Overview

Dataset statistics

Number of variables44
Number of observations1604
Missing cells15301
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory587.5 KiB
Average record size in memory375.1 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric4
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18400/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (73.2%)Imbalance
여성종사자수 is highly imbalanced (73.3%)Imbalance
영업장주변구분명 is highly imbalanced (68.3%)Imbalance
등급구분명 is highly imbalanced (70.3%)Imbalance
급수시설구분명 is highly imbalanced (78.4%)Imbalance
총인원 is highly imbalanced (73.3%)Imbalance
공장사무직종업원수 is highly imbalanced (66.4%)Imbalance
보증액 is highly imbalanced (63.1%)Imbalance
월세액 is highly imbalanced (63.1%)Imbalance
시설총규모 is highly imbalanced (57.4%)Imbalance
인허가취소일자 has 1604 (100.0%) missing valuesMissing
폐업일자 has 759 (47.3%) missing valuesMissing
휴업시작일자 has 1604 (100.0%) missing valuesMissing
휴업종료일자 has 1604 (100.0%) missing valuesMissing
재개업일자 has 1604 (100.0%) missing valuesMissing
전화번호 has 769 (47.9%) missing valuesMissing
소재지면적 has 84 (5.2%) missing valuesMissing
도로명주소 has 252 (15.7%) missing valuesMissing
도로명우편번호 has 260 (16.2%) missing valuesMissing
좌표정보(X) has 99 (6.2%) missing valuesMissing
좌표정보(Y) has 99 (6.2%) missing valuesMissing
본사종업원수 has 1327 (82.7%) missing valuesMissing
다중이용업소여부 has 423 (26.4%) missing valuesMissing
전통업소지정번호 has 1604 (100.0%) missing valuesMissing
전통업소주된음식 has 1604 (100.0%) missing valuesMissing
홈페이지 has 1604 (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 272 (17.0%) zerosZeros

Reproduction

Analysis started2024-05-18 00:17:36.681229
Analysis finished2024-05-18 00:17:39.270416
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
3230000
1604 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 1604
100.0%

Length

2024-05-18T09:17:39.465395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:39.779953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 1604
100.0%

관리번호
Text

UNIQUE 

Distinct1604
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2024-05-18T09:17:40.229097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters35288
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

Unique1604 ?
Unique (%)100.0%

Sample

1st row3230000-113-1993-01637
2nd row3230000-113-1994-01638
3rd row3230000-113-1994-01639
4th row3230000-113-1994-01640
5th row3230000-113-1994-01773
ValueCountFrequency (%)
3230000-113-1993-01637 1
 
0.1%
3230000-113-2019-00038 1
 
0.1%
3230000-113-2019-00049 1
 
0.1%
3230000-113-2019-00048 1
 
0.1%
3230000-113-2019-00047 1
 
0.1%
3230000-113-2019-00046 1
 
0.1%
3230000-113-2019-00045 1
 
0.1%
3230000-113-2019-00044 1
 
0.1%
3230000-113-2019-00043 1
 
0.1%
3230000-113-2019-00042 1
 
0.1%
Other values (1594) 1594
99.4%
2024-05-18T09:17:41.108013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13172
37.3%
3 5466
15.5%
- 4812
 
13.6%
1 4774
 
13.5%
2 4250
 
12.0%
9 623
 
1.8%
5 492
 
1.4%
6 467
 
1.3%
4 455
 
1.3%
8 403
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30476
86.4%
Dash Punctuation 4812
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13172
43.2%
3 5466
17.9%
1 4774
 
15.7%
2 4250
 
13.9%
9 623
 
2.0%
5 492
 
1.6%
6 467
 
1.5%
4 455
 
1.5%
8 403
 
1.3%
7 374
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 4812
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13172
37.3%
3 5466
15.5%
- 4812
 
13.6%
1 4774
 
13.5%
2 4250
 
12.0%
9 623
 
1.8%
5 492
 
1.4%
6 467
 
1.3%
4 455
 
1.3%
8 403
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13172
37.3%
3 5466
15.5%
- 4812
 
13.6%
1 4774
 
13.5%
2 4250
 
12.0%
9 623
 
1.8%
5 492
 
1.4%
6 467
 
1.3%
4 455
 
1.3%
8 403
 
1.1%
Distinct1372
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum1993-10-21 00:00:00
Maximum2024-05-14 00:00:00
2024-05-18T09:17:41.533951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:17:41.956130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
3
845 
1
759 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 845
52.7%
1 759
47.3%

Length

2024-05-18T09:17:42.374852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:42.693848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 845
52.7%
1 759
47.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
폐업
845 
영업/정상
759 

Length

Max length5
Median length2
Mean length3.4195761
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 845
52.7%
영업/정상 759
47.3%

Length

2024-05-18T09:17:43.046016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:43.370891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 845
52.7%
영업/정상 759
47.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2
845 
1
759 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 845
52.7%
1 759
47.3%

Length

2024-05-18T09:17:43.716438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:43.963038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 845
52.7%
1 759
47.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
폐업
845 
영업
759 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 845
52.7%
영업 759
47.3%

Length

2024-05-18T09:17:44.214851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:44.530571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 845
52.7%
영업 759
47.3%

폐업일자
Date

MISSING 

Distinct622
Distinct (%)73.6%
Missing759
Missing (%)47.3%
Memory size12.7 KiB
Minimum1996-04-10 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T09:17:44.891533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:17:45.391721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

전화번호
Text

MISSING 

Distinct798
Distinct (%)95.6%
Missing769
Missing (%)47.9%
Memory size12.7 KiB
2024-05-18T09:17:46.056662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.953293
Min length2

Characters and Unicode

Total characters9146
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

Unique771 ?
Unique (%)92.3%

Sample

1st row02 4308217
2nd row02 4251943
3rd row02 4045100
4th row02 4044574
5th row02 4181300
ValueCountFrequency (%)
02 626
34.9%
070 80
 
4.5%
031 14
 
0.8%
420 11
 
0.6%
448 9
 
0.5%
400 9
 
0.5%
416 9
 
0.5%
407 8
 
0.4%
409 8
 
0.4%
404 7
 
0.4%
Other values (891) 1011
56.4%
2024-05-18T09:17:47.127040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1716
18.8%
2 1378
15.1%
1329
14.5%
4 972
10.6%
1 673
 
7.4%
3 640
 
7.0%
7 584
 
6.4%
5 537
 
5.9%
8 483
 
5.3%
6 429
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7817
85.5%
Space Separator 1329
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1716
22.0%
2 1378
17.6%
4 972
12.4%
1 673
 
8.6%
3 640
 
8.2%
7 584
 
7.5%
5 537
 
6.9%
8 483
 
6.2%
6 429
 
5.5%
9 405
 
5.2%
Space Separator
ValueCountFrequency (%)
1329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9146
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1716
18.8%
2 1378
15.1%
1329
14.5%
4 972
10.6%
1 673
 
7.4%
3 640
 
7.0%
7 584
 
6.4%
5 537
 
5.9%
8 483
 
5.3%
6 429
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1716
18.8%
2 1378
15.1%
1329
14.5%
4 972
10.6%
1 673
 
7.4%
3 640
 
7.0%
7 584
 
6.4%
5 537
 
5.9%
8 483
 
5.3%
6 429
 
4.7%

소재지면적
Text

MISSING 

Distinct694
Distinct (%)45.7%
Missing84
Missing (%)5.2%
Memory size12.7 KiB
2024-05-18T09:17:47.801369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length4.9756579
Min length3

Characters and Unicode

Total characters7563
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

Unique535 ?
Unique (%)35.2%

Sample

1st row.00
2nd row.00
3rd row.00
4th row.00
5th row.00
ValueCountFrequency (%)
00 65
 
4.3%
33.00 57
 
3.8%
3.30 48
 
3.2%
10.00 48
 
3.2%
30.00 46
 
3.0%
20.00 36
 
2.4%
15.00 24
 
1.6%
66.00 23
 
1.5%
2.00 21
 
1.4%
22.68 18
 
1.2%
Other values (684) 1134
74.6%
2024-05-18T09:17:48.838519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2188
28.9%
. 1520
20.1%
3 655
 
8.7%
2 616
 
8.1%
1 553
 
7.3%
6 412
 
5.4%
5 383
 
5.1%
4 355
 
4.7%
9 338
 
4.5%
8 305
 
4.0%
Other values (2) 238
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6038
79.8%
Other Punctuation 1525
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2188
36.2%
3 655
 
10.8%
2 616
 
10.2%
1 553
 
9.2%
6 412
 
6.8%
5 383
 
6.3%
4 355
 
5.9%
9 338
 
5.6%
8 305
 
5.1%
7 233
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 1520
99.7%
, 5
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2188
28.9%
. 1520
20.1%
3 655
 
8.7%
2 616
 
8.1%
1 553
 
7.3%
6 412
 
5.4%
5 383
 
5.1%
4 355
 
4.7%
9 338
 
4.5%
8 305
 
4.0%
Other values (2) 238
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2188
28.9%
. 1520
20.1%
3 655
 
8.7%
2 616
 
8.1%
1 553
 
7.3%
6 412
 
5.4%
5 383
 
5.1%
4 355
 
4.7%
9 338
 
4.5%
8 305
 
4.0%
Other values (2) 238
 
3.1%
Distinct193
Distinct (%)12.0%
Missing1
Missing (%)0.1%
Memory size12.7 KiB
2024-05-18T09:17:49.459505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1852776
Min length6

Characters and Unicode

Total characters9915
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

Unique39 ?
Unique (%)2.4%

Sample

1st row138200
2nd row138840
3rd row138200
4th row138200
5th row138866
ValueCountFrequency (%)
138888 129
 
8.0%
138200 67
 
4.2%
138881 66
 
4.1%
138960 48
 
3.0%
138806 42
 
2.6%
138-888 41
 
2.6%
138934 38
 
2.4%
138803 31
 
1.9%
138827 28
 
1.7%
138828 28
 
1.7%
Other values (183) 1085
67.7%
2024-05-18T09:17:50.495792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 3413
34.4%
1 1951
19.7%
3 1883
19.0%
0 600
 
6.1%
2 353
 
3.6%
4 334
 
3.4%
6 317
 
3.2%
5 298
 
3.0%
- 297
 
3.0%
9 265
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9618
97.0%
Dash Punctuation 297
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 3413
35.5%
1 1951
20.3%
3 1883
19.6%
0 600
 
6.2%
2 353
 
3.7%
4 334
 
3.5%
6 317
 
3.3%
5 298
 
3.1%
9 265
 
2.8%
7 204
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 3413
34.4%
1 1951
19.7%
3 1883
19.0%
0 600
 
6.1%
2 353
 
3.6%
4 334
 
3.4%
6 317
 
3.2%
5 298
 
3.0%
- 297
 
3.0%
9 265
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 3413
34.4%
1 1951
19.7%
3 1883
19.0%
0 600
 
6.1%
2 353
 
3.6%
4 334
 
3.4%
6 317
 
3.2%
5 298
 
3.0%
- 297
 
3.0%
9 265
 
2.7%
Distinct1245
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2024-05-18T09:17:51.041697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length25.19015
Min length6

Characters and Unicode

Total characters40405
Distinct characters350
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1111 ?
Unique (%)69.3%

Sample

1st row서울특별시 송파구 문정동 산 4-6
2nd row서울특별시 송파구 삼전동 132-6
3rd row서울특별시 송파구 문정동 산 42-9 대호빌딩 지하동 1층호
4th row서울특별시 송파구 문정동 산 99-9 성은빌딩3 0000호
5th row서울특별시 송파구 잠실동 313-10
ValueCountFrequency (%)
서울특별시 1603
19.9%
송파구 1602
19.9%
가락동 458
 
5.7%
문정동 404
 
5.0%
방이동 181
 
2.2%
잠실동 121
 
1.5%
석촌동 98
 
1.2%
송파동 95
 
1.2%
600 74
 
0.9%
삼전동 72
 
0.9%
Other values (1551) 3360
41.6%
2024-05-18T09:17:52.236150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7525
18.6%
1902
 
4.7%
1761
 
4.4%
1723
 
4.3%
1706
 
4.2%
1610
 
4.0%
1607
 
4.0%
1603
 
4.0%
1603
 
4.0%
1603
 
4.0%
Other values (340) 17762
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24207
59.9%
Space Separator 7525
 
18.6%
Decimal Number 7051
 
17.5%
Dash Punctuation 1249
 
3.1%
Uppercase Letter 187
 
0.5%
Open Punctuation 66
 
0.2%
Close Punctuation 65
 
0.2%
Other Punctuation 46
 
0.1%
Lowercase Letter 5
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1902
 
7.9%
1761
 
7.3%
1723
 
7.1%
1706
 
7.0%
1610
 
6.7%
1607
 
6.6%
1603
 
6.6%
1603
 
6.6%
1603
 
6.6%
581
 
2.4%
Other values (290) 8508
35.1%
Uppercase Letter
ValueCountFrequency (%)
B 24
12.8%
T 18
 
9.6%
S 17
 
9.1%
A 15
 
8.0%
D 14
 
7.5%
L 12
 
6.4%
O 11
 
5.9%
C 10
 
5.3%
E 10
 
5.3%
J 10
 
5.3%
Other values (14) 46
24.6%
Decimal Number
ValueCountFrequency (%)
1 1596
22.6%
2 904
12.8%
0 730
10.4%
6 668
9.5%
3 645
9.1%
4 591
 
8.4%
5 558
 
7.9%
9 537
 
7.6%
7 447
 
6.3%
8 375
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 31
67.4%
/ 10
 
21.7%
? 3
 
6.5%
. 2
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
t 1
20.0%
i 1
20.0%
u 1
20.0%
Math Symbol
ValueCountFrequency (%)
~ 1
33.3%
> 1
33.3%
< 1
33.3%
Space Separator
ValueCountFrequency (%)
7525
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24205
59.9%
Common 16005
39.6%
Latin 193
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1902
 
7.9%
1761
 
7.3%
1723
 
7.1%
1706
 
7.0%
1610
 
6.7%
1607
 
6.6%
1603
 
6.6%
1603
 
6.6%
1603
 
6.6%
581
 
2.4%
Other values (288) 8506
35.1%
Latin
ValueCountFrequency (%)
B 24
12.4%
T 18
 
9.3%
S 17
 
8.8%
A 15
 
7.8%
D 14
 
7.3%
L 12
 
6.2%
O 11
 
5.7%
C 10
 
5.2%
E 10
 
5.2%
J 10
 
5.2%
Other values (19) 52
26.9%
Common
ValueCountFrequency (%)
7525
47.0%
1 1596
 
10.0%
- 1249
 
7.8%
2 904
 
5.6%
0 730
 
4.6%
6 668
 
4.2%
3 645
 
4.0%
4 591
 
3.7%
5 558
 
3.5%
9 537
 
3.4%
Other values (11) 1002
 
6.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24205
59.9%
ASCII 16197
40.1%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7525
46.5%
1 1596
 
9.9%
- 1249
 
7.7%
2 904
 
5.6%
0 730
 
4.5%
6 668
 
4.1%
3 645
 
4.0%
4 591
 
3.6%
5 558
 
3.4%
9 537
 
3.3%
Other values (39) 1194
 
7.4%
Hangul
ValueCountFrequency (%)
1902
 
7.9%
1761
 
7.3%
1723
 
7.1%
1706
 
7.0%
1610
 
6.7%
1607
 
6.6%
1603
 
6.6%
1603
 
6.6%
1603
 
6.6%
581
 
2.4%
Other values (288) 8506
35.1%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct1316
Distinct (%)97.3%
Missing252
Missing (%)15.7%
Memory size12.7 KiB
2024-05-18T09:17:52.844384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length53
Mean length37.110947
Min length22

Characters and Unicode

Total characters50174
Distinct characters356
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1285 ?
Unique (%)95.0%

Sample

1st row서울특별시 송파구 삼학사로 67 (삼전동)
2nd row서울특별시 송파구 새말로 148 (문정동)
3rd row서울특별시 송파구 송파대로 222 (가락동)
4th row서울특별시 송파구 동남로9길 4-3 (가락동)
5th row서울특별시 송파구 양재대로 1222 (방이동)
ValueCountFrequency (%)
서울특별시 1352
 
14.1%
송파구 1351
 
14.1%
문정동 354
 
3.7%
가락동 325
 
3.4%
방이동 129
 
1.3%
3층 124
 
1.3%
2층 122
 
1.3%
충민로 106
 
1.1%
잠실동 106
 
1.1%
1층 99
 
1.0%
Other values (1730) 5490
57.4%
2024-05-18T09:17:53.876489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8216
 
16.4%
1 1973
 
3.9%
1815
 
3.6%
1708
 
3.4%
1666
 
3.3%
, 1628
 
3.2%
1457
 
2.9%
( 1380
 
2.8%
) 1379
 
2.7%
1369
 
2.7%
Other values (346) 27583
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28417
56.6%
Decimal Number 8378
 
16.7%
Space Separator 8216
 
16.4%
Other Punctuation 1634
 
3.3%
Open Punctuation 1380
 
2.8%
Close Punctuation 1379
 
2.7%
Uppercase Letter 430
 
0.9%
Dash Punctuation 326
 
0.6%
Lowercase Letter 10
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1815
 
6.4%
1708
 
6.0%
1666
 
5.9%
1457
 
5.1%
1369
 
4.8%
1367
 
4.8%
1363
 
4.8%
1352
 
4.8%
1352
 
4.8%
1352
 
4.8%
Other values (296) 13616
47.9%
Uppercase Letter
ValueCountFrequency (%)
B 71
16.5%
A 69
16.0%
C 43
10.0%
S 34
 
7.9%
T 31
 
7.2%
L 25
 
5.8%
E 23
 
5.3%
G 22
 
5.1%
Y 14
 
3.3%
R 13
 
3.0%
Other values (14) 85
19.8%
Decimal Number
ValueCountFrequency (%)
1 1973
23.5%
2 1357
16.2%
3 979
11.7%
0 928
11.1%
6 691
 
8.2%
4 672
 
8.0%
5 518
 
6.2%
8 456
 
5.4%
7 404
 
4.8%
9 400
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
f 2
20.0%
a 2
20.0%
e 2
20.0%
i 1
10.0%
t 1
10.0%
u 1
10.0%
s 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 1628
99.6%
? 3
 
0.2%
/ 2
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1380
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1379
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28415
56.6%
Common 21317
42.5%
Latin 440
 
0.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1815
 
6.4%
1708
 
6.0%
1666
 
5.9%
1457
 
5.1%
1369
 
4.8%
1367
 
4.8%
1363
 
4.8%
1352
 
4.8%
1352
 
4.8%
1352
 
4.8%
Other values (294) 13614
47.9%
Latin
ValueCountFrequency (%)
B 71
16.1%
A 69
15.7%
C 43
9.8%
S 34
 
7.7%
T 31
 
7.0%
L 25
 
5.7%
E 23
 
5.2%
G 22
 
5.0%
Y 14
 
3.2%
R 13
 
3.0%
Other values (21) 95
21.6%
Common
ValueCountFrequency (%)
8216
38.5%
1 1973
 
9.3%
, 1628
 
7.6%
( 1380
 
6.5%
) 1379
 
6.5%
2 1357
 
6.4%
3 979
 
4.6%
0 928
 
4.4%
6 691
 
3.2%
4 672
 
3.2%
Other values (9) 2114
 
9.9%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28415
56.6%
ASCII 21757
43.4%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8216
37.8%
1 1973
 
9.1%
, 1628
 
7.5%
( 1380
 
6.3%
) 1379
 
6.3%
2 1357
 
6.2%
3 979
 
4.5%
0 928
 
4.3%
6 691
 
3.2%
4 672
 
3.1%
Other values (40) 2554
 
11.7%
Hangul
ValueCountFrequency (%)
1815
 
6.4%
1708
 
6.0%
1666
 
5.9%
1457
 
5.1%
1369
 
4.8%
1367
 
4.8%
1363
 
4.8%
1352
 
4.8%
1352
 
4.8%
1352
 
4.8%
Other values (294) 13614
47.9%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct249
Distinct (%)18.5%
Missing260
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean5708.0246
Minimum5501
Maximum6035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-18T09:17:54.317893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5501
5-th percentile5542
Q15617.5
median5710
Q35826
95-th percentile5854
Maximum6035
Range534
Interquartile range (IQR)208.5

Descriptive statistics

Standard deviation108.69058
Coefficient of variation (CV)0.019041715
Kurtosis-1.1715155
Mean5708.0246
Median Absolute Deviation (MAD)99.5
Skewness-0.19929718
Sum7671585
Variance11813.641
MonotonicityNot monotonic
2024-05-18T09:17:54.802107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5838 73
 
4.6%
5699 70
 
4.4%
5719 62
 
3.9%
5854 55
 
3.4%
5855 41
 
2.6%
5510 36
 
2.2%
5836 27
 
1.7%
5829 26
 
1.6%
5556 24
 
1.5%
5542 23
 
1.4%
Other values (239) 907
56.5%
(Missing) 260
 
16.2%
ValueCountFrequency (%)
5501 3
 
0.2%
5503 1
 
0.1%
5504 3
 
0.2%
5507 2
 
0.1%
5510 36
2.2%
5513 1
 
0.1%
5514 1
 
0.1%
5518 1
 
0.1%
5525 2
 
0.1%
5531 1
 
0.1%
ValueCountFrequency (%)
6035 1
 
0.1%
5855 41
2.6%
5854 55
3.4%
5852 2
 
0.1%
5849 4
 
0.2%
5842 2
 
0.1%
5841 14
 
0.9%
5840 20
 
1.2%
5839 4
 
0.2%
5838 73
4.6%
Distinct1578
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2024-05-18T09:17:55.479396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length7.5829177
Min length2

Characters and Unicode

Total characters12163
Distinct characters652
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1552 ?
Unique (%)96.8%

Sample

1st row주식회사해표
2nd row(주)동일산업
3rd row옥견식품
4th row(주)청솔식품
5th row실로암식품(주)
ValueCountFrequency (%)
주식회사 187
 
9.6%
11
 
0.6%
농업회사법인 6
 
0.3%
푸드 5
 
0.3%
찬상반찬카페 4
 
0.2%
인터내셔널 4
 
0.2%
컴퍼니 4
 
0.2%
생활건강 3
 
0.2%
주)제너시스 3
 
0.2%
3
 
0.2%
Other values (1669) 1711
88.2%
2024-05-18T09:17:56.438573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1014
 
8.3%
) 845
 
6.9%
( 841
 
6.9%
393
 
3.2%
359
 
3.0%
337
 
2.8%
277
 
2.3%
262
 
2.2%
236
 
1.9%
227
 
1.9%
Other values (642) 7372
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9840
80.9%
Close Punctuation 845
 
6.9%
Open Punctuation 841
 
6.9%
Space Separator 337
 
2.8%
Uppercase Letter 164
 
1.3%
Lowercase Letter 95
 
0.8%
Decimal Number 25
 
0.2%
Other Punctuation 11
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1014
 
10.3%
393
 
4.0%
359
 
3.6%
277
 
2.8%
262
 
2.7%
236
 
2.4%
227
 
2.3%
204
 
2.1%
177
 
1.8%
147
 
1.5%
Other values (580) 6544
66.5%
Uppercase Letter
ValueCountFrequency (%)
O 16
 
9.8%
S 16
 
9.8%
N 14
 
8.5%
D 11
 
6.7%
T 10
 
6.1%
G 10
 
6.1%
F 10
 
6.1%
B 9
 
5.5%
A 9
 
5.5%
M 8
 
4.9%
Other values (13) 51
31.1%
Lowercase Letter
ValueCountFrequency (%)
a 15
15.8%
e 15
15.8%
l 8
 
8.4%
s 8
 
8.4%
r 5
 
5.3%
t 5
 
5.3%
n 5
 
5.3%
o 5
 
5.3%
h 4
 
4.2%
u 4
 
4.2%
Other values (12) 21
22.1%
Decimal Number
ValueCountFrequency (%)
0 5
20.0%
1 5
20.0%
3 4
16.0%
5 3
12.0%
2 2
 
8.0%
6 2
 
8.0%
9 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%
4 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 5
45.5%
. 5
45.5%
' 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 845
100.0%
Open Punctuation
ValueCountFrequency (%)
( 841
100.0%
Space Separator
ValueCountFrequency (%)
337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9838
80.9%
Common 2064
 
17.0%
Latin 259
 
2.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1014
 
10.3%
393
 
4.0%
359
 
3.6%
277
 
2.8%
262
 
2.7%
236
 
2.4%
227
 
2.3%
204
 
2.1%
177
 
1.8%
147
 
1.5%
Other values (578) 6542
66.5%
Latin
ValueCountFrequency (%)
O 16
 
6.2%
S 16
 
6.2%
a 15
 
5.8%
e 15
 
5.8%
N 14
 
5.4%
D 11
 
4.2%
T 10
 
3.9%
G 10
 
3.9%
F 10
 
3.9%
B 9
 
3.5%
Other values (35) 133
51.4%
Common
ValueCountFrequency (%)
) 845
40.9%
( 841
40.7%
337
 
16.3%
0 5
 
0.2%
1 5
 
0.2%
- 5
 
0.2%
& 5
 
0.2%
. 5
 
0.2%
3 4
 
0.2%
5 3
 
0.1%
Other values (7) 9
 
0.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9838
80.9%
ASCII 2323
 
19.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1014
 
10.3%
393
 
4.0%
359
 
3.6%
277
 
2.8%
262
 
2.7%
236
 
2.4%
227
 
2.3%
204
 
2.1%
177
 
1.8%
147
 
1.5%
Other values (578) 6542
66.5%
ASCII
ValueCountFrequency (%)
) 845
36.4%
( 841
36.2%
337
 
14.5%
O 16
 
0.7%
S 16
 
0.7%
a 15
 
0.6%
e 15
 
0.6%
N 14
 
0.6%
D 11
 
0.5%
T 10
 
0.4%
Other values (52) 203
 
8.7%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct1551
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum1999-02-02 00:00:00
Maximum2024-05-16 09:43:23
2024-05-18T09:17:56.845166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:17:57.298795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
I
1138 
U
466 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1138
70.9%
U 466
29.1%

Length

2024-05-18T09:17:57.728869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:58.248780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1138
70.9%
u 466
29.1%
Distinct638
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-18T09:17:58.582415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:17:59.013117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
유통전문판매업
1604 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 1604
100.0%

Length

2024-05-18T09:17:59.430818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:17:59.742854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1604
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct840
Distinct (%)55.8%
Missing99
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean210178.43
Minimum201772.16
Maximum213977.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-18T09:18:00.043989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201772.16
5-th percentile207415.86
Q1209429.19
median210431.83
Q3210986.46
95-th percentile212291.09
Maximum213977.36
Range12205.198
Interquartile range (IQR)1557.2754

Descriptive statistics

Standard deviation1345.8567
Coefficient of variation (CV)0.0064034007
Kurtosis1.2041335
Mean210178.43
Median Absolute Deviation (MAD)640.87295
Skewness-0.55499836
Sum3.1631854 × 108
Variance1811330.4
MonotonicityNot monotonic
2024-05-18T09:18:00.563776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.959909032 75
 
4.7%
210986.460698452 64
 
4.0%
210431.832858016 35
 
2.2%
209140.885315651 18
 
1.1%
210480.282018702 17
 
1.1%
209427.410217251 17
 
1.1%
210558.0 15
 
0.9%
210591.787825479 15
 
0.9%
209074.900840074 12
 
0.7%
210627.0 11
 
0.7%
Other values (830) 1226
76.4%
(Missing) 99
 
6.2%
ValueCountFrequency (%)
201772.158218006 1
 
0.1%
206777.243257553 1
 
0.1%
206802.873762097 1
 
0.1%
206817.419432561 1
 
0.1%
206895.380256076 2
 
0.1%
206908.348523164 7
0.4%
206914.005245094 2
 
0.1%
206916.75835 2
 
0.1%
206932.357872339 7
0.4%
206941.757489986 6
0.4%
ValueCountFrequency (%)
213977.355937651 1
0.1%
213842.681773192 1
0.1%
213712.175713909 1
0.1%
213533.171043128 1
0.1%
213523.083515713 2
0.1%
213468.096258992 1
0.1%
213461.103265851 1
0.1%
213394.68917515 1
0.1%
213392.525576079 1
0.1%
213387.798522479 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct839
Distinct (%)55.7%
Missing99
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean444105.91
Minimum441446
Maximum448601.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-18T09:18:00.970171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441446
5-th percentile441833.16
Q1443392.69
median444107.35
Q3445055.52
95-th percentile446035.17
Maximum448601.32
Range7155.3246
Interquartile range (IQR)1662.8275

Descriptive statistics

Standard deviation1285.8427
Coefficient of variation (CV)0.0028953514
Kurtosis-0.28684786
Mean444105.91
Median Absolute Deviation (MAD)845.25365
Skewness0.083315381
Sum6.683794 × 108
Variance1653391.4
MonotonicityNot monotonic
2024-05-18T09:18:01.406694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443481.212174317 75
 
4.7%
441725.293491662 64
 
4.0%
443465.4592322 35
 
2.2%
446042.592367722 18
 
1.1%
441833.16323518 17
 
1.1%
445829.725943441 17
 
1.1%
442587.0 15
 
0.9%
443574.427660288 15
 
0.9%
445657.80932984 12
 
0.7%
442875.0 11
 
0.7%
Other values (829) 1226
76.4%
(Missing) 99
 
6.2%
ValueCountFrequency (%)
441446.0 2
 
0.1%
441586.029967716 1
 
0.1%
441590.062253247 1
 
0.1%
441725.293491662 64
4.0%
441730.920486073 3
 
0.2%
441833.16323518 17
 
1.1%
441953.803802768 1
 
0.1%
441969.456994265 1
 
0.1%
441971.271264751 2
 
0.1%
441996.227705236 7
 
0.4%
ValueCountFrequency (%)
448601.324644324 1
0.1%
448429.421913785 1
0.1%
448335.76381476 1
0.1%
448323.498359444 1
0.1%
447998.314259267 1
0.1%
447896.684233092 1
0.1%
447872.361184195 1
0.1%
447772.223360781 2
0.1%
447661.821030513 1
0.1%
447597.538529595 1
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
유통전문판매업
1181 
<NA>
423 

Length

Max length7
Median length7
Mean length6.2088529
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 1181
73.6%
<NA> 423
 
26.4%

Length

2024-05-18T09:18:01.890033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:02.232001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1181
73.6%
na 423
 
26.4%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1435 
0
154 
1
 
13
2
 
2

Length

Max length4
Median length4
Mean length3.6839152
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1435
89.5%
0 154
 
9.6%
1 13
 
0.8%
2 2
 
0.1%

Length

2024-05-18T09:18:02.633081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:03.000665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1435
89.5%
0 154
 
9.6%
1 13
 
0.8%
2 2
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1435 
0
154 
1
 
14
2
 
1

Length

Max length4
Median length4
Mean length3.6839152
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1435
89.5%
0 154
 
9.6%
1 14
 
0.9%
2 1
 
0.1%

Length

2024-05-18T09:18:03.392827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:03.725924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1435
89.5%
0 154
 
9.6%
1 14
 
0.9%
2 1
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1419 
기타
 
104
주택가주변
 
80
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.9208229
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1419
88.5%
기타 104
 
6.5%
주택가주변 80
 
5.0%
아파트지역 1
 
0.1%

Length

2024-05-18T09:18:04.082546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:04.472827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1419
88.5%
기타 104
 
6.5%
주택가주변 80
 
5.0%
아파트지역 1
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1419 
기타
 
101
우수
 
59
자율
 
17
 
8

Length

Max length4
Median length4
Mean length3.7643392
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자율
2nd row자율
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
<NA> 1419
88.5%
기타 101
 
6.3%
우수 59
 
3.7%
자율 17
 
1.1%
8
 
0.5%

Length

2024-05-18T09:18:04.833924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:05.222957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1419
88.5%
기타 101
 
6.3%
우수 59
 
3.7%
자율 17
 
1.1%
8
 
0.5%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1469 
상수도전용
 
132
상수도(음용)지하수(주방용)겸용
 
2
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.0991272
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1469
91.6%
상수도전용 132
 
8.2%
상수도(음용)지하수(주방용)겸용 2
 
0.1%
지하수전용 1
 
0.1%

Length

2024-05-18T09:18:05.686279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:06.056166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1469
91.6%
상수도전용 132
 
8.2%
상수도(음용)지하수(주방용)겸용 2
 
0.1%
지하수전용 1
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1531 
0
 
73

Length

Max length4
Median length4
Mean length3.8634663
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> 1531
95.4%
0 73
 
4.6%

Length

2024-05-18T09:18:06.406235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:06.740173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1531
95.4%
0 73
 
4.6%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.2%
Missing1327
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.090252708
Minimum0
Maximum11
Zeros272
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-18T09:18:07.081597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.84429819
Coefficient of variation (CV)9.3548239
Kurtosis129.34518
Mean0.090252708
Median Absolute Deviation (MAD)0
Skewness11.069769
Sum25
Variance0.71283943
MonotonicityNot monotonic
2024-05-18T09:18:07.428319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 272
 
17.0%
3 1
 
0.1%
11 1
 
0.1%
8 1
 
0.1%
2 1
 
0.1%
1 1
 
0.1%
(Missing) 1327
82.7%
ValueCountFrequency (%)
0 272
17.0%
1 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%
8 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
8 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
1 1
 
0.1%
0 272
17.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1330 
0
272 
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.4875312
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1330
82.9%
0 272
 
17.0%
1 1
 
0.1%
2 1
 
0.1%

Length

2024-05-18T09:18:07.808900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:08.025353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1330
82.9%
0 272
 
17.0%
1 1
 
0.1%
2 1
 
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1332 
0
272 

Length

Max length4
Median length4
Mean length3.4912718
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> 1332
83.0%
0 272
 
17.0%

Length

2024-05-18T09:18:08.318801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:08.634711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1332
83.0%
0 272
 
17.0%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1332 
0
272 

Length

Max length4
Median length4
Mean length3.4912718
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> 1332
83.0%
0 272
 
17.0%

Length

2024-05-18T09:18:09.026688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:09.364042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1332
83.0%
0 272
 
17.0%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
719 
자가
447 
임대
438 

Length

Max length4
Median length2
Mean length2.8965087
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> 719
44.8%
자가 447
27.9%
임대 438
27.3%

Length

2024-05-18T09:18:09.762129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:09.985182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 719
44.8%
자가 447
27.9%
임대 438
27.3%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1383 
0
220 
300
 
1

Length

Max length4
Median length4
Mean length3.5879052
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1383
86.2%
0 220
 
13.7%
300 1
 
0.1%

Length

2024-05-18T09:18:10.306713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:10.540752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1383
86.2%
0 220
 
13.7%
300 1
 
0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1383 
0
220 
35
 
1

Length

Max length4
Median length4
Mean length3.5872818
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1383
86.2%
0 220
 
13.7%
35 1
 
0.1%

Length

2024-05-18T09:18:10.908417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:11.253650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1383
86.2%
0 220
 
13.7%
35 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing423
Missing (%)26.4%
Memory size3.3 KiB
False
1181 
(Missing)
423 
ValueCountFrequency (%)
False 1181
73.6%
(Missing) 423
 
26.4%
2024-05-18T09:18:11.511798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
0.0
1178 
<NA>
423 
26.8
 
2
532.24
 
1

Length

Max length6
Median length3
Mean length3.2668329
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 1178
73.4%
<NA> 423
 
26.4%
26.8 2
 
0.1%
532.24 1
 
0.1%

Length

2024-05-18T09:18:11.704152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:18:11.995115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1178
73.4%
na 423
 
26.4%
26.8 2
 
0.1%
532.24 1
 
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1604
Missing (%)100.0%
Memory size14.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032300003230000-113-1993-0163719931021<NA>3폐업2폐업19981105<NA><NA><NA>02 4308217.00138200서울특별시 송파구 문정동 산 4-6<NA><NA>주식회사해표2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업<NA><NA>유통전문판매업20주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132300003230000-113-1994-0163819940402<NA>3폐업2폐업20161223<NA><NA><NA>02 4251943.00138840서울특별시 송파구 삼전동 132-6서울특별시 송파구 삼학사로 67 (삼전동)5603(주)동일산업2016-12-21 17:24:39I2018-08-31 23:59:59.0유통전문판매업208488.631001444574.426119유통전문판매업00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232300003230000-113-1994-0163919940706<NA>3폐업2폐업19960410<NA><NA><NA>02 4045100.00138200서울특별시 송파구 문정동 산 42-9 대호빌딩 지하동 1층호<NA><NA>옥견식품2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업<NA><NA>유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332300003230000-113-1994-0164019940823<NA>3폐업2폐업20161223<NA><NA><NA>02 4044574.00138200서울특별시 송파구 문정동 산 99-9 성은빌딩3 0000호서울특별시 송파구 새말로 148 (문정동)5799(주)청솔식품2016-12-22 07:59:53I2018-08-31 23:59:59.0유통전문판매업211449.735562442433.484581유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432300003230000-113-1994-0177319941103<NA>3폐업2폐업19990413<NA><NA><NA>02 4181300.00138866서울특별시 송파구 잠실동 313-10<NA><NA>실로암식품(주)2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업207281.95105444809.979964유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532300003230000-113-1995-0164119950112<NA>3폐업2폐업19980227<NA><NA><NA>02 4088004.00138200서울특별시 송파구 문정동 124-9<NA><NA>진우식품(주)2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업211644.389626442965.846277유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632300003230000-113-1995-0164219950128<NA>3폐업2폐업19961210<NA><NA><NA>02 0.00138849서울특별시 송파구 송파동 32-2<NA><NA>진양농수산(주)2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업209329.441021445322.687864유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732300003230000-113-1995-0164319950224<NA>3폐업2폐업20161223<NA><NA><NA>02 0.00138806서울특별시 송파구 가락동 101-7서울특별시 송파구 송파대로 222 (가락동)5831(주)엄마손식품2016-12-22 08:49:52I2018-08-31 23:59:59.0유통전문판매업210633.066881443084.373969유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832300003230000-113-1995-0164419950508<NA>3폐업2폐업19960722<NA><NA><NA>02 4210112.00138836서울특별시 송파구 방이동 219-9<NA><NA>(주)로마노피자2003-09-16 00:00:00I2018-08-31 23:59:59.0유통전문판매업210674.776089445055.519973유통전문판매업11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932300003230000-113-1995-0164519950519<NA>3폐업2폐업19970421<NA><NA><NA>02 4062264.00138200서울특별시 송파구 문정동 산 14-5<NA><NA>한미수산주식회사2002-09-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업<NA><NA>유통전문판매업01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
159432300003230000-113-2024-000272024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.00138-845서울특별시 송파구 석촌동 240-2서울특별시 송파구 가락로 42, 4층 401호 (석촌동)5694이에스테크2024-04-11 15:03:04I2023-12-03 23:03:00.0유통전문판매업208884.641482444096.622478<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159532300003230000-113-2024-000282024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.00138-826서울특별시 송파구 문정동 66-5서울특별시 송파구 송파대로14길 7-10, 2층 201-387호 (문정동)5807스카이라인2024-04-12 13:25:14I2023-12-03 23:04:00.0유통전문판매업210983.587452442438.127125<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159632300003230000-113-2024-000292024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00138-926서울특별시 송파구 장지동 894 위례아이파크서울특별시 송파구 위례광장로 136, 상가5동 1층 E-112호 (장지동, 위례아이파크)5852니아이 커피2024-04-18 13:41:02I2023-12-03 22:00:00.0유통전문판매업212494.327676441590.062253<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159732300003230000-113-2024-000302024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30138-715서울특별시 송파구 가락동 99-3 제일오피스텔서울특별시 송파구 송파대로 260, 제일오피스텔 5층 511호 (가락동)5719(주)마이라이프밸런스2024-04-24 12:02:31I2023-12-03 22:06:00.0유통전문판매업210431.832858443465.459232<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159832300003230000-113-2024-000312024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.63138-885서울특별시 송파구 문정동 150-4서울특별시 송파구 중대로 56, 7층 25호 (문정동)5833더샤인2024-04-24 13:07:56I2023-12-03 22:06:00.0유통전문판매업210112.318379443221.728318<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159932300003230000-113-2024-000322024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-040서울특별시 송파구 풍납동 509 씨티극동아파트서울특별시 송파구 한가람로 478, 101동 311호 (풍납동, 씨티극동아파트)5514신토불이약초2024-04-26 14:45:37I2023-12-03 22:08:00.0유통전문판매업210377.46167448601.324644<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
160032300003230000-113-2024-000332024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>431.16138-847서울특별시 송파구 석촌동 286-7서울특별시 송파구 백제고분로 362, 6층 (석촌동)5685신라에스지(주)2024-04-30 15:08:44I2023-12-05 00:02:00.0유통전문판매업209357.458011444700.650339<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
160132300003230000-113-2024-000342024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.45138-888서울특별시 송파구 문정동 652 송파법조타운푸르지오시티서울특별시 송파구 법원로4길 5, 송파법조타운푸르지오시티 지하1층 B109호 (문정동)5855주식회사 그릿2024-05-03 10:04:20I2023-12-05 00:05:00.0유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
160232300003230000-113-2024-000352024-01-18<NA>1영업/정상1영업<NA><NA><NA><NA>023472337393.15138-888서울특별시 송파구 문정동 651-14 송파유탑테크밸리서울특별시 송파구 법원로6길 7, 송파유탑테크밸리 4층 405호 (문정동)5855비타믹스2024-05-03 16:35:49I2023-12-05 00:05:00.0유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
160332300003230000-113-2024-000362024-05-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30138-800서울특별시 송파구 가락동 10-7 대명빌딩서울특별시 송파구 중대로 207, 대명빌딩 2층 201-J43호 (가락동)5702주식회사 더블유디에프엔비2024-05-14 09:21:23I2023-12-04 23:06:00.0유통전문판매업211108.961742444263.057029<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>