Overview

Dataset statistics

Number of variables44
Number of observations865
Missing cells9431
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory317.7 KiB
Average record size in memory376.2 B

Variable types

Categorical17
Text6
DateTime4
Unsupported7
Numeric9
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18274/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (52.2%)Imbalance
영업상태명 is highly imbalanced (52.2%)Imbalance
상세영업상태코드 is highly imbalanced (52.2%)Imbalance
상세영업상태명 is highly imbalanced (52.2%)Imbalance
업태구분명 is highly imbalanced (60.8%)Imbalance
남성종사자수 is highly imbalanced (70.0%)Imbalance
여성종사자수 is highly imbalanced (70.3%)Imbalance
영업장주변구분명 is highly imbalanced (59.4%)Imbalance
등급구분명 is highly imbalanced (53.5%)Imbalance
총인원 is highly imbalanced (77.2%)Imbalance
인허가취소일자 has 865 (100.0%) missing valuesMissing
폐업일자 has 89 (10.3%) missing valuesMissing
휴업시작일자 has 865 (100.0%) missing valuesMissing
휴업종료일자 has 865 (100.0%) missing valuesMissing
재개업일자 has 865 (100.0%) missing valuesMissing
전화번호 has 207 (23.9%) missing valuesMissing
소재지면적 has 60 (6.9%) missing valuesMissing
도로명주소 has 408 (47.2%) missing valuesMissing
도로명우편번호 has 415 (48.0%) missing valuesMissing
좌표정보(X) has 9 (1.0%) missing valuesMissing
좌표정보(Y) has 9 (1.0%) missing valuesMissing
공장판매직종업원수 has 343 (39.7%) missing valuesMissing
공장생산직종업원수 has 341 (39.4%) missing valuesMissing
보증액 has 685 (79.2%) missing valuesMissing
월세액 has 686 (79.3%) missing valuesMissing
다중이용업소여부 has 61 (7.1%) missing valuesMissing
시설총규모 has 61 (7.1%) missing valuesMissing
전통업소지정번호 has 865 (100.0%) missing valuesMissing
전통업소주된음식 has 865 (100.0%) missing valuesMissing
홈페이지 has 865 (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
소재지면적 has 11 (1.3%) zerosZeros
공장판매직종업원수 has 514 (59.4%) zerosZeros
공장생산직종업원수 has 486 (56.2%) zerosZeros
보증액 has 166 (19.2%) zerosZeros
월세액 has 166 (19.2%) zerosZeros
시설총규모 has 637 (73.6%) zerosZeros

Reproduction

Analysis started2024-04-06 11:16:47.873472
Analysis finished2024-04-06 11:16:49.635121
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
3220000
865 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 865
100.0%

Length

2024-04-06T20:16:49.763958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:16:49.961596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 865
100.0%

관리번호
Text

UNIQUE 

Distinct865
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-06T20:16:50.296748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters19030
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

Unique865 ?
Unique (%)100.0%

Sample

1st row3220000-106-1899-01179
2nd row3220000-106-1975-00001
3rd row3220000-106-1987-00955
4th row3220000-106-1988-00001
5th row3220000-106-1988-00002
ValueCountFrequency (%)
3220000-106-1899-01179 1
 
0.1%
3220000-106-2012-00021 1
 
0.1%
3220000-106-2012-00034 1
 
0.1%
3220000-106-2012-00011 1
 
0.1%
3220000-106-2012-00012 1
 
0.1%
3220000-106-2012-00013 1
 
0.1%
3220000-106-2012-00014 1
 
0.1%
3220000-106-2012-00015 1
 
0.1%
3220000-106-2012-00016 1
 
0.1%
3220000-106-2012-00017 1
 
0.1%
Other values (855) 855
98.8%
2024-04-06T20:16:50.949794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8019
42.1%
2 2904
 
15.3%
- 2595
 
13.6%
1 1907
 
10.0%
3 1139
 
6.0%
6 1063
 
5.6%
9 572
 
3.0%
8 224
 
1.2%
4 216
 
1.1%
5 198
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16435
86.4%
Dash Punctuation 2595
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8019
48.8%
2 2904
 
17.7%
1 1907
 
11.6%
3 1139
 
6.9%
6 1063
 
6.5%
9 572
 
3.5%
8 224
 
1.4%
4 216
 
1.3%
5 198
 
1.2%
7 193
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 2595
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8019
42.1%
2 2904
 
15.3%
- 2595
 
13.6%
1 1907
 
10.0%
3 1139
 
6.0%
6 1063
 
5.6%
9 572
 
3.0%
8 224
 
1.2%
4 216
 
1.1%
5 198
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8019
42.1%
2 2904
 
15.3%
- 2595
 
13.6%
1 1907
 
10.0%
3 1139
 
6.0%
6 1063
 
5.6%
9 572
 
3.0%
8 224
 
1.2%
4 216
 
1.1%
5 198
 
1.0%

인허가일자
Date

Distinct786
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
Minimum1975-10-11 00:00:00
Maximum2024-03-28 00:00:00
2024-04-06T20:16:51.293025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:16:51.542448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
3
776 
1
89 

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 (%)
3 776
89.7%
1 89
 
10.3%

Length

2024-04-06T20:16:51.798615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:16:51.963674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 776
89.7%
1 89
 
10.3%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
폐업
776 
영업/정상
89 

Length

Max length5
Median length2
Mean length2.3086705
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 776
89.7%
영업/정상 89
 
10.3%

Length

2024-04-06T20:16:52.295748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:16:52.476549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 776
89.7%
영업/정상 89
 
10.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2
776 
1
89 

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 (%)
2 776
89.7%
1 89
 
10.3%

Length

2024-04-06T20:16:52.644963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:16:52.824339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 776
89.7%
1 89
 
10.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
폐업
776 
영업
89 

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 776
89.7%
영업 89
 
10.3%

Length

2024-04-06T20:16:53.026075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:16:53.200224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 776
89.7%
영업 89
 
10.3%

폐업일자
Date

MISSING 

Distinct653
Distinct (%)84.1%
Missing89
Missing (%)10.3%
Memory size6.9 KiB
Minimum1992-10-06 00:00:00
Maximum2024-01-19 00:00:00
2024-04-06T20:16:53.394567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:16:53.670559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

전화번호
Text

MISSING 

Distinct626
Distinct (%)95.1%
Missing207
Missing (%)23.9%
Memory size6.9 KiB
2024-04-06T20:16:54.200860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.268997
Min length2

Characters and Unicode

Total characters6757
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

Unique606 ?
Unique (%)92.1%

Sample

1st row02 5387575
2nd row02 5674605
3rd row0205761400
4th row02 5753532
5th row02 5482511
ValueCountFrequency (%)
02 459
36.0%
070 24
 
1.9%
512 7
 
0.5%
555 6
 
0.5%
515 5
 
0.4%
540 5
 
0.4%
578 5
 
0.4%
546 5
 
0.4%
566 4
 
0.3%
568 4
 
0.3%
Other values (683) 750
58.9%
2024-04-06T20:16:55.005197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1085
16.1%
2 974
14.4%
5 877
13.0%
820
12.1%
4 581
8.6%
1 450
6.7%
3 436
6.5%
6 431
 
6.4%
7 420
 
6.2%
8 386
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5937
87.9%
Space Separator 820
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1085
18.3%
2 974
16.4%
5 877
14.8%
4 581
9.8%
1 450
7.6%
3 436
7.3%
6 431
 
7.3%
7 420
 
7.1%
8 386
 
6.5%
9 297
 
5.0%
Space Separator
ValueCountFrequency (%)
820
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6757
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1085
16.1%
2 974
14.4%
5 877
13.0%
820
12.1%
4 581
8.6%
1 450
6.7%
3 436
6.5%
6 431
 
6.4%
7 420
 
6.2%
8 386
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6757
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1085
16.1%
2 974
14.4%
5 877
13.0%
820
12.1%
4 581
8.6%
1 450
6.7%
3 436
6.5%
6 431
 
6.4%
7 420
 
6.2%
8 386
 
5.7%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct589
Distinct (%)73.2%
Missing60
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean69.942683
Minimum0
Maximum512.11
Zeros11
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:16:55.332946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.188
Q123.8
median49.5
Q398.4
95-th percentile198.332
Maximum512.11
Range512.11
Interquartile range (IQR)74.6

Descriptive statistics

Standard deviation68.640936
Coefficient of variation (CV)0.98138838
Kurtosis8.0387177
Mean69.942683
Median Absolute Deviation (MAD)30.88
Skewness2.3410027
Sum56303.86
Variance4711.5782
MonotonicityNot monotonic
2024-04-06T20:16:55.600626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 11
 
1.3%
66.0 10
 
1.2%
20.0 10
 
1.2%
33.0 9
 
1.0%
66.11 7
 
0.8%
10.0 7
 
0.8%
9.0 6
 
0.7%
30.0 6
 
0.7%
6.6 6
 
0.7%
19.8 6
 
0.7%
Other values (579) 727
84.0%
(Missing) 60
 
6.9%
ValueCountFrequency (%)
0.0 11
1.3%
3.0 1
 
0.1%
3.3 3
 
0.3%
4.0 1
 
0.1%
4.16 1
 
0.1%
4.17 1
 
0.1%
4.4 1
 
0.1%
4.95 1
 
0.1%
5.0 1
 
0.1%
5.75 1
 
0.1%
ValueCountFrequency (%)
512.11 1
0.1%
470.15 1
0.1%
452.6 1
0.1%
428.0 1
0.1%
413.0 1
0.1%
400.68 1
0.1%
389.3 1
0.1%
354.7 1
0.1%
335.34 1
0.1%
317.64 1
0.1%

소재지우편번호
Text

Distinct201
Distinct (%)23.3%
Missing1
Missing (%)0.1%
Memory size6.9 KiB
2024-04-06T20:16:56.074801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0381944
Min length6

Characters and Unicode

Total characters5217
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

Unique67 ?
Unique (%)7.8%

Sample

1st row135909
2nd row135935
3rd row135925
4th row135945
5th row135957
ValueCountFrequency (%)
135855 21
 
2.4%
135888 19
 
2.2%
135945 17
 
2.0%
135509 17
 
2.0%
135962 17
 
2.0%
135819 17
 
2.0%
135891 16
 
1.9%
135964 16
 
1.9%
135860 16
 
1.9%
135896 16
 
1.9%
Other values (191) 692
80.1%
2024-04-06T20:16:56.861336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1153
22.1%
1 1048
20.1%
3 997
19.1%
8 607
11.6%
9 542
10.4%
0 195
 
3.7%
2 179
 
3.4%
6 178
 
3.4%
4 166
 
3.2%
7 119
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5184
99.4%
Dash Punctuation 33
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1153
22.2%
1 1048
20.2%
3 997
19.2%
8 607
11.7%
9 542
10.5%
0 195
 
3.8%
2 179
 
3.5%
6 178
 
3.4%
4 166
 
3.2%
7 119
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5217
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1153
22.1%
1 1048
20.1%
3 997
19.1%
8 607
11.6%
9 542
10.4%
0 195
 
3.7%
2 179
 
3.4%
6 178
 
3.4%
4 166
 
3.2%
7 119
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1153
22.1%
1 1048
20.1%
3 997
19.1%
8 607
11.6%
9 542
10.4%
0 195
 
3.7%
2 179
 
3.4%
6 178
 
3.4%
4 166
 
3.2%
7 119
 
2.3%

지번주소
Text

Distinct842
Distinct (%)97.5%
Missing1
Missing (%)0.1%
Memory size6.9 KiB
2024-04-06T20:16:57.238672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length27.084491
Min length16

Characters and Unicode

Total characters23401
Distinct characters262
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

Unique821 ?
Unique (%)95.0%

Sample

1st row서울특별시 강남구 역삼동 641-7번지 지상2층
2nd row서울특별시 강남구 역삼동 826-37번지
3rd row서울특별시 강남구 역삼동 749-22번지
4th row서울특별시 강남구 일원동 643-5번지
5th row서울특별시 강남구 청담동 125-16번지
ValueCountFrequency (%)
서울특별시 863
20.1%
강남구 863
20.1%
역삼동 134
 
3.1%
논현동 128
 
3.0%
신사동 122
 
2.8%
지하1층 120
 
2.8%
대치동 102
 
2.4%
삼성동 94
 
2.2%
지상1층 87
 
2.0%
개포동 85
 
2.0%
Other values (1158) 1688
39.4%
2024-04-06T20:16:57.966644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4181
 
17.9%
1 1261
 
5.4%
지 1096
 
4.7%
동 904
 
3.9%
구 882
 
3.8%
남 875
 
3.7%
서 874
 
3.7%
시 869
 
3.7%
강 866
 
3.7%
울 865
 
3.7%
Other values (252) 10728
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13609
58.2%
Decimal Number 4688
 
20.0%
Space Separator 4181
 
17.9%
Dash Punctuation 818
 
3.5%
Uppercase Letter 64
 
0.3%
Other Punctuation 25
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1096
 
8.1%
동 904
 
6.6%
구 882
 
6.5%
남 875
 
6.4%
서 874
 
6.4%
시 869
 
6.4%
강 866
 
6.4%
울 865
 
6.4%
별 865
 
6.4%
특 863
 
6.3%
Other values (215) 4650
34.2%
Uppercase Letter
ValueCountFrequency (%)
B 26
40.6%
S 6
 
9.4%
A 5
 
7.8%
E 4
 
6.2%
T 3
 
4.7%
K 3
 
4.7%
W 2
 
3.1%
O 2
 
3.1%
M 2
 
3.1%
P 2
 
3.1%
Other values (8) 9
 
14.1%
Decimal Number
ValueCountFrequency (%)
1 1261
26.9%
2 599
12.8%
6 425
 
9.1%
0 405
 
8.6%
5 393
 
8.4%
4 365
 
7.8%
3 362
 
7.7%
7 324
 
6.9%
9 296
 
6.3%
8 258
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 23
92.0%
. 1
 
4.0%
? 1
 
4.0%
Space Separator
ValueCountFrequency (%)
4181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 818
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13609
58.2%
Common 9727
41.6%
Latin 65
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1096
 
8.1%
동 904
 
6.6%
구 882
 
6.5%
남 875
 
6.4%
서 874
 
6.4%
시 869
 
6.4%
강 866
 
6.4%
울 865
 
6.4%
별 865
 
6.4%
특 863
 
6.3%
Other values (215) 4650
34.2%
Latin
ValueCountFrequency (%)
B 26
40.0%
S 6
 
9.2%
A 5
 
7.7%
E 4
 
6.2%
T 3
 
4.6%
K 3
 
4.6%
W 2
 
3.1%
O 2
 
3.1%
M 2
 
3.1%
P 2
 
3.1%
Other values (9) 10
 
15.4%
Common
ValueCountFrequency (%)
4181
43.0%
1 1261
 
13.0%
- 818
 
8.4%
2 599
 
6.2%
6 425
 
4.4%
0 405
 
4.2%
5 393
 
4.0%
4 365
 
3.8%
3 362
 
3.7%
7 324
 
3.3%
Other values (8) 594
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13609
58.2%
ASCII 9792
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4181
42.7%
1 1261
 
12.9%
- 818
 
8.4%
2 599
 
6.1%
6 425
 
4.3%
0 405
 
4.1%
5 393
 
4.0%
4 365
 
3.7%
3 362
 
3.7%
7 324
 
3.3%
Other values (27) 659
 
6.7%
Hangul
ValueCountFrequency (%)
지 1096
 
8.1%
동 904
 
6.6%
구 882
 
6.5%
남 875
 
6.4%
서 874
 
6.4%
시 869
 
6.4%
강 866
 
6.4%
울 865
 
6.4%
별 865
 
6.4%
특 863
 
6.3%
Other values (215) 4650
34.2%

도로명주소
Text

MISSING 

Distinct456
Distinct (%)99.8%
Missing408
Missing (%)47.2%
Memory size6.9 KiB
2024-04-06T20:16:58.500402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length33.052516
Min length22

Characters and Unicode

Total characters15105
Distinct characters242
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

Unique455 ?
Unique (%)99.6%

Sample

1st row서울특별시 강남구 강남대로118길 29, 지하1층 (논현동)
2nd row서울특별시 강남구 삼성로 14 (개포동,개포주공상가 마동 105호)
3rd row서울특별시 강남구 학동로4길 31 (논현동)
4th row서울특별시 강남구 압구정로29길 71 (압구정동)
5th row서울특별시 강남구 강남대로118길 34 (논현동)
ValueCountFrequency (%)
서울특별시 456
 
16.0%
강남구 456
 
16.0%
지하1층 74
 
2.6%
1층 72
 
2.5%
신사동 62
 
2.2%
논현동 61
 
2.1%
역삼동 60
 
2.1%
삼성동 46
 
1.6%
지상1층 39
 
1.4%
도곡동 37
 
1.3%
Other values (736) 1488
52.2%
2024-04-06T20:16:59.295081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2394
 
15.8%
1 765
 
5.1%
동 515
 
3.4%
구 500
 
3.3%
남 498
 
3.3%
강 484
 
3.2%
, 471
 
3.1%
서 462
 
3.1%
로 461
 
3.1%
) 459
 
3.0%
Other values (232) 8096
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8676
57.4%
Decimal Number 2522
 
16.7%
Space Separator 2394
 
15.8%
Other Punctuation 472
 
3.1%
Close Punctuation 459
 
3.0%
Open Punctuation 459
 
3.0%
Uppercase Letter 66
 
0.4%
Dash Punctuation 54
 
0.4%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 515
 
5.9%
구 500
 
5.8%
남 498
 
5.7%
강 484
 
5.6%
서 462
 
5.3%
로 461
 
5.3%
시 457
 
5.3%
별 456
 
5.3%
특 456
 
5.3%
울 456
 
5.3%
Other values (198) 3931
45.3%
Uppercase Letter
ValueCountFrequency (%)
B 27
40.9%
S 7
 
10.6%
E 4
 
6.1%
A 4
 
6.1%
T 3
 
4.5%
I 3
 
4.5%
O 2
 
3.0%
K 2
 
3.0%
F 2
 
3.0%
U 2
 
3.0%
Other values (7) 10
 
15.2%
Decimal Number
ValueCountFrequency (%)
1 765
30.3%
2 344
13.6%
3 265
 
10.5%
0 234
 
9.3%
4 218
 
8.6%
6 186
 
7.4%
5 182
 
7.2%
7 134
 
5.3%
8 111
 
4.4%
9 83
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 471
99.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2394
100.0%
Close Punctuation
ValueCountFrequency (%)
) 459
100.0%
Open Punctuation
ValueCountFrequency (%)
( 459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8676
57.4%
Common 6363
42.1%
Latin 66
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 515
 
5.9%
구 500
 
5.8%
남 498
 
5.7%
강 484
 
5.6%
서 462
 
5.3%
로 461
 
5.3%
시 457
 
5.3%
별 456
 
5.3%
특 456
 
5.3%
울 456
 
5.3%
Other values (198) 3931
45.3%
Common
ValueCountFrequency (%)
2394
37.6%
1 765
 
12.0%
, 471
 
7.4%
) 459
 
7.2%
( 459
 
7.2%
2 344
 
5.4%
3 265
 
4.2%
0 234
 
3.7%
4 218
 
3.4%
6 186
 
2.9%
Other values (7) 568
 
8.9%
Latin
ValueCountFrequency (%)
B 27
40.9%
S 7
 
10.6%
E 4
 
6.1%
A 4
 
6.1%
T 3
 
4.5%
I 3
 
4.5%
O 2
 
3.0%
K 2
 
3.0%
F 2
 
3.0%
U 2
 
3.0%
Other values (7) 10
 
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8676
57.4%
ASCII 6429
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2394
37.2%
1 765
 
11.9%
, 471
 
7.3%
) 459
 
7.1%
( 459
 
7.1%
2 344
 
5.4%
3 265
 
4.1%
0 234
 
3.6%
4 218
 
3.4%
6 186
 
2.9%
Other values (24) 634
 
9.9%
Hangul
ValueCountFrequency (%)
동 515
 
5.9%
구 500
 
5.8%
남 498
 
5.7%
강 484
 
5.6%
서 462
 
5.3%
로 461
 
5.3%
시 457
 
5.3%
별 456
 
5.3%
특 456
 
5.3%
울 456
 
5.3%
Other values (198) 3931
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct196
Distinct (%)43.6%
Missing415
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean6165.8644
Minimum6002
Maximum10301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:16:59.542913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6002
5-th percentile6017.45
Q16054.25
median6153
Q36256.75
95-th percentile6339
Maximum10301
Range4299
Interquartile range (IQR)202.5

Descriptive statistics

Standard deviation223.40467
Coefficient of variation (CV)0.036232497
Kurtosis262.0153
Mean6165.8644
Median Absolute Deviation (MAD)99
Skewness14.188808
Sum2774639
Variance49909.645
MonotonicityNot monotonic
2024-04-06T20:16:59.767843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6302 13
 
1.5%
6028 11
 
1.3%
6154 8
 
0.9%
6015 7
 
0.8%
6034 6
 
0.7%
6267 6
 
0.7%
6194 5
 
0.6%
6054 5
 
0.6%
6021 5
 
0.6%
6059 5
 
0.6%
Other values (186) 379
43.8%
(Missing) 415
48.0%
ValueCountFrequency (%)
6002 2
 
0.2%
6004 1
 
0.1%
6006 1
 
0.1%
6008 2
 
0.2%
6013 1
 
0.1%
6014 4
0.5%
6015 7
0.8%
6017 5
0.6%
6018 4
0.5%
6019 4
0.5%
ValueCountFrequency (%)
10301 1
 
0.1%
6376 1
 
0.1%
6373 2
 
0.2%
6369 1
 
0.1%
6365 1
 
0.1%
6355 1
 
0.1%
6354 3
0.3%
6343 3
0.3%
6342 5
0.6%
6341 2
 
0.2%

사업장명
Text

Distinct826
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-06T20:17:00.232141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length6.6381503
Min length1

Characters and Unicode

Total characters5742
Distinct characters561
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

Unique791 ?
Unique (%)91.4%

Sample

1st row(주)생기나라
2nd row태극당
3rd row(주)신선식품
4th row피크닉도시락
5th row(주)나정식품
ValueCountFrequency (%)
주식회사 16
 
1.6%
홍삼나라 6
 
0.6%
얼음나라 4
 
0.4%
주)나정식품 3
 
0.3%
주)미스터커피 3
 
0.3%
커피 3
 
0.3%
홍삼농원 2
 
0.2%
슈크레 2
 
0.2%
아노후식공장 2
 
0.2%
다온식품 2
 
0.2%
Other values (898) 934
95.6%
2024-04-06T20:17:00.900171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 262
 
4.6%
) 249
 
4.3%
( 247
 
4.3%
스 184
 
3.2%
리 146
 
2.5%
이 146
 
2.5%
113
 
2.0%
식 112
 
2.0%
커 87
 
1.5%
품 83
 
1.4%
Other values (551) 4113
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4963
86.4%
Close Punctuation 249
 
4.3%
Open Punctuation 247
 
4.3%
Space Separator 113
 
2.0%
Uppercase Letter 86
 
1.5%
Lowercase Letter 57
 
1.0%
Decimal Number 19
 
0.3%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 262
 
5.3%
스 184
 
3.7%
리 146
 
2.9%
이 146
 
2.9%
식 112
 
2.3%
커 87
 
1.8%
품 83
 
1.7%
라 81
 
1.6%
피 79
 
1.6%
아 79
 
1.6%
Other values (500) 3704
74.6%
Uppercase Letter
ValueCountFrequency (%)
A 12
14.0%
E 10
11.6%
C 8
 
9.3%
B 7
 
8.1%
N 5
 
5.8%
M 5
 
5.8%
O 5
 
5.8%
T 5
 
5.8%
R 5
 
5.8%
L 4
 
4.7%
Other values (10) 20
23.3%
Lowercase Letter
ValueCountFrequency (%)
e 11
19.3%
a 8
14.0%
o 6
10.5%
r 5
8.8%
s 3
 
5.3%
d 3
 
5.3%
i 3
 
5.3%
n 3
 
5.3%
f 3
 
5.3%
t 2
 
3.5%
Other values (6) 10
17.5%
Decimal Number
ValueCountFrequency (%)
2 5
26.3%
7 3
15.8%
3 3
15.8%
1 2
 
10.5%
6 2
 
10.5%
8 1
 
5.3%
0 1
 
5.3%
9 1
 
5.3%
4 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
? 4
50.0%
. 3
37.5%
& 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 247
100.0%
Space Separator
ValueCountFrequency (%)
113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4963
86.4%
Common 636
 
11.1%
Latin 143
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 262
 
5.3%
스 184
 
3.7%
리 146
 
2.9%
이 146
 
2.9%
식 112
 
2.3%
커 87
 
1.8%
품 83
 
1.7%
라 81
 
1.6%
피 79
 
1.6%
아 79
 
1.6%
Other values (500) 3704
74.6%
Latin
ValueCountFrequency (%)
A 12
 
8.4%
e 11
 
7.7%
E 10
 
7.0%
C 8
 
5.6%
a 8
 
5.6%
B 7
 
4.9%
o 6
 
4.2%
N 5
 
3.5%
M 5
 
3.5%
O 5
 
3.5%
Other values (26) 66
46.2%
Common
ValueCountFrequency (%)
) 249
39.2%
( 247
38.8%
113
17.8%
2 5
 
0.8%
? 4
 
0.6%
7 3
 
0.5%
3 3
 
0.5%
. 3
 
0.5%
1 2
 
0.3%
6 2
 
0.3%
Other values (5) 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4963
86.4%
ASCII 779
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 262
 
5.3%
스 184
 
3.7%
리 146
 
2.9%
이 146
 
2.9%
식 112
 
2.3%
커 87
 
1.8%
품 83
 
1.7%
라 81
 
1.6%
피 79
 
1.6%
아 79
 
1.6%
Other values (500) 3704
74.6%
ASCII
ValueCountFrequency (%)
) 249
32.0%
( 247
31.7%
113
14.5%
A 12
 
1.5%
e 11
 
1.4%
E 10
 
1.3%
C 8
 
1.0%
a 8
 
1.0%
B 7
 
0.9%
o 6
 
0.8%
Other values (41) 108
13.9%

최종수정일자
Date

Distinct665
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
Minimum2001-05-28 00:00:00
Maximum2024-03-29 13:46:49
2024-04-06T20:17:01.178845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:17:01.512914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
I
694 
U
171 

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 694
80.2%
U 171
 
19.8%

Length

2024-04-06T20:17:01.827821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:02.011366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 694
80.2%
u 171
 
19.8%

데이터갱신일자
Date

Distinct168
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 23:03:00
2024-04-06T20:17:02.263243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:17:02.634120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
식품제조가공업
677 
기타 식품제조가공업
185 
도시락제조업
 
2
PB제품 제조업체
 
1

Length

Max length10
Median length7
Mean length7.6416185
Min length6

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 677
78.3%
기타 식품제조가공업 185
 
21.4%
도시락제조업 2
 
0.2%
PB제품 제조업체 1
 
0.1%

Length

2024-04-06T20:17:02.900640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:03.187932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 862
82.0%
기타 185
 
17.6%
도시락제조업 2
 
0.2%
pb제품 1
 
0.1%
제조업체 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct717
Distinct (%)83.8%
Missing9
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean203890.02
Minimum181309.92
Maximum209384.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:03.813059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181309.92
5-th percentile202003.93
Q1202988.02
median203798.66
Q3204615.15
95-th percentile207157.69
Maximum209384.71
Range28074.785
Interquartile range (IQR)1627.1273

Descriptive statistics

Standard deviation1595.6326
Coefficient of variation (CV)0.0078259477
Kurtosis46.684321
Mean203890.02
Median Absolute Deviation (MAD)814.58914
Skewness-2.6565824
Sum1.7452986 × 108
Variance2546043.4
MonotonicityNot monotonic
2024-04-06T20:17:04.051733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205707.089399978 14
 
1.6%
205130.591678902 5
 
0.6%
204669.543366778 5
 
0.6%
202398.594377612 4
 
0.5%
204652.111034177 4
 
0.5%
205707.361024519 3
 
0.3%
207950.137458581 3
 
0.3%
205034.15838707 3
 
0.3%
203121.203642767 3
 
0.3%
203279.713576614 3
 
0.3%
Other values (707) 809
93.5%
(Missing) 9
 
1.0%
ValueCountFrequency (%)
181309.923908659 1
0.1%
201646.385389914 1
0.1%
201650.787158848 1
0.1%
201658.416590861 1
0.1%
201667.786866215 1
0.1%
201681.348293082 1
0.1%
201683.414501672 1
0.1%
201687.568509064 1
0.1%
201695.733022919 1
0.1%
201695.800640834 1
0.1%
ValueCountFrequency (%)
209384.708472884 1
 
0.1%
209090.360365095 1
 
0.1%
209083.642145052 1
 
0.1%
209038.198426983 1
 
0.1%
208547.303164015 1
 
0.1%
208334.06570268 1
 
0.1%
207950.137458581 3
0.3%
207914.471699463 2
0.2%
207679.579278773 1
 
0.1%
207669.423687645 2
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct717
Distinct (%)83.8%
Missing9
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean444762.18
Minimum440112.99
Maximum463399.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:04.325377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440112.99
5-th percentile441658.68
Q1443451.12
median444862.03
Q3446282.45
95-th percentile447088.52
Maximum463399.03
Range23286.039
Interquartile range (IQR)2831.3381

Descriptive statistics

Standard deviation1818.9581
Coefficient of variation (CV)0.004089732
Kurtosis11.58444
Mean444762.18
Median Absolute Deviation (MAD)1415.6682
Skewness0.9930346
Sum3.8071642 × 108
Variance3308608.6
MonotonicityNot monotonic
2024-04-06T20:17:04.558030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443914.194133105 14
 
1.6%
445590.096837802 5
 
0.6%
443873.621189048 5
 
0.6%
447864.763737276 4
 
0.5%
445353.174360925 4
 
0.5%
445550.602656568 3
 
0.3%
442526.253635088 3
 
0.3%
446675.932361885 3
 
0.3%
446464.379990564 3
 
0.3%
446829.052325387 3
 
0.3%
Other values (707) 809
93.5%
(Missing) 9
 
1.0%
ValueCountFrequency (%)
440112.987487173 1
 
0.1%
440518.651807226 1
 
0.1%
441086.596187726 1
 
0.1%
441163.795720684 1
 
0.1%
441219.494091723 1
 
0.1%
441257.215350061 3
0.3%
441259.39158021 1
 
0.1%
441279.306789347 1
 
0.1%
441282.675442575 1
 
0.1%
441298.354779877 1
 
0.1%
ValueCountFrequency (%)
463399.026581454 1
 
0.1%
447864.763737276 4
0.5%
447782.51322707 2
0.2%
447663.86257666 1
 
0.1%
447521.520319158 2
0.2%
447386.554980471 1
 
0.1%
447369.579851952 2
0.2%
447333.413958566 1
 
0.1%
447313.362226154 1
 
0.1%
447300.581590235 1
 
0.1%

위생업태명
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
식품제조가공업
664 
기타 식품제조가공업
138 
<NA>
 
61
도시락제조업
 
2

Length

Max length10
Median length7
Mean length7.2647399
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 664
76.8%
기타 식품제조가공업 138
 
16.0%
<NA> 61
 
7.1%
도시락제조업 2
 
0.2%

Length

2024-04-06T20:17:04.774694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:05.040505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 802
80.0%
기타 138
 
13.8%
na 61
 
6.1%
도시락제조업 2
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
704 
0
151 
1
 
5
3
 
2
2
 
2

Length

Max length4
Median length4
Mean length3.4416185
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 704
81.4%
0 151
 
17.5%
1 5
 
0.6%
3 2
 
0.2%
2 2
 
0.2%
4 1
 
0.1%

Length

2024-04-06T20:17:05.362611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:05.600261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 704
81.4%
0 151
 
17.5%
1 5
 
0.6%
3 2
 
0.2%
2 2
 
0.2%
4 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
705 
0
151 
1
 
4
2
 
3
5
 
1

Length

Max length4
Median length4
Mean length3.4450867
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row5
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 705
81.5%
0 151
 
17.5%
1 4
 
0.5%
2 3
 
0.3%
5 1
 
0.1%
4 1
 
0.1%

Length

2024-04-06T20:17:05.799108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:05.991794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 705
81.5%
0 151
 
17.5%
1 4
 
0.5%
2 3
 
0.3%
5 1
 
0.1%
4 1
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
688 
기타
166 
주택가주변
 
7
아파트지역
 
4

Length

Max length5
Median length4
Mean length3.6289017
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 688
79.5%
기타 166
 
19.2%
주택가주변 7
 
0.8%
아파트지역 4
 
0.5%

Length

2024-04-06T20:17:06.202700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:06.388340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 688
79.5%
기타 166
 
19.2%
주택가주변 7
 
0.8%
아파트지역 4
 
0.5%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
688 
기타
116 
자율
 
60
갑
 
1

Length

Max length4
Median length4
Mean length3.5895954
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 688
79.5%
기타 116
 
13.4%
자율 60
 
6.9%
갑 1
 
0.1%

Length

2024-04-06T20:17:06.612364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:06.807920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 688
79.5%
기타 116
 
13.4%
자율 60
 
6.9%
갑 1
 
0.1%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
642 
상수도전용
222 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.2578035
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 642
74.2%
상수도전용 222
 
25.7%
지하수전용 1
 
0.1%

Length

2024-04-06T20:17:07.003724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:07.168741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 642
74.2%
상수도전용 222
 
25.7%
지하수전용 1
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
833 
0
 
32

Length

Max length4
Median length4
Mean length3.8890173
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> 833
96.3%
0 32
 
3.7%

Length

2024-04-06T20:17:07.341704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:07.535493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 833
96.3%
0 32
 
3.7%

본사종업원수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
0
520 
<NA>
345 

Length

Max length4
Median length1
Mean length2.1965318
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 520
60.1%
<NA> 345
39.9%

Length

2024-04-06T20:17:07.749133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:07.917865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 520
60.1%
na 345
39.9%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
0
519 
<NA>
343 
1
 
3

Length

Max length4
Median length1
Mean length2.1895954
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 519
60.0%
<NA> 343
39.7%
1 3
 
0.3%

Length

2024-04-06T20:17:08.103383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:08.340808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 519
60.0%
na 343
39.7%
1 3
 
0.3%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.1%
Missing343
Missing (%)39.7%
Infinite0
Infinite (%)0.0%
Mean0.076628352
Minimum0
Maximum20
Zeros514
Zeros (%)59.4%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:08.500336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.95073955
Coefficient of variation (CV)12.407151
Kurtosis374.5868
Mean0.076628352
Median Absolute Deviation (MAD)0
Skewness18.397128
Sum40
Variance0.90390569
MonotonicityNot monotonic
2024-04-06T20:17:08.690680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 514
59.4%
5 2
 
0.2%
3 2
 
0.2%
1 2
 
0.2%
20 1
 
0.1%
2 1
 
0.1%
(Missing) 343
39.7%
ValueCountFrequency (%)
0 514
59.4%
1 2
 
0.2%
2 1
 
0.1%
3 2
 
0.2%
5 2
 
0.2%
20 1
 
0.1%
ValueCountFrequency (%)
20 1
 
0.1%
5 2
 
0.2%
3 2
 
0.2%
2 1
 
0.1%
1 2
 
0.2%
0 514
59.4%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)2.3%
Missing341
Missing (%)39.4%
Infinite0
Infinite (%)0.0%
Mean0.31679389
Minimum0
Maximum18
Zeros486
Zeros (%)56.2%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:08.885320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4590734
Coefficient of variation (CV)4.6057498
Kurtosis56.530534
Mean0.31679389
Median Absolute Deviation (MAD)0
Skewness6.6161069
Sum166
Variance2.1288952
MonotonicityNot monotonic
2024-04-06T20:17:09.066301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 486
56.2%
2 7
 
0.8%
1 7
 
0.8%
5 6
 
0.7%
7 4
 
0.5%
3 4
 
0.5%
4 4
 
0.5%
6 2
 
0.2%
12 1
 
0.1%
8 1
 
0.1%
Other values (2) 2
 
0.2%
(Missing) 341
39.4%
ValueCountFrequency (%)
0 486
56.2%
1 7
 
0.8%
2 7
 
0.8%
3 4
 
0.5%
4 4
 
0.5%
5 6
 
0.7%
6 2
 
0.2%
7 4
 
0.5%
8 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
18 1
 
0.1%
12 1
 
0.1%
9 1
 
0.1%
8 1
 
0.1%
7 4
0.5%
6 2
 
0.2%
5 6
0.7%
4 4
0.5%
3 4
0.5%
2 7
0.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
<NA>
488 
임대
200 
자가
177 

Length

Max length4
Median length4
Mean length3.1283237
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> 488
56.4%
임대 200
23.1%
자가 177
 
20.5%

Length

2024-04-06T20:17:09.323040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:17:09.521833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 488
56.4%
임대 200
23.1%
자가 177
 
20.5%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.1%
Missing685
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean3981055.6
Minimum0
Maximum2 × 108
Zeros166
Zeros (%)19.2%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:09.714137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile30000000
Maximum2 × 108
Range2 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19471091
Coefficient of variation (CV)4.8909367
Kurtosis62.77292
Mean3981055.6
Median Absolute Deviation (MAD)0
Skewness7.2590729
Sum7.1659 × 108
Variance3.7912337 × 1014
MonotonicityNot monotonic
2024-04-06T20:17:09.911754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 166
 
19.2%
30000000 4
 
0.5%
10000000 2
 
0.2%
50000000 1
 
0.1%
12000000 1
 
0.1%
90000000 1
 
0.1%
200000000 1
 
0.1%
100000000 1
 
0.1%
64590000 1
 
0.1%
20000000 1
 
0.1%
(Missing) 685
79.2%
ValueCountFrequency (%)
0 166
19.2%
10000000 2
 
0.2%
12000000 1
 
0.1%
20000000 1
 
0.1%
30000000 4
 
0.5%
40000000 1
 
0.1%
50000000 1
 
0.1%
64590000 1
 
0.1%
90000000 1
 
0.1%
100000000 1
 
0.1%
ValueCountFrequency (%)
200000000 1
 
0.1%
100000000 1
 
0.1%
90000000 1
 
0.1%
64590000 1
 
0.1%
50000000 1
 
0.1%
40000000 1
 
0.1%
30000000 4
0.5%
20000000 1
 
0.1%
12000000 1
 
0.1%
10000000 2
0.2%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)6.7%
Missing686
Missing (%)79.3%
Infinite0
Infinite (%)0.0%
Mean248135.75
Minimum0
Maximum19000000
Zeros166
Zeros (%)19.2%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:10.145326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1305000
Maximum19000000
Range19000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1532929.6
Coefficient of variation (CV)6.1777859
Kurtosis127.69176
Mean248135.75
Median Absolute Deviation (MAD)0
Skewness10.669297
Sum44416300
Variance2.3498731 × 1012
MonotonicityNot monotonic
2024-04-06T20:17:10.356120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 166
 
19.2%
1000000 2
 
0.2%
2000000 2
 
0.2%
1250000 1
 
0.1%
3800000 1
 
0.1%
19000000 1
 
0.1%
845000 1
 
0.1%
3000000 1
 
0.1%
2300000 1
 
0.1%
1900000 1
 
0.1%
Other values (2) 2
 
0.2%
(Missing) 686
79.3%
ValueCountFrequency (%)
0 166
19.2%
845000 1
 
0.1%
1000000 2
 
0.2%
1250000 1
 
0.1%
1800000 1
 
0.1%
1900000 1
 
0.1%
2000000 2
 
0.2%
2300000 1
 
0.1%
3000000 1
 
0.1%
3800000 1
 
0.1%
ValueCountFrequency (%)
19000000 1
0.1%
4521300 1
0.1%
3800000 1
0.1%
3000000 1
0.1%
2300000 1
0.1%
2000000 2
0.2%
1900000 1
0.1%
1800000 1
0.1%
1250000 1
0.1%
1000000 2
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing61
Missing (%)7.1%
Memory size1.8 KiB
False
804 
(Missing)
 
61
ValueCountFrequency (%)
False 804
92.9%
(Missing) 61
 
7.1%
2024-04-06T20:17:10.529275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct134
Distinct (%)16.7%
Missing61
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean15.125784
Minimum0
Maximum512.11
Zeros637
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2024-04-06T20:17:10.720352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile98.9715
Maximum512.11
Range512.11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation44.97244
Coefficient of variation (CV)2.9732304
Kurtosis35.043836
Mean15.125784
Median Absolute Deviation (MAD)0
Skewness4.9979191
Sum12161.13
Variance2022.5203
MonotonicityNot monotonic
2024-04-06T20:17:10.995658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 637
73.6%
33.0 6
 
0.7%
66.0 6
 
0.7%
20.0 3
 
0.3%
19.0 3
 
0.3%
8.0 3
 
0.3%
10.0 3
 
0.3%
30.0 3
 
0.3%
6.6 3
 
0.3%
52.8 2
 
0.2%
Other values (124) 135
 
15.6%
(Missing) 61
 
7.1%
ValueCountFrequency (%)
0.0 637
73.6%
3.3 2
 
0.2%
4.0 1
 
0.1%
5.0 1
 
0.1%
6.0 1
 
0.1%
6.6 3
 
0.3%
7.56 1
 
0.1%
8.0 3
 
0.3%
8.91 1
 
0.1%
8.92 1
 
0.1%
ValueCountFrequency (%)
512.11 1
0.1%
428.0 1
0.1%
292.0 1
0.1%
274.62 1
0.1%
262.49 1
0.1%
253.23 1
0.1%
240.0 1
0.1%
232.3 1
0.1%
219.84 1
0.1%
213.77 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing865
Missing (%)100.0%
Memory size7.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032200003220000-106-1899-0117919991006<NA>3폐업2폐업20020222<NA><NA><NA>02 538757518.62135909서울특별시 강남구 역삼동 641-7번지 지상2층<NA><NA>(주)생기나라2002-03-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업203081.738793444520.246867식품제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
132200003220000-106-1975-0000119751011<NA>3폐업2폐업19960904<NA><NA><NA>02 5674605<NA>135935서울특별시 강남구 역삼동 826-37번지<NA><NA>태극당2001-09-14 00:00:00I2018-08-31 23:59:59.0식품제조가공업202619.098126443688.691713식품제조가공업<NA><NA><NA><NA><NA><NA>00012<NA><NA><NA>N0.0<NA><NA><NA>
232200003220000-106-1987-0095519870724<NA>3폐업2폐업19990421<NA><NA><NA>0205761400126.44135925서울특별시 강남구 역삼동 749-22번지<NA><NA>(주)신선식품2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업203113.004912443772.381445식품제조가공업35기타기타상수도전용<NA>0008<NA><NA><NA>N0.0<NA><NA><NA>
332200003220000-106-1988-0000119880715<NA>3폐업2폐업19970704<NA><NA><NA>02 5753532<NA>135945서울특별시 강남구 일원동 643-5번지<NA><NA>피크닉도시락2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업207656.77533443327.738108식품제조가공업<NA><NA><NA><NA><NA><NA>0002<NA><NA><NA>N0.0<NA><NA><NA>
432200003220000-106-1988-0000219880213<NA>3폐업2폐업19941126<NA><NA><NA>02 5482511<NA>135957서울특별시 강남구 청담동 125-16번지<NA><NA>(주)나정식품2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업204526.082052446991.199463식품제조가공업<NA><NA><NA><NA><NA><NA>0006<NA><NA><NA>N0.0<NA><NA><NA>
532200003220000-106-1989-0000119890721<NA>3폐업2폐업19960724<NA><NA><NA>02 5530101<NA>135998서울특별시 강남구 대치동 937-0번지<NA><NA>그랜드절임식품2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업204669.543367443873.621189식품제조가공업<NA><NA><NA><NA><NA><NA>0007<NA><NA><NA>N0.0<NA><NA><NA>
632200003220000-106-1989-0000219890615<NA>3폐업2폐업19930806<NA><NA><NA>02 5687256<NA>135936서울특별시 강남구 역삼동 829-8번지<NA><NA>용원농산외식산업2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업202875.86531443608.987141식품제조가공업<NA><NA><NA><NA><NA><NA>0005<NA><NA><NA>N0.0<NA><NA><NA>
732200003220000-106-1989-0000319891023<NA>3폐업2폐업20030328<NA><NA><NA>02 5510893<NA>135090서울특별시 강남구 삼성동 159-1번지<NA><NA>(주)수라방2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업205340.631122445354.571117식품제조가공업<NA><NA><NA><NA><NA><NA>0007<NA><NA><NA>N0.0<NA><NA><NA>
832200003220000-106-1990-0053919901226<NA>3폐업2폐업19960724<NA><NA><NA>02 00000105.24135998서울특별시 강남구 대치동 937-0번지<NA><NA>그랜드백화점2001-09-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업204669.543367443873.621189식품제조가공업<NA><NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
932200003220000-106-1990-0097919900508<NA>3폐업2폐업20040706<NA><NA><NA>02057572130.0135964서울특별시 강남구 개포동 1231-16번지<NA><NA>세미식품2001-09-06 00:00:00I2018-08-31 23:59:59.0식품제조가공업204169.645441719.34식품제조가공업42주택가주변기타상수도전용<NA>0006<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
85532200003220000-106-2022-0000920220801<NA>1영업/정상1영업<NA><NA><NA><NA><NA>103.21135892서울특별시 강남구 신사동 586-9서울특별시 강남구 도산대로27길 18, 지하1층 (신사동)6032(주)만나당2022-08-01 10:05:23I2021-12-08 00:03:00.0기타 식품제조가공업202368.939378446526.88032<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85632200003220000-106-2022-0001020220922<NA>1영업/정상1영업<NA><NA><NA><NA><NA>94.0135829서울특별시 강남구 논현동 214-23서울특별시 강남구 학동로34길 24, 2층 (논현동)6105주식회사 메이크어딜리버리2022-09-22 18:42:47I2021-12-08 22:04:00.0기타 식품제조가공업202911.049918445642.85435<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85732200003220000-106-2022-0001120220923<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.05135964서울특별시 강남구 개포동 1238-2 금화빌딩서울특별시 강남구 개포로 206, 지상 1층 1호 (개포동)6307알제이글로벌그룹(주) 카페 비투비씨 로스터리2022-09-27 16:38:11U2021-12-08 22:09:00.0기타 식품제조가공업203946.726845441785.581589<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85832200003220000-106-2022-0001220221115<NA>1영업/정상1영업<NA><NA><NA><NA>026958889115.0135874서울특별시 강남구 삼성동 112-23서울특별시 강남구 선릉로 570, 1층 (삼성동)6153마그마커피(MAGMA COFFEE)2022-11-15 19:05:13I2021-10-31 23:07:00.0기타 식품제조가공업203861.021589445244.697619<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85932200003220000-106-2023-000012023-04-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.12135-835서울특별시 강남구 대치동 316서울특별시 강남구 삼성로 212-2, 은마종합상가 A동 지하1층 61호 (대치동)6284고보2023-04-28 16:50:27I2022-12-03 21:00:00.0기타 식품제조가공업205707.0894443914.194133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86032200003220000-106-2023-000022023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>113.85135-871서울특별시 강남구 삼성동 78-4 청구아파트서울특별시 강남구 영동대로128길 5, 상가동 지하1층 1~8호 (삼성동, 청구아파트)6078빅터스그룹 주식회사2023-09-01 10:52:34I2022-12-09 00:03:00.0기타 식품제조가공업205089.782282446395.391526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86132200003220000-106-2024-000012024-02-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>113.65135-859서울특별시 강남구 도곡동 942-6서울특별시 강남구 도곡로6길 6, 지하1층 (도곡동)6259주식회사 스아게코리아2024-02-05 15:20:18I2023-12-02 00:07:00.0기타 식품제조가공업202942.623606443067.962046<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86232200003220000-106-2024-000022024-03-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.1135-882서울특별시 강남구 삼성동 168-27서울특별시 강남구 테헤란로103길 5 (삼성동)6173포스톤즈2024-03-11 15:15:37I2023-12-02 23:03:00.0기타 식품제조가공업205589.056548445294.29816<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86332200003220000-106-2024-000032024-03-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>215.87135-734서울특별시 강남구 논현동 84 송암빌딩서울특별시 강남구 언주로 709, 송암빌딩 지하1층 (논현동)6053주식회사 이일이공구2024-03-18 14:32:34I2023-12-02 22:00:00.0기타 식품제조가공업203008.146544446054.41135<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
86432200003220000-106-2024-000042024-03-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.2135-876서울특별시 강남구 삼성동 142-5서울특별시 강남구 테헤란로63길 8 (삼성동)6160(주)유로스컴퍼니2024-03-29 13:46:49I2023-12-02 21:01:00.0기타 식품제조가공업204399.988565444849.431548<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>