Overview

Dataset statistics

Number of variables44
Number of observations659
Missing cells5992
Missing cells (%)20.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory241.5 KiB
Average record size in memory375.2 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18178/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (54.5%)Imbalance
남성종사자수 is highly imbalanced (75.1%)Imbalance
여성종사자수 is highly imbalanced (72.8%)Imbalance
영업장주변구분명 is highly imbalanced (79.7%)Imbalance
등급구분명 is highly imbalanced (75.1%)Imbalance
총인원 is highly imbalanced (54.5%)Imbalance
공장사무직종업원수 is highly imbalanced (75.0%)Imbalance
공장생산직종업원수 is highly imbalanced (75.3%)Imbalance
보증액 is highly imbalanced (54.5%)Imbalance
월세액 is highly imbalanced (54.5%)Imbalance
인허가취소일자 has 659 (100.0%) missing valuesMissing
폐업일자 has 187 (28.4%) missing valuesMissing
휴업시작일자 has 659 (100.0%) missing valuesMissing
휴업종료일자 has 659 (100.0%) missing valuesMissing
재개업일자 has 659 (100.0%) missing valuesMissing
전화번호 has 258 (39.2%) missing valuesMissing
소재지면적 has 59 (9.0%) missing valuesMissing
도로명주소 has 270 (41.0%) missing valuesMissing
도로명우편번호 has 271 (41.1%) missing valuesMissing
좌표정보(X) has 40 (6.1%) missing valuesMissing
좌표정보(Y) has 40 (6.1%) missing valuesMissing
본사종업원수 has 63 (9.6%) missing valuesMissing
공장판매직종업원수 has 63 (9.6%) missing valuesMissing
다중이용업소여부 has 63 (9.6%) missing valuesMissing
시설총규모 has 63 (9.6%) missing valuesMissing
전통업소지정번호 has 659 (100.0%) missing valuesMissing
전통업소주된음식 has 659 (100.0%) missing valuesMissing
홈페이지 has 659 (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
본사종업원수 has 582 (88.3%) zerosZeros
공장판매직종업원수 has 500 (75.9%) zerosZeros
시설총규모 has 454 (68.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:14:20.846346
Analysis finished2024-05-11 06:14:22.084864
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3010000
659 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 659
100.0%

Length

2024-05-11T15:14:22.206739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:22.372034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 659
100.0%

관리번호
Text

UNIQUE 

Distinct659
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:14:22.605722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters14498
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

Unique659 ?
Unique (%)100.0%

Sample

1st row3010000-109-1983-00027
2nd row3010000-109-1986-00001
3rd row3010000-109-1989-00001
4th row3010000-109-1989-00002
5th row3010000-109-1991-00178
ValueCountFrequency (%)
3010000-109-1983-00027 1
 
0.2%
3010000-109-2011-00025 1
 
0.2%
3010000-109-2012-00007 1
 
0.2%
3010000-109-2011-00028 1
 
0.2%
3010000-109-2012-00001 1
 
0.2%
3010000-109-2012-00002 1
 
0.2%
3010000-109-2012-00003 1
 
0.2%
3010000-109-2012-00004 1
 
0.2%
3010000-109-2012-00005 1
 
0.2%
3010000-109-2012-00006 1
 
0.2%
Other values (649) 649
98.5%
2024-05-11T15:14:23.110648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7165
49.4%
- 1977
 
13.6%
1 1914
 
13.2%
2 942
 
6.5%
9 885
 
6.1%
3 846
 
5.8%
5 180
 
1.2%
6 164
 
1.1%
4 162
 
1.1%
7 137
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12521
86.4%
Dash Punctuation 1977
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7165
57.2%
1 1914
 
15.3%
2 942
 
7.5%
9 885
 
7.1%
3 846
 
6.8%
5 180
 
1.4%
6 164
 
1.3%
4 162
 
1.3%
7 137
 
1.1%
8 126
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1977
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7165
49.4%
- 1977
 
13.6%
1 1914
 
13.2%
2 942
 
6.5%
9 885
 
6.1%
3 846
 
5.8%
5 180
 
1.2%
6 164
 
1.1%
4 162
 
1.1%
7 137
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7165
49.4%
- 1977
 
13.6%
1 1914
 
13.2%
2 942
 
6.5%
9 885
 
6.1%
3 846
 
5.8%
5 180
 
1.2%
6 164
 
1.1%
4 162
 
1.1%
7 137
 
0.9%
Distinct577
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1983-02-09 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T15:14:23.388268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:23.638808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3
472 
1
187 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 472
71.6%
1 187
 
28.4%

Length

2024-05-11T15:14:23.966814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:24.151698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 472
71.6%
1 187
 
28.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
472 
영업/정상
187 

Length

Max length5
Median length2
Mean length2.8512898
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 472
71.6%
영업/정상 187
 
28.4%

Length

2024-05-11T15:14:24.343105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:24.497848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 472
71.6%
영업/정상 187
 
28.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2
472 
1
187 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 472
71.6%
1 187
 
28.4%

Length

2024-05-11T15:14:24.680577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:24.883444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 472
71.6%
1 187
 
28.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
472 
영업
187 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 472
71.6%
영업 187
 
28.4%

Length

2024-05-11T15:14:25.119675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:25.388920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 472
71.6%
영업 187
 
28.4%

폐업일자
Date

MISSING 

Distinct389
Distinct (%)82.4%
Missing187
Missing (%)28.4%
Memory size5.3 KiB
Minimum1997-12-12 00:00:00
Maximum2024-04-12 00:00:00
2024-05-11T15:14:25.595944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:25.871754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

전화번호
Text

MISSING 

Distinct383
Distinct (%)95.5%
Missing258
Missing (%)39.2%
Memory size5.3 KiB
2024-05-11T15:14:26.435658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.733167
Min length2

Characters and Unicode

Total characters4304
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

Unique367 ?
Unique (%)91.5%

Sample

1st row0222741347
2nd row027723 013
3rd row02 392 1758
4th row022679 829
5th row0222343306
ValueCountFrequency (%)
02 231
31.6%
754 8
 
1.1%
031 8
 
1.1%
070 6
 
0.8%
755 6
 
0.8%
310 5
 
0.7%
752 4
 
0.5%
753 4
 
0.5%
318 4
 
0.5%
777 3
 
0.4%
Other values (420) 453
61.9%
2024-05-11T15:14:27.173495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1031
24.0%
0 648
15.1%
487
11.3%
7 461
10.7%
3 314
 
7.3%
5 272
 
6.3%
1 252
 
5.9%
6 235
 
5.5%
4 208
 
4.8%
8 202
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3817
88.7%
Space Separator 487
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1031
27.0%
0 648
17.0%
7 461
12.1%
3 314
 
8.2%
5 272
 
7.1%
1 252
 
6.6%
6 235
 
6.2%
4 208
 
5.4%
8 202
 
5.3%
9 194
 
5.1%
Space Separator
ValueCountFrequency (%)
487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1031
24.0%
0 648
15.1%
487
11.3%
7 461
10.7%
3 314
 
7.3%
5 272
 
6.3%
1 252
 
5.9%
6 235
 
5.5%
4 208
 
4.8%
8 202
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1031
24.0%
0 648
15.1%
487
11.3%
7 461
10.7%
3 314
 
7.3%
5 272
 
6.3%
1 252
 
5.9%
6 235
 
5.5%
4 208
 
4.8%
8 202
 
4.7%

소재지면적
Text

MISSING 

Distinct249
Distinct (%)41.5%
Missing59
Missing (%)9.0%
Memory size5.3 KiB
2024-05-11T15:14:27.864872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6216667
Min length3

Characters and Unicode

Total characters2773
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

Unique182 ?
Unique (%)30.3%

Sample

1st row.00
2nd row104.00
3rd row82.93
4th row42.48
5th row94.70
ValueCountFrequency (%)
6.60 33
 
5.5%
3.30 32
 
5.3%
10.00 26
 
4.3%
9.90 18
 
3.0%
6.00 16
 
2.7%
33.00 16
 
2.7%
3.00 16
 
2.7%
16.50 12
 
2.0%
2.00 12
 
2.0%
13.20 12
 
2.0%
Other values (239) 407
67.8%
2024-05-11T15:14:28.847078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 782
28.2%
. 600
21.6%
1 239
 
8.6%
3 229
 
8.3%
6 216
 
7.8%
2 188
 
6.8%
5 149
 
5.4%
4 117
 
4.2%
9 109
 
3.9%
8 89
 
3.2%
Other values (2) 55
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2172
78.3%
Other Punctuation 601
 
21.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 782
36.0%
1 239
 
11.0%
3 229
 
10.5%
6 216
 
9.9%
2 188
 
8.7%
5 149
 
6.9%
4 117
 
5.4%
9 109
 
5.0%
8 89
 
4.1%
7 54
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 600
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 782
28.2%
. 600
21.6%
1 239
 
8.6%
3 229
 
8.3%
6 216
 
7.8%
2 188
 
6.8%
5 149
 
5.4%
4 117
 
4.2%
9 109
 
3.9%
8 89
 
3.2%
Other values (2) 55
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 782
28.2%
. 600
21.6%
1 239
 
8.6%
3 229
 
8.3%
6 216
 
7.8%
2 188
 
6.8%
5 149
 
5.4%
4 117
 
4.2%
9 109
 
3.9%
8 89
 
3.2%
Other values (2) 55
 
2.0%
Distinct113
Distinct (%)17.2%
Missing1
Missing (%)0.2%
Memory size5.3 KiB
2024-05-11T15:14:29.313055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0592705
Min length6

Characters and Unicode

Total characters3987
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

Unique54 ?
Unique (%)8.2%

Sample

1st row100812
2nd row100070
3rd row100-859
4th row100400
5th row100871
ValueCountFrequency (%)
100310 128
19.5%
100804 71
 
10.8%
100070 63
 
9.6%
100011 51
 
7.8%
100195 47
 
7.1%
100330 27
 
4.1%
100162 22
 
3.3%
100848 12
 
1.8%
100811 12
 
1.8%
100-310 9
 
1.4%
Other values (103) 216
32.8%
2024-05-11T15:14:29.945303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1819
45.6%
1 1055
26.5%
8 254
 
6.4%
3 233
 
5.8%
4 148
 
3.7%
7 101
 
2.5%
9 96
 
2.4%
5 96
 
2.4%
2 90
 
2.3%
6 56
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3948
99.0%
Dash Punctuation 39
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1819
46.1%
1 1055
26.7%
8 254
 
6.4%
3 233
 
5.9%
4 148
 
3.7%
7 101
 
2.6%
9 96
 
2.4%
5 96
 
2.4%
2 90
 
2.3%
6 56
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3987
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1819
45.6%
1 1055
26.5%
8 254
 
6.4%
3 233
 
5.8%
4 148
 
3.7%
7 101
 
2.5%
9 96
 
2.4%
5 96
 
2.4%
2 90
 
2.3%
6 56
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1819
45.6%
1 1055
26.5%
8 254
 
6.4%
3 233
 
5.8%
4 148
 
3.7%
7 101
 
2.5%
9 96
 
2.4%
5 96
 
2.4%
2 90
 
2.3%
6 56
 
1.4%
Distinct536
Distinct (%)81.5%
Missing1
Missing (%)0.2%
Memory size5.3 KiB
2024-05-11T15:14:30.494757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length37
Mean length25.790274
Min length14

Characters and Unicode

Total characters16970
Distinct characters211
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique494 ?
Unique (%)75.1%

Sample

1st row서울특별시 중구 방산동 116-2
2nd row서울특별시 중구 소공동 1
3rd row서울특별시 중구 중림동 393-2 지하1층
4th row서울특별시 중구 쌍림동 276-10
5th row서울특별시 중구 황학동 1589-0
ValueCountFrequency (%)
서울특별시 657
18.7%
중구 657
18.7%
오장동 137
 
3.9%
남창동 79
 
2.2%
1층 78
 
2.2%
소공동 64
 
1.8%
1 63
 
1.8%
신당동 61
 
1.7%
지하1층 60
 
1.7%
충무로1가 54
 
1.5%
Other values (737) 1603
45.6%
2024-05-11T15:14:31.234506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3416
20.1%
1 990
 
5.8%
700
 
4.1%
694
 
4.1%
687
 
4.0%
672
 
4.0%
667
 
3.9%
657
 
3.9%
657
 
3.9%
2 623
 
3.7%
Other values (201) 7207
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9348
55.1%
Decimal Number 3469
 
20.4%
Space Separator 3416
 
20.1%
Dash Punctuation 549
 
3.2%
Uppercase Letter 81
 
0.5%
Other Punctuation 40
 
0.2%
Open Punctuation 28
 
0.2%
Close Punctuation 28
 
0.2%
Lowercase Letter 7
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
700
 
7.5%
694
 
7.4%
687
 
7.3%
672
 
7.2%
667
 
7.1%
657
 
7.0%
657
 
7.0%
588
 
6.3%
298
 
3.2%
258
 
2.8%
Other values (167) 3470
37.1%
Decimal Number
ValueCountFrequency (%)
1 990
28.5%
2 623
18.0%
3 361
 
10.4%
4 356
 
10.3%
5 318
 
9.2%
0 204
 
5.9%
7 200
 
5.8%
6 158
 
4.6%
9 147
 
4.2%
8 112
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
D 28
34.6%
A 17
21.0%
B 15
18.5%
C 12
14.8%
E 5
 
6.2%
N 1
 
1.2%
J 1
 
1.2%
S 1
 
1.2%
K 1
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
v 1
14.3%
i 1
14.3%
l 1
14.3%
u 1
14.3%
n 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 37
92.5%
/ 2
 
5.0%
. 1
 
2.5%
Space Separator
ValueCountFrequency (%)
3416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9348
55.1%
Common 7533
44.4%
Latin 89
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
700
 
7.5%
694
 
7.4%
687
 
7.3%
672
 
7.2%
667
 
7.1%
657
 
7.0%
657
 
7.0%
588
 
6.3%
298
 
3.2%
258
 
2.8%
Other values (167) 3470
37.1%
Common
ValueCountFrequency (%)
3416
45.3%
1 990
 
13.1%
2 623
 
8.3%
- 549
 
7.3%
3 361
 
4.8%
4 356
 
4.7%
5 318
 
4.2%
0 204
 
2.7%
7 200
 
2.7%
6 158
 
2.1%
Other values (8) 358
 
4.8%
Latin
ValueCountFrequency (%)
D 28
31.5%
A 17
19.1%
B 15
16.9%
C 12
13.5%
E 5
 
5.6%
e 2
 
2.2%
v 1
 
1.1%
N 1
 
1.1%
J 1
 
1.1%
S 1
 
1.1%
Other values (6) 6
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9348
55.1%
ASCII 7621
44.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3416
44.8%
1 990
 
13.0%
2 623
 
8.2%
- 549
 
7.2%
3 361
 
4.7%
4 356
 
4.7%
5 318
 
4.2%
0 204
 
2.7%
7 200
 
2.6%
6 158
 
2.1%
Other values (23) 446
 
5.9%
Hangul
ValueCountFrequency (%)
700
 
7.5%
694
 
7.4%
687
 
7.3%
672
 
7.2%
667
 
7.1%
657
 
7.0%
657
 
7.0%
588
 
6.3%
298
 
3.2%
258
 
2.8%
Other values (167) 3470
37.1%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct372
Distinct (%)95.6%
Missing270
Missing (%)41.0%
Memory size5.3 KiB
2024-05-11T15:14:31.659839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length45
Mean length34.200514
Min length21

Characters and Unicode

Total characters13304
Distinct characters194
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

Unique359 ?
Unique (%)92.3%

Sample

1st row서울특별시 중구 을지로35길 32-28 (방산동)
2nd row서울특별시 중구 을지로 30 (소공동)
3rd row서울특별시 중구 중림로4길 30 (중림동,지하1층)
4th row서울특별시 중구 퇴계로 310 (쌍림동)
5th row서울특별시 중구 을지로32길 15-25 (을지로5가)
ValueCountFrequency (%)
서울특별시 388
 
15.0%
중구 388
 
15.0%
1층 101
 
3.9%
오장동 66
 
2.5%
을지로32길 64
 
2.5%
남대문시장4길 61
 
2.4%
9 44
 
1.7%
24 39
 
1.5%
신당동 37
 
1.4%
남창동 35
 
1.4%
Other values (615) 1366
52.8%
2024-05-11T15:14:32.491622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2203
 
16.6%
1 506
 
3.8%
487
 
3.7%
467
 
3.5%
3 432
 
3.2%
, 429
 
3.2%
2 426
 
3.2%
410
 
3.1%
408
 
3.1%
406
 
3.1%
Other values (184) 7130
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7336
55.1%
Decimal Number 2374
 
17.8%
Space Separator 2203
 
16.6%
Other Punctuation 431
 
3.2%
Open Punctuation 404
 
3.0%
Close Punctuation 404
 
3.0%
Dash Punctuation 75
 
0.6%
Uppercase Letter 66
 
0.5%
Lowercase Letter 6
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
487
 
6.6%
467
 
6.4%
410
 
5.6%
408
 
5.6%
406
 
5.5%
394
 
5.4%
388
 
5.3%
388
 
5.3%
385
 
5.2%
290
 
4.0%
Other values (153) 3313
45.2%
Decimal Number
ValueCountFrequency (%)
1 506
21.3%
3 432
18.2%
2 426
17.9%
4 269
11.3%
0 181
 
7.6%
5 147
 
6.2%
7 111
 
4.7%
8 104
 
4.4%
9 103
 
4.3%
6 95
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
D 27
40.9%
A 14
21.2%
B 9
 
13.6%
C 7
 
10.6%
E 5
 
7.6%
S 2
 
3.0%
N 1
 
1.5%
J 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
v 1
16.7%
n 1
16.7%
u 1
16.7%
l 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 429
99.5%
. 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 404
100.0%
Close Punctuation
ValueCountFrequency (%)
) 404
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7336
55.1%
Common 5896
44.3%
Latin 72
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
487
 
6.6%
467
 
6.4%
410
 
5.6%
408
 
5.6%
406
 
5.5%
394
 
5.4%
388
 
5.3%
388
 
5.3%
385
 
5.2%
290
 
4.0%
Other values (153) 3313
45.2%
Common
ValueCountFrequency (%)
2203
37.4%
1 506
 
8.6%
3 432
 
7.3%
, 429
 
7.3%
2 426
 
7.2%
( 404
 
6.9%
) 404
 
6.9%
4 269
 
4.6%
0 181
 
3.1%
5 147
 
2.5%
Other values (8) 495
 
8.4%
Latin
ValueCountFrequency (%)
D 27
37.5%
A 14
19.4%
B 9
 
12.5%
C 7
 
9.7%
E 5
 
6.9%
S 2
 
2.8%
e 2
 
2.8%
N 1
 
1.4%
J 1
 
1.4%
v 1
 
1.4%
Other values (3) 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7336
55.1%
ASCII 5968
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2203
36.9%
1 506
 
8.5%
3 432
 
7.2%
, 429
 
7.2%
2 426
 
7.1%
( 404
 
6.8%
) 404
 
6.8%
4 269
 
4.5%
0 181
 
3.0%
5 147
 
2.5%
Other values (21) 567
 
9.5%
Hangul
ValueCountFrequency (%)
487
 
6.6%
467
 
6.4%
410
 
5.6%
408
 
5.6%
406
 
5.5%
394
 
5.4%
388
 
5.3%
388
 
5.3%
385
 
5.2%
290
 
4.0%
Other values (153) 3313
45.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)19.6%
Missing271
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean4565.7655
Minimum4500
Maximum10252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:32.762401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4500
5-th percentile4527
Q14530
median4547
Q34547
95-th percentile4615
Maximum10252
Range5752
Interquartile range (IQR)17

Descriptive statistics

Standard deviation290.68234
Coefficient of variation (CV)0.063665631
Kurtosis381.256
Mean4565.7655
Median Absolute Deviation (MAD)14
Skewness19.442059
Sum1771517
Variance84496.221
MonotonicityNot monotonic
2024-05-11T15:14:33.019531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4547 129
19.6%
4529 55
 
8.3%
4546 32
 
4.9%
4528 20
 
3.0%
4530 12
 
1.8%
4533 10
 
1.5%
4576 5
 
0.8%
4534 5
 
0.8%
4591 4
 
0.6%
4597 4
 
0.6%
Other values (66) 112
17.0%
(Missing) 271
41.1%
ValueCountFrequency (%)
4500 1
 
0.2%
4503 2
0.3%
4504 1
 
0.2%
4505 1
 
0.2%
4508 1
 
0.2%
4509 2
0.3%
4511 1
 
0.2%
4513 1
 
0.2%
4515 1
 
0.2%
4516 3
0.5%
ValueCountFrequency (%)
10252 1
 
0.2%
4633 1
 
0.2%
4632 1
 
0.2%
4631 1
 
0.2%
4627 3
0.5%
4626 2
0.3%
4624 1
 
0.2%
4623 3
0.5%
4622 2
0.3%
4618 1
 
0.2%
Distinct611
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:14:33.496046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length5.7602428
Min length2

Characters and Unicode

Total characters3796
Distinct characters449
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

Unique565 ?
Unique (%)85.7%

Sample

1st row웅천상사
2nd row롯데쇼핑(주)
3rd row장원식품
4th row남영상사(주)
5th row삼한유통
ValueCountFrequency (%)
주식회사 19
 
2.6%
명동점 4
 
0.5%
제이에프앤비 4
 
0.5%
주)교동씨엠 3
 
0.4%
동경식품 3
 
0.4%
월푸드 3
 
0.4%
파랑월드 2
 
0.3%
함지식품 2
 
0.3%
선동실업(주 2
 
0.3%
태현유통 2
 
0.3%
Other values (657) 701
94.1%
2024-05-11T15:14:34.686853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
3.9%
) 137
 
3.6%
( 135
 
3.6%
114
 
3.0%
102
 
2.7%
93
 
2.4%
92
 
2.4%
86
 
2.3%
80
 
2.1%
79
 
2.1%
Other values (439) 2729
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3309
87.2%
Close Punctuation 137
 
3.6%
Open Punctuation 135
 
3.6%
Space Separator 86
 
2.3%
Lowercase Letter 66
 
1.7%
Uppercase Letter 47
 
1.2%
Decimal Number 9
 
0.2%
Other Punctuation 6
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
149
 
4.5%
114
 
3.4%
102
 
3.1%
93
 
2.8%
92
 
2.8%
80
 
2.4%
79
 
2.4%
70
 
2.1%
68
 
2.1%
64
 
1.9%
Other values (388) 2398
72.5%
Uppercase Letter
ValueCountFrequency (%)
C 6
12.8%
F 4
 
8.5%
M 4
 
8.5%
S 3
 
6.4%
E 3
 
6.4%
T 3
 
6.4%
H 3
 
6.4%
A 3
 
6.4%
B 3
 
6.4%
V 2
 
4.3%
Other values (10) 13
27.7%
Lowercase Letter
ValueCountFrequency (%)
o 11
16.7%
e 9
13.6%
a 7
10.6%
d 6
9.1%
n 5
7.6%
i 4
 
6.1%
r 3
 
4.5%
l 3
 
4.5%
g 3
 
4.5%
s 3
 
4.5%
Other values (7) 12
18.2%
Decimal Number
ValueCountFrequency (%)
8 2
22.2%
2 1
11.1%
3 1
11.1%
7 1
11.1%
9 1
11.1%
6 1
11.1%
0 1
11.1%
1 1
11.1%
Other Punctuation
ValueCountFrequency (%)
& 4
66.7%
. 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3309
87.2%
Common 374
 
9.9%
Latin 113
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
149
 
4.5%
114
 
3.4%
102
 
3.1%
93
 
2.8%
92
 
2.8%
80
 
2.4%
79
 
2.4%
70
 
2.1%
68
 
2.1%
64
 
1.9%
Other values (388) 2398
72.5%
Latin
ValueCountFrequency (%)
o 11
 
9.7%
e 9
 
8.0%
a 7
 
6.2%
d 6
 
5.3%
C 6
 
5.3%
n 5
 
4.4%
F 4
 
3.5%
i 4
 
3.5%
M 4
 
3.5%
S 3
 
2.7%
Other values (27) 54
47.8%
Common
ValueCountFrequency (%)
) 137
36.6%
( 135
36.1%
86
23.0%
& 4
 
1.1%
. 2
 
0.5%
8 2
 
0.5%
2 1
 
0.3%
3 1
 
0.3%
7 1
 
0.3%
9 1
 
0.3%
Other values (4) 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3309
87.2%
ASCII 487
 
12.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
149
 
4.5%
114
 
3.4%
102
 
3.1%
93
 
2.8%
92
 
2.8%
80
 
2.4%
79
 
2.4%
70
 
2.1%
68
 
2.1%
64
 
1.9%
Other values (388) 2398
72.5%
ASCII
ValueCountFrequency (%)
) 137
28.1%
( 135
27.7%
86
17.7%
o 11
 
2.3%
e 9
 
1.8%
a 7
 
1.4%
d 6
 
1.2%
C 6
 
1.2%
n 5
 
1.0%
& 4
 
0.8%
Other values (41) 81
16.6%
Distinct610
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1999-02-12 00:00:00
Maximum2024-04-30 11:18:11
2024-05-11T15:14:34.922637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:35.134969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
I
514 
U
145 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 514
78.0%
U 145
 
22.0%

Length

2024-05-11T15:14:35.379523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:35.552467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 514
78.0%
u 145
 
22.0%
Distinct176
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T15:14:35.751983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:36.023094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
식품소분업
659 

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 659
100.0%

Length

2024-05-11T15:14:36.260436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:36.465569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 659
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct290
Distinct (%)46.8%
Missing40
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean199283.81
Minimum182438.57
Maximum201959.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:36.685310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182438.57
5-th percentile197230.21
Q1198259.65
median199901.84
Q3200015.5
95-th percentile201347.79
Maximum201959.9
Range19521.328
Interquartile range (IQR)1755.846

Descriptive statistics

Standard deviation1403.419
Coefficient of variation (CV)0.007042313
Kurtosis32.102401
Mean199283.81
Median Absolute Deviation (MAD)1074.1149
Skewness-2.7948501
Sum1.2335668 × 108
Variance1969584.8
MonotonicityNot monotonic
2024-05-11T15:14:36.984655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198259.65357739 64
 
9.7%
197936.261142268 41
 
6.2%
200015.499568016 38
 
5.8%
198263.90839194 30
 
4.6%
197230.206089772 18
 
2.7%
200007.706358494 17
 
2.6%
200002.952736046 13
 
2.0%
199996.623217512 9
 
1.4%
201823.908977364 7
 
1.1%
198253.896034899 7
 
1.1%
Other values (280) 375
56.9%
(Missing) 40
 
6.1%
ValueCountFrequency (%)
182438.570400174 1
 
0.2%
196689.378204656 1
 
0.2%
196742.514203089 1
 
0.2%
196746.506418769 1
 
0.2%
196823.277384941 2
0.3%
196864.942838297 3
0.5%
196910.145101423 1
 
0.2%
197063.020822371 1
 
0.2%
197087.772928041 1
 
0.2%
197100.970920667 1
 
0.2%
ValueCountFrequency (%)
201959.898811582 1
 
0.2%
201866.039519433 1
 
0.2%
201823.908977364 7
1.1%
201805.019724045 1
 
0.2%
201744.608195905 1
 
0.2%
201729.243163099 1
 
0.2%
201709.571110817 1
 
0.2%
201704.709824399 1
 
0.2%
201703.923338909 1
 
0.2%
201689.153872791 2
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct290
Distinct (%)46.8%
Missing40
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean451233.06
Minimum449582.54
Maximum469091.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:37.285828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449582.54
5-th percentile450378.21
Q1450850.82
median451392.2
Q3451485.35
95-th percentile451820.37
Maximum469091.22
Range19508.689
Interquartile range (IQR)634.52827

Descriptive statistics

Standard deviation846.19403
Coefficient of variation (CV)0.0018752926
Kurtosis321.38009
Mean451233.06
Median Absolute Deviation (MAD)237.96583
Skewness15.111062
Sum2.7931326 × 108
Variance716044.34
MonotonicityNot monotonic
2024-05-11T15:14:37.543014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451392.198218657 64
 
9.7%
450837.498547725 41
 
6.2%
451485.349952584 38
 
5.8%
450960.762964932 30
 
4.6%
450446.684395506 18
 
2.7%
451436.293606541 17
 
2.6%
451823.532462914 13
 
2.0%
451764.640382462 9
 
1.4%
452076.818664092 7
 
1.1%
450905.28446798 7
 
1.1%
Other values (280) 375
56.9%
(Missing) 40
 
6.1%
ValueCountFrequency (%)
449582.535532427 1
0.2%
449638.824308081 2
0.3%
449777.020219574 1
0.2%
449919.627798891 1
0.2%
449984.760022967 1
0.2%
449991.726117085 2
0.3%
449991.895498034 1
0.2%
450010.190882608 1
0.2%
450057.342070413 1
0.2%
450072.485315804 2
0.3%
ValueCountFrequency (%)
469091.224213731 1
 
0.2%
452076.818664092 7
1.1%
452026.206096556 1
 
0.2%
451879.538815181 2
 
0.3%
451862.242663852 1
 
0.2%
451860.881154812 1
 
0.2%
451836.458256618 2
 
0.3%
451830.547003379 1
 
0.2%
451827.10709985 1
 
0.2%
451824.473329922 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
식품소분업
596 
<NA>
63 

Length

Max length5
Median length5
Mean length4.9044006
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 596
90.4%
<NA> 63
 
9.6%

Length

2024-05-11T15:14:37.789085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:37.969627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 596
90.4%
na 63
 
9.6%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
587 
<NA>
63 
1
 
4
2
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 587
89.1%
<NA> 63
 
9.6%
1 4
 
0.6%
2 3
 
0.5%
3 2
 
0.3%

Length

2024-05-11T15:14:38.190036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:38.424532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 587
89.1%
na 63
 
9.6%
1 4
 
0.6%
2 3
 
0.5%
3 2
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
589 
<NA>
63 
1
 
6
4
 
1

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 589
89.4%
<NA> 63
 
9.6%
1 6
 
0.9%
4 1
 
0.2%

Length

2024-05-11T15:14:38.663288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:38.858279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 589
89.4%
na 63
 
9.6%
1 6
 
0.9%
4 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
611 
기타
 
45
주택가주변
 
2
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.8725341
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 611
92.7%
기타 45
 
6.8%
주택가주변 2
 
0.3%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-11T15:14:39.090613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:39.352805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 611
92.7%
기타 45
 
6.8%
주택가주변 2
 
0.3%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
611 
기타
 
46
자율
 
2

Length

Max length4
Median length4
Mean length3.8543247
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 611
92.7%
기타 46
 
7.0%
자율 2
 
0.3%

Length

2024-05-11T15:14:39.552475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:39.726700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 611
92.7%
기타 46
 
7.0%
자율 2
 
0.3%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
532 
상수도전용
127 

Length

Max length5
Median length4
Mean length4.1927162
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 532
80.7%
상수도전용 127
 
19.3%

Length

2024-05-11T15:14:39.902836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:40.064212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 532
80.7%
상수도전용 127
 
19.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
596 
<NA>
63 

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 596
90.4%
<NA> 63
 
9.6%

Length

2024-05-11T15:14:40.279240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:40.498608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 596
90.4%
na 63
 
9.6%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.0%
Missing63
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean0.062080537
Minimum0
Maximum15
Zeros582
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:40.670717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.68194361
Coefficient of variation (CV)10.984821
Kurtosis393.48459
Mean0.062080537
Median Absolute Deviation (MAD)0
Skewness18.649763
Sum37
Variance0.46504709
MonotonicityNot monotonic
2024-05-11T15:14:40.894045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 582
88.3%
1 8
 
1.2%
2 3
 
0.5%
3 1
 
0.2%
15 1
 
0.2%
5 1
 
0.2%
(Missing) 63
 
9.6%
ValueCountFrequency (%)
0 582
88.3%
1 8
 
1.2%
2 3
 
0.5%
3 1
 
0.2%
5 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
5 1
 
0.2%
3 1
 
0.2%
2 3
 
0.5%
1 8
 
1.2%
0 582
88.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
593 
<NA>
63 
1
 
2
4
 
1

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 593
90.0%
<NA> 63
 
9.6%
1 2
 
0.3%
4 1
 
0.2%

Length

2024-05-11T15:14:41.132357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:41.289416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 593
90.0%
na 63
 
9.6%
1 2
 
0.3%
4 1
 
0.2%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.3%
Missing63
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean0.30704698
Minimum0
Maximum10
Zeros500
Zeros (%)75.9%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:41.443168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.90638297
Coefficient of variation (CV)2.9519358
Kurtosis31.236605
Mean0.30704698
Median Absolute Deviation (MAD)0
Skewness4.695786
Sum183
Variance0.82153009
MonotonicityNot monotonic
2024-05-11T15:14:41.614638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 500
75.9%
1 50
 
7.6%
2 29
 
4.4%
3 6
 
0.9%
5 5
 
0.8%
4 4
 
0.6%
6 1
 
0.2%
10 1
 
0.2%
(Missing) 63
 
9.6%
ValueCountFrequency (%)
0 500
75.9%
1 50
 
7.6%
2 29
 
4.4%
3 6
 
0.9%
4 4
 
0.6%
5 5
 
0.8%
6 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
6 1
 
0.2%
5 5
 
0.8%
4 4
 
0.6%
3 6
 
0.9%
2 29
 
4.4%
1 50
 
7.6%
0 500
75.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
587 
<NA>
63 
1
 
6
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 587
89.1%
<NA> 63
 
9.6%
1 6
 
0.9%
2 2
 
0.3%
3 1
 
0.2%

Length

2024-05-11T15:14:41.771491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:41.933112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 587
89.1%
na 63
 
9.6%
1 6
 
0.9%
2 2
 
0.3%
3 1
 
0.2%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
247 
임대
236 
자가
176 

Length

Max length4
Median length2
Mean length2.7496206
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> 247
37.5%
임대 236
35.8%
자가 176
26.7%

Length

2024-05-11T15:14:42.104455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:42.275187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
37.5%
임대 236
35.8%
자가 176
26.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
596 
<NA>
63 

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 596
90.4%
<NA> 63
 
9.6%

Length

2024-05-11T15:14:42.461598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:42.613480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 596
90.4%
na 63
 
9.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
596 
<NA>
63 

Length

Max length4
Median length1
Mean length1.2867982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 596
90.4%
<NA> 63
 
9.6%

Length

2024-05-11T15:14:42.781094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:42.982739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 596
90.4%
na 63
 
9.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing63
Missing (%)9.6%
Memory size1.4 KiB
False
596 
(Missing)
63 
ValueCountFrequency (%)
False 596
90.4%
(Missing) 63
 
9.6%
2024-05-11T15:14:43.110119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct101
Distinct (%)16.9%
Missing63
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean6.9502013
Minimum0
Maximum286.94
Zeros454
Zeros (%)68.9%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:14:43.262946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile36
Maximum286.94
Range286.94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22.161252
Coefficient of variation (CV)3.188577
Kurtosis61.022049
Mean6.9502013
Median Absolute Deviation (MAD)0
Skewness6.6478078
Sum4142.32
Variance491.1211
MonotonicityNot monotonic
2024-05-11T15:14:43.445729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 454
68.9%
10.0 9
 
1.4%
6.6 9
 
1.4%
33.0 5
 
0.8%
15.04 4
 
0.6%
9.9 4
 
0.6%
3.3 3
 
0.5%
30.0 3
 
0.5%
66.0 3
 
0.5%
3.0 2
 
0.3%
Other values (91) 100
 
15.2%
(Missing) 63
 
9.6%
ValueCountFrequency (%)
0.0 454
68.9%
0.87 1
 
0.2%
1.0 1
 
0.2%
1.65 1
 
0.2%
2.2 1
 
0.2%
3.0 2
 
0.3%
3.3 3
 
0.5%
3.5 1
 
0.2%
4.29 1
 
0.2%
4.8 1
 
0.2%
ValueCountFrequency (%)
286.94 1
0.2%
182.0 1
0.2%
172.82 1
0.2%
169.24 1
0.2%
125.62 1
0.2%
115.0 1
0.2%
88.22 1
0.2%
84.88 1
0.2%
74.38 1
0.2%
70.0 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing659
Missing (%)100.0%
Memory size5.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-109-1983-0002719830209<NA>3폐업2폐업20180309<NA><NA><NA>0222741347.00100812서울특별시 중구 방산동 116-2서울특별시 중구 을지로35길 32-28 (방산동)4546웅천상사2018-03-09 11:17:47I2018-08-31 23:59:59.0식품소분업200086.973863451747.615142식품소분업00기타기타상수도전용00000<NA>00N0.0<NA><NA><NA>
130100003010000-109-1986-0000119860906<NA>1영업/정상1영업<NA><NA><NA><NA>027723 013<NA>100070서울특별시 중구 소공동 1서울특별시 중구 을지로 30 (소공동)4533롯데쇼핑(주)2022-04-15 17:15:42U2021-12-03 23:07:00.0식품소분업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230100003010000-109-1989-000011989-06-02<NA>3폐업2폐업2023-05-22<NA><NA><NA>02 392 1758104.00100-859서울특별시 중구 중림동 393-2 지하1층서울특별시 중구 중림로4길 30 (중림동,지하1층)4503장원식품2023-05-22 11:51:33U2022-12-04 22:04:00.0식품소분업196742.514203450624.32997<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
330100003010000-109-1989-0000219891214<NA>1영업/정상1영업<NA><NA><NA><NA>022679 829<NA>100400서울특별시 중구 쌍림동 276-10서울특별시 중구 퇴계로 310 (쌍림동)4615남영상사(주)2002-01-26 00:00:00I2018-08-31 23:59:59.0식품소분업200466.604847451254.380291식품소분업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
430100003010000-109-1991-0017819910112<NA>3폐업2폐업20050214<NA><NA><NA>022234330682.93100871서울특별시 중구 황학동 1589-0<NA><NA>삼한유통1999-02-12 00:00:00I2018-08-31 23:59:59.0식품소분업201959.898812451862.242664식품소분업24주택가주변기타상수도전용00000<NA>00N0.0<NA><NA><NA>
530100003010000-109-1994-0000119940111<NA>3폐업2폐업20050401<NA><NA><NA>0222338148<NA>100870서울특별시 중구 황학동 1012<NA><NA>대도종합식품산업사2005-04-01 00:00:00I2018-08-31 23:59:59.0식품소분업201805.019724451696.542048식품소분업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
630100003010000-109-1994-0000219940302<NA>3폐업2폐업20020524<NA><NA><NA>0222638057<NA>100848서울특별시 중구 을지로4가 162-3<NA><NA>예덕종합물산주식회사2002-01-26 00:00:00I2018-08-31 23:59:59.0식품소분업199916.545265451556.573961식품소분업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
730100003010000-109-1994-000031994-05-26<NA>1영업/정상1영업<NA><NA><NA><NA>0222726415<NA>100-195서울특별시 중구 을지로5가 272-6<NA><NA>그린유통2024-01-26 15:36:29U2023-11-30 22:08:00.0식품소분업200000.509817451519.109287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830100003010000-109-1994-0000419940627<NA>3폐업2폐업20090609<NA><NA><NA>0222728395<NA>100310서울특별시 중구 오장동 139-15<NA><NA>새암식품유통2009-02-09 09:42:43I2018-08-31 23:59:59.0식품소분업200091.793057451440.686774식품소분업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
930100003010000-109-1994-0000519940728<NA>1영업/정상1영업<NA><NA><NA><NA>0222655076<NA>100195서울특별시 중구 을지로5가 272-4서울특별시 중구 을지로32길 15-25 (을지로5가)4547흥부식품2019-10-31 15:56:28U2019-11-02 02:40:00.0식품소분업200035.998677451519.255532식품소분업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
64930100003010000-109-2023-000032023-04-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.20100-731서울특별시 중구 순화동 5-2 순화빌딩서울특별시 중구 서소문로 89, 순화빌딩 17층 D-1718호 (순화동)4516(주)닥트리오컴퍼니2023-04-07 13:57:21I2022-12-04 00:09:00.0식품소분업197346.664858451164.449754<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65030100003010000-109-2023-000042023-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00100-869서울특별시 중구 황학동 444서울특별시 중구 퇴계로87길 39-26, 1층 (황학동)4576벅스유2023-04-25 09:48:42I2022-12-03 22:07:00.0식품소분업201689.153873451677.855985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65130100003010000-109-2023-000052023-06-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 2263285620.00100-281서울특별시 중구 인현동1가 112-3 한영빌딩서울특별시 중구 마른내로4길 3, 한영빌딩 1층 102호 (인현동1가)4556한국코디2023-06-09 10:59:48I2022-12-05 23:01:00.0식품소분업199407.554813451316.122181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65230100003010000-109-2023-000062023-06-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30100-804서울특별시 중구 남창동 51-1서울특별시 중구 소월로 3, 지하2층 B2-32호 (남창동)4528더존스푼2023-06-26 17:53:24I2022-12-05 22:08:00.0식품소분업197831.002724450794.314832<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65330100003010000-109-2023-000072023-07-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00100-300서울특별시 중구 초동 53-19서울특별시 중구 충무로 21-19, 1층 (초동)4555필로소피라운지2023-07-05 11:28:46I2022-12-07 00:07:00.0식품소분업199216.039356451215.114568<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65430100003010000-109-2023-000082023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.40100-195서울특별시 중구 을지로5가 274-32서울특별시 중구 을지로36길 17, 2층 (을지로5가)4547환sea푸드2023-09-01 17:55:07I2022-12-09 00:03:00.0식품소분업200084.133091451515.616018<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65530100003010000-109-2023-000092023-12-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.00100-310서울특별시 중구 오장동 206-3 넥서스타워서울특별시 중구 퇴계로51길 20, 넥서스타워 지2층 나19호 (오장동)4559목향2023-12-29 09:22:30I2022-11-01 21:01:00.0식품소분업200098.006851451307.510521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65630100003010000-109-2024-000012024-02-19<NA>1영업/정상1영업<NA><NA><NA><NA>022061809917.00100-840서울특별시 중구 신당동 372-96서울특별시 중구 동호로7길 31, 104호 (신당동)4596황진사김치가 약수대리점2024-02-19 15:25:18I2023-12-01 22:01:00.0식품소분업200893.965677450010.190883<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65730100003010000-109-2024-000022024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.00100-093서울특별시 중구 남대문로3가 96 청남빌딩서울특별시 중구 남대문로 29, 청남빌딩 1층 (남대문로3가)4526주식회사 금성관2024-03-29 10:48:40I2023-12-02 21:01:00.0식품소분업198061.045795451016.590199<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65830100003010000-109-2024-000032024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4.00100-804서울특별시 중구 남창동 51-1 에티버스타워서울특별시 중구 소월로 3, 에티버스타워 지하1층 222호 (남창동)4528오리온2024-04-30 11:18:11I2023-12-05 00:02:00.0식품소분업197831.002724450794.314832<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>