Overview

Dataset statistics

Number of variables47
Number of observations771
Missing cells7602
Missing cells (%)21.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory304.3 KiB
Average record size in memory404.2 B

Variable types

Categorical22
Text7
DateTime4
Unsupported7
Numeric5
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-17976/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (91.3%)Imbalance
위생업태명 is highly imbalanced (72.6%)Imbalance
사용시작지하층 is highly imbalanced (53.9%)Imbalance
사용끝지하층 is highly imbalanced (85.1%)Imbalance
여성종사자수 is highly imbalanced (70.6%)Imbalance
남성종사자수 is highly imbalanced (70.6%)Imbalance
회수건조수 is highly imbalanced (70.1%)Imbalance
인허가취소일자 has 771 (100.0%) missing valuesMissing
폐업일자 has 156 (20.2%) missing valuesMissing
휴업시작일자 has 771 (100.0%) missing valuesMissing
휴업종료일자 has 771 (100.0%) missing valuesMissing
재개업일자 has 771 (100.0%) missing valuesMissing
전화번호 has 64 (8.3%) missing valuesMissing
도로명주소 has 437 (56.7%) missing valuesMissing
도로명우편번호 has 450 (58.4%) missing valuesMissing
좌표정보(X) has 49 (6.4%) missing valuesMissing
좌표정보(Y) has 49 (6.4%) missing valuesMissing
건물지상층수 has 175 (22.7%) missing valuesMissing
발한실여부 has 91 (11.8%) missing valuesMissing
조건부허가신고사유 has 771 (100.0%) missing valuesMissing
조건부허가시작일자 has 771 (100.0%) missing valuesMissing
조건부허가종료일자 has 771 (100.0%) missing valuesMissing
세탁기수 has 651 (84.4%) missing valuesMissing
다중이용업소여부 has 83 (10.8%) 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
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 248 (32.2%) zerosZeros
세탁기수 has 24 (3.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:35:17.733343
Analysis finished2024-05-11 05:35:19.081614
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
3240000
771 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3240000 771
100.0%

Length

2024-05-11T14:35:19.180409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:19.360882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 771
100.0%

관리번호
Text

UNIQUE 

Distinct771
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T14:35:19.692399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters16962
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

Unique771 ?
Unique (%)100.0%

Sample

1st row3240000-205-1987-01919
2nd row3240000-205-1987-01926
3rd row3240000-205-1987-02184
4th row3240000-205-1987-02191
5th row3240000-205-1987-02192
ValueCountFrequency (%)
3240000-205-1987-01919 1
 
0.1%
3240000-205-1993-02000 1
 
0.1%
3240000-205-2003-00026 1
 
0.1%
3240000-205-2003-00017 1
 
0.1%
3240000-205-2003-00018 1
 
0.1%
3240000-205-2003-00019 1
 
0.1%
3240000-205-2003-00020 1
 
0.1%
3240000-205-2003-00021 1
 
0.1%
3240000-205-2003-00022 1
 
0.1%
3240000-205-2003-00023 1
 
0.1%
Other values (761) 761
98.7%
2024-05-11T14:35:20.240341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6105
36.0%
2 2558
15.1%
- 2313
 
13.6%
3 1128
 
6.7%
1 988
 
5.8%
4 973
 
5.7%
5 946
 
5.6%
9 942
 
5.6%
8 478
 
2.8%
7 362
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14649
86.4%
Dash Punctuation 2313
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6105
41.7%
2 2558
17.5%
3 1128
 
7.7%
1 988
 
6.7%
4 973
 
6.6%
5 946
 
6.5%
9 942
 
6.4%
8 478
 
3.3%
7 362
 
2.5%
6 169
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 2313
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6105
36.0%
2 2558
15.1%
- 2313
 
13.6%
3 1128
 
6.7%
1 988
 
5.8%
4 973
 
5.7%
5 946
 
5.6%
9 942
 
5.6%
8 478
 
2.8%
7 362
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6105
36.0%
2 2558
15.1%
- 2313
 
13.6%
3 1128
 
6.7%
1 988
 
5.8%
4 973
 
5.7%
5 946
 
5.6%
9 942
 
5.6%
8 478
 
2.8%
7 362
 
2.1%
Distinct455
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum1987-02-21 00:00:00
Maximum2024-01-08 00:00:00
2024-05-11T14:35:20.511918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:20.802414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
3
615 
1
156 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 615
79.8%
1 156
 
20.2%

Length

2024-05-11T14:35:21.079454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:21.249893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 615
79.8%
1 156
 
20.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
폐업
615 
영업/정상
156 

Length

Max length5
Median length2
Mean length2.6070039
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 615
79.8%
영업/정상 156
 
20.2%

Length

2024-05-11T14:35:21.449200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:21.655025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 615
79.8%
영업/정상 156
 
20.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2
615 
1
156 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 615
79.8%
1 156
 
20.2%

Length

2024-05-11T14:35:21.875716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:22.046147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 615
79.8%
1 156
 
20.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
폐업
615 
영업
156 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 615
79.8%
영업 156
 
20.2%

Length

2024-05-11T14:35:22.247797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:22.479688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 615
79.8%
영업 156
 
20.2%

폐업일자
Date

MISSING 

Distinct469
Distinct (%)76.3%
Missing156
Missing (%)20.2%
Memory size6.2 KiB
Minimum1989-08-29 00:00:00
Maximum2024-03-07 00:00:00
2024-05-11T14:35:22.703927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:22.984634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB

전화번호
Text

MISSING 

Distinct596
Distinct (%)84.3%
Missing64
Missing (%)8.3%
Memory size6.2 KiB
2024-05-11T14:35:23.490491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8571429
Min length2

Characters and Unicode

Total characters6969
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

Unique565 ?
Unique (%)79.9%

Sample

1st row02 00000
2nd row0204854195
3rd row0234272644
4th row02 00000
5th row02 00000
ValueCountFrequency (%)
02 397
34.9%
0200000000 36
 
3.2%
00000 18
 
1.6%
442 10
 
0.9%
441 7
 
0.6%
426 5
 
0.4%
4811212 4
 
0.4%
428 4
 
0.4%
475 4
 
0.4%
470 4
 
0.4%
Other values (602) 650
57.1%
2024-05-11T14:35:24.345566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1629
23.4%
2 1153
16.5%
4 982
14.1%
550
 
7.9%
8 538
 
7.7%
7 528
 
7.6%
6 355
 
5.1%
5 332
 
4.8%
3 328
 
4.7%
1 326
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6419
92.1%
Space Separator 550
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1629
25.4%
2 1153
18.0%
4 982
15.3%
8 538
 
8.4%
7 528
 
8.2%
6 355
 
5.5%
5 332
 
5.2%
3 328
 
5.1%
1 326
 
5.1%
9 248
 
3.9%
Space Separator
ValueCountFrequency (%)
550
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6969
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1629
23.4%
2 1153
16.5%
4 982
14.1%
550
 
7.9%
8 538
 
7.7%
7 528
 
7.6%
6 355
 
5.1%
5 332
 
4.8%
3 328
 
4.7%
1 326
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6969
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1629
23.4%
2 1153
16.5%
4 982
14.1%
550
 
7.9%
8 538
 
7.7%
7 528
 
7.6%
6 355
 
5.1%
5 332
 
4.8%
3 328
 
4.7%
1 326
 
4.7%
Distinct369
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T14:35:24.927056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9623865
Min length3

Characters and Unicode

Total characters3826
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

Unique286 ?
Unique (%)37.1%

Sample

1st row16.34
2nd row10.08
3rd row23.10
4th row20.00
5th row19.72
ValueCountFrequency (%)
33.00 46
 
6.0%
00 43
 
5.6%
15.00 28
 
3.6%
23.10 26
 
3.4%
26.40 25
 
3.2%
20.00 24
 
3.1%
24.00 16
 
2.1%
30.00 16
 
2.1%
19.80 16
 
2.1%
21.00 12
 
1.6%
Other values (359) 519
67.3%
2024-05-11T14:35:25.897710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 943
24.6%
. 771
20.2%
1 432
11.3%
2 372
 
9.7%
3 294
 
7.7%
4 228
 
6.0%
6 204
 
5.3%
5 184
 
4.8%
9 162
 
4.2%
8 141
 
3.7%
Other values (2) 95
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3053
79.8%
Other Punctuation 773
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 943
30.9%
1 432
14.2%
2 372
 
12.2%
3 294
 
9.6%
4 228
 
7.5%
6 204
 
6.7%
5 184
 
6.0%
9 162
 
5.3%
8 141
 
4.6%
7 93
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 771
99.7%
, 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3826
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 943
24.6%
. 771
20.2%
1 432
11.3%
2 372
 
9.7%
3 294
 
7.7%
4 228
 
6.0%
6 204
 
5.3%
5 184
 
4.8%
9 162
 
4.2%
8 141
 
3.7%
Other values (2) 95
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 943
24.6%
. 771
20.2%
1 432
11.3%
2 372
 
9.7%
3 294
 
7.7%
4 228
 
6.0%
6 204
 
5.3%
5 184
 
4.8%
9 162
 
4.2%
8 141
 
3.7%
Other values (2) 95
 
2.5%
Distinct107
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T14:35:26.329775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0285344
Min length6

Characters and Unicode

Total characters4648
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

Unique23 ?
Unique (%)3.0%

Sample

1st row134830
2nd row134868
3rd row134830
4th row134840
5th row134844
ValueCountFrequency (%)
134864 37
 
4.8%
134830 30
 
3.9%
134861 28
 
3.6%
134867 23
 
3.0%
134841 23
 
3.0%
134868 21
 
2.7%
134050 18
 
2.3%
134822 18
 
2.3%
134817 18
 
2.3%
134859 17
 
2.2%
Other values (97) 538
69.8%
2024-05-11T14:35:27.036670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 969
20.8%
4 964
20.7%
3 900
19.4%
8 802
17.3%
0 276
 
5.9%
6 223
 
4.8%
7 172
 
3.7%
5 139
 
3.0%
2 113
 
2.4%
9 68
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4626
99.5%
Dash Punctuation 22
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 969
20.9%
4 964
20.8%
3 900
19.5%
8 802
17.3%
0 276
 
6.0%
6 223
 
4.8%
7 172
 
3.7%
5 139
 
3.0%
2 113
 
2.4%
9 68
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 969
20.8%
4 964
20.7%
3 900
19.4%
8 802
17.3%
0 276
 
5.9%
6 223
 
4.8%
7 172
 
3.7%
5 139
 
3.0%
2 113
 
2.4%
9 68
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 969
20.8%
4 964
20.7%
3 900
19.4%
8 802
17.3%
0 276
 
5.9%
6 223
 
4.8%
7 172
 
3.7%
5 139
 
3.0%
2 113
 
2.4%
9 68
 
1.5%
Distinct707
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T14:35:27.614004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length24.45655
Min length15

Characters and Unicode

Total characters18856
Distinct characters173
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique651 ?
Unique (%)84.4%

Sample

1st row서울특별시 강동구 명일동 351-12번지
2nd row서울특별시 강동구 천호동 316-0번지
3rd row서울특별시 강동구 명일동 333-17번지
4th row서울특별시 강동구 성내동 12-39번지
5th row서울특별시 강동구 성내동 405-17번지
ValueCountFrequency (%)
서울특별시 771
22.1%
강동구 771
22.1%
천호동 208
 
6.0%
성내동 132
 
3.8%
길동 107
 
3.1%
암사동 103
 
2.9%
명일동 66
 
1.9%
둔촌동 57
 
1.6%
1층 50
 
1.4%
고덕동 49
 
1.4%
Other values (866) 1179
33.8%
2024-05-11T14:35:28.446234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3366
17.9%
1602
 
8.5%
807
 
4.3%
1 797
 
4.2%
776
 
4.1%
774
 
4.1%
772
 
4.1%
771
 
4.1%
771
 
4.1%
771
 
4.1%
Other values (163) 7649
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10965
58.2%
Decimal Number 3776
 
20.0%
Space Separator 3366
 
17.9%
Dash Punctuation 666
 
3.5%
Uppercase Letter 30
 
0.2%
Open Punctuation 23
 
0.1%
Close Punctuation 23
 
0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1602
14.6%
807
 
7.4%
776
 
7.1%
774
 
7.1%
772
 
7.0%
771
 
7.0%
771
 
7.0%
771
 
7.0%
680
 
6.2%
647
 
5.9%
Other values (138) 2594
23.7%
Decimal Number
ValueCountFrequency (%)
1 797
21.1%
4 485
12.8%
2 481
12.7%
3 456
12.1%
0 380
10.1%
5 289
 
7.7%
6 242
 
6.4%
7 219
 
5.8%
9 217
 
5.7%
8 210
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
A 9
30.0%
K 4
13.3%
P 4
13.3%
B 3
 
10.0%
S 2
 
6.7%
R 2
 
6.7%
T 2
 
6.7%
I 2
 
6.7%
M 1
 
3.3%
G 1
 
3.3%
Space Separator
ValueCountFrequency (%)
3366
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 666
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10965
58.2%
Common 7861
41.7%
Latin 30
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1602
14.6%
807
 
7.4%
776
 
7.1%
774
 
7.1%
772
 
7.0%
771
 
7.0%
771
 
7.0%
771
 
7.0%
680
 
6.2%
647
 
5.9%
Other values (138) 2594
23.7%
Common
ValueCountFrequency (%)
3366
42.8%
1 797
 
10.1%
- 666
 
8.5%
4 485
 
6.2%
2 481
 
6.1%
3 456
 
5.8%
0 380
 
4.8%
5 289
 
3.7%
6 242
 
3.1%
7 219
 
2.8%
Other values (5) 480
 
6.1%
Latin
ValueCountFrequency (%)
A 9
30.0%
K 4
13.3%
P 4
13.3%
B 3
 
10.0%
S 2
 
6.7%
R 2
 
6.7%
T 2
 
6.7%
I 2
 
6.7%
M 1
 
3.3%
G 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10965
58.2%
ASCII 7891
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3366
42.7%
1 797
 
10.1%
- 666
 
8.4%
4 485
 
6.1%
2 481
 
6.1%
3 456
 
5.8%
0 380
 
4.8%
5 289
 
3.7%
6 242
 
3.1%
7 219
 
2.8%
Other values (15) 510
 
6.5%
Hangul
ValueCountFrequency (%)
1602
14.6%
807
 
7.4%
776
 
7.1%
774
 
7.1%
772
 
7.0%
771
 
7.0%
771
 
7.0%
771
 
7.0%
680
 
6.2%
647
 
5.9%
Other values (138) 2594
23.7%

도로명주소
Text

MISSING 

Distinct330
Distinct (%)98.8%
Missing437
Missing (%)56.7%
Memory size6.2 KiB
2024-05-11T14:35:28.898836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length49
Mean length31.197605
Min length21

Characters and Unicode

Total characters10420
Distinct characters175
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

Unique326 ?
Unique (%)97.6%

Sample

1st row서울특별시 강동구 양재대로136길 11 (명일동)
2nd row서울특별시 강동구 양재대로123길 52 (천호동)
3rd row서울특별시 강동구 천중로29길 5 (천호동)
4th row서울특별시 강동구 상암로27길 16 (천호동)
5th row서울특별시 강동구 천중로 79 (천호동)
ValueCountFrequency (%)
서울특별시 334
 
17.0%
강동구 334
 
17.0%
천호동 76
 
3.9%
1층 61
 
3.1%
성내동 50
 
2.5%
암사동 40
 
2.0%
길동 34
 
1.7%
명일동 30
 
1.5%
상일동 21
 
1.1%
둔촌동 21
 
1.1%
Other values (501) 966
49.1%
2024-05-11T14:35:29.636878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1636
 
15.7%
731
 
7.0%
1 440
 
4.2%
378
 
3.6%
367
 
3.5%
( 348
 
3.3%
) 348
 
3.3%
338
 
3.2%
334
 
3.2%
334
 
3.2%
Other values (165) 5166
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6054
58.1%
Decimal Number 1770
 
17.0%
Space Separator 1636
 
15.7%
Open Punctuation 348
 
3.3%
Close Punctuation 348
 
3.3%
Other Punctuation 214
 
2.1%
Uppercase Letter 26
 
0.2%
Dash Punctuation 23
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
731
 
12.1%
378
 
6.2%
367
 
6.1%
338
 
5.6%
334
 
5.5%
334
 
5.5%
334
 
5.5%
334
 
5.5%
326
 
5.4%
290
 
4.8%
Other values (141) 2288
37.8%
Decimal Number
ValueCountFrequency (%)
1 440
24.9%
2 224
12.7%
3 192
10.8%
0 185
10.5%
4 146
 
8.2%
5 142
 
8.0%
6 128
 
7.2%
7 127
 
7.2%
9 99
 
5.6%
8 87
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
A 10
38.5%
P 4
 
15.4%
K 3
 
11.5%
R 2
 
7.7%
T 2
 
7.7%
I 2
 
7.7%
B 2
 
7.7%
M 1
 
3.8%
Space Separator
ValueCountFrequency (%)
1636
100.0%
Open Punctuation
ValueCountFrequency (%)
( 348
100.0%
Close Punctuation
ValueCountFrequency (%)
) 348
100.0%
Other Punctuation
ValueCountFrequency (%)
, 214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6054
58.1%
Common 4340
41.7%
Latin 26
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
731
 
12.1%
378
 
6.2%
367
 
6.1%
338
 
5.6%
334
 
5.5%
334
 
5.5%
334
 
5.5%
334
 
5.5%
326
 
5.4%
290
 
4.8%
Other values (141) 2288
37.8%
Common
ValueCountFrequency (%)
1636
37.7%
1 440
 
10.1%
( 348
 
8.0%
) 348
 
8.0%
2 224
 
5.2%
, 214
 
4.9%
3 192
 
4.4%
0 185
 
4.3%
4 146
 
3.4%
5 142
 
3.3%
Other values (6) 465
 
10.7%
Latin
ValueCountFrequency (%)
A 10
38.5%
P 4
 
15.4%
K 3
 
11.5%
R 2
 
7.7%
T 2
 
7.7%
I 2
 
7.7%
B 2
 
7.7%
M 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6054
58.1%
ASCII 4366
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1636
37.5%
1 440
 
10.1%
( 348
 
8.0%
) 348
 
8.0%
2 224
 
5.1%
, 214
 
4.9%
3 192
 
4.4%
0 185
 
4.2%
4 146
 
3.3%
5 142
 
3.3%
Other values (14) 491
 
11.2%
Hangul
ValueCountFrequency (%)
731
 
12.1%
378
 
6.2%
367
 
6.1%
338
 
5.6%
334
 
5.5%
334
 
5.5%
334
 
5.5%
334
 
5.5%
326
 
5.4%
290
 
4.8%
Other values (141) 2288
37.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)46.7%
Missing450
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean5310.9346
Minimum5209
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T14:35:30.008058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5209
5-th percentile5225
Q15262
median5312
Q35354
95-th percentile5402
Maximum5415
Range206
Interquartile range (IQR)92

Descriptive statistics

Standard deviation56.757038
Coefficient of variation (CV)0.010686827
Kurtosis-1.1394179
Mean5310.9346
Median Absolute Deviation (MAD)48
Skewness0.010696256
Sum1704810
Variance3221.3613
MonotonicityNot monotonic
2024-05-11T14:35:30.255399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5331 8
 
1.0%
5301 7
 
0.9%
5271 7
 
0.9%
5351 5
 
0.6%
5364 5
 
0.6%
5336 5
 
0.6%
5403 5
 
0.6%
5227 5
 
0.6%
5383 5
 
0.6%
5321 5
 
0.6%
Other values (140) 264
34.2%
(Missing) 450
58.4%
ValueCountFrequency (%)
5209 2
0.3%
5210 2
0.3%
5211 1
 
0.1%
5214 2
0.3%
5216 1
 
0.1%
5217 1
 
0.1%
5218 1
 
0.1%
5219 1
 
0.1%
5220 3
0.4%
5222 1
 
0.1%
ValueCountFrequency (%)
5415 2
 
0.3%
5412 1
 
0.1%
5408 1
 
0.1%
5407 2
 
0.3%
5406 4
0.5%
5404 1
 
0.1%
5403 5
0.6%
5402 2
 
0.3%
5401 2
 
0.3%
5400 3
0.4%
Distinct510
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T14:35:30.653739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length4.1595331
Min length2

Characters and Unicode

Total characters3207
Distinct characters300
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

Unique395 ?
Unique (%)51.2%

Sample

1st row제일
2nd row백양
3rd row대원사
4th row열매사
5th row현대사
ValueCountFrequency (%)
백양사 30
 
3.8%
현대사 20
 
2.5%
백조사 13
 
1.6%
백양세탁소 10
 
1.3%
백성사 8
 
1.0%
일광사 7
 
0.9%
월풀빨래방 6
 
0.8%
대성사 6
 
0.8%
태양사 6
 
0.8%
우성세탁소 6
 
0.8%
Other values (511) 685
85.9%
2024-05-11T14:35:31.375623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
378
 
11.8%
234
 
7.3%
230
 
7.2%
123
 
3.8%
106
 
3.3%
88
 
2.7%
78
 
2.4%
67
 
2.1%
64
 
2.0%
58
 
1.8%
Other values (290) 1781
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3167
98.8%
Space Separator 26
 
0.8%
Uppercase Letter 8
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
378
 
11.9%
234
 
7.4%
230
 
7.3%
123
 
3.9%
106
 
3.3%
88
 
2.8%
78
 
2.5%
67
 
2.1%
64
 
2.0%
58
 
1.8%
Other values (278) 1741
55.0%
Uppercase Letter
ValueCountFrequency (%)
I 2
25.0%
G 1
12.5%
L 1
12.5%
F 1
12.5%
C 1
12.5%
T 1
12.5%
K 1
12.5%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3167
98.8%
Common 32
 
1.0%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
378
 
11.9%
234
 
7.4%
230
 
7.3%
123
 
3.9%
106
 
3.3%
88
 
2.8%
78
 
2.5%
67
 
2.1%
64
 
2.0%
58
 
1.8%
Other values (278) 1741
55.0%
Latin
ValueCountFrequency (%)
I 2
25.0%
G 1
12.5%
L 1
12.5%
F 1
12.5%
C 1
12.5%
T 1
12.5%
K 1
12.5%
Common
ValueCountFrequency (%)
26
81.2%
) 2
 
6.2%
( 2
 
6.2%
& 1
 
3.1%
- 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3167
98.8%
ASCII 40
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
378
 
11.9%
234
 
7.4%
230
 
7.3%
123
 
3.9%
106
 
3.3%
88
 
2.8%
78
 
2.5%
67
 
2.1%
64
 
2.0%
58
 
1.8%
Other values (278) 1741
55.0%
ASCII
ValueCountFrequency (%)
26
65.0%
) 2
 
5.0%
( 2
 
5.0%
I 2
 
5.0%
G 1
 
2.5%
L 1
 
2.5%
& 1
 
2.5%
F 1
 
2.5%
C 1
 
2.5%
T 1
 
2.5%
Other values (2) 2
 
5.0%
Distinct427
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum1999-02-12 00:00:00
Maximum2024-03-07 09:10:01
2024-05-11T14:35:31.631632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:31.904532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
I
605 
U
166 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 605
78.5%
U 166
 
21.5%

Length

2024-05-11T14:35:32.235036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:32.414891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 605
78.5%
u 166
 
21.5%
Distinct130
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:09:00
2024-05-11T14:35:32.618105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:32.887366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
일반세탁업
755 
운동화전문세탁업
 
8
빨래방업
 
6
세탁업 기타
 
2

Length

Max length8
Median length5
Mean length5.0259403
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 755
97.9%
운동화전문세탁업 8
 
1.0%
빨래방업 6
 
0.8%
세탁업 기타 2
 
0.3%

Length

2024-05-11T14:35:33.170426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:33.825623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 755
97.7%
운동화전문세탁업 8
 
1.0%
빨래방업 6
 
0.8%
세탁업 2
 
0.3%
기타 2
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct558
Distinct (%)77.3%
Missing49
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean212269.58
Minimum210624
Maximum216072.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T14:35:34.055851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210624
5-th percentile210882.74
Q1211506.36
median212075.49
Q3212752.71
95-th percentile214830.79
Maximum216072.18
Range5448.1785
Interquartile range (IQR)1246.3556

Descriptive statistics

Standard deviation1103.6459
Coefficient of variation (CV)0.0051992657
Kurtosis1.1369566
Mean212269.58
Median Absolute Deviation (MAD)615.33506
Skewness1.150989
Sum1.5325864 × 108
Variance1218034.3
MonotonicityNot monotonic
2024-05-11T14:35:34.301930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211047.878697259 8
 
1.0%
213048.692179757 5
 
0.6%
212480.463676316 5
 
0.6%
214293.085340515 5
 
0.6%
213640.409719271 5
 
0.6%
215008.531272849 4
 
0.5%
214672.069198977 4
 
0.5%
213030.184792779 4
 
0.5%
212860.982126977 4
 
0.5%
211729.143097102 4
 
0.5%
Other values (548) 674
87.4%
(Missing) 49
 
6.4%
ValueCountFrequency (%)
210623.999214074 2
0.3%
210674.026410574 2
0.3%
210682.838396073 1
0.1%
210692.723792014 1
0.1%
210694.356443976 1
0.1%
210702.347047613 1
0.1%
210702.406777082 1
0.1%
210714.338056246 1
0.1%
210742.934504221 1
0.1%
210747.861777943 1
0.1%
ValueCountFrequency (%)
216072.177742182 1
 
0.1%
215888.898816 2
0.3%
215875.024969 1
 
0.1%
215784.2264 2
0.3%
215527.721278 2
0.3%
215422.746119624 3
0.4%
215361.163713829 1
 
0.1%
215303.913311463 1
 
0.1%
215223.604630417 1
 
0.1%
215201.290186508 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct558
Distinct (%)77.3%
Missing49
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean449006.64
Minimum446699.2
Maximum452213.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T14:35:34.597590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446699.2
5-th percentile447271.9
Q1448189.49
median448976.43
Q3449799.48
95-th percentile450846.43
Maximum452213.42
Range5514.2207
Interquartile range (IQR)1609.9902

Descriptive statistics

Standard deviation1080.7948
Coefficient of variation (CV)0.0024070797
Kurtosis-0.40639027
Mean449006.64
Median Absolute Deviation (MAD)818.86656
Skewness0.16381915
Sum3.241828 × 108
Variance1168117.3
MonotonicityNot monotonic
2024-05-11T14:35:34.849759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450021.504957301 8
 
1.0%
450124.105734971 5
 
0.6%
450472.374955204 5
 
0.6%
450636.626425939 5
 
0.6%
449810.525251162 5
 
0.6%
450016.148655397 4
 
0.5%
449978.944077781 4
 
0.5%
449881.868861553 4
 
0.5%
448990.045525377 4
 
0.5%
448643.365100299 4
 
0.5%
Other values (548) 674
87.4%
(Missing) 49
 
6.4%
ValueCountFrequency (%)
446699.196101461 1
0.1%
446800.369554447 1
0.1%
446824.910976521 1
0.1%
446833.993029127 1
0.1%
446846.089755545 1
0.1%
446928.682055134 1
0.1%
446966.454190768 2
0.3%
446979.497842093 1
0.1%
447002.595464207 1
0.1%
447018.459750024 1
0.1%
ValueCountFrequency (%)
452213.416817557 1
0.1%
452189.755118282 1
0.1%
452130.329696 2
0.3%
452076.939632 2
0.3%
451839.097942 2
0.3%
451722.369440998 1
0.1%
451370.39819 1
0.1%
451140.814969126 1
0.1%
451120.470507797 1
0.1%
451115.727164347 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
일반세탁업
675 
<NA>
83 
운동화전문세탁업
 
6
빨래방업
 
6
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.9092088
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 675
87.5%
<NA> 83
 
10.8%
운동화전문세탁업 6
 
0.8%
빨래방업 6
 
0.8%
세탁업 기타 1
 
0.1%

Length

2024-05-11T14:35:35.106073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:35.313590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 675
87.4%
na 83
 
10.8%
운동화전문세탁업 6
 
0.8%
빨래방업 6
 
0.8%
세탁업 1
 
0.1%
기타 1
 
0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)2.3%
Missing175
Missing (%)22.7%
Infinite0
Infinite (%)0.0%
Mean1.7634228
Minimum0
Maximum28
Zeros248
Zeros (%)32.2%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T14:35:35.490614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4
Maximum28
Range28
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5123703
Coefficient of variation (CV)1.4247124
Kurtosis38.872531
Mean1.7634228
Median Absolute Deviation (MAD)1
Skewness4.8452642
Sum1051
Variance6.3120044
MonotonicityNot monotonic
2024-05-11T14:35:35.727941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 248
32.2%
2 112
14.5%
3 93
 
12.1%
4 66
 
8.6%
1 51
 
6.6%
5 16
 
2.1%
16 2
 
0.3%
7 2
 
0.3%
24 1
 
0.1%
28 1
 
0.1%
Other values (4) 4
 
0.5%
(Missing) 175
22.7%
ValueCountFrequency (%)
0 248
32.2%
1 51
 
6.6%
2 112
14.5%
3 93
 
12.1%
4 66
 
8.6%
5 16
 
2.1%
7 2
 
0.3%
9 1
 
0.1%
10 1
 
0.1%
15 1
 
0.1%
ValueCountFrequency (%)
28 1
 
0.1%
24 1
 
0.1%
21 1
 
0.1%
16 2
 
0.3%
15 1
 
0.1%
10 1
 
0.1%
9 1
 
0.1%
7 2
 
0.3%
5 16
 
2.1%
4 66
8.6%
Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
304 
0
285 
1
175 
2
 
4
5
 
2

Length

Max length4
Median length1
Mean length2.1828794
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 304
39.4%
0 285
37.0%
1 175
22.7%
2 4
 
0.5%
5 2
 
0.3%
3 1
 
0.1%

Length

2024-05-11T14:35:35.980818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:36.183494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 304
39.4%
0 285
37.0%
1 175
22.7%
2 4
 
0.5%
5 2
 
0.3%
3 1
 
0.1%
Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
1
372 
<NA>
192 
0
182 
2
 
23
3
 
2

Length

Max length4
Median length1
Mean length1.7470817
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 372
48.2%
<NA> 192
24.9%
0 182
23.6%
2 23
 
3.0%
3 2
 
0.3%

Length

2024-05-11T14:35:36.390446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:36.584719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 372
48.2%
na 192
24.9%
0 182
23.6%
2 23
 
3.0%
3 2
 
0.3%
Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
375 
1
363 
2
 
22
0
 
9
3
 
2

Length

Max length4
Median length1
Mean length2.459144
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 375
48.6%
1 363
47.1%
2 22
 
2.9%
0 9
 
1.2%
3 2
 
0.3%

Length

2024-05-11T14:35:36.793530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:36.965147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 375
48.6%
1 363
47.1%
2 22
 
2.9%
0 9
 
1.2%
3 2
 
0.3%

사용시작지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
563 
0
198 
1
 
9
2
 
1

Length

Max length4
Median length4
Mean length3.1906615
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 563
73.0%
0 198
 
25.7%
1 9
 
1.2%
2 1
 
0.1%

Length

2024-05-11T14:35:37.159521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:37.353631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 563
73.0%
0 198
 
25.7%
1 9
 
1.2%
2 1
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
738 
0
 
24
1
 
8
2
 
1

Length

Max length4
Median length4
Mean length3.8715953
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 738
95.7%
0 24
 
3.1%
1 8
 
1.0%
2 1
 
0.1%

Length

2024-05-11T14:35:37.588182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:37.815999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 738
95.7%
0 24
 
3.1%
1 8
 
1.0%
2 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
476 
0
295 

Length

Max length4
Median length4
Mean length2.8521401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 476
61.7%
0 295
38.3%

Length

2024-05-11T14:35:38.031512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:38.224297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 476
61.7%
0 295
38.3%

양실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
476 
0
295 

Length

Max length4
Median length4
Mean length2.8521401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 476
61.7%
0 295
38.3%

Length

2024-05-11T14:35:38.433406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:38.583457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 476
61.7%
0 295
38.3%

욕실수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
476 
0
295 

Length

Max length4
Median length4
Mean length2.8521401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 476
61.7%
0 295
38.3%

Length

2024-05-11T14:35:38.789905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:38.998880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 476
61.7%
0 295
38.3%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing91
Missing (%)11.8%
Memory size1.6 KiB
False
680 
(Missing)
91 
ValueCountFrequency (%)
False 680
88.2%
(Missing) 91
 
11.8%
2024-05-11T14:35:39.146284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
473 
0
295 
4
 
3

Length

Max length4
Median length4
Mean length2.8404669
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 473
61.3%
0 295
38.3%
4 3
 
0.4%

Length

2024-05-11T14:35:39.288331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:39.444615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 473
61.3%
0 295
38.3%
4 3
 
0.4%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing771
Missing (%)100.0%
Memory size6.9 KiB
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
394 
임대
367 
자가
 
10

Length

Max length4
Median length4
Mean length3.0220493
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 394
51.1%
임대 367
47.6%
자가 10
 
1.3%

Length

2024-05-11T14:35:39.624151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:39.827524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 394
51.1%
임대 367
47.6%
자가 10
 
1.3%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)5.0%
Missing651
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean1.4083333
Minimum0
Maximum6
Zeros24
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T14:35:39.941411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1264269
Coefficient of variation (CV)0.79982974
Kurtosis1.4255821
Mean1.4083333
Median Absolute Deviation (MAD)1
Skewness0.96782442
Sum169
Variance1.2688375
MonotonicityNot monotonic
2024-05-11T14:35:40.105378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 50
 
6.5%
2 26
 
3.4%
0 24
 
3.1%
3 15
 
1.9%
4 4
 
0.5%
6 1
 
0.1%
(Missing) 651
84.4%
ValueCountFrequency (%)
0 24
3.1%
1 50
6.5%
2 26
3.4%
3 15
 
1.9%
4 4
 
0.5%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 4
 
0.5%
3 15
 
1.9%
2 26
3.4%
1 50
6.5%
0 24
3.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
731 
0
 
40

Length

Max length4
Median length4
Mean length3.844358
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> 731
94.8%
0 40
 
5.2%

Length

2024-05-11T14:35:40.305053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:40.449360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 731
94.8%
0 40
 
5.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
731 
0
 
40

Length

Max length4
Median length4
Mean length3.844358
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> 731
94.8%
0 40
 
5.2%

Length

2024-05-11T14:35:40.654590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:40.825677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 731
94.8%
0 40
 
5.2%

회수건조수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
666 
0
 
50
1
 
44
2
 
9
4
 
1

Length

Max length4
Median length4
Mean length3.5914397
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 666
86.4%
0 50
 
6.5%
1 44
 
5.7%
2 9
 
1.2%
4 1
 
0.1%
3 1
 
0.1%

Length

2024-05-11T14:35:40.979532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:41.176810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 666
86.4%
0 50
 
6.5%
1 44
 
5.7%
2 9
 
1.2%
4 1
 
0.1%
3 1
 
0.1%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
669 
0
102 

Length

Max length4
Median length4
Mean length3.6031128
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> 669
86.8%
0 102
 
13.2%

Length

2024-05-11T14:35:41.436621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:41.740421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 669
86.8%
0 102
 
13.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing83
Missing (%)10.8%
Memory size1.6 KiB
False
688 
(Missing)
83 
ValueCountFrequency (%)
False 688
89.2%
(Missing) 83
 
10.8%
2024-05-11T14:35:41.917413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032400003240000-205-1987-0191919871006<NA>3폐업2폐업19971002<NA><NA><NA>02 0000016.34134830서울특별시 강동구 명일동 351-12번지<NA><NA>제일2002-06-06 00:00:00I2018-08-31 23:59:59.0일반세탁업212682.212173449190.216686일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132400003240000-205-1987-0192619871204<NA>3폐업2폐업19951206<NA><NA><NA>020485419510.08134868서울특별시 강동구 천호동 316-0번지<NA><NA>백양2002-06-06 00:00:00I2018-08-31 23:59:59.0일반세탁업211048.953703449531.013087일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232400003240000-205-1987-0218419870613<NA>1영업/정상1영업<NA><NA><NA><NA>023427264423.10134830서울특별시 강동구 명일동 333-17번지서울특별시 강동구 양재대로136길 11 (명일동)5295대원사2003-05-26 00:00:00I2018-08-31 23:59:59.0일반세탁업212690.951004449612.9966일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
332400003240000-205-1987-0219119871219<NA>3폐업2폐업19971201<NA><NA><NA>02 0000020.00134840서울특별시 강동구 성내동 12-39번지<NA><NA>열매사2002-06-06 00:00:00I2018-08-31 23:59:59.0일반세탁업211148.767663448243.200916일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432400003240000-205-1987-0219219871219<NA>3폐업2폐업19971201<NA><NA><NA>02 0000019.72134844서울특별시 강동구 성내동 405-17번지<NA><NA>현대사2002-06-06 00:00:00I2018-08-31 23:59:59.0일반세탁업211804.926218447713.815055일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
532400003240000-205-1987-0221019871006<NA>3폐업2폐업19891023<NA><NA><NA>02 0000015.00134861서울특별시 강동구 천호동 18-96번지<NA><NA>삼성사2002-06-06 00:00:00I2018-08-31 23:59:59.0일반세탁업212284.744465449735.046172일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
632400003240000-205-1987-0221119871006<NA>1영업/정상1영업<NA><NA><NA><NA>020486604733.00134861서울특별시 강동구 천호동 47-32번지서울특별시 강동구 양재대로123길 52 (천호동)5313대원사2003-05-22 00:00:00I2018-08-31 23:59:59.0일반세탁업212227.277517449097.368248일반세탁업4111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
732400003240000-205-1987-0221219871006<NA>1영업/정상1영업<NA><NA><NA><NA>020473294020.00134863서울특별시 강동구 천호동 102-5번지서울특별시 강동구 천중로29길 5 (천호동)5311국제사2003-05-23 00:00:00I2018-08-31 23:59:59.0일반세탁업211921.282584448984.519134일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
832400003240000-205-1987-0221419871006<NA>3폐업2폐업20221020<NA><NA><NA>020477346823.10134866서울특별시 강동구 천호동 227-6서울특별시 강동구 상암로27길 16 (천호동)5308천호사2022-10-20 11:19:35U2021-10-30 22:02:00.0일반세탁업212096.810194449401.391924<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
932400003240000-205-1987-0221519871016<NA>3폐업2폐업20130214<NA><NA><NA>020482704933.00134812서울특별시 강동구 길동 369-19번지<NA><NA>백양사2003-05-23 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업4111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
76132400003240000-205-2021-000012021-01-12<NA>3폐업2폐업2023-06-07<NA><NA><NA>02 442 999832.49134-100서울특별시 강동구 강일동 76-2 아이메디컬서울특별시 강동구 아리수로93나길 38, 아이메디컬 1층 118호 (강일동)5415미사세탁(고덕강일점)2023-06-07 09:16:49U2022-12-06 00:09:00.0일반세탁업215303.913311452189.755118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
76232400003240000-205-2021-000022021-02-01<NA>3폐업2폐업2024-01-31<NA><NA><NA><NA>16.70134-090서울특별시 강동구 상일동 513 고덕센트럴 IPARK(A상가)서울특별시 강동구 고덕로80길 123, 고덕센트럴 IPARK(A상가) 114호 (상일동)5276동산수선세탁2024-01-31 14:06:38U2023-12-02 00:03:00.0일반세탁업214664.448708449988.90385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
76332400003240000-205-2021-0000320210401<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.30134803서울특별시 강동구 고덕동 236-2서울특별시 강동구 아리수로76길 17, 1층 (고덕동)5220백양세탁소2021-04-01 10:28:12I2021-04-03 00:22:58.0일반세탁업214298.918189451084.250858일반세탁업0011<NA><NA>000N0<NA><NA><NA>임대10000N
76432400003240000-205-2021-0000420210427<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.00134080서울특별시 강동구 고덕동 688 래미안힐스테이트고덕서울특별시 강동구 아리수로50길 50, 153호 (고덕동, 래미안힐스테이트고덕)5229고래힐 명품세탁2021-04-27 14:51:06I2021-04-29 00:23:08.0일반세탁업212926.089913450751.524332일반세탁업0011<NA><NA>000N0<NA><NA><NA>임대10000N
76532400003240000-205-2021-0000520210429<NA>3폐업2폐업20220518<NA><NA><NA><NA>24.44134020서울특별시 강동구 천호동 574 청운캐슬서울특별시 강동구 천중로27길 70, 101동 101호 (천호동, 청운캐슬)5312마마운동화세탁2022-05-18 16:43:41U2021-12-04 22:00:00.0운동화전문세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
76632400003240000-205-2021-0000620210813<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.00134867서울특별시 강동구 천호동 301-41 대원빌딩서울특별시 강동구 천중로 81, 대원빌딩 101호 (천호동)5321현대세탁소2021-08-13 10:11:36I2021-08-15 00:23:01.0일반세탁업211503.058382449190.279763일반세탁업001100000N0<NA><NA><NA>임대00000N
76732400003240000-205-2022-000012022-01-05<NA>3폐업2폐업2023-05-25<NA><NA><NA>02 485 848239.00134-845서울특별시 강동구 성내동 419-12서울특별시 강동구 양재대로91길 72, 1층 (성내동)5403마미운동화 빨래방2023-05-25 17:01:35U2022-12-04 22:07:00.0운동화전문세탁업211613.997669447409.628033<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
76832400003240000-205-2022-0000220221004<NA>1영업/정상1영업<NA><NA><NA><NA>02 442 436818.75134787서울특별시 강동구 명일동 42 우성아파트서울특별시 강동구 고덕로62길 66, 우성아파트 1층 101호 (명일동)5268우성세탁소2022-10-04 11:50:32I2021-10-31 00:06:00.0일반세탁업213354.8068449887.005648<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
76932400003240000-205-2022-0000320221125<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00134100서울특별시 강동구 강일동 76-7 MK프라자서울특별시 강동구 아리수로93나길 50, MK프라자 103호 (강일동)5415정하세탁2022-11-25 17:16:46I2021-10-31 22:07:00.0일반세탁업215361.163714452213.416818<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
77032400003240000-205-2024-000012024-01-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.44134-060서울특별시 강동구 둔촌동 546 신성둔촌미소지움서울특별시 강동구 명일로 104, 신성둔촌미소지움 105,106호 (둔촌동)5370신성세탁2024-02-06 10:27:54U2023-12-02 00:08:00.0세탁업 기타212555.389554447299.675826<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>