Overview

Dataset statistics

Number of variables44
Number of observations571
Missing cells5226
Missing cells (%)20.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory209.8 KiB
Average record size in memory376.2 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18198/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (78.7%)Imbalance
여성종사자수 is highly imbalanced (83.3%)Imbalance
영업장주변구분명 is highly imbalanced (80.6%)Imbalance
등급구분명 is highly imbalanced (77.4%)Imbalance
급수시설구분명 is highly imbalanced (71.0%)Imbalance
총인원 is highly imbalanced (85.3%)Imbalance
보증액 is highly imbalanced (55.4%)Imbalance
월세액 is highly imbalanced (55.4%)Imbalance
다중이용업소여부 is highly imbalanced (94.6%)Imbalance
인허가취소일자 has 571 (100.0%) missing valuesMissing
폐업일자 has 111 (19.4%) missing valuesMissing
휴업시작일자 has 571 (100.0%) missing valuesMissing
휴업종료일자 has 571 (100.0%) missing valuesMissing
재개업일자 has 571 (100.0%) missing valuesMissing
전화번호 has 256 (44.8%) missing valuesMissing
소재지면적 has 161 (28.2%) missing valuesMissing
도로명주소 has 254 (44.5%) missing valuesMissing
도로명우편번호 has 257 (45.0%) missing valuesMissing
좌표정보(X) has 15 (2.6%) missing valuesMissing
좌표정보(Y) has 15 (2.6%) missing valuesMissing
다중이용업소여부 has 80 (14.0%) missing valuesMissing
시설총규모 has 80 (14.0%) missing valuesMissing
전통업소지정번호 has 571 (100.0%) missing valuesMissing
전통업소주된음식 has 571 (100.0%) missing valuesMissing
홈페이지 has 571 (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
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
시설총규모 has 421 (73.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:07:51.586461
Analysis finished2024-05-11 06:07:53.570391
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
3210000
571 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 571
100.0%

Length

2024-05-11T06:07:53.806115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:07:54.148093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 571
100.0%

관리번호
Text

UNIQUE 

Distinct571
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-11T06:07:54.596408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters12562
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

Unique571 ?
Unique (%)100.0%

Sample

1st row3210000-109-1982-00284
2nd row3210000-109-1983-01564
3rd row3210000-109-1985-00001
4th row3210000-109-1987-00001
5th row3210000-109-1988-00285
ValueCountFrequency (%)
3210000-109-1982-00284 1
 
0.2%
3210000-109-2012-00004 1
 
0.2%
3210000-109-2012-00006 1
 
0.2%
3210000-109-2011-00014 1
 
0.2%
3210000-109-2011-00015 1
 
0.2%
3210000-109-2012-00001 1
 
0.2%
3210000-109-2012-00002 1
 
0.2%
3210000-109-2012-00003 1
 
0.2%
3210000-109-2011-00012 1
 
0.2%
3210000-109-2011-00011 1
 
0.2%
Other values (561) 561
98.2%
2024-05-11T06:07:55.571079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5568
44.3%
1 1747
 
13.9%
- 1713
 
13.6%
2 1393
 
11.1%
9 798
 
6.4%
3 711
 
5.7%
5 145
 
1.2%
4 142
 
1.1%
8 134
 
1.1%
6 108
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10849
86.4%
Dash Punctuation 1713
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5568
51.3%
1 1747
 
16.1%
2 1393
 
12.8%
9 798
 
7.4%
3 711
 
6.6%
5 145
 
1.3%
4 142
 
1.3%
8 134
 
1.2%
6 108
 
1.0%
7 103
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1713
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12562
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5568
44.3%
1 1747
 
13.9%
- 1713
 
13.6%
2 1393
 
11.1%
9 798
 
6.4%
3 711
 
5.7%
5 145
 
1.2%
4 142
 
1.1%
8 134
 
1.1%
6 108
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12562
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5568
44.3%
1 1747
 
13.9%
- 1713
 
13.6%
2 1393
 
11.1%
9 798
 
6.4%
3 711
 
5.7%
5 145
 
1.2%
4 142
 
1.1%
8 134
 
1.1%
6 108
 
0.9%

인허가일자
Date

Distinct537
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum1982-09-20 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T06:07:56.077927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:07:56.583743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
3
460 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 460
80.6%
1 111
 
19.4%

Length

2024-05-11T06:07:57.061524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:07:57.423155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 460
80.6%
1 111
 
19.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
폐업
460 
영업/정상
111 

Length

Max length5
Median length2
Mean length2.5831874
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 460
80.6%
영업/정상 111
 
19.4%

Length

2024-05-11T06:07:57.775956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:07:58.195954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 460
80.6%
영업/정상 111
 
19.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2
460 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 460
80.6%
1 111
 
19.4%

Length

2024-05-11T06:07:58.597096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:07:58.961095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 460
80.6%
1 111
 
19.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
폐업
460 
영업
111 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 460
80.6%
영업 111
 
19.4%

Length

2024-05-11T06:07:59.353232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:07:59.672870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 460
80.6%
영업 111
 
19.4%

폐업일자
Date

MISSING 

Distinct367
Distinct (%)79.8%
Missing111
Missing (%)19.4%
Memory size4.6 KiB
Minimum1991-08-22 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T06:08:00.072590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:08:00.762053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

전화번호
Text

MISSING 

Distinct292
Distinct (%)92.7%
Missing256
Missing (%)44.8%
Memory size4.6 KiB
2024-05-11T06:08:01.523446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.488889
Min length2

Characters and Unicode

Total characters3304
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

Unique275 ?
Unique (%)87.3%

Sample

1st row0205912031
2nd row025666 315
3rd row0205861871
4th row02 5856561
5th row02 0
ValueCountFrequency (%)
02 229
36.3%
031 8
 
1.3%
070 6
 
1.0%
0221551052 4
 
0.6%
0 4
 
0.6%
522 4
 
0.6%
573 3
 
0.5%
521 3
 
0.5%
578 3
 
0.5%
15881234 3
 
0.5%
Other values (341) 363
57.6%
2024-05-11T06:08:02.977665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 504
15.3%
2 480
14.5%
422
12.8%
5 381
11.5%
3 253
7.7%
7 246
7.4%
4 240
7.3%
1 236
7.1%
8 200
 
6.1%
6 176
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2882
87.2%
Space Separator 422
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 504
17.5%
2 480
16.7%
5 381
13.2%
3 253
8.8%
7 246
8.5%
4 240
8.3%
1 236
8.2%
8 200
 
6.9%
6 176
 
6.1%
9 166
 
5.8%
Space Separator
ValueCountFrequency (%)
422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 504
15.3%
2 480
14.5%
422
12.8%
5 381
11.5%
3 253
7.7%
7 246
7.4%
4 240
7.3%
1 236
7.1%
8 200
 
6.1%
6 176
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 504
15.3%
2 480
14.5%
422
12.8%
5 381
11.5%
3 253
7.7%
7 246
7.4%
4 240
7.3%
1 236
7.1%
8 200
 
6.1%
6 176
 
5.3%

소재지면적
Real number (ℝ)

MISSING 

Distinct243
Distinct (%)59.3%
Missing161
Missing (%)28.2%
Infinite0
Infinite (%)0.0%
Mean44.137683
Minimum0
Maximum434.97
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T06:08:03.442872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16.6
median20
Q356.7775
95-th percentile164.019
Maximum434.97
Range434.97
Interquartile range (IQR)50.1775

Descriptive statistics

Standard deviation59.200772
Coefficient of variation (CV)1.341275
Kurtosis9.5491858
Mean44.137683
Median Absolute Deviation (MAD)15.515
Skewness2.6169006
Sum18096.45
Variance3504.7314
MonotonicityNot monotonic
2024-05-11T06:08:04.027020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 19
 
3.3%
3.3 17
 
3.0%
3.0 16
 
2.8%
6.6 14
 
2.5%
6.0 10
 
1.8%
9.9 8
 
1.4%
30.0 7
 
1.2%
33.0 6
 
1.1%
16.5 6
 
1.1%
20.0 6
 
1.1%
Other values (233) 301
52.7%
(Missing) 161
28.2%
ValueCountFrequency (%)
0.0 2
0.4%
1.0 3
0.5%
1.1 1
 
0.2%
1.3 1
 
0.2%
1.5 3
0.5%
1.9 1
 
0.2%
2.0 2
0.4%
2.31 1
 
0.2%
2.5 3
0.5%
2.65 1
 
0.2%
ValueCountFrequency (%)
434.97 1
0.2%
408.1 1
0.2%
310.69 1
0.2%
270.0 1
0.2%
261.6 1
0.2%
226.73 1
0.2%
225.4 1
0.2%
222.41 1
0.2%
210.24 1
0.2%
200.53 1
0.2%

소재지우편번호
Text

Distinct148
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-11T06:08:04.621511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0823117
Min length6

Characters and Unicode

Total characters3473
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

Unique56 ?
Unique (%)9.8%

Sample

1st row137906
2nd row137040
3rd row137070
4th row137879
5th row137732
ValueCountFrequency (%)
137893 55
 
9.6%
137713 51
 
8.9%
137896 15
 
2.6%
137908 13
 
2.3%
137890 12
 
2.1%
137899 11
 
1.9%
137894 11
 
1.9%
137906 9
 
1.6%
137895 9
 
1.6%
137130 9
 
1.6%
Other values (138) 376
65.8%
2024-05-11T06:08:05.682997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 749
21.6%
7 716
20.6%
1 712
20.5%
8 527
15.2%
9 248
 
7.1%
0 178
 
5.1%
6 107
 
3.1%
4 71
 
2.0%
2 60
 
1.7%
5 58
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3426
98.6%
Dash Punctuation 47
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 749
21.9%
7 716
20.9%
1 712
20.8%
8 527
15.4%
9 248
 
7.2%
0 178
 
5.2%
6 107
 
3.1%
4 71
 
2.1%
2 60
 
1.8%
5 58
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 749
21.6%
7 716
20.6%
1 712
20.5%
8 527
15.2%
9 248
 
7.1%
0 178
 
5.1%
6 107
 
3.1%
4 71
 
2.0%
2 60
 
1.7%
5 58
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 749
21.6%
7 716
20.6%
1 712
20.5%
8 527
15.2%
9 248
 
7.1%
0 178
 
5.1%
6 107
 
3.1%
4 71
 
2.0%
2 60
 
1.7%
5 58
 
1.7%

지번주소
Text

Distinct510
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-11T06:08:06.259772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length38
Mean length26.50613
Min length16

Characters and Unicode

Total characters15135
Distinct characters268
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique487 ?
Unique (%)85.3%

Sample

1st row서울특별시 서초구 잠원동 50-5 지하
2nd row서울특별시 서초구 반포동 444-1
3rd row서울특별시 서초구 서초동 산 1336
4th row서울특별시 서초구 서초동 1628-27
5th row서울특별시 서초구 서초동 1445-14 진로유통 지하동 1층호
ValueCountFrequency (%)
서울특별시 571
18.6%
서초구 571
18.6%
양재동 187
 
6.1%
서초동 125
 
4.1%
반포동 104
 
3.4%
1층 99
 
3.2%
방배동 98
 
3.2%
지하1층 73
 
2.4%
19-3 53
 
1.7%
230 41
 
1.3%
Other values (786) 1150
37.4%
2024-05-11T06:08:07.311770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2960
19.6%
서 1285
 
8.5%
1 815
 
5.4%
초 706
 
4.7%
동 598
 
4.0%
시 587
 
3.9%
울 575
 
3.8%
별 571
 
3.8%
특 571
 
3.8%
구 571
 
3.8%
Other values (258) 5896
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8563
56.6%
Decimal Number 3021
 
20.0%
Space Separator 2960
 
19.6%
Dash Punctuation 477
 
3.2%
Uppercase Letter 64
 
0.4%
Other Punctuation 20
 
0.1%
Close Punctuation 13
 
0.1%
Open Punctuation 13
 
0.1%
Other Symbol 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1285
15.0%
초 706
 
8.2%
동 598
 
7.0%
시 587
 
6.9%
울 575
 
6.7%
별 571
 
6.7%
특 571
 
6.7%
구 571
 
6.7%
층 289
 
3.4%
양 205
 
2.4%
Other values (226) 2605
30.4%
Uppercase Letter
ValueCountFrequency (%)
B 28
43.8%
A 8
 
12.5%
C 5
 
7.8%
T 5
 
7.8%
D 5
 
7.8%
F 4
 
6.2%
S 3
 
4.7%
E 2
 
3.1%
H 1
 
1.6%
M 1
 
1.6%
Other values (2) 2
 
3.1%
Decimal Number
ValueCountFrequency (%)
1 815
27.0%
2 417
13.8%
3 392
13.0%
0 277
 
9.2%
4 210
 
7.0%
5 193
 
6.4%
9 187
 
6.2%
7 184
 
6.1%
6 184
 
6.1%
8 162
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 15
75.0%
/ 5
 
25.0%
Space Separator
ValueCountFrequency (%)
2960
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8563
56.6%
Common 6506
43.0%
Latin 66
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1285
15.0%
초 706
 
8.2%
동 598
 
7.0%
시 587
 
6.9%
울 575
 
6.7%
별 571
 
6.7%
특 571
 
6.7%
구 571
 
6.7%
층 289
 
3.4%
양 205
 
2.4%
Other values (226) 2605
30.4%
Common
ValueCountFrequency (%)
2960
45.5%
1 815
 
12.5%
- 477
 
7.3%
2 417
 
6.4%
3 392
 
6.0%
0 277
 
4.3%
4 210
 
3.2%
5 193
 
3.0%
9 187
 
2.9%
7 184
 
2.8%
Other values (8) 394
 
6.1%
Latin
ValueCountFrequency (%)
B 28
42.4%
A 8
 
12.1%
C 5
 
7.6%
T 5
 
7.6%
D 5
 
7.6%
F 4
 
6.1%
S 3
 
4.5%
E 2
 
3.0%
H 1
 
1.5%
M 1
 
1.5%
Other values (4) 4
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8563
56.6%
ASCII 6570
43.4%
CJK Compat 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2960
45.1%
1 815
 
12.4%
- 477
 
7.3%
2 417
 
6.3%
3 392
 
6.0%
0 277
 
4.2%
4 210
 
3.2%
5 193
 
2.9%
9 187
 
2.8%
7 184
 
2.8%
Other values (20) 458
 
7.0%
Hangul
ValueCountFrequency (%)
서 1285
15.0%
초 706
 
8.2%
동 598
 
7.0%
시 587
 
6.9%
울 575
 
6.7%
별 571
 
6.7%
특 571
 
6.7%
구 571
 
6.7%
층 289
 
3.4%
양 205
 
2.4%
Other values (226) 2605
30.4%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct312
Distinct (%)98.4%
Missing254
Missing (%)44.5%
Memory size4.6 KiB
2024-05-11T06:08:08.108722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length33.675079
Min length22

Characters and Unicode

Total characters10675
Distinct characters259
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

Unique308 ?
Unique (%)97.2%

Sample

1st row서울특별시 서초구 서초대로15길 80 (방배동)
2nd row서울특별시 서초구 논현로5길 16-9 (양재동)
3rd row서울특별시 서초구 동산로16길 20, 1층 (양재동)
4th row서울특별시 서초구 동산로16길 55 (양재동)
5th row서울특별시 서초구 서초대로15길 8-22 (방배동)
ValueCountFrequency (%)
서울특별시 317
 
15.3%
서초구 317
 
15.3%
1층 87
 
4.2%
양재동 72
 
3.5%
서초동 64
 
3.1%
방배동 57
 
2.8%
지하1층 44
 
2.1%
2층 31
 
1.5%
반포동 28
 
1.4%
10 20
 
1.0%
Other values (590) 1032
49.9%
2024-05-11T06:08:09.677891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1753
 
16.4%
서 776
 
7.3%
1 497
 
4.7%
초 445
 
4.2%
, 369
 
3.5%
동 348
 
3.3%
시 329
 
3.1%
) 322
 
3.0%
( 322
 
3.0%
로 320
 
3.0%
Other values (249) 5194
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6225
58.3%
Space Separator 1753
 
16.4%
Decimal Number 1598
 
15.0%
Other Punctuation 370
 
3.5%
Close Punctuation 322
 
3.0%
Open Punctuation 322
 
3.0%
Dash Punctuation 46
 
0.4%
Uppercase Letter 37
 
0.3%
Lowercase Letter 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 776
 
12.5%
초 445
 
7.1%
동 348
 
5.6%
시 329
 
5.3%
로 320
 
5.1%
구 319
 
5.1%
울 319
 
5.1%
별 317
 
5.1%
특 317
 
5.1%
층 236
 
3.8%
Other values (221) 2499
40.1%
Decimal Number
ValueCountFrequency (%)
1 497
31.1%
2 203
12.7%
3 168
 
10.5%
0 156
 
9.8%
4 119
 
7.4%
6 118
 
7.4%
5 109
 
6.8%
7 101
 
6.3%
8 67
 
4.2%
9 60
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 16
43.2%
A 5
 
13.5%
T 5
 
13.5%
C 4
 
10.8%
S 2
 
5.4%
P 1
 
2.7%
F 1
 
2.7%
D 1
 
2.7%
M 1
 
2.7%
Y 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 369
99.7%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1753
100.0%
Close Punctuation
ValueCountFrequency (%)
) 322
100.0%
Open Punctuation
ValueCountFrequency (%)
( 322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6225
58.3%
Common 4411
41.3%
Latin 39
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 776
 
12.5%
초 445
 
7.1%
동 348
 
5.6%
시 329
 
5.3%
로 320
 
5.1%
구 319
 
5.1%
울 319
 
5.1%
별 317
 
5.1%
특 317
 
5.1%
층 236
 
3.8%
Other values (221) 2499
40.1%
Common
ValueCountFrequency (%)
1753
39.7%
1 497
 
11.3%
, 369
 
8.4%
) 322
 
7.3%
( 322
 
7.3%
2 203
 
4.6%
3 168
 
3.8%
0 156
 
3.5%
4 119
 
2.7%
6 118
 
2.7%
Other values (6) 384
 
8.7%
Latin
ValueCountFrequency (%)
B 16
41.0%
A 5
 
12.8%
T 5
 
12.8%
C 4
 
10.3%
S 2
 
5.1%
P 1
 
2.6%
F 1
 
2.6%
D 1
 
2.6%
M 1
 
2.6%
Y 1
 
2.6%
Other values (2) 2
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6225
58.3%
ASCII 4449
41.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1753
39.4%
1 497
 
11.2%
, 369
 
8.3%
) 322
 
7.2%
( 322
 
7.2%
2 203
 
4.6%
3 168
 
3.8%
0 156
 
3.5%
4 119
 
2.7%
6 118
 
2.7%
Other values (17) 422
 
9.5%
Hangul
ValueCountFrequency (%)
서 776
 
12.5%
초 445
 
7.1%
동 348
 
5.6%
시 329
 
5.3%
로 320
 
5.1%
구 319
 
5.1%
울 319
 
5.1%
별 317
 
5.1%
특 317
 
5.1%
층 236
 
3.8%
Other values (221) 2499
40.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)50.3%
Missing257
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean6671.5637
Minimum6502
Maximum6806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T06:08:10.160688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6502
5-th percentile6525.65
Q16582.25
median6677
Q36768.75
95-th percentile6800
Maximum6806
Range304
Interquartile range (IQR)186.5

Descriptive statistics

Standard deviation94.184362
Coefficient of variation (CV)0.014117284
Kurtosis-1.3525913
Mean6671.5637
Median Absolute Deviation (MAD)93.5
Skewness-0.14673623
Sum2094871
Variance8870.694
MonotonicityNot monotonic
2024-05-11T06:08:10.963654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6797 16
 
2.8%
6546 13
 
2.3%
6774 8
 
1.4%
6804 6
 
1.1%
6677 5
 
0.9%
6781 5
 
0.9%
6748 5
 
0.9%
6511 4
 
0.7%
6771 4
 
0.7%
6802 4
 
0.7%
Other values (148) 244
42.7%
(Missing) 257
45.0%
ValueCountFrequency (%)
6502 1
 
0.2%
6506 1
 
0.2%
6510 2
0.4%
6511 4
0.7%
6512 2
0.4%
6515 1
 
0.2%
6518 1
 
0.2%
6523 1
 
0.2%
6524 2
0.4%
6525 1
 
0.2%
ValueCountFrequency (%)
6806 3
 
0.5%
6804 6
 
1.1%
6803 1
 
0.2%
6802 4
 
0.7%
6800 3
 
0.5%
6797 16
2.8%
6793 1
 
0.2%
6791 1
 
0.2%
6789 1
 
0.2%
6785 3
 
0.5%

사업장명
Text

Distinct543
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-05-11T06:08:11.588405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length7.2521891
Min length2

Characters and Unicode

Total characters4141
Distinct characters480
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

Unique518 ?
Unique (%)90.7%

Sample

1st row(주)시대수산
2nd row(주)삼호유통
3rd row우성마트
4th row일광식품
5th row주)진로종합유통
ValueCountFrequency (%)
주식회사 37
 
5.3%
서초점 7
 
1.0%
양재점 6
 
0.9%
만보수산 5
 
0.7%
강남점 5
 
0.7%
방배점 4
 
0.6%
주)신세계이마트 3
 
0.4%
주)교동씨엠 3
 
0.4%
주)지에스리테일 3
 
0.4%
주)진로종합유통 2
 
0.3%
Other values (591) 624
89.3%
2024-05-11T06:08:12.600729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 253
 
6.1%
) 221
 
5.3%
( 220
 
5.3%
128
 
3.1%
이 98
 
2.4%
식 90
 
2.2%
스 81
 
2.0%
트 70
 
1.7%
사 64
 
1.5%
리 59
 
1.4%
Other values (470) 2857
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3435
83.0%
Close Punctuation 221
 
5.3%
Open Punctuation 220
 
5.3%
Space Separator 128
 
3.1%
Uppercase Letter 69
 
1.7%
Lowercase Letter 36
 
0.9%
Decimal Number 22
 
0.5%
Other Punctuation 7
 
0.2%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 253
 
7.4%
이 98
 
2.9%
식 90
 
2.6%
스 81
 
2.4%
트 70
 
2.0%
사 64
 
1.9%
리 59
 
1.7%
마 56
 
1.6%
통 55
 
1.6%
아 51
 
1.5%
Other values (415) 2558
74.5%
Uppercase Letter
ValueCountFrequency (%)
S 9
13.0%
E 7
 
10.1%
A 7
 
10.1%
L 6
 
8.7%
N 5
 
7.2%
R 4
 
5.8%
F 3
 
4.3%
W 3
 
4.3%
K 3
 
4.3%
C 3
 
4.3%
Other values (12) 19
27.5%
Lowercase Letter
ValueCountFrequency (%)
t 5
13.9%
e 4
11.1%
a 4
11.1%
r 3
 
8.3%
i 3
 
8.3%
y 2
 
5.6%
l 2
 
5.6%
p 2
 
5.6%
u 2
 
5.6%
o 1
 
2.8%
Other values (8) 8
22.2%
Decimal Number
ValueCountFrequency (%)
1 5
22.7%
3 5
22.7%
0 3
13.6%
2 2
 
9.1%
6 2
 
9.1%
5 2
 
9.1%
8 1
 
4.5%
7 1
 
4.5%
4 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 221
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Space Separator
ValueCountFrequency (%)
128
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3435
83.0%
Common 601
 
14.5%
Latin 105
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 253
 
7.4%
이 98
 
2.9%
식 90
 
2.6%
스 81
 
2.4%
트 70
 
2.0%
사 64
 
1.9%
리 59
 
1.7%
마 56
 
1.6%
통 55
 
1.6%
아 51
 
1.5%
Other values (415) 2558
74.5%
Latin
ValueCountFrequency (%)
S 9
 
8.6%
E 7
 
6.7%
A 7
 
6.7%
L 6
 
5.7%
N 5
 
4.8%
t 5
 
4.8%
e 4
 
3.8%
a 4
 
3.8%
R 4
 
3.8%
r 3
 
2.9%
Other values (30) 51
48.6%
Common
ValueCountFrequency (%)
) 221
36.8%
( 220
36.6%
128
21.3%
. 7
 
1.2%
1 5
 
0.8%
3 5
 
0.8%
0 3
 
0.5%
2 2
 
0.3%
6 2
 
0.3%
- 2
 
0.3%
Other values (5) 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3435
83.0%
ASCII 706
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 253
 
7.4%
이 98
 
2.9%
식 90
 
2.6%
스 81
 
2.4%
트 70
 
2.0%
사 64
 
1.9%
리 59
 
1.7%
마 56
 
1.6%
통 55
 
1.6%
아 51
 
1.5%
Other values (415) 2558
74.5%
ASCII
ValueCountFrequency (%)
) 221
31.3%
( 220
31.2%
128
18.1%
S 9
 
1.3%
E 7
 
1.0%
A 7
 
1.0%
. 7
 
1.0%
L 6
 
0.8%
1 5
 
0.7%
N 5
 
0.7%
Other values (45) 91
12.9%

최종수정일자
Date

Distinct488
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum1999-07-15 00:00:00
Maximum2024-05-09 17:27:05
2024-05-11T06:08:13.021045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:08:13.571339image/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 size4.6 KiB
I
438 
U
133 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 438
76.7%
U 133
 
23.3%

Length

2024-05-11T06:08:14.032372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:14.454610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 438
76.7%
u 133
 
23.3%

데이터갱신일자
Date

Distinct144
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T06:08:14.846361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:08:15.354288image/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 size4.6 KiB
식품소분업
571 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 571
100.0%

Length

2024-05-11T06:08:15.824374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:16.194398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 571
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct375
Distinct (%)67.4%
Missing15
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean201646.01
Minimum198394.43
Maximum206099.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T06:08:16.602267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198394.43
5-th percentile198716.08
Q1200250.45
median201551.3
Q3203422.52
95-th percentile204055.3
Maximum206099.81
Range7705.3747
Interquartile range (IQR)3172.0683

Descriptive statistics

Standard deviation1818.2086
Coefficient of variation (CV)0.0090168339
Kurtosis-1.1993128
Mean201646.01
Median Absolute Deviation (MAD)1681.759
Skewness-0.073209933
Sum1.1211518 × 108
Variance3305882.5
MonotonicityNot monotonic
2024-05-11T06:08:17.364995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200250.447804795 52
 
9.1%
203811.366422118 41
 
7.2%
203204.755637424 11
 
1.9%
203392.793460583 11
 
1.9%
200576.608647619 10
 
1.8%
203171.974508939 9
 
1.6%
198791.788015494 5
 
0.9%
201643.318591414 4
 
0.7%
201386.338220173 4
 
0.7%
202478.1048837 3
 
0.5%
Other values (365) 406
71.1%
(Missing) 15
 
2.6%
ValueCountFrequency (%)
198394.433265008 1
0.2%
198443.792714945 1
0.2%
198460.897460477 1
0.2%
198462.438803051 1
0.2%
198470.186359333 1
0.2%
198485.718658225 1
0.2%
198490.751641835 1
0.2%
198491.247008023 1
0.2%
198492.797210723 2
0.4%
198498.675756673 1
0.2%
ValueCountFrequency (%)
206099.808000096 1
0.2%
205235.018649725 1
0.2%
205203.899329664 1
0.2%
205185.318387598 1
0.2%
204995.272423887 1
0.2%
204895.51633927 1
0.2%
204882.608755706 1
0.2%
204875.466915578 2
0.4%
204847.138893841 1
0.2%
204416.625355221 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct375
Distinct (%)67.4%
Missing15
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean442595.44
Minimum436961.57
Maximum446179.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T06:08:17.997788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436961.57
5-th percentile440070.73
Q1441275.52
median442590.54
Q3443958.57
95-th percentile445266.68
Maximum446179.31
Range9217.7387
Interquartile range (IQR)2683.0482

Descriptive statistics

Standard deviation1751.1185
Coefficient of variation (CV)0.0039564765
Kurtosis-0.63224618
Mean442595.44
Median Absolute Deviation (MAD)1344.2425
Skewness-0.15798785
Sum2.4608307 × 108
Variance3066416
MonotonicityNot monotonic
2024-05-11T06:08:18.525142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444683.220506107 52
 
9.1%
440070.727589935 41
 
7.2%
440136.781183797 11
 
1.9%
440676.379919661 11
 
1.9%
445241.8984183 10
 
1.8%
439620.265870293 9
 
1.6%
444392.672548989 5
 
0.9%
443772.466475611 4
 
0.7%
443689.075119969 4
 
0.7%
443306.064904505 3
 
0.5%
Other values (365) 406
71.1%
(Missing) 15
 
2.6%
ValueCountFrequency (%)
436961.570793747 1
 
0.2%
437864.710924867 1
 
0.2%
437890.507732031 1
 
0.2%
437959.961132488 1
 
0.2%
438400.973299439 1
 
0.2%
438416.991038311 2
 
0.4%
439029.959102177 1
 
0.2%
439369.980698955 1
 
0.2%
439407.27399616 1
 
0.2%
439620.265870293 9
1.6%
ValueCountFrequency (%)
446179.309516814 1
0.2%
446144.110278895 1
0.2%
446102.588876 1
0.2%
446100.917105583 1
0.2%
445992.459343379 1
0.2%
445919.859629417 1
0.2%
445892.414984064 1
0.2%
445861.078952221 1
0.2%
445734.537719607 1
0.2%
445533.225557562 1
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
식품소분업
491 
<NA>
80 

Length

Max length5
Median length5
Mean length4.8598949
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 491
86.0%
<NA> 80
 
14.0%

Length

2024-05-11T06:08:19.269153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:19.564178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 491
86.0%
na 80
 
14.0%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
538 
0
 
31
2
 
2

Length

Max length4
Median length4
Mean length3.82662
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 538
94.2%
0 31
 
5.4%
2 2
 
0.4%

Length

2024-05-11T06:08:20.118739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:20.702002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 538
94.2%
0 31
 
5.4%
2 2
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
539 
0
 
30
5
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.8318739
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row5
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row3

Common Values

ValueCountFrequency (%)
<NA> 539
94.4%
0 30
 
5.3%
5 1
 
0.2%
3 1
 
0.2%

Length

2024-05-11T06:08:21.364719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:21.692067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 539
94.4%
0 30
 
5.3%
5 1
 
0.2%
3 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
535 
기타
 
30
주택가주변
 
5
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.9054291
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 535
93.7%
기타 30
 
5.3%
주택가주변 5
 
0.9%
아파트지역 1
 
0.2%

Length

2024-05-11T06:08:22.037936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:22.429230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 535
93.7%
기타 30
 
5.3%
주택가주변 5
 
0.9%
아파트지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
535 
기타
 
34
갑
 
2

Length

Max length4
Median length4
Mean length3.8704028
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 535
93.7%
기타 34
 
6.0%
갑 2
 
0.4%

Length

2024-05-11T06:08:22.898066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:23.239140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 535
93.7%
기타 34
 
6.0%
갑 2
 
0.4%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
542 
상수도전용
 
29

Length

Max length5
Median length4
Mean length4.0507881
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 542
94.9%
상수도전용 29
 
5.1%

Length

2024-05-11T06:08:23.717936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:24.035697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 542
94.9%
상수도전용 29
 
5.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
559 
0
 
12

Length

Max length4
Median length4
Mean length3.9369527
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 559
97.9%
0 12
 
2.1%

Length

2024-05-11T06:08:24.393092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:24.732188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 559
97.9%
0 12
 
2.1%

본사종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
402 
0
169 

Length

Max length4
Median length4
Mean length3.1120841
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
70.4%
0 169
29.6%

Length

2024-05-11T06:08:25.145300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:25.501355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
70.4%
0 169
29.6%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
402 
0
169 

Length

Max length4
Median length4
Mean length3.1120841
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
70.4%
0 169
29.6%

Length

2024-05-11T06:08:25.861676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:26.448241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
70.4%
0 169
29.6%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
402 
0
169 

Length

Max length4
Median length4
Mean length3.1120841
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
70.4%
0 169
29.6%

Length

2024-05-11T06:08:26.815832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:27.178349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
70.4%
0 169
29.6%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
402 
0
169 

Length

Max length4
Median length4
Mean length3.1120841
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 402
70.4%
0 169
29.6%

Length

2024-05-11T06:08:27.616644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:27.981587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
70.4%
0 169
29.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
285 
임대
168 
자가
118 

Length

Max length4
Median length2
Mean length2.9982487
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 285
49.9%
임대 168
29.4%
자가 118
20.7%

Length

2024-05-11T06:08:28.322584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:28.779138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
49.9%
임대 168
29.4%
자가 118
20.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
518 
0
53 

Length

Max length4
Median length4
Mean length3.7215412
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 518
90.7%
0 53
 
9.3%

Length

2024-05-11T06:08:29.209416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:29.626003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 518
90.7%
0 53
 
9.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
518 
0
53 

Length

Max length4
Median length4
Mean length3.7215412
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 518
90.7%
0 53
 
9.3%

Length

2024-05-11T06:08:30.053629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:08:30.502992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 518
90.7%
0 53
 
9.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing80
Missing (%)14.0%
Memory size1.2 KiB
False
488 
True
 
3
(Missing)
80 
ValueCountFrequency (%)
False 488
85.5%
True 3
 
0.5%
(Missing) 80
 
14.0%
2024-05-11T06:08:30.853790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct58
Distinct (%)11.8%
Missing80
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean7.3214257
Minimum0
Maximum310.69
Zeros421
Zeros (%)73.7%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T06:08:31.406178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile45.1
Maximum310.69
Range310.69
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.56789
Coefficient of variation (CV)4.0385427
Kurtosis39.177107
Mean7.3214257
Median Absolute Deviation (MAD)0
Skewness5.766847
Sum3594.82
Variance874.26013
MonotonicityNot monotonic
2024-05-11T06:08:31.891391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 421
73.7%
10.0 4
 
0.7%
6.6 4
 
0.7%
3.3 4
 
0.7%
3.0 2
 
0.4%
33.0 2
 
0.4%
60.0 2
 
0.4%
25.0 2
 
0.4%
2.0 1
 
0.2%
52.05 1
 
0.2%
Other values (48) 48
 
8.4%
(Missing) 80
 
14.0%
ValueCountFrequency (%)
0.0 421
73.7%
2.0 1
 
0.2%
3.0 2
 
0.4%
3.3 4
 
0.7%
4.0 1
 
0.2%
4.3 1
 
0.2%
5.0 1
 
0.2%
6.0 1
 
0.2%
6.6 4
 
0.7%
7.0 1
 
0.2%
ValueCountFrequency (%)
310.69 1
0.2%
200.53 1
0.2%
189.97 1
0.2%
182.0 1
0.2%
177.34 1
0.2%
171.9 1
0.2%
165.02 1
0.2%
160.26 1
0.2%
145.2 1
0.2%
130.0 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-109-1982-0028419820920<NA>3폐업2폐업20030408<NA><NA><NA>0205912031408.1137906서울특별시 서초구 잠원동 50-5 지하<NA><NA>(주)시대수산2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업201230.693449445992.459343식품소분업25기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132100003210000-109-1983-0156419831024<NA>3폐업2폐업19960704<NA><NA><NA><NA><NA>137040서울특별시 서초구 반포동 444-1<NA><NA>(주)삼호유통2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232100003210000-109-1985-0000119850215<NA>3폐업2폐업20140904<NA><NA><NA>025666 315<NA>137070서울특별시 서초구 서초동 산 1336<NA><NA>우성마트2003-08-16 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332100003210000-109-1987-0000119870918<NA>3폐업2폐업19920804<NA><NA><NA><NA><NA>137879서울특별시 서초구 서초동 1628-27<NA><NA>일광식품2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업201493.506816442962.460314식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432100003210000-109-1988-0028519880201<NA>3폐업2폐업20000821<NA><NA><NA>020586187184.0137732서울특별시 서초구 서초동 1445-14 진로유통 지하동 1층호<NA><NA>주)진로종합유통2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업201493.614233442372.299423식품소분업03기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532100003210000-109-1988-0028619880328<NA>3폐업2폐업20180628<NA><NA><NA><NA><NA>137832서울특별시 서초구 방배동 819-30서울특별시 서초구 서초대로15길 80 (방배동)6563청능식품2018-06-28 19:27:54I2018-08-31 23:59:59.0식품소분업198904.023114443083.063107식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632100003210000-109-1989-0000119890906<NA>3폐업2폐업19950726<NA><NA><NA><NA><NA>137864서울특별시 서초구 서초동 1428-4<NA><NA>(주)선일특산2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업201759.055873442426.129738식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732100003210000-109-1989-0000219891209<NA>3폐업2폐업19920209<NA><NA><NA>02 5856561<NA>137820서울특별시 서초구 방배동 477-7 지층<NA><NA>(주)오끼나인터내쇼날2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업198829.374217441644.033888식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832100003210000-109-1990-0028619900209<NA>3폐업2폐업20050211<NA><NA><NA>02 047.25137811서울특별시 서초구 반포동 1141-0<NA><NA>(주)현대백화점 반포점2003-02-08 00:00:00I2018-08-31 23:59:59.0식품소분업198791.788015444392.672549식품소분업<NA><NA>아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932100003210000-109-1990-0028819900728<NA>3폐업2폐업19910822<NA><NA><NA>02 5775011<NA>137890서울특별시 서초구 양재동 89-1<NA><NA>(주)진미식품2002-07-11 00:00:00I2018-08-31 23:59:59.0식품소분업203628.289529441924.866967식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
56132100003210000-109-2023-000072023-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.5137-870서울특별시 서초구 서초동 1498-5 마제스타시티, 힐스테이트 서리풀서울특별시 서초구 서초대로38길 12, 지하2층 (서초동, 마제스타시티, 힐스테이트 서리풀)6655소담생과방2023-04-12 17:31:56I2022-12-03 23:04:00.0식품소분업200440.010812443124.671418<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56232100003210000-109-2023-000082023-07-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0137-898서울특별시 서초구 양재동 361-1 화인빌딩 101호서울특별시 서초구 강남대로6길 90-6, 1층 101호 (양재동)6789피케이파트너스2023-07-10 09:26:17I2022-12-06 23:03:00.0식품소분업203943.694798440754.956662<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56332100003210000-109-2023-000102023-09-20<NA>1영업/정상1영업<NA><NA><NA><NA>02 571933415.0137-150서울특별시 서초구 원지동 419서울특별시 서초구 원터6길 3 (원지동)6806동지섣달 꽃본듯이2023-09-20 16:23:52I2022-12-08 22:02:00.0식품소분업204847.138894437890.507732<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56432100003210000-109-2023-000112023-10-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1.3137-900서울특별시 서초구 우면동 66-2 지하1층 133호서울특별시 서초구 바우뫼로7길 8, 지하1층 133호 (우면동)6762바로빈스 주식회사2023-10-10 16:23:44I2022-10-30 23:02:00.0식품소분업202175.011113440963.759051<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56532100003210000-109-2023-000122023-11-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0137-160서울특별시 서초구 신원동 610 영동농협(청계산역)종합시설서울특별시 서초구 청계산로 197, 하나로마트 1층 (신원동)6802주식회사 만보수산2023-11-06 15:09:56I2022-11-01 00:08:00.0식품소분업204882.608756438400.973299<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56632100003210000-109-2023-000132023-11-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0137-180서울특별시 서초구 내곡동 376 서울영동농협종합시설서울특별시 서초구 헌릉로 176, 하나로마트 1층 (내곡동)6800주식회사 만보수산2023-11-06 15:10:11I2022-11-01 00:08:00.0식품소분업205185.318388439369.980699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56732100003210000-109-2023-000142023-05-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0137-040서울특별시 서초구 반포동 0 원베일리 스퀘어 B151호서울특별시 서초구 반포대로 291, 원베일리 스퀘어 B151호 (반포동)6506김치얼스2024-02-27 16:37:54I2023-12-01 22:09:00.0식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56832100003210000-109-2024-000012024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.65137-927서울특별시 서초구 서초동 1451-21 1층서울특별시 서초구 효령로52길 18, 1층 (서초동)6716부스스2024-01-19 15:09:12I2023-11-30 22:01:00.0식품소분업201070.923487442367.351699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56932100003210000-109-2024-000022024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0137-867서울특별시 서초구 서초동 1452-7 신빌딩 1층 102호서울특별시 서초구 남부순환로325길 17, 신빌딩 1층 102호 (서초동)6717젬인브라운서초2024-04-30 09:43:04I2023-12-05 00:02:00.0식품소분업201221.213519442203.180545<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
57032100003210000-109-2024-000032024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.0137-841서울특별시 서초구 방배동 899-3 401호서울특별시 서초구 방배로 140, 401호 (방배동)6664(주)토데스2024-05-08 17:42:25I2023-12-04 23:00:00.0식품소분업199466.639207442699.894714<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>