Overview

Dataset statistics

Number of variables47
Number of observations458
Missing cells4546
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory181.3 KiB
Average record size in memory405.3 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric7
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-17957/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (73.0%)Imbalance
위생업태명 is highly imbalanced (50.2%)Imbalance
사용시작지하층 is highly imbalanced (71.0%)Imbalance
사용끝지하층 is highly imbalanced (71.0%)Imbalance
여성종사자수 is highly imbalanced (71.6%)Imbalance
남성종사자수 is highly imbalanced (71.0%)Imbalance
인허가취소일자 has 458 (100.0%) missing valuesMissing
폐업일자 has 148 (32.3%) missing valuesMissing
휴업시작일자 has 458 (100.0%) missing valuesMissing
휴업종료일자 has 458 (100.0%) missing valuesMissing
재개업일자 has 458 (100.0%) missing valuesMissing
전화번호 has 87 (19.0%) missing valuesMissing
소재지면적 has 5 (1.1%) missing valuesMissing
도로명주소 has 155 (33.8%) missing valuesMissing
도로명우편번호 has 160 (34.9%) missing valuesMissing
좌표정보(X) has 19 (4.1%) missing valuesMissing
좌표정보(Y) has 19 (4.1%) missing valuesMissing
건물지상층수 has 126 (27.5%) missing valuesMissing
사용시작지상층 has 132 (28.8%) missing valuesMissing
발한실여부 has 88 (19.2%) missing valuesMissing
조건부허가신고사유 has 458 (100.0%) missing valuesMissing
조건부허가시작일자 has 458 (100.0%) missing valuesMissing
조건부허가종료일자 has 458 (100.0%) missing valuesMissing
세탁기수 has 321 (70.1%) missing valuesMissing
다중이용업소여부 has 80 (17.5%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 6 (1.3%) zerosZeros
건물지상층수 has 77 (16.8%) zerosZeros
사용시작지상층 has 5 (1.1%) zerosZeros
세탁기수 has 35 (7.6%) zerosZeros

Reproduction

Analysis started2024-05-11 08:36:33.454809
Analysis finished2024-05-11 08:36:35.706700
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3050000
458 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 458
100.0%

Length

2024-05-11T08:36:35.997675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:36.415001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 458
100.0%

관리번호
Text

UNIQUE 

Distinct458
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T08:36:37.027920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10076
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

Unique458 ?
Unique (%)100.0%

Sample

1st row3050000-205-1987-02372
2nd row3050000-205-1987-02374
3rd row3050000-205-1987-02381
4th row3050000-205-1987-02387
5th row3050000-205-1987-02388
ValueCountFrequency (%)
3050000-205-1987-02372 1
 
0.2%
3050000-205-2006-00014 1
 
0.2%
3050000-205-2006-00012 1
 
0.2%
3050000-205-2006-00011 1
 
0.2%
3050000-205-2006-00010 1
 
0.2%
3050000-205-2006-00009 1
 
0.2%
3050000-205-2006-00008 1
 
0.2%
3050000-205-2006-00007 1
 
0.2%
3050000-205-2006-00006 1
 
0.2%
3050000-205-2006-00005 1
 
0.2%
Other values (448) 448
97.8%
2024-05-11T08:36:38.417788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4456
44.2%
- 1374
 
13.6%
5 1057
 
10.5%
2 1047
 
10.4%
3 646
 
6.4%
1 380
 
3.8%
9 316
 
3.1%
8 283
 
2.8%
7 205
 
2.0%
6 158
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8702
86.4%
Dash Punctuation 1374
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4456
51.2%
5 1057
 
12.1%
2 1047
 
12.0%
3 646
 
7.4%
1 380
 
4.4%
9 316
 
3.6%
8 283
 
3.3%
7 205
 
2.4%
6 158
 
1.8%
4 154
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 1374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10076
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4456
44.2%
- 1374
 
13.6%
5 1057
 
10.5%
2 1047
 
10.4%
3 646
 
6.4%
1 380
 
3.8%
9 316
 
3.1%
8 283
 
2.8%
7 205
 
2.0%
6 158
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4456
44.2%
- 1374
 
13.6%
5 1057
 
10.5%
2 1047
 
10.4%
3 646
 
6.4%
1 380
 
3.8%
9 316
 
3.1%
8 283
 
2.8%
7 205
 
2.0%
6 158
 
1.6%

인허가일자
Date

Distinct319
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1987-06-20 00:00:00
Maximum2023-07-13 00:00:00
2024-05-11T08:36:38.928839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:36:39.441439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3
310 
1
148 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 310
67.7%
1 148
32.3%

Length

2024-05-11T08:36:39.849675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:40.159004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 310
67.7%
1 148
32.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
310 
영업/정상
148 

Length

Max length5
Median length2
Mean length2.9694323
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 310
67.7%
영업/정상 148
32.3%

Length

2024-05-11T08:36:40.495760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:40.864213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 310
67.7%
영업/정상 148
32.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2
310 
1
148 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 310
67.7%
1 148
32.3%

Length

2024-05-11T08:36:41.190106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:41.577070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 310
67.7%
1 148
32.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
310 
영업
148 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 310
67.7%
영업 148
32.3%

Length

2024-05-11T08:36:41.927356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:42.281676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 310
67.7%
영업 148
32.3%

폐업일자
Date

MISSING 

Distinct280
Distinct (%)90.3%
Missing148
Missing (%)32.3%
Memory size3.7 KiB
Minimum2003-06-27 00:00:00
Maximum2024-04-12 00:00:00
2024-05-11T08:36:42.606647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:36:43.081076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct355
Distinct (%)95.7%
Missing87
Missing (%)19.0%
Memory size3.7 KiB
2024-05-11T08:36:43.663078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.148248
Min length10

Characters and Unicode

Total characters3765
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

Unique340 ?
Unique (%)91.6%

Sample

1st row0222468664
2nd row0222468701
3rd row0209621746
4th row02 2121638
5th row0209629104
ValueCountFrequency (%)
02 118
 
22.1%
02962 5
 
0.9%
02964 4
 
0.7%
02968 4
 
0.7%
0222131960 3
 
0.6%
02923 3
 
0.6%
02963 3
 
0.6%
9666641 2
 
0.4%
0222136361 2
 
0.4%
02966 2
 
0.4%
Other values (371) 389
72.7%
2024-05-11T08:36:44.662780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1002
26.6%
0 571
15.2%
4 338
 
9.0%
6 318
 
8.4%
9 302
 
8.0%
3 251
 
6.7%
1 244
 
6.5%
5 192
 
5.1%
190
 
5.0%
7 180
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3575
95.0%
Space Separator 190
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1002
28.0%
0 571
16.0%
4 338
 
9.5%
6 318
 
8.9%
9 302
 
8.4%
3 251
 
7.0%
1 244
 
6.8%
5 192
 
5.4%
7 180
 
5.0%
8 177
 
5.0%
Space Separator
ValueCountFrequency (%)
190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3765
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1002
26.6%
0 571
15.2%
4 338
 
9.0%
6 318
 
8.4%
9 302
 
8.0%
3 251
 
6.7%
1 244
 
6.5%
5 192
 
5.1%
190
 
5.0%
7 180
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3765
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1002
26.6%
0 571
15.2%
4 338
 
9.0%
6 318
 
8.4%
9 302
 
8.0%
3 251
 
6.7%
1 244
 
6.5%
5 192
 
5.1%
190
 
5.0%
7 180
 
4.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct293
Distinct (%)64.7%
Missing5
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean29.632715
Minimum0
Maximum364
Zeros6
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:36:45.141496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.53
Q117.35
median24.67
Q332
95-th percentile60.97
Maximum364
Range364
Interquartile range (IQR)14.65

Descriptive statistics

Standard deviation29.729115
Coefficient of variation (CV)1.0032532
Kurtosis56.582255
Mean29.632715
Median Absolute Deviation (MAD)7.33
Skewness6.5493683
Sum13423.62
Variance883.82029
MonotonicityNot monotonic
2024-05-11T08:36:45.630663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 13
 
2.8%
30.0 9
 
2.0%
26.0 9
 
2.0%
23.0 7
 
1.5%
25.0 7
 
1.5%
20.0 7
 
1.5%
23.1 7
 
1.5%
15.0 7
 
1.5%
13.0 6
 
1.3%
26.4 6
 
1.3%
Other values (283) 375
81.9%
ValueCountFrequency (%)
0.0 6
1.3%
8.32 1
 
0.2%
9.0 1
 
0.2%
9.6 2
 
0.4%
9.9 1
 
0.2%
10.0 1
 
0.2%
10.2 1
 
0.2%
10.4 1
 
0.2%
10.5 2
 
0.4%
10.9 1
 
0.2%
ValueCountFrequency (%)
364.0 1
0.2%
280.0 1
0.2%
244.36 1
0.2%
208.68 1
0.2%
201.0 1
0.2%
128.62 1
0.2%
114.1 1
0.2%
111.0 1
0.2%
106.83 1
0.2%
90.0 1
0.2%

소재지우편번호
Text

Distinct100
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T08:36:46.177558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0458515
Min length6

Characters and Unicode

Total characters2769
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

Unique39 ?
Unique (%)8.5%

Sample

1st row130837
2nd row130843
3rd row130864
4th row130843
5th row130822
ValueCountFrequency (%)
130842 21
 
4.6%
130827 15
 
3.3%
130831 15
 
3.3%
130839 14
 
3.1%
130840 14
 
3.1%
130817 13
 
2.8%
130862 12
 
2.6%
130867 11
 
2.4%
130829 11
 
2.4%
130835 11
 
2.4%
Other values (90) 321
70.1%
2024-05-11T08:36:47.125097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 580
20.9%
3 572
20.7%
1 522
18.9%
8 488
17.6%
2 121
 
4.4%
4 116
 
4.2%
7 110
 
4.0%
5 102
 
3.7%
6 92
 
3.3%
9 45
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2748
99.2%
Dash Punctuation 21
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 580
21.1%
3 572
20.8%
1 522
19.0%
8 488
17.8%
2 121
 
4.4%
4 116
 
4.2%
7 110
 
4.0%
5 102
 
3.7%
6 92
 
3.3%
9 45
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2769
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 580
20.9%
3 572
20.7%
1 522
18.9%
8 488
17.6%
2 121
 
4.4%
4 116
 
4.2%
7 110
 
4.0%
5 102
 
3.7%
6 92
 
3.3%
9 45
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 580
20.9%
3 572
20.7%
1 522
18.9%
8 488
17.6%
2 121
 
4.4%
4 116
 
4.2%
7 110
 
4.0%
5 102
 
3.7%
6 92
 
3.3%
9 45
 
1.6%

지번주소
Text

Distinct451
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T08:36:47.853400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length51
Mean length27.489083
Min length18

Characters and Unicode

Total characters12590
Distinct characters187
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

Unique444 ?
Unique (%)96.9%

Sample

1st row서울특별시 동대문구 장안동 195-11번지 (장일중앙길14)
2nd row서울특별시 동대문구 장안동 405-12번지
3rd row서울특별시 동대문구 제기동 892-12번지 (약령서길38)
4th row서울특별시 동대문구 장안동 400-6번지
5th row서울특별시 동대문구 용두동 80-8번지 (용두일길11)
ValueCountFrequency (%)
서울특별시 458
21.3%
동대문구 458
21.3%
장안동 127
 
5.9%
이문동 64
 
3.0%
전농동 60
 
2.8%
답십리동 55
 
2.6%
1층 45
 
2.1%
용두동 42
 
1.9%
휘경동 37
 
1.7%
제기동 35
 
1.6%
Other values (648) 773
35.9%
2024-05-11T08:36:49.061307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2076
 
16.5%
동 952
 
7.6%
문 531
 
4.2%
1 531
 
4.2%
대 474
 
3.8%
시 465
 
3.7%
서 461
 
3.7%
구 459
 
3.6%
울 459
 
3.6%
특 458
 
3.6%
Other values (177) 5724
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7290
57.9%
Decimal Number 2522
 
20.0%
Space Separator 2076
 
16.5%
Dash Punctuation 416
 
3.3%
Close Punctuation 134
 
1.1%
Open Punctuation 134
 
1.1%
Uppercase Letter 13
 
0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 952
13.1%
문 531
 
7.3%
대 474
 
6.5%
시 465
 
6.4%
서 461
 
6.3%
구 459
 
6.3%
울 459
 
6.3%
특 458
 
6.3%
별 458
 
6.3%
지 352
 
4.8%
Other values (154) 2221
30.5%
Decimal Number
ValueCountFrequency (%)
1 531
21.1%
2 349
13.8%
3 343
13.6%
4 247
9.8%
5 208
 
8.2%
9 184
 
7.3%
6 172
 
6.8%
0 171
 
6.8%
8 161
 
6.4%
7 156
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
30.8%
K 4
30.8%
A 2
15.4%
Y 1
 
7.7%
L 1
 
7.7%
B 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
. 1
 
20.0%
@ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2076
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 416
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7290
57.9%
Common 5287
42.0%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 952
13.1%
문 531
 
7.3%
대 474
 
6.5%
시 465
 
6.4%
서 461
 
6.3%
구 459
 
6.3%
울 459
 
6.3%
특 458
 
6.3%
별 458
 
6.3%
지 352
 
4.8%
Other values (154) 2221
30.5%
Common
ValueCountFrequency (%)
2076
39.3%
1 531
 
10.0%
- 416
 
7.9%
2 349
 
6.6%
3 343
 
6.5%
4 247
 
4.7%
5 208
 
3.9%
9 184
 
3.5%
6 172
 
3.3%
0 171
 
3.2%
Other values (7) 590
 
11.2%
Latin
ValueCountFrequency (%)
S 4
30.8%
K 4
30.8%
A 2
15.4%
Y 1
 
7.7%
L 1
 
7.7%
B 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7290
57.9%
ASCII 5300
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2076
39.2%
1 531
 
10.0%
- 416
 
7.8%
2 349
 
6.6%
3 343
 
6.5%
4 247
 
4.7%
5 208
 
3.9%
9 184
 
3.5%
6 172
 
3.2%
0 171
 
3.2%
Other values (13) 603
 
11.4%
Hangul
ValueCountFrequency (%)
동 952
13.1%
문 531
 
7.3%
대 474
 
6.5%
시 465
 
6.4%
서 461
 
6.3%
구 459
 
6.3%
울 459
 
6.3%
특 458
 
6.3%
별 458
 
6.3%
지 352
 
4.8%
Other values (154) 2221
30.5%

도로명주소
Text

MISSING 

Distinct293
Distinct (%)96.7%
Missing155
Missing (%)33.8%
Memory size3.7 KiB
2024-05-11T08:36:49.783673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length52
Mean length32.085809
Min length23

Characters and Unicode

Total characters9722
Distinct characters168
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

Unique285 ?
Unique (%)94.1%

Sample

1st row서울특별시 동대문구 천호대로77가길 9-2 (장안동)
2nd row서울특별시 동대문구 천호대로79길 89 (장안동)
3rd row서울특별시 동대문구 무학로43길 47 (용두동)
4th row서울특별시 동대문구 천호대로7길 17 (신설동)
5th row서울특별시 동대문구 제기로6길 22 (제기동)
ValueCountFrequency (%)
서울특별시 303
 
16.9%
동대문구 303
 
16.9%
1층 102
 
5.7%
장안동 72
 
4.0%
이문동 44
 
2.5%
전농동 36
 
2.0%
용두동 27
 
1.5%
답십리동 24
 
1.3%
제기동 21
 
1.2%
휘경동 20
 
1.1%
Other values (463) 841
46.9%
2024-05-11T08:36:51.073831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1491
 
15.3%
동 661
 
6.8%
1 441
 
4.5%
문 376
 
3.9%
대 360
 
3.7%
) 337
 
3.5%
( 337
 
3.5%
시 330
 
3.4%
서 314
 
3.2%
울 312
 
3.2%
Other values (158) 4763
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5779
59.4%
Decimal Number 1500
 
15.4%
Space Separator 1491
 
15.3%
Close Punctuation 337
 
3.5%
Open Punctuation 337
 
3.5%
Other Punctuation 226
 
2.3%
Dash Punctuation 41
 
0.4%
Uppercase Letter 10
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 661
 
11.4%
문 376
 
6.5%
대 360
 
6.2%
시 330
 
5.7%
서 314
 
5.4%
울 312
 
5.4%
로 304
 
5.3%
구 303
 
5.2%
별 303
 
5.2%
특 303
 
5.2%
Other values (134) 2213
38.3%
Decimal Number
ValueCountFrequency (%)
1 441
29.4%
2 226
15.1%
3 142
 
9.5%
4 124
 
8.3%
0 109
 
7.3%
6 108
 
7.2%
5 107
 
7.1%
8 96
 
6.4%
7 88
 
5.9%
9 59
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
S 3
30.0%
K 3
30.0%
B 1
 
10.0%
Y 1
 
10.0%
L 1
 
10.0%
A 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 224
99.1%
/ 1
 
0.4%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 337
100.0%
Open Punctuation
ValueCountFrequency (%)
( 337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5779
59.4%
Common 3932
40.4%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 661
 
11.4%
문 376
 
6.5%
대 360
 
6.2%
시 330
 
5.7%
서 314
 
5.4%
울 312
 
5.4%
로 304
 
5.3%
구 303
 
5.2%
별 303
 
5.2%
특 303
 
5.2%
Other values (134) 2213
38.3%
Common
ValueCountFrequency (%)
1491
37.9%
1 441
 
11.2%
) 337
 
8.6%
( 337
 
8.6%
2 226
 
5.7%
, 224
 
5.7%
3 142
 
3.6%
4 124
 
3.2%
0 109
 
2.8%
6 108
 
2.7%
Other values (7) 393
 
10.0%
Latin
ValueCountFrequency (%)
S 3
27.3%
K 3
27.3%
B 1
 
9.1%
Y 1
 
9.1%
L 1
 
9.1%
A 1
 
9.1%
b 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5779
59.4%
ASCII 3943
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1491
37.8%
1 441
 
11.2%
) 337
 
8.5%
( 337
 
8.5%
2 226
 
5.7%
, 224
 
5.7%
3 142
 
3.6%
4 124
 
3.1%
0 109
 
2.8%
6 108
 
2.7%
Other values (14) 404
 
10.2%
Hangul
ValueCountFrequency (%)
동 661
 
11.4%
문 376
 
6.5%
대 360
 
6.2%
시 330
 
5.7%
서 314
 
5.4%
울 312
 
5.4%
로 304
 
5.3%
구 303
 
5.2%
별 303
 
5.2%
특 303
 
5.2%
Other values (134) 2213
38.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct155
Distinct (%)52.0%
Missing160
Missing (%)34.9%
Infinite0
Infinite (%)0.0%
Mean2534.057
Minimum2401
Maximum2646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:36:51.637964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2401
5-th percentile2412
Q12473.25
median2534
Q32602
95-th percentile2639
Maximum2646
Range245
Interquartile range (IQR)128.75

Descriptive statistics

Standard deviation74.498504
Coefficient of variation (CV)0.029398905
Kurtosis-1.2094098
Mean2534.057
Median Absolute Deviation (MAD)64
Skewness-0.15767615
Sum755149
Variance5550.027
MonotonicityNot monotonic
2024-05-11T08:36:52.111356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2624 8
 
1.7%
2639 6
 
1.3%
2578 5
 
1.1%
2441 5
 
1.1%
2524 5
 
1.1%
2480 5
 
1.1%
2641 4
 
0.9%
2449 4
 
0.9%
2507 4
 
0.9%
2562 4
 
0.9%
Other values (145) 248
54.1%
(Missing) 160
34.9%
ValueCountFrequency (%)
2401 3
0.7%
2403 1
 
0.2%
2404 3
0.7%
2405 1
 
0.2%
2407 2
0.4%
2409 3
0.7%
2410 1
 
0.2%
2412 2
0.4%
2413 2
0.4%
2414 1
 
0.2%
ValueCountFrequency (%)
2646 3
0.7%
2644 1
 
0.2%
2643 2
 
0.4%
2642 2
 
0.4%
2641 4
0.9%
2640 2
 
0.4%
2639 6
1.3%
2638 1
 
0.2%
2637 3
0.7%
2636 4
0.9%

사업장명
Text

Distinct343
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T08:36:52.620978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length4.4716157
Min length2

Characters and Unicode

Total characters2048
Distinct characters235
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

Unique273 ?
Unique (%)59.6%

Sample

1st row두꺼비
2nd row대중사
3rd row백영사
4th row백설사
5th row형신사
ValueCountFrequency (%)
백조사 9
 
1.9%
백양사 8
 
1.7%
현대세탁소 6
 
1.3%
세탁소 6
 
1.3%
백영사 5
 
1.0%
현대사 5
 
1.0%
백양세탁소 4
 
0.8%
현대세탁 4
 
0.8%
월풀빨래방 4
 
0.8%
광명사 4
 
0.8%
Other values (339) 424
88.5%
2024-05-11T08:36:53.619390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 201
 
9.8%
세 175
 
8.5%
탁 175
 
8.5%
소 113
 
5.5%
백 55
 
2.7%
래 41
 
2.0%
성 40
 
2.0%
빨 35
 
1.7%
방 35
 
1.7%
대 35
 
1.7%
Other values (225) 1143
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1996
97.5%
Space Separator 24
 
1.2%
Decimal Number 12
 
0.6%
Uppercase Letter 11
 
0.5%
Dash Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 201
 
10.1%
세 175
 
8.8%
탁 175
 
8.8%
소 113
 
5.7%
백 55
 
2.8%
래 41
 
2.1%
성 40
 
2.0%
빨 35
 
1.8%
방 35
 
1.8%
대 35
 
1.8%
Other values (211) 1091
54.7%
Uppercase Letter
ValueCountFrequency (%)
G 3
27.3%
L 3
27.3%
A 2
18.2%
W 1
 
9.1%
J 1
 
9.1%
Z 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 7
58.3%
4 5
41.7%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1996
97.5%
Common 40
 
2.0%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 201
 
10.1%
세 175
 
8.8%
탁 175
 
8.8%
소 113
 
5.7%
백 55
 
2.8%
래 41
 
2.1%
성 40
 
2.0%
빨 35
 
1.8%
방 35
 
1.8%
대 35
 
1.8%
Other values (211) 1091
54.7%
Common
ValueCountFrequency (%)
24
60.0%
2 7
 
17.5%
4 5
 
12.5%
- 1
 
2.5%
& 1
 
2.5%
) 1
 
2.5%
( 1
 
2.5%
Latin
ValueCountFrequency (%)
G 3
25.0%
L 3
25.0%
A 2
16.7%
W 1
 
8.3%
J 1
 
8.3%
e 1
 
8.3%
Z 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1996
97.5%
ASCII 52
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 201
 
10.1%
세 175
 
8.8%
탁 175
 
8.8%
소 113
 
5.7%
백 55
 
2.8%
래 41
 
2.1%
성 40
 
2.0%
빨 35
 
1.8%
방 35
 
1.8%
대 35
 
1.8%
Other values (211) 1091
54.7%
ASCII
ValueCountFrequency (%)
24
46.2%
2 7
 
13.5%
4 5
 
9.6%
G 3
 
5.8%
L 3
 
5.8%
A 2
 
3.8%
W 1
 
1.9%
J 1
 
1.9%
- 1
 
1.9%
e 1
 
1.9%
Other values (4) 4
 
7.7%

최종수정일자
Date

Distinct389
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2003-03-24 00:00:00
Maximum2024-04-12 17:26:06
2024-05-11T08:36:53.896333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:36:54.222283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
I
301 
U
157 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 301
65.7%
U 157
34.3%

Length

2024-05-11T08:36:54.499993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:54.706225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 301
65.7%
u 157
34.3%

데이터갱신일자
Date

Distinct133
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:04:00
2024-05-11T08:36:55.032367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:36:55.437063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반세탁업
418 
빨래방업
 
25
운동화전문세탁업
 
10
세탁업 기타
 
5

Length

Max length8
Median length5
Mean length5.0218341
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 418
91.3%
빨래방업 25
 
5.5%
운동화전문세탁업 10
 
2.2%
세탁업 기타 5
 
1.1%

Length

2024-05-11T08:36:55.842759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:56.150659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 418
90.3%
빨래방업 25
 
5.4%
운동화전문세탁업 10
 
2.2%
세탁업 5
 
1.1%
기타 5
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct363
Distinct (%)82.7%
Missing19
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean204956.96
Minimum202145.73
Maximum206590.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:36:56.817717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202145.73
5-th percentile202796.43
Q1204207.41
median205210.66
Q3205829.91
95-th percentile206396.87
Maximum206590.05
Range4444.3141
Interquartile range (IQR)1622.4982

Descriptive statistics

Standard deviation1111.9964
Coefficient of variation (CV)0.0054255116
Kurtosis-0.50343262
Mean204956.96
Median Absolute Deviation (MAD)745.95545
Skewness-0.66935381
Sum89976107
Variance1236535.9
MonotonicityNot monotonic
2024-05-11T08:36:57.249985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206590.046202018 8
 
1.7%
203594.89002851 4
 
0.9%
205271.704936121 4
 
0.9%
205649.766438518 3
 
0.7%
203735.418776552 3
 
0.7%
205027.544251529 3
 
0.7%
204089.817117361 3
 
0.7%
205954.030465451 3
 
0.7%
206453.980260918 3
 
0.7%
205764.252046853 2
 
0.4%
Other values (353) 403
88.0%
(Missing) 19
 
4.1%
ValueCountFrequency (%)
202145.732067019 1
0.2%
202206.095110985 1
0.2%
202257.985695221 1
0.2%
202322.997422803 1
0.2%
202341.643845812 1
0.2%
202373.95385279 1
0.2%
202374.477394445 1
0.2%
202421.272662443 1
0.2%
202435.631005989 1
0.2%
202505.816544908 1
0.2%
ValueCountFrequency (%)
206590.046202018 8
1.7%
206586.572428103 2
 
0.4%
206521.405320134 2
 
0.4%
206485.471340735 1
 
0.2%
206484.233644024 1
 
0.2%
206483.555525111 1
 
0.2%
206467.439786823 1
 
0.2%
206453.980260918 3
 
0.7%
206419.497908653 2
 
0.4%
206412.153025463 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct363
Distinct (%)82.7%
Missing19
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean453088.48
Minimum451092.01
Maximum455899.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:36:57.565412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451092.01
5-th percentile451417.74
Q1452104.89
median452860.67
Q3453922.73
95-th percentile455229.41
Maximum455899.98
Range4807.9749
Interquartile range (IQR)1817.8469

Descriptive statistics

Standard deviation1200.3142
Coefficient of variation (CV)0.0026491827
Kurtosis-0.74874388
Mean453088.48
Median Absolute Deviation (MAD)872.45291
Skewness0.45175324
Sum1.9890584 × 108
Variance1440754.2
MonotonicityNot monotonic
2024-05-11T08:36:58.102109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452410.619464697 8
 
1.7%
453625.626503834 4
 
0.9%
452706.897879436 4
 
0.9%
451860.629398111 3
 
0.7%
453376.974761127 3
 
0.7%
451546.21295578 3
 
0.7%
453314.135663101 3
 
0.7%
451191.758625155 3
 
0.7%
451744.383087562 3
 
0.7%
451705.563105342 2
 
0.4%
Other values (353) 403
88.0%
(Missing) 19
 
4.1%
ValueCountFrequency (%)
451092.007482124 1
 
0.2%
451151.851538223 1
 
0.2%
451153.480867218 1
 
0.2%
451175.469414988 1
 
0.2%
451183.08273569 1
 
0.2%
451191.758625155 3
0.7%
451204.020073624 1
 
0.2%
451218.341681454 1
 
0.2%
451246.138464487 2
0.4%
451250.289450048 1
 
0.2%
ValueCountFrequency (%)
455899.982370316 2
0.4%
455758.767536948 1
0.2%
455737.080962827 1
0.2%
455735.644473957 1
0.2%
455646.252375629 1
0.2%
455645.787564326 1
0.2%
455630.081586315 1
0.2%
455612.996762285 1
0.2%
455607.35377855 1
0.2%
455584.872318917 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반세탁업
340 
<NA>
80 
빨래방업
 
25
운동화전문세탁업
 
10
세탁업 기타
 
3

Length

Max length8
Median length5
Mean length4.8427948
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 340
74.2%
<NA> 80
 
17.5%
빨래방업 25
 
5.5%
운동화전문세탁업 10
 
2.2%
세탁업 기타 3
 
0.7%

Length

2024-05-11T08:36:58.692700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:36:59.064153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 340
73.8%
na 80
 
17.4%
빨래방업 25
 
5.4%
운동화전문세탁업 10
 
2.2%
세탁업 3
 
0.7%
기타 3
 
0.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)3.0%
Missing126
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean2.0993976
Minimum0
Maximum30
Zeros77
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:36:59.389005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum30
Range30
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1818531
Coefficient of variation (CV)1.0392758
Kurtosis80.651707
Mean2.0993976
Median Absolute Deviation (MAD)1
Skewness6.5598415
Sum697
Variance4.760483
MonotonicityNot monotonic
2024-05-11T08:36:59.750441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 102
22.3%
0 77
16.8%
2 59
12.9%
1 50
 
10.9%
4 33
 
7.2%
5 6
 
1.3%
6 2
 
0.4%
11 1
 
0.2%
8 1
 
0.2%
30 1
 
0.2%
(Missing) 126
27.5%
ValueCountFrequency (%)
0 77
16.8%
1 50
10.9%
2 59
12.9%
3 102
22.3%
4 33
 
7.2%
5 6
 
1.3%
6 2
 
0.4%
8 1
 
0.2%
11 1
 
0.2%
30 1
 
0.2%
ValueCountFrequency (%)
30 1
 
0.2%
11 1
 
0.2%
8 1
 
0.2%
6 2
 
0.4%
5 6
 
1.3%
4 33
 
7.2%
3 102
22.3%
2 59
12.9%
1 50
10.9%
0 77
16.8%

건물지하층수
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
283 
0
97 
1
77 
5
 
1

Length

Max length4
Median length4
Mean length2.8537118
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 283
61.8%
0 97
 
21.2%
1 77
 
16.8%
5 1
 
0.2%

Length

2024-05-11T08:37:00.169647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:00.493200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 283
61.8%
0 97
 
21.2%
1 77
 
16.8%
5 1
 
0.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.8%
Missing132
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean1.0981595
Minimum0
Maximum6
Zeros5
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:37:00.803401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.49879515
Coefficient of variation (CV)0.45421011
Kurtosis42.22644
Mean1.0981595
Median Absolute Deviation (MAD)0
Skewness5.4355169
Sum358
Variance0.2487966
MonotonicityNot monotonic
2024-05-11T08:37:01.076381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 296
64.6%
2 18
 
3.9%
0 5
 
1.1%
3 5
 
1.1%
5 1
 
0.2%
6 1
 
0.2%
(Missing) 132
28.8%
ValueCountFrequency (%)
0 5
 
1.1%
1 296
64.6%
2 18
 
3.9%
3 5
 
1.1%
5 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 1
 
0.2%
3 5
 
1.1%
2 18
 
3.9%
1 296
64.6%
0 5
 
1.1%

사용끝지상층
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
1
300 
<NA>
131 
2
 
20
0
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.8580786
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 300
65.5%
<NA> 131
28.6%
2 20
 
4.4%
0 5
 
1.1%
3 2
 
0.4%

Length

2024-05-11T08:37:01.374822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:01.630874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 300
65.5%
na 131
28.6%
2 20
 
4.4%
0 5
 
1.1%
3 2
 
0.4%

사용시작지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
420 
0
 
33
1
 
5

Length

Max length4
Median length4
Mean length3.7510917
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 420
91.7%
0 33
 
7.2%
1 5
 
1.1%

Length

2024-05-11T08:37:01.894802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:02.161349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 420
91.7%
0 33
 
7.2%
1 5
 
1.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
420 
0
 
33
1
 
5

Length

Max length4
Median length4
Mean length3.7510917
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 420
91.7%
0 33
 
7.2%
1 5
 
1.1%

Length

2024-05-11T08:37:02.405940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:02.638682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 420
91.7%
0 33
 
7.2%
1 5
 
1.1%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
346 
0
112 

Length

Max length4
Median length4
Mean length3.2663755
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 346
75.5%
0 112
 
24.5%

Length

2024-05-11T08:37:02.958091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:03.300472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
75.5%
0 112
 
24.5%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
346 
0
112 

Length

Max length4
Median length4
Mean length3.2663755
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 346
75.5%
0 112
 
24.5%

Length

2024-05-11T08:37:03.577347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:03.817142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
75.5%
0 112
 
24.5%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
346 
0
112 

Length

Max length4
Median length4
Mean length3.2663755
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 346
75.5%
0 112
 
24.5%

Length

2024-05-11T08:37:04.182332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:04.526035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
75.5%
0 112
 
24.5%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing88
Missing (%)19.2%
Memory size1.0 KiB
False
370 
(Missing)
88 
ValueCountFrequency (%)
False 370
80.8%
(Missing) 88
 
19.2%
2024-05-11T08:37:04.800200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
346 
0
112 

Length

Max length4
Median length4
Mean length3.2663755
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 346
75.5%
0 112
 
24.5%

Length

2024-05-11T08:37:05.166871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:05.463252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
75.5%
0 112
 
24.5%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing458
Missing (%)100.0%
Memory size4.2 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
232 
임대
190 
자가
36 

Length

Max length4
Median length4
Mean length3.0131004
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임대
2nd row임대
3rd row임대
4th row임대
5th row자가

Common Values

ValueCountFrequency (%)
<NA> 232
50.7%
임대 190
41.5%
자가 36
 
7.9%

Length

2024-05-11T08:37:05.798677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:06.067904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
50.7%
임대 190
41.5%
자가 36
 
7.9%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)5.1%
Missing321
Missing (%)70.1%
Infinite0
Infinite (%)0.0%
Mean1.6423358
Minimum0
Maximum6
Zeros35
Zeros (%)7.6%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T08:37:06.285422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3705797
Coefficient of variation (CV)0.83453073
Kurtosis0.36233901
Mean1.6423358
Median Absolute Deviation (MAD)1
Skewness0.70540516
Sum225
Variance1.8784886
MonotonicityNot monotonic
2024-05-11T08:37:06.602767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 42
 
9.2%
0 35
 
7.6%
1 29
 
6.3%
3 18
 
3.9%
4 9
 
2.0%
5 2
 
0.4%
6 2
 
0.4%
(Missing) 321
70.1%
ValueCountFrequency (%)
0 35
7.6%
1 29
6.3%
2 42
9.2%
3 18
3.9%
4 9
 
2.0%
5 2
 
0.4%
6 2
 
0.4%
ValueCountFrequency (%)
6 2
 
0.4%
5 2
 
0.4%
4 9
 
2.0%
3 18
3.9%
2 42
9.2%
1 29
6.3%
0 35
7.6%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
417 
0
 
40
1
 
1

Length

Max length4
Median length4
Mean length3.731441
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> 417
91.0%
0 40
 
8.7%
1 1
 
0.2%

Length

2024-05-11T08:37:07.015275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:07.241351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 417
91.0%
0 40
 
8.7%
1 1
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
417 
0
 
39
1
 
2

Length

Max length4
Median length4
Mean length3.731441
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> 417
91.0%
0 39
 
8.5%
1 2
 
0.4%

Length

2024-05-11T08:37:07.486207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:07.740855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 417
91.0%
0 39
 
8.5%
1 2
 
0.4%

회수건조수
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
285 
0
85 
1
78 
3
 
7
2
 
3

Length

Max length4
Median length4
Mean length2.8668122
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 285
62.2%
0 85
 
18.6%
1 78
 
17.0%
3 7
 
1.5%
2 3
 
0.7%

Length

2024-05-11T08:37:08.356110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:09.272505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
62.2%
0 85
 
18.6%
1 78
 
17.0%
3 7
 
1.5%
2 3
 
0.7%

침대수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
381 
0
77 

Length

Max length4
Median length4
Mean length3.4956332
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 381
83.2%
0 77
 
16.8%

Length

2024-05-11T08:37:10.402971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:11.436321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
83.2%
0 77
 
16.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing80
Missing (%)17.5%
Memory size1.0 KiB
False
378 
(Missing)
80 
ValueCountFrequency (%)
False 378
82.5%
(Missing) 80
 
17.5%
2024-05-11T08:37:12.159041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030500003050000-205-1987-0237219870620<NA>3폐업2폐업20081113<NA><NA><NA>022246866422.12130837서울특별시 동대문구 장안동 195-11번지 (장일중앙길14)<NA><NA>두꺼비2007-05-25 00:00:00I2018-08-31 23:59:59.0일반세탁업205591.831559451635.523228일반세탁업4<NA><NA>1<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
130500003050000-205-1987-0237419870620<NA>3폐업2폐업20171201<NA><NA><NA>022246870114.4130843서울특별시 동대문구 장안동 405-12번지서울특별시 동대문구 천호대로77가길 9-2 (장안동)2635대중사2017-12-01 13:00:35I2018-08-31 23:59:59.0일반세탁업205478.896614451310.874222일반세탁업4<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA>0<NA>N
230500003050000-205-1987-0238119870624<NA>3폐업2폐업20110817<NA><NA><NA>020962174648.0130864서울특별시 동대문구 제기동 892-12번지 (약령서길38)<NA><NA>백영사2011-08-17 15:50:52I2018-08-31 23:59:59.0일반세탁업203133.56129453027.983308일반세탁업4111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
330500003050000-205-1987-0238719870626<NA>1영업/정상1영업<NA><NA><NA><NA>02 212163815.0130843서울특별시 동대문구 장안동 400-6번지서울특별시 동대문구 천호대로79길 89 (장안동)2630백설사2019-01-04 10:44:22U2019-01-06 02:40:00.0일반세탁업205677.330653451533.153866일반세탁업201100000N0<NA><NA><NA>임대0<NA><NA>00N
430500003050000-205-1987-0238819870626<NA>3폐업2폐업20071206<NA><NA><NA>020962910434.45130822서울특별시 동대문구 용두동 80-8번지 (용두일길11)<NA><NA>형신사2007-05-25 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
530500003050000-205-1987-0238919870626<NA>3폐업2폐업20180725<NA><NA><NA>02926 451115.6130823서울특별시 동대문구 용두동 200-2번지서울특별시 동대문구 무학로43길 47 (용두동)2578백운사2018-07-25 15:56:53I2018-08-31 23:59:59.0일반세탁업202435.631006453012.090838일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA>1<NA>N
630500003050000-205-1987-0239019870626<NA>1영업/정상1영업<NA><NA><NA><NA>02922 767013.0130811서울특별시 동대문구 신설동 93-42서울특별시 동대문구 천호대로7길 17 (신설동)2582태창사2022-12-02 08:59:00U2021-11-02 00:04:00.0일반세탁업202373.953853452498.880329<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730500003050000-205-1987-0239619870629<NA>3폐업2폐업20181218<NA><NA><NA>02 923731813.0130860서울특별시 동대문구 제기동 67-14번지서울특별시 동대문구 제기로6길 22 (제기동)2475한양사2018-12-18 15:20:21U2018-12-20 02:40:00.0일반세탁업202959.854577453681.035767일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
830500003050000-205-1987-0239919870629<NA>3폐업2폐업20130719<NA><NA><NA>020923491521.6130860서울특별시 동대문구 제기동 135-67번지 (고대앞2길10)<NA><NA>경일사2007-05-25 00:00:00I2018-08-31 23:59:59.0일반세탁업203066.251739453873.122449일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
930500003050000-205-1987-0240019870629<NA>3폐업2폐업20050929<NA><NA><NA>020244081326.0130843서울특별시 동대문구 장안동 406-11번지<NA><NA>성북사2004-03-16 00:00:00I2018-08-31 23:59:59.0일반세탁업205426.777178451218.341681일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
44830500003050000-205-2022-0000220220819<NA>1영업/정상1영업<NA><NA><NA><NA>02 2245960617.84130848서울특별시 동대문구 전농동 6 전농우성아파트서울특별시 동대문구 사가정로 190, 2층 11,12호 (전농동, 전농우성아파트)2533우성세탁소2022-08-19 11:05:51I2021-12-07 22:01:00.0일반세탁업205668.475125452777.056578<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44930500003050000-205-2022-0000320221102<NA>1영업/정상1영업<NA><NA><NA><NA>02 2215254829.0130842서울특별시 동대문구 장안동 390-1서울특별시 동대문구 한천로26길 44, 1층 (장안동)2624잉꼬세탁2022-11-02 11:28:22I2021-11-01 00:04:00.0일반세탁업205949.522967452094.668449<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45030500003050000-205-2022-000042022-11-08<NA>3폐업2폐업2023-10-31<NA><NA><NA><NA>17.0130-863서울특별시 동대문구 제기동 122-518서울특별시 동대문구 회기로4길 41, 1층 (제기동)2465일류세탁2023-10-31 15:54:38U2022-11-01 00:02:00.0일반세탁업203221.35327454112.250027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45130500003050000-205-2022-0000520221109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.53130817서울특별시 동대문구 용두동 39-112서울특별시 동대문구 천호대로35길 25, 1층 (용두동)2564백성세탁소2022-11-09 10:39:15I2021-10-31 23:01:00.0일반세탁업203587.373928452462.586888<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45230500003050000-205-2022-000062022-11-15<NA>3폐업2폐업2023-10-25<NA><NA><NA>02 969240530.0130-817서울특별시 동대문구 용두동 39-574서울특별시 동대문구 고산자로30길 67, 1층 (용두동)2562태광 세탁2023-10-25 10:29:21U2022-10-30 22:08:00.0일반세탁업203650.948629452568.757787<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45330500003050000-205-2023-0000120230109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.6130844서울특별시 동대문구 장안동 431-5 신부파스칼텔서울특별시 동대문구 천호대로83길 32, 신부파스칼텔 103호 (장안동)2636화이트 세탁소2023-01-09 15:19:43I2022-11-30 23:01:00.0일반세탁업205692.623595451246.138464<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45430500003050000-205-2023-000022023-02-15<NA>1영업/정상1영업<NA><NA><NA><NA>02 964 322233.0130-867서울특별시 동대문구 청량리동 52-2서울특별시 동대문구 왕산로45길 21, 1층 (청량리동)2488유미사2023-02-15 15:00:18I2022-12-01 23:07:00.0일반세탁업204232.967212453574.746652<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45530500003050000-205-2023-000032023-03-20<NA>3폐업2폐업2024-04-12<NA><NA><NA><NA>81.07130-835서울특별시 동대문구 장안동 96-9서울특별시 동대문구 한천로42길 21, 1층 (장안동)2518크린하우스2024-04-12 17:26:06U2023-12-03 23:04:00.0일반세탁업206069.750657453031.004209<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45630500003050000-205-2023-000042023-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.36130-866서울특별시 동대문구 청량리동 38-14서울특별시 동대문구 제기로37길 8-2, 1층 (청량리동)2462익스프레스 런드리토탈서비스 JW2023-05-08 14:22:33I2022-12-04 23:00:00.0세탁업 기타204349.849234453779.653902<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45730500003050000-205-2023-000052023-07-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.8130-859서울특별시 동대문구 전농동 648-100서울특별시 동대문구 서울시립대로4길 19, 1층 (전농동)2594더클린2023-07-13 11:19:44I2022-12-06 23:05:00.0일반세탁업204151.455337452473.285104<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>