Overview

Dataset statistics

Number of variables47
Number of observations463
Missing cells5070
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory183.2 KiB
Average record size in memory405.3 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric9
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-17932/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (90.0%)Imbalance
위생업태명 is highly imbalanced (57.0%)Imbalance
여성종사자수 is highly imbalanced (64.1%)Imbalance
남성종사자수 is highly imbalanced (65.4%)Imbalance
침대수 is highly imbalanced (51.2%)Imbalance
인허가취소일자 has 463 (100.0%) missing valuesMissing
폐업일자 has 117 (25.3%) missing valuesMissing
휴업시작일자 has 463 (100.0%) missing valuesMissing
휴업종료일자 has 463 (100.0%) missing valuesMissing
재개업일자 has 463 (100.0%) missing valuesMissing
전화번호 has 200 (43.2%) missing valuesMissing
도로명주소 has 218 (47.1%) missing valuesMissing
도로명우편번호 has 222 (47.9%) missing valuesMissing
좌표정보(X) has 27 (5.8%) missing valuesMissing
좌표정보(Y) has 27 (5.8%) missing valuesMissing
건물지상층수 has 131 (28.3%) missing valuesMissing
건물지하층수 has 255 (55.1%) missing valuesMissing
사용시작지상층 has 230 (49.7%) missing valuesMissing
사용끝지상층 has 188 (40.6%) missing valuesMissing
발한실여부 has 73 (15.8%) missing valuesMissing
좌석수 has 76 (16.4%) missing valuesMissing
조건부허가신고사유 has 463 (100.0%) missing valuesMissing
조건부허가시작일자 has 463 (100.0%) missing valuesMissing
조건부허가종료일자 has 463 (100.0%) missing valuesMissing
다중이용업소여부 has 65 (14.0%) 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 7 (1.5%) zerosZeros
건물지상층수 has 99 (21.4%) zerosZeros
건물지하층수 has 114 (24.6%) zerosZeros
사용시작지상층 has 30 (6.5%) zerosZeros
사용끝지상층 has 26 (5.6%) zerosZeros

Reproduction

Analysis started2024-05-11 02:40:21.284872
Analysis finished2024-05-11 02:40:23.004927
Duration1.72 second
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
463 

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 463
100.0%

Length

2024-05-11T02:40:23.360291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:23.698274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 463
100.0%

관리번호
Text

UNIQUE 

Distinct463
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T02:40:24.220636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10186
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

Unique463 ?
Unique (%)100.0%

Sample

1st row3050000-203-1965-00694
2nd row3050000-203-1968-00708
3rd row3050000-203-1970-00601
4th row3050000-203-1970-00723
5th row3050000-203-1973-00617
ValueCountFrequency (%)
3050000-203-1965-00694 1
 
0.2%
3050000-203-2006-00002 1
 
0.2%
3050000-203-2007-00006 1
 
0.2%
3050000-203-2007-00005 1
 
0.2%
3050000-203-2007-00004 1
 
0.2%
3050000-203-2007-00003 1
 
0.2%
3050000-203-2007-00002 1
 
0.2%
3050000-203-2007-00001 1
 
0.2%
3050000-203-2006-00022 1
 
0.2%
3050000-203-2006-00021 1
 
0.2%
Other values (453) 453
97.8%
2024-05-11T02:40:25.156176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4645
45.6%
- 1389
 
13.6%
3 1080
 
10.6%
2 936
 
9.2%
5 598
 
5.9%
1 490
 
4.8%
9 351
 
3.4%
8 209
 
2.1%
7 208
 
2.0%
6 142
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8797
86.4%
Dash Punctuation 1389
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4645
52.8%
3 1080
 
12.3%
2 936
 
10.6%
5 598
 
6.8%
1 490
 
5.6%
9 351
 
4.0%
8 209
 
2.4%
7 208
 
2.4%
6 142
 
1.6%
4 138
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1389
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10186
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4645
45.6%
- 1389
 
13.6%
3 1080
 
10.6%
2 936
 
9.2%
5 598
 
5.9%
1 490
 
4.8%
9 351
 
3.4%
8 209
 
2.1%
7 208
 
2.0%
6 142
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4645
45.6%
- 1389
 
13.6%
3 1080
 
10.6%
2 936
 
9.2%
5 598
 
5.9%
1 490
 
4.8%
9 351
 
3.4%
8 209
 
2.1%
7 208
 
2.0%
6 142
 
1.4%

인허가일자
Date

Distinct408
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1965-09-29 00:00:00
Maximum2024-03-08 00:00:00
2024-05-11T02:40:25.574409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:26.027010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3
346 
1
117 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 346
74.7%
1 117
 
25.3%

Length

2024-05-11T02:40:26.442664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:26.763981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 346
74.7%
1 117
 
25.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
346 
영업/정상
117 

Length

Max length5
Median length2
Mean length2.7580994
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 346
74.7%
영업/정상 117
 
25.3%

Length

2024-05-11T02:40:27.123869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:27.436358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 346
74.7%
영업/정상 117
 
25.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2
346 
1
117 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 346
74.7%
1 117
 
25.3%

Length

2024-05-11T02:40:27.819306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:28.110262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 346
74.7%
1 117
 
25.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐업
346 
영업
117 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 346
74.7%
영업 117
 
25.3%

Length

2024-05-11T02:40:28.555944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:28.968479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 346
74.7%
영업 117
 
25.3%

폐업일자
Date

MISSING 

Distinct315
Distinct (%)91.0%
Missing117
Missing (%)25.3%
Memory size3.7 KiB
Minimum2003-02-25 00:00:00
Maximum2024-04-01 00:00:00
2024-05-11T02:40:29.440774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:30.013373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct259
Distinct (%)98.5%
Missing200
Missing (%)43.2%
Memory size3.7 KiB
2024-05-11T02:40:30.984912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9923954
Min length7

Characters and Unicode

Total characters2628
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

Unique255 ?
Unique (%)97.0%

Sample

1st row0222442819
2nd row0222463733
3rd row0209233214
4th row0222448261
5th row0209637414
ValueCountFrequency (%)
02 87
 
24.0%
02960 3
 
0.8%
9625748 2
 
0.6%
0200000000 2
 
0.6%
0222442684 2
 
0.6%
9665474 2
 
0.6%
02965 2
 
0.6%
9663248 2
 
0.6%
9676223 1
 
0.3%
0222165008 1
 
0.3%
Other values (258) 258
71.3%
2024-05-11T02:40:32.626963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 680
25.9%
0 439
16.7%
9 263
 
10.0%
6 221
 
8.4%
4 218
 
8.3%
1 152
 
5.8%
5 151
 
5.7%
8 146
 
5.6%
3 129
 
4.9%
7 128
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2527
96.2%
Space Separator 101
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 680
26.9%
0 439
17.4%
9 263
 
10.4%
6 221
 
8.7%
4 218
 
8.6%
1 152
 
6.0%
5 151
 
6.0%
8 146
 
5.8%
3 129
 
5.1%
7 128
 
5.1%
Space Separator
ValueCountFrequency (%)
101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 680
25.9%
0 439
16.7%
9 263
 
10.0%
6 221
 
8.4%
4 218
 
8.3%
1 152
 
5.8%
5 151
 
5.7%
8 146
 
5.6%
3 129
 
4.9%
7 128
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 680
25.9%
0 439
16.7%
9 263
 
10.0%
6 221
 
8.4%
4 218
 
8.3%
1 152
 
5.8%
5 151
 
5.7%
8 146
 
5.6%
3 129
 
4.9%
7 128
 
4.9%

소재지면적
Real number (ℝ)

ZEROS 

Distinct229
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.520605
Minimum0
Maximum144
Zeros7
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:33.174731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q113
median20
Q333
95-th percentile66
Maximum144
Range144
Interquartile range (IQR)20

Descriptive statistics

Standard deviation20.141582
Coefficient of variation (CV)0.78922823
Kurtosis6.811644
Mean25.520605
Median Absolute Deviation (MAD)9.02
Skewness2.2038245
Sum11816.04
Variance405.68331
MonotonicityNot monotonic
2024-05-11T02:40:34.014993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 29
 
6.3%
10.0 18
 
3.9%
6.6 14
 
3.0%
16.5 13
 
2.8%
20.0 11
 
2.4%
26.4 10
 
2.2%
18.0 10
 
2.2%
15.0 10
 
2.2%
66.0 9
 
1.9%
30.0 9
 
1.9%
Other values (219) 330
71.3%
ValueCountFrequency (%)
0.0 7
1.5%
2.0 2
 
0.4%
2.07 1
 
0.2%
3.15 1
 
0.2%
3.3 2
 
0.4%
3.78 1
 
0.2%
4.0 3
 
0.6%
5.0 4
0.9%
5.52 1
 
0.2%
6.0 8
1.7%
ValueCountFrequency (%)
144.0 1
 
0.2%
130.0 1
 
0.2%
125.02 1
 
0.2%
115.0 1
 
0.2%
99.0 2
0.4%
96.2 1
 
0.2%
90.0 2
0.4%
82.5 1
 
0.2%
82.0 3
0.6%
81.2 1
 
0.2%

소재지우편번호
Text

Distinct98
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T02:40:34.719523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.075594
Min length6

Characters and Unicode

Total characters2813
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

Unique32 ?
Unique (%)6.9%

Sample

1st row130850
2nd row130-852
3rd row130823
4th row130859
5th row130820
ValueCountFrequency (%)
130867 22
 
4.8%
130817 18
 
3.9%
130875 18
 
3.9%
130823 16
 
3.5%
130862 16
 
3.5%
130827 13
 
2.8%
130840 13
 
2.8%
130811 12
 
2.6%
130864 12
 
2.6%
130883 12
 
2.6%
Other values (88) 311
67.2%
2024-05-11T02:40:35.849134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 579
20.6%
3 553
19.7%
1 552
19.6%
8 505
18.0%
7 133
 
4.7%
6 115
 
4.1%
2 114
 
4.1%
5 104
 
3.7%
4 90
 
3.2%
- 35
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2778
98.8%
Dash Punctuation 35
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 579
20.8%
3 553
19.9%
1 552
19.9%
8 505
18.2%
7 133
 
4.8%
6 115
 
4.1%
2 114
 
4.1%
5 104
 
3.7%
4 90
 
3.2%
9 33
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2813
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 579
20.6%
3 553
19.7%
1 552
19.6%
8 505
18.0%
7 133
 
4.7%
6 115
 
4.1%
2 114
 
4.1%
5 104
 
3.7%
4 90
 
3.2%
- 35
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 579
20.6%
3 553
19.7%
1 552
19.6%
8 505
18.0%
7 133
 
4.7%
6 115
 
4.1%
2 114
 
4.1%
5 104
 
3.7%
4 90
 
3.2%
- 35
 
1.2%

지번주소
Text

Distinct433
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T02:40:36.661716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length40
Mean length26.345572
Min length18

Characters and Unicode

Total characters12198
Distinct characters183
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

Unique408 ?
Unique (%)88.1%

Sample

1st row서울특별시 동대문구 전농동 60-15
2nd row서울특별시 동대문구 전농동 190-8
3rd row서울특별시 동대문구 용두동 193-34번지
4th row서울특별시 동대문구 전농동 648-114번지 (간데메서길18)
5th row서울특별시 동대문구 용두동 102-42번지 (용두남길25)
ValueCountFrequency (%)
서울특별시 463
22.0%
동대문구 463
22.0%
장안동 71
 
3.4%
전농동 67
 
3.2%
답십리동 55
 
2.6%
용두동 54
 
2.6%
제기동 48
 
2.3%
청량리동 47
 
2.2%
휘경동 45
 
2.1%
이문동 38
 
1.8%
Other values (550) 749
35.7%
2024-05-11T02:40:38.291626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2040
 
16.7%
동 943
 
7.7%
문 507
 
4.2%
대 473
 
3.9%
1 472
 
3.9%
서 469
 
3.8%
시 468
 
3.8%
구 465
 
3.8%
울 464
 
3.8%
특 463
 
3.8%
Other values (173) 5434
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7195
59.0%
Decimal Number 2314
 
19.0%
Space Separator 2040
 
16.7%
Dash Punctuation 423
 
3.5%
Open Punctuation 106
 
0.9%
Close Punctuation 106
 
0.9%
Uppercase Letter 9
 
0.1%
Lowercase Letter 4
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 943
13.1%
문 507
 
7.0%
대 473
 
6.6%
서 469
 
6.5%
시 468
 
6.5%
구 465
 
6.5%
울 464
 
6.4%
특 463
 
6.4%
별 463
 
6.4%
지 401
 
5.6%
Other values (153) 2079
28.9%
Decimal Number
ValueCountFrequency (%)
1 472
20.4%
2 302
13.1%
3 292
12.6%
5 228
9.9%
4 202
8.7%
6 194
8.4%
0 166
 
7.2%
9 154
 
6.7%
8 153
 
6.6%
7 151
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
K 4
44.4%
S 4
44.4%
C 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
k 2
50.0%
Space Separator
ValueCountFrequency (%)
2040
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7195
59.0%
Common 4990
40.9%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 943
13.1%
문 507
 
7.0%
대 473
 
6.6%
서 469
 
6.5%
시 468
 
6.5%
구 465
 
6.5%
울 464
 
6.4%
특 463
 
6.4%
별 463
 
6.4%
지 401
 
5.6%
Other values (153) 2079
28.9%
Common
ValueCountFrequency (%)
2040
40.9%
1 472
 
9.5%
- 423
 
8.5%
2 302
 
6.1%
3 292
 
5.9%
5 228
 
4.6%
4 202
 
4.0%
6 194
 
3.9%
0 166
 
3.3%
9 154
 
3.1%
Other values (5) 517
 
10.4%
Latin
ValueCountFrequency (%)
K 4
30.8%
S 4
30.8%
s 2
15.4%
k 2
15.4%
C 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7195
59.0%
ASCII 5003
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2040
40.8%
1 472
 
9.4%
- 423
 
8.5%
2 302
 
6.0%
3 292
 
5.8%
5 228
 
4.6%
4 202
 
4.0%
6 194
 
3.9%
0 166
 
3.3%
9 154
 
3.1%
Other values (10) 530
 
10.6%
Hangul
ValueCountFrequency (%)
동 943
13.1%
문 507
 
7.0%
대 473
 
6.6%
서 469
 
6.5%
시 468
 
6.5%
구 465
 
6.5%
울 464
 
6.4%
특 463
 
6.4%
별 463
 
6.4%
지 401
 
5.6%
Other values (153) 2079
28.9%

도로명주소
Text

MISSING 

Distinct233
Distinct (%)95.1%
Missing218
Missing (%)47.1%
Memory size3.7 KiB
2024-05-11T02:40:39.211029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length46
Mean length30.926531
Min length23

Characters and Unicode

Total characters7577
Distinct characters143
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

Unique224 ?
Unique (%)91.4%

Sample

1st row서울특별시 동대문구 사가정로13길 27 (전농동)
2nd row서울특별시 동대문구 전농로 169, 1층 (전농동)
3rd row서울특별시 동대문구 답십리로45길 32 (답십리동,(전답길30))
4th row서울특별시 동대문구 무학로34길 14 (용두동)
5th row서울특별시 동대문구 약령시로 114, 1층 (제기동)
ValueCountFrequency (%)
서울특별시 245
 
17.1%
동대문구 245
 
17.1%
1층 69
 
4.8%
장안동 40
 
2.8%
전농동 30
 
2.1%
제기동 29
 
2.0%
답십리동 26
 
1.8%
청량리동 24
 
1.7%
용두동 24
 
1.7%
지하1층 23
 
1.6%
Other values (349) 681
47.4%
2024-05-11T02:40:40.545771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1192
 
15.7%
동 518
 
6.8%
1 328
 
4.3%
문 284
 
3.7%
대 281
 
3.7%
( 263
 
3.5%
) 263
 
3.5%
시 263
 
3.5%
서 256
 
3.4%
울 255
 
3.4%
Other values (133) 3674
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4528
59.8%
Space Separator 1192
 
15.7%
Decimal Number 1086
 
14.3%
Open Punctuation 263
 
3.5%
Close Punctuation 263
 
3.5%
Other Punctuation 184
 
2.4%
Dash Punctuation 52
 
0.7%
Uppercase Letter 7
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 518
 
11.4%
문 284
 
6.3%
대 281
 
6.2%
시 263
 
5.8%
서 256
 
5.7%
울 255
 
5.6%
로 250
 
5.5%
구 247
 
5.5%
별 245
 
5.4%
특 245
 
5.4%
Other values (113) 1684
37.2%
Decimal Number
ValueCountFrequency (%)
1 328
30.2%
2 157
14.5%
3 126
 
11.6%
4 104
 
9.6%
6 75
 
6.9%
5 74
 
6.8%
0 69
 
6.4%
7 60
 
5.5%
8 49
 
4.5%
9 44
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
K 3
42.9%
S 3
42.9%
C 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
1192
100.0%
Open Punctuation
ValueCountFrequency (%)
( 263
100.0%
Close Punctuation
ValueCountFrequency (%)
) 263
100.0%
Other Punctuation
ValueCountFrequency (%)
, 184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4528
59.8%
Common 3040
40.1%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 518
 
11.4%
문 284
 
6.3%
대 281
 
6.2%
시 263
 
5.8%
서 256
 
5.7%
울 255
 
5.6%
로 250
 
5.5%
구 247
 
5.5%
별 245
 
5.4%
특 245
 
5.4%
Other values (113) 1684
37.2%
Common
ValueCountFrequency (%)
1192
39.2%
1 328
 
10.8%
( 263
 
8.7%
) 263
 
8.7%
, 184
 
6.1%
2 157
 
5.2%
3 126
 
4.1%
4 104
 
3.4%
6 75
 
2.5%
5 74
 
2.4%
Other values (5) 274
 
9.0%
Latin
ValueCountFrequency (%)
K 3
33.3%
S 3
33.3%
C 1
 
11.1%
s 1
 
11.1%
k 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4528
59.8%
ASCII 3049
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1192
39.1%
1 328
 
10.8%
( 263
 
8.6%
) 263
 
8.6%
, 184
 
6.0%
2 157
 
5.1%
3 126
 
4.1%
4 104
 
3.4%
6 75
 
2.5%
5 74
 
2.4%
Other values (10) 283
 
9.3%
Hangul
ValueCountFrequency (%)
동 518
 
11.4%
문 284
 
6.3%
대 281
 
6.2%
시 263
 
5.8%
서 256
 
5.7%
울 255
 
5.6%
로 250
 
5.5%
구 247
 
5.5%
별 245
 
5.4%
특 245
 
5.4%
Other values (113) 1684
37.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct123
Distinct (%)51.0%
Missing222
Missing (%)47.9%
Infinite0
Infinite (%)0.0%
Mean2536.8382
Minimum2404
Maximum2644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:41.101582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2404
5-th percentile2425
Q12483
median2546
Q32586
95-th percentile2637
Maximum2644
Range240
Interquartile range (IQR)103

Descriptive statistics

Standard deviation67.236358
Coefficient of variation (CV)0.026504
Kurtosis-1.0609467
Mean2536.8382
Median Absolute Deviation (MAD)54
Skewness-0.28157256
Sum611378
Variance4520.7279
MonotonicityNot monotonic
2024-05-11T02:40:41.585195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2572 9
 
1.9%
2432 6
 
1.3%
2573 5
 
1.1%
2436 5
 
1.1%
2628 5
 
1.1%
2577 4
 
0.9%
2644 4
 
0.9%
2427 4
 
0.9%
2569 4
 
0.9%
2488 4
 
0.9%
Other values (113) 191
41.3%
(Missing) 222
47.9%
ValueCountFrequency (%)
2404 1
 
0.2%
2406 1
 
0.2%
2409 1
 
0.2%
2410 1
 
0.2%
2411 1
 
0.2%
2412 1
 
0.2%
2418 1
 
0.2%
2420 1
 
0.2%
2423 3
0.6%
2424 1
 
0.2%
ValueCountFrequency (%)
2644 4
0.9%
2642 1
 
0.2%
2640 1
 
0.2%
2639 2
0.4%
2638 2
0.4%
2637 3
0.6%
2635 1
 
0.2%
2634 1
 
0.2%
2630 1
 
0.2%
2629 1
 
0.2%

사업장명
Text

Distinct382
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-05-11T02:40:42.457724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length4.3736501
Min length1

Characters and Unicode

Total characters2025
Distinct characters302
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

Unique325 ?
Unique (%)70.2%

Sample

1st row우주
2nd row신진 부자 이용원
3rd row미화
4th row에덴
5th row친절
ValueCountFrequency (%)
이용원 14
 
2.7%
태후사랑 7
 
1.4%
바버샵 6
 
1.2%
이발관 5
 
1.0%
이발소 5
 
1.0%
오땡큐 4
 
0.8%
현대 4
 
0.8%
태양 4
 
0.8%
하남이용원 4
 
0.8%
복지이용원 3
 
0.6%
Other values (394) 462
89.2%
2024-05-11T02:40:43.613605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 203
 
10.0%
용 138
 
6.8%
원 133
 
6.6%
발 61
 
3.0%
55
 
2.7%
성 47
 
2.3%
사 37
 
1.8%
동 34
 
1.7%
우 34
 
1.7%
나 30
 
1.5%
Other values (292) 1253
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1888
93.2%
Space Separator 55
 
2.7%
Uppercase Letter 21
 
1.0%
Lowercase Letter 18
 
0.9%
Open Punctuation 14
 
0.7%
Close Punctuation 14
 
0.7%
Decimal Number 11
 
0.5%
Other Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 203
 
10.8%
용 138
 
7.3%
원 133
 
7.0%
발 61
 
3.2%
성 47
 
2.5%
사 37
 
2.0%
동 34
 
1.8%
우 34
 
1.8%
나 30
 
1.6%
대 27
 
1.4%
Other values (257) 1144
60.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
19.0%
K 2
9.5%
S 2
9.5%
A 2
9.5%
J 2
9.5%
G 1
 
4.8%
N 1
 
4.8%
O 1
 
4.8%
E 1
 
4.8%
H 1
 
4.8%
Other values (4) 4
19.0%
Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
a 3
16.7%
e 2
11.1%
o 2
11.1%
h 2
11.1%
i 1
 
5.6%
g 1
 
5.6%
l 1
 
5.6%
b 1
 
5.6%
p 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 3
27.3%
0 2
 
18.2%
7 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
? 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1888
93.2%
Common 98
 
4.8%
Latin 39
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 203
 
10.8%
용 138
 
7.3%
원 133
 
7.0%
발 61
 
3.2%
성 47
 
2.5%
사 37
 
2.0%
동 34
 
1.8%
우 34
 
1.8%
나 30
 
1.6%
대 27
 
1.4%
Other values (257) 1144
60.6%
Latin
ValueCountFrequency (%)
B 4
 
10.3%
r 3
 
7.7%
a 3
 
7.7%
K 2
 
5.1%
e 2
 
5.1%
S 2
 
5.1%
A 2
 
5.1%
J 2
 
5.1%
o 2
 
5.1%
h 2
 
5.1%
Other values (15) 15
38.5%
Common
ValueCountFrequency (%)
55
56.1%
( 14
 
14.3%
) 14
 
14.3%
2 5
 
5.1%
1 3
 
3.1%
? 2
 
2.0%
0 2
 
2.0%
- 1
 
1.0%
. 1
 
1.0%
7 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1888
93.2%
ASCII 137
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 203
 
10.8%
용 138
 
7.3%
원 133
 
7.0%
발 61
 
3.2%
성 47
 
2.5%
사 37
 
2.0%
동 34
 
1.8%
우 34
 
1.8%
나 30
 
1.6%
대 27
 
1.4%
Other values (257) 1144
60.6%
ASCII
ValueCountFrequency (%)
55
40.1%
( 14
 
10.2%
) 14
 
10.2%
2 5
 
3.6%
B 4
 
2.9%
1 3
 
2.2%
r 3
 
2.2%
a 3
 
2.2%
K 2
 
1.5%
e 2
 
1.5%
Other values (25) 32
23.4%

최종수정일자
Date

Distinct351
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2003-03-24 00:00:00
Maximum2024-04-15 14:25:03
2024-05-11T02:40:44.033934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:44.420955image/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
357 
U
106 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 357
77.1%
U 106
 
22.9%

Length

2024-05-11T02:40:44.714883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:44.903987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 357
77.1%
u 106
 
22.9%

데이터갱신일자
Date

Distinct125
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-05-11T02:40:45.161905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:45.564322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반이용업
457 
이용업 기타
 
6

Length

Max length6
Median length5
Mean length5.012959
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 457
98.7%
이용업 기타 6
 
1.3%

Length

2024-05-11T02:40:45.909805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:46.146834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 457
97.4%
이용업 6
 
1.3%
기타 6
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct331
Distinct (%)75.9%
Missing27
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean204561.03
Minimum202013.4
Maximum206562.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:46.581637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202013.4
5-th percentile202414.3
Q1203693.38
median204832.08
Q3205530.07
95-th percentile206209.89
Maximum206562.65
Range4549.2477
Interquartile range (IQR)1836.6884

Descriptive statistics

Standard deviation1178.3489
Coefficient of variation (CV)0.0057603783
Kurtosis-0.91727426
Mean204561.03
Median Absolute Deviation (MAD)952.04586
Skewness-0.31713186
Sum89188608
Variance1388506.2
MonotonicityNot monotonic
2024-05-11T02:40:47.080387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205271.704936121 7
 
1.5%
202792.678699836 6
 
1.3%
206521.405320134 5
 
1.1%
202257.985695221 5
 
1.1%
203704.207020897 5
 
1.1%
205450.919680774 4
 
0.9%
202249.681763064 4
 
0.9%
204082.111844228 4
 
0.9%
204908.049769787 4
 
0.9%
205980.772169045 4
 
0.9%
Other values (321) 388
83.8%
(Missing) 27
 
5.8%
ValueCountFrequency (%)
202013.401502902 1
 
0.2%
202023.921749857 1
 
0.2%
202056.089579192 1
 
0.2%
202123.025510581 1
 
0.2%
202171.998905496 1
 
0.2%
202174.322410313 2
 
0.4%
202186.468072494 1
 
0.2%
202249.681763064 4
0.9%
202257.985695221 5
1.1%
202308.172724147 1
 
0.2%
ValueCountFrequency (%)
206562.649224959 1
 
0.2%
206543.156690365 1
 
0.2%
206521.405320134 5
1.1%
206502.751884821 1
 
0.2%
206495.99270129 1
 
0.2%
206484.233644024 1
 
0.2%
206460.770782597 1
 
0.2%
206438.571508725 1
 
0.2%
206419.497908653 1
 
0.2%
206391.975425701 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct331
Distinct (%)75.9%
Missing27
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean453083.17
Minimum451068.47
Maximum455790.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:47.572667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451068.47
5-th percentile451607.21
Q1452418.27
median452914.87
Q3453793.08
95-th percentile455107.16
Maximum455790.63
Range4722.1609
Interquartile range (IQR)1374.8113

Descriptive statistics

Standard deviation1029.6047
Coefficient of variation (CV)0.0022724409
Kurtosis-0.27706086
Mean453083.17
Median Absolute Deviation (MAD)650.2419
Skewness0.49392128
Sum1.9754426 × 108
Variance1060085.9
MonotonicityNot monotonic
2024-05-11T02:40:48.105444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452706.897879436 7
 
1.5%
452915.127892459 6
 
1.3%
451940.119059947 5
 
1.1%
452478.339896363 5
 
1.1%
453045.097960344 5
 
1.1%
454258.218194207 4
 
0.9%
452629.681527354 4
 
0.9%
452472.990548179 4
 
0.9%
452950.268125459 4
 
0.9%
455275.835949587 4
 
0.9%
Other values (321) 388
83.8%
(Missing) 27
 
5.8%
ValueCountFrequency (%)
451068.470216265 1
0.2%
451070.709075884 1
0.2%
451110.245309908 1
0.2%
451176.461668212 1
0.2%
451250.289450048 2
0.4%
451255.046415979 1
0.2%
451257.524024265 1
0.2%
451291.485950675 1
0.2%
451373.15341337 1
0.2%
451373.58169187 1
0.2%
ValueCountFrequency (%)
455790.631069022 1
0.2%
455735.739070861 1
0.2%
455681.221589435 1
0.2%
455643.381169191 1
0.2%
455615.342142779 1
0.2%
455604.548013058 1
0.2%
455520.929097871 2
0.4%
455477.289437189 1
0.2%
455412.405461075 1
0.2%
455396.451044954 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
일반이용업
392 
<NA>
65 
이용업 기타
 
6

Length

Max length6
Median length5
Mean length4.8725702
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 392
84.7%
<NA> 65
 
14.0%
이용업 기타 6
 
1.3%

Length

2024-05-11T02:40:48.713978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:49.098536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 392
83.6%
na 65
 
13.9%
이용업 6
 
1.3%
기타 6
 
1.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)3.6%
Missing131
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean1.9909639
Minimum0
Maximum14
Zeros99
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:49.403817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1478387
Coefficient of variation (CV)1.0787934
Kurtosis7.4677091
Mean1.9909639
Median Absolute Deviation (MAD)1
Skewness2.0345177
Sum661
Variance4.6132112
MonotonicityNot monotonic
2024-05-11T02:40:49.815274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 99
21.4%
1 71
15.3%
3 63
13.6%
2 38
 
8.2%
4 29
 
6.3%
5 18
 
3.9%
6 6
 
1.3%
8 3
 
0.6%
14 2
 
0.4%
13 1
 
0.2%
Other values (2) 2
 
0.4%
(Missing) 131
28.3%
ValueCountFrequency (%)
0 99
21.4%
1 71
15.3%
2 38
 
8.2%
3 63
13.6%
4 29
 
6.3%
5 18
 
3.9%
6 6
 
1.3%
7 1
 
0.2%
8 3
 
0.6%
11 1
 
0.2%
ValueCountFrequency (%)
14 2
 
0.4%
13 1
 
0.2%
11 1
 
0.2%
8 3
 
0.6%
7 1
 
0.2%
6 6
 
1.3%
5 18
 
3.9%
4 29
6.3%
3 63
13.6%
2 38
8.2%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.8%
Missing255
Missing (%)55.1%
Infinite0
Infinite (%)0.0%
Mean0.60096154
Minimum0
Maximum12
Zeros114
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:50.214914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1.65
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1247755
Coefficient of variation (CV)1.8716264
Kurtosis53.861437
Mean0.60096154
Median Absolute Deviation (MAD)0
Skewness6.0801248
Sum125
Variance1.2651198
MonotonicityNot monotonic
2024-05-11T02:40:50.540194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 114
24.6%
1 83
 
17.9%
2 6
 
1.3%
5 1
 
0.2%
12 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
(Missing) 255
55.1%
ValueCountFrequency (%)
0 114
24.6%
1 83
17.9%
2 6
 
1.3%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
6 1
 
0.2%
5 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
2 6
 
1.3%
1 83
17.9%
0 114
24.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.6%
Missing230
Missing (%)49.7%
Infinite0
Infinite (%)0.0%
Mean1.223176
Minimum0
Maximum5
Zeros30
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:50.957731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.87196481
Coefficient of variation (CV)0.71286948
Kurtosis6.2345489
Mean1.223176
Median Absolute Deviation (MAD)0
Skewness1.8710016
Sum285
Variance0.76032263
MonotonicityNot monotonic
2024-05-11T02:40:51.426241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 143
30.9%
2 49
 
10.6%
0 30
 
6.5%
3 5
 
1.1%
5 5
 
1.1%
4 1
 
0.2%
(Missing) 230
49.7%
ValueCountFrequency (%)
0 30
 
6.5%
1 143
30.9%
2 49
 
10.6%
3 5
 
1.1%
4 1
 
0.2%
5 5
 
1.1%
ValueCountFrequency (%)
5 5
 
1.1%
4 1
 
0.2%
3 5
 
1.1%
2 49
 
10.6%
1 143
30.9%
0 30
 
6.5%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.2%
Missing188
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean1.2327273
Minimum0
Maximum5
Zeros26
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:51.941955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.80849833
Coefficient of variation (CV)0.65586147
Kurtosis7.4777836
Mean1.2327273
Median Absolute Deviation (MAD)0
Skewness2.0555035
Sum339
Variance0.65366954
MonotonicityNot monotonic
2024-05-11T02:40:52.517032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 182
39.3%
2 55
 
11.9%
0 26
 
5.6%
3 6
 
1.3%
5 5
 
1.1%
4 1
 
0.2%
(Missing) 188
40.6%
ValueCountFrequency (%)
0 26
 
5.6%
1 182
39.3%
2 55
 
11.9%
3 6
 
1.3%
4 1
 
0.2%
5 5
 
1.1%
ValueCountFrequency (%)
5 5
 
1.1%
4 1
 
0.2%
3 6
 
1.3%
2 55
 
11.9%
1 182
39.3%
0 26
 
5.6%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
363 
1
54 
0
38 
2
 
8

Length

Max length4
Median length4
Mean length3.3520518
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 363
78.4%
1 54
 
11.7%
0 38
 
8.2%
2 8
 
1.7%

Length

2024-05-11T02:40:53.023360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:53.437971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
78.4%
1 54
 
11.7%
0 38
 
8.2%
2 8
 
1.7%

사용끝지하층
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
354 
1
63 
0
37 
2
 
9

Length

Max length4
Median length4
Mean length3.2937365
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
76.5%
1 63
 
13.6%
0 37
 
8.0%
2 9
 
1.9%

Length

2024-05-11T02:40:54.020308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:54.457036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 354
76.5%
1 63
 
13.6%
0 37
 
8.0%
2 9
 
1.9%

한실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
337 
0
126 

Length

Max length4
Median length4
Mean length3.1835853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
72.8%
0 126
 
27.2%

Length

2024-05-11T02:40:54.974644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:55.408804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
72.8%
0 126
 
27.2%

양실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
337 
0
126 

Length

Max length4
Median length4
Mean length3.1835853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
72.8%
0 126
 
27.2%

Length

2024-05-11T02:40:55.915200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:56.349739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
72.8%
0 126
 
27.2%

욕실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
337 
0
126 

Length

Max length4
Median length4
Mean length3.1835853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
72.8%
0 126
 
27.2%

Length

2024-05-11T02:40:56.912606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:57.347327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
72.8%
0 126
 
27.2%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing73
Missing (%)15.8%
Memory size1.0 KiB
False
390 
(Missing)
73 
ValueCountFrequency (%)
False 390
84.2%
(Missing) 73
 
15.8%
2024-05-11T02:40:57.742881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)2.6%
Missing76
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean3.3359173
Minimum0
Maximum9
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T02:40:58.151868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5272403
Coefficient of variation (CV)0.45781721
Kurtosis1.1285314
Mean3.3359173
Median Absolute Deviation (MAD)1
Skewness0.90796601
Sum1291
Variance2.3324631
MonotonicityNot monotonic
2024-05-11T02:40:58.650853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 126
27.2%
2 89
19.2%
4 66
14.3%
5 42
 
9.1%
1 28
 
6.0%
6 21
 
4.5%
7 8
 
1.7%
8 3
 
0.6%
9 3
 
0.6%
0 1
 
0.2%
(Missing) 76
16.4%
ValueCountFrequency (%)
0 1
 
0.2%
1 28
 
6.0%
2 89
19.2%
3 126
27.2%
4 66
14.3%
5 42
 
9.1%
6 21
 
4.5%
7 8
 
1.7%
8 3
 
0.6%
9 3
 
0.6%
ValueCountFrequency (%)
9 3
 
0.6%
8 3
 
0.6%
7 8
 
1.7%
6 21
 
4.5%
5 42
 
9.1%
4 66
14.3%
3 126
27.2%
2 89
19.2%
1 28
 
6.0%
0 1
 
0.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing463
Missing (%)100.0%
Memory size4.2 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
233 
임대
224 
자가
 
6

Length

Max length4
Median length4
Mean length3.0064795
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 233
50.3%
임대 224
48.4%
자가 6
 
1.3%

Length

2024-05-11T02:40:59.165028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:40:59.641509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 233
50.3%
임대 224
48.4%
자가 6
 
1.3%

세탁기수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
337 
0
126 

Length

Max length4
Median length4
Mean length3.1835853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 337
72.8%
0 126
 
27.2%

Length

2024-05-11T02:41:00.522663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:41:00.887936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
72.8%
0 126
 
27.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
407 
0
53 
1
 
3

Length

Max length4
Median length4
Mean length3.637149
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> 407
87.9%
0 53
 
11.4%
1 3
 
0.6%

Length

2024-05-11T02:41:01.267187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:41:01.654411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 407
87.9%
0 53
 
11.4%
1 3
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
407 
0
55 
1
 
1

Length

Max length4
Median length4
Mean length3.637149
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> 407
87.9%
0 55
 
11.9%
1 1
 
0.2%

Length

2024-05-11T02:41:02.068487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:41:02.523638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 407
87.9%
0 55
 
11.9%
1 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
360 
0
103 

Length

Max length4
Median length4
Mean length3.3326134
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 360
77.8%
0 103
 
22.2%

Length

2024-05-11T02:41:03.019767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:41:03.404582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 360
77.8%
0 103
 
22.2%

침대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
<NA>
362 
0
100 
1
 
1

Length

Max length4
Median length4
Mean length3.3455724
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 362
78.2%
0 100
 
21.6%
1 1
 
0.2%

Length

2024-05-11T02:41:04.097968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:41:04.516370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 362
78.2%
0 100
 
21.6%
1 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing65
Missing (%)14.0%
Memory size1.0 KiB
False
398 
(Missing)
65 
ValueCountFrequency (%)
False 398
86.0%
(Missing) 65
 
14.0%
2024-05-11T02:41:04.884580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030500003050000-203-1965-0069419650929<NA>1영업/정상1영업<NA><NA><NA><NA>022244281919.53130850서울특별시 동대문구 전농동 60-15서울특별시 동대문구 사가정로13길 27 (전농동)2506우주2022-11-04 10:39:09U2021-11-01 00:06:00.0일반이용업205077.208925452971.812841<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130500003050000-203-1968-007081968-08-30<NA>1영업/정상1영업<NA><NA><NA><NA>022246373346.0130-852서울특별시 동대문구 전농동 190-8서울특별시 동대문구 전농로 169, 1층 (전농동)2545신진 부자 이용원2023-08-30 12:02:09U2022-12-09 00:01:00.0일반이용업204882.69697453037.86258<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230500003050000-203-1970-0060119700827<NA>3폐업2폐업20041015<NA><NA><NA>020923321415.6130823서울특별시 동대문구 용두동 193-34번지<NA><NA>미화2004-03-05 00:00:00I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업1<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA>임대<NA><NA><NA><NA><NA>N
330500003050000-203-1970-0072319700822<NA>3폐업2폐업20090615<NA><NA><NA>022244826116.24130859서울특별시 동대문구 전농동 648-114번지 (간데메서길18)<NA><NA>에덴2007-05-23 00:00:00I2018-08-31 23:59:59.0일반이용업204211.134493452460.897787일반이용업1<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA>임대<NA><NA><NA><NA><NA>N
430500003050000-203-1973-0061719730813<NA>3폐업2폐업20110328<NA><NA><NA>020963741421.0130820서울특별시 동대문구 용두동 102-42번지 (용두남길25)<NA><NA>친절2011-05-25 14:14:39I2018-08-31 23:59:59.0일반이용업202863.650954452491.039461일반이용업100100000N2<NA><NA><NA>임대0<NA><NA>00N
530500003050000-203-1973-0228319730627<NA>3폐업2폐업20111228<NA><NA><NA>022217074016.47130856서울특별시 동대문구 전농동 471-37번지 (활터11길14)<NA><NA>오성2011-12-05 13:28:21I2018-08-31 23:59:59.0일반이용업204290.758129452594.853473일반이용업000000000N3<NA><NA><NA>임대0<NA><NA>00N
630500003050000-203-1976-0074519760831<NA>3폐업2폐업20140729<NA><NA><NA>022248295117.76130802서울특별시 동대문구 답십리동 102-10번지 (전답길30)서울특별시 동대문구 답십리로45길 32 (답십리동,(전답길30))<NA>춘흥2007-05-23 00:00:00I2018-08-31 23:59:59.0일반이용업204857.603247452459.02357일반이용업1<NA>11<NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730500003050000-203-1977-0058619771015<NA>3폐업2폐업20030814<NA><NA><NA>020921085836.0130812서울특별시 동대문구 신설동 101-7번지<NA><NA>궁전2003-06-09 00:00:00I2018-08-31 23:59:59.0일반이용업202056.089579452590.463014일반이용업6<NA><NA>2<NA><NA><NA><NA><NA>N7<NA><NA><NA>임대<NA><NA><NA><NA><NA>N
830500003050000-203-1977-0061119771015<NA>3폐업2폐업20090609<NA><NA><NA>020963745710.5130817서울특별시 동대문구 용두동 39-16번지<NA><NA>은성이용원2006-09-15 00:00:00I2018-08-31 23:59:59.0일반이용업203547.112426452701.712027일반이용업3<NA><NA>1<NA><NA><NA><NA><NA>N3<NA><NA><NA>자가<NA><NA><NA><NA><NA>N
930500003050000-203-1977-0061619771015<NA>3폐업2폐업20200313<NA><NA><NA>02 922186926.0130820서울특별시 동대문구 용두동 118-113번지서울특별시 동대문구 무학로34길 14 (용두동)2584제일2020-03-13 11:21:13U2020-03-15 02:40:00.0일반이용업202701.559826452668.075625일반이용업3<NA>11<NA><NA><NA><NA><NA>N3<NA><NA><NA>임대<NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
45330500003050000-203-2023-000022023-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.68130-820서울특별시 동대문구 용두동 100-1 랜드마크타워1서울특별시 동대문구 천호대로25길 81, 랜드마크타워1 1층 106호 (용두동)2585모먼트 바버샵2023-05-01 11:09:17I2022-12-05 00:03:00.0일반이용업202929.480858452835.105671<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45430500003050000-203-2023-000032023-05-18<NA>3폐업2폐업2023-11-02<NA><NA><NA><NA>13.0130-883서울특별시 동대문구 답십리동 94-9 목련빌딩서울특별시 동대문구 전농로 102, 목련빌딩 (답십리동)2538목련이용원2023-11-02 13:29:46U2022-11-01 00:04:00.0일반이용업205049.095911452418.270436<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45530500003050000-203-2023-000042023-06-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.07130-848서울특별시 동대문구 전농동 10 전농 SK아파트서울특별시 동대문구 사가정로 148, 5층 501호 (전농동, 전농 SK아파트)2532백두산2023-06-20 11:21:01I2022-12-05 22:02:00.0일반이용업205271.704936452706.897879<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45630500003050000-203-2023-000052023-07-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>69.68130-090서울특별시 동대문구 휘경동 380서울특별시 동대문구 망우로 46, 401동 3107호 (휘경동)2496헤어바이맨 더킹2023-07-25 14:57:13I2022-12-06 22:07:00.0일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45730500003050000-203-2023-000062023-08-16<NA>3폐업2폐업2023-12-06<NA><NA><NA><NA>64.45130-831서울특별시 동대문구 이문동 322-2서울특별시 동대문구 이문로16길 11, 2층 (이문동)244017살롱2023-12-06 12:46:01U2022-11-02 00:09:00.0일반이용업205168.284316454644.292716<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45830500003050000-203-2023-000072023-10-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.86130-879서울특별시 동대문구 휘경동 308-134서울특별시 동대문구 망우로12길 64, 1층 (휘경동)2496엔듀어바버샵2023-10-11 14:02:01I2022-10-30 23:03:00.0일반이용업204975.85686453876.795142<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45930500003050000-203-2024-000012024-01-16<NA>3폐업2폐업2024-03-26<NA><NA><NA><NA>16.5130-883서울특별시 동대문구 답십리동 94-9 목련빌딩서울특별시 동대문구 전농로 102, 목련빌딩 지하1층 (답십리동)2538목련2024-03-26 15:07:42U2023-12-02 22:08:00.0일반이용업205049.095911452418.270436<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46030500003050000-203-2024-000022024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.2130-844서울특별시 동대문구 장안동 419-1 플러스홈서울특별시 동대문구 천호대로79길 26, 1층 101호 (장안동, 플러스홈)2634카브라(KABRA) 바버샵2024-02-06 15:53:15I2023-12-02 00:08:00.0일반이용업205505.960117451257.524024<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46130500003050000-203-2024-000032024-02-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6130-823서울특별시 동대문구 용두동 138-41 두산베어스타워서울특별시 동대문구 왕산로 81, 지하1층 (용두동, 두산베어스타워)2577용두동수안보싸우나2024-02-16 11:00:32I2023-12-01 23:08:00.0일반이용업202792.6787452915.127892<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46230500003050000-203-2024-000042024-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.03130-851서울특별시 동대문구 전농동 103-319서울특별시 동대문구 전농로 230-1, 1층 (전농동)2492희망 이발소2024-03-08 13:12:09I2023-12-02 23:00:00.0일반이용업204613.864789453581.737276<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>