Overview

Dataset statistics

Number of variables44
Number of observations444
Missing cells4754
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory163.2 KiB
Average record size in memory376.3 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric7
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18394/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (52.7%)Imbalance
여성종사자수 is highly imbalanced (52.7%)Imbalance
영업장주변구분명 is highly imbalanced (90.3%)Imbalance
등급구분명 is highly imbalanced (88.4%)Imbalance
급수시설구분명 is highly imbalanced (64.3%)Imbalance
총인원 is highly imbalanced (54.8%)Imbalance
본사종업원수 is highly imbalanced (53.7%)Imbalance
인허가취소일자 has 444 (100.0%) missing valuesMissing
폐업일자 has 201 (45.3%) missing valuesMissing
휴업시작일자 has 444 (100.0%) missing valuesMissing
휴업종료일자 has 444 (100.0%) missing valuesMissing
재개업일자 has 444 (100.0%) missing valuesMissing
전화번호 has 161 (36.3%) missing valuesMissing
소재지면적 has 15 (3.4%) missing valuesMissing
도로명주소 has 48 (10.8%) missing valuesMissing
도로명우편번호 has 49 (11.0%) missing valuesMissing
보증액 has 388 (87.4%) missing valuesMissing
월세액 has 388 (87.4%) missing valuesMissing
다중이용업소여부 has 192 (43.2%) missing valuesMissing
시설총규모 has 192 (43.2%) missing valuesMissing
전통업소지정번호 has 444 (100.0%) missing valuesMissing
전통업소주된음식 has 444 (100.0%) missing valuesMissing
홈페이지 has 444 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 5 (1.1%) zerosZeros
보증액 has 44 (9.9%) zerosZeros
월세액 has 44 (9.9%) zerosZeros
시설총규모 has 239 (53.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:44:17.203721
Analysis finished2024-05-11 05:44:18.468487
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3170000
444 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 444
100.0%

Length

2024-05-11T14:44:18.545303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:18.654139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 444
100.0%

관리번호
Text

UNIQUE 

Distinct444
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-05-11T14:44:18.886461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9768
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

Unique444 ?
Unique (%)100.0%

Sample

1st row3170000-113-1995-00334
2nd row3170000-113-1995-00335
3rd row3170000-113-1995-00404
4th row3170000-113-1996-00402
5th row3170000-113-1996-00405
ValueCountFrequency (%)
3170000-113-1995-00334 1
 
0.2%
3170000-113-2020-00048 1
 
0.2%
3170000-113-2020-00059 1
 
0.2%
3170000-113-2020-00058 1
 
0.2%
3170000-113-2020-00057 1
 
0.2%
3170000-113-2020-00056 1
 
0.2%
3170000-113-2020-00055 1
 
0.2%
3170000-113-2020-00054 1
 
0.2%
3170000-113-2020-00053 1
 
0.2%
3170000-113-2020-00052 1
 
0.2%
Other values (434) 434
97.7%
2024-05-11T14:44:19.306079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3865
39.6%
1 1740
17.8%
- 1332
 
13.6%
3 1041
 
10.7%
2 804
 
8.2%
7 522
 
5.3%
4 119
 
1.2%
9 103
 
1.1%
6 82
 
0.8%
8 82
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8436
86.4%
Dash Punctuation 1332
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3865
45.8%
1 1740
20.6%
3 1041
 
12.3%
2 804
 
9.5%
7 522
 
6.2%
4 119
 
1.4%
9 103
 
1.2%
6 82
 
1.0%
8 82
 
1.0%
5 78
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1332
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9768
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3865
39.6%
1 1740
17.8%
- 1332
 
13.6%
3 1041
 
10.7%
2 804
 
8.2%
7 522
 
5.3%
4 119
 
1.2%
9 103
 
1.1%
6 82
 
0.8%
8 82
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3865
39.6%
1 1740
17.8%
- 1332
 
13.6%
3 1041
 
10.7%
2 804
 
8.2%
7 522
 
5.3%
4 119
 
1.2%
9 103
 
1.1%
6 82
 
0.8%
8 82
 
0.8%

인허가일자
Date

Distinct402
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1995-05-02 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:44:19.493398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:44:19.682986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3
243 
1
201 

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 (%)
3 243
54.7%
1 201
45.3%

Length

2024-05-11T14:44:19.877272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:20.016949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 243
54.7%
1 201
45.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
243 
영업/정상
201 

Length

Max length5
Median length2
Mean length3.3581081
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 243
54.7%
영업/정상 201
45.3%

Length

2024-05-11T14:44:20.170174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:20.351039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 243
54.7%
영업/정상 201
45.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2
243 
1
201 

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 (%)
2 243
54.7%
1 201
45.3%

Length

2024-05-11T14:44:20.489198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:20.617345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 243
54.7%
1 201
45.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
243 
영업
201 

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 243
54.7%
영업 201
45.3%

Length

2024-05-11T14:44:20.759369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:20.898995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 243
54.7%
영업 201
45.3%

폐업일자
Date

MISSING 

Distinct206
Distinct (%)84.8%
Missing201
Missing (%)45.3%
Memory size3.6 KiB
Minimum1999-09-21 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T14:44:21.072715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:44:21.298219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

전화번호
Text

MISSING 

Distinct274
Distinct (%)96.8%
Missing161
Missing (%)36.3%
Memory size3.6 KiB
2024-05-11T14:44:21.699392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.918728
Min length2

Characters and Unicode

Total characters3090
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

Unique266 ?
Unique (%)94.0%

Sample

1st row02 8613511
2nd row02 0
3rd row02 8574142
4th row02 8371611
5th row02
ValueCountFrequency (%)
02 154
28.9%
070 38
 
7.1%
031 4
 
0.8%
88852016 3
 
0.6%
853 3
 
0.6%
857 3
 
0.6%
0700 2
 
0.4%
1247 2
 
0.4%
856 2
 
0.4%
861 2
 
0.4%
Other values (312) 320
60.0%
2024-05-11T14:44:22.316413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 581
18.8%
2 406
13.1%
347
11.2%
8 312
10.1%
7 252
8.2%
1 224
 
7.2%
5 222
 
7.2%
6 208
 
6.7%
4 204
 
6.6%
3 170
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2743
88.8%
Space Separator 347
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 581
21.2%
2 406
14.8%
8 312
11.4%
7 252
9.2%
1 224
 
8.2%
5 222
 
8.1%
6 208
 
7.6%
4 204
 
7.4%
3 170
 
6.2%
9 164
 
6.0%
Space Separator
ValueCountFrequency (%)
347
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 581
18.8%
2 406
13.1%
347
11.2%
8 312
10.1%
7 252
8.2%
1 224
 
7.2%
5 222
 
7.2%
6 208
 
6.7%
4 204
 
6.6%
3 170
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 581
18.8%
2 406
13.1%
347
11.2%
8 312
10.1%
7 252
8.2%
1 224
 
7.2%
5 222
 
7.2%
6 208
 
6.7%
4 204
 
6.6%
3 170
 
5.5%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct248
Distinct (%)57.8%
Missing15
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean51.191212
Minimum0
Maximum1024.79
Zeros5
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:22.525463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.7
Q16
median21.7
Q360
95-th percentile191.374
Maximum1024.79
Range1024.79
Interquartile range (IQR)54

Descriptive statistics

Standard deviation92.976651
Coefficient of variation (CV)1.8162619
Kurtosis42.836413
Mean51.191212
Median Absolute Deviation (MAD)18
Skewness5.4402163
Sum21961.03
Variance8644.6575
MonotonicityNot monotonic
2024-05-11T14:44:22.759918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 19
 
4.3%
3.0 18
 
4.1%
10.0 16
 
3.6%
3.3 14
 
3.2%
6.0 14
 
3.2%
30.0 12
 
2.7%
8.0 9
 
2.0%
33.0 8
 
1.8%
9.9 8
 
1.8%
15.0 7
 
1.6%
Other values (238) 304
68.5%
(Missing) 15
 
3.4%
ValueCountFrequency (%)
0.0 5
1.1%
1.0 7
1.6%
1.1 1
 
0.2%
1.3 6
1.4%
1.65 1
 
0.2%
1.7 3
0.7%
1.82 1
 
0.2%
2.0 2
 
0.5%
2.1 5
1.1%
2.2 1
 
0.2%
ValueCountFrequency (%)
1024.79 1
0.2%
834.3 1
0.2%
525.0 1
0.2%
522.72 1
0.2%
455.62 1
0.2%
359.32 1
0.2%
330.0 1
0.2%
327.17 1
0.2%
288.0 1
0.2%
286.25 1
0.2%

소재지우편번호
Text

Distinct65
Distinct (%)14.7%
Missing3
Missing (%)0.7%
Memory size3.6 KiB
2024-05-11T14:44:23.042112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3174603
Min length6

Characters and Unicode

Total characters2786
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

Unique25 ?
Unique (%)5.7%

Sample

1st row153802
2nd row153813
3rd row153812
4th row153801
5th row153802
ValueCountFrequency (%)
153803 91
20.6%
153-803 47
 
10.7%
153802 33
 
7.5%
153-801 25
 
5.7%
153768 23
 
5.2%
153801 22
 
5.0%
153759 19
 
4.3%
153-768 15
 
3.4%
153813 15
 
3.4%
153776 13
 
2.9%
Other values (55) 138
31.3%
2024-05-11T14:44:23.480234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 628
22.5%
1 530
19.0%
5 481
17.3%
8 373
13.4%
0 285
10.2%
- 140
 
5.0%
7 126
 
4.5%
6 86
 
3.1%
2 73
 
2.6%
9 47
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2646
95.0%
Dash Punctuation 140
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 628
23.7%
1 530
20.0%
5 481
18.2%
8 373
14.1%
0 285
10.8%
7 126
 
4.8%
6 86
 
3.3%
2 73
 
2.8%
9 47
 
1.8%
4 17
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 628
22.5%
1 530
19.0%
5 481
17.3%
8 373
13.4%
0 285
10.2%
- 140
 
5.0%
7 126
 
4.5%
6 86
 
3.1%
2 73
 
2.6%
9 47
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 628
22.5%
1 530
19.0%
5 481
17.3%
8 373
13.4%
0 285
10.2%
- 140
 
5.0%
7 126
 
4.5%
6 86
 
3.1%
2 73
 
2.6%
9 47
 
1.7%

지번주소
Text

Distinct314
Distinct (%)71.2%
Missing3
Missing (%)0.7%
Memory size3.6 KiB
2024-05-11T14:44:23.834280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length30.337868
Min length17

Characters and Unicode

Total characters13379
Distinct characters211
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique263 ?
Unique (%)59.6%

Sample

1st row서울특별시 금천구 가산동 345-48
2nd row서울특별시 금천구 독산동 291-1
3rd row서울특별시 금천구 독산동 288-6
4th row서울특별시 금천구 가산동 234-42
5th row서울특별시 금천구 가산동 345-48
ValueCountFrequency (%)
서울특별시 441
17.8%
금천구 441
17.8%
가산동 324
 
13.1%
독산동 66
 
2.7%
시흥동 52
 
2.1%
가산 35
 
1.4%
371-16 27
 
1.1%
it캐슬2차 27
 
1.1%
426-5 26
 
1.1%
월드메르디앙2차 21
 
0.8%
Other values (461) 1012
40.9%
2024-05-11T14:44:24.427356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2225
 
16.6%
1 619
 
4.6%
시 510
 
3.8%
산 485
 
3.6%
동 478
 
3.6%
- 453
 
3.4%
서 447
 
3.3%
금 447
 
3.3%
천 447
 
3.3%
울 443
 
3.3%
Other values (201) 6825
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7588
56.7%
Decimal Number 2818
 
21.1%
Space Separator 2225
 
16.6%
Dash Punctuation 453
 
3.4%
Uppercase Letter 172
 
1.3%
Open Punctuation 52
 
0.4%
Close Punctuation 51
 
0.4%
Lowercase Letter 12
 
0.1%
Other Punctuation 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 510
 
6.7%
산 485
 
6.4%
동 478
 
6.3%
서 447
 
5.9%
금 447
 
5.9%
천 447
 
5.9%
울 443
 
5.8%
특 441
 
5.8%
별 441
 
5.8%
구 441
 
5.8%
Other values (159) 3008
39.6%
Uppercase Letter
ValueCountFrequency (%)
T 54
31.4%
I 53
30.8%
B 16
 
9.3%
A 14
 
8.1%
G 11
 
6.4%
L 8
 
4.7%
C 5
 
2.9%
O 3
 
1.7%
K 2
 
1.2%
F 1
 
0.6%
Other values (5) 5
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 619
22.0%
2 340
12.1%
0 330
11.7%
3 323
11.5%
5 282
10.0%
4 282
10.0%
6 182
 
6.5%
7 180
 
6.4%
9 171
 
6.1%
8 109
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
r 2
16.7%
w 1
 
8.3%
o 1
 
8.3%
u 1
 
8.3%
n 1
 
8.3%
t 1
 
8.3%
b 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 37
71.2%
[ 15
28.8%
Close Punctuation
ValueCountFrequency (%)
) 36
70.6%
] 15
29.4%
Other Punctuation
ValueCountFrequency (%)
, 5
71.4%
' 2
 
28.6%
Space Separator
ValueCountFrequency (%)
2225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 453
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7588
56.7%
Common 5607
41.9%
Latin 184
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 510
 
6.7%
산 485
 
6.4%
동 478
 
6.3%
서 447
 
5.9%
금 447
 
5.9%
천 447
 
5.9%
울 443
 
5.8%
특 441
 
5.8%
별 441
 
5.8%
구 441
 
5.8%
Other values (159) 3008
39.6%
Latin
ValueCountFrequency (%)
T 54
29.3%
I 53
28.8%
B 16
 
8.7%
A 14
 
7.6%
G 11
 
6.0%
L 8
 
4.3%
C 5
 
2.7%
e 4
 
2.2%
O 3
 
1.6%
K 2
 
1.1%
Other values (13) 14
 
7.6%
Common
ValueCountFrequency (%)
2225
39.7%
1 619
 
11.0%
- 453
 
8.1%
2 340
 
6.1%
0 330
 
5.9%
3 323
 
5.8%
5 282
 
5.0%
4 282
 
5.0%
6 182
 
3.2%
7 180
 
3.2%
Other values (9) 391
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7588
56.7%
ASCII 5791
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2225
38.4%
1 619
 
10.7%
- 453
 
7.8%
2 340
 
5.9%
0 330
 
5.7%
3 323
 
5.6%
5 282
 
4.9%
4 282
 
4.9%
6 182
 
3.1%
7 180
 
3.1%
Other values (32) 575
 
9.9%
Hangul
ValueCountFrequency (%)
시 510
 
6.7%
산 485
 
6.4%
동 478
 
6.3%
서 447
 
5.9%
금 447
 
5.9%
천 447
 
5.9%
울 443
 
5.8%
특 441
 
5.8%
별 441
 
5.8%
구 441
 
5.8%
Other values (159) 3008
39.6%

도로명주소
Text

MISSING 

Distinct375
Distinct (%)94.7%
Missing48
Missing (%)10.8%
Memory size3.6 KiB
2024-05-11T14:44:24.871910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length43.39899
Min length22

Characters and Unicode

Total characters17186
Distinct characters220
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)90.2%

Sample

1st row서울특별시 금천구 시흥대로47길 43, B동 4호, 11호 (시흥동, 럭키아파트상가)
2nd row서울특별시 금천구 시흥대로 378 (독산동,지상1층)
3rd row서울특별시 금천구 벚꽃로 104, 독산역 롯데캐슬 금천롯데타워 7층 (독산동)
4th row서울특별시 금천구 남부순환로128길 63 (독산동)
5th row서울특별시 금천구 시흥대로153길 36, 2층 (독산동, 제1호건물)
ValueCountFrequency (%)
서울특별시 396
 
13.2%
금천구 396
 
13.2%
가산동 307
 
10.2%
가산디지털1로 143
 
4.8%
가산디지털2로 77
 
2.6%
독산동 44
 
1.5%
시흥동 37
 
1.2%
디지털로9길 35
 
1.2%
가산 35
 
1.2%
it캐슬2차 27
 
0.9%
Other values (639) 1511
50.2%
2024-05-11T14:44:25.547966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2612
 
15.2%
1 890
 
5.2%
산 687
 
4.0%
가 594
 
3.5%
2 560
 
3.3%
시 492
 
2.9%
동 456
 
2.7%
, 451
 
2.6%
0 448
 
2.6%
) 439
 
2.6%
Other values (210) 9557
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9539
55.5%
Decimal Number 3261
 
19.0%
Space Separator 2612
 
15.2%
Other Punctuation 453
 
2.6%
Close Punctuation 443
 
2.6%
Open Punctuation 443
 
2.6%
Uppercase Letter 223
 
1.3%
Dash Punctuation 183
 
1.1%
Lowercase Letter 27
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 687
 
7.2%
가 594
 
6.2%
시 492
 
5.2%
동 456
 
4.8%
서 429
 
4.5%
금 413
 
4.3%
천 402
 
4.2%
울 398
 
4.2%
특 396
 
4.2%
별 396
 
4.2%
Other values (162) 4876
51.1%
Uppercase Letter
ValueCountFrequency (%)
T 60
26.9%
I 55
24.7%
B 30
13.5%
A 24
 
10.8%
G 11
 
4.9%
L 10
 
4.5%
C 10
 
4.5%
O 5
 
2.2%
V 3
 
1.3%
F 2
 
0.9%
Other values (9) 13
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 890
27.3%
2 560
17.2%
0 448
13.7%
3 308
 
9.4%
4 208
 
6.4%
9 207
 
6.3%
6 191
 
5.9%
7 157
 
4.8%
5 153
 
4.7%
8 139
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 6
22.2%
r 4
14.8%
a 4
14.8%
b 3
11.1%
w 3
11.1%
o 3
11.1%
c 1
 
3.7%
u 1
 
3.7%
n 1
 
3.7%
t 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 451
99.6%
' 2
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 439
99.1%
] 4
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 439
99.1%
[ 4
 
0.9%
Space Separator
ValueCountFrequency (%)
2612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9539
55.5%
Common 7397
43.0%
Latin 250
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 687
 
7.2%
가 594
 
6.2%
시 492
 
5.2%
동 456
 
4.8%
서 429
 
4.5%
금 413
 
4.3%
천 402
 
4.2%
울 398
 
4.2%
특 396
 
4.2%
별 396
 
4.2%
Other values (162) 4876
51.1%
Latin
ValueCountFrequency (%)
T 60
24.0%
I 55
22.0%
B 30
12.0%
A 24
 
9.6%
G 11
 
4.4%
L 10
 
4.0%
C 10
 
4.0%
e 6
 
2.4%
O 5
 
2.0%
r 4
 
1.6%
Other values (19) 35
14.0%
Common
ValueCountFrequency (%)
2612
35.3%
1 890
 
12.0%
2 560
 
7.6%
, 451
 
6.1%
0 448
 
6.1%
) 439
 
5.9%
( 439
 
5.9%
3 308
 
4.2%
4 208
 
2.8%
9 207
 
2.8%
Other values (9) 835
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9539
55.5%
ASCII 7647
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2612
34.2%
1 890
 
11.6%
2 560
 
7.3%
, 451
 
5.9%
0 448
 
5.9%
) 439
 
5.7%
( 439
 
5.7%
3 308
 
4.0%
4 208
 
2.7%
9 207
 
2.7%
Other values (38) 1085
14.2%
Hangul
ValueCountFrequency (%)
산 687
 
7.2%
가 594
 
6.2%
시 492
 
5.2%
동 456
 
4.8%
서 429
 
4.5%
금 413
 
4.3%
천 402
 
4.2%
울 398
 
4.2%
특 396
 
4.2%
별 396
 
4.2%
Other values (162) 4876
51.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)17.5%
Missing49
Missing (%)11.0%
Infinite0
Infinite (%)0.0%
Mean8538.6582
Minimum8500
Maximum8657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:25.716943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8502
Q18505
median8507
Q38589
95-th percentile8639
Maximum8657
Range157
Interquartile range (IQR)84

Descriptive statistics

Standard deviation47.586332
Coefficient of variation (CV)0.0055730457
Kurtosis-0.46831301
Mean8538.6582
Median Absolute Deviation (MAD)4
Skewness1.0201126
Sum3372770
Variance2264.459
MonotonicityNot monotonic
2024-05-11T14:44:25.881659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8506 62
14.0%
8505 36
 
8.1%
8503 31
 
7.0%
8504 26
 
5.9%
8511 23
 
5.2%
8507 19
 
4.3%
8589 19
 
4.3%
8512 13
 
2.9%
8502 10
 
2.3%
8639 10
 
2.3%
Other values (59) 146
32.9%
(Missing) 49
 
11.0%
ValueCountFrequency (%)
8500 5
 
1.1%
8501 9
 
2.0%
8502 10
 
2.3%
8503 31
7.0%
8504 26
5.9%
8505 36
8.1%
8506 62
14.0%
8507 19
 
4.3%
8509 2
 
0.5%
8510 6
 
1.4%
ValueCountFrequency (%)
8657 1
 
0.2%
8656 6
1.4%
8655 2
 
0.5%
8650 1
 
0.2%
8646 1
 
0.2%
8639 10
2.3%
8637 2
 
0.5%
8635 1
 
0.2%
8634 1
 
0.2%
8632 3
 
0.7%

사업장명
Text

Distinct436
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-05-11T14:44:26.220517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.759009
Min length2

Characters and Unicode

Total characters3445
Distinct characters409
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique428 ?
Unique (%)96.4%

Sample

1st row시골종합식품(주)
2nd row한국코카콜라보틀링(주)_
3rd row제일수산
4th row(주)자연촌
5th row유미물산(주)
ValueCountFrequency (%)
주식회사 77
 
14.1%
농업회사법인 3
 
0.5%
주)해피레인 2
 
0.4%
한국코카콜라보틀링(주 2
 
0.4%
진생당 2
 
0.4%
주)데이바이미 2
 
0.4%
유한책임회사 2
 
0.4%
주 2
 
0.4%
주)휴럼 2
 
0.4%
주)온샵 2
 
0.4%
Other values (447) 451
82.4%
2024-05-11T14:44:26.841486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 306
 
8.9%
( 221
 
6.4%
) 221
 
6.4%
이 150
 
4.4%
사 103
 
3.0%
103
 
3.0%
식 96
 
2.8%
스 96
 
2.8%
회 91
 
2.6%
리 73
 
2.1%
Other values (399) 1985
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2850
82.7%
Open Punctuation 221
 
6.4%
Close Punctuation 221
 
6.4%
Space Separator 103
 
3.0%
Uppercase Letter 31
 
0.9%
Lowercase Letter 8
 
0.2%
Decimal Number 7
 
0.2%
Other Punctuation 2
 
0.1%
Connector Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 306
 
10.7%
이 150
 
5.3%
사 103
 
3.6%
식 96
 
3.4%
스 96
 
3.4%
회 91
 
3.2%
리 73
 
2.6%
에 52
 
1.8%
드 50
 
1.8%
오 43
 
1.5%
Other values (365) 1790
62.8%
Uppercase Letter
ValueCountFrequency (%)
B 5
16.1%
M 4
12.9%
P 4
12.9%
A 2
 
6.5%
O 2
 
6.5%
I 2
 
6.5%
F 2
 
6.5%
N 2
 
6.5%
H 1
 
3.2%
J 1
 
3.2%
Other values (6) 6
19.4%
Decimal Number
ValueCountFrequency (%)
7 1
14.3%
1 1
14.3%
0 1
14.3%
3 1
14.3%
6 1
14.3%
9 1
14.3%
5 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
l 2
25.0%
a 1
12.5%
v 1
12.5%
e 1
12.5%
w 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 221
100.0%
Space Separator
ValueCountFrequency (%)
103
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2850
82.7%
Common 556
 
16.1%
Latin 39
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 306
 
10.7%
이 150
 
5.3%
사 103
 
3.6%
식 96
 
3.4%
스 96
 
3.4%
회 91
 
3.2%
리 73
 
2.6%
에 52
 
1.8%
드 50
 
1.8%
오 43
 
1.5%
Other values (365) 1790
62.8%
Latin
ValueCountFrequency (%)
B 5
12.8%
M 4
 
10.3%
P 4
 
10.3%
A 2
 
5.1%
O 2
 
5.1%
I 2
 
5.1%
i 2
 
5.1%
F 2
 
5.1%
N 2
 
5.1%
l 2
 
5.1%
Other values (12) 12
30.8%
Common
ValueCountFrequency (%)
( 221
39.7%
) 221
39.7%
103
18.5%
& 2
 
0.4%
_ 2
 
0.4%
7 1
 
0.2%
1 1
 
0.2%
0 1
 
0.2%
3 1
 
0.2%
6 1
 
0.2%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2850
82.7%
ASCII 595
 
17.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 306
 
10.7%
이 150
 
5.3%
사 103
 
3.6%
식 96
 
3.4%
스 96
 
3.4%
회 91
 
3.2%
리 73
 
2.6%
에 52
 
1.8%
드 50
 
1.8%
오 43
 
1.5%
Other values (365) 1790
62.8%
ASCII
ValueCountFrequency (%)
( 221
37.1%
) 221
37.1%
103
17.3%
B 5
 
0.8%
M 4
 
0.7%
P 4
 
0.7%
A 2
 
0.3%
O 2
 
0.3%
I 2
 
0.3%
i 2
 
0.3%
Other values (24) 29
 
4.9%

최종수정일자
Date

Distinct440
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1999-08-31 00:00:00
Maximum2024-05-09 10:23:42
2024-05-11T14:44:27.060896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:44:27.271413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
I
234 
U
210 

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 234
52.7%
U 210
47.3%

Length

2024-05-11T14:44:27.437917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:27.547695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 234
52.7%
u 210
47.3%

데이터갱신일자
Date

Distinct259
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:03:00
2024-05-11T14:44:27.668360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:44:28.111771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
유통전문판매업
444 

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 444
100.0%

Length

2024-05-11T14:44:28.255207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:28.381390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 444
100.0%

좌표정보(X)
Real number (ℝ)

Distinct161
Distinct (%)36.5%
Missing3
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean189915.58
Minimum188907.88
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:28.501932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188907.88
5-th percentile189055.14
Q1189369.54
median189647.05
Q3190300.45
95-th percentile191391.97
Maximum192754.35
Range3846.4668
Interquartile range (IQR)930.91234

Descriptive statistics

Standard deviation795.88514
Coefficient of variation (CV)0.0041907311
Kurtosis1.1686808
Mean189915.58
Median Absolute Deviation (MAD)331.00417
Skewness1.3053121
Sum83752772
Variance633433.16
MonotonicityNot monotonic
2024-05-11T14:44:28.721143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189497.04098479 27
 
6.1%
189202.600232089 26
 
5.9%
189055.138252216 21
 
4.7%
189378.332493727 17
 
3.8%
189459.065518928 14
 
3.2%
189369.53962474 12
 
2.7%
191226.287379467 12
 
2.7%
189700.026948955 10
 
2.3%
189538.020935968 9
 
2.0%
189834.383375802 9
 
2.0%
Other values (151) 284
64.0%
ValueCountFrequency (%)
188907.879367078 1
 
0.2%
188927.953883941 2
 
0.5%
188965.473671835 1
 
0.2%
189016.465808265 4
 
0.9%
189055.138252216 21
4.7%
189092.729912585 3
 
0.7%
189127.981104583 1
 
0.2%
189174.558570016 2
 
0.5%
189188.74756733 2
 
0.5%
189201.559775268 4
 
0.9%
ValueCountFrequency (%)
192754.34619252 2
 
0.5%
192742.326147617 1
 
0.2%
192368.43764933 6
1.4%
192233.382815227 1
 
0.2%
191924.359561902 1
 
0.2%
191922.312767219 1
 
0.2%
191879.175980379 1
 
0.2%
191853.378601365 1
 
0.2%
191825.153190485 1
 
0.2%
191794.387105728 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct161
Distinct (%)36.5%
Missing3
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean441224.52
Minimum437644.05
Maximum442636.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:28.943847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437644.05
5-th percentile438460.67
Q1440870.09
median441728.27
Q3441958.33
95-th percentile442320.78
Maximum442636.32
Range4992.2729
Interquartile range (IQR)1088.2418

Descriptive statistics

Standard deviation1156.7733
Coefficient of variation (CV)0.002621734
Kurtosis1.6440021
Mean441224.52
Median Absolute Deviation (MAD)365.03992
Skewness-1.5693415
Sum1.9458001 × 108
Variance1338124.5
MonotonicityNot monotonic
2024-05-11T14:44:29.114126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441728.27059771 27
 
6.1%
441848.24299943 26
 
5.9%
441958.334400683 21
 
4.7%
442066.99866487 17
 
3.8%
441844.960857588 14
 
3.2%
441629.361414684 12
 
2.7%
437914.06299827 12
 
2.7%
441229.110998601 10
 
2.3%
441982.427934953 9
 
2.0%
441938.326056501 9
 
2.0%
Other values (151) 284
64.0%
ValueCountFrequency (%)
437644.047174663 3
 
0.7%
437816.239800826 1
 
0.2%
437914.06299827 12
2.7%
438004.273717434 1
 
0.2%
438107.173119592 1
 
0.2%
438266.70898504 1
 
0.2%
438358.367852933 1
 
0.2%
438410.522111193 1
 
0.2%
438458.097193512 1
 
0.2%
438460.667319682 1
 
0.2%
ValueCountFrequency (%)
442636.320100968 2
 
0.5%
442562.722742062 2
 
0.5%
442493.020182986 8
1.8%
442478.356256941 3
 
0.7%
442460.505542105 1
 
0.2%
442417.955057116 1
 
0.2%
442367.500287732 2
 
0.5%
442320.784167212 4
0.9%
442309.174987731 1
 
0.2%
442298.784420302 2
 
0.5%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
유통전문판매업
252 
<NA>
192 

Length

Max length7
Median length7
Mean length5.7027027
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 252
56.8%
<NA> 192
43.2%

Length

2024-05-11T14:44:29.259428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:29.403967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 252
56.8%
na 192
43.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
399 
0
45 

Length

Max length4
Median length4
Mean length3.6959459
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
89.9%
0 45
 
10.1%

Length

2024-05-11T14:44:29.560736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:29.710175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
89.9%
0 45
 
10.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
399 
0
45 

Length

Max length4
Median length4
Mean length3.6959459
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
89.9%
0 45
 
10.1%

Length

2024-05-11T14:44:29.838512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:29.972811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
89.9%
0 45
 
10.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
433 
기타
 
8
주택가주변
 
2
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9774775
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 433
97.5%
기타 8
 
1.8%
주택가주변 2
 
0.5%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-11T14:44:30.118134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:30.255719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 433
97.5%
기타 8
 
1.8%
주택가주변 2
 
0.5%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
433 
기타
 
9
자율
 
2

Length

Max length4
Median length4
Mean length3.9504505
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 433
97.5%
기타 9
 
2.0%
자율 2
 
0.5%

Length

2024-05-11T14:44:30.406980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:30.536069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 433
97.5%
기타 9
 
2.0%
자율 2
 
0.5%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
414 
상수도전용
 
30

Length

Max length5
Median length4
Mean length4.0675676
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 414
93.2%
상수도전용 30
 
6.8%

Length

2024-05-11T14:44:30.645699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:30.771061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 414
93.2%
상수도전용 30
 
6.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
402 
0
42 

Length

Max length4
Median length4
Mean length3.7162162
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> 402
90.5%
0 42
 
9.5%

Length

2024-05-11T14:44:30.896654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:31.016873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 402
90.5%
0 42
 
9.5%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
318 
0
122 
2
 
3
1
 
1

Length

Max length4
Median length4
Mean length3.1486486
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 318
71.6%
0 122
 
27.5%
2 3
 
0.7%
1 1
 
0.2%

Length

2024-05-11T14:44:31.164400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:31.302529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 318
71.6%
0 122
 
27.5%
2 3
 
0.7%
1 1
 
0.2%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
318 
0
125 
2
 
1

Length

Max length4
Median length4
Mean length3.1486486
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 318
71.6%
0 125
 
28.2%
2 1
 
0.2%

Length

2024-05-11T14:44:31.447971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:31.637547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 318
71.6%
0 125
 
28.2%
2 1
 
0.2%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
319 
0
125 

Length

Max length4
Median length4
Mean length3.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
71.8%
0 125
 
28.2%

Length

2024-05-11T14:44:31.865576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:32.073909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
71.8%
0 125
 
28.2%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
319 
0
125 

Length

Max length4
Median length4
Mean length3.1554054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 319
71.8%
0 125
 
28.2%

Length

2024-05-11T14:44:32.230746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:32.372671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 319
71.8%
0 125
 
28.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
264 
자가
134 
임대
46 

Length

Max length4
Median length4
Mean length3.1891892
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> 264
59.5%
자가 134
30.2%
임대 46
 
10.4%

Length

2024-05-11T14:44:32.523075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:32.643836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 264
59.5%
자가 134
30.2%
임대 46
 
10.4%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)12.5%
Missing388
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean1789285.7
Minimum0
Maximum16000000
Zeros44
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:32.739490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10000000
Maximum16000000
Range16000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3914666.1
Coefficient of variation (CV)2.1878373
Kurtosis3.172897
Mean1789285.7
Median Absolute Deviation (MAD)0
Skewness2.0744497
Sum1.002 × 108
Variance1.532461 × 1013
MonotonicityNot monotonic
2024-05-11T14:44:32.859871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 44
 
9.9%
10000000 7
 
1.6%
1700000 1
 
0.2%
1500000 1
 
0.2%
6000000 1
 
0.2%
16000000 1
 
0.2%
5000000 1
 
0.2%
(Missing) 388
87.4%
ValueCountFrequency (%)
0 44
9.9%
1500000 1
 
0.2%
1700000 1
 
0.2%
5000000 1
 
0.2%
6000000 1
 
0.2%
10000000 7
 
1.6%
16000000 1
 
0.2%
ValueCountFrequency (%)
16000000 1
 
0.2%
10000000 7
 
1.6%
6000000 1
 
0.2%
5000000 1
 
0.2%
1700000 1
 
0.2%
1500000 1
 
0.2%
0 44
9.9%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)19.6%
Missing388
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean296308.93
Minimum0
Maximum6000000
Zeros44
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:32.970054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1362500
Maximum6000000
Range6000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation925952.35
Coefficient of variation (CV)3.1249559
Kurtosis27.164092
Mean296308.93
Median Absolute Deviation (MAD)0
Skewness4.8483107
Sum16593300
Variance8.5738775 × 1011
MonotonicityNot monotonic
2024-05-11T14:44:33.111053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 44
 
9.9%
1200000 2
 
0.5%
500000 2
 
0.5%
170000 1
 
0.2%
1850000 1
 
0.2%
6000000 1
 
0.2%
416000 1
 
0.2%
250000 1
 
0.2%
2700000 1
 
0.2%
1107300 1
 
0.2%
(Missing) 388
87.4%
ValueCountFrequency (%)
0 44
9.9%
170000 1
 
0.2%
250000 1
 
0.2%
416000 1
 
0.2%
500000 2
 
0.5%
700000 1
 
0.2%
1107300 1
 
0.2%
1200000 2
 
0.5%
1850000 1
 
0.2%
2700000 1
 
0.2%
ValueCountFrequency (%)
6000000 1
0.2%
2700000 1
0.2%
1850000 1
0.2%
1200000 2
0.5%
1107300 1
0.2%
700000 1
0.2%
500000 2
0.5%
416000 1
0.2%
250000 1
0.2%
170000 1
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing192
Missing (%)43.2%
Memory size1020.0 B
False
252 
(Missing)
192 
ValueCountFrequency (%)
False 252
56.8%
(Missing) 192
43.2%
2024-05-11T14:44:33.209783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)5.6%
Missing192
Missing (%)43.2%
Infinite0
Infinite (%)0.0%
Mean0.63702381
Minimum0
Maximum24.44
Zeros239
Zeros (%)53.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-05-11T14:44:33.303577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.45
Maximum24.44
Range24.44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1944055
Coefficient of variation (CV)5.0145779
Kurtosis32.434437
Mean0.63702381
Median Absolute Deviation (MAD)0
Skewness5.602912
Sum160.53
Variance10.204227
MonotonicityNot monotonic
2024-05-11T14:44:33.459399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 239
53.8%
13.5 1
 
0.2%
3.72 1
 
0.2%
7.03 1
 
0.2%
1.0 1
 
0.2%
10.44 1
 
0.2%
22.88 1
 
0.2%
7.6 1
 
0.2%
4.29 1
 
0.2%
12.67 1
 
0.2%
Other values (4) 4
 
0.9%
(Missing) 192
43.2%
ValueCountFrequency (%)
0.0 239
53.8%
1.0 1
 
0.2%
3.72 1
 
0.2%
4.29 1
 
0.2%
7.03 1
 
0.2%
7.6 1
 
0.2%
10.44 1
 
0.2%
12.67 1
 
0.2%
13.5 1
 
0.2%
14.52 1
 
0.2%
ValueCountFrequency (%)
24.44 1
0.2%
22.88 1
0.2%
19.88 1
0.2%
18.56 1
0.2%
14.52 1
0.2%
13.5 1
0.2%
12.67 1
0.2%
10.44 1
0.2%
7.6 1
0.2%
7.03 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing444
Missing (%)100.0%
Memory size4.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-113-1995-0033419950502<NA>3폐업2폐업20060707<NA><NA><NA>02 861351146.32153802서울특별시 금천구 가산동 345-48<NA><NA>시골종합식품(주)2003-12-11 00:00:00I2018-08-31 23:59:59.0유통전문판매업189561.360526440925.407622유통전문판매업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131700003170000-113-1995-0033519951107<NA>3폐업2폐업19990921<NA><NA><NA>02 00.0153813서울특별시 금천구 독산동 291-1<NA><NA>한국코카콜라보틀링(주)_2002-01-13 00:00:00I2018-08-31 23:59:59.0유통전문판매업190694.880295440764.426278유통전문판매업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231700003170000-113-1995-0040419951208<NA>3폐업2폐업20050414<NA><NA><NA>02 857414263.0153812서울특별시 금천구 독산동 288-6<NA><NA>제일수산1999-08-31 00:00:00I2018-08-31 23:59:59.0유통전문판매업190882.328667440895.71538유통전문판매업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331700003170000-113-1996-0040219960318<NA>3폐업2폐업20060307<NA><NA><NA>02 837161121.0153801서울특별시 금천구 가산동 234-42<NA><NA>(주)자연촌1999-08-31 00:00:00I2018-08-31 23:59:59.0유통전문판매업190521.187976441254.625991유통전문판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431700003170000-113-1996-0040519961128<NA>3폐업2폐업20050331<NA><NA><NA>0235.36153802서울특별시 금천구 가산동 345-48<NA><NA>유미물산(주)2003-06-25 00:00:00I2018-08-31 23:59:59.0유통전문판매업189561.360526440925.407622유통전문판매업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531700003170000-113-1997-0040619970322<NA>3폐업2폐업20060324<NA><NA><NA>02 80252920.0153863서울특별시 금천구 시흥동 984-3<NA><NA>대미식품1999-08-31 00:00:00I2018-08-31 23:59:59.0유통전문판매업191380.862054438107.17312유통전문판매업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631700003170000-113-1997-004071997-07-01<NA>1영업/정상1영업<NA><NA><NA><NA>02 806786140.7153-761서울특별시 금천구 시흥동 1002-1 럭키아파트상가 B-4,11서울특별시 금천구 시흥대로47길 43, B동 4호, 11호 (시흥동, 럭키아파트상가)8634태평양유통2023-12-14 13:42:29U2022-11-01 23:06:00.0유통전문판매업191026.637158438701.205635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731700003170000-113-1997-0040819971020<NA>3폐업2폐업20221207<NA><NA><NA>02 838110131.39153821서울특별시 금천구 독산동 1030-1 지상1층서울특별시 금천구 시흥대로 378 (독산동,지상1층)8580노보텔엠버서더독산서울2022-12-07 15:12:17U2021-11-02 00:09:00.0유통전문판매업190941.203219440593.575842<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831700003170000-113-1998-0033719980813<NA>3폐업2폐업20060509<NA><NA><NA>02 8986102104.94153833서울특별시 금천구 독산동 1106-1<NA><NA>광장유통1999-09-01 00:00:00I2018-08-31 23:59:59.0유통전문판매업190304.775697439082.498036유통전문판매업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931700003170000-113-1998-0033819980813<NA>3폐업2폐업20050414<NA><NA><NA>0215887999120.0153803서울특별시 금천구 가산동 371-8<NA><NA>대일유통2005-03-07 00:00:00I2018-08-31 23:59:59.0유통전문판매업189292.647938441963.693321유통전문판매업00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
43431700003170000-113-2024-000062024-02-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.52153-806서울특별시 금천구 독산동 144-57서울특별시 금천구 시흥대로141길 65, 1층 (독산동)8531이집 닭강정 잘하네2024-02-23 13:41:11U2023-12-01 22:05:00.0유통전문판매업190869.778202441522.721274<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43531700003170000-113-2024-000072024-02-20<NA>1영업/정상1영업<NA><NA><NA><NA>02633998543.3153-801서울특별시 금천구 가산동 60-3 대륭포스트타워 5차 1층 111-324호서울특별시 금천구 디지털로9길 68, 대륭포스트타워 5차 1층 111-324호 (가산동)8512인터필2024-02-20 15:50:24I2023-12-01 22:02:00.0유통전문판매업189877.178944442093.648597<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43631700003170000-113-2024-000082024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>76.7153-802서울특별시 금천구 가산동 319 호서대벤처타워서울특별시 금천구 가산디지털1로 70, 호서대벤처타워 4층 407호 (가산동)8590(주)컴퍼니와우2024-02-27 09:18:28I2023-12-01 22:09:00.0유통전문판매업189841.076534441127.322444<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43731700003170000-113-2024-000092024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA>022088813150.0153-801서울특별시 금천구 가산동 60-17 백상스타타워1차서울특별시 금천구 디지털로9길 65, 백상스타타워1차 15층 1505(일부)호 (가산동)8511(주)트렌디래빗2024-03-05 14:08:42I2023-12-03 00:07:00.0유통전문판매업189790.323887442017.867458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43831700003170000-113-2024-000102024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA>02347110073.7153-801서울특별시 금천구 가산동 60-17 백상스타타워1차서울특별시 금천구 디지털로9길 65, 백상스타타워1차 2층 203(일부)호 (가산동)8511제이포유 주식회사2024-03-21 11:04:11I2023-12-02 22:03:00.0유통전문판매업189790.323887442017.867458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43931700003170000-113-2024-000112024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.0153-768서울특별시 금천구 가산동 550-1 IT캐슬서울특별시 금천구 가산디지털2로 98, IT캐슬 2동 209호 (가산동)8506주식회사 유어니즈2024-03-21 15:01:50I2023-12-02 22:03:00.0유통전문판매업189369.539625441629.361415<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44031700003170000-113-2024-000122024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA>070 8095458817.0153-030서울특별시 금천구 시흥동 1013-7 벽산중심상가서울특별시 금천구 금하로 763, 벽산중심상가 205-P3호 (시흥동)8656드링컴트루2024-04-19 14:12:31I2023-12-03 22:01:00.0유통전문판매업192368.437649438690.814038<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44131700003170000-113-2024-000132024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 621538903.3153-802서울특별시 금천구 가산동 345-13 파트너스타워 201-A9호서울특별시 금천구 가산디지털1로 83, 파트너스타워 201-A9호 (가산동)8589뉴클라베2024-04-23 14:32:56I2023-12-03 22:05:00.0유통전문판매업189700.026949441229.110999<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44231700003170000-113-2024-000142024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0153-768서울특별시 금천구 가산동 371-16 IT캐슬2차서울특별시 금천구 가산디지털1로 137, IT캐슬2차 19층 1901-3-14호 (가산동)8506주식회사 씨앤엘무역2024-05-01 17:04:10I2023-12-05 00:03:00.0유통전문판매업189497.040985441728.270598<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44331700003170000-113-2024-000152024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA>022104047566.0153-782서울특별시 금천구 가산동 345-30 남성프라자서울특별시 금천구 디지털로 130, 남성프라자 5층 501호 (가산동)8589(주)셀루메드2024-05-09 10:23:42I2023-12-04 23:01:00.0유통전문판매업189472.091899441483.675018<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>