Overview

Dataset statistics

Number of variables44
Number of observations468
Missing cells4555
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory172.4 KiB
Average record size in memory377.3 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
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-18409/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (60.9%)Imbalance
등급구분명 is highly imbalanced (61.3%)Imbalance
총인원 is highly imbalanced (74.5%)Imbalance
본사종업원수 is highly imbalanced (74.5%)Imbalance
공장사무직종업원수 is highly imbalanced (74.5%)Imbalance
공장판매직종업원수 is highly imbalanced (74.5%)Imbalance
공장생산직종업원수 is highly imbalanced (74.5%)Imbalance
보증액 is highly imbalanced (74.5%)Imbalance
월세액 is highly imbalanced (74.5%)Imbalance
다중이용업소여부 is highly imbalanced (95.2%)Imbalance
인허가취소일자 has 468 (100.0%) missing valuesMissing
폐업일자 has 123 (26.3%) missing valuesMissing
휴업시작일자 has 468 (100.0%) missing valuesMissing
휴업종료일자 has 468 (100.0%) missing valuesMissing
재개업일자 has 468 (100.0%) missing valuesMissing
전화번호 has 228 (48.7%) missing valuesMissing
소재지면적 has 6 (1.3%) missing valuesMissing
도로명주소 has 118 (25.2%) missing valuesMissing
도로명우편번호 has 128 (27.4%) missing valuesMissing
좌표정보(X) has 15 (3.2%) missing valuesMissing
좌표정보(Y) has 15 (3.2%) missing valuesMissing
건물소유구분명 has 468 (100.0%) missing valuesMissing
다중이용업소여부 has 89 (19.0%) missing valuesMissing
시설총규모 has 89 (19.0%) missing valuesMissing
전통업소지정번호 has 468 (100.0%) missing valuesMissing
전통업소주된음식 has 468 (100.0%) missing valuesMissing
홈페이지 has 468 (100.0%) 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
건물소유구분명 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 8 (1.7%) zerosZeros
시설총규모 has 8 (1.7%) zerosZeros

Reproduction

Analysis started2024-05-11 07:13:10.454529
Analysis finished2024-05-11 07:13:11.281075
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3070000
468 

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 468
100.0%

Length

2024-05-11T16:13:11.335543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:11.428896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 468
100.0%

관리번호
Text

UNIQUE 

Distinct468
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T16:13:11.585482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10296
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

Unique468 ?
Unique (%)100.0%

Sample

1st row3070000-121-1969-08691
2nd row3070000-121-1970-08093
3rd row3070000-121-1976-08099
4th row3070000-121-1977-08087
5th row3070000-121-1978-08141
ValueCountFrequency (%)
3070000-121-1969-08691 1
 
0.2%
3070000-121-2015-00003 1
 
0.2%
3070000-121-2015-00016 1
 
0.2%
3070000-121-2015-00015 1
 
0.2%
3070000-121-2015-00014 1
 
0.2%
3070000-121-2015-00013 1
 
0.2%
3070000-121-2015-00012 1
 
0.2%
3070000-121-2015-00011 1
 
0.2%
3070000-121-2015-00010 1
 
0.2%
3070000-121-2015-00009 1
 
0.2%
Other values (458) 458
97.9%
2024-05-11T16:13:11.941314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4388
42.6%
1 1477
 
14.3%
- 1404
 
13.6%
2 1115
 
10.8%
7 584
 
5.7%
3 583
 
5.7%
9 246
 
2.4%
8 175
 
1.7%
6 113
 
1.1%
4 113
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8892
86.4%
Dash Punctuation 1404
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4388
49.3%
1 1477
 
16.6%
2 1115
 
12.5%
7 584
 
6.6%
3 583
 
6.6%
9 246
 
2.8%
8 175
 
2.0%
6 113
 
1.3%
4 113
 
1.3%
5 98
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1404
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4388
42.6%
1 1477
 
14.3%
- 1404
 
13.6%
2 1115
 
10.8%
7 584
 
5.7%
3 583
 
5.7%
9 246
 
2.4%
8 175
 
1.7%
6 113
 
1.1%
4 113
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4388
42.6%
1 1477
 
14.3%
- 1404
 
13.6%
2 1115
 
10.8%
7 584
 
5.7%
3 583
 
5.7%
9 246
 
2.4%
8 175
 
1.7%
6 113
 
1.1%
4 113
 
1.1%

인허가일자
Date

Distinct448
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1965-10-07 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T16:13:12.101873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:13:12.259204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
345 
1
123 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 345
73.7%
1 123
 
26.3%

Length

2024-05-11T16:13:12.409389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:12.498453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 345
73.7%
1 123
 
26.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
345 
영업/정상
123 

Length

Max length5
Median length2
Mean length2.7884615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 345
73.7%
영업/정상 123
 
26.3%

Length

2024-05-11T16:13:12.596335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:12.703013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 345
73.7%
영업/정상 123
 
26.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
345 
1
123 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 345
73.7%
1 123
 
26.3%

Length

2024-05-11T16:13:12.803153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:12.891427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 345
73.7%
1 123
 
26.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
345 
영업
123 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 345
73.7%
영업 123
 
26.3%

Length

2024-05-11T16:13:12.984506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:13.072695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 345
73.7%
영업 123
 
26.3%

폐업일자
Date

MISSING 

Distinct321
Distinct (%)93.0%
Missing123
Missing (%)26.3%
Memory size3.8 KiB
Minimum2005-08-25 00:00:00
Maximum2024-04-27 00:00:00
2024-05-11T16:13:13.412706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:13:13.568460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct230
Distinct (%)95.8%
Missing228
Missing (%)48.7%
Memory size3.8 KiB
2024-05-11T16:13:13.935825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.6375
Min length2

Characters and Unicode

Total characters2553
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

Unique221 ?
Unique (%)92.1%

Sample

1st row7427421
2nd row0209146913
3rd row0209181183
4th row02 9154732
5th row02 9179443
ValueCountFrequency (%)
02 194
38.6%
070 7
 
1.4%
0010 4
 
0.8%
909 4
 
0.8%
031 3
 
0.6%
911 3
 
0.6%
919 3
 
0.6%
922 3
 
0.6%
755 3
 
0.6%
921 3
 
0.6%
Other values (256) 275
54.8%
2024-05-11T16:13:14.352742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 453
17.7%
0 448
17.5%
337
13.2%
9 292
11.4%
1 218
8.5%
4 152
 
6.0%
3 143
 
5.6%
5 135
 
5.3%
7 129
 
5.1%
6 127
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2216
86.8%
Space Separator 337
 
13.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 453
20.4%
0 448
20.2%
9 292
13.2%
1 218
9.8%
4 152
 
6.9%
3 143
 
6.5%
5 135
 
6.1%
7 129
 
5.8%
6 127
 
5.7%
8 119
 
5.4%
Space Separator
ValueCountFrequency (%)
337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 453
17.7%
0 448
17.5%
337
13.2%
9 292
11.4%
1 218
8.5%
4 152
 
6.0%
3 143
 
5.6%
5 135
 
5.3%
7 129
 
5.1%
6 127
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 453
17.7%
0 448
17.5%
337
13.2%
9 292
11.4%
1 218
8.5%
4 152
 
6.0%
3 143
 
5.6%
5 135
 
5.3%
7 129
 
5.1%
6 127
 
5.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct331
Distinct (%)71.6%
Missing6
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean44.340844
Minimum0
Maximum921.94
Zeros8
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T16:13:14.504094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.609
Q116.85
median32.795
Q355.33
95-th percentile99.228
Maximum921.94
Range921.94
Interquartile range (IQR)38.48

Descriptive statistics

Standard deviation66.429507
Coefficient of variation (CV)1.4981561
Kurtosis90.783488
Mean44.340844
Median Absolute Deviation (MAD)18.615
Skewness8.3959082
Sum20485.47
Variance4412.8793
MonotonicityNot monotonic
2024-05-11T16:13:14.655073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 14
 
3.0%
9.9 10
 
2.1%
26.4 10
 
2.1%
0.0 8
 
1.7%
6.6 8
 
1.7%
10.0 7
 
1.5%
29.7 7
 
1.5%
3.3 6
 
1.3%
12.0 5
 
1.1%
46.2 5
 
1.1%
Other values (321) 382
81.6%
(Missing) 6
 
1.3%
ValueCountFrequency (%)
0.0 8
1.7%
1.5 1
 
0.2%
2.16 1
 
0.2%
2.25 1
 
0.2%
3.0 2
 
0.4%
3.2 1
 
0.2%
3.3 6
1.3%
4.0 3
 
0.6%
4.6 1
 
0.2%
4.78 1
 
0.2%
ValueCountFrequency (%)
921.94 1
0.2%
626.73 1
0.2%
539.97 2
0.4%
221.1 1
0.2%
158.4 1
0.2%
149.4 1
0.2%
148.73 1
0.2%
139.98 1
0.2%
136.85 1
0.2%
134.79 1
0.2%

소재지우편번호
Text

Distinct125
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T16:13:14.875860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1260684
Min length6

Characters and Unicode

Total characters2867
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

Unique49 ?
Unique (%)10.5%

Sample

1st row136041
2nd row136877
3rd row136836
4th row136837
5th row136140
ValueCountFrequency (%)
136719 36
 
7.7%
136800 36
 
7.7%
136110 26
 
5.6%
136-719 15
 
3.2%
136075 14
 
3.0%
136060 13
 
2.8%
136865 13
 
2.8%
136051 9
 
1.9%
136130 9
 
1.9%
136829 8
 
1.7%
Other values (115) 289
61.8%
2024-05-11T16:13:15.246155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 665
23.2%
3 565
19.7%
6 538
18.8%
0 328
11.4%
8 246
 
8.6%
5 119
 
4.2%
7 116
 
4.0%
4 80
 
2.8%
9 78
 
2.7%
2 73
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2808
97.9%
Dash Punctuation 59
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 665
23.7%
3 565
20.1%
6 538
19.2%
0 328
11.7%
8 246
 
8.8%
5 119
 
4.2%
7 116
 
4.1%
4 80
 
2.8%
9 78
 
2.8%
2 73
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2867
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 665
23.2%
3 565
19.7%
6 538
18.8%
0 328
11.4%
8 246
 
8.6%
5 119
 
4.2%
7 116
 
4.0%
4 80
 
2.8%
9 78
 
2.7%
2 73
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 665
23.2%
3 565
19.7%
6 538
18.8%
0 328
11.4%
8 246
 
8.6%
5 119
 
4.2%
7 116
 
4.0%
4 80
 
2.8%
9 78
 
2.7%
2 73
 
2.5%

지번주소
Text

Distinct408
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T16:13:15.493719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length26.679487
Min length18

Characters and Unicode

Total characters12486
Distinct characters188
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique384 ?
Unique (%)82.1%

Sample

1st row서울특별시 성북구 삼선동1가 13번지 지19 성북천복개지상
2nd row서울특별시 성북구 정릉동 403-9
3rd row서울특별시 성북구 장위동 231-590번지
4th row서울특별시 성북구 장위동 233-264번지
5th row서울특별시 성북구 장위동 64-8번지 ,9,10
ValueCountFrequency (%)
서울특별시 468
20.6%
성북구 468
20.6%
길음동 129
 
5.7%
정릉동 53
 
2.3%
장위동 47
 
2.1%
현대백화점미아점 44
 
1.9%
1층 43
 
1.9%
하월곡동 42
 
1.8%
20-1 39
 
1.7%
지하1층 35
 
1.5%
Other values (543) 905
39.8%
2024-05-11T16:13:15.882778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2169
 
17.4%
1 656
 
5.3%
동 566
 
4.5%
성 486
 
3.9%
북 480
 
3.8%
시 472
 
3.8%
구 470
 
3.8%
서 468
 
3.7%
울 468
 
3.7%
별 468
 
3.7%
Other values (178) 5783
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7513
60.2%
Decimal Number 2315
 
18.5%
Space Separator 2169
 
17.4%
Dash Punctuation 360
 
2.9%
Close Punctuation 41
 
0.3%
Open Punctuation 41
 
0.3%
Other Punctuation 26
 
0.2%
Uppercase Letter 18
 
0.1%
Lowercase Letter 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 566
 
7.5%
성 486
 
6.5%
북 480
 
6.4%
시 472
 
6.3%
구 470
 
6.3%
서 468
 
6.2%
울 468
 
6.2%
별 468
 
6.2%
특 468
 
6.2%
지 407
 
5.4%
Other values (153) 2760
36.7%
Decimal Number
ValueCountFrequency (%)
1 656
28.3%
2 387
16.7%
0 261
 
11.3%
3 191
 
8.3%
5 168
 
7.3%
4 157
 
6.8%
8 139
 
6.0%
6 136
 
5.9%
7 136
 
5.9%
9 84
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
B 10
55.6%
A 3
 
16.7%
S 2
 
11.1%
K 1
 
5.6%
G 1
 
5.6%
E 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 24
92.3%
. 2
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
2169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 360
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7513
60.2%
Common 4953
39.7%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 566
 
7.5%
성 486
 
6.5%
북 480
 
6.4%
시 472
 
6.3%
구 470
 
6.3%
서 468
 
6.2%
울 468
 
6.2%
별 468
 
6.2%
특 468
 
6.2%
지 407
 
5.4%
Other values (153) 2760
36.7%
Common
ValueCountFrequency (%)
2169
43.8%
1 656
 
13.2%
2 387
 
7.8%
- 360
 
7.3%
0 261
 
5.3%
3 191
 
3.9%
5 168
 
3.4%
4 157
 
3.2%
8 139
 
2.8%
6 136
 
2.7%
Other values (7) 329
 
6.6%
Latin
ValueCountFrequency (%)
B 10
50.0%
A 3
 
15.0%
S 2
 
10.0%
b 1
 
5.0%
K 1
 
5.0%
e 1
 
5.0%
G 1
 
5.0%
E 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7513
60.2%
ASCII 4972
39.8%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2169
43.6%
1 656
 
13.2%
2 387
 
7.8%
- 360
 
7.2%
0 261
 
5.2%
3 191
 
3.8%
5 168
 
3.4%
4 157
 
3.2%
8 139
 
2.8%
6 136
 
2.7%
Other values (14) 348
 
7.0%
Hangul
ValueCountFrequency (%)
동 566
 
7.5%
성 486
 
6.5%
북 480
 
6.4%
시 472
 
6.3%
구 470
 
6.3%
서 468
 
6.2%
울 468
 
6.2%
별 468
 
6.2%
특 468
 
6.2%
지 407
 
5.4%
Other values (153) 2760
36.7%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

도로명주소
Text

MISSING 

Distinct301
Distinct (%)86.0%
Missing118
Missing (%)25.2%
Memory size3.8 KiB
2024-05-11T16:13:16.180445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length51
Mean length33.714286
Min length21

Characters and Unicode

Total characters11800
Distinct characters203
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

Unique293 ?
Unique (%)83.7%

Sample

1st row서울특별시 성북구 보국문로 40-3 (정릉동)
2nd row서울특별시 성북구 돌곶이로 105 (장위동,,9,10)
3rd row서울특별시 성북구 장월로 168 (장위동)
4th row서울특별시 성북구 장위로 106 (장위동)
5th row서울특별시 성북구 종암로3길 18, 낙원빌딩 1층 (종암동)
ValueCountFrequency (%)
서울특별시 350
 
15.9%
성북구 350
 
15.9%
길음동 89
 
4.0%
동소문로 74
 
3.4%
1층 71
 
3.2%
315 61
 
2.8%
지하1층 61
 
2.8%
현대백화점미아점 44
 
2.0%
정릉동 34
 
1.5%
하월곡동 29
 
1.3%
Other values (492) 1045
47.3%
2024-05-11T16:13:16.655792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1858
 
15.7%
1 579
 
4.9%
동 548
 
4.6%
성 382
 
3.2%
북 379
 
3.2%
( 375
 
3.2%
) 375
 
3.2%
서 356
 
3.0%
시 354
 
3.0%
구 352
 
3.0%
Other values (193) 6242
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7044
59.7%
Space Separator 1858
 
15.7%
Decimal Number 1749
 
14.8%
Open Punctuation 375
 
3.2%
Close Punctuation 375
 
3.2%
Other Punctuation 333
 
2.8%
Dash Punctuation 41
 
0.3%
Uppercase Letter 22
 
0.2%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 548
 
7.8%
성 382
 
5.4%
북 379
 
5.4%
서 356
 
5.1%
시 354
 
5.0%
구 352
 
5.0%
로 351
 
5.0%
별 350
 
5.0%
울 350
 
5.0%
특 350
 
5.0%
Other values (168) 3272
46.5%
Decimal Number
ValueCountFrequency (%)
1 579
33.1%
2 226
 
12.9%
3 188
 
10.7%
5 170
 
9.7%
0 135
 
7.7%
4 120
 
6.9%
6 98
 
5.6%
7 95
 
5.4%
8 72
 
4.1%
9 66
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 14
63.6%
A 3
 
13.6%
S 2
 
9.1%
G 1
 
4.5%
K 1
 
4.5%
E 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 330
99.1%
@ 2
 
0.6%
? 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1858
100.0%
Open Punctuation
ValueCountFrequency (%)
( 375
100.0%
Close Punctuation
ValueCountFrequency (%)
) 375
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7044
59.7%
Common 4733
40.1%
Latin 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 548
 
7.8%
성 382
 
5.4%
북 379
 
5.4%
서 356
 
5.1%
시 354
 
5.0%
구 352
 
5.0%
로 351
 
5.0%
별 350
 
5.0%
울 350
 
5.0%
특 350
 
5.0%
Other values (168) 3272
46.5%
Common
ValueCountFrequency (%)
1858
39.3%
1 579
 
12.2%
( 375
 
7.9%
) 375
 
7.9%
, 330
 
7.0%
2 226
 
4.8%
3 188
 
4.0%
5 170
 
3.6%
0 135
 
2.9%
4 120
 
2.5%
Other values (8) 377
 
8.0%
Latin
ValueCountFrequency (%)
B 14
60.9%
A 3
 
13.0%
S 2
 
8.7%
G 1
 
4.3%
b 1
 
4.3%
K 1
 
4.3%
E 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7044
59.7%
ASCII 4756
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1858
39.1%
1 579
 
12.2%
( 375
 
7.9%
) 375
 
7.9%
, 330
 
6.9%
2 226
 
4.8%
3 188
 
4.0%
5 170
 
3.6%
0 135
 
2.8%
4 120
 
2.5%
Other values (15) 400
 
8.4%
Hangul
ValueCountFrequency (%)
동 548
 
7.8%
성 382
 
5.4%
북 379
 
5.4%
서 356
 
5.1%
시 354
 
5.0%
구 352
 
5.0%
로 351
 
5.0%
별 350
 
5.0%
울 350
 
5.0%
특 350
 
5.0%
Other values (168) 3272
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct109
Distinct (%)32.1%
Missing128
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean2776.2647
Minimum2701
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T16:13:16.814077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2701
5-th percentile2710
Q12730
median2754
Q32830
95-th percentile2865
Maximum2880
Range179
Interquartile range (IQR)100

Descriptive statistics

Standard deviation54.10615
Coefficient of variation (CV)0.01948883
Kurtosis-1.3572784
Mean2776.2647
Median Absolute Deviation (MAD)36
Skewness0.40409516
Sum943930
Variance2927.4754
MonotonicityNot monotonic
2024-05-11T16:13:16.970830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2730 64
 
13.7%
2845 13
 
2.8%
2721 10
 
2.1%
2751 9
 
1.9%
2709 8
 
1.7%
2804 8
 
1.7%
2829 7
 
1.5%
2752 6
 
1.3%
2715 6
 
1.3%
2831 6
 
1.3%
Other values (99) 203
43.4%
(Missing) 128
27.4%
ValueCountFrequency (%)
2701 1
 
0.2%
2702 3
 
0.6%
2705 1
 
0.2%
2709 8
1.7%
2710 5
1.1%
2711 2
 
0.4%
2713 3
 
0.6%
2715 6
1.3%
2717 3
 
0.6%
2718 2
 
0.4%
ValueCountFrequency (%)
2880 5
1.1%
2879 1
 
0.2%
2878 1
 
0.2%
2876 1
 
0.2%
2873 1
 
0.2%
2872 2
 
0.4%
2871 1
 
0.2%
2869 1
 
0.2%
2866 2
 
0.4%
2865 4
0.9%

사업장명
Text

Distinct421
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T16:13:17.230766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length7.8653846
Min length2

Characters and Unicode

Total characters3681
Distinct characters430
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

Unique390 ?
Unique (%)83.3%

Sample

1st row나폴레온
2nd row파리바게뜨 정릉점
3rd row라크렘
4th row모나리자과자점
5th row케익하우스 밀레
ValueCountFrequency (%)
파리바게뜨 18
 
2.8%
뚜레쥬르 12
 
1.9%
베이커리 8
 
1.3%
미아점 7
 
1.1%
달콤한위로 7
 
1.1%
씨유 5
 
0.8%
신라명과 5
 
0.8%
파리바게트 5
 
0.8%
던킨도너츠 4
 
0.6%
길음뉴타운점 4
 
0.6%
Other values (485) 559
88.2%
2024-05-11T16:13:17.636582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 172
 
4.7%
166
 
4.5%
점 141
 
3.8%
이 119
 
3.2%
( 85
 
2.3%
) 85
 
2.3%
베 81
 
2.2%
커 69
 
1.9%
빵 68
 
1.8%
레 63
 
1.7%
Other values (420) 2632
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3033
82.4%
Lowercase Letter 210
 
5.7%
Space Separator 166
 
4.5%
Open Punctuation 85
 
2.3%
Close Punctuation 85
 
2.3%
Uppercase Letter 84
 
2.3%
Decimal Number 10
 
0.3%
Other Punctuation 7
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 172
 
5.7%
점 141
 
4.6%
이 119
 
3.9%
베 81
 
2.7%
커 69
 
2.3%
빵 68
 
2.2%
레 63
 
2.1%
파 54
 
1.8%
바 50
 
1.6%
게 47
 
1.5%
Other values (364) 2169
71.5%
Lowercase Letter
ValueCountFrequency (%)
e 31
14.8%
o 26
12.4%
i 20
9.5%
a 16
 
7.6%
n 15
 
7.1%
r 14
 
6.7%
l 11
 
5.2%
c 10
 
4.8%
g 10
 
4.8%
f 8
 
3.8%
Other values (12) 49
23.3%
Uppercase Letter
ValueCountFrequency (%)
B 10
11.9%
A 8
 
9.5%
O 7
 
8.3%
P 7
 
8.3%
T 6
 
7.1%
D 6
 
7.1%
S 6
 
7.1%
R 4
 
4.8%
E 4
 
4.8%
L 4
 
4.8%
Other values (11) 22
26.2%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
5 2
20.0%
1 2
20.0%
0 1
 
10.0%
9 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
& 3
42.9%
? 2
28.6%
' 1
 
14.3%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
166
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3033
82.4%
Common 354
 
9.6%
Latin 294
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 172
 
5.7%
점 141
 
4.6%
이 119
 
3.9%
베 81
 
2.7%
커 69
 
2.3%
빵 68
 
2.2%
레 63
 
2.1%
파 54
 
1.8%
바 50
 
1.6%
게 47
 
1.5%
Other values (364) 2169
71.5%
Latin
ValueCountFrequency (%)
e 31
 
10.5%
o 26
 
8.8%
i 20
 
6.8%
a 16
 
5.4%
n 15
 
5.1%
r 14
 
4.8%
l 11
 
3.7%
B 10
 
3.4%
c 10
 
3.4%
g 10
 
3.4%
Other values (33) 131
44.6%
Common
ValueCountFrequency (%)
166
46.9%
( 85
24.0%
) 85
24.0%
2 4
 
1.1%
& 3
 
0.8%
5 2
 
0.6%
? 2
 
0.6%
1 2
 
0.6%
' 1
 
0.3%
- 1
 
0.3%
Other values (3) 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3033
82.4%
ASCII 648
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 172
 
5.7%
점 141
 
4.6%
이 119
 
3.9%
베 81
 
2.7%
커 69
 
2.3%
빵 68
 
2.2%
레 63
 
2.1%
파 54
 
1.8%
바 50
 
1.6%
게 47
 
1.5%
Other values (364) 2169
71.5%
ASCII
ValueCountFrequency (%)
166
25.6%
( 85
13.1%
) 85
13.1%
e 31
 
4.8%
o 26
 
4.0%
i 20
 
3.1%
a 16
 
2.5%
n 15
 
2.3%
r 14
 
2.2%
l 11
 
1.7%
Other values (46) 179
27.6%

최종수정일자
Date

Distinct435
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2001-12-13 00:00:00
Maximum2024-04-28 04:15:09
2024-05-11T16:13:17.776133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:13:17.953963image/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 size3.8 KiB
I
318 
U
150 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 318
67.9%
U 150
32.1%

Length

2024-05-11T16:13:18.124546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:18.236663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 318
67.9%
u 150
32.1%

데이터갱신일자
Date

Distinct162
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:04:00
2024-05-11T16:13:18.351308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:13:18.491984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
제과점영업
468 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 468
100.0%

Length

2024-05-11T16:13:18.626889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:18.712714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 468
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct300
Distinct (%)66.2%
Missing15
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean202329.91
Minimum198921.45
Maximum205996.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T16:13:18.824537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198921.45
5-th percentile200524.39
Q1201412.46
median202466.8
Q3202955.36
95-th percentile204840.28
Maximum205996.72
Range7075.2723
Interquartile range (IQR)1542.896

Descriptive statistics

Standard deviation1308.7417
Coefficient of variation (CV)0.006468355
Kurtosis-0.14708302
Mean202329.91
Median Absolute Deviation (MAD)873.80976
Skewness0.45233787
Sum91655449
Variance1712804.8
MonotonicityNot monotonic
2024-05-11T16:13:18.982128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202466.801104742 55
 
11.8%
202466.801084521 16
 
3.4%
202555.30089577 12
 
2.6%
200841.726990037 8
 
1.7%
201648.204071174 7
 
1.5%
202667.468802014 6
 
1.3%
201592.991324089 5
 
1.1%
202789.692329185 4
 
0.9%
203318.127254872 4
 
0.9%
201358.893989884 3
 
0.6%
Other values (290) 333
71.2%
(Missing) 15
 
3.2%
ValueCountFrequency (%)
198921.445609008 1
0.2%
199589.675776144 1
0.2%
199641.375343857 1
0.2%
199865.361967559 1
0.2%
199868.750279855 2
0.4%
199888.694291511 1
0.2%
199894.977167748 1
0.2%
199949.578425859 1
0.2%
199955.212381036 1
0.2%
200133.922389169 1
0.2%
ValueCountFrequency (%)
205996.717928956 1
0.2%
205665.070767038 1
0.2%
205662.098794841 1
0.2%
205580.504678403 1
0.2%
205507.445473959 1
0.2%
205450.006120967 1
0.2%
205420.298784738 1
0.2%
205418.575037784 1
0.2%
205308.217055574 2
0.4%
205305.770050907 2
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct300
Distinct (%)66.2%
Missing15
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean455617.73
Minimum453058.7
Maximum457844.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T16:13:19.128736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453058.7
5-th percentile453784.87
Q1454721.51
median455997.21
Q3456244.72
95-th percentile457160.17
Maximum457844.35
Range4785.6524
Interquartile range (IQR)1523.2139

Descriptive statistics

Standard deviation1037.6784
Coefficient of variation (CV)0.0022775197
Kurtosis-0.68579143
Mean455617.73
Median Absolute Deviation (MAD)505.86114
Skewness-0.46113496
Sum2.0639483 × 108
Variance1076776.4
MonotonicityNot monotonic
2024-05-11T16:13:19.272544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456227.571665528 55
 
11.8%
456227.571720914 16
 
3.4%
456503.066230481 12
 
2.6%
454721.505180141 8
 
1.7%
455717.855906877 7
 
1.5%
455858.920803881 6
 
1.3%
456382.966061703 5
 
1.1%
454049.551940162 4
 
0.9%
456078.982123486 4
 
0.9%
454439.085102224 3
 
0.6%
Other values (290) 333
71.2%
(Missing) 15
 
3.2%
ValueCountFrequency (%)
453058.695646493 1
0.2%
453114.709951076 1
0.2%
453162.376311852 1
0.2%
453287.155232581 1
0.2%
453369.485060555 1
0.2%
453384.726106159 1
0.2%
453421.714752101 1
0.2%
453548.631152749 1
0.2%
453558.860562699 1
0.2%
453616.163591944 1
0.2%
ValueCountFrequency (%)
457844.348010616 2
0.4%
457664.961911112 1
0.2%
457579.21641655 1
0.2%
457486.12146569 1
0.2%
457442.584177337 1
0.2%
457437.789670966 1
0.2%
457426.160610241 1
0.2%
457424.675484944 2
0.4%
457415.285262352 1
0.2%
457387.820430259 1
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
제과점영업
379 
<NA>
89 

Length

Max length5
Median length5
Mean length4.8098291
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 379
81.0%
<NA> 89
 
19.0%

Length

2024-05-11T16:13:19.406099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:19.500144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 379
81.0%
na 89
 
19.0%

남성종사자수
Categorical

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
289 
0
128 
1
39 
2
 
9
3
 
2

Length

Max length4
Median length4
Mean length2.8525641
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 289
61.8%
0 128
27.4%
1 39
 
8.3%
2 9
 
1.9%
3 2
 
0.4%
4 1
 
0.2%

Length

2024-05-11T16:13:19.598784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:19.730882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
61.8%
0 128
27.4%
1 39
 
8.3%
2 9
 
1.9%
3 2
 
0.4%
4 1
 
0.2%

여성종사자수
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
289 
0
144 
1
32 
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length2.8525641
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 289
61.8%
0 144
30.8%
1 32
 
6.8%
2 2
 
0.4%
3 1
 
0.2%

Length

2024-05-11T16:13:19.850517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:19.965466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 289
61.8%
0 144
30.8%
1 32
 
6.8%
2 2
 
0.4%
3 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
372 
주택가주변
59 
기타
 
28
아파트지역
 
7
학교정화(절대)
 
1

Length

Max length8
Median length4
Mean length4.0384615
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 372
79.5%
주택가주변 59
 
12.6%
기타 28
 
6.0%
아파트지역 7
 
1.5%
학교정화(절대) 1
 
0.2%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-11T16:13:20.095115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:20.239254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 372
79.5%
주택가주변 59
 
12.6%
기타 28
 
6.0%
아파트지역 7
 
1.5%
학교정화(절대 1
 
0.2%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
374 
기타
58 
자율
 
28
우수
 
4
을
 
2

Length

Max length4
Median length4
Mean length3.5940171
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 374
79.9%
기타 58
 
12.4%
자율 28
 
6.0%
우수 4
 
0.9%
을 2
 
0.4%
관리 2
 
0.4%

Length

2024-05-11T16:13:20.349854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:20.456623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 374
79.9%
기타 58
 
12.4%
자율 28
 
6.0%
우수 4
 
0.9%
을 2
 
0.4%
관리 2
 
0.4%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
235 
상수도전용
233 

Length

Max length5
Median length4
Mean length4.4978632
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 235
50.2%
상수도전용 233
49.8%

Length

2024-05-11T16:13:20.566959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:20.653541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
50.2%
상수도전용 233
49.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:21.042394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:21.147176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:21.243511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:21.341398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:21.448425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:21.557164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:21.670755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:21.771423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:21.866024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:21.956932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:22.044795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:22.147823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
448 
0
 
20

Length

Max length4
Median length4
Mean length3.8717949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
95.7%
0 20
 
4.3%

Length

2024-05-11T16:13:22.255300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:13:22.351985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 448
95.7%
0 20
 
4.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing89
Missing (%)19.0%
Memory size1.0 KiB
False
377 
True
 
2
(Missing)
89 
ValueCountFrequency (%)
False 377
80.6%
True 2
 
0.4%
(Missing) 89
 
19.0%
2024-05-11T16:13:22.421320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct274
Distinct (%)72.3%
Missing89
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean45.169631
Minimum0
Maximum921.94
Zeros8
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T16:13:22.515054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.762
Q117.15
median32.88
Q355.44
95-th percentile99
Maximum921.94
Range921.94
Interquartile range (IQR)38.29

Descriptive statistics

Standard deviation71.592304
Coefficient of variation (CV)1.5849654
Kurtosis81.587633
Mean45.169631
Median Absolute Deviation (MAD)17.88
Skewness8.1269456
Sum17119.29
Variance5125.458
MonotonicityNot monotonic
2024-05-11T16:13:22.632466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 12
 
2.6%
26.4 10
 
2.1%
9.9 9
 
1.9%
0.0 8
 
1.7%
29.7 7
 
1.5%
6.6 7
 
1.5%
10.0 6
 
1.3%
23.1 4
 
0.9%
66.0 4
 
0.9%
27.0 3
 
0.6%
Other values (264) 309
66.0%
(Missing) 89
 
19.0%
ValueCountFrequency (%)
0.0 8
1.7%
1.5 1
 
0.2%
2.25 1
 
0.2%
3.0 2
 
0.4%
3.2 1
 
0.2%
3.3 2
 
0.4%
4.0 3
 
0.6%
4.6 1
 
0.2%
4.78 1
 
0.2%
4.95 3
 
0.6%
ValueCountFrequency (%)
921.94 1
0.2%
626.73 1
0.2%
539.97 2
0.4%
221.1 1
0.2%
148.73 1
0.2%
139.98 1
0.2%
134.79 1
0.2%
132.0 1
0.2%
125.84 1
0.2%
121.56 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing468
Missing (%)100.0%
Memory size4.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-121-1969-0869119690415<NA>3폐업2폐업20071016<NA><NA><NA>7427421626.73136041서울특별시 성북구 삼선동1가 13번지 지19 성북천복개지상<NA><NA>나폴레온2001-12-13 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업00주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N626.73<NA><NA><NA>
130700003070000-121-1970-0809319700418<NA>1영업/정상1영업<NA><NA><NA><NA>020914691390.46136877서울특별시 성북구 정릉동 403-9서울특별시 성북구 보국문로 40-3 (정릉동)2717파리바게뜨 정릉점2021-08-10 11:23:56U2021-08-12 02:40:00.0제과점영업200829.156091456231.922957제과점영업01주택가주변자율상수도전용00000<NA>00N90.46<NA><NA><NA>
230700003070000-121-1976-0809919761229<NA>3폐업2폐업20120105<NA><NA><NA>020918118356.77136836서울특별시 성북구 장위동 231-590번지<NA><NA>라크렘2005-11-10 00:00:00I2018-08-31 23:59:59.0제과점영업203527.671631456874.247386제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.77<NA><NA><NA>
330700003070000-121-1977-0808719770310<NA>3폐업2폐업20070821<NA><NA><NA>02 915473244.96136837서울특별시 성북구 장위동 233-264번지<NA><NA>모나리자과자점2002-01-11 00:00:00I2018-08-31 23:59:59.0제과점영업203749.396678456830.017353제과점영업10주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N44.96<NA><NA><NA>
430700003070000-121-1978-0814119781202<NA>3폐업2폐업20150327<NA><NA><NA>02 917944342.24136140서울특별시 성북구 장위동 64-8번지 ,9,10서울특별시 성북구 돌곶이로 105 (장위동,,9,10)2771케익하우스 밀레2005-08-31 00:00:00I2018-08-31 23:59:59.0제과점영업204812.657781456654.871159제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.24<NA><NA><NA>
530700003070000-121-1979-0797319790611<NA>3폐업2폐업20160520<NA><NA><NA>020915958233.59136140서울특별시 성북구 장위동 151-1번지서울특별시 성북구 장월로 168 (장위동)<NA>부산뉴욕2002-01-11 00:00:00I2018-08-31 23:59:59.0제과점영업204621.275126457415.285262제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.59<NA><NA><NA>
630700003070000-121-1979-0806319790112<NA>3폐업2폐업20061121<NA><NA><NA>020965923345.2136816서울특별시 성북구 석관동 124-16번지<NA><NA>우상춘과자점2002-01-11 00:00:00I2018-08-31 23:59:59.0제과점영업205418.575038456527.550971제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.2<NA><NA><NA>
730700003070000-121-1979-0810019791010<NA>3폐업2폐업20060119<NA><NA><NA>020918746527.0136827서울특별시 성북구 장위동 70-25번지<NA><NA>빵굽는 고을로2003-07-03 00:00:00I2018-08-31 23:59:59.0제과점영업204872.883228456812.420042제과점영업01주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.0<NA><NA><NA>
830700003070000-121-1980-0796219800827<NA>3폐업2폐업20060412<NA><NA><NA>02 912907142.43136865서울특별시 성북구 하월곡동 17-7번지<NA><NA>크라운베이커리2002-01-11 00:00:00I2018-08-31 23:59:59.0제과점영업203712.588634455712.035845제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.43<NA><NA><NA>
930700003070000-121-1980-080321980-05-16<NA>3폐업2폐업2024-04-18<NA><NA><NA>020915003159.1136-837서울특별시 성북구 장위동 233-438서울특별시 성북구 장위로 106 (장위동)2746또래명과2024-04-18 11:12:19U2023-12-03 22:00:00.0제과점영업204207.137484456800.711636<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
45830700003070000-121-2023-000112023-11-13<NA>3폐업2폐업2023-11-15<NA><NA><NA><NA>12.0136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730비비드크로넛 현대백화점미아점2023-11-15 11:22:34U2022-10-31 23:07:00.0제과점영업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45930700003070000-121-2023-000122023-11-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.11136-821서울특별시 성북구 성북동 113-6서울특별시 성북구 성북로19길 9, 지하1층 (성북동)2879밀곳간(누룩과 소금꽃)2023-11-14 13:19:16I2022-10-31 23:07:00.0제과점영업199641.375344454481.918921<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46030700003070000-121-2023-000132023-11-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.98136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730하이제씨2023-11-21 15:31:56I2022-10-31 22:03:00.0제과점영업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46130700003070000-121-2023-000142023-12-12<NA>3폐업2폐업2023-12-25<NA><NA><NA><NA>3.3136-130서울특별시 성북구 하월곡동 230 동일하이빌뉴시티서울특별시 성북구 종암로 167, 지하2층 (하월곡동, 동일하이빌뉴시티)2734이베이커리 하월곡점2023-12-26 04:15:09U2022-11-01 22:08:00.0제과점영업202667.468802455858.920804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46230700003070000-121-2024-000012024-01-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.2136-054서울특별시 성북구 동선동4가 11서울특별시 성북구 아리랑로 6, 1층 (동선동4가)2829아리랑빵집2024-01-04 15:23:12I2023-12-01 00:06:00.0제과점영업201393.320824454558.364064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46330700003070000-121-2024-000022024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.0136-849서울특별시 성북구 정릉동 266-94서울특별시 성북구 보국문로16길 60 (정릉동)2717filling coffee2024-02-06 13:42:51I2023-12-02 00:08:00.0제과점영업200821.456936456677.427167<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46430700003070000-121-2024-000032024-02-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.28136-042서울특별시 성북구 삼선동2가 44-2서울특별시 성북구 삼선교로 28, 지상1층 (삼선동2가)2864베이크 하우스2024-02-14 10:49:59I2023-12-01 23:06:00.0제과점영업200716.145505453958.049209<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46530700003070000-121-2024-000042024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.5136-865서울특별시 성북구 하월곡동 18-4서울특별시 성북구 장월로1길 111, 지상1층 102호 (하월곡동)2752샤롱샤롱2024-03-04 14:25:36I2023-12-03 00:06:00.0제과점영업203727.187734455773.025465<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46630700003070000-121-2024-000052024-04-01<NA>3폐업2폐업2024-04-25<NA><NA><NA><NA>3.3136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730나폴레옹과자점2024-04-26 04:15:10U2023-12-03 22:08:00.0제과점영업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46730700003070000-121-2024-000062024-04-25<NA>3폐업2폐업2024-04-27<NA><NA><NA><NA>3.3136-849서울특별시 성북구 정릉동 286-6서울특별시 성북구 보국문로18길 1, 한양새마을금고 보국문지점 일대 (정릉동)2711filling coffee2024-04-28 04:15:09U2023-12-03 21:00:00.0제과점영업200718.117705456570.84335<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>