Overview

Dataset statistics

Number of variables44
Number of observations127
Missing cells1685
Missing cells (%)30.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.9 KiB
Average record size in memory378.0 B

Variable types

Categorical17
Text7
DateTime4
Unsupported9
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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18054/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (60.2%)Imbalance
여성종사자수 is highly imbalanced (60.2%)Imbalance
급수시설구분명 is highly imbalanced (83.9%)Imbalance
총인원 is highly imbalanced (60.2%)Imbalance
본사종업원수 is highly imbalanced (59.4%)Imbalance
공장생산직종업원수 is highly imbalanced (53.9%)Imbalance
보증액 is highly imbalanced (67.0%)Imbalance
인허가취소일자 has 127 (100.0%) missing valuesMissing
폐업일자 has 75 (59.1%) missing valuesMissing
휴업시작일자 has 127 (100.0%) missing valuesMissing
휴업종료일자 has 127 (100.0%) missing valuesMissing
재개업일자 has 127 (100.0%) missing valuesMissing
전화번호 has 70 (55.1%) missing valuesMissing
소재지면적 has 14 (11.0%) missing valuesMissing
도로명주소 has 11 (8.7%) missing valuesMissing
도로명우편번호 has 11 (8.7%) missing valuesMissing
영업장주변구분명 has 127 (100.0%) missing valuesMissing
등급구분명 has 127 (100.0%) missing valuesMissing
공장사무직종업원수 has 95 (74.8%) missing valuesMissing
공장판매직종업원수 has 97 (76.4%) missing valuesMissing
월세액 has 106 (83.5%) missing valuesMissing
다중이용업소여부 has 63 (49.6%) missing valuesMissing
전통업소지정번호 has 127 (100.0%) missing valuesMissing
전통업소주된음식 has 127 (100.0%) missing valuesMissing
홈페이지 has 127 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
공장사무직종업원수 has 20 (15.7%) zerosZeros
공장판매직종업원수 has 23 (18.1%) zerosZeros
월세액 has 16 (12.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:15:58.421928
Analysis finished2024-05-11 06:15:59.911270
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3020000
127 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 127
100.0%

Length

2024-05-11T06:16:00.185832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:00.672320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 127
100.0%

관리번호
Text

UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T06:16:01.270392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2794
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

Unique127 ?
Unique (%)100.0%

Sample

1st row3020000-135-2004-00001
2nd row3020000-135-2004-00002
3rd row3020000-135-2004-00003
4th row3020000-135-2004-00004
5th row3020000-135-2004-00005
ValueCountFrequency (%)
3020000-135-2004-00001 1
 
0.8%
3020000-135-2022-00006 1
 
0.8%
3020000-135-2022-00003 1
 
0.8%
3020000-135-2022-00002 1
 
0.8%
3020000-135-2022-00001 1
 
0.8%
3020000-135-2021-00013 1
 
0.8%
3020000-135-2021-00012 1
 
0.8%
3020000-135-2021-00011 1
 
0.8%
3020000-135-2021-00010 1
 
0.8%
3020000-135-2021-00009 1
 
0.8%
Other values (117) 117
92.1%
2024-05-11T06:16:02.453868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1287
46.1%
- 381
 
13.6%
2 356
 
12.7%
3 292
 
10.5%
1 230
 
8.2%
5 145
 
5.2%
4 35
 
1.3%
6 22
 
0.8%
7 18
 
0.6%
8 14
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2413
86.4%
Dash Punctuation 381
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1287
53.3%
2 356
 
14.8%
3 292
 
12.1%
1 230
 
9.5%
5 145
 
6.0%
4 35
 
1.5%
6 22
 
0.9%
7 18
 
0.7%
8 14
 
0.6%
9 14
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 381
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2794
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1287
46.1%
- 381
 
13.6%
2 356
 
12.7%
3 292
 
10.5%
1 230
 
8.2%
5 145
 
5.2%
4 35
 
1.3%
6 22
 
0.8%
7 18
 
0.6%
8 14
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1287
46.1%
- 381
 
13.6%
2 356
 
12.7%
3 292
 
10.5%
1 230
 
8.2%
5 145
 
5.2%
4 35
 
1.3%
6 22
 
0.8%
7 18
 
0.6%
8 14
 
0.5%

인허가일자
Date

Distinct121
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2004-05-18 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T06:16:03.129110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:16:03.772911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
75 
3
52 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 75
59.1%
3 52
40.9%

Length

2024-05-11T06:16:04.218409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:04.619492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 75
59.1%
3 52
40.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업/정상
75 
폐업
52 

Length

Max length5
Median length5
Mean length3.7716535
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 75
59.1%
폐업 52
40.9%

Length

2024-05-11T06:16:05.078125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:05.547056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 75
59.1%
폐업 52
40.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
75 
2
52 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 75
59.1%
2 52
40.9%

Length

2024-05-11T06:16:06.002254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:06.582202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 75
59.1%
2 52
40.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업
75 
폐업
52 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 75
59.1%
폐업 52
40.9%

Length

2024-05-11T06:16:07.050794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:07.423532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 75
59.1%
폐업 52
40.9%

폐업일자
Date

MISSING 

Distinct45
Distinct (%)86.5%
Missing75
Missing (%)59.1%
Memory size1.1 KiB
Minimum2006-02-22 00:00:00
Maximum2024-04-15 00:00:00
2024-05-11T06:16:07.858742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:16:08.338692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

전화번호
Text

MISSING 

Distinct57
Distinct (%)100.0%
Missing70
Missing (%)55.1%
Memory size1.1 KiB
2024-05-11T06:16:09.016396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.105263
Min length7

Characters and Unicode

Total characters633
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

Unique57 ?
Unique (%)100.0%

Sample

1st row02 7964657
2nd row7095114
3rd row02 7975723
4th row02 7935441
5th row027985 007
ValueCountFrequency (%)
02 34
28.3%
070 6
 
5.0%
031 2
 
1.7%
558 2
 
1.7%
798 2
 
1.7%
792 2
 
1.7%
799 2
 
1.7%
704 1
 
0.8%
7463 1
 
0.8%
9355 1
 
0.8%
Other values (67) 67
55.8%
2024-05-11T06:16:10.065050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 114
18.0%
86
13.6%
2 83
13.1%
7 71
11.2%
5 51
8.1%
1 44
 
7.0%
9 41
 
6.5%
6 38
 
6.0%
4 38
 
6.0%
8 34
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 547
86.4%
Space Separator 86
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 114
20.8%
2 83
15.2%
7 71
13.0%
5 51
9.3%
1 44
 
8.0%
9 41
 
7.5%
6 38
 
6.9%
4 38
 
6.9%
8 34
 
6.2%
3 33
 
6.0%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 633
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 114
18.0%
86
13.6%
2 83
13.1%
7 71
11.2%
5 51
8.1%
1 44
 
7.0%
9 41
 
6.5%
6 38
 
6.0%
4 38
 
6.0%
8 34
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 114
18.0%
86
13.6%
2 83
13.1%
7 71
11.2%
5 51
8.1%
1 44
 
7.0%
9 41
 
6.5%
6 38
 
6.0%
4 38
 
6.0%
8 34
 
5.4%

소재지면적
Text

MISSING 

Distinct73
Distinct (%)64.6%
Missing14
Missing (%)11.0%
Memory size1.1 KiB
2024-05-11T06:16:10.757524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0176991
Min length3

Characters and Unicode

Total characters567
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

Unique62 ?
Unique (%)54.9%

Sample

1st row170.48
2nd row13,103.00
3rd row190.00
4th row56.00
5th row.00
ValueCountFrequency (%)
3.30 15
 
13.3%
10.00 12
 
10.6%
100.00 4
 
3.5%
00 3
 
2.7%
30.00 3
 
2.7%
33.00 3
 
2.7%
15.00 3
 
2.7%
5.00 2
 
1.8%
0.00 2
 
1.8%
1.10 2
 
1.8%
Other values (63) 64
56.6%
2024-05-11T06:16:11.918816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 192
33.9%
. 113
19.9%
1 61
 
10.8%
3 58
 
10.2%
5 28
 
4.9%
6 25
 
4.4%
4 23
 
4.1%
8 20
 
3.5%
2 19
 
3.4%
9 13
 
2.3%
Other values (2) 15
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 451
79.5%
Other Punctuation 116
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 192
42.6%
1 61
 
13.5%
3 58
 
12.9%
5 28
 
6.2%
6 25
 
5.5%
4 23
 
5.1%
8 20
 
4.4%
2 19
 
4.2%
9 13
 
2.9%
7 12
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 113
97.4%
, 3
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 192
33.9%
. 113
19.9%
1 61
 
10.8%
3 58
 
10.2%
5 28
 
4.9%
6 25
 
4.4%
4 23
 
4.1%
8 20
 
3.5%
2 19
 
3.4%
9 13
 
2.3%
Other values (2) 15
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 192
33.9%
. 113
19.9%
1 61
 
10.8%
3 58
 
10.2%
5 28
 
4.9%
6 25
 
4.4%
4 23
 
4.1%
8 20
 
3.5%
2 19
 
3.4%
9 13
 
2.3%
Other values (2) 15
 
2.6%

소재지우편번호
Text

Distinct79
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T06:16:12.651859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3779528
Min length6

Characters and Unicode

Total characters810
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

Unique50 ?
Unique (%)39.4%

Sample

1st row140880
2nd row140871
3rd row140775
4th row140871
5th row140011
ValueCountFrequency (%)
140-012 6
 
4.7%
140011 4
 
3.1%
140-013 4
 
3.1%
140887 4
 
3.1%
140863 4
 
3.1%
140882 3
 
2.4%
140901 3
 
2.4%
140884 3
 
2.4%
140872 3
 
2.4%
140871 3
 
2.4%
Other values (69) 90
70.9%
2024-05-11T06:16:13.796654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 180
22.2%
0 178
22.0%
4 138
17.0%
8 99
12.2%
7 49
 
6.0%
- 48
 
5.9%
2 33
 
4.1%
3 31
 
3.8%
9 26
 
3.2%
5 17
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 762
94.1%
Dash Punctuation 48
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 180
23.6%
0 178
23.4%
4 138
18.1%
8 99
13.0%
7 49
 
6.4%
2 33
 
4.3%
3 31
 
4.1%
9 26
 
3.4%
5 17
 
2.2%
6 11
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 180
22.2%
0 178
22.0%
4 138
17.0%
8 99
12.2%
7 49
 
6.0%
- 48
 
5.9%
2 33
 
4.1%
3 31
 
3.8%
9 26
 
3.2%
5 17
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 180
22.2%
0 178
22.0%
4 138
17.0%
8 99
12.2%
7 49
 
6.0%
- 48
 
5.9%
2 33
 
4.1%
3 31
 
3.8%
9 26
 
3.2%
5 17
 
2.1%

지번주소
Text

Distinct111
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T06:16:14.374629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length26.07874
Min length17

Characters and Unicode

Total characters3312
Distinct characters171
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)78.7%

Sample

1st row서울특별시 용산구 한강로*가 **-*번지
2nd row서울특별시 용산구 한강로*가 ***번지
3rd row서울특별시 용산구 이태원동 ***-***번지 남송빌딩 별관 ***호
4th row서울특별시 용산구 한강로*가 ***-*번지 대우디오빌 ****호
5th row서울특별시 용산구 한강로*가 ***-*번지
ValueCountFrequency (%)
서울특별시 127
20.2%
용산구 127
20.2%
83
13.2%
한강로*가 46
 
7.3%
번지 42
 
6.7%
호 16
 
2.5%
이태원동 13
 
2.1%
한남동 13
 
2.1%
층 10
 
1.6%
원효로*가 10
 
1.6%
Other values (90) 141
22.5%
2024-05-11T06:16:15.474584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 619
18.7%
559
16.9%
용 148
 
4.5%
산 144
 
4.3%
시 132
 
4.0%
서 131
 
4.0%
울 129
 
3.9%
별 128
 
3.9%
구 128
 
3.9%
특 127
 
3.8%
Other values (161) 1067
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2004
60.5%
Other Punctuation 622
 
18.8%
Space Separator 559
 
16.9%
Dash Punctuation 96
 
2.9%
Uppercase Letter 14
 
0.4%
Decimal Number 12
 
0.4%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 148
 
7.4%
산 144
 
7.2%
시 132
 
6.6%
서 131
 
6.5%
울 129
 
6.4%
별 128
 
6.4%
구 128
 
6.4%
특 127
 
6.3%
동 86
 
4.3%
가 70
 
3.5%
Other values (135) 781
39.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
21.4%
S 2
14.3%
T 1
 
7.1%
H 1
 
7.1%
L 1
 
7.1%
E 1
 
7.1%
V 1
 
7.1%
K 1
 
7.1%
D 1
 
7.1%
G 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 4
33.3%
4 2
16.7%
3 2
16.7%
5 1
 
8.3%
9 1
 
8.3%
8 1
 
8.3%
6 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
* 619
99.5%
, 2
 
0.3%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
559
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2004
60.5%
Common 1293
39.0%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 148
 
7.4%
산 144
 
7.2%
시 132
 
6.6%
서 131
 
6.5%
울 129
 
6.4%
별 128
 
6.4%
구 128
 
6.4%
특 127
 
6.3%
동 86
 
4.3%
가 70
 
3.5%
Other values (135) 781
39.0%
Common
ValueCountFrequency (%)
* 619
47.9%
559
43.2%
- 96
 
7.4%
2 4
 
0.3%
4 2
 
0.2%
, 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
3 2
 
0.2%
5 1
 
0.1%
Other values (4) 4
 
0.3%
Latin
ValueCountFrequency (%)
I 3
20.0%
S 2
13.3%
T 1
 
6.7%
H 1
 
6.7%
L 1
 
6.7%
E 1
 
6.7%
V 1
 
6.7%
Ⅲ 1
 
6.7%
K 1
 
6.7%
D 1
 
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2004
60.5%
ASCII 1307
39.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 619
47.4%
559
42.8%
- 96
 
7.3%
2 4
 
0.3%
I 3
 
0.2%
4 2
 
0.2%
, 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
S 2
 
0.2%
Other values (15) 16
 
1.2%
Hangul
ValueCountFrequency (%)
용 148
 
7.4%
산 144
 
7.2%
시 132
 
6.6%
서 131
 
6.5%
울 129
 
6.4%
별 128
 
6.4%
구 128
 
6.4%
특 127
 
6.3%
동 86
 
4.3%
가 70
 
3.5%
Other values (135) 781
39.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

도로명주소
Text

MISSING 

Distinct105
Distinct (%)90.5%
Missing11
Missing (%)8.7%
Memory size1.1 KiB
2024-05-11T06:16:16.116219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length36.956897
Min length24

Characters and Unicode

Total characters4287
Distinct characters188
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)83.6%

Sample

1st row서울특별시 용산구 한강대로 *** (한강로*가,대우디오빌 ****호)
2nd row서울특별시 용산구 한강대로 *** (한강로*가)
3rd row서울특별시 용산구 한강대로 ***, 아모레퍼시픽 *층 (한강로*가)
4th row서울특별시 용산구 한강대로 ** (한강로*가,신세기한덕빌딩 *층)
5th row서울특별시 용산구 한강대로 *** (갈월동)
ValueCountFrequency (%)
서울특별시 116
14.2%
용산구 116
14.2%
115
14.1%
층 67
 
8.2%
호 50
 
6.1%
한강로*가 39
 
4.8%
한강대로 21
 
2.6%
이태원동 12
 
1.5%
한남동 11
 
1.3%
동 10
 
1.2%
Other values (143) 260
31.8%
2024-05-11T06:16:17.636613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 722
16.8%
701
 
16.4%
로 165
 
3.8%
, 142
 
3.3%
용 136
 
3.2%
산 133
 
3.1%
서 131
 
3.1%
시 123
 
2.9%
( 119
 
2.8%
울 119
 
2.8%
Other values (178) 1796
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2419
56.4%
Other Punctuation 866
 
20.2%
Space Separator 701
 
16.4%
Open Punctuation 119
 
2.8%
Close Punctuation 119
 
2.8%
Uppercase Letter 21
 
0.5%
Dash Punctuation 20
 
0.5%
Decimal Number 20
 
0.5%
Lowercase Letter 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 165
 
6.8%
용 136
 
5.6%
산 133
 
5.5%
서 131
 
5.4%
시 123
 
5.1%
울 119
 
4.9%
별 118
 
4.9%
구 117
 
4.8%
특 116
 
4.8%
동 97
 
4.0%
Other values (150) 1164
48.1%
Uppercase Letter
ValueCountFrequency (%)
E 3
14.3%
L 3
14.3%
I 3
14.3%
B 2
9.5%
S 2
9.5%
A 2
9.5%
N 2
9.5%
T 1
 
4.8%
H 1
 
4.8%
V 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 6
30.0%
2 4
20.0%
0 4
20.0%
4 2
 
10.0%
6 2
 
10.0%
7 1
 
5.0%
3 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
* 722
83.4%
, 142
 
16.4%
: 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
701
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2419
56.4%
Common 1845
43.0%
Latin 23
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 165
 
6.8%
용 136
 
5.6%
산 133
 
5.5%
서 131
 
5.4%
시 123
 
5.1%
울 119
 
4.9%
별 118
 
4.9%
구 117
 
4.8%
특 116
 
4.8%
동 97
 
4.0%
Other values (150) 1164
48.1%
Common
ValueCountFrequency (%)
* 722
39.1%
701
38.0%
, 142
 
7.7%
( 119
 
6.4%
) 119
 
6.4%
- 20
 
1.1%
1 6
 
0.3%
2 4
 
0.2%
0 4
 
0.2%
4 2
 
0.1%
Other values (5) 6
 
0.3%
Latin
ValueCountFrequency (%)
E 3
13.0%
L 3
13.0%
I 3
13.0%
B 2
8.7%
S 2
8.7%
A 2
8.7%
N 2
8.7%
b 1
 
4.3%
T 1
 
4.3%
H 1
 
4.3%
Other values (3) 3
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2419
56.4%
ASCII 1867
43.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 722
38.7%
701
37.5%
, 142
 
7.6%
( 119
 
6.4%
) 119
 
6.4%
- 20
 
1.1%
1 6
 
0.3%
2 4
 
0.2%
0 4
 
0.2%
E 3
 
0.2%
Other values (17) 27
 
1.4%
Hangul
ValueCountFrequency (%)
로 165
 
6.8%
용 136
 
5.6%
산 133
 
5.5%
서 131
 
5.4%
시 123
 
5.1%
울 119
 
4.9%
별 118
 
4.9%
구 117
 
4.8%
특 116
 
4.8%
동 97
 
4.0%
Other values (150) 1164
48.1%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)50.0%
Missing11
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean4365.5517
Minimum4300
Maximum4420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:18.137367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4309
Q14337.5
median4376
Q34387
95-th percentile4408
Maximum4420
Range120
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation31.919558
Coefficient of variation (CV)0.0073116893
Kurtosis-0.85693542
Mean4365.5517
Median Absolute Deviation (MAD)17
Skewness-0.49658838
Sum506404
Variance1018.8582
MonotonicityNot monotonic
2024-05-11T06:16:18.790017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4382 7
 
5.5%
4378 7
 
5.5%
4387 7
 
5.5%
4376 6
 
4.7%
4328 4
 
3.1%
4386 4
 
3.1%
4401 4
 
3.1%
4373 4
 
3.1%
4392 3
 
2.4%
4344 3
 
2.4%
Other values (48) 67
52.8%
(Missing) 11
 
8.7%
ValueCountFrequency (%)
4300 1
 
0.8%
4307 1
 
0.8%
4308 3
2.4%
4309 3
2.4%
4310 1
 
0.8%
4312 1
 
0.8%
4314 1
 
0.8%
4315 1
 
0.8%
4316 2
1.6%
4317 1
 
0.8%
ValueCountFrequency (%)
4420 2
1.6%
4419 2
1.6%
4416 1
 
0.8%
4414 1
 
0.8%
4406 1
 
0.8%
4405 2
1.6%
4402 1
 
0.8%
4401 4
3.1%
4398 1
 
0.8%
4395 1
 
0.8%

사업장명
Text

Distinct125
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T06:16:19.866221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length8.8188976
Min length2

Characters and Unicode

Total characters1120
Distinct characters258
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)96.9%

Sample

1st row(주)씨스팜
2nd row(주)아모레퍼시픽
3rd row(주)포모펠릭스
4th row(주)비트로시스인터내셔날
5th row주-휴먼앤위팡
ValueCountFrequency (%)
주식회사 34
 
20.1%
도즈랩 2
 
1.2%
주)아모레퍼시픽 2
 
1.2%
주)에코제이비 1
 
0.6%
바스켓코퍼레이션 1
 
0.6%
핀슬러코리아 1
 
0.6%
발렌라이프 1
 
0.6%
큐라에스 1
 
0.6%
주)소키씨앤티 1
 
0.6%
주)마르코코리아 1
 
0.6%
Other values (124) 124
73.4%
2024-05-11T06:16:22.004094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 102
 
9.1%
) 69
 
6.2%
( 69
 
6.2%
이 48
 
4.3%
42
 
3.8%
사 40
 
3.6%
식 37
 
3.3%
회 37
 
3.3%
스 31
 
2.8%
리 25
 
2.2%
Other values (248) 620
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 916
81.8%
Close Punctuation 69
 
6.2%
Open Punctuation 69
 
6.2%
Space Separator 42
 
3.8%
Uppercase Letter 13
 
1.2%
Lowercase Letter 8
 
0.7%
Decimal Number 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 102
 
11.1%
이 48
 
5.2%
사 40
 
4.4%
식 37
 
4.0%
회 37
 
4.0%
스 31
 
3.4%
리 25
 
2.7%
아 22
 
2.4%
코 18
 
2.0%
에 16
 
1.7%
Other values (225) 540
59.0%
Uppercase Letter
ValueCountFrequency (%)
E 3
23.1%
O 2
15.4%
B 2
15.4%
N 1
 
7.7%
Y 1
 
7.7%
R 1
 
7.7%
V 1
 
7.7%
H 1
 
7.7%
M 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
b 1
12.5%
m 1
12.5%
o 1
12.5%
y 1
12.5%
t 1
12.5%
u 1
12.5%
a 1
12.5%
e 1
12.5%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 916
81.8%
Common 183
 
16.3%
Latin 21
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 102
 
11.1%
이 48
 
5.2%
사 40
 
4.4%
식 37
 
4.0%
회 37
 
4.0%
스 31
 
3.4%
리 25
 
2.7%
아 22
 
2.4%
코 18
 
2.0%
에 16
 
1.7%
Other values (225) 540
59.0%
Latin
ValueCountFrequency (%)
E 3
14.3%
O 2
 
9.5%
B 2
 
9.5%
N 1
 
4.8%
Y 1
 
4.8%
R 1
 
4.8%
V 1
 
4.8%
b 1
 
4.8%
m 1
 
4.8%
o 1
 
4.8%
Other values (7) 7
33.3%
Common
ValueCountFrequency (%)
) 69
37.7%
( 69
37.7%
42
23.0%
- 1
 
0.5%
3 1
 
0.5%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 916
81.8%
ASCII 204
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 102
 
11.1%
이 48
 
5.2%
사 40
 
4.4%
식 37
 
4.0%
회 37
 
4.0%
스 31
 
3.4%
리 25
 
2.7%
아 22
 
2.4%
코 18
 
2.0%
에 16
 
1.7%
Other values (225) 540
59.0%
ASCII
ValueCountFrequency (%)
) 69
33.8%
( 69
33.8%
42
20.6%
E 3
 
1.5%
O 2
 
1.0%
B 2
 
1.0%
N 1
 
0.5%
Y 1
 
0.5%
R 1
 
0.5%
V 1
 
0.5%
Other values (13) 13
 
6.4%

최종수정일자
Date

UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2004-11-04 00:00:00
Maximum2024-04-26 17:35:46
2024-05-11T06:16:22.680008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:16:23.399483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
I
66 
U
61 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 66
52.0%
U 61
48.0%

Length

2024-05-11T06:16:23.837931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:24.467431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 66
52.0%
u 61
48.0%

데이터갱신일자
Date

Distinct83
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-05-11T06:16:25.033034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:16:25.550602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
건강기능식품유통전문판매업
127 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 127
100.0%

Length

2024-05-11T06:16:26.146136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:26.571041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 127
100.0%

좌표정보(X)
Real number (ℝ)

Distinct99
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197755.3
Minimum195385.72
Maximum201013.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:27.052606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195385.72
5-th percentile196083.42
Q1196888.3
median197219.56
Q3198971.77
95-th percentile200422.06
Maximum201013.82
Range5628.0968
Interquartile range (IQR)2083.4674

Descriptive statistics

Standard deviation1351.809
Coefficient of variation (CV)0.0068357659
Kurtosis-0.43737165
Mean197755.3
Median Absolute Deviation (MAD)512.43331
Skewness0.79451258
Sum25114923
Variance1827387.5
MonotonicityNot monotonic
2024-05-11T06:16:27.656263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197056.728931087 6
 
4.7%
198470.128904862 4
 
3.1%
196861.350875235 4
 
3.1%
197138.702350444 3
 
2.4%
198066.163465586 2
 
1.6%
197563.069805939 2
 
1.6%
197117.41843467 2
 
1.6%
199446.264890312 2
 
1.6%
197011.737528847 2
 
1.6%
196081.468322436 2
 
1.6%
Other values (89) 98
77.2%
ValueCountFrequency (%)
195385.722601944 1
0.8%
195653.553341643 1
0.8%
195907.049513033 1
0.8%
196005.836412851 1
0.8%
196060.559012563 1
0.8%
196081.468322436 2
1.6%
196087.977652228 2
1.6%
196103.276672219 1
0.8%
196170.529435542 1
0.8%
196189.205036161 1
0.8%
ValueCountFrequency (%)
201013.819447755 1
0.8%
200887.091124451 1
0.8%
200793.804471719 1
0.8%
200697.42588055 1
0.8%
200597.940803088 1
0.8%
200463.643383148 1
0.8%
200449.713090044 1
0.8%
200357.541925483 1
0.8%
200231.538140657 1
0.8%
200162.364933746 2
1.6%

좌표정보(Y)
Real number (ℝ)

Distinct99
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448094.49
Minimum446768.13
Maximum450168.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:28.193232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446768.13
5-th percentile447017.87
Q1447430.1
median447925.58
Q3448714.75
95-th percentile449684.32
Maximum450168.32
Range3400.1944
Interquartile range (IQR)1284.6474

Descriptive statistics

Standard deviation881.57269
Coefficient of variation (CV)0.0019673813
Kurtosis-0.54403019
Mean448094.49
Median Absolute Deviation (MAD)597.02853
Skewness0.65898581
Sum56908000
Variance777170.41
MonotonicityNot monotonic
2024-05-11T06:16:28.791270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447077.126289262 6
 
4.7%
449639.883505951 4
 
3.1%
447226.720509901 4
 
3.1%
449437.548980044 3
 
2.4%
449321.068367082 2
 
1.6%
449934.157783456 2
 
1.6%
447527.338271365 2
 
1.6%
447655.336883019 2
 
1.6%
447430.100250997 2
 
1.6%
447051.059264129 2
 
1.6%
Other values (89) 98
77.2%
ValueCountFrequency (%)
446768.129158285 2
 
1.6%
446850.237245754 1
 
0.8%
446918.407128289 1
 
0.8%
446976.898272172 1
 
0.8%
446986.411557186 1
 
0.8%
447009.361612995 1
 
0.8%
447037.735392015 1
 
0.8%
447051.059264129 2
 
1.6%
447073.62284187 2
 
1.6%
447077.126289262 6
4.7%
ValueCountFrequency (%)
450168.3235982 1
 
0.8%
450126.951675139 1
 
0.8%
450119.606517113 1
 
0.8%
449934.157783456 2
1.6%
449844.319841559 1
 
0.8%
449690.498160018 1
 
0.8%
449669.915617367 1
 
0.8%
449639.883505951 4
3.1%
449437.548980044 3
2.4%
449321.068367082 2
1.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
건강기능식품유통전문판매업
64 
<NA>
63 

Length

Max length13
Median length13
Mean length8.5354331
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 64
50.4%
<NA> 63
49.6%

Length

2024-05-11T06:16:29.270799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:29.560960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 64
50.4%
na 63
49.6%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
117 
0
 
10

Length

Max length4
Median length4
Mean length3.7637795
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> 117
92.1%
0 10
 
7.9%

Length

2024-05-11T06:16:29.960417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:30.407242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
92.1%
0 10
 
7.9%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
117 
0
 
10

Length

Max length4
Median length4
Mean length3.7637795
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> 117
92.1%
0 10
 
7.9%

Length

2024-05-11T06:16:30.927067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:31.437267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
92.1%
0 10
 
7.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
124 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.023622
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 124
97.6%
상수도전용 3
 
2.4%

Length

2024-05-11T06:16:32.058431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:32.555246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
97.6%
상수도전용 3
 
2.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
117 
0
 
10

Length

Max length4
Median length4
Mean length3.7637795
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> 117
92.1%
0 10
 
7.9%

Length

2024-05-11T06:16:33.019079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:33.455854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
92.1%
0 10
 
7.9%

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
97 
0
24 
13
 
2
2
 
2
2500
 
1

Length

Max length4
Median length4
Mean length3.3307087
Min length1

Unique

Unique2 ?
Unique (%)1.6%

Sample

1st row13
2nd row2500
3rd row0
4th row0
5th row2

Common Values

ValueCountFrequency (%)
<NA> 97
76.4%
0 24
 
18.9%
13 2
 
1.6%
2 2
 
1.6%
2500 1
 
0.8%
5 1
 
0.8%

Length

2024-05-11T06:16:34.049251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:34.500695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 97
76.4%
0 24
 
18.9%
13 2
 
1.6%
2 2
 
1.6%
2500 1
 
0.8%
5 1
 
0.8%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)28.1%
Missing95
Missing (%)74.8%
Infinite0
Infinite (%)0.0%
Mean79.375
Minimum0
Maximum2500
Zeros20
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:34.998155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7.9
Maximum2500
Range2500
Interquartile range (IQR)2

Descriptive statistics

Standard deviation441.71971
Coefficient of variation (CV)5.5649728
Kurtosis31.998063
Mean79.375
Median Absolute Deviation (MAD)0
Skewness5.6566056
Sum2540
Variance195116.31
MonotonicityNot monotonic
2024-05-11T06:16:35.620152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 20
 
15.7%
1 3
 
2.4%
2 2
 
1.6%
4 2
 
1.6%
2500 1
 
0.8%
3 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
9 1
 
0.8%
(Missing) 95
74.8%
ValueCountFrequency (%)
0 20
15.7%
1 3
 
2.4%
2 2
 
1.6%
3 1
 
0.8%
4 2
 
1.6%
6 1
 
0.8%
7 1
 
0.8%
9 1
 
0.8%
2500 1
 
0.8%
ValueCountFrequency (%)
2500 1
 
0.8%
9 1
 
0.8%
7 1
 
0.8%
6 1
 
0.8%
4 2
 
1.6%
3 1
 
0.8%
2 2
 
1.6%
1 3
 
2.4%
0 20
15.7%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)26.7%
Missing97
Missing (%)76.4%
Infinite0
Infinite (%)0.0%
Mean1.1666667
Minimum0
Maximum10
Zeros23
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:36.103477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6140645
Coefficient of variation (CV)2.2406267
Kurtosis4.9156935
Mean1.1666667
Median Absolute Deviation (MAD)0
Skewness2.373964
Sum35
Variance6.8333333
MonotonicityNot monotonic
2024-05-11T06:16:36.609694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 23
 
18.1%
8 1
 
0.8%
1 1
 
0.8%
3 1
 
0.8%
6 1
 
0.8%
10 1
 
0.8%
5 1
 
0.8%
2 1
 
0.8%
(Missing) 97
76.4%
ValueCountFrequency (%)
0 23
18.1%
1 1
 
0.8%
2 1
 
0.8%
3 1
 
0.8%
5 1
 
0.8%
6 1
 
0.8%
8 1
 
0.8%
10 1
 
0.8%
ValueCountFrequency (%)
10 1
 
0.8%
8 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
3 1
 
0.8%
2 1
 
0.8%
1 1
 
0.8%
0 23
18.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
97 
0
27 
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.2913386
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row0
2nd row0
3rd row4
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 97
76.4%
0 27
 
21.3%
2 2
 
1.6%
4 1
 
0.8%

Length

2024-05-11T06:16:37.176406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:37.658666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 97
76.4%
0 27
 
21.3%
2 2
 
1.6%
4 1
 
0.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
75 
자가
31 
임대
21 

Length

Max length4
Median length4
Mean length3.1811024
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임대
2nd row자가
3rd row임대
4th row임대
5th row임대

Common Values

ValueCountFrequency (%)
<NA> 75
59.1%
자가 31
24.4%
임대 21
 
16.5%

Length

2024-05-11T06:16:38.300175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:38.858963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 75
59.1%
자가 31
24.4%
임대 21
 
16.5%

보증액
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
106 
0
16 
10000000
 
2
55000000
 
1
14000000
 
1

Length

Max length9
Median length4
Mean length3.7874016
Min length1

Unique

Unique3 ?
Unique (%)2.4%

Sample

1st row55000000
2nd row0
3rd row10000000
4th row10000000
5th row0

Common Values

ValueCountFrequency (%)
<NA> 106
83.5%
0 16
 
12.6%
10000000 2
 
1.6%
55000000 1
 
0.8%
14000000 1
 
0.8%
200000000 1
 
0.8%

Length

2024-05-11T06:16:39.430424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:39.962455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
83.5%
0 16
 
12.6%
10000000 2
 
1.6%
55000000 1
 
0.8%
14000000 1
 
0.8%
200000000 1
 
0.8%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)28.6%
Missing106
Missing (%)83.5%
Infinite0
Infinite (%)0.0%
Mean517619.05
Minimum0
Maximum6000000
Zeros16
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T06:16:40.457595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2200000
Maximum6000000
Range6000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1372158.5
Coefficient of variation (CV)2.6509043
Kurtosis13.880705
Mean517619.05
Median Absolute Deviation (MAD)0
Skewness3.5842112
Sum10870000
Variance1.882819 × 1012
MonotonicityNot monotonic
2024-05-11T06:16:40.913483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 16
 
12.6%
1100000 1
 
0.8%
2200000 1
 
0.8%
770000 1
 
0.8%
800000 1
 
0.8%
6000000 1
 
0.8%
(Missing) 106
83.5%
ValueCountFrequency (%)
0 16
12.6%
770000 1
 
0.8%
800000 1
 
0.8%
1100000 1
 
0.8%
2200000 1
 
0.8%
6000000 1
 
0.8%
ValueCountFrequency (%)
6000000 1
 
0.8%
2200000 1
 
0.8%
1100000 1
 
0.8%
800000 1
 
0.8%
770000 1
 
0.8%
0 16
12.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.6%
Missing63
Missing (%)49.6%
Memory size386.0 B
False
64 
(Missing)
63 
ValueCountFrequency (%)
False 64
50.4%
(Missing) 63
49.6%
2024-05-11T06:16:41.351156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
63 
0.0
62 
63.33
 
1
30.0
 
1

Length

Max length5
Median length4
Mean length3.519685
Min length3

Unique

Unique2 ?
Unique (%)1.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
<NA> 63
49.6%
0.0 62
48.8%
63.33 1
 
0.8%
30.0 1
 
0.8%

Length

2024-05-11T06:16:41.784494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:16:42.346904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 63
49.6%
0.0 62
48.8%
63.33 1
 
0.8%
30.0 1
 
0.8%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing127
Missing (%)100.0%
Memory size1.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030200003020000-135-2004-0000120040518<NA>3폐업2폐업20060619<NA><NA><NA>02 7964657170.48140880서울특별시 용산구 한강로*가 **-*번지<NA><NA>(주)씨스팜2005-02-16 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업196606.215519447009.361613건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>13000임대550000001100000N0.0<NA><NA><NA>
130200003020000-135-2004-0000220040617<NA>3폐업2폐업20121210<NA><NA><NA>709511413,103.00140871서울특별시 용산구 한강로*가 ***번지<NA><NA>(주)아모레퍼시픽2011-10-30 14:50:37I2018-08-31 23:59:59.0건강기능식품유통전문판매업197138.823553447436.953717건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>2500250000자가00N0.0<NA><NA><NA>
230200003020000-135-2004-0000320040720<NA>3폐업2폐업20060222<NA><NA><NA>02 7975723190.00140775서울특별시 용산구 이태원동 ***-***번지 남송빌딩 별관 ***호<NA><NA>(주)포모펠릭스2005-03-30 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업199214.102397448891.79444건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0284임대100000002200000N0.0<NA><NA><NA>
330200003020000-135-2004-0000420040802<NA>3폐업2폐업20190911<NA><NA><NA>02 793544156.00140871서울특별시 용산구 한강로*가 ***-*번지 대우디오빌 ****호서울특별시 용산구 한강대로 *** (한강로*가,대우디오빌 ****호)4376(주)비트로시스인터내셔날2019-09-11 17:49:26U2019-09-13 02:40:00.0건강기능식품유통전문판매업197143.611431447561.482331건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0210임대10000000770000N0.0<NA><NA><NA>
430200003020000-135-2004-0000520040909<NA>3폐업2폐업20190911<NA><NA><NA>027985 007.00140011서울특별시 용산구 한강로*가 ***-*번지서울특별시 용산구 한강대로 *** (한강로*가)4375주-휴먼앤위팡2019-09-11 17:49:53U2019-09-13 02:40:00.0건강기능식품유통전문판매업197451.131492447970.481337건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>2000임대00N0.0<NA><NA><NA>
530200003020000-135-2004-0000620041104<NA>3폐업2폐업20060622<NA><NA><NA>05059805 52810.64140806서울특별시 용산구 갈월동 **-**번지 유니온빌딩 *층***호<NA><NA>지인2004-11-04 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업197418.853137449290.688144건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>5000임대00N0.0<NA><NA><NA>
630200003020000-135-2004-0000720041119<NA>3폐업2폐업20190911<NA><NA><NA>02 708500859.40140011서울특별시 용산구 한강로*가 ***-*번지 *층<NA><NA>(주)아라메디2019-09-11 17:50:20U2019-09-13 02:40:00.0건강기능식품유통전문판매업197486.672168448019.082066건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0132임대14000000800000N0.0<NA><NA><NA>
730200003020000-135-2004-000082004-06-17<NA>1영업/정상1영업<NA><NA><NA><NA>031 899 260333.00140-777서울특별시 용산구 한강로*가 *** 아모레퍼시픽서울특별시 용산구 한강대로 ***, 아모레퍼시픽 *층 (한강로*가)4386(주)아모레퍼시픽2024-01-25 15:24:29U2023-11-30 22:07:00.0건강기능식품유통전문판매업197158.923648447399.964398<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830200003020000-135-2005-0000120050228<NA>3폐업2폐업20070503<NA><NA><NA>02 795657199.00140883서울특별시 용산구 한강로*가 **-***번지 트럼프월드*차 ***-****<NA><NA>(주)닥터헬스디에이치팜2006-06-30 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업196655.421476446768.129158건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0160자가00N0.0<NA><NA><NA>
930200003020000-135-2005-0000220050518<NA>3폐업2폐업20100127<NA><NA><NA><NA>289.00140851서울특별시 용산구 원효로*가 ***번지<NA><NA>건인약품(주)2007-05-28 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업195385.722602447982.919184건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>03100자가<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
11730200003020000-135-2023-000172023-08-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1.10140-858서울특별시 용산구 이태원동 ***-* 이태원로***서울특별시 용산구 이태원로 ***, *층 ***호 (이태원동)4405주식회사 에브리루틴2023-08-25 17:53:56I2022-12-07 22:07:00.0건강기능식품유통전문판매업199592.672867448020.184718<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11830200003020000-135-2023-000182023-09-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1.10140-012서울특별시 용산구 한강로*가 *** 용산푸르지오써밋서울특별시 용산구 한강대로 **, 업무동 *층 ***호 (한강로*가, 용산푸르지오써밋)4378(주)뉴트리글로우2023-09-19 10:21:21I2022-12-08 22:01:00.0건강기능식품유통전문판매업196861.350875447226.72051<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11930200003020000-135-2023-000192023-09-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.00140-879서울특별시 용산구 한강로*가 **-** 한통빌딩서울특별시 용산구 청파로 **, 한통빌딩 ***호 (한강로*가)4373(주)카르도씨앤에스2023-09-19 15:30:11I2022-12-08 22:01:00.0건강기능식품유통전문판매업196087.977652447749.621213<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12030200003020000-135-2023-000202023-12-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30140-012서울특별시 용산구 한강로*가 *** 래미안용산 더 센트럴서울특별시 용산구 한강대로 **, A동 ***호 (한강로*가, 래미안용산 더 센트럴)4378(주)육달상회2024-02-29 16:28:04U2023-12-03 00:02:00.0건강기능식품유통전문판매업197011.737529447430.100251<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12130200003020000-135-2024-000012024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>100.00140-013서울특별시 용산구 한강로*가 **서울특별시 용산구 서빙고로 **, **층 (한강로*가)4387주식회사 페이퍼백2024-03-13 09:50:26U2023-12-02 23:06:00.0건강기능식품유통전문판매업197056.728931447077.126289<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12230200003020000-135-2024-000022024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.63140-832서울특별시 용산구 용문동 **-***서울특별시 용산구 효창원로**가길 **, ***호 (용문동)4356메딕바이옴 주식회사2024-03-07 14:35:37U2023-12-03 00:09:00.0건강기능식품유통전문판매업196170.529436448326.850969<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12330200003020000-135-2024-000032024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30140-230서울특별시 용산구 동빙고동 *** 용산푸르지오파크타운서울특별시 용산구 녹사평대로 **, ***동 ***호 (동빙고동, 용산푸르지오파크타운)4398만나2024-03-27 15:51:22I2023-12-02 22:09:00.0건강기능식품유통전문판매업199436.428968446918.407128<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12430200003020000-135-2024-000042024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 792 567983.85140-901서울특별시 용산구 후암동 ***-** 대원정사서울특별시 용산구 두텁바위로**길 **, 대원정사 별관 나동 지하*층 (후암동)4328남산적송 주식회사2024-04-04 14:52:24I2023-12-04 00:06:00.0건강기능식품유통전문판매업198470.128905449639.883506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12530200003020000-135-2024-000052024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30140-190서울특별시 용산구 후암동 ***-** 대경빌딩서울특별시 용산구 두텁바위로 **-*, 대경빌딩 지층 E-**호 (후암동)4336주식회사 로맨시브 수면연구소2024-04-05 17:58:21I2023-12-04 00:07:00.0건강기능식품유통전문판매업198066.163466449321.068367<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12630200003020000-135-2024-000062024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1.74140-013서울특별시 용산구 한강로*가 **서울특별시 용산구 서빙고로 **, 공공시설동 *층 (한강로*가)4387(주)필라멘토2024-04-25 16:10:45I2023-12-03 22:07:00.0건강기능식품유통전문판매업197056.728931447077.126289<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>