Overview

Dataset statistics

Number of variables44
Number of observations755
Missing cells7011
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory276.6 KiB
Average record size in memory375.2 B

Variable types

Categorical20
Text7
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18199/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (56.8%)Imbalance
남성종사자수 is highly imbalanced (74.2%)Imbalance
여성종사자수 is highly imbalanced (74.2%)Imbalance
영업장주변구분명 is highly imbalanced (67.1%)Imbalance
등급구분명 is highly imbalanced (72.0%)Imbalance
총인원 is highly imbalanced (79.7%)Imbalance
공장판매직종업원수 is highly imbalanced (60.9%)Imbalance
인허가취소일자 has 755 (100.0%) missing valuesMissing
폐업일자 has 124 (16.4%) missing valuesMissing
휴업시작일자 has 755 (100.0%) missing valuesMissing
휴업종료일자 has 755 (100.0%) missing valuesMissing
재개업일자 has 755 (100.0%) missing valuesMissing
전화번호 has 236 (31.3%) missing valuesMissing
소재지면적 has 51 (6.8%) missing valuesMissing
도로명주소 has 335 (44.4%) missing valuesMissing
도로명우편번호 has 338 (44.8%) missing valuesMissing
좌표정보(X) has 11 (1.5%) missing valuesMissing
좌표정보(Y) has 11 (1.5%) missing valuesMissing
공장생산직종업원수 has 484 (64.1%) missing valuesMissing
다중이용업소여부 has 67 (8.9%) missing valuesMissing
시설총규모 has 67 (8.9%) missing valuesMissing
전통업소지정번호 has 755 (100.0%) missing valuesMissing
전통업소주된음식 has 755 (100.0%) missing valuesMissing
홈페이지 has 755 (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
공장생산직종업원수 has 262 (34.7%) zerosZeros
시설총규모 has 433 (57.4%) zerosZeros

Reproduction

Analysis started2024-04-06 12:58:28.564805
Analysis finished2024-04-06 12:58:30.395353
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3220000
755 

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 755
100.0%

Length

2024-04-06T21:58:30.570877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:30.802301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 755
100.0%

관리번호
Text

UNIQUE 

Distinct755
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-06T21:58:31.111187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters16610
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

Unique755 ?
Unique (%)100.0%

Sample

1st row3220000-109-1988-00001
2nd row3220000-109-1988-00002
3rd row3220000-109-1988-00003
4th row3220000-109-1989-01091
5th row3220000-109-1989-01175
ValueCountFrequency (%)
3220000-109-1988-00001 1
 
0.1%
3220000-109-2012-00026 1
 
0.1%
3220000-109-2012-00037 1
 
0.1%
3220000-109-2012-00018 1
 
0.1%
3220000-109-2012-00019 1
 
0.1%
3220000-109-2012-00020 1
 
0.1%
3220000-109-2012-00021 1
 
0.1%
3220000-109-2012-00022 1
 
0.1%
3220000-109-2012-00023 1
 
0.1%
3220000-109-2012-00024 1
 
0.1%
Other values (745) 745
98.7%
2024-04-06T21:58:31.721291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7233
43.5%
2 2610
 
15.7%
- 2265
 
13.6%
1 1513
 
9.1%
9 1053
 
6.3%
3 1029
 
6.2%
4 212
 
1.3%
6 195
 
1.2%
5 176
 
1.1%
8 172
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14345
86.4%
Dash Punctuation 2265
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7233
50.4%
2 2610
 
18.2%
1 1513
 
10.5%
9 1053
 
7.3%
3 1029
 
7.2%
4 212
 
1.5%
6 195
 
1.4%
5 176
 
1.2%
8 172
 
1.2%
7 152
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 2265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7233
43.5%
2 2610
 
15.7%
- 2265
 
13.6%
1 1513
 
9.1%
9 1053
 
6.3%
3 1029
 
6.2%
4 212
 
1.3%
6 195
 
1.2%
5 176
 
1.1%
8 172
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7233
43.5%
2 2610
 
15.7%
- 2265
 
13.6%
1 1513
 
9.1%
9 1053
 
6.3%
3 1029
 
6.2%
4 212
 
1.3%
6 195
 
1.2%
5 176
 
1.1%
8 172
 
1.0%
Distinct683
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum1988-03-28 00:00:00
Maximum2024-01-29 00:00:00
2024-04-06T21:58:32.009328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:32.270462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3
631 
1
124 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 631
83.6%
1 124
 
16.4%

Length

2024-04-06T21:58:32.467111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:32.652557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 631
83.6%
1 124
 
16.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
폐업
631 
영업/정상
124 

Length

Max length5
Median length2
Mean length2.4927152
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 631
83.6%
영업/정상 124
 
16.4%

Length

2024-04-06T21:58:32.848023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:33.055733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 631
83.6%
영업/정상 124
 
16.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2
631 
1
124 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 631
83.6%
1 124
 
16.4%

Length

2024-04-06T21:58:33.264960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:33.434175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 631
83.6%
1 124
 
16.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
폐업
631 
영업
124 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 631
83.6%
영업 124
 
16.4%

Length

2024-04-06T21:58:33.949623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:34.138882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 631
83.6%
영업 124
 
16.4%

폐업일자
Date

MISSING 

Distinct451
Distinct (%)71.5%
Missing124
Missing (%)16.4%
Memory size6.0 KiB
Minimum1991-06-03 00:00:00
Maximum2024-03-04 00:00:00
2024-04-06T21:58:34.338899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:34.733530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

전화번호
Text

MISSING 

Distinct484
Distinct (%)93.3%
Missing236
Missing (%)31.3%
Memory size6.0 KiB
2024-04-06T21:58:35.262291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.086705
Min length2

Characters and Unicode

Total characters5235
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

Unique457 ?
Unique (%)88.1%

Sample

1st row02 5400848
2nd row02 5430794
3rd row02 5772507
4th row02 5444904
5th row0205530101
ValueCountFrequency (%)
02 296
31.0%
070 22
 
2.3%
031 10
 
1.0%
540 4
 
0.4%
552 4
 
0.4%
34494114 4
 
0.4%
5312021 4
 
0.4%
556 4
 
0.4%
514 3
 
0.3%
554 3
 
0.3%
Other values (545) 601
62.9%
2024-04-06T21:58:36.010623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 863
16.5%
2 739
14.1%
5 627
12.0%
582
11.1%
4 478
9.1%
3 397
7.6%
1 386
7.4%
7 364
7.0%
6 320
 
6.1%
8 246
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4653
88.9%
Space Separator 582
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 863
18.5%
2 739
15.9%
5 627
13.5%
4 478
10.3%
3 397
8.5%
1 386
8.3%
7 364
7.8%
6 320
 
6.9%
8 246
 
5.3%
9 233
 
5.0%
Space Separator
ValueCountFrequency (%)
582
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 863
16.5%
2 739
14.1%
5 627
12.0%
582
11.1%
4 478
9.1%
3 397
7.6%
1 386
7.4%
7 364
7.0%
6 320
 
6.1%
8 246
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 863
16.5%
2 739
14.1%
5 627
12.0%
582
11.1%
4 478
9.1%
3 397
7.6%
1 386
7.4%
7 364
7.0%
6 320
 
6.1%
8 246
 
4.7%

소재지면적
Text

MISSING 

Distinct374
Distinct (%)53.1%
Missing51
Missing (%)6.8%
Memory size6.0 KiB
2024-04-06T21:58:36.682251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.7713068
Min length3

Characters and Unicode

Total characters3359
Distinct characters12
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

Unique296 ?
Unique (%)42.0%

Sample

1st row.00
2nd row.00
3rd row100.05
4th row113.52
5th row114.60
ValueCountFrequency (%)
3.30 49
 
7.0%
10.00 25
 
3.6%
33.00 21
 
3.0%
6.60 20
 
2.8%
9.90 17
 
2.4%
3.00 16
 
2.3%
16.50 14
 
2.0%
6.00 11
 
1.6%
9.91 10
 
1.4%
00 9
 
1.3%
Other values (364) 512
72.7%
2024-04-06T21:58:37.727255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 764
22.7%
. 704
21.0%
1 321
9.6%
3 315
9.4%
2 255
 
7.6%
6 228
 
6.8%
5 214
 
6.4%
9 182
 
5.4%
4 146
 
4.3%
8 132
 
3.9%
Other values (2) 98
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2652
79.0%
Other Punctuation 707
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 764
28.8%
1 321
12.1%
3 315
11.9%
2 255
 
9.6%
6 228
 
8.6%
5 214
 
8.1%
9 182
 
6.9%
4 146
 
5.5%
8 132
 
5.0%
7 95
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 704
99.6%
, 3
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 764
22.7%
. 704
21.0%
1 321
9.6%
3 315
9.4%
2 255
 
7.6%
6 228
 
6.8%
5 214
 
6.4%
9 182
 
5.4%
4 146
 
4.3%
8 132
 
3.9%
Other values (2) 98
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 764
22.7%
. 704
21.0%
1 321
9.6%
3 315
9.4%
2 255
 
7.6%
6 228
 
6.8%
5 214
 
6.4%
9 182
 
5.4%
4 146
 
4.3%
8 132
 
3.9%
Other values (2) 98
 
2.9%
Distinct195
Distinct (%)25.9%
Missing1
Missing (%)0.1%
Memory size6.0 KiB
2024-04-06T21:58:38.217695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0530504
Min length6

Characters and Unicode

Total characters4564
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

Unique73 ?
Unique (%)9.7%

Sample

1st row135820
2nd row135821
3rd row135945
4th row135863
5th row135998
ValueCountFrequency (%)
135090 49
 
6.5%
135900 31
 
4.1%
135998 28
 
3.7%
135962 21
 
2.8%
135856 14
 
1.9%
135902 14
 
1.9%
135906 13
 
1.7%
135897 11
 
1.5%
135829 10
 
1.3%
135896 10
 
1.3%
Other values (185) 553
73.3%
2024-04-06T21:58:39.063820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 928
20.3%
1 879
19.3%
3 871
19.1%
9 525
11.5%
8 445
9.8%
0 298
 
6.5%
2 178
 
3.9%
6 152
 
3.3%
4 144
 
3.2%
7 104
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4524
99.1%
Dash Punctuation 40
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 928
20.5%
1 879
19.4%
3 871
19.3%
9 525
11.6%
8 445
9.8%
0 298
 
6.6%
2 178
 
3.9%
6 152
 
3.4%
4 144
 
3.2%
7 104
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4564
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 928
20.3%
1 879
19.3%
3 871
19.1%
9 525
11.5%
8 445
9.8%
0 298
 
6.5%
2 178
 
3.9%
6 152
 
3.3%
4 144
 
3.2%
7 104
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 928
20.3%
1 879
19.3%
3 871
19.1%
9 525
11.5%
8 445
9.8%
0 298
 
6.5%
2 178
 
3.9%
6 152
 
3.3%
4 144
 
3.2%
7 104
 
2.3%
Distinct678
Distinct (%)89.9%
Missing1
Missing (%)0.1%
Memory size6.0 KiB
2024-04-06T21:58:39.551592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length25.969496
Min length16

Characters and Unicode

Total characters19581
Distinct characters305
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

Unique642 ?
Unique (%)85.1%

Sample

1st row서울특별시 강남구 논현동 119
2nd row서울특별시 강남구 논현동 113-26
3rd row서울특별시 강남구 일원동 645-4
4th row서울특별시 강남구 삼성동 5-1
5th row서울특별시 강남구 대치동 937
ValueCountFrequency (%)
서울특별시 754
20.3%
강남구 753
20.3%
역삼동 104
 
2.8%
대치동 100
 
2.7%
삼성동 100
 
2.7%
지하1층 94
 
2.5%
논현동 90
 
2.4%
개포동 78
 
2.1%
신사동 75
 
2.0%
압구정동 67
 
1.8%
Other values (915) 1492
40.2%
2024-04-06T21:58:40.297166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3619
18.5%
1 983
 
5.0%
827
 
4.2%
778
 
4.0%
773
 
3.9%
763
 
3.9%
762
 
3.9%
757
 
3.9%
756
 
3.9%
754
 
3.9%
Other values (295) 8809
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11375
58.1%
Decimal Number 3855
 
19.7%
Space Separator 3619
 
18.5%
Dash Punctuation 677
 
3.5%
Uppercase Letter 35
 
0.2%
Other Punctuation 9
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
827
 
7.3%
778
 
6.8%
773
 
6.8%
763
 
6.7%
762
 
6.7%
757
 
6.7%
756
 
6.6%
754
 
6.6%
754
 
6.6%
376
 
3.3%
Other values (258) 4075
35.8%
Uppercase Letter
ValueCountFrequency (%)
B 13
37.1%
O 3
 
8.6%
I 2
 
5.7%
C 2
 
5.7%
N 2
 
5.7%
F 2
 
5.7%
S 1
 
2.9%
R 1
 
2.9%
V 1
 
2.9%
W 1
 
2.9%
Other values (7) 7
20.0%
Decimal Number
ValueCountFrequency (%)
1 983
25.5%
2 443
11.5%
4 360
 
9.3%
0 344
 
8.9%
5 321
 
8.3%
9 320
 
8.3%
7 316
 
8.2%
6 308
 
8.0%
3 287
 
7.4%
8 173
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
. 1
 
11.1%
/ 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
3619
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 677
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11375
58.1%
Common 8169
41.7%
Latin 37
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
827
 
7.3%
778
 
6.8%
773
 
6.8%
763
 
6.7%
762
 
6.7%
757
 
6.7%
756
 
6.6%
754
 
6.6%
754
 
6.6%
376
 
3.3%
Other values (258) 4075
35.8%
Latin
ValueCountFrequency (%)
B 13
35.1%
O 3
 
8.1%
I 2
 
5.4%
C 2
 
5.4%
N 2
 
5.4%
F 2
 
5.4%
S 1
 
2.7%
R 1
 
2.7%
V 1
 
2.7%
W 1
 
2.7%
Other values (9) 9
24.3%
Common
ValueCountFrequency (%)
3619
44.3%
1 983
 
12.0%
- 677
 
8.3%
2 443
 
5.4%
4 360
 
4.4%
0 344
 
4.2%
5 321
 
3.9%
9 320
 
3.9%
7 316
 
3.9%
6 308
 
3.8%
Other values (8) 478
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11375
58.1%
ASCII 8206
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3619
44.1%
1 983
 
12.0%
- 677
 
8.3%
2 443
 
5.4%
4 360
 
4.4%
0 344
 
4.2%
5 321
 
3.9%
9 320
 
3.9%
7 316
 
3.9%
6 308
 
3.8%
Other values (27) 515
 
6.3%
Hangul
ValueCountFrequency (%)
827
 
7.3%
778
 
6.8%
773
 
6.8%
763
 
6.7%
762
 
6.7%
757
 
6.7%
756
 
6.6%
754
 
6.6%
754
 
6.6%
376
 
3.3%
Other values (258) 4075
35.8%

도로명주소
Text

MISSING 

Distinct406
Distinct (%)96.7%
Missing335
Missing (%)44.4%
Memory size6.0 KiB
2024-04-06T21:58:40.762024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length35.32381
Min length23

Characters and Unicode

Total characters14836
Distinct characters278
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

Unique394 ?
Unique (%)93.8%

Sample

1st row서울특별시 강남구 선릉로130길 56 (삼성동)
2nd row서울특별시 강남구 압구정로 201 (압구정동)
3rd row서울특별시 강남구 테헤란로 517 (삼성동)
4th row서울특별시 강남구 선릉로 30 (개포동,개포B/D 지하)
5th row서울특별시 강남구 논현로149길 69 (논현동,신흥빌딩2층)
ValueCountFrequency (%)
서울특별시 420
 
15.4%
강남구 419
 
15.4%
지하1층 90
 
3.3%
지상1층 58
 
2.1%
삼성동 50
 
1.8%
역삼동 46
 
1.7%
신사동 42
 
1.5%
논현동 41
 
1.5%
대치동 35
 
1.3%
지상2층 34
 
1.2%
Other values (752) 1485
54.6%
2024-04-06T21:58:41.504677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2300
 
15.5%
1 719
 
4.8%
, 517
 
3.5%
488
 
3.3%
484
 
3.3%
460
 
3.1%
452
 
3.0%
432
 
2.9%
430
 
2.9%
( 426
 
2.9%
Other values (268) 8128
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8640
58.2%
Decimal Number 2424
 
16.3%
Space Separator 2300
 
15.5%
Other Punctuation 520
 
3.5%
Open Punctuation 426
 
2.9%
Close Punctuation 426
 
2.9%
Dash Punctuation 48
 
0.3%
Uppercase Letter 48
 
0.3%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
488
 
5.6%
484
 
5.6%
460
 
5.3%
452
 
5.2%
432
 
5.0%
430
 
5.0%
422
 
4.9%
421
 
4.9%
420
 
4.9%
420
 
4.9%
Other values (230) 4211
48.7%
Uppercase Letter
ValueCountFrequency (%)
B 20
41.7%
G 4
 
8.3%
O 3
 
6.2%
I 3
 
6.2%
S 3
 
6.2%
N 2
 
4.2%
F 2
 
4.2%
V 1
 
2.1%
P 1
 
2.1%
C 1
 
2.1%
Other values (8) 8
 
16.7%
Decimal Number
ValueCountFrequency (%)
1 719
29.7%
2 347
14.3%
3 246
 
10.1%
0 227
 
9.4%
4 206
 
8.5%
5 201
 
8.3%
6 150
 
6.2%
7 128
 
5.3%
8 123
 
5.1%
9 77
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 517
99.4%
. 2
 
0.4%
/ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
2300
100.0%
Open Punctuation
ValueCountFrequency (%)
( 426
100.0%
Close Punctuation
ValueCountFrequency (%)
) 426
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8640
58.2%
Common 6146
41.4%
Latin 50
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
488
 
5.6%
484
 
5.6%
460
 
5.3%
452
 
5.2%
432
 
5.0%
430
 
5.0%
422
 
4.9%
421
 
4.9%
420
 
4.9%
420
 
4.9%
Other values (230) 4211
48.7%
Latin
ValueCountFrequency (%)
B 20
40.0%
G 4
 
8.0%
O 3
 
6.0%
I 3
 
6.0%
S 3
 
6.0%
N 2
 
4.0%
F 2
 
4.0%
i 1
 
2.0%
s 1
 
2.0%
V 1
 
2.0%
Other values (10) 10
20.0%
Common
ValueCountFrequency (%)
2300
37.4%
1 719
 
11.7%
, 517
 
8.4%
( 426
 
6.9%
) 426
 
6.9%
2 347
 
5.6%
3 246
 
4.0%
0 227
 
3.7%
4 206
 
3.4%
5 201
 
3.3%
Other values (8) 531
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8640
58.2%
ASCII 6196
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2300
37.1%
1 719
 
11.6%
, 517
 
8.3%
( 426
 
6.9%
) 426
 
6.9%
2 347
 
5.6%
3 246
 
4.0%
0 227
 
3.7%
4 206
 
3.3%
5 201
 
3.2%
Other values (28) 581
 
9.4%
Hangul
ValueCountFrequency (%)
488
 
5.6%
484
 
5.6%
460
 
5.3%
452
 
5.2%
432
 
5.0%
430
 
5.0%
422
 
4.9%
421
 
4.9%
420
 
4.9%
420
 
4.9%
Other values (230) 4211
48.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct199
Distinct (%)47.7%
Missing338
Missing (%)44.8%
Infinite0
Infinite (%)0.0%
Mean6151.1295
Minimum3723
Maximum6378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-06T21:58:41.757626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3723
5-th percentile6009.6
Q16056
median6156
Q36241
95-th percentile6336
Maximum6378
Range2655
Interquartile range (IQR)185

Descriptive statistics

Standard deviation161.98449
Coefficient of variation (CV)0.026334104
Kurtosis120.51759
Mean6151.1295
Median Absolute Deviation (MAD)96
Skewness-7.9996317
Sum2565021
Variance26238.974
MonotonicityNot monotonic
2024-04-06T21:58:42.027604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6164 22
 
2.9%
6001 10
 
1.3%
6312 9
 
1.2%
6018 7
 
0.9%
6367 7
 
0.9%
6028 7
 
0.9%
6008 6
 
0.8%
6329 5
 
0.7%
6039 5
 
0.7%
6206 5
 
0.7%
Other values (189) 334
44.2%
(Missing) 338
44.8%
ValueCountFrequency (%)
3723 1
 
0.1%
6001 10
1.3%
6002 1
 
0.1%
6004 3
 
0.4%
6008 6
0.8%
6010 1
 
0.1%
6011 3
 
0.4%
6012 1
 
0.1%
6014 5
0.7%
6015 2
 
0.3%
ValueCountFrequency (%)
6378 1
 
0.1%
6377 1
 
0.1%
6370 1
 
0.1%
6367 7
0.9%
6365 1
 
0.1%
6362 1
 
0.1%
6360 1
 
0.1%
6342 1
 
0.1%
6341 1
 
0.1%
6339 2
 
0.3%
Distinct698
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-06T21:58:42.447286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length7.2768212
Min length2

Characters and Unicode

Total characters5494
Distinct characters527
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique654 ?
Unique (%)86.6%

Sample

1st row나산백화점강남지점
2nd row한국메디아
3rd row동림사
4th row오시리 주식회사
5th row그랜드백화점
ValueCountFrequency (%)
주식회사 26
 
3.0%
주)교동씨엠 6
 
0.7%
5
 
0.6%
위고에빅토르 4
 
0.5%
카페 4
 
0.5%
주)제이에프앤비 4
 
0.5%
gs수퍼 3
 
0.3%
주)지에스리테일 3
 
0.3%
오양수산(주 3
 
0.3%
주)동진인터내셔날 3
 
0.3%
Other values (769) 819
93.1%
2024-04-06T21:58:43.022426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
6.3%
( 331
 
6.0%
) 329
 
6.0%
149
 
2.7%
127
 
2.3%
125
 
2.3%
118
 
2.1%
93
 
1.7%
89
 
1.6%
77
 
1.4%
Other values (517) 3712
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4509
82.1%
Open Punctuation 331
 
6.0%
Close Punctuation 329
 
6.0%
Space Separator 125
 
2.3%
Uppercase Letter 95
 
1.7%
Lowercase Letter 80
 
1.5%
Decimal Number 19
 
0.3%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
344
 
7.6%
149
 
3.3%
127
 
2.8%
118
 
2.6%
93
 
2.1%
89
 
2.0%
77
 
1.7%
69
 
1.5%
62
 
1.4%
62
 
1.4%
Other values (461) 3319
73.6%
Uppercase Letter
ValueCountFrequency (%)
E 9
 
9.5%
R 9
 
9.5%
S 9
 
9.5%
T 8
 
8.4%
A 7
 
7.4%
N 6
 
6.3%
C 6
 
6.3%
O 6
 
6.3%
G 5
 
5.3%
I 4
 
4.2%
Other values (12) 26
27.4%
Lowercase Letter
ValueCountFrequency (%)
e 13
16.2%
o 11
13.8%
n 7
 
8.8%
s 5
 
6.2%
l 5
 
6.2%
a 5
 
6.2%
t 4
 
5.0%
r 4
 
5.0%
i 4
 
5.0%
y 3
 
3.8%
Other values (11) 19
23.8%
Decimal Number
ValueCountFrequency (%)
1 8
42.1%
2 3
 
15.8%
3 3
 
15.8%
8 2
 
10.5%
0 1
 
5.3%
6 1
 
5.3%
5 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
? 3
50.0%
& 2
33.3%
: 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 331
100.0%
Close Punctuation
ValueCountFrequency (%)
) 329
100.0%
Space Separator
ValueCountFrequency (%)
125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4507
82.0%
Common 810
 
14.7%
Latin 175
 
3.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
344
 
7.6%
149
 
3.3%
127
 
2.8%
118
 
2.6%
93
 
2.1%
89
 
2.0%
77
 
1.7%
69
 
1.5%
62
 
1.4%
62
 
1.4%
Other values (459) 3317
73.6%
Latin
ValueCountFrequency (%)
e 13
 
7.4%
o 11
 
6.3%
E 9
 
5.1%
R 9
 
5.1%
S 9
 
5.1%
T 8
 
4.6%
A 7
 
4.0%
n 7
 
4.0%
N 6
 
3.4%
C 6
 
3.4%
Other values (33) 90
51.4%
Common
ValueCountFrequency (%)
( 331
40.9%
) 329
40.6%
125
 
15.4%
1 8
 
1.0%
2 3
 
0.4%
3 3
 
0.4%
? 3
 
0.4%
& 2
 
0.2%
8 2
 
0.2%
: 1
 
0.1%
Other values (3) 3
 
0.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4507
82.0%
ASCII 985
 
17.9%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
344
 
7.6%
149
 
3.3%
127
 
2.8%
118
 
2.6%
93
 
2.1%
89
 
2.0%
77
 
1.7%
69
 
1.5%
62
 
1.4%
62
 
1.4%
Other values (459) 3317
73.6%
ASCII
ValueCountFrequency (%)
( 331
33.6%
) 329
33.4%
125
 
12.7%
e 13
 
1.3%
o 11
 
1.1%
E 9
 
0.9%
R 9
 
0.9%
S 9
 
0.9%
1 8
 
0.8%
T 8
 
0.8%
Other values (46) 133
13.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct640
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2001-09-19 00:00:00
Maximum2024-03-04 13:11:06
2024-04-06T21:58:43.305347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:43.577601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
I
573 
U
182 

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 573
75.9%
U 182
 
24.1%

Length

2024-04-06T21:58:43.813429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:44.006027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 573
75.9%
u 182
 
24.1%
Distinct177
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T21:58:44.207726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:44.441483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
식품소분업
755 

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 755
100.0%

Length

2024-04-06T21:58:44.662383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:44.823357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 755
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct517
Distinct (%)69.5%
Missing11
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean204027.48
Minimum194125.84
Maximum209592.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-06T21:58:45.020311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194125.84
5-th percentile201993.62
Q1202957.67
median203962.05
Q3204828.48
95-th percentile206943.9
Maximum209592.46
Range15466.625
Interquartile range (IQR)1870.8097

Descriptive statistics

Standard deviation1513.0842
Coefficient of variation (CV)0.0074160805
Kurtosis3.4985326
Mean204027.48
Median Absolute Deviation (MAD)952.9501
Skewness0.47972043
Sum1.5179645 × 108
Variance2289423.9
MonotonicityNot monotonic
2024-04-06T21:58:45.347793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202358.505687227 34
 
4.5%
205210.358779172 31
 
4.1%
203470.848439305 27
 
3.6%
204669.543366778 24
 
3.2%
205130.591678902 12
 
1.6%
204749.304517964 9
 
1.2%
204213.643236507 9
 
1.2%
209052.072465426 7
 
0.9%
205707.089399978 6
 
0.8%
204452.460703969 6
 
0.8%
Other values (507) 579
76.7%
(Missing) 11
 
1.5%
ValueCountFrequency (%)
194125.835067413 1
0.1%
201609.62721933 1
0.1%
201641.741382771 1
0.1%
201646.385389914 1
0.1%
201667.786866215 1
0.1%
201677.925882649 1
0.1%
201703.283181154 1
0.1%
201715.375406496 1
0.1%
201716.723205531 1
0.1%
201718.789410144 1
0.1%
ValueCountFrequency (%)
209592.460472051 1
 
0.1%
209398.934372826 1
 
0.1%
209394.0 1
 
0.1%
209167.226468272 1
 
0.1%
209144.783150288 1
 
0.1%
209056.521296887 1
 
0.1%
209052.072465426 7
0.9%
208276.0 1
 
0.1%
207748.487100942 2
 
0.3%
207679.579278773 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct517
Distinct (%)69.5%
Missing11
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean444882.64
Minimum440183.87
Maximum452046.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-06T21:58:45.686016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440183.87
5-th percentile441732.69
Q1443740.44
median445118.94
Q3446326.49
95-th percentile447321.13
Maximum452046.24
Range11862.368
Interquartile range (IQR)2586.0445

Descriptive statistics

Standard deviation1743.7206
Coefficient of variation (CV)0.0039195069
Kurtosis-0.48887507
Mean444882.64
Median Absolute Deviation (MAD)1310.5236
Skewness-0.22737536
Sum3.3099269 × 108
Variance3040561.5
MonotonicityNot monotonic
2024-04-06T21:58:46.035269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447232.955697694 34
 
4.5%
445154.42225208 31
 
4.1%
447369.579851952 27
 
3.6%
443873.621189048 24
 
3.2%
445590.096837802 12
 
1.6%
443058.194678364 9
 
1.2%
444113.028210915 9
 
1.2%
442797.138150563 7
 
0.9%
443914.194133105 6
 
0.8%
443870.082533557 6
 
0.8%
Other values (507) 579
76.7%
(Missing) 11
 
1.5%
ValueCountFrequency (%)
440183.87349816 1
0.1%
440481.379196637 1
0.1%
440732.028087332 1
0.1%
441096.843331453 1
0.1%
441109.775 2
0.3%
441119.156988213 1
0.1%
441205.716346342 1
0.1%
441217.281583585 1
0.1%
441251.451660388 1
0.1%
441255.936666912 1
0.1%
ValueCountFrequency (%)
452046.241712223 1
 
0.1%
447864.763737276 1
 
0.1%
447748.161018109 1
 
0.1%
447521.520319158 3
 
0.4%
447391.130408384 1
 
0.1%
447386.554980471 1
 
0.1%
447369.579851952 27
3.6%
447366.539357322 2
 
0.3%
447323.737268385 1
 
0.1%
447306.347407051 1
 
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
식품소분업
688 
<NA>
 
67

Length

Max length5
Median length5
Mean length4.9112583
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 688
91.1%
<NA> 67
 
8.9%

Length

2024-04-06T21:58:46.347459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:46.528821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 688
91.1%
na 67
 
8.9%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
675 
0
77 
2
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.6821192
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row2

Common Values

ValueCountFrequency (%)
<NA> 675
89.4%
0 77
 
10.2%
2 2
 
0.3%
1 1
 
0.1%

Length

2024-04-06T21:58:46.730570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:46.918392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 675
89.4%
0 77
 
10.2%
2 2
 
0.3%
1 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
675 
0
77 
3
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.6821192
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 675
89.4%
0 77
 
10.2%
3 2
 
0.3%
1 1
 
0.1%

Length

2024-04-06T21:58:47.157780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:47.437539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 675
89.4%
0 77
 
10.2%
3 2
 
0.3%
1 1
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
682 
기타
 
61
주택가주변
 
12

Length

Max length5
Median length4
Mean length3.8543046
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 682
90.3%
기타 61
 
8.1%
주택가주변 12
 
1.6%

Length

2024-04-06T21:58:47.697595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:47.922101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 682
90.3%
기타 61
 
8.1%
주택가주변 12
 
1.6%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
682 
기타
 
45
자율
 
27
 
1

Length

Max length4
Median length4
Mean length3.805298
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 682
90.3%
기타 45
 
6.0%
자율 27
 
3.6%
1
 
0.1%

Length

2024-04-06T21:58:48.190069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:48.431081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 682
90.3%
기타 45
 
6.0%
자율 27
 
3.6%
1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
618 
상수도전용
137 

Length

Max length5
Median length4
Mean length4.181457
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 618
81.9%
상수도전용 137
 
18.1%

Length

2024-04-06T21:58:48.672993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:48.911591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 618
81.9%
상수도전용 137
 
18.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
731 
0
 
24

Length

Max length4
Median length4
Mean length3.9046358
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> 731
96.8%
0 24
 
3.2%

Length

2024-04-06T21:58:49.219653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:49.946074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 731
96.8%
0 24
 
3.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
485 
0
270 

Length

Max length4
Median length4
Mean length2.9271523
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 485
64.2%
0 270
35.8%

Length

2024-04-06T21:58:50.188027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:50.429835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 485
64.2%
0 270
35.8%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
484 
0
270 
1
 
1

Length

Max length4
Median length4
Mean length2.9231788
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 484
64.1%
0 270
35.8%
1 1
 
0.1%

Length

2024-04-06T21:58:50.649829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:50.908225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 484
64.1%
0 270
35.8%
1 1
 
0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
485 
0
264 
2
 
2
3
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.9271523
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row4
5th row5

Common Values

ValueCountFrequency (%)
<NA> 485
64.2%
0 264
35.0%
2 2
 
0.3%
3 2
 
0.3%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-06T21:58:51.180599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:51.436492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 485
64.2%
0 264
35.0%
2 2
 
0.3%
3 2
 
0.3%
4 1
 
0.1%
5 1
 
0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.6%
Missing484
Missing (%)64.1%
Infinite0
Infinite (%)0.0%
Mean0.14760148
Minimum0
Maximum9
Zeros262
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-06T21:58:51.649377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.87368089
Coefficient of variation (CV)5.919188
Kurtosis53.340115
Mean0.14760148
Median Absolute Deviation (MAD)0
Skewness6.8922185
Sum40
Variance0.7633183
MonotonicityNot monotonic
2024-04-06T21:58:51.854164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 262
34.7%
4 3
 
0.4%
3 2
 
0.3%
6 1
 
0.1%
5 1
 
0.1%
9 1
 
0.1%
2 1
 
0.1%
(Missing) 484
64.1%
ValueCountFrequency (%)
0 262
34.7%
2 1
 
0.1%
3 2
 
0.3%
4 3
 
0.4%
5 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
9 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 3
 
0.4%
3 2
 
0.3%
2 1
 
0.1%
0 262
34.7%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
자가
380 
<NA>
202 
임대
173 

Length

Max length4
Median length2
Mean length2.5350993
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 (%)
자가 380
50.3%
<NA> 202
26.8%
임대 173
22.9%

Length

2024-04-06T21:58:52.099060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:52.307447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가 380
50.3%
na 202
26.8%
임대 173
22.9%

보증액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
515 
0
240 

Length

Max length4
Median length4
Mean length3.0463576
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> 515
68.2%
0 240
31.8%

Length

2024-04-06T21:58:52.502676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:52.696016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 515
68.2%
0 240
31.8%

월세액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
515 
0
240 

Length

Max length4
Median length4
Mean length3.0463576
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> 515
68.2%
0 240
31.8%

Length

2024-04-06T21:58:52.893916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:53.090077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 515
68.2%
0 240
31.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing67
Missing (%)8.9%
Memory size1.6 KiB
False
688 
(Missing)
 
67
ValueCountFrequency (%)
False 688
91.1%
(Missing) 67
 
8.9%
2024-04-06T21:58:53.266075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct157
Distinct (%)22.8%
Missing67
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean22.391395
Minimum0
Maximum3372.7
Zeros433
Zeros (%)57.4%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-06T21:58:53.457430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39.905
95-th percentile101.95
Maximum3372.7
Range3372.7
Interquartile range (IQR)9.905

Descriptive statistics

Standard deviation143.43848
Coefficient of variation (CV)6.4059645
Kurtosis443.31681
Mean22.391395
Median Absolute Deviation (MAD)0
Skewness19.725249
Sum15405.28
Variance20574.598
MonotonicityNot monotonic
2024-04-06T21:58:53.740850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 433
57.4%
3.3 17
 
2.3%
10.0 13
 
1.7%
9.9 12
 
1.6%
33.0 11
 
1.5%
6.6 9
 
1.2%
16.5 7
 
0.9%
5.0 5
 
0.7%
12.0 5
 
0.7%
20.0 4
 
0.5%
Other values (147) 172
 
22.8%
(Missing) 67
 
8.9%
ValueCountFrequency (%)
0.0 433
57.4%
1.3 1
 
0.1%
1.5 1
 
0.1%
2.0 3
 
0.4%
3.0 4
 
0.5%
3.03 1
 
0.1%
3.2 1
 
0.1%
3.3 17
 
2.3%
3.9 1
 
0.1%
4.0 1
 
0.1%
ValueCountFrequency (%)
3372.7 1
0.1%
1296.2 1
0.1%
322.71 1
0.1%
311.17 1
0.1%
295.28 1
0.1%
292.68 1
0.1%
282.0 1
0.1%
257.4 1
0.1%
228.23 1
0.1%
226.48 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing755
Missing (%)100.0%
Memory size6.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032200003220000-109-1988-0000119880328<NA>3폐업2폐업19970422<NA><NA><NA>02 5400848<NA>135820서울특별시 강남구 논현동 119<NA><NA>나산백화점강남지점2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업203522.611749446136.224972식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132200003220000-109-1988-0000219881128<NA>3폐업2폐업19910603<NA><NA><NA>02 5430794<NA>135821서울특별시 강남구 논현동 113-26<NA><NA>한국메디아2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업203311.208046446109.224734식품소분업<NA><NA><NA><NA><NA><NA>0006<NA><NA><NA>N0.0<NA><NA><NA>
232200003220000-109-1988-0000319881201<NA>3폐업2폐업19990724<NA><NA><NA>02 5772507<NA>135945서울특별시 강남구 일원동 645-4<NA><NA>동림사2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업207554.946704443157.693943식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332200003220000-109-1989-0109119890313<NA>1영업/정상1영업<NA><NA><NA><NA>02 5444904.00135863서울특별시 강남구 삼성동 5-1서울특별시 강남구 선릉로130길 56 (삼성동)6089오시리 주식회사2015-08-11 12:09:47I2018-08-31 23:59:59.0식품소분업204022.338876446109.98858식품소분업13주택가주변<NA><NA>0040<NA><NA><NA>N0.0<NA><NA><NA>
432200003220000-109-1989-0117519890630<NA>3폐업2폐업19991001<NA><NA><NA>0205530101.00135998서울특별시 강남구 대치동 937<NA><NA>그랜드백화점2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업204669.543367443873.621189식품소분업23주택가주변자율상수도전용<NA>0050<NA><NA><NA>N0.0<NA><NA><NA>
532200003220000-109-1989-0117619890118<NA>3폐업2폐업19950330<NA><NA><NA>02 5440070<NA>135894서울특별시 강남구 신사동 616-2<NA><NA>(주)썬락2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업202772.968268447366.539357식품소분업<NA><NA><NA><NA><NA><NA>0004<NA><NA><NA>N0.0<NA><NA><NA>
632200003220000-109-1991-0067819911106<NA>3폐업2폐업20030408<NA><NA><NA>0205163361100.05135517서울특별시 강남구 청담동 98-6<NA><NA>(주)세진세프라이2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업204030.198549446914.823814식품소분업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732200003220000-109-1991-0067919910318<NA>3폐업2폐업19950612<NA><NA><NA>02 5779813<NA>135961서울특별시 강남구 개포동 1168-5<NA><NA>수정상사2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업204524.175073441205.716346식품소분업<NA><NA><NA><NA><NA><NA>0005<NA><NA><NA>N0.0<NA><NA><NA>
832200003220000-109-1991-0068019910318<NA>3폐업2폐업19991008<NA><NA><NA>02 5784477<NA>135945서울특별시 강남구 일원동 659-5<NA><NA>대봉건해산물2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업207532.744907443177.898636식품소분업<NA><NA><NA><NA><NA><NA>0004<NA><NA><NA>N0.0<NA><NA><NA>
932200003220000-109-1991-0068119910626<NA>3폐업2폐업19950612<NA><NA><NA><NA><NA>135943서울특별시 강남구 일원동 639-7<NA><NA>송해상사2001-09-19 00:00:00I2018-08-31 23:59:59.0식품소분업207509.155189443693.062062식품소분업<NA><NA><NA><NA><NA><NA>0004<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
74532200003220000-109-2023-000042023-06-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00135-888서울특별시 강남구 신사동 520-1서울특별시 강남구 강남대로162길 40, 지상1층 202호 (신사동)6028파치노 에스프레소 바2023-06-30 09:39:13I2022-12-07 00:02:00.0식품소분업201839.302582446497.371404<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
74632200003220000-109-2023-000052023-07-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 575 652533.00135-949서울특별시 강남구 청담동 13-26 CROWN GOOSE서울특별시 강남구 도산대로78길 40, CROWN GOOSE 3층 (청담동)6063(주)지에이치씨지2023-07-12 16:35:49I2022-12-06 23:04:00.0식품소분업204017.902668446602.997192<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
74732200003220000-109-2023-000062023-08-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 577 345739.05135-240서울특별시 강남구 개포동 1282 개포 래미안 포레스트서울특별시 강남구 개포로 264, 상가1동 지하1층 102호 (개포동, 개포 래미안 포레스트)6310조선식품관2023-08-09 15:42:03I2022-12-07 23:01:00.0식품소분업204696.031322441829.029826<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
74832200003220000-109-2023-000072023-08-18<NA>1영업/정상1영업<NA><NA><NA><NA>02 595 914716.50135-896서울특별시 강남구 신사동 643-28서울특별시 강남구 언주로170길 23, 지상2층 (신사동)6017(주)델픽 도산2023-08-18 16:43:50I2022-12-07 22:00:00.0식품소분업203075.818795447180.289007<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
74932200003220000-109-2023-000082023-09-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.25135-509서울특별시 강남구 삼성동 119-17서울특별시 강남구 봉은사로78길 15, 지상1층 101호 (삼성동)6154키헤이커피2023-09-18 09:54:24I2022-12-08 22:00:00.0식품소분업204632.409046445512.891433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
75032200003220000-109-2023-000092023-10-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.00135-994서울특별시 강남구 개포동 186-7서울특별시 강남구 개포로82길 13-17, 지상4층 402-1호 (개포동)6329틴지오브소울2023-10-11 16:01:25I2022-10-30 23:03:00.0식품소분업205996.639125442966.118103<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
75132200003220000-109-2023-000102023-11-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00135-864서울특별시 강남구 삼성동 24-1서울특별시 강남구 삼성로119길 21, 지상3층 (삼성동)6094(주)메디프코리아2023-11-24 17:14:57U2022-10-31 22:06:00.0식품소분업204332.699904445937.673469<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
75232200003220000-109-2023-000112023-12-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30135-513서울특별시 강남구 역삼동 704-47서울특별시 강남구 테헤란로51길 23, 지상1층 103호 (역삼동)6148알렉산더커피(Alexander Coffee)2023-12-28 14:57:04I2022-11-01 21:00:00.0식품소분업203976.105146444774.942611<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
75332200003220000-109-2024-000012024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA>070 8282672313.00135-954서울특별시 강남구 청담동 88-37 아시아청담부띠끄서울특별시 강남구 선릉로152길 17, 지상1층 101호 (청담동)6014기욤2024-01-12 17:18:02I2023-11-30 23:04:00.0식품소분업203559.800138446912.293423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
75432200003220000-109-2024-000022024-01-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 445 091916.10135-945서울특별시 강남구 일원동 644-2 조이빌딩서울특별시 강남구 양재대로55길 13, 조이빌딩 지상5층 (일원동)6342래그랜느보호작업장2024-01-29 14:23:06I2023-11-30 21:01:00.0식품소분업207669.386561443281.337114<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>