Overview

Dataset statistics

Number of variables44
Number of observations5440
Missing cells49119
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 MiB
Average record size in memory376.0 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
Boolean1

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,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18434/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (52.2%)Imbalance
영업상태명 is highly imbalanced (52.2%)Imbalance
상세영업상태코드 is highly imbalanced (52.2%)Imbalance
상세영업상태명 is highly imbalanced (52.2%)Imbalance
업태구분명 is highly imbalanced (98.8%)Imbalance
위생업태명 is highly imbalanced (54.5%)Imbalance
남성종사자수 is highly imbalanced (67.1%)Imbalance
여성종사자수 is highly imbalanced (74.2%)Imbalance
영업장주변구분명 is highly imbalanced (81.4%)Imbalance
등급구분명 is highly imbalanced (73.1%)Imbalance
급수시설구분명 is highly imbalanced (59.2%)Imbalance
총인원 is highly imbalanced (65.9%)Imbalance
보증액 is highly imbalanced (69.2%)Imbalance
월세액 is highly imbalanced (69.2%)Imbalance
인허가취소일자 has 5440 (100.0%) missing valuesMissing
폐업일자 has 560 (10.3%) missing valuesMissing
휴업시작일자 has 5440 (100.0%) missing valuesMissing
휴업종료일자 has 5440 (100.0%) missing valuesMissing
재개업일자 has 5440 (100.0%) missing valuesMissing
전화번호 has 2892 (53.2%) missing valuesMissing
소재지면적 has 2884 (53.0%) missing valuesMissing
도로명주소 has 1150 (21.1%) missing valuesMissing
도로명우편번호 has 1205 (22.2%) missing valuesMissing
좌표정보(X) has 112 (2.1%) missing valuesMissing
좌표정보(Y) has 112 (2.1%) missing valuesMissing
다중이용업소여부 has 1055 (19.4%) missing valuesMissing
시설총규모 has 1055 (19.4%) missing valuesMissing
전통업소지정번호 has 5440 (100.0%) missing valuesMissing
전통업소주된음식 has 5440 (100.0%) missing valuesMissing
홈페이지 has 5440 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 48.2494063)Skewed
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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 141 (2.6%) zerosZeros
시설총규모 has 4321 (79.4%) zerosZeros

Reproduction

Analysis started2024-05-11 02:21:52.554381
Analysis finished2024-05-11 02:21:56.500963
Duration3.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
3070000
5440 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 5440
100.0%

Length

2024-05-11T02:21:56.780542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:57.217382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 5440
100.0%

관리번호
Text

UNIQUE 

Distinct5440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
2024-05-11T02:21:57.820061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters119680
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

Unique5440 ?
Unique (%)100.0%

Sample

1st row3070000-107-1972-00212
2nd row3070000-107-1972-00240
3rd row3070000-107-1972-00260
4th row3070000-107-1972-00261
5th row3070000-107-1972-00271
ValueCountFrequency (%)
3070000-107-1972-00212 1
 
< 0.1%
3070000-107-2019-00447 1
 
< 0.1%
3070000-107-2019-00456 1
 
< 0.1%
3070000-107-2019-00455 1
 
< 0.1%
3070000-107-2019-00454 1
 
< 0.1%
3070000-107-2019-00453 1
 
< 0.1%
3070000-107-2019-00452 1
 
< 0.1%
3070000-107-2019-00451 1
 
< 0.1%
3070000-107-2019-00450 1
 
< 0.1%
3070000-107-2019-00449 1
 
< 0.1%
Other values (5430) 5430
99.8%
2024-05-11T02:21:59.315008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53496
44.7%
- 16320
 
13.6%
7 12595
 
10.5%
1 11159
 
9.3%
2 9303
 
7.8%
3 7924
 
6.6%
9 2399
 
2.0%
4 1744
 
1.5%
8 1713
 
1.4%
6 1646
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103360
86.4%
Dash Punctuation 16320
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53496
51.8%
7 12595
 
12.2%
1 11159
 
10.8%
2 9303
 
9.0%
3 7924
 
7.7%
9 2399
 
2.3%
4 1744
 
1.7%
8 1713
 
1.7%
6 1646
 
1.6%
5 1381
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 16320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119680
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53496
44.7%
- 16320
 
13.6%
7 12595
 
10.5%
1 11159
 
9.3%
2 9303
 
7.8%
3 7924
 
6.6%
9 2399
 
2.0%
4 1744
 
1.5%
8 1713
 
1.4%
6 1646
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53496
44.7%
- 16320
 
13.6%
7 12595
 
10.5%
1 11159
 
9.3%
2 9303
 
7.8%
3 7924
 
6.6%
9 2399
 
2.0%
4 1744
 
1.5%
8 1713
 
1.4%
6 1646
 
1.4%
Distinct3121
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
Minimum1972-03-29 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T02:22:00.048834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:22:00.647400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
3
4880 
1
560 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 4880
89.7%
1 560
 
10.3%

Length

2024-05-11T02:22:01.294266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:01.739691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4880
89.7%
1 560
 
10.3%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
폐업
4880 
영업/정상
560 

Length

Max length5
Median length2
Mean length2.3088235
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4880
89.7%
영업/정상 560
 
10.3%

Length

2024-05-11T02:22:02.105530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:02.551262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4880
89.7%
영업/정상 560
 
10.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
2
4880 
1
560 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 4880
89.7%
1 560
 
10.3%

Length

2024-05-11T02:22:03.032981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:03.448933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 4880
89.7%
1 560
 
10.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
폐업
4880 
영업
560 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4880
89.7%
영업 560
 
10.3%

Length

2024-05-11T02:22:03.786459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:04.217476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4880
89.7%
영업 560
 
10.3%

폐업일자
Date

MISSING 

Distinct2785
Distinct (%)57.1%
Missing560
Missing (%)10.3%
Memory size42.6 KiB
Minimum1997-12-23 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T02:22:04.948304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:22:05.494861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

전화번호
Text

MISSING 

Distinct1538
Distinct (%)60.4%
Missing2892
Missing (%)53.2%
Memory size42.6 KiB
2024-05-11T02:22:06.463959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.765699
Min length2

Characters and Unicode

Total characters27431
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

Unique1286 ?
Unique (%)50.5%

Sample

1st row02 9233968
2nd row02 9262234
3rd row02 9239949
4th row02 9238386
5th row02 9121138
ValueCountFrequency (%)
02 1299
23.7%
031 570
 
10.4%
032 113
 
2.1%
792 70
 
1.3%
070 52
 
0.9%
055 49
 
0.9%
8581226 43
 
0.8%
4266949 32
 
0.6%
6949 31
 
0.6%
062 30
 
0.5%
Other values (1699) 3185
58.2%
2024-05-11T02:22:07.864733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4096
14.9%
0 3952
14.4%
3428
12.5%
1 2883
10.5%
9 2570
9.4%
3 2192
8.0%
4 1821
6.6%
5 1767
6.4%
7 1638
 
6.0%
6 1631
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24003
87.5%
Space Separator 3428
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4096
17.1%
0 3952
16.5%
1 2883
12.0%
9 2570
10.7%
3 2192
9.1%
4 1821
7.6%
5 1767
7.4%
7 1638
 
6.8%
6 1631
 
6.8%
8 1453
 
6.1%
Space Separator
ValueCountFrequency (%)
3428
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27431
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4096
14.9%
0 3952
14.4%
3428
12.5%
1 2883
10.5%
9 2570
9.4%
3 2192
8.0%
4 1821
6.6%
5 1767
6.4%
7 1638
 
6.0%
6 1631
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27431
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4096
14.9%
0 3952
14.4%
3428
12.5%
1 2883
10.5%
9 2570
9.4%
3 2192
8.0%
4 1821
6.6%
5 1767
6.4%
7 1638
 
6.0%
6 1631
 
5.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct982
Distinct (%)38.4%
Missing2884
Missing (%)53.0%
Infinite0
Infinite (%)0.0%
Mean16.792085
Minimum0
Maximum330.47
Zeros141
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-05-11T02:22:08.299680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.515
median12.41
Q323.3325
95-th percentile46.22
Maximum330.47
Range330.47
Interquartile range (IQR)18.8175

Descriptive statistics

Standard deviation18.620492
Coefficient of variation (CV)1.108885
Kurtosis68.574448
Mean16.792085
Median Absolute Deviation (MAD)8.69
Skewness5.3747276
Sum42920.57
Variance346.72272
MonotonicityNot monotonic
2024-05-11T02:22:09.234724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 141
 
2.6%
3.3 98
 
1.8%
6.6 85
 
1.6%
10.0 67
 
1.2%
3.0 67
 
1.2%
4.0 64
 
1.2%
6.0 62
 
1.1%
5.0 57
 
1.0%
2.0 50
 
0.9%
15.0 46
 
0.8%
Other values (972) 1819
33.4%
(Missing) 2884
53.0%
ValueCountFrequency (%)
0.0 141
2.6%
0.28 1
 
< 0.1%
0.5 4
 
0.1%
0.54 1
 
< 0.1%
0.6 2
 
< 0.1%
0.63 1
 
< 0.1%
0.78 1
 
< 0.1%
0.9 1
 
< 0.1%
1.0 9
 
0.2%
1.07 1
 
< 0.1%
ValueCountFrequency (%)
330.47 2
< 0.1%
172.4 1
< 0.1%
153.97 1
< 0.1%
145.5 1
< 0.1%
138.97 1
< 0.1%
108.3 1
< 0.1%
106.3 1
< 0.1%
106.0 1
< 0.1%
104.58 1
< 0.1%
100.0 2
< 0.1%
Distinct210
Distinct (%)3.9%
Missing7
Missing (%)0.1%
Memory size42.6 KiB
2024-05-11T02:22:09.958082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1117246
Min length6

Characters and Unicode

Total characters33205
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

Unique40 ?
Unique (%)0.7%

Sample

1st row136035
2nd row136035
3rd row136081
4th row136081
5th row136800
ValueCountFrequency (%)
136800 1011
18.6%
136719 944
17.4%
136865 456
 
8.4%
136130 356
 
6.6%
136060 258
 
4.7%
136753 159
 
2.9%
136-719 152
 
2.8%
136035 128
 
2.4%
136829 99
 
1.8%
136818 86
 
1.6%
Other values (200) 1784
32.8%
2024-05-11T02:22:11.177432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7518
22.6%
3 6603
19.9%
6 6486
19.5%
0 4030
12.1%
8 3013
9.1%
7 1509
 
4.5%
9 1306
 
3.9%
5 1199
 
3.6%
- 607
 
1.8%
2 495
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32598
98.2%
Dash Punctuation 607
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7518
23.1%
3 6603
20.3%
6 6486
19.9%
0 4030
12.4%
8 3013
9.2%
7 1509
 
4.6%
9 1306
 
4.0%
5 1199
 
3.7%
2 495
 
1.5%
4 439
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 607
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33205
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7518
22.6%
3 6603
19.9%
6 6486
19.5%
0 4030
12.1%
8 3013
9.1%
7 1509
 
4.5%
9 1306
 
3.9%
5 1199
 
3.6%
- 607
 
1.8%
2 495
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7518
22.6%
3 6603
19.9%
6 6486
19.5%
0 4030
12.1%
8 3013
9.1%
7 1509
 
4.5%
9 1306
 
3.9%
5 1199
 
3.6%
- 607
 
1.8%
2 495
 
1.5%
Distinct2002
Distinct (%)36.8%
Missing7
Missing (%)0.1%
Memory size42.6 KiB
2024-05-11T02:22:11.862100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length52
Mean length26.246273
Min length17

Characters and Unicode

Total characters142596
Distinct characters314
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1704 ?
Unique (%)31.4%

Sample

1st row서울특별시 성북구 동소문동5가 55-1
2nd row서울특별시 성북구 동소문동5가 63-11
3rd row서울특별시 성북구 보문동1가 201-0
4th row서울특별시 성북구 보문동1가 203-0
5th row서울특별시 성북구 길음동 877-197
ValueCountFrequency (%)
서울특별시 5432
19.8%
성북구 5430
19.8%
길음동 2334
 
8.5%
20-1 1527
 
5.6%
현대백화점미아점 1074
 
3.9%
하월곡동 1003
 
3.7%
25-2 572
 
2.1%
돈암동 501
 
1.8%
46-73 476
 
1.7%
이마트 338
 
1.2%
Other values (1882) 8704
31.8%
2024-05-11T02:22:12.970646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26221
 
18.4%
6156
 
4.3%
5678
 
4.0%
5629
 
3.9%
5604
 
3.9%
5445
 
3.8%
5444
 
3.8%
5436
 
3.8%
5432
 
3.8%
5432
 
3.8%
Other values (304) 66119
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89077
62.5%
Space Separator 26221
 
18.4%
Decimal Number 21401
 
15.0%
Dash Punctuation 4460
 
3.1%
Open Punctuation 526
 
0.4%
Close Punctuation 525
 
0.4%
Uppercase Letter 323
 
0.2%
Other Punctuation 52
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6156
 
6.9%
5678
 
6.4%
5629
 
6.3%
5604
 
6.3%
5445
 
6.1%
5444
 
6.1%
5436
 
6.1%
5432
 
6.1%
5432
 
6.1%
2820
 
3.2%
Other values (262) 36001
40.4%
Uppercase Letter
ValueCountFrequency (%)
G 101
31.3%
S 101
31.3%
B 31
 
9.6%
A 18
 
5.6%
T 14
 
4.3%
P 14
 
4.3%
K 13
 
4.0%
L 9
 
2.8%
E 6
 
1.9%
F 3
 
0.9%
Other values (9) 13
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 4616
21.6%
2 4433
20.7%
0 2981
13.9%
3 1946
9.1%
6 1810
 
8.5%
5 1498
 
7.0%
4 1371
 
6.4%
7 1214
 
5.7%
9 796
 
3.7%
8 736
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 40
76.9%
@ 9
 
17.3%
/ 1
 
1.9%
? 1
 
1.9%
. 1
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
g 3
37.5%
s 3
37.5%
e 2
25.0%
Space Separator
ValueCountFrequency (%)
26221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4460
100.0%
Open Punctuation
ValueCountFrequency (%)
( 526
100.0%
Close Punctuation
ValueCountFrequency (%)
) 525
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89077
62.5%
Common 53188
37.3%
Latin 331
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6156
 
6.9%
5678
 
6.4%
5629
 
6.3%
5604
 
6.3%
5445
 
6.1%
5444
 
6.1%
5436
 
6.1%
5432
 
6.1%
5432
 
6.1%
2820
 
3.2%
Other values (262) 36001
40.4%
Latin
ValueCountFrequency (%)
G 101
30.5%
S 101
30.5%
B 31
 
9.4%
A 18
 
5.4%
T 14
 
4.2%
P 14
 
4.2%
K 13
 
3.9%
L 9
 
2.7%
E 6
 
1.8%
g 3
 
0.9%
Other values (12) 21
 
6.3%
Common
ValueCountFrequency (%)
26221
49.3%
1 4616
 
8.7%
- 4460
 
8.4%
2 4433
 
8.3%
0 2981
 
5.6%
3 1946
 
3.7%
6 1810
 
3.4%
5 1498
 
2.8%
4 1371
 
2.6%
7 1214
 
2.3%
Other values (10) 2638
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89077
62.5%
ASCII 53519
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26221
49.0%
1 4616
 
8.6%
- 4460
 
8.3%
2 4433
 
8.3%
0 2981
 
5.6%
3 1946
 
3.6%
6 1810
 
3.4%
5 1498
 
2.8%
4 1371
 
2.6%
7 1214
 
2.3%
Other values (32) 2969
 
5.5%
Hangul
ValueCountFrequency (%)
6156
 
6.9%
5678
 
6.4%
5629
 
6.3%
5604
 
6.3%
5445
 
6.1%
5444
 
6.1%
5436
 
6.1%
5432
 
6.1%
5432
 
6.1%
2820
 
3.2%
Other values (262) 36001
40.4%

도로명주소
Text

MISSING 

Distinct1617
Distinct (%)37.7%
Missing1150
Missing (%)21.1%
Memory size42.6 KiB
2024-05-11T02:22:13.804490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length59.5
Mean length36.852914
Min length21

Characters and Unicode

Total characters158099
Distinct characters310
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1380 ?
Unique (%)32.2%

Sample

1st row서울특별시 성북구 인촌로6길 18 (보문동1가)
2nd row서울특별시 성북구 동소문로 225-13, 1층 (길음동)
3rd row서울특별시 성북구 장위로38길 16 (장위동)
4th row서울특별시 성북구 장위로40라길 22, 2호 (장위동, 지상1층)
5th row서울특별시 성북구 장위로 126 (장위동)
ValueCountFrequency (%)
서울특별시 4289
 
14.2%
성북구 4287
 
14.2%
지하1층 1940
 
6.4%
길음동 1901
 
6.3%
동소문로 1453
 
4.8%
315 1385
 
4.6%
현대백화점미아점 1086
 
3.6%
하월곡동 885
 
2.9%
1층 631
 
2.1%
미아점 558
 
1.9%
Other values (1342) 11747
38.9%
2024-05-11T02:22:15.125043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25880
 
16.4%
6552
 
4.1%
1 6321
 
4.0%
, 4938
 
3.1%
4907
 
3.1%
4779
 
3.0%
4528
 
2.9%
( 4465
 
2.8%
) 4463
 
2.8%
4309
 
2.7%
Other values (300) 86957
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100559
63.6%
Space Separator 25880
 
16.4%
Decimal Number 17200
 
10.9%
Other Punctuation 4942
 
3.1%
Open Punctuation 4465
 
2.8%
Close Punctuation 4463
 
2.8%
Uppercase Letter 316
 
0.2%
Dash Punctuation 236
 
0.1%
Lowercase Letter 33
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6552
 
6.5%
4907
 
4.9%
4779
 
4.8%
4528
 
4.5%
4309
 
4.3%
4302
 
4.3%
4295
 
4.3%
4291
 
4.3%
4289
 
4.3%
4289
 
4.3%
Other values (260) 54018
53.7%
Uppercase Letter
ValueCountFrequency (%)
S 124
39.2%
G 116
36.7%
B 41
 
13.0%
K 11
 
3.5%
A 4
 
1.3%
E 3
 
0.9%
P 2
 
0.6%
W 2
 
0.6%
V 2
 
0.6%
I 2
 
0.6%
Other values (7) 9
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 6321
36.8%
5 2097
 
12.2%
3 2053
 
11.9%
7 1563
 
9.1%
2 1531
 
8.9%
6 1233
 
7.2%
4 1071
 
6.2%
8 539
 
3.1%
0 529
 
3.1%
9 263
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
s 14
42.4%
g 14
42.4%
e 3
 
9.1%
b 2
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 4938
99.9%
@ 3
 
0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
25880
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4465
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4463
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 236
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100559
63.6%
Common 57191
36.2%
Latin 349
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6552
 
6.5%
4907
 
4.9%
4779
 
4.8%
4528
 
4.5%
4309
 
4.3%
4302
 
4.3%
4295
 
4.3%
4291
 
4.3%
4289
 
4.3%
4289
 
4.3%
Other values (260) 54018
53.7%
Latin
ValueCountFrequency (%)
S 124
35.5%
G 116
33.2%
B 41
 
11.7%
s 14
 
4.0%
g 14
 
4.0%
K 11
 
3.2%
A 4
 
1.1%
E 3
 
0.9%
e 3
 
0.9%
b 2
 
0.6%
Other values (11) 17
 
4.9%
Common
ValueCountFrequency (%)
25880
45.3%
1 6321
 
11.1%
, 4938
 
8.6%
( 4465
 
7.8%
) 4463
 
7.8%
5 2097
 
3.7%
3 2053
 
3.6%
7 1563
 
2.7%
2 1531
 
2.7%
6 1233
 
2.2%
Other values (9) 2647
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100558
63.6%
ASCII 57540
36.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25880
45.0%
1 6321
 
11.0%
, 4938
 
8.6%
( 4465
 
7.8%
) 4463
 
7.8%
5 2097
 
3.6%
3 2053
 
3.6%
7 1563
 
2.7%
2 1531
 
2.7%
6 1233
 
2.1%
Other values (30) 2996
 
5.2%
Hangul
ValueCountFrequency (%)
6552
 
6.5%
4907
 
4.9%
4779
 
4.8%
4528
 
4.5%
4309
 
4.3%
4302
 
4.3%
4295
 
4.3%
4291
 
4.3%
4289
 
4.3%
4289
 
4.3%
Other values (259) 54017
53.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct155
Distinct (%)3.7%
Missing1205
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean2764.5249
Minimum2700
Maximum16996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-05-11T02:22:15.526506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2700
5-th percentile2724
Q12730
median2734
Q32784
95-th percentile2846
Maximum16996
Range14296
Interquartile range (IQR)54

Descriptive statistics

Standard deviation249.39294
Coefficient of variation (CV)0.090211864
Kurtosis2601.9198
Mean2764.5249
Median Absolute Deviation (MAD)6
Skewness48.249406
Sum11707763
Variance62196.841
MonotonicityNot monotonic
2024-05-11T02:22:16.072699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2730 1385
25.5%
2751 485
 
8.9%
2734 318
 
5.8%
2729 239
 
4.4%
2831 208
 
3.8%
2728 183
 
3.4%
2828 139
 
2.6%
2846 84
 
1.5%
2784 65
 
1.2%
2770 47
 
0.9%
Other values (145) 1082
19.9%
(Missing) 1205
22.2%
ValueCountFrequency (%)
2700 2
 
< 0.1%
2701 4
 
0.1%
2702 5
 
0.1%
2704 2
 
< 0.1%
2705 1
 
< 0.1%
2708 1
 
< 0.1%
2709 19
0.3%
2710 30
0.6%
2711 14
0.3%
2712 1
 
< 0.1%
ValueCountFrequency (%)
16996 1
 
< 0.1%
8793 1
 
< 0.1%
6797 1
 
< 0.1%
2880 24
0.4%
2879 2
 
< 0.1%
2878 1
 
< 0.1%
2874 1
 
< 0.1%
2873 12
0.2%
2872 7
 
0.1%
2871 2
 
< 0.1%
Distinct2634
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
2024-05-11T02:22:16.672284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length6.4487132
Min length2

Characters and Unicode

Total characters35081
Distinct characters741
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2116 ?
Unique (%)38.9%

Sample

1st row영주
2nd row화성
3rd row풍년상회
4th row영남
5th row시장기름집
ValueCountFrequency (%)
주식회사 355
 
5.7%
주)햇살드림 108
 
1.7%
주)단우 87
 
1.4%
주)월드푸드 85
 
1.4%
주)인네이처 79
 
1.3%
주)에이치제이에프 73
 
1.2%
토담 58
 
0.9%
주)명진푸드시스템 58
 
0.9%
장원에프엔비 54
 
0.9%
월드푸드 53
 
0.9%
Other values (2791) 5224
83.8%
2024-05-11T02:22:17.985934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2129
 
6.1%
) 1880
 
5.4%
( 1861
 
5.3%
1111
 
3.2%
794
 
2.3%
792
 
2.3%
779
 
2.2%
664
 
1.9%
648
 
1.8%
567
 
1.6%
Other values (731) 23856
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29761
84.8%
Close Punctuation 1880
 
5.4%
Open Punctuation 1861
 
5.3%
Space Separator 794
 
2.3%
Lowercase Letter 364
 
1.0%
Uppercase Letter 257
 
0.7%
Other Punctuation 92
 
0.3%
Decimal Number 65
 
0.2%
Dash Punctuation 6
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2129
 
7.2%
1111
 
3.7%
792
 
2.7%
779
 
2.6%
664
 
2.2%
648
 
2.2%
567
 
1.9%
504
 
1.7%
475
 
1.6%
446
 
1.5%
Other values (664) 21646
72.7%
Lowercase Letter
ValueCountFrequency (%)
e 51
14.0%
o 39
10.7%
h 28
 
7.7%
m 26
 
7.1%
i 24
 
6.6%
a 23
 
6.3%
t 22
 
6.0%
r 21
 
5.8%
n 21
 
5.8%
s 16
 
4.4%
Other values (13) 93
25.5%
Uppercase Letter
ValueCountFrequency (%)
M 24
 
9.3%
F 21
 
8.2%
O 20
 
7.8%
S 19
 
7.4%
B 17
 
6.6%
H 17
 
6.6%
K 15
 
5.8%
A 15
 
5.8%
D 14
 
5.4%
R 14
 
5.4%
Other values (13) 81
31.5%
Decimal Number
ValueCountFrequency (%)
2 12
18.5%
1 11
16.9%
5 11
16.9%
0 8
12.3%
3 5
7.7%
9 5
7.7%
4 4
 
6.2%
6 3
 
4.6%
7 3
 
4.6%
8 3
 
4.6%
Other Punctuation
ValueCountFrequency (%)
& 61
66.3%
, 11
 
12.0%
. 11
 
12.0%
? 4
 
4.3%
/ 3
 
3.3%
' 2
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 1880
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1861
100.0%
Space Separator
ValueCountFrequency (%)
794
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29758
84.8%
Common 4699
 
13.4%
Latin 621
 
1.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2129
 
7.2%
1111
 
3.7%
792
 
2.7%
779
 
2.6%
664
 
2.2%
648
 
2.2%
567
 
1.9%
504
 
1.7%
475
 
1.6%
446
 
1.5%
Other values (661) 21643
72.7%
Latin
ValueCountFrequency (%)
e 51
 
8.2%
o 39
 
6.3%
h 28
 
4.5%
m 26
 
4.2%
M 24
 
3.9%
i 24
 
3.9%
a 23
 
3.7%
t 22
 
3.5%
F 21
 
3.4%
r 21
 
3.4%
Other values (36) 342
55.1%
Common
ValueCountFrequency (%)
) 1880
40.0%
( 1861
39.6%
794
16.9%
& 61
 
1.3%
2 12
 
0.3%
1 11
 
0.2%
5 11
 
0.2%
, 11
 
0.2%
. 11
 
0.2%
0 8
 
0.2%
Other values (11) 39
 
0.8%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29758
84.8%
ASCII 5320
 
15.2%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2129
 
7.2%
1111
 
3.7%
792
 
2.7%
779
 
2.6%
664
 
2.2%
648
 
2.2%
567
 
1.9%
504
 
1.7%
475
 
1.6%
446
 
1.5%
Other values (661) 21643
72.7%
ASCII
ValueCountFrequency (%)
) 1880
35.3%
( 1861
35.0%
794
14.9%
& 61
 
1.1%
e 51
 
1.0%
o 39
 
0.7%
h 28
 
0.5%
m 26
 
0.5%
M 24
 
0.5%
i 24
 
0.5%
Other values (57) 532
 
10.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct3650
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
Minimum2001-10-29 00:00:00
Maximum2024-05-09 10:09:36
2024-05-11T02:22:18.411486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:22:19.278115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
I
2887 
U
2553 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2887
53.1%
U 2553
46.9%

Length

2024-05-11T02:22:19.809021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:20.142550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2887
53.1%
u 2553
46.9%
Distinct1219
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T02:22:20.520174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:22:20.972781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
즉석판매제조가공업
5434 
기타
 
6

Length

Max length9
Median length9
Mean length8.9922794
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 5434
99.9%
기타 6
 
0.1%

Length

2024-05-11T02:22:21.436095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:21.762184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 5434
99.9%
기타 6
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1157
Distinct (%)21.7%
Missing112
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean202473.77
Minimum196881.91
Maximum205996.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-05-11T02:22:22.113163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196881.91
5-th percentile200741.81
Q1201852.59
median202466.8
Q3202776.31
95-th percentile204481.55
Maximum205996.72
Range9114.8079
Interquartile range (IQR)923.7227

Descriptive statistics

Standard deviation1133.9572
Coefficient of variation (CV)0.0056005141
Kurtosis0.7713318
Mean202473.77
Median Absolute Deviation (MAD)521.02559
Skewness0.20997165
Sum1.0787802 × 109
Variance1285858.9
MonotonicityNot monotonic
2024-05-11T02:22:22.596505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202466.801104742 1359
25.0%
202555.30089577 572
 
10.5%
203502.004139568 475
 
8.7%
202667.468802014 315
 
5.8%
200841.726990037 310
 
5.7%
202466.801084521 169
 
3.1%
201501.474496909 141
 
2.6%
201358.893989884 55
 
1.0%
203318.127254872 55
 
1.0%
199586.316865115 54
 
1.0%
Other values (1147) 1823
33.5%
(Missing) 112
 
2.1%
ValueCountFrequency (%)
196881.909980582 1
 
< 0.1%
198921.445609008 1
 
< 0.1%
199090.91528523 1
 
< 0.1%
199094.914328436 1
 
< 0.1%
199265.747571241 1
 
< 0.1%
199289.212742034 2
 
< 0.1%
199351.832787571 1
 
< 0.1%
199455.31327238 1
 
< 0.1%
199586.316865115 54
1.0%
199621.266942781 1
 
< 0.1%
ValueCountFrequency (%)
205996.717928956 18
0.3%
205729.347626245 1
 
< 0.1%
205717.342622356 1
 
< 0.1%
205699.692847663 1
 
< 0.1%
205667.18057534 1
 
< 0.1%
205665.070767038 1
 
< 0.1%
205658.568580673 1
 
< 0.1%
205626.659611385 1
 
< 0.1%
205623.732291159 1
 
< 0.1%
205621.064756583 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1158
Distinct (%)21.7%
Missing112
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean455820.92
Minimum440070.73
Maximum457844.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-05-11T02:22:23.060979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440070.73
5-th percentile454304.94
Q1455500.57
median456227.57
Q3456227.57
95-th percentile456704.52
Maximum457844.35
Range17773.62
Interquartile range (IQR)727.00275

Descriptive statistics

Standard deviation851.61391
Coefficient of variation (CV)0.0018683081
Kurtosis37.092598
Mean455820.92
Median Absolute Deviation (MAD)322.91586
Skewness-2.8014038
Sum2.4286138 × 109
Variance725246.26
MonotonicityNot monotonic
2024-05-11T02:22:23.537095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456227.571665528 1359
25.0%
456503.066230481 572
 
10.5%
455500.568972657 475
 
8.7%
455858.920803881 315
 
5.8%
454721.505180141 305
 
5.6%
456227.571720914 169
 
3.1%
455061.698603977 141
 
2.6%
454439.085102224 55
 
1.0%
456078.982123486 55
 
1.0%
454632.316678757 54
 
1.0%
Other values (1148) 1828
33.6%
(Missing) 112
 
2.1%
ValueCountFrequency (%)
440070.727589935 1
< 0.1%
441429.938309013 1
< 0.1%
452935.221547454 1
< 0.1%
452963.515149491 1
< 0.1%
452969.237097436 1
< 0.1%
453013.952137832 1
< 0.1%
453015.878818415 1
< 0.1%
453034.911408 1
< 0.1%
453056.536906206 1
< 0.1%
453060.946220955 1
< 0.1%
ValueCountFrequency (%)
457844.348010616 22
0.4%
457803.264646008 1
 
< 0.1%
457768.96703203 1
 
< 0.1%
457664.961911112 6
 
0.1%
457581.254031821 1
 
< 0.1%
457579.21641655 3
 
0.1%
457561.490871873 1
 
< 0.1%
457552.739712952 1
 
< 0.1%
457533.773053035 1
 
< 0.1%
457527.065931978 2
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
즉석판매제조가공업
4379 
<NA>
1055 
기타
 
6

Length

Max length9
Median length9
Mean length8.0226103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 4379
80.5%
<NA> 1055
 
19.4%
기타 6
 
0.1%

Length

2024-05-11T02:22:24.026191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:24.376441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 4379
80.5%
na 1055
 
19.4%
기타 6
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4776 
0
 
398
1
 
263
2
 
3

Length

Max length4
Median length4
Mean length3.6338235
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4776
87.8%
0 398
 
7.3%
1 263
 
4.8%
2 3
 
0.1%

Length

2024-05-11T02:22:24.745778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:25.180494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4776
87.8%
0 398
 
7.3%
1 263
 
4.8%
2 3
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4846 
0
 
413
1
 
177
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.6724265
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4846
89.1%
0 413
 
7.6%
1 177
 
3.3%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-05-11T02:22:25.551812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:25.884146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4846
89.1%
0 413
 
7.6%
1 177
 
3.3%
2 3
 
0.1%
3 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
5067 
주택가주변
 
271
기타
 
86
아파트지역
 
14
학교정화(절대)
 
2

Length

Max length8
Median length4
Mean length4.0222426
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5067
93.1%
주택가주변 271
 
5.0%
기타 86
 
1.6%
아파트지역 14
 
0.3%
학교정화(절대) 2
 
< 0.1%

Length

2024-05-11T02:22:26.311686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:26.743113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5067
93.1%
주택가주변 271
 
5.0%
기타 86
 
1.6%
아파트지역 14
 
0.3%
학교정화(절대 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
5067 
기타
 
231
자율
 
142

Length

Max length4
Median length4
Mean length3.8628676
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자율
2nd row자율
3rd row기타
4th row자율
5th row자율

Common Values

ValueCountFrequency (%)
<NA> 5067
93.1%
기타 231
 
4.2%
자율 142
 
2.6%

Length

2024-05-11T02:22:27.289116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:28.060542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5067
93.1%
기타 231
 
4.2%
자율 142
 
2.6%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4996 
상수도전용
 
444

Length

Max length5
Median length4
Mean length4.0816176
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4996
91.8%
상수도전용 444
 
8.2%

Length

2024-05-11T02:22:28.496607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:28.976638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4996
91.8%
상수도전용 444
 
8.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
5095 
0
 
345

Length

Max length4
Median length4
Mean length3.8097426
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> 5095
93.7%
0 345
 
6.3%

Length

2024-05-11T02:22:29.502846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:29.911041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5095
93.7%
0 345
 
6.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4011 
0
1429 

Length

Max length4
Median length4
Mean length3.2119485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4011
73.7%
0 1429
 
26.3%

Length

2024-05-11T02:22:30.246394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:30.567781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4011
73.7%
0 1429
 
26.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4011 
0
1429 

Length

Max length4
Median length4
Mean length3.2119485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4011
73.7%
0 1429
 
26.3%

Length

2024-05-11T02:22:30.914352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:31.147215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4011
73.7%
0 1429
 
26.3%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4008 
0
1429 
1
 
3

Length

Max length4
Median length4
Mean length3.2102941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4008
73.7%
0 1429
 
26.3%
1 3
 
0.1%

Length

2024-05-11T02:22:31.582710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:31.964072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4008
73.7%
0 1429
 
26.3%
1 3
 
0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4009 
0
1429 
1
 
2

Length

Max length4
Median length4
Mean length3.2108456
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4009
73.7%
0 1429
 
26.3%
1 2
 
< 0.1%

Length

2024-05-11T02:22:32.393854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:32.773297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4009
73.7%
0 1429
 
26.3%
1 2
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4011 
자가
1152 
임대
 
277

Length

Max length4
Median length4
Mean length3.4746324
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4011
73.7%
자가 1152
 
21.2%
임대 277
 
5.1%

Length

2024-05-11T02:22:33.267452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:33.699490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4011
73.7%
자가 1152
 
21.2%
임대 277
 
5.1%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4865 
0
574 
5000000
 
1

Length

Max length7
Median length4
Mean length3.6840074
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4865
89.4%
0 574
 
10.6%
5000000 1
 
< 0.1%

Length

2024-05-11T02:22:34.068868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:34.416452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4865
89.4%
0 574
 
10.6%
5000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.6 KiB
<NA>
4865 
0
574 
350000
 
1

Length

Max length6
Median length4
Mean length3.6838235
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4865
89.4%
0 574
 
10.6%
350000 1
 
< 0.1%

Length

2024-05-11T02:22:34.736224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:35.053572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4865
89.4%
0 574
 
10.6%
350000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1055
Missing (%)19.4%
Memory size10.8 KiB
False
4385 
(Missing)
1055 
ValueCountFrequency (%)
False 4385
80.6%
(Missing) 1055
 
19.4%
2024-05-11T02:22:35.354974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct52
Distinct (%)1.2%
Missing1055
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean0.33661574
Minimum0
Maximum59.4
Zeros4321
Zeros (%)79.4%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-05-11T02:22:35.751294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum59.4
Range59.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2302893
Coefficient of variation (CV)9.5963704
Kurtosis154.71829
Mean0.33661574
Median Absolute Deviation (MAD)0
Skewness11.656407
Sum1476.06
Variance10.434769
MonotonicityNot monotonic
2024-05-11T02:22:36.189093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4321
79.4%
30.0 3
 
0.1%
20.0 3
 
0.1%
8.7 2
 
< 0.1%
26.4 2
 
< 0.1%
24.0 2
 
< 0.1%
33.0 2
 
< 0.1%
10.0 2
 
< 0.1%
9.9 2
 
< 0.1%
32.0 2
 
< 0.1%
Other values (42) 44
 
0.8%
(Missing) 1055
 
19.4%
ValueCountFrequency (%)
0.0 4321
79.4%
3.0 1
 
< 0.1%
3.3 1
 
< 0.1%
4.0 1
 
< 0.1%
6.3 1
 
< 0.1%
6.6 1
 
< 0.1%
6.84 1
 
< 0.1%
7.0 1
 
< 0.1%
7.03 1
 
< 0.1%
8.7 2
 
< 0.1%
ValueCountFrequency (%)
59.4 1
< 0.1%
58.76 1
< 0.1%
56.57 1
< 0.1%
53.97 1
< 0.1%
50.0 1
< 0.1%
42.9 1
< 0.1%
42.72 1
< 0.1%
39.0 1
< 0.1%
36.6 1
< 0.1%
34.4 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5440
Missing (%)100.0%
Memory size47.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-107-1972-0021219720330<NA>3폐업2폐업20110426<NA><NA><NA>02 923396823.2136035서울특별시 성북구 동소문동5가 55-1<NA><NA>영주2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업1<NA>주택가주변자율<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130700003070000-107-1972-0024019720413<NA>3폐업2폐업20070927<NA><NA><NA>02 926223414.0136035서울특별시 성북구 동소문동5가 63-11<NA><NA>화성2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업201276.599089454386.871308즉석판매제조가공업1<NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230700003070000-107-1972-0026019720605<NA>3폐업2폐업20010321<NA><NA><NA>02 923994925.37136081서울특별시 성북구 보문동1가 201-0<NA><NA>풍년상회2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업201773.58423453621.538494즉석판매제조가공업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330700003070000-107-1972-0026119720605<NA>3폐업2폐업20180817<NA><NA><NA>02 923838615.0136081서울특별시 성북구 보문동1가 203-0서울특별시 성북구 인촌로6길 18 (보문동1가)2852영남2018-08-17 18:00:07I2018-08-31 23:59:59.0즉석판매제조가공업201774.432166453629.993756즉석판매제조가공업1<NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430700003070000-107-1972-0027119720525<NA>1영업/정상1영업<NA><NA><NA><NA>02 912113835.54136800서울특별시 성북구 길음동 877-197서울특별시 성북구 동소문로 225-13, 1층 (길음동)2721시장기름집2020-03-25 13:52:42U2020-03-27 02:40:00.0즉석판매제조가공업201816.279241455550.330359즉석판매제조가공업1<NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530700003070000-107-1972-0027219720704<NA>3폐업2폐업20000328<NA><NA><NA>02 917659919.41136802서울특별시 성북구 길음동 550-19<NA><NA>연수기름집2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업01주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630700003070000-107-1972-0028619720526<NA>3폐업2폐업20050816<NA><NA><NA>02 912297913.86136858서울특별시 성북구 종암동 3-74<NA><NA>경북2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업1<NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730700003070000-107-1972-0030419720408<NA>3폐업2폐업20191230<NA><NA><NA>02 915485718.54136829서울특별시 성북구 장위동 68-1014 1층서울특별시 성북구 장위로38길 16 (장위동)2769부산2019-12-30 13:50:02U2020-01-01 02:40:00.0즉석판매제조가공업204367.347788456732.945005즉석판매제조가공업1<NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830700003070000-107-1972-0031119720329<NA>3폐업2폐업20050315<NA><NA><NA>02 916001217.28136826서울특별시 성북구 장위동 37-28<NA><NA>삼광기름집2002-02-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업205038.489914456842.863249즉석판매제조가공업11주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930700003070000-107-1972-0031219720413<NA>1영업/정상1영업<NA><NA><NA><NA>02 936309121.0136829서울특별시 성북구 장위동 68-703 (2호, 지상1층)서울특별시 성북구 장위로40라길 22, 2호 (장위동, 지상1층)2770상주기름집2012-04-30 20:11:58I2018-08-31 23:59:59.0즉석판매제조가공업204460.12645456545.517392즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
543030700003070000-107-2024-001082024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-849서울특별시 성북구 정릉동 266-179서울특별시 성북구 보국문로18길 12, 1층 101호 (정릉동)2717진앤삼생명공학연구소2024-05-07 11:05:26I2023-12-05 00:09:00.0즉석판매제조가공업200765.497623456541.983878<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543130700003070000-107-2024-001092024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.28136-801서울특별시 성북구 길음동 1158서울특별시 성북구 삼양로 38, 2층 201호 (길음동)2732슬로우티스푼2024-05-07 14:32:25I2023-12-05 00:09:00.0즉석판매제조가공업202057.952343456032.940593<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543230700003070000-107-2024-001102024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 22816340<NA>136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730주식회사 지오에프앤씨2024-05-07 14:43:11I2023-12-05 00:09:00.0즉석판매제조가공업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543330700003070000-107-2024-001112024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-865서울특별시 성북구 하월곡동 46-73 코업스타클래스서울특별시 성북구 화랑로 76, 코업스타클래스 지하1층 (하월곡동)2751주식회사 케이프라이드2024-05-07 15:54:22I2023-12-05 00:09:00.0즉석판매제조가공업203502.00414455500.568973<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543430700003070000-107-2024-001122024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4.0136-841서울특별시 성북구 정릉동 16-89서울특별시 성북구 정릉로40길 40, 지하1층 2호 (정릉동)2816먹거리연구소2024-05-07 16:55:18I2023-12-05 00:09:00.0즉석판매제조가공업201606.895629455366.313892<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543530700003070000-107-2024-001132024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730(주)팜덕2024-05-08 10:20:27I2023-12-04 23:00:00.0즉석판매제조가공업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543630700003070000-107-2024-001142024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730(주)미르2024-05-08 13:18:53I2023-12-04 23:00:00.0즉석판매제조가공업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543730700003070000-107-2024-001152024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>031 792 5521<NA>136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730주식회사 두성2024-05-08 13:22:50I2023-12-04 23:00:00.0즉석판매제조가공업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543830700003070000-107-2024-001162024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>032 561 5209<NA>136-140서울특별시 성북구 장위동 316-3 센트럴타운서울특별시 성북구 월계로40길 7, 센트럴타운 1층 (장위동)2759(주)미트뱅크2024-05-08 16:00:22I2023-12-04 23:00:00.0즉석판매제조가공업204208.631201457844.348011<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543930700003070000-107-2024-001172024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-706서울특별시 성북구 삼선동5가 411 성북구청서울특별시 성북구 보문로 168, 성북동 성북로 일대 (삼선동5가)2848톡투미다바사회적협동조합2024-05-09 10:09:36I2023-12-04 23:01:00.0즉석판매제조가공업201416.773357454126.789905<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>