Overview

Dataset statistics

Number of variables44
Number of observations425
Missing cells4450
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory156.6 KiB
Average record size in memory377.3 B

Variable types

Categorical19
Text6
DateTime4
Unsupported8
Numeric6
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18421/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
등급구분명 is highly imbalanced (55.6%)Imbalance
총인원 is highly imbalanced (63.2%)Imbalance
본사종업원수 is highly imbalanced (63.2%)Imbalance
공장사무직종업원수 is highly imbalanced (63.2%)Imbalance
공장판매직종업원수 is highly imbalanced (63.2%)Imbalance
공장생산직종업원수 is highly imbalanced (63.2%)Imbalance
보증액 is highly imbalanced (63.2%)Imbalance
월세액 is highly imbalanced (63.2%)Imbalance
인허가취소일자 has 425 (100.0%) missing valuesMissing
폐업일자 has 131 (30.8%) missing valuesMissing
휴업시작일자 has 425 (100.0%) missing valuesMissing
휴업종료일자 has 425 (100.0%) missing valuesMissing
재개업일자 has 425 (100.0%) missing valuesMissing
전화번호 has 215 (50.6%) missing valuesMissing
소재지면적 has 7 (1.6%) missing valuesMissing
소재지우편번호 has 7 (1.6%) missing valuesMissing
지번주소 has 6 (1.4%) missing valuesMissing
도로명주소 has 113 (26.6%) missing valuesMissing
도로명우편번호 has 117 (27.5%) missing valuesMissing
좌표정보(X) has 10 (2.4%) missing valuesMissing
좌표정보(Y) has 10 (2.4%) missing valuesMissing
남성종사자수 has 264 (62.1%) missing valuesMissing
건물소유구분명 has 425 (100.0%) missing valuesMissing
다중이용업소여부 has 85 (20.0%) missing valuesMissing
시설총규모 has 85 (20.0%) missing valuesMissing
전통업소지정번호 has 425 (100.0%) missing valuesMissing
전통업소주된음식 has 425 (100.0%) missing valuesMissing
홈페이지 has 425 (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
남성종사자수 has 96 (22.6%) zerosZeros
시설총규모 has 6 (1.4%) zerosZeros

Reproduction

Analysis started2024-05-11 00:31:13.583757
Analysis finished2024-05-11 00:31:15.370460
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
3190000
425 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 425
100.0%

Length

2024-05-11T00:31:15.564880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:15.881483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 425
100.0%

관리번호
Text

UNIQUE 

Distinct425
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-05-11T00:31:16.286234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9350
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

Unique425 ?
Unique (%)100.0%

Sample

1st row3190000-121-1970-01555
2nd row3190000-121-1972-07055
3rd row3190000-121-1973-01554
4th row3190000-121-1975-01491
5th row3190000-121-1979-01516
ValueCountFrequency (%)
3190000-121-1970-01555 1
 
0.2%
3190000-121-2017-00012 1
 
0.2%
3190000-121-2017-00010 1
 
0.2%
3190000-121-2017-00009 1
 
0.2%
3190000-121-2017-00008 1
 
0.2%
3190000-121-2017-00007 1
 
0.2%
3190000-121-2017-00006 1
 
0.2%
3190000-121-2017-00005 1
 
0.2%
3190000-121-2017-00004 1
 
0.2%
3190000-121-2017-00003 1
 
0.2%
Other values (415) 415
97.6%
2024-05-11T00:31:17.151026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3566
38.1%
1 1774
19.0%
- 1275
 
13.6%
2 987
 
10.6%
9 640
 
6.8%
3 538
 
5.8%
7 129
 
1.4%
4 117
 
1.3%
8 116
 
1.2%
6 105
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8075
86.4%
Dash Punctuation 1275
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3566
44.2%
1 1774
22.0%
2 987
 
12.2%
9 640
 
7.9%
3 538
 
6.7%
7 129
 
1.6%
4 117
 
1.4%
8 116
 
1.4%
6 105
 
1.3%
5 103
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1275
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3566
38.1%
1 1774
19.0%
- 1275
 
13.6%
2 987
 
10.6%
9 640
 
6.8%
3 538
 
5.8%
7 129
 
1.4%
4 117
 
1.3%
8 116
 
1.2%
6 105
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3566
38.1%
1 1774
19.0%
- 1275
 
13.6%
2 987
 
10.6%
9 640
 
6.8%
3 538
 
5.8%
7 129
 
1.4%
4 117
 
1.3%
8 116
 
1.2%
6 105
 
1.1%

인허가일자
Date

Distinct413
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum1970-07-10 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T00:31:17.558334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:31:18.046848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
3
294 
1
131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 294
69.2%
1 131
30.8%

Length

2024-05-11T00:31:18.354477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:18.672127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 294
69.2%
1 131
30.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
폐업
294 
영업/정상
131 

Length

Max length5
Median length2
Mean length2.9247059
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 294
69.2%
영업/정상 131
30.8%

Length

2024-05-11T00:31:19.082967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:19.428625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 294
69.2%
영업/정상 131
30.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2
294 
1
131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 294
69.2%
1 131
30.8%

Length

2024-05-11T00:31:19.761679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:20.090219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 294
69.2%
1 131
30.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
폐업
294 
영업
131 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 294
69.2%
영업 131
30.8%

Length

2024-05-11T00:31:20.484485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:20.805893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 294
69.2%
영업 131
30.8%

폐업일자
Date

MISSING 

Distinct264
Distinct (%)89.8%
Missing131
Missing (%)30.8%
Memory size3.4 KiB
Minimum2003-09-30 00:00:00
Maximum2024-04-16 00:00:00
2024-05-11T00:31:21.144303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:31:21.549448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

전화번호
Text

MISSING 

Distinct206
Distinct (%)98.1%
Missing215
Missing (%)50.6%
Memory size3.4 KiB
2024-05-11T00:31:22.207534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.157143
Min length2

Characters and Unicode

Total characters2133
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

Unique202 ?
Unique (%)96.2%

Sample

1st row0208136550
2nd row0208139387
3rd row02 8159081
4th row0208142575
5th row02 8224634
ValueCountFrequency (%)
02 144
37.1%
070 4
 
1.0%
2158 2
 
0.5%
8210480 2
 
0.5%
825 2
 
0.5%
591 2
 
0.5%
4245 2
 
0.5%
823 2
 
0.5%
812 2
 
0.5%
34711988 2
 
0.5%
Other values (219) 224
57.7%
2024-05-11T00:31:23.239686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 372
17.4%
0 350
16.4%
8 248
11.6%
216
10.1%
5 180
8.4%
1 156
7.3%
3 139
 
6.5%
4 136
 
6.4%
7 123
 
5.8%
6 113
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1917
89.9%
Space Separator 216
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 372
19.4%
0 350
18.3%
8 248
12.9%
5 180
9.4%
1 156
8.1%
3 139
 
7.3%
4 136
 
7.1%
7 123
 
6.4%
6 113
 
5.9%
9 100
 
5.2%
Space Separator
ValueCountFrequency (%)
216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2133
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 372
17.4%
0 350
16.4%
8 248
11.6%
216
10.1%
5 180
8.4%
1 156
7.3%
3 139
 
6.5%
4 136
 
6.4%
7 123
 
5.8%
6 113
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 372
17.4%
0 350
16.4%
8 248
11.6%
216
10.1%
5 180
8.4%
1 156
7.3%
3 139
 
6.5%
4 136
 
6.4%
7 123
 
5.8%
6 113
 
5.3%

소재지면적
Real number (ℝ)

MISSING 

Distinct353
Distinct (%)84.4%
Missing7
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean43.174665
Minimum2
Maximum525.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:23.769516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile11.5365
Q123.1
median34.33
Q353.98
95-th percentile95.4
Maximum525.28
Range523.28
Interquartile range (IQR)30.88

Descriptive statistics

Standard deviation36.78672
Coefficient of variation (CV)0.85204412
Kurtosis71.744729
Mean43.174665
Median Absolute Deviation (MAD)13.45
Skewness6.204767
Sum18047.01
Variance1353.2627
MonotonicityNot monotonic
2024-05-11T00:31:24.373576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.0 6
 
1.4%
33.0 5
 
1.2%
30.0 5
 
1.2%
20.0 4
 
0.9%
10.0 4
 
0.9%
26.4 3
 
0.7%
3.3 3
 
0.7%
45.0 3
 
0.7%
26.0 3
 
0.7%
23.1 3
 
0.7%
Other values (343) 379
89.2%
(Missing) 7
 
1.6%
ValueCountFrequency (%)
2.0 1
 
0.2%
3.0 1
 
0.2%
3.3 3
0.7%
5.96 1
 
0.2%
7.2 1
 
0.2%
7.3 1
 
0.2%
8.55 1
 
0.2%
9.1 1
 
0.2%
9.68 1
 
0.2%
9.75 1
 
0.2%
ValueCountFrequency (%)
525.28 1
0.2%
227.6 1
0.2%
171.0 1
0.2%
151.73 1
0.2%
149.94 1
0.2%
129.22 1
0.2%
129.14 2
0.5%
125.4 1
0.2%
115.29 1
0.2%
109.08 1
0.2%

소재지우편번호
Text

MISSING 

Distinct102
Distinct (%)24.4%
Missing7
Missing (%)1.6%
Memory size3.4 KiB
2024-05-11T00:31:25.040190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1363636
Min length6

Characters and Unicode

Total characters2565
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

Unique34 ?
Unique (%)8.1%

Sample

1st row156860
2nd row156806
3rd row156861
4th row156847
5th row156844
ValueCountFrequency (%)
156030 37
 
8.9%
156815 18
 
4.3%
156816 14
 
3.3%
156826 12
 
2.9%
156800 12
 
2.9%
156801 12
 
2.9%
156839 11
 
2.6%
156090 11
 
2.6%
156811 11
 
2.6%
156861 10
 
2.4%
Other values (92) 270
64.6%
2024-05-11T00:31:26.520601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 565
22.0%
5 491
19.1%
6 478
18.6%
8 358
14.0%
0 242
9.4%
3 127
 
5.0%
2 77
 
3.0%
7 67
 
2.6%
- 57
 
2.2%
4 56
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2508
97.8%
Dash Punctuation 57
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 565
22.5%
5 491
19.6%
6 478
19.1%
8 358
14.3%
0 242
9.6%
3 127
 
5.1%
2 77
 
3.1%
7 67
 
2.7%
4 56
 
2.2%
9 47
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2565
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 565
22.0%
5 491
19.1%
6 478
18.6%
8 358
14.0%
0 242
9.4%
3 127
 
5.0%
2 77
 
3.0%
7 67
 
2.6%
- 57
 
2.2%
4 56
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 565
22.0%
5 491
19.1%
6 478
18.6%
8 358
14.0%
0 242
9.4%
3 127
 
5.0%
2 77
 
3.0%
7 67
 
2.6%
- 57
 
2.2%
4 56
 
2.2%

지번주소
Text

MISSING 

Distinct398
Distinct (%)95.0%
Missing6
Missing (%)1.4%
Memory size3.4 KiB
2024-05-11T00:31:27.376039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length24.782816
Min length17

Characters and Unicode

Total characters10384
Distinct characters189
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique378 ?
Unique (%)90.2%

Sample

1st row서울특별시 동작구 흑석동 102-30
2nd row서울특별시 동작구 노량진동 308-4번지
3rd row서울특별시 동작구 흑석동 223-1번지
4th row서울특별시 동작구 신대방동 348-3번지
5th row서울특별시 동작구 상도동 259-16번지
ValueCountFrequency (%)
서울특별시 418
21.7%
동작구 418
21.7%
사당동 128
 
6.6%
상도동 110
 
5.7%
노량진동 48
 
2.5%
흑석동 43
 
2.2%
신대방동 37
 
1.9%
1층 34
 
1.8%
대방동 27
 
1.4%
상도1동 12
 
0.6%
Other values (531) 654
33.9%
2024-05-11T00:31:29.184065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1834
17.7%
동 863
 
8.3%
1 483
 
4.7%
작 425
 
4.1%
구 424
 
4.1%
울 418
 
4.0%
서 418
 
4.0%
시 418
 
4.0%
별 418
 
4.0%
특 418
 
4.0%
Other values (179) 4265
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6032
58.1%
Decimal Number 2074
 
20.0%
Space Separator 1834
 
17.7%
Dash Punctuation 350
 
3.4%
Open Punctuation 30
 
0.3%
Close Punctuation 30
 
0.3%
Other Punctuation 18
 
0.2%
Uppercase Letter 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 863
14.3%
작 425
 
7.0%
구 424
 
7.0%
울 418
 
6.9%
서 418
 
6.9%
시 418
 
6.9%
별 418
 
6.9%
특 418
 
6.9%
지 282
 
4.7%
번 248
 
4.1%
Other values (153) 1700
28.2%
Decimal Number
ValueCountFrequency (%)
1 483
23.3%
2 284
13.7%
3 272
13.1%
0 217
10.5%
4 192
 
9.3%
6 155
 
7.5%
5 140
 
6.8%
7 131
 
6.3%
9 104
 
5.0%
8 96
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
37.5%
A 4
25.0%
D 2
 
12.5%
C 1
 
6.2%
S 1
 
6.2%
R 1
 
6.2%
G 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 14
77.8%
/ 1
 
5.6%
@ 1
 
5.6%
& 1
 
5.6%
? 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 350
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6032
58.1%
Common 4336
41.8%
Latin 16
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 863
14.3%
작 425
 
7.0%
구 424
 
7.0%
울 418
 
6.9%
서 418
 
6.9%
시 418
 
6.9%
별 418
 
6.9%
특 418
 
6.9%
지 282
 
4.7%
번 248
 
4.1%
Other values (153) 1700
28.2%
Common
ValueCountFrequency (%)
1834
42.3%
1 483
 
11.1%
- 350
 
8.1%
2 284
 
6.5%
3 272
 
6.3%
0 217
 
5.0%
4 192
 
4.4%
6 155
 
3.6%
5 140
 
3.2%
7 131
 
3.0%
Other values (9) 278
 
6.4%
Latin
ValueCountFrequency (%)
B 6
37.5%
A 4
25.0%
D 2
 
12.5%
C 1
 
6.2%
S 1
 
6.2%
R 1
 
6.2%
G 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6032
58.1%
ASCII 4352
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1834
42.1%
1 483
 
11.1%
- 350
 
8.0%
2 284
 
6.5%
3 272
 
6.2%
0 217
 
5.0%
4 192
 
4.4%
6 155
 
3.6%
5 140
 
3.2%
7 131
 
3.0%
Other values (16) 294
 
6.8%
Hangul
ValueCountFrequency (%)
동 863
14.3%
작 425
 
7.0%
구 424
 
7.0%
울 418
 
6.9%
서 418
 
6.9%
시 418
 
6.9%
별 418
 
6.9%
특 418
 
6.9%
지 282
 
4.7%
번 248
 
4.1%
Other values (153) 1700
28.2%

도로명주소
Text

MISSING 

Distinct307
Distinct (%)98.4%
Missing113
Missing (%)26.6%
Memory size3.4 KiB
2024-05-11T00:31:29.904845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length32.612179
Min length22

Characters and Unicode

Total characters10175
Distinct characters195
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

Unique302 ?
Unique (%)96.8%

Sample

1st row서울특별시 동작구 서달로13길 5-30 (흑석동)
2nd row서울특별시 동작구 국사봉1길 4 (상도동)
3rd row서울특별시 동작구 사당로23길 177 (사당동)
4th row서울특별시 동작구 사당로16길 18 (사당동)
5th row서울특별시 동작구 여의대방로 250, 상가동 105호 (대방동)
ValueCountFrequency (%)
서울특별시 312
 
15.8%
동작구 312
 
15.8%
1층 113
 
5.7%
사당동 89
 
4.5%
상도동 72
 
3.6%
상도로 32
 
1.6%
노량진동 30
 
1.5%
흑석동 25
 
1.3%
신대방동 22
 
1.1%
지하 20
 
1.0%
Other values (451) 946
47.9%
2024-05-11T00:31:31.340413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1662
 
16.3%
동 723
 
7.1%
1 534
 
5.2%
작 375
 
3.7%
) 335
 
3.3%
( 335
 
3.3%
서 321
 
3.2%
구 318
 
3.1%
시 314
 
3.1%
별 312
 
3.1%
Other values (185) 4946
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5836
57.4%
Space Separator 1662
 
16.3%
Decimal Number 1633
 
16.0%
Close Punctuation 335
 
3.3%
Open Punctuation 335
 
3.3%
Other Punctuation 303
 
3.0%
Dash Punctuation 45
 
0.4%
Uppercase Letter 25
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 723
 
12.4%
작 375
 
6.4%
서 321
 
5.5%
구 318
 
5.4%
시 314
 
5.4%
별 312
 
5.3%
울 312
 
5.3%
특 312
 
5.3%
로 292
 
5.0%
상 198
 
3.4%
Other values (161) 2359
40.4%
Decimal Number
ValueCountFrequency (%)
1 534
32.7%
2 252
15.4%
0 174
 
10.7%
3 156
 
9.6%
4 100
 
6.1%
6 98
 
6.0%
7 94
 
5.8%
5 80
 
4.9%
9 74
 
4.5%
8 71
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 19
76.0%
A 2
 
8.0%
T 1
 
4.0%
P 1
 
4.0%
C 1
 
4.0%
D 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 301
99.3%
@ 1
 
0.3%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1662
100.0%
Close Punctuation
ValueCountFrequency (%)
) 335
100.0%
Open Punctuation
ValueCountFrequency (%)
( 335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5836
57.4%
Common 4313
42.4%
Latin 26
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 723
 
12.4%
작 375
 
6.4%
서 321
 
5.5%
구 318
 
5.4%
시 314
 
5.4%
별 312
 
5.3%
울 312
 
5.3%
특 312
 
5.3%
로 292
 
5.0%
상 198
 
3.4%
Other values (161) 2359
40.4%
Common
ValueCountFrequency (%)
1662
38.5%
1 534
 
12.4%
) 335
 
7.8%
( 335
 
7.8%
, 301
 
7.0%
2 252
 
5.8%
0 174
 
4.0%
3 156
 
3.6%
4 100
 
2.3%
6 98
 
2.3%
Other values (7) 366
 
8.5%
Latin
ValueCountFrequency (%)
B 19
73.1%
A 2
 
7.7%
e 1
 
3.8%
T 1
 
3.8%
P 1
 
3.8%
C 1
 
3.8%
D 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5836
57.4%
ASCII 4339
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1662
38.3%
1 534
 
12.3%
) 335
 
7.7%
( 335
 
7.7%
, 301
 
6.9%
2 252
 
5.8%
0 174
 
4.0%
3 156
 
3.6%
4 100
 
2.3%
6 98
 
2.3%
Other values (14) 392
 
9.0%
Hangul
ValueCountFrequency (%)
동 723
 
12.4%
작 375
 
6.4%
서 321
 
5.5%
구 318
 
5.4%
시 314
 
5.4%
별 312
 
5.3%
울 312
 
5.3%
특 312
 
5.3%
로 292
 
5.0%
상 198
 
3.4%
Other values (161) 2359
40.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)36.7%
Missing117
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean6991.5747
Minimum6902
Maximum7073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:32.284171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6902
5-th percentile6913.35
Q16956
median7002.5
Q37025
95-th percentile7066.3
Maximum7073
Range171
Interquartile range (IQR)69

Descriptive statistics

Standard deviation46.171162
Coefficient of variation (CV)0.0066038287
Kurtosis-0.94763615
Mean6991.5747
Median Absolute Deviation (MAD)34.5
Skewness-0.21763427
Sum2153405
Variance2131.7762
MonotonicityNot monotonic
2024-05-11T00:31:32.901450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7008 19
 
4.5%
7010 14
 
3.3%
7025 11
 
2.6%
6979 9
 
2.1%
7041 8
 
1.9%
7013 8
 
1.9%
7040 7
 
1.6%
6922 6
 
1.4%
6974 6
 
1.4%
7037 5
 
1.2%
Other values (103) 215
50.6%
(Missing) 117
27.5%
ValueCountFrequency (%)
6902 2
0.5%
6904 2
0.5%
6906 2
0.5%
6908 2
0.5%
6910 1
 
0.2%
6911 1
 
0.2%
6912 2
0.5%
6913 4
0.9%
6914 3
0.7%
6917 2
0.5%
ValueCountFrequency (%)
7073 1
 
0.2%
7072 1
 
0.2%
7071 5
1.2%
7070 1
 
0.2%
7069 3
0.7%
7068 3
0.7%
7067 2
 
0.5%
7065 1
 
0.2%
7064 2
 
0.5%
7063 2
 
0.5%

사업장명
Text

Distinct393
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-05-11T00:31:33.626534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length8.0211765
Min length2

Characters and Unicode

Total characters3409
Distinct characters431
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)87.8%

Sample

1st row파리바게뜨
2nd row케익하우스마망
3rd row그린하우스
4th row뚜레쥬르
5th row송승철과자점
ValueCountFrequency (%)
파리바게뜨 23
 
3.8%
뚜레쥬르 12
 
2.0%
베이커리 10
 
1.7%
크라운베이커리 8
 
1.3%
브레댄코 6
 
1.0%
파리바게트 5
 
0.8%
즉석빵집 4
 
0.7%
핫브레드 4
 
0.7%
베이커리팩토리 4
 
0.7%
과자점 3
 
0.5%
Other values (461) 520
86.8%
2024-05-11T00:31:34.990483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
5.1%
리 149
 
4.4%
이 137
 
4.0%
점 135
 
4.0%
베 74
 
2.2%
커 73
 
2.1%
스 65
 
1.9%
빵 65
 
1.9%
( 56
 
1.6%
) 56
 
1.6%
Other values (421) 2425
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2752
80.7%
Lowercase Letter 249
 
7.3%
Space Separator 174
 
5.1%
Uppercase Letter 87
 
2.6%
Open Punctuation 56
 
1.6%
Close Punctuation 56
 
1.6%
Decimal Number 26
 
0.8%
Other Punctuation 8
 
0.2%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 149
 
5.4%
이 137
 
5.0%
점 135
 
4.9%
베 74
 
2.7%
커 73
 
2.7%
스 65
 
2.4%
빵 65
 
2.4%
레 53
 
1.9%
바 52
 
1.9%
대 45
 
1.6%
Other values (362) 1904
69.2%
Lowercase Letter
ValueCountFrequency (%)
e 35
14.1%
a 25
10.0%
o 23
 
9.2%
n 19
 
7.6%
l 19
 
7.6%
t 17
 
6.8%
r 15
 
6.0%
s 13
 
5.2%
i 12
 
4.8%
b 10
 
4.0%
Other values (12) 61
24.5%
Uppercase Letter
ValueCountFrequency (%)
A 10
 
11.5%
B 10
 
11.5%
C 7
 
8.0%
E 6
 
6.9%
N 6
 
6.9%
K 5
 
5.7%
S 5
 
5.7%
I 5
 
5.7%
M 4
 
4.6%
G 4
 
4.6%
Other values (11) 25
28.7%
Decimal Number
ValueCountFrequency (%)
1 9
34.6%
0 5
19.2%
2 5
19.2%
3 2
 
7.7%
4 2
 
7.7%
8 1
 
3.8%
7 1
 
3.8%
6 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
& 3
37.5%
' 2
25.0%
, 2
25.0%
? 1
 
12.5%
Space Separator
ValueCountFrequency (%)
174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2751
80.7%
Latin 336
 
9.9%
Common 321
 
9.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 149
 
5.4%
이 137
 
5.0%
점 135
 
4.9%
베 74
 
2.7%
커 73
 
2.7%
스 65
 
2.4%
빵 65
 
2.4%
레 53
 
1.9%
바 52
 
1.9%
대 45
 
1.6%
Other values (361) 1903
69.2%
Latin
ValueCountFrequency (%)
e 35
 
10.4%
a 25
 
7.4%
o 23
 
6.8%
n 19
 
5.7%
l 19
 
5.7%
t 17
 
5.1%
r 15
 
4.5%
s 13
 
3.9%
i 12
 
3.6%
A 10
 
3.0%
Other values (33) 148
44.0%
Common
ValueCountFrequency (%)
174
54.2%
( 56
 
17.4%
) 56
 
17.4%
1 9
 
2.8%
0 5
 
1.6%
2 5
 
1.6%
& 3
 
0.9%
3 2
 
0.6%
' 2
 
0.6%
4 2
 
0.6%
Other values (6) 7
 
2.2%
Han
ValueCountFrequency (%)
味 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2751
80.7%
ASCII 657
 
19.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
26.5%
( 56
 
8.5%
) 56
 
8.5%
e 35
 
5.3%
a 25
 
3.8%
o 23
 
3.5%
n 19
 
2.9%
l 19
 
2.9%
t 17
 
2.6%
r 15
 
2.3%
Other values (49) 218
33.2%
Hangul
ValueCountFrequency (%)
리 149
 
5.4%
이 137
 
5.0%
점 135
 
4.9%
베 74
 
2.7%
커 73
 
2.7%
스 65
 
2.4%
빵 65
 
2.4%
레 53
 
1.9%
바 52
 
1.9%
대 45
 
1.6%
Other values (361) 1903
69.2%
CJK
ValueCountFrequency (%)
味 1
100.0%

최종수정일자
Date

Distinct395
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2000-03-22 00:00:00
Maximum2024-05-09 15:02:04
2024-05-11T00:31:35.401208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:31:35.936989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
I
255 
U
170 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 255
60.0%
U 170
40.0%

Length

2024-05-11T00:31:36.426949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:36.760087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 255
60.0%
u 170
40.0%

데이터갱신일자
Date

Distinct193
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T00:31:37.294181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:31:38.018551image/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 size3.4 KiB
제과점영업
425 

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 425
100.0%

Length

2024-05-11T00:31:38.607859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:39.187073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 425
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct333
Distinct (%)80.2%
Missing10
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean195755.44
Minimum191691.68
Maximum198364.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:39.640353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191691.68
5-th percentile192559.32
Q1194321.81
median195634.2
Q3197497.88
95-th percentile198270.3
Maximum198364.24
Range6672.5569
Interquartile range (IQR)3176.0701

Descriptive statistics

Standard deviation1835.2311
Coefficient of variation (CV)0.0093751216
Kurtosis-1.0195987
Mean195755.44
Median Absolute Deviation (MAD)1660.5009
Skewness-0.17658688
Sum81238509
Variance3368073.2
MonotonicityNot monotonic
2024-05-11T00:31:40.258723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196122.678608319 6
 
1.4%
197802.054854046 5
 
1.2%
198362.996258131 4
 
0.9%
198161.292479758 4
 
0.9%
193218.36400997 4
 
0.9%
196598.04833644 4
 
0.9%
193896.384765772 4
 
0.9%
195359.600787554 3
 
0.7%
197839.678764919 3
 
0.7%
193537.613233653 3
 
0.7%
Other values (323) 375
88.2%
(Missing) 10
 
2.4%
ValueCountFrequency (%)
191691.678396263 1
0.2%
191775.553539103 1
0.2%
191826.307710005 1
0.2%
191841.985106362 2
0.5%
191853.593009781 1
0.2%
191882.052202649 1
0.2%
191912.540279361 1
0.2%
191912.86873227 1
0.2%
191946.135275517 1
0.2%
192113.200600983 1
0.2%
ValueCountFrequency (%)
198364.235287192 1
 
0.2%
198362.996258131 4
0.9%
198353.622717679 1
 
0.2%
198320.791404486 1
 
0.2%
198307.861970121 2
0.5%
198307.119626065 1
 
0.2%
198305.619512013 2
0.5%
198303.527071078 1
 
0.2%
198299.206898579 1
 
0.2%
198298.155052509 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct333
Distinct (%)80.2%
Missing10
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean443859.73
Minimum441564.27
Maximum445755.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:40.918948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441564.27
5-th percentile441820.58
Q1442874.24
median444008.6
Q3444855.9
95-th percentile445605.4
Maximum445755.68
Range4191.4096
Interquartile range (IQR)1981.6607

Descriptive statistics

Standard deviation1164.585
Coefficient of variation (CV)0.002623768
Kurtosis-1.0937344
Mean443859.73
Median Absolute Deviation (MAD)997.0848
Skewness-0.21527647
Sum1.8420179 × 108
Variance1356258.1
MonotonicityNot monotonic
2024-05-11T00:31:41.473970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444705.530165147 6
 
1.4%
443049.47147487 5
 
1.2%
442875.120672624 4
 
0.9%
443614.335996111 4
 
0.9%
443239.581054145 4
 
0.9%
445014.002982422 4
 
0.9%
444196.484790728 4
 
0.9%
444794.527703017 3
 
0.7%
441582.949309562 3
 
0.7%
444162.946884802 3
 
0.7%
Other values (323) 375
88.2%
(Missing) 10
 
2.4%
ValueCountFrequency (%)
441564.273638609 1
 
0.2%
441569.058208929 1
 
0.2%
441582.949309562 3
0.7%
441588.861462309 1
 
0.2%
441635.715989023 1
 
0.2%
441636.298345044 2
0.5%
441674.847444835 2
0.5%
441696.145605791 2
0.5%
441698.064755179 1
 
0.2%
441724.168994744 1
 
0.2%
ValueCountFrequency (%)
445755.68326333 1
0.2%
445749.645488877 1
0.2%
445695.614065476 1
0.2%
445693.456564059 1
0.2%
445686.8730425 1
0.2%
445686.158478401 2
0.5%
445686.008483928 1
0.2%
445680.282421568 1
0.2%
445676.46193133 1
0.2%
445669.585939743 1
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
제과점영업
340 
<NA>
85 

Length

Max length5
Median length5
Mean length4.8
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 340
80.0%
<NA> 85
 
20.0%

Length

2024-05-11T00:31:41.910945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:42.262361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 340
80.0%
na 85
 
20.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.7%
Missing264
Missing (%)62.1%
Infinite0
Infinite (%)0.0%
Mean0.60869565
Minimum0
Maximum5
Zeros96
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:42.658149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.89564162
Coefficient of variation (CV)1.4714112
Kurtosis3.9137613
Mean0.60869565
Median Absolute Deviation (MAD)0
Skewness1.7556885
Sum98
Variance0.80217391
MonotonicityNot monotonic
2024-05-11T00:31:43.087498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 96
 
22.6%
1 40
 
9.4%
2 20
 
4.7%
3 3
 
0.7%
4 1
 
0.2%
5 1
 
0.2%
(Missing) 264
62.1%
ValueCountFrequency (%)
0 96
22.6%
1 40
9.4%
2 20
 
4.7%
3 3
 
0.7%
4 1
 
0.2%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 1
 
0.2%
3 3
 
0.7%
2 20
 
4.7%
1 40
9.4%
0 96
22.6%

여성종사자수
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
264 
0
96 
1
30 
2
29 
3
 
6

Length

Max length4
Median length4
Mean length2.8635294
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
<NA> 264
62.1%
0 96
 
22.6%
1 30
 
7.1%
2 29
 
6.8%
3 6
 
1.4%

Length

2024-05-11T00:31:43.512756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:43.950917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 264
62.1%
0 96
 
22.6%
1 30
 
7.1%
2 29
 
6.8%
3 6
 
1.4%

영업장주변구분명
Categorical

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
298 
주택가주변
59 
기타
43 
아파트지역
 
22
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length4.0164706
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 298
70.1%
주택가주변 59
 
13.9%
기타 43
 
10.1%
아파트지역 22
 
5.2%
유흥업소밀집지역 2
 
0.5%
학교정화(상대) 1
 
0.2%

Length

2024-05-11T00:31:44.527794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:44.985698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
70.1%
주택가주변 59
 
13.9%
기타 43
 
10.1%
아파트지역 22
 
5.2%
유흥업소밀집지역 2
 
0.5%
학교정화(상대 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
334 
기타
46 
자율
 
17
을
 
16
관리
 
10

Length

Max length4
Median length4
Mean length3.5294118
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 334
78.6%
기타 46
 
10.8%
자율 17
 
4.0%
을 16
 
3.8%
관리 10
 
2.4%
갑 2
 
0.5%

Length

2024-05-11T00:31:45.449367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:45.874181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 334
78.6%
기타 46
 
10.8%
자율 17
 
4.0%
을 16
 
3.8%
관리 10
 
2.4%
갑 2
 
0.5%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
상수도전용
222 
<NA>
203 

Length

Max length5
Median length5
Mean length4.5223529
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 222
52.2%
<NA> 203
47.8%

Length

2024-05-11T00:31:46.410342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:46.845478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 222
52.2%
na 203
47.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:47.263896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:47.676669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:48.280567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:48.606037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:49.000387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:49.479099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:50.056231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:50.502381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:51.061012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:51.548163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:52.068783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:52.480466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
395 
0
 
30

Length

Max length4
Median length4
Mean length3.7882353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 395
92.9%
0 30
 
7.1%

Length

2024-05-11T00:31:53.001420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:31:53.379109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 395
92.9%
0 30
 
7.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing85
Missing (%)20.0%
Memory size982.0 B
False
340 
(Missing)
85 
ValueCountFrequency (%)
False 340
80.0%
(Missing) 85
 
20.0%
2024-05-11T00:31:53.641590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct294
Distinct (%)86.5%
Missing85
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean40.796
Minimum0
Maximum525.28
Zeros6
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T00:31:54.019997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.5455
Q122.9875
median33.385
Q350.7575
95-th percentile86.445
Maximum525.28
Range525.28
Interquartile range (IQR)27.77

Descriptive statistics

Standard deviation35.658973
Coefficient of variation (CV)0.87408013
Kurtosis100.14224
Mean40.796
Median Absolute Deviation (MAD)12.13
Skewness7.7486992
Sum13870.64
Variance1271.5624
MonotonicityNot monotonic
2024-05-11T00:31:54.684784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
1.4%
33.0 5
 
1.2%
30.0 4
 
0.9%
25.0 4
 
0.9%
29.7 3
 
0.7%
10.0 3
 
0.7%
26.0 3
 
0.7%
23.0 2
 
0.5%
13.2 2
 
0.5%
43.75 2
 
0.5%
Other values (284) 306
72.0%
(Missing) 85
 
20.0%
ValueCountFrequency (%)
0.0 6
1.4%
7.2 1
 
0.2%
7.3 1
 
0.2%
8.55 1
 
0.2%
9.1 1
 
0.2%
9.75 1
 
0.2%
9.9 1
 
0.2%
10.0 3
0.7%
10.99 1
 
0.2%
11.46 1
 
0.2%
ValueCountFrequency (%)
525.28 1
0.2%
129.22 1
0.2%
129.14 1
0.2%
125.4 1
0.2%
115.29 1
0.2%
109.08 1
0.2%
108.25 1
0.2%
106.74 1
0.2%
104.08 1
0.2%
97.23 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing425
Missing (%)100.0%
Memory size3.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031900003190000-121-1970-0155519700710<NA>1영업/정상1영업<NA><NA><NA><NA>020813655073.5156860서울특별시 동작구 흑석동 102-30서울특별시 동작구 서달로13길 5-30 (흑석동)6972파리바게뜨2021-11-17 13:30:51U2021-11-19 02:40:00.0제과점영업196537.566709445053.769809제과점영업23주택가주변을상수도전용00000<NA>00N73.5<NA><NA><NA>
131900003190000-121-1972-0705519721031<NA>3폐업2폐업20061123<NA><NA><NA>020813938762.82156806서울특별시 동작구 노량진동 308-4번지<NA><NA>케익하우스마망2005-08-25 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업23유흥업소밀집지역을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.82<NA><NA><NA>
231900003190000-121-1973-0155419730126<NA>3폐업2폐업20060904<NA><NA><NA>02 8159081129.22156861서울특별시 동작구 흑석동 223-1번지<NA><NA>그린하우스2006-03-08 00:00:00I2018-08-31 23:59:59.0제과점영업196392.468179445005.685282제과점영업12주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.22<NA><NA><NA>
331900003190000-121-1975-0149119751229<NA>3폐업2폐업20100409<NA><NA><NA>020814257541.0156847서울특별시 동작구 신대방동 348-3번지<NA><NA>뚜레쥬르2005-08-25 00:00:00I2018-08-31 23:59:59.0제과점영업193592.513357444026.3532제과점영업22주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N41.0<NA><NA><NA>
431900003190000-121-1979-0151619790310<NA>3폐업2폐업20120206<NA><NA><NA>02 822463427.6156844서울특별시 동작구 상도동 259-16번지<NA><NA>송승철과자점2005-08-25 00:00:00I2018-08-31 23:59:59.0제과점영업194102.642723443995.79344제과점영업12주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.6<NA><NA><NA>
531900003190000-121-1979-0152819790911<NA>3폐업2폐업20110131<NA><NA><NA>02 582245737.43156826서울특별시 동작구 사당동 1030-20번지<NA><NA>크라운베이커리사당1호점2004-11-04 00:00:00I2018-08-31 23:59:59.0제과점영업198279.266223442017.925074제과점영업12주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.43<NA><NA><NA>
631900003190000-121-1981-0151719810206<NA>1영업/정상1영업<NA><NA><NA><NA>020821104566.0156839서울특별시 동작구 상도동 328-10서울특별시 동작구 국사봉1길 4 (상도동)7042파리바게뜨 신대방삼거리역점2021-12-10 15:04:36U2021-12-12 02:40:00.0제과점영업193643.020206444066.052899제과점영업23주택가주변을상수도전용00000<NA>00N66.0<NA><NA><NA>
731900003190000-121-1981-0155219810520<NA>3폐업2폐업20060515<NA><NA><NA>02 813584716.16156030서울특별시 동작구 상도동 463-11번지<NA><NA>백제당2005-08-26 00:00:00I2018-08-31 23:59:59.0제과점영업195654.714248444087.935273제과점영업11주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.16<NA><NA><NA>
831900003190000-121-1981-0155919811013<NA>3폐업2폐업20110502<NA><NA><NA>02 813020849.0156813서울특별시 동작구 본동 400-0번지<NA><NA>헤미니스 제과점2010-10-06 15:46:57I2018-08-31 23:59:59.0제과점영업195625.02384445584.324294제과점영업11주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.0<NA><NA><NA>
931900003190000-121-1982-0157019820504<NA>3폐업2폐업20120903<NA><NA><NA>02 815634337.32156030서울특별시 동작구 상도동 793-1번지<NA><NA>케익하우스 몽마2007-06-19 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업22주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.32<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
41531900003190000-121-2023-000192023-10-17<NA>1영업/정상1영업<NA><NA><NA><NA>023280877969.0156-807서울특별시 동작구 대방동 17-31서울특별시 동작구 여의대방로36길 105, 2층 (대방동)6942낸시스 커피월드(Nancy's coffee world)2023-10-17 11:35:39I2022-10-30 23:09:00.0제과점영업193902.608244445183.360339<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41631900003190000-121-2023-000202023-10-17<NA>1영업/정상1영업<NA><NA><NA><NA>0215779063227.6156-755서울특별시 동작구 흑석동 221 중앙대학교서울특별시 동작구 흑석로 84, 중앙대학교 1층 303관 B107,B108호 (흑석동)69741847베이글(bagel)2023-10-17 16:09:39I2022-10-30 23:09:00.0제과점영업196122.678608444705.530165<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41731900003190000-121-2023-000212023-11-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.0156-060서울특별시 동작구 본동 48-16서울특별시 동작구 노량진로26길 3-2, 1층 (본동)6908이담공방2023-11-03 14:29:34I2022-11-01 00:05:00.0제과점영업195907.15056445537.460615<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41831900003190000-121-2024-000012024-01-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3156-816서울특별시 동작구 사당동 147-29 이마트에브리데이 내서울특별시 동작구 사당로 300 (사당동, 이수자이)7013베이커리팩토리 이수점2024-01-30 15:57:29I2023-12-02 00:01:00.0제과점영업198202.472533442471.241038<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41931900003190000-121-2024-000032024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.96156-855서울특별시 동작구 신대방동 724 보라매자이 더 포레스트서울특별시 동작구 여의대방로22길 121, 제상가동 제1층 1212호 (신대방동, 보라매자이 더 포레스트)7056꼬메르제과2024-03-04 13:17:47I2023-12-03 00:06:00.0제과점영업193394.538706444040.843568<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42031900003190000-121-2024-000042024-03-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.0156-815서울특별시 동작구 사당동 105서울특별시 동작구 동작대로29길 110, 1층 (사당동, 신동아아파트)6998베이커리팩토리 사당동점2024-03-26 13:20:19I2023-12-02 22:08:00.0제과점영업197802.436613443049.214039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42131900003190000-121-2024-000052024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0156-859서울특별시 동작구 흑석동 97-2서울특별시 동작구 서달로 158 (흑석동, 아파트)6979베이커리팩토리 흑석동점2024-03-27 10:30:59I2023-12-02 22:09:00.0제과점영업196598.048336445014.002982<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42231900003190000-121-2024-000062024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.1156-839서울특별시 동작구 상도동 350-20서울특별시 동작구 상도로15길 11, 1층 101호 (상도동)6952에프(eff)2024-04-01 16:12:14I2023-12-04 00:03:00.0제과점영업193994.826689444368.294784<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42331900003190000-121-2024-000072024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>91.63156-830서울특별시 동작구 상도1동 572 청남빌딩서울특별시 동작구 강남초등8길 20, 청남빌딩 1층 (상도1동)6912더머커피 상도점2024-05-02 11:16:19I2023-12-05 00:04:00.0제과점영업195596.844447444784.248282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42431900003190000-121-2024-000082024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.5156-090서울특별시 동작구 사당동 38-4서울특별시 동작구 동작대로 163, 2층 202호 (사당동)6995피미엔타 베이커리2024-05-09 15:02:04I2023-12-04 23:01:00.0제과점영업198364.235287443215.230489<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>