum2023-07-05 00:00:00
2024-05-11T15:19:50.642479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:50.892542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing606
Missing (%)100.0%
Memory size5.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
509 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 509
84.0%
1 97
 
16.0%

Length

2024-05-11T15:19:51.072663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:51.205659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 509
84.0%
1 97
 
16.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
509 
영업/정상
97 

Length

Max length5
Median length2
Mean length2.480198
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 509
84.0%
영업/정상 97
 
16.0%

Length

2024-05-11T15:19:51.359988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:51.515948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 509
84.0%
영업/정상 97
 
16.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2
509 
1
97 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 509
84.0%
1 97
 
16.0%

Length

2024-05-11T15:19:51.679605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:51.857083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 509
84.0%
1 97
 
16.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
509 
영업
97 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 509
84.0%
영업 97
 
16.0%

Length

2024-05-11T15:19:52.036196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:52.210048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 509
84.0%
영업 97
 
16.0%

폐업일자
Date

MISSING 

Distinct392
Distinct (%)77.0%
Missing97
Missing (%)16.0%
Memory size4.9 KiB
Minimum1988-01-01 00:00:00
Maximum2024-03-08 00:00:00
2024-05-11T15:19:52.482892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:52.729187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing606
Missing (%)100.0%
Memory size5.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing606
Missing (%)100.0%
Memory size5.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing606
Missing (%)100.0%
Memory size5.5 KiB

전화번호
Text

MISSING 

Distinct536
Distinct (%)93.4%
Missing32
Missing (%)5.3%
Memory size4.9 KiB
2024-05-11T15:19:53.127414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8675958
Min length2

Characters and Unicode

Total characters5664
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

Unique508 ?
Unique (%)88.5%

Sample

1st row02 3247135
2nd row0200000000
3rd row02 3025089
4th row0203744764
5th row0203032684
ValueCountFrequency (%)
02 318
35.3%
0200000000 7
 
0.8%
3799887 4
 
0.4%
3739176 4
 
0.4%
3652990 3
 
0.3%
0 3
 
0.3%
3765358 3
 
0.3%
3230133 2
 
0.2%
3098482 2
 
0.2%
3747921 2
 
0.2%
Other values (528) 554
61.4%
2024-05-11T15:19:53.723507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1195
21.1%
3 974
17.2%
2 943
16.6%
7 400
 
7.1%
350
 
6.2%
9 347
 
6.1%
6 339
 
6.0%
4 311
 
5.5%
1 287
 
5.1%
5 280
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5314
93.8%
Space Separator 350
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1195
22.5%
3 974
18.3%
2 943
17.7%
7 400
 
7.5%
9 347
 
6.5%
6 339
 
6.4%
4 311
 
5.9%
1 287
 
5.4%
5 280
 
5.3%
8 238
 
4.5%
Space Separator
ValueCountFrequency (%)
350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5664
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1195
21.1%
3 974
17.2%
2 943
16.6%
7 400
 
7.1%
350
 
6.2%
9 347
 
6.1%
6 339
 
6.0%
4 311
 
5.5%
1 287
 
5.1%
5 280
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1195
21.1%
3 974
17.2%
2 943
16.6%
7 400
 
7.1%
350
 
6.2%
9 347
 
6.1%
6 339
 
6.0%
4 311
 
5.5%
1 287
 
5.1%
5 280
 
4.9%

소재지면적
Real number (ℝ)

ZEROS 

Distinct381
Distinct (%)63.0%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean34.85757
Minimum0
Maximum958.88
Zeros68
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:19:53.977034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113.65
median20.8
Q330.09
95-th percentile78.36
Maximum958.88
Range958.88
Interquartile range (IQR)16.44

Descriptive statistics

Standard deviation78.540702
Coefficient of variation (CV)2.2531892
Kurtosis71.929206
Mean34.85757
Median Absolute Deviation (MAD)8.2
Skewness7.8186252
Sum21088.83
Variance6168.6419
MonotonicityNot monotonic
2024-05-11T15:19:54.222357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 68
 
11.2%
33.0 15
 
2.5%
26.4 11
 
1.8%
23.1 8
 
1.3%
30.0 7
 
1.2%
19.8 6
 
1.0%
12.6 6
 
1.0%
16.5 5
 
0.8%
21.0 5
 
0.8%
23.11 4
 
0.7%
Other values (371) 470
77.6%
ValueCountFrequency (%)
0.0 68
11.2%
6.6 1
 
0.2%
6.82 1
 
0.2%
8.05 1
 
0.2%
9.0 1
 
0.2%
9.3 1
 
0.2%
9.57 1
 
0.2%
9.86 1
 
0.2%
9.9 3
 
0.5%
9.92 1
 
0.2%
ValueCountFrequency (%)
958.88 1
0.2%
893.0 1
0.2%
659.84 1
0.2%
573.86 1
0.2%
524.34 1
0.2%
517.14 1
0.2%
492.27 1
0.2%
428.03 1
0.2%
353.75 1
0.2%
255.0 1
0.2%

소재지우편번호
Text

Distinct93
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:19:54.611197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.019802
Min length6

Characters and Unicode

Total characters3648
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

Unique21 ?
Unique (%)3.5%

Sample

1st row120825
2nd row120817
3rd row120848
4th row120848
5th row120814
ValueCountFrequency (%)
120805 28
 
4.6%
120100 24
 
4.0%
120848 19
 
3.1%
120841 19
 
3.1%
120807 18
 
3.0%
120810 17
 
2.8%
120806 16
 
2.6%
120827 16
 
2.6%
120802 15
 
2.5%
120857 15
 
2.5%
Other values (83) 419
69.1%
2024-05-11T15:19:55.229539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 957
26.2%
1 835
22.9%
2 729
20.0%
8 534
14.6%
5 126
 
3.5%
4 118
 
3.2%
3 99
 
2.7%
6 96
 
2.6%
7 90
 
2.5%
9 52
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3636
99.7%
Dash Punctuation 12
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 957
26.3%
1 835
23.0%
2 729
20.0%
8 534
14.7%
5 126
 
3.5%
4 118
 
3.2%
3 99
 
2.7%
6 96
 
2.6%
7 90
 
2.5%
9 52
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 957
26.2%
1 835
22.9%
2 729
20.0%
8 534
14.6%
5 126
 
3.5%
4 118
 
3.2%
3 99
 
2.7%
6 96
 
2.6%
7 90
 
2.5%
9 52
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 957
26.2%
1 835
22.9%
2 729
20.0%
8 534
14.6%
5 126
 
3.5%
4 118
 
3.2%
3 99
 
2.7%
6 96
 
2.6%
7 90
 
2.5%
9 52
 
1.4%

지번주소
Text

Distinct562
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:19:55.529842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length46
Mean length25.665017
Min length17

Characters and Unicode

Total characters15553
Distinct characters158
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

Unique521 ?
Unique (%)86.0%

Sample

1st row서울특별시 서대문구 연희동 106-3번지
2nd row서울특별시 서대문구 북가좌동 420-33번지
3rd row서울특별시 서대문구 홍은동 395-18번지
4th row서울특별시 서대문구 홍은동 407-19번지
5th row서울특별시 서대문구 북가좌동 317-17번지
ValueCountFrequency (%)
서울특별시 606
22.9%
서대문구 606
22.9%
남가좌동 112
 
4.2%
북가좌동 97
 
3.7%
홍은동 93
 
3.5%
홍제동 83
 
3.1%
북아현동 64
 
2.4%
연희동 63
 
2.4%
1층 36
 
1.4%
창천동 20
 
0.8%
Other values (682) 869
32.8%
2024-05-11T15:19:56.046044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2604
 
16.7%
서 1212
 
7.8%
대 642
 
4.1%
동 630
 
4.1%
문 612
 
3.9%
구 610
 
3.9%
울 609
 
3.9%
시 608
 
3.9%
별 607
 
3.9%
특 606
 
3.9%
Other values (148) 6813
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9359
60.2%
Decimal Number 2903
 
18.7%
Space Separator 2604
 
16.7%
Dash Punctuation 527
 
3.4%
Close Punctuation 49
 
0.3%
Open Punctuation 48
 
0.3%
Uppercase Letter 41
 
0.3%
Other Punctuation 17
 
0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1212
13.0%
대 642
 
6.9%
동 630
 
6.7%
문 612
 
6.5%
구 610
 
6.5%
울 609
 
6.5%
시 608
 
6.5%
별 607
 
6.5%
특 606
 
6.5%
지 578
 
6.2%
Other values (117) 2645
28.3%
Decimal Number
ValueCountFrequency (%)
1 586
20.2%
2 420
14.5%
3 378
13.0%
4 290
10.0%
0 268
9.2%
5 245
8.4%
7 186
 
6.4%
6 184
 
6.3%
9 176
 
6.1%
8 170
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 20
48.8%
B 6
 
14.6%
D 3
 
7.3%
M 3
 
7.3%
C 3
 
7.3%
P 2
 
4.9%
T 2
 
4.9%
S 1
 
2.4%
K 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
c 2
40.0%
e 1
20.0%
d 1
20.0%
m 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 48
98.0%
] 1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 47
97.9%
[ 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 14
82.4%
. 3
 
17.6%
Space Separator
ValueCountFrequency (%)
2604
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 527
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9359
60.2%
Common 6148
39.5%
Latin 46
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1212
13.0%
대 642
 
6.9%
동 630
 
6.7%
문 612
 
6.5%
구 610
 
6.5%
울 609
 
6.5%
시 608
 
6.5%
별 607
 
6.5%
특 606
 
6.5%
지 578
 
6.2%
Other values (117) 2645
28.3%
Common
ValueCountFrequency (%)
2604
42.4%
1 586
 
9.5%
- 527
 
8.6%
2 420
 
6.8%
3 378
 
6.1%
4 290
 
4.7%
0 268
 
4.4%
5 245
 
4.0%
7 186
 
3.0%
6 184
 
3.0%
Other values (8) 460
 
7.5%
Latin
ValueCountFrequency (%)
A 20
43.5%
B 6
 
13.0%
D 3
 
6.5%
M 3
 
6.5%
C 3
 
6.5%
c 2
 
4.3%
P 2
 
4.3%
T 2
 
4.3%
e 1
 
2.2%
d 1
 
2.2%
Other values (3) 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9359
60.2%
ASCII 6194
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2604
42.0%
1 586
 
9.5%
- 527
 
8.5%
2 420
 
6.8%
3 378
 
6.1%
4 290
 
4.7%
0 268
 
4.3%
5 245
 
4.0%
7 186
 
3.0%
6 184
 
3.0%
Other values (21) 506
 
8.2%
Hangul
ValueCountFrequency (%)
서 1212
13.0%
대 642
 
6.9%
동 630
 
6.7%
문 612
 
6.5%
구 610
 
6.5%
울 609
 
6.5%
시 608
 
6.5%
별 607
 
6.5%
특 606
 
6.5%
지 578
 
6.2%
Other values (117) 2645
28.3%

도로명주소
Text

MISSING 

Distinct238
Distinct (%)99.6%
Missing367
Missing (%)60.6%
Memory size4.9 KiB
2024-05-11T15:19:56.494730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length32.158996
Min length23

Characters and Unicode

Total characters7686
Distinct characters178
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

Unique237 ?
Unique (%)99.2%

Sample

1st row서울특별시 서대문구 증가로 49 (연희동)
2nd row서울특별시 서대문구 가좌로 50 (홍은동)
3rd row서울특별시 서대문구 거북골로22길 9-7 (북가좌동)
4th row서울특별시 서대문구 응암로 128-6 (북가좌동)
5th row서울특별시 서대문구 증가로 232 (북가좌동)
ValueCountFrequency (%)
서울특별시 239
 
17.0%
서대문구 239
 
17.0%
1층 38
 
2.7%
북가좌동 34
 
2.4%
홍은동 34
 
2.4%
홍제동 32
 
2.3%
연희동 28
 
2.0%
남가좌동 20
 
1.4%
북아현동 15
 
1.1%
창천동 11
 
0.8%
Other values (425) 714
50.9%
2024-05-11T15:19:57.236511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1165
 
15.2%
서 486
 
6.3%
1 288
 
3.7%
대 279
 
3.6%
동 270
 
3.5%
( 267
 
3.5%
) 267
 
3.5%
문 259
 
3.4%
울 253
 
3.3%
구 242
 
3.1%
Other values (168) 3910
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4647
60.5%
Space Separator 1165
 
15.2%
Decimal Number 1097
 
14.3%
Open Punctuation 268
 
3.5%
Close Punctuation 268
 
3.5%
Other Punctuation 165
 
2.1%
Dash Punctuation 42
 
0.5%
Uppercase Letter 29
 
0.4%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 486
 
10.5%
대 279
 
6.0%
동 270
 
5.8%
문 259
 
5.6%
울 253
 
5.4%
구 242
 
5.2%
시 242
 
5.2%
별 240
 
5.2%
특 239
 
5.1%
로 205
 
4.4%
Other values (139) 1932
41.6%
Decimal Number
ValueCountFrequency (%)
1 288
26.3%
2 177
16.1%
3 144
13.1%
0 113
 
10.3%
4 96
 
8.8%
5 61
 
5.6%
6 60
 
5.5%
8 57
 
5.2%
9 55
 
5.0%
7 46
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 7
24.1%
B 7
24.1%
C 5
17.2%
D 4
13.8%
M 4
13.8%
S 1
 
3.4%
K 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
d 1
20.0%
m 1
20.0%
c 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 267
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 267
99.6%
] 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 163
98.8%
. 2
 
1.2%
Space Separator
ValueCountFrequency (%)
1165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4647
60.5%
Common 3005
39.1%
Latin 34
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 486
 
10.5%
대 279
 
6.0%
동 270
 
5.8%
문 259
 
5.6%
울 253
 
5.4%
구 242
 
5.2%
시 242
 
5.2%
별 240
 
5.2%
특 239
 
5.1%
로 205
 
4.4%
Other values (139) 1932
41.6%
Common
ValueCountFrequency (%)
1165
38.8%
1 288
 
9.6%
( 267
 
8.9%
) 267
 
8.9%
2 177
 
5.9%
, 163
 
5.4%
3 144
 
4.8%
0 113
 
3.8%
4 96
 
3.2%
5 61
 
2.0%
Other values (8) 264
 
8.8%
Latin
ValueCountFrequency (%)
A 7
20.6%
B 7
20.6%
C 5
14.7%
D 4
11.8%
M 4
11.8%
e 2
 
5.9%
d 1
 
2.9%
m 1
 
2.9%
c 1
 
2.9%
S 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4647
60.5%
ASCII 3039
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1165
38.3%
1 288
 
9.5%
( 267
 
8.8%
) 267
 
8.8%
2 177
 
5.8%
, 163
 
5.4%
3 144
 
4.7%
0 113
 
3.7%
4 96
 
3.2%
5 61
 
2.0%
Other values (19) 298
 
9.8%
Hangul
ValueCountFrequency (%)
서 486
 
10.5%
대 279
 
6.0%
동 270
 
5.8%
문 259
 
5.6%
울 253
 
5.4%
구 242
 
5.2%
시 242
 
5.2%
별 240
 
5.2%
특 239
 
5.1%
로 205
 
4.4%
Other values (139) 1932
41.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct128
Distinct (%)56.9%
Missing381
Missing (%)62.9%
Infinite0
Infinite (%)0.0%
Mean3692.6222
Minimum3600
Maximum3791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:19:57.551988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3600
5-th percentile3611
Q13650
median3693
Q33733
95-th percentile3780.8
Maximum3791
Range191
Interquartile range (IQR)83

Descriptive statistics

Standard deviation52.501313
Coefficient of variation (CV)0.014217895
Kurtosis-0.99018934
Mean3692.6222
Median Absolute Deviation (MAD)41
Skewness0.036812931
Sum830840
Variance2756.3879
MonotonicityNot monotonic
2024-05-11T15:19:57.822240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3709 5
 
0.8%
3714 5
 
0.8%
3622 5
 
0.8%
3665 4
 
0.7%
3615 4
 
0.7%
3786 3
 
0.5%
3601 3
 
0.5%
3700 3
 
0.5%
3660 3
 
0.5%
3725 3
 
0.5%
Other values (118) 187
30.9%
(Missing) 381
62.9%
ValueCountFrequency (%)
3600 1
 
0.2%
3601 3
0.5%
3602 1
 
0.2%
3605 1
 
0.2%
3606 3
0.5%
3607 1
 
0.2%
3610 1
 
0.2%
3611 2
0.3%
3612 2
0.3%
3615 4
0.7%
ValueCountFrequency (%)
3791 2
0.3%
3789 1
 
0.2%
3786 3
0.5%
3785 1
 
0.2%
3783 2
0.3%
3782 1
 
0.2%
3781 2
0.3%
3780 2
0.3%
3779 2
0.3%
3778 1
 
0.2%

사업장명
Text

Distinct416
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T15:19:58.323666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length4.3118812
Min length2

Characters and Unicode

Total characters2613
Distinct characters263
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique333 ?
Unique (%)55.0%

Sample

1st row미조컴퓨터크리닝
2nd row기쁨사
3rd row현대사
4th row홍남사
5th row백왕사
ValueCountFrequency (%)
백양사 14
 
2.2%
현대사 13
 
2.1%
현대세탁 10
 
1.6%
월풀빨래방 8
 
1.3%
일광사 8
 
1.3%
백영사 8
 
1.3%
제일사 7
 
1.1%
백조사 7
 
1.1%
셀프크리닝 6
 
1.0%
백광사 6
 
1.0%
Other values (413) 537
86.1%
2024-05-11T15:19:59.068323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 326
 
12.5%
세 187
 
7.2%
탁 178
 
6.8%
소 110
 
4.2%
백 70
 
2.7%
크 64
 
2.4%
대 62
 
2.4%
리 58
 
2.2%
닝 51
 
2.0%
미 51
 
2.0%
Other values (253) 1456
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2560
98.0%
Space Separator 18
 
0.7%
Decimal Number 17
 
0.7%
Uppercase Letter 10
 
0.4%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 326
 
12.7%
세 187
 
7.3%
탁 178
 
7.0%
소 110
 
4.3%
백 70
 
2.7%
크 64
 
2.5%
대 62
 
2.4%
리 58
 
2.3%
닝 51
 
2.0%
미 51
 
2.0%
Other values (236) 1403
54.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
K 2
20.0%
T 1
10.0%
H 1
10.0%
A 1
10.0%
W 1
10.0%
E 1
10.0%
M 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 7
41.2%
3 3
17.6%
5 3
17.6%
9 2
 
11.8%
6 1
 
5.9%
2 1
 
5.9%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2560
98.0%
Common 43
 
1.6%
Latin 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 326
 
12.7%
세 187
 
7.3%
탁 178
 
7.0%
소 110
 
4.3%
백 70
 
2.7%
크 64
 
2.5%
대 62
 
2.4%
리 58
 
2.3%
닝 51
 
2.0%
미 51
 
2.0%
Other values (236) 1403
54.8%
Common
ValueCountFrequency (%)
18
41.9%
1 7
 
16.3%
) 4
 
9.3%
( 4
 
9.3%
3 3
 
7.0%
5 3
 
7.0%
9 2
 
4.7%
6 1
 
2.3%
2 1
 
2.3%
Latin
ValueCountFrequency (%)
S 2
20.0%
K 2
20.0%
T 1
10.0%
H 1
10.0%
A 1
10.0%
W 1
10.0%
E 1
10.0%
M 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2560
98.0%
ASCII 53
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 326
 
12.7%
세 187
 
7.3%
탁 178
 
7.0%
소 110
 
4.3%
백 70
 
2.7%
크 64
 
2.5%
대 62
 
2.4%
리 58
 
2.3%
닝 51
 
2.0%
미 51
 
2.0%
Other values (236) 1403
54.8%
ASCII
ValueCountFrequency (%)
18
34.0%
1 7
 
13.2%
) 4
 
7.5%
( 4
 
7.5%
3 3
 
5.7%
5 3
 
5.7%
S 2
 
3.8%
K 2
 
3.8%
9 2
 
3.8%
T 1
 
1.9%
Other values (7) 7
 
13.2%

최종수정일자
Date

Distinct332
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2001-12-06 00:00:00
Maximum2024-03-08 16:08:37
2024-05-11T15:19:59.312085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:59.585175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
I
503 
U
103 

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 503
83.0%
U 103
 
17.0%

Length

2024-05-11T15:19:59.852881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:00.133596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 503
83.0%
u 103
 
17.0%

데이터갱신일자
Date

Distinct89
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 23:00:00
2024-05-11T15:20:00.335220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:00.577327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반세탁업
589 
빨래방업
 
9
운동화전문세탁업
 
7
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length5.0214521
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 589
97.2%
빨래방업 9
 
1.5%
운동화전문세탁업 7
 
1.2%
세탁업 기타 1
 
0.2%

Length

2024-05-11T15:20:00.821813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:01.009658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 589
97.0%
빨래방업 9
 
1.5%
운동화전문세탁업 7
 
1.2%
세탁업 1
 
0.2%
기타 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct408
Distinct (%)81.9%
Missing108
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean194295.44
Minimum191540.26
Maximum197144.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:20:01.197142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191540.26
5-th percentile192009.96
Q1193140.89
median194304.41
Q3195443.58
95-th percentile196486.16
Maximum197144.02
Range5603.7549
Interquartile range (IQR)2302.6964

Descriptive statistics

Standard deviation1423.3727
Coefficient of variation (CV)0.0073258162
Kurtosis-1.077553
Mean194295.44
Median Absolute Deviation (MAD)1143.0418
Skewness-0.08270554
Sum96759131
Variance2025989.9
MonotonicityNot monotonic
2024-05-11T15:20:01.453909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192260.299912091 5
 
0.8%
191900.345924872 5
 
0.8%
196111.168694145 4
 
0.7%
195057.033841623 4
 
0.7%
195586.623870384 4
 
0.7%
191604.289576468 3
 
0.5%
192874.514454351 3
 
0.5%
195723.539073553 3
 
0.5%
195163.355584401 3
 
0.5%
194754.676374401 3
 
0.5%
Other values (398) 461
76.1%
(Missing) 108
 
17.8%
ValueCountFrequency (%)
191540.260492627 2
0.3%
191552.612967645 2
0.3%
191576.039193146 2
0.3%
191604.289576468 3
0.5%
191705.251436204 1
 
0.2%
191725.089590592 1
 
0.2%
191765.349284486 1
 
0.2%
191793.47656279 2
0.3%
191798.272173715 1
 
0.2%
191806.114698627 1
 
0.2%
ValueCountFrequency (%)
197144.015440398 1
0.2%
197086.878372168 1
0.2%
197071.295879678 1
0.2%
197036.034948766 1
0.2%
196945.454641052 2
0.3%
196892.09236853 1
0.2%
196822.991861785 1
0.2%
196762.710442635 1
0.2%
196753.553383122 1
0.2%
196739.979206517 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct408
Distinct (%)81.9%
Missing108
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean452760.68
Minimum450392.77
Maximum455710.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:20:01.749726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450392.77
5-th percentile450644.44
Q1451681.1
median452829.59
Q3453653.99
95-th percentile455145.33
Maximum455710.43
Range5317.6558
Interquartile range (IQR)1972.8923

Descriptive statistics

Standard deviation1343.9118
Coefficient of variation (CV)0.0029682609
Kurtosis-0.80408788
Mean452760.68
Median Absolute Deviation (MAD)961.14759
Skewness0.089257426
Sum2.2547482 × 108
Variance1806099
MonotonicityNot monotonic
2024-05-11T15:20:02.415316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452692.508806554 5
 
0.8%
452626.221252439 5
 
0.8%
452194.834634239 4
 
0.7%
454786.019433577 4
 
0.7%
453692.90633961 4
 
0.7%
452508.067716791 3
 
0.5%
452525.219515622 3
 
0.5%
454754.899472127 3
 
0.5%
454725.816505084 3
 
0.5%
454078.028449131 3
 
0.5%
Other values (398) 461
76.1%
(Missing) 108
 
17.8%
ValueCountFrequency (%)
450392.774100774 1
0.2%
450404.411213779 1
0.2%
450432.176153874 1
0.2%
450482.852899186 1
0.2%
450496.933830942 1
0.2%
450528.914374025 1
0.2%
450546.535234295 1
0.2%
450563.335982259 1
0.2%
450573.690449065 1
0.2%
450580.868612383 2
0.3%
ValueCountFrequency (%)
455710.429910779 1
0.2%
455611.934791501 1
0.2%
455588.317096857 2
0.3%
455521.138091877 1
0.2%
455510.91644523 2
0.3%
455472.258286059 1
0.2%
455430.406456381 1
0.2%
455414.392407621 1
0.2%
455337.489991811 1
0.2%
455323.028921961 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
일반세탁업
558 
<NA>
 
35
빨래방업
 
7
운동화전문세탁업
 
5
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.9570957
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 558
92.1%
<NA> 35
 
5.8%
빨래방업 7
 
1.2%
운동화전문세탁업 5
 
0.8%
세탁업 기타 1
 
0.2%

Length

2024-05-11T15:20:02.735613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:02.961512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 558
91.9%
na 35
 
5.8%
빨래방업 7
 
1.2%
운동화전문세탁업 5
 
0.8%
세탁업 1
 
0.2%
기타 1
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)2.6%
Missing216
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean0.81538462
Minimum0
Maximum15
Zeros287
Zeros (%)47.4%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:20:03.114719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7656445
Coefficient of variation (CV)2.1654131
Kurtosis22.720193
Mean0.81538462
Median Absolute Deviation (MAD)0
Skewness3.8287448
Sum318
Variance3.1175005
MonotonicityNot monotonic
2024-05-11T15:20:03.300843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 287
47.4%
3 35
 
5.8%
2 32
 
5.3%
1 12
 
2.0%
4 12
 
2.0%
5 7
 
1.2%
15 2
 
0.3%
8 1
 
0.2%
6 1
 
0.2%
10 1
 
0.2%
(Missing) 216
35.6%
ValueCountFrequency (%)
0 287
47.4%
1 12
 
2.0%
2 32
 
5.3%
3 35
 
5.8%
4 12
 
2.0%
5 7
 
1.2%
6 1
 
0.2%
8 1
 
0.2%
10 1
 
0.2%
15 2
 
0.3%
ValueCountFrequency (%)
15 2
 
0.3%
10 1
 
0.2%
8 1
 
0.2%
6 1
 
0.2%
5 7
 
1.2%
4 12
 
2.0%
3 35
 
5.8%
2 32
 
5.3%
1 12
 
2.0%
0 287
47.4%

건물지하층수
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
292 
<NA>
258 
1
50 
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length2.2772277
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 292
48.2%
<NA> 258
42.6%
1 50
 
8.3%
2 3
 
0.5%
3 2
 
0.3%
6 1
 
0.2%

Length

2024-05-11T15:20:03.562603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:03.785629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 292
48.2%
na 258
42.6%
1 50
 
8.3%
2 3
 
0.5%
3 2
 
0.3%
6 1
 
0.2%

사용시작지상층
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
241 
<NA>
237 
1
110 
2
 
17
3
 
1

Length

Max length4
Median length1
Mean length2.1732673
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 241
39.8%
<NA> 237
39.1%
1 110
18.2%
2 17
 
2.8%
3 1
 
0.2%

Length

2024-05-11T15:20:04.035416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:04.356319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 241
39.8%
na 237
39.1%
1 110
18.2%
2 17
 
2.8%
3 1
 
0.2%

사용끝지상층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
470 
1
105 
0
 
15
2
 
15
3
 
1

Length

Max length4
Median length4
Mean length3.3267327
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 470
77.6%
1 105
 
17.3%
0 15
 
2.5%
2 15
 
2.5%
3 1
 
0.2%

Length

2024-05-11T15:20:04.573877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:04.808284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 470
77.6%
1 105
 
17.3%
0 15
 
2.5%
2 15
 
2.5%
3 1
 
0.2%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
343 
0
245 
1
 
17
2
 
1

Length

Max length4
Median length4
Mean length2.6980198
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 343
56.6%
0 245
40.4%
1 17
 
2.8%
2 1
 
0.2%

Length

2024-05-11T15:20:05.069363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:05.259216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
56.6%
0 245
40.4%
1 17
 
2.8%
2 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
570 
0
 
19
1
 
16
2
 
1

Length

Max length4
Median length4
Mean length3.8217822
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 570
94.1%
0 19
 
3.1%
1 16
 
2.6%
2 1
 
0.2%

Length

2024-05-11T15:20:05.467788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:05.680749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 570
94.1%
0 19
 
3.1%
1 16
 
2.6%
2 1
 
0.2%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
306 
<NA>
300 

Length

Max length4
Median length1
Mean length2.4851485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 306
50.5%
<NA> 300
49.5%

Length

2024-05-11T15:20:05.927589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:06.126434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 306
50.5%
na 300
49.5%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
306 
<NA>
300 

Length

Max length4
Median length1
Mean length2.4851485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 306
50.5%
<NA> 300
49.5%

Length

2024-05-11T15:20:06.349027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:06.546464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 306
50.5%
na 300
49.5%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
306 
<NA>
300 

Length

Max length4
Median length1
Mean length2.4851485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 306
50.5%
<NA> 300
49.5%

Length

2024-05-11T15:20:06.817600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:07.028999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 306
50.5%
na 300
49.5%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing35
Missing (%)5.8%
Memory size1.3 KiB
False
571 
(Missing)
 
35
ValueCountFrequency (%)
False 571
94.2%
(Missing) 35
 
5.8%
2024-05-11T15:20:07.206504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
0
306 
<NA>
299 
3
 
1

Length

Max length4
Median length1
Mean length2.480198
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 306
50.5%
<NA> 299
49.3%
3 1
 
0.2%

Length

2024-05-11T15:20:07.433068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:07.678154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 306
50.5%
na 299
49.3%
3 1
 
0.2%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing605
Missing (%)99.8%
Memory size4.9 KiB
2024-05-11T15:20:07.936468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row주택과-2366(2007.2.8)호[준공인가전 사용허가 기간연장 승인]
ValueCountFrequency (%)
주택과-2366(2007.2.8)호[준공인가전 1
25.0%
사용허가 1
25.0%
기간연장 1
25.0%
승인 1
25.0%
2024-05-11T15:20:08.414063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
 
7.7%
2 3
 
7.7%
0 2
 
5.1%
6 2
 
5.1%
. 2
 
5.1%
인 2
 
5.1%
가 2
 
5.1%
간 1
 
2.6%
연 1
 
2.6%
기 1
 
2.6%
Other values (20) 20
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19
48.7%
Decimal Number 10
25.6%
Space Separator 3
 
7.7%
Other Punctuation 2
 
5.1%
Open Punctuation 2
 
5.1%
Close Punctuation 2
 
5.1%
Dash Punctuation 1
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 2
 
10.5%
가 2
 
10.5%
간 1
 
5.3%
연 1
 
5.3%
기 1
 
5.3%
장 1
 
5.3%
허 1
 
5.3%
용 1
 
5.3%
사 1
 
5.3%
승 1
 
5.3%
Other values (7) 7
36.8%
Decimal Number
ValueCountFrequency (%)
2 3
30.0%
0 2
20.0%
6 2
20.0%
8 1
 
10.0%
7 1
 
10.0%
3 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
50.0%
( 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 1
50.0%
] 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
51.3%
Hangul 19
48.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 2
 
10.5%
가 2
 
10.5%
간 1
 
5.3%
연 1
 
5.3%
기 1
 
5.3%
장 1
 
5.3%
허 1
 
5.3%
용 1
 
5.3%
사 1
 
5.3%
승 1
 
5.3%
Other values (7) 7
36.8%
Common
ValueCountFrequency (%)
3
15.0%
2 3
15.0%
0 2
10.0%
6 2
10.0%
. 2
10.0%
[ 1
 
5.0%
) 1
 
5.0%
8 1
 
5.0%
7 1
 
5.0%
( 1
 
5.0%
Other values (3) 3
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
51.3%
Hangul 19
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
15.0%
2 3
15.0%
0 2
10.0%
6 2
10.0%
. 2
10.0%
[ 1
 
5.0%
) 1
 
5.0%
8 1
 
5.0%
7 1
 
5.0%
( 1
 
5.0%
Other values (3) 3
15.0%
Hangul
ValueCountFrequency (%)
인 2
 
10.5%
가 2
 
10.5%
간 1
 
5.3%
연 1
 
5.3%
기 1
 
5.3%
장 1
 
5.3%
허 1
 
5.3%
용 1
 
5.3%
사 1
 
5.3%
승 1
 
5.3%
Other values (7) 7
36.8%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
605 
20071224
 
1

Length

Max length8
Median length4
Mean length4.0066007
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 605
99.8%
20071224 1
 
0.2%

Length

2024-05-11T15:20:08.678719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:08.895539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 605
99.8%
20071224 1
 
0.2%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
605 
20080211
 
1

Length

Max length8
Median length4
Mean length4.0066007
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 605
99.8%
20080211 1
 
0.2%

Length

2024-05-11T15:20:09.099990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:09.283265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 605
99.8%
20080211 1
 
0.2%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
515 
임대
85 
자가
 
6

Length

Max length4
Median length4
Mean length3.69967
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> 515
85.0%
임대 85
 
14.0%
자가 6
 
1.0%

Length

2024-05-11T15:20:09.485226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:09.695225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 515
85.0%
임대 85
 
14.0%
자가 6
 
1.0%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.0%
Missing520
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean1.4534884
Minimum0
Maximum7
Zeros16
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T15:20:09.844749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1236179
Coefficient of variation (CV)0.77304909
Kurtosis5.7240864
Mean1.4534884
Median Absolute Deviation (MAD)1
Skewness1.468747
Sum125
Variance1.2625171
MonotonicityNot monotonic
2024-05-11T15:20:10.017273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 31
 
5.1%
2 28
 
4.6%
0 16
 
2.6%
3 9
 
1.5%
4 1
 
0.2%
7 1
 
0.2%
(Missing) 520
85.8%
ValueCountFrequency (%)
0 16
2.6%
1 31
5.1%
2 28
4.6%
3 9
 
1.5%
4 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
4 1
 
0.2%
3 9
 
1.5%
2 28
4.6%
1 31
5.1%
0 16
2.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
572 
0
 
34

Length

Max length4
Median length4
Mean length3.8316832
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> 572
94.4%
0 34
 
5.6%

Length

2024-05-11T15:20:10.240145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:10.435538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 572
94.4%
0 34
 
5.6%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
572 
0
 
32
1
 
2

Length

Max length4
Median length4
Mean length3.8316832
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> 572
94.4%
0 32
 
5.3%
1 2
 
0.3%

Length

2024-05-11T15:20:10.604119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:10.782721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 572
94.4%
0 32
 
5.3%
1 2
 
0.3%

회수건조수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
478 
1
84 
0
 
43
2
 
1

Length

Max length4
Median length4
Mean length3.3663366
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 478
78.9%
1 84
 
13.9%
0 43
 
7.1%
2 1
 
0.2%

Length

2024-05-11T15:20:10.942088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:11.123017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 478
78.9%
1 84
 
13.9%
0 43
 
7.1%
2 1
 
0.2%

침대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
543 
0
63 

Length

Max length4
Median length4
Mean length3.6881188
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 543
89.6%
0 63
 
10.4%

Length

2024-05-11T15:20:11.316450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:11.475814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 543
89.6%
0 63
 
10.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing35
Missing (%)5.8%
Memory size1.3 KiB
False
571 
(Missing)
 
35
ValueCountFrequency (%)
False 571
94.2%
(Missing) 35
 
5.8%
2024-05-11T15:20:11.600637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
031200003120000-205-1982-0083219821012<NA>1영업/정상1영업<NA><NA><NA><NA>02 324713539.5120825서울특별시 서대문구 연희동 106-3번지서울특별시 서대문구 증가로 49 (연희동)3702미조컴퓨터크리닝2019-07-24 17:28:59U2019-07-26 02:40:00.0일반세탁업193648.318636452220.970384일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
131200003120000-205-1982-0083919820507<NA>3폐업2폐업19940426<NA><NA><NA>02000000000.0120817서울특별시 서대문구 북가좌동 420-33번지<NA><NA>기쁨사2002-05-10 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
231200003120000-205-1987-0070119870608<NA>1영업/정상1영업<NA><NA><NA><NA>02 302508914.0120848서울특별시 서대문구 홍은동 395-18번지서울특별시 서대문구 가좌로 50 (홍은동)3659현대사2014-01-02 14:14:21I2018-08-31 23:59:59.0일반세탁업193780.417814452893.679737일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
331200003120000-205-1987-0070219870608<NA>3폐업2폐업20120717<NA><NA><NA>020374476437.44120848서울특별시 서대문구 홍은동 407-19번지<NA><NA>홍남사2009-11-04 14:01:42I2018-08-31 23:59:59.0일반세탁업193526.930798452953.491854일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA>1<NA>N
431200003120000-205-1987-0070319870608<NA>3폐업2폐업20131119<NA><NA><NA>020303268420.0120814서울특별시 서대문구 북가좌동 317-17번지서울특별시 서대문구 거북골로22길 9-7 (북가좌동)<NA>백왕사2005-09-23 00:00:00I2018-08-31 23:59:59.0일반세탁업191806.114699453023.648104일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
531200003120000-205-1987-0070419870608<NA>3폐업2폐업19961226<NA><NA><NA>02 302881013.44120806서울특별시 서대문구 남가좌동 329-4번지<NA><NA>현대사2002-05-09 00:00:00I2018-08-31 23:59:59.0일반세탁업193284.695007452653.451399일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
631200003120000-205-1987-0070519870608<NA>3폐업2폐업19931213<NA><NA><NA>020302615226.22120805서울특별시 서대문구 남가좌동 277-10번지<NA><NA>백양사2002-05-09 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
731200003120000-205-1987-0070619870608<NA>3폐업2폐업20090414<NA><NA><NA>020374149714.24120802서울특별시 서대문구 남가좌동 124-259번지<NA><NA>미성사2003-07-01 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업2111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
831200003120000-205-1987-0070719870608<NA>3폐업2폐업20040130<NA><NA><NA>020739138326.0120859서울특별시 서대문구 홍제동 308-209번지<NA><NA>태용사2002-05-09 00:00:00I2018-08-31 23:59:59.0일반세탁업194863.695774453954.70169일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
931200003120000-205-1987-0070819870608<NA>3폐업2폐업20160317<NA><NA><NA>02 372400317.55120812서울특별시 서대문구 북가좌동 278-16번지서울특별시 서대문구 응암로 128-6 (북가좌동)<NA>미미사2014-01-02 14:14:54I2018-08-31 23:59:59.0일반세탁업192376.772654453478.316537일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
59631200003120000-205-2021-000022021-03-23<NA>3폐업2폐업2023-12-28<NA><NA><NA><NA>58.54120-866서울특별시 서대문구 북아현동 1-954 힐스테이트 신촌 상가109호서울특별시 서대문구 이화여대8길 123, 상가109호 (북아현동, 힐스테이트 신촌)3763힐스테이트 세탁2023-12-28 10:42:22U2022-11-01 21:00:00.0일반세탁업195603.439807451086.627831<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59731200003120000-205-2021-0000320210324<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.02120800서울특별시 서대문구 남가좌동 5-76 1층서울특별시 서대문구 명지대3길 42, 1층 (남가좌동)3672현대세탁2021-03-24 14:18:18I2021-03-26 00:22:59.0일반세탁업192997.393341453299.559438일반세탁업0011<NA><NA>000N0<NA><NA><NA>임대10010N
59831200003120000-205-2021-0000420210405<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.12120810서울특별시 서대문구 북가좌동 3-251 B02호서울특별시 서대문구 증가로24마길 46, B02호 (북가좌동)3668태운크리닝2021-04-05 15:46:03I2021-04-07 00:22:58.0일반세탁업192761.484102453383.318749일반세탁업00<NA><NA>11000N0<NA><NA><NA>임대10000N
59931200003120000-205-2021-0000520210927<NA>1영업/정상1영업<NA><NA><NA><NA>02 395 770728.89120100서울특별시 서대문구 홍은동 460 홍은동풍림아이원아파트서울특별시 서대문구 홍은중앙로 149, 상가동 103호 (홍은동, 홍은동풍림아이원아파트)3600풍림향균세탁소2021-09-27 15:04:19I2021-09-29 00:22:48.0일반세탁업195360.542102455710.429911일반세탁업001100000N0<NA><NA><NA><NA>10000N
60031200003120000-205-2021-0000620211124<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0120834서울특별시 서대문구 창천동 67-8서울특별시 서대문구 신촌로11길 37, 101호 (창천동)3782우리옷수선 운동화빨래방2021-11-24 12:49:49I2021-11-26 00:22:55.0일반세탁업194041.902427450680.128094일반세탁업000000000N0<NA><NA><NA><NA>00000N
60131200003120000-205-2022-0000120220103<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0120841서울특별시 서대문구 홍은동 8-739서울특별시 서대문구 홍은중앙로 130-1, 1층 (홍은동)3601백일세탁소2022-01-03 15:50:35I2022-01-05 00:22:41.0일반세탁업195443.589391455510.916445일반세탁업100000000N0<NA><NA><NA><NA>10000N
60231200003120000-205-2022-000022022-10-21<NA>3폐업2폐업2023-12-27<NA><NA><NA><NA>42.63120-808서울특별시 서대문구 대현동 37-32 영타운 지웰 에스테이트서울특별시 서대문구 이화여대5길 35, 영타운 지웰 에스테이트 119호 (대현동)3766레드프래그2023-12-27 13:55:54U2022-11-01 22:09:00.0운동화전문세탁업194960.929139450652.212058<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60331200003120000-205-2022-0000320221213<NA>1영업/정상1영업<NA><NA><NA><NA><NA>43.0120853서울특별시 서대문구 홍제동 82 홍제한양아파트서울특별시 서대문구 통일로25길 30, 1층 106호 (홍제동, 홍제한양아파트)3730한양세탁소2022-12-13 11:57:25I2021-11-01 23:05:00.0일반세탁업195259.429273453430.811542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60431200003120000-205-2023-000012023-05-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.55120-758서울특별시 서대문구 남가좌동 376 현대아파트서울특별시 서대문구 가재울로 43, 현대아파트 상가1동 207, 208, 209호 (남가좌동)3710이엠세탁소2023-08-28 14:12:20U2022-12-07 21:00:00.0일반세탁업192874.514454452525.219516<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60531200003120000-205-2023-000022023-07-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 324 102770.56120-847서울특별시 서대문구 홍은동 274-58 데미안빌서울특별시 서대문구 모래내로 342, 1층 102호 (홍은동, 데미안빌)3658서대문지역자활센터(이야기담은빨래방)2023-12-01 14:12:35U2022-11-02 00:03:00.0일반세탁업194159.233125453130.069501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>