Overview

Dataset statistics

Number of variables30
Number of observations130
Missing cells532
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.4 KiB
Average record size in memory255.0 B

Variable types

Categorical14
Numeric5
DateTime5
Unsupported2
Text4

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),축산업무구분명,축산물가공업구분명,축산일련번호,권리주체일련번호,총인원
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18119/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (93.5%)Imbalance
휴업종료일자 is highly imbalanced (93.5%)Imbalance
업태구분명 is highly imbalanced (80.3%)Imbalance
인허가취소일자 has 130 (100.0%) missing valuesMissing
폐업일자 has 48 (36.9%) missing valuesMissing
재개업일자 has 92 (70.8%) missing valuesMissing
전화번호 has 87 (66.9%) missing valuesMissing
소재지우편번호 has 130 (100.0%) missing valuesMissing
도로명우편번호 has 45 (34.6%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 120 (92.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:19:51.224503
Analysis finished2024-05-11 06:19:52.287674
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3170000
130 

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 130
100.0%

Length

2024-05-11T15:19:52.418000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:52.580670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 130
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.17 × 1017
Minimum3.17 × 1017
Maximum3.17 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:19:52.760253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.17 × 1017
5-th percentile3.17 × 1017
Q13.17 × 1017
median3.17 × 1017
Q33.17 × 1017
95-th percentile3.17 × 1017
Maximum3.17 × 1017
Range290000
Interquartile range (IQR)87488

Descriptive statistics

Standard deviation62421.136
Coefficient of variation (CV)1.969121 × 10-13
Kurtosis-0.58307513
Mean3.17 × 1017
Median Absolute Deviation (MAD)40000
Skewness0.10264018
Sum4.3165119 × 1018
Variance3.8963983 × 109
MonotonicityStrictly increasing
2024-05-11T15:19:53.008403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
317000000419940001 1
 
0.8%
317000000420140007 1
 
0.8%
317000000420140005 1
 
0.8%
317000000420140004 1
 
0.8%
317000000420140003 1
 
0.8%
317000000420140002 1
 
0.8%
317000000420140001 1
 
0.8%
317000000420130012 1
 
0.8%
317000000420130011 1
 
0.8%
317000000420130010 1
 
0.8%
Other values (120) 120
92.3%
ValueCountFrequency (%)
317000000419940001 1
0.8%
317000000419980001 1
0.8%
317000000419980002 1
0.8%
317000000419980003 1
0.8%
317000000420000001 1
0.8%
317000000420000002 1
0.8%
317000000420000003 1
0.8%
317000000420010001 1
0.8%
317000000420020001 1
0.8%
317000000420020002 1
0.8%
ValueCountFrequency (%)
317000000420230001 1
0.8%
317000000420220003 1
0.8%
317000000420220002 1
0.8%
317000000420220001 1
0.8%
317000000420210007 1
0.8%
317000000420210006 1
0.8%
317000000420210005 1
0.8%
317000000420210004 1
0.8%
317000000420210003 1
0.8%
317000000420210002 1
0.8%

인허가일자
Date

Distinct121
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1994-09-13 00:00:00
Maximum2023-12-28 00:00:00
2024-05-11T15:19:53.248151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:53.474773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
63 
1
44 
4
22 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row3
2nd row4
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
3 63
48.5%
1 44
33.8%
4 22
 
16.9%
2 1
 
0.8%

Length

2024-05-11T15:19:53.638545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:53.790657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 63
48.5%
1 44
33.8%
4 22
 
16.9%
2 1
 
0.8%

영업상태명
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
63 
영업/정상
44 
취소/말소/만료/정지/중지
22 
휴업
 
1

Length

Max length14
Median length5
Mean length5.0461538
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row폐업
2nd row취소/말소/만료/정지/중지
3rd row폐업
4th row폐업
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
폐업 63
48.5%
영업/정상 44
33.8%
취소/말소/만료/정지/중지 22
 
16.9%
휴업 1
 
0.8%

Length

2024-05-11T15:19:53.985506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:54.165572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 63
48.5%
영업/정상 44
33.8%
취소/말소/만료/정지/중지 22
 
16.9%
휴업 1
 
0.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2
63 
0
44 
4
22 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row2
2nd row4
3rd row2
4th row2
5th row4

Common Values

ValueCountFrequency (%)
2 63
48.5%
0 44
33.8%
4 22
 
16.9%
1 1
 
0.8%

Length

2024-05-11T15:19:54.362440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:54.531101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 63
48.5%
0 44
33.8%
4 22
 
16.9%
1 1
 
0.8%

상세영업상태명
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
63 
정상
44 
말소
22 
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 63
48.5%
정상 44
33.8%
말소 22
 
16.9%
휴업 1
 
0.8%

Length

2024-05-11T15:19:54.778128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:54.948565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 63
48.5%
정상 44
33.8%
말소 22
 
16.9%
휴업 1
 
0.8%

폐업일자
Date

MISSING 

Distinct60
Distinct (%)73.2%
Missing48
Missing (%)36.9%
Memory size1.1 KiB
Minimum2004-06-30 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T15:19:55.148188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:55.389994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
129 
20210726
 
1

Length

Max length8
Median length4
Mean length4.0307692
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
99.2%
20210726 1
 
0.8%

Length

2024-05-11T15:19:55.580159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:55.739505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
99.2%
20210726 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
129 
20220726
 
1

Length

Max length8
Median length4
Mean length4.0307692
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
99.2%
20220726 1
 
0.8%

Length

2024-05-11T15:19:55.910968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:56.076606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
99.2%
20220726 1
 
0.8%

재개업일자
Date

MISSING 

Distinct33
Distinct (%)86.8%
Missing92
Missing (%)70.8%
Memory size1.1 KiB
Minimum2017-02-07 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T15:19:56.229054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:56.413157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

전화번호
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing87
Missing (%)66.9%
Memory size1.1 KiB
2024-05-11T15:19:56.712969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.6511628
Min length8

Characters and Unicode

Total characters415
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row805-7644
2nd row839-9676
3rd row893-6400
4th row838-7703
5th row807-3913
ValueCountFrequency (%)
805-7644 1
 
2.3%
02-868-9613 1
 
2.3%
861-3725 1
 
2.3%
867-0025~6 1
 
2.3%
02-868-0201 1
 
2.3%
02-806-9097 1
 
2.3%
804-0546 1
 
2.3%
02-892-9200 1
 
2.3%
849-1999 1
 
2.3%
02-898-8019 1
 
2.3%
Other values (33) 33
76.7%
2024-05-11T15:19:57.314816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 65
15.7%
8 63
15.2%
0 57
13.7%
2 44
10.6%
9 37
8.9%
6 34
8.2%
7 28
6.7%
3 28
6.7%
4 23
 
5.5%
5 18
 
4.3%
Other values (2) 18
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 348
83.9%
Dash Punctuation 65
 
15.7%
Math Symbol 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 63
18.1%
0 57
16.4%
2 44
12.6%
9 37
10.6%
6 34
9.8%
7 28
8.0%
3 28
8.0%
4 23
 
6.6%
5 18
 
5.2%
1 16
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 65
15.7%
8 63
15.2%
0 57
13.7%
2 44
10.6%
9 37
8.9%
6 34
8.2%
7 28
6.7%
3 28
6.7%
4 23
 
5.5%
5 18
 
4.3%
Other values (2) 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 65
15.7%
8 63
15.2%
0 57
13.7%
2 44
10.6%
9 37
8.9%
6 34
8.2%
7 28
6.7%
3 28
6.7%
4 23
 
5.5%
5 18
 
4.3%
Other values (2) 18
 
4.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.960308
Minimum0
Maximum8503
Zeros120
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:19:57.566008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile181.04
Maximum8503
Range8503
Interquartile range (IQR)0

Descriptive statistics

Standard deviation758.5614
Coefficient of variation (CV)7.823422
Kurtosis119.44627
Mean96.960308
Median Absolute Deviation (MAD)0
Skewness10.751249
Sum12604.84
Variance575415.4
MonotonicityNot monotonic
2024-05-11T15:19:57.792433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 120
92.3%
155.85 1
 
0.8%
154.8 1
 
0.8%
975.52 1
 
0.8%
288.25 1
 
0.8%
658.49 1
 
0.8%
201.65 1
 
0.8%
1182.5 1
 
0.8%
46.58 1
 
0.8%
438.2 1
 
0.8%
ValueCountFrequency (%)
0.0 120
92.3%
46.58 1
 
0.8%
154.8 1
 
0.8%
155.85 1
 
0.8%
201.65 1
 
0.8%
288.25 1
 
0.8%
438.2 1
 
0.8%
658.49 1
 
0.8%
975.52 1
 
0.8%
1182.5 1
 
0.8%
ValueCountFrequency (%)
8503.0 1
0.8%
1182.5 1
0.8%
975.52 1
0.8%
658.49 1
0.8%
438.2 1
0.8%
288.25 1
0.8%
201.65 1
0.8%
155.85 1
0.8%
154.8 1
0.8%
46.58 1
0.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

지번주소
Text

Distinct121
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:19:58.357402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length25.492308
Min length14

Characters and Unicode

Total characters3314
Distinct characters104
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

Unique113 ?
Unique (%)86.9%

Sample

1st row서울특별시 금천구 독산동 331-40번지
2nd row서울특별시 금천구 독산동 331-59
3rd row서울특별시 금천구 독산동 144-30번지
4th row서울특별시 금천구 시흥동 985-1번지
5th row서울특별시 금천구 독산동 1027-18번지
ValueCountFrequency (%)
금천구 137
21.9%
서울특별시 134
21.4%
독산동 75
 
12.0%
가산동 37
 
5.9%
시흥동 18
 
2.9%
지하1층 6
 
1.0%
1층 4
 
0.6%
1002-1번지 4
 
0.6%
327-32 3
 
0.5%
293-4 3
 
0.5%
Other values (175) 206
32.9%
2024-05-11T15:19:59.195178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
579
 
17.5%
시 152
 
4.6%
1 145
 
4.4%
금 137
 
4.1%
천 137
 
4.1%
구 137
 
4.1%
동 135
 
4.1%
서 134
 
4.0%
특 134
 
4.0%
별 134
 
4.0%
Other values (94) 1490
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1861
56.2%
Decimal Number 711
 
21.5%
Space Separator 579
 
17.5%
Dash Punctuation 124
 
3.7%
Other Punctuation 13
 
0.4%
Close Punctuation 11
 
0.3%
Open Punctuation 11
 
0.3%
Uppercase Letter 2
 
0.1%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 152
 
8.2%
금 137
 
7.4%
천 137
 
7.4%
구 137
 
7.4%
동 135
 
7.3%
서 134
 
7.2%
특 134
 
7.2%
별 134
 
7.2%
울 134
 
7.2%
산 124
 
6.7%
Other values (77) 503
27.0%
Decimal Number
ValueCountFrequency (%)
1 145
20.4%
2 113
15.9%
3 106
14.9%
0 87
12.2%
9 75
10.5%
4 50
 
7.0%
6 41
 
5.8%
5 39
 
5.5%
8 36
 
5.1%
7 19
 
2.7%
Space Separator
ValueCountFrequency (%)
579
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1861
56.2%
Common 1451
43.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 152
 
8.2%
금 137
 
7.4%
천 137
 
7.4%
구 137
 
7.4%
동 135
 
7.3%
서 134
 
7.2%
특 134
 
7.2%
별 134
 
7.2%
울 134
 
7.2%
산 124
 
6.7%
Other values (77) 503
27.0%
Common
ValueCountFrequency (%)
579
39.9%
1 145
 
10.0%
- 124
 
8.5%
2 113
 
7.8%
3 106
 
7.3%
0 87
 
6.0%
9 75
 
5.2%
4 50
 
3.4%
6 41
 
2.8%
5 39
 
2.7%
Other values (6) 92
 
6.3%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1861
56.2%
ASCII 1453
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
579
39.8%
1 145
 
10.0%
- 124
 
8.5%
2 113
 
7.8%
3 106
 
7.3%
0 87
 
6.0%
9 75
 
5.2%
4 50
 
3.4%
6 41
 
2.8%
5 39
 
2.7%
Other values (7) 94
 
6.5%
Hangul
ValueCountFrequency (%)
시 152
 
8.2%
금 137
 
7.4%
천 137
 
7.4%
구 137
 
7.4%
동 135
 
7.3%
서 134
 
7.2%
특 134
 
7.2%
별 134
 
7.2%
울 134
 
7.2%
산 124
 
6.7%
Other values (77) 503
27.0%

도로명주소
Text

Distinct112
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:19:59.656366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length31.592308
Min length23

Characters and Unicode

Total characters4107
Distinct characters123
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

Unique97 ?
Unique (%)74.6%

Sample

1st row서울특별시 금천구 범안로 1189 (독산동)
2nd row서울특별시 금천구 범안로15길 14 (독산동)
3rd row서울특별시 금천구 시흥대로151길 46 (독산동)
4th row서울특별시 금천구 시흥대로39길 16 (시흥동)
5th row서울특별시 금천구 범안로 1239 (독산동)
ValueCountFrequency (%)
금천구 134
 
17.1%
서울특별시 130
 
16.6%
독산동 70
 
8.9%
가산동 29
 
3.7%
시흥동 17
 
2.2%
1층 14
 
1.8%
벚꽃로 9
 
1.1%
범안로21길 8
 
1.0%
14 7
 
0.9%
지하1층 7
 
0.9%
Other values (206) 360
45.9%
2024-05-11T15:20:00.382555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
655
 
15.9%
1 224
 
5.5%
시 182
 
4.4%
산 158
 
3.8%
) 141
 
3.4%
( 141
 
3.4%
금 140
 
3.4%
동 137
 
3.3%
천 137
 
3.3%
구 137
 
3.3%
Other values (113) 2055
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2377
57.9%
Decimal Number 669
 
16.3%
Space Separator 655
 
15.9%
Close Punctuation 141
 
3.4%
Open Punctuation 141
 
3.4%
Other Punctuation 92
 
2.2%
Dash Punctuation 15
 
0.4%
Uppercase Letter 13
 
0.3%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 182
 
7.7%
산 158
 
6.6%
금 140
 
5.9%
동 137
 
5.8%
천 137
 
5.8%
구 137
 
5.8%
서 136
 
5.7%
울 134
 
5.6%
별 134
 
5.6%
특 134
 
5.6%
Other values (92) 948
39.9%
Decimal Number
ValueCountFrequency (%)
1 224
33.5%
2 93
13.9%
3 60
 
9.0%
4 57
 
8.5%
6 45
 
6.7%
0 44
 
6.6%
5 43
 
6.4%
8 36
 
5.4%
9 35
 
5.2%
7 32
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
61.5%
C 2
 
15.4%
A 2
 
15.4%
Y 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 91
98.9%
? 1
 
1.1%
Space Separator
ValueCountFrequency (%)
655
100.0%
Close Punctuation
ValueCountFrequency (%)
) 141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2377
57.9%
Common 1717
41.8%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 182
 
7.7%
산 158
 
6.6%
금 140
 
5.9%
동 137
 
5.8%
천 137
 
5.8%
구 137
 
5.8%
서 136
 
5.7%
울 134
 
5.6%
별 134
 
5.6%
특 134
 
5.6%
Other values (92) 948
39.9%
Common
ValueCountFrequency (%)
655
38.1%
1 224
 
13.0%
) 141
 
8.2%
( 141
 
8.2%
2 93
 
5.4%
, 91
 
5.3%
3 60
 
3.5%
4 57
 
3.3%
6 45
 
2.6%
0 44
 
2.6%
Other values (7) 166
 
9.7%
Latin
ValueCountFrequency (%)
B 8
61.5%
C 2
 
15.4%
A 2
 
15.4%
Y 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2377
57.9%
ASCII 1730
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
655
37.9%
1 224
 
12.9%
) 141
 
8.2%
( 141
 
8.2%
2 93
 
5.4%
, 91
 
5.3%
3 60
 
3.5%
4 57
 
3.3%
6 45
 
2.6%
0 44
 
2.5%
Other values (11) 179
 
10.3%
Hangul
ValueCountFrequency (%)
시 182
 
7.7%
산 158
 
6.6%
금 140
 
5.9%
동 137
 
5.8%
천 137
 
5.8%
구 137
 
5.8%
서 136
 
5.7%
울 134
 
5.6%
별 134
 
5.6%
특 134
 
5.6%
Other values (92) 948
39.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)45.9%
Missing45
Missing (%)34.6%
Infinite0
Infinite (%)0.0%
Mean8569.3176
Minimum8501
Maximum8654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:20:00.602619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8501
5-th percentile8513
Q18524
median8585
Q38601
95-th percentile8633.6
Maximum8654
Range153
Interquartile range (IQR)77

Descriptive statistics

Standard deviation41.022993
Coefficient of variation (CV)0.0047871949
Kurtosis-1.2298031
Mean8569.3176
Median Absolute Deviation (MAD)29
Skewness-0.13328432
Sum728392
Variance1682.886
MonotonicityNot monotonic
2024-05-11T15:20:00.814456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
8585 11
 
8.5%
8524 6
 
4.6%
8604 5
 
3.8%
8513 5
 
3.8%
8526 5
 
3.8%
8584 4
 
3.1%
8586 4
 
3.1%
8603 3
 
2.3%
8592 3
 
2.3%
8521 3
 
2.3%
Other values (29) 36
27.7%
(Missing) 45
34.6%
ValueCountFrequency (%)
8501 1
 
0.8%
8504 1
 
0.8%
8506 1
 
0.8%
8508 1
 
0.8%
8513 5
3.8%
8515 1
 
0.8%
8517 2
 
1.5%
8518 1
 
0.8%
8521 3
2.3%
8524 6
4.6%
ValueCountFrequency (%)
8654 1
 
0.8%
8636 1
 
0.8%
8634 3
2.3%
8632 2
 
1.5%
8628 1
 
0.8%
8620 1
 
0.8%
8615 1
 
0.8%
8614 1
 
0.8%
8604 5
3.8%
8603 3
2.3%

사업장명
Text

Distinct122
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:20:01.318703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length6.7
Min length3

Characters and Unicode

Total characters871
Distinct characters199
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

Unique114 ?
Unique (%)87.7%

Sample

1st row(주)효림농축
2nd row번영유통
3rd row광원식품
4th row설인식품
5th row돈아돈아
ValueCountFrequency (%)
주식회사 12
 
7.5%
농업회사법인 3
 
1.9%
에이스뉴식품 3
 
1.9%
청정나라 2
 
1.3%
푸드 2
 
1.3%
막창골돈순대 2
 
1.3%
설인식품 2
 
1.3%
리베로인터내셔날(주 2
 
1.3%
주)신양축산유통 2
 
1.3%
강원 2
 
1.3%
Other values (124) 127
79.9%
2024-05-11T15:20:02.149438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 57
 
6.5%
) 43
 
4.9%
( 43
 
4.9%
식 37
 
4.2%
29
 
3.3%
드 29
 
3.3%
푸 24
 
2.8%
이 23
 
2.6%
품 22
 
2.5%
유 19
 
2.2%
Other values (189) 545
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 730
83.8%
Close Punctuation 43
 
4.9%
Open Punctuation 43
 
4.9%
Space Separator 29
 
3.3%
Uppercase Letter 18
 
2.1%
Lowercase Letter 3
 
0.3%
Other Punctuation 2
 
0.2%
Decimal Number 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 57
 
7.8%
식 37
 
5.1%
드 29
 
4.0%
푸 24
 
3.3%
이 23
 
3.2%
품 22
 
3.0%
유 19
 
2.6%
통 18
 
2.5%
사 18
 
2.5%
회 17
 
2.3%
Other values (170) 466
63.8%
Uppercase Letter
ValueCountFrequency (%)
F 6
33.3%
O 3
16.7%
C 2
 
11.1%
M 1
 
5.6%
I 1
 
5.6%
E 1
 
5.6%
D 1
 
5.6%
B 1
 
5.6%
S 1
 
5.6%
A 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
o 2
66.7%
d 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 730
83.8%
Common 120
 
13.8%
Latin 21
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 57
 
7.8%
식 37
 
5.1%
드 29
 
4.0%
푸 24
 
3.3%
이 23
 
3.2%
품 22
 
3.0%
유 19
 
2.6%
통 18
 
2.5%
사 18
 
2.5%
회 17
 
2.3%
Other values (170) 466
63.8%
Latin
ValueCountFrequency (%)
F 6
28.6%
O 3
14.3%
o 2
 
9.5%
C 2
 
9.5%
M 1
 
4.8%
I 1
 
4.8%
E 1
 
4.8%
D 1
 
4.8%
B 1
 
4.8%
S 1
 
4.8%
Other values (2) 2
 
9.5%
Common
ValueCountFrequency (%)
) 43
35.8%
( 43
35.8%
29
24.2%
& 2
 
1.7%
2 1
 
0.8%
7 1
 
0.8%
- 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 730
83.8%
ASCII 141
 
16.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 57
 
7.8%
식 37
 
5.1%
드 29
 
4.0%
푸 24
 
3.3%
이 23
 
3.2%
품 22
 
3.0%
유 19
 
2.6%
통 18
 
2.5%
사 18
 
2.5%
회 17
 
2.3%
Other values (170) 466
63.8%
ASCII
ValueCountFrequency (%)
) 43
30.5%
( 43
30.5%
29
20.6%
F 6
 
4.3%
O 3
 
2.1%
& 2
 
1.4%
o 2
 
1.4%
C 2
 
1.4%
M 1
 
0.7%
I 1
 
0.7%
Other values (9) 9
 
6.4%

최종수정일자
Date

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2004-06-30 14:38:08
Maximum2024-04-25 17:46:09
2024-05-11T15:20:02.415906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:02.657532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
U
91 
I
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 91
70.0%
I 39
30.0%

Length

2024-05-11T15:20:03.257612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:03.433423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 91
70.0%
i 39
30.0%

데이터갱신일자
Date

Distinct68
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:07:00
2024-05-11T15:20:03.648165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:03.922786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
식육가공업
124 
유가공업
 
4
알가공업
 
2

Length

Max length5
Median length5
Mean length4.9538462
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 124
95.4%
유가공업 4
 
3.1%
알가공업 2
 
1.5%

Length

2024-05-11T15:20:04.196842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:04.386759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 124
95.4%
유가공업 4
 
3.1%
알가공업 2
 
1.5%

좌표정보(X)
Real number (ℝ)

Distinct91
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190530.23
Minimum188979.23
Maximum192140.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:20:04.625323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188979.23
5-th percentile189624.86
Q1190211.31
median190623.23
Q3190775.97
95-th percentile191325.98
Maximum192140.31
Range3161.0881
Interquartile range (IQR)564.6509

Descriptive statistics

Standard deviation528.75904
Coefficient of variation (CV)0.0027751976
Kurtosis0.68054129
Mean190530.23
Median Absolute Deviation (MAD)335.96634
Skewness-0.38127501
Sum24768930
Variance279586.12
MonotonicityNot monotonic
2024-05-11T15:20:04.954672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191026.637157812 5
 
3.8%
190641.951025262 4
 
3.1%
190735.202947348 4
 
3.1%
189855.309927286 3
 
2.3%
189972.552916449 3
 
2.3%
190287.265818567 3
 
2.3%
190739.936380206 3
 
2.3%
189686.475000033 3
 
2.3%
190744.536066955 2
 
1.5%
190998.785108578 2
 
1.5%
Other values (81) 98
75.4%
ValueCountFrequency (%)
188979.225789508 1
 
0.8%
189089.927764903 1
 
0.8%
189232.30642848 1
 
0.8%
189372.263026296 1
 
0.8%
189522.336721798 1
 
0.8%
189537.204992731 1
 
0.8%
189574.452264019 1
 
0.8%
189686.475000033 3
2.3%
189691.858978981 2
1.5%
189758.612470019 1
 
0.8%
ValueCountFrequency (%)
192140.313893951 1
0.8%
191756.343265715 1
0.8%
191415.30250909 2
1.5%
191373.898531534 1
0.8%
191343.258866153 2
1.5%
191304.860335391 1
0.8%
191282.305189152 1
0.8%
191156.22947938 1
0.8%
191148.03144045 1
0.8%
191139.10742573 1
0.8%

좌표정보(Y)
Real number (ℝ)

Distinct91
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440681.06
Minimum436946.36
Maximum442569.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:20:05.188928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436946.36
5-th percentile438701.21
Q1440453.87
median440793.93
Q3441238.75
95-th percentile441975.8
Maximum442569.3
Range5622.942
Interquartile range (IQR)784.87703

Descriptive statistics

Standard deviation1012.0746
Coefficient of variation (CV)0.0022966148
Kurtosis2.2599079
Mean440681.06
Median Absolute Deviation (MAD)373.5412
Skewness-1.2350965
Sum57288538
Variance1024295
MonotonicityNot monotonic
2024-05-11T15:20:05.421705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
438701.205634976 5
 
3.8%
440592.30478192 4
 
3.1%
440588.586890064 4
 
3.1%
441540.894601732 3
 
2.3%
441080.376788547 3
 
2.3%
441289.191201814 3
 
2.3%
441067.923407233 3
 
2.3%
440870.092608694 3
 
2.3%
440333.908681771 2
 
1.5%
439029.823242263 2
 
1.5%
Other values (81) 98
75.4%
ValueCountFrequency (%)
436946.358720615 2
 
1.5%
438356.170313032 1
 
0.8%
438390.455865698 1
 
0.8%
438501.776187315 1
 
0.8%
438693.72165701 1
 
0.8%
438701.205634976 5
3.8%
438878.890260179 1
 
0.8%
439017.110637925 2
 
1.5%
439029.823242263 2
 
1.5%
439155.134354676 1
 
0.8%
ValueCountFrequency (%)
442569.300676147 1
0.8%
442478.356256941 1
0.8%
442449.739120109 1
0.8%
442354.304734197 2
1.5%
442283.3264104 1
0.8%
442035.622560657 1
0.8%
441902.681311108 1
0.8%
441725.583245474 2
1.5%
441711.686804011 1
0.8%
441699.385300487 2
1.5%

축산업무구분명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
축산물가공업
89 
<NA>
41 

Length

Max length6
Median length6
Mean length5.3692308
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 89
68.5%
<NA> 41
31.5%

Length

2024-05-11T15:20:05.691975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:05.903195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 89
68.5%
na 41
31.5%

축산물가공업구분명
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
식육가공업
85 
<NA>
41 
유가공업
 
3
알가공업
 
1

Length

Max length5
Median length5
Mean length4.6538462
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 85
65.4%
<NA> 41
31.5%
유가공업 3
 
2.3%
알가공업 1
 
0.8%

Length

2024-05-11T15:20:06.099019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:06.302744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 85
65.4%
na 41
31.5%
유가공업 3
 
2.3%
알가공업 1
 
0.8%

축산일련번호
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
113 
0
17 

Length

Max length4
Median length4
Mean length3.6076923
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> 113
86.9%
0 17
 
13.1%

Length

2024-05-11T15:20:06.521239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:06.726447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
86.9%
0 17
 
13.1%

권리주체일련번호
Categorical

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
000
58 
<NA>
41 
L00
31 

Length

Max length4
Median length3
Mean length3.3153846
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row000
2nd row<NA>
3rd row000
4th row000
5th row000

Common Values

ValueCountFrequency (%)
000 58
44.6%
<NA> 41
31.5%
L00 31
23.8%

Length

2024-05-11T15:20:06.910484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:07.126736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 58
44.6%
na 41
31.5%
l00 31
23.8%

총인원
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
113 
0
17 

Length

Max length4
Median length4
Mean length3.6076923
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> 113
86.9%
0 17
 
13.1%

Length

2024-05-11T15:20:07.355992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:07.551138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
86.9%
0 17
 
13.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0317000031700000041994000119940913<NA>3폐업2폐업20190424<NA><NA>20190424<NA>0.0<NA>서울특별시 금천구 독산동 331-40번지서울특별시 금천구 범안로 1189 (독산동)<NA>(주)효림농축2019-04-24 17:51:43U2019-04-26 02:40:00.0식육가공업190543.280013440511.573358축산물가공업식육가공업<NA>000<NA>
1317000031700000041998000119980529<NA>4취소/말소/만료/정지/중지4말소20220429<NA><NA><NA>805-76440.0<NA>서울특별시 금천구 독산동 331-59서울특별시 금천구 범안로15길 14 (독산동)<NA>번영유통2022-04-29 09:11:06U2021-12-05 00:03:00.0식육가공업190489.654581440569.045196<NA><NA><NA><NA><NA>
2317000031700000041998000219980922<NA>3폐업2폐업20080826<NA><NA><NA>839-96760.0<NA>서울특별시 금천구 독산동 144-30번지서울특별시 금천구 시흥대로151길 46 (독산동)<NA>광원식품2008-08-26 17:24:40I2018-08-31 23:59:59.0식육가공업190783.126126441598.460764축산물가공업식육가공업<NA>000<NA>
3317000031700000041998000319981215<NA>3폐업2폐업20040630<NA><NA><NA>893-64000.0<NA>서울특별시 금천구 시흥동 985-1번지서울특별시 금천구 시흥대로39길 16 (시흥동)<NA>설인식품2004-06-30 14:38:08I2018-08-31 23:59:59.0식육가공업191282.305189438356.170313축산물가공업식육가공업<NA>000<NA>
4317000031700000042000000120000330<NA>4취소/말소/만료/정지/중지4말소<NA><NA><NA><NA>838-77030.0<NA>서울특별시 금천구 독산동 1027-18번지서울특별시 금천구 범안로 1239 (독산동)8580돈아돈아2014-07-16 09:39:33I2018-08-31 23:59:59.0식육가공업191041.796152440503.475513축산물가공업식육가공업<NA>000<NA>
5317000031700000042000000220000711<NA>3폐업2폐업20190417<NA><NA>20190417807-39130.0<NA>서울특별시 금천구 독산동 293-4번지서울특별시 금천구 범안로21길 19 (독산동)<NA>(주)대용축산2019-04-17 16:14:09U2019-04-19 02:40:00.0식육가공업190735.202947440588.58689축산물가공업식육가공업<NA>L00<NA>
6317000031700000042000000320000904<NA>3폐업2폐업20040729<NA><NA><NA>854-76100.0<NA>서울특별시 금천구 독산동 1021-1번지서울특별시 금천구 독산로74길 16 (독산동)<NA>농장축산유통2004-07-29 09:47:15I2018-08-31 23:59:59.0식육가공업191373.898532440716.41268축산물가공업식육가공업<NA>000<NA>
7317000031700000042001000120011113<NA>3폐업2폐업20180126<NA><NA>20180126894-32560.0<NA>서울특별시 금천구 독산동 331-44번지서울특별시 금천구 범안로15길 8 (독산동)<NA>(주)그린로지텍2018-01-26 10:40:05I2018-08-31 23:59:59.0식육가공업190492.917874440537.518197축산물가공업식육가공업<NA>000<NA>
8317000031700000042002000120020408<NA>4취소/말소/만료/정지/중지4말소20220422<NA><NA><NA><NA>0.0<NA>서울특별시 금천구 시흥동 979-1서울특별시 금천구 시흥대로2길 8 (시흥동, 대아약국)8654한우리식품2022-04-22 13:08:42U2021-12-03 22:04:00.0식육가공업191415.302509436946.358721<NA><NA><NA><NA><NA>
9317000031700000042002000220020829<NA>4취소/말소/만료/정지/중지4말소20220429<NA><NA><NA><NA>0.0<NA>서울특별시 금천구 가산동 151-36서울특별시 금천구 가산로 122 (가산동)8529대도물류(주)2022-04-29 09:14:25U2021-12-05 00:03:00.0식육가공업190457.772818441601.325701<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
120317000031700000042021000220210414<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 가산동 345-34서울특별시 금천구 서부샛길 468, 1층 (가산동)8588환푸드F&B2021-04-14 09:04:24I2021-04-16 00:22:57.0식육가공업189372.263026441319.717856축산물가공업식육가공업<NA>000<NA>
121317000031700000042021000320210603<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 가산동 219-6 에이스 하이엔드타워 클래식 지식산업센터서울특별시 금천구 벚꽃로24길 26, 에이스 하이엔드타워 클래식 지식산업센터 1층 108호 (가산동)8517케이에스 앤 푸드2021-07-15 14:17:07U2021-07-17 02:40:00.0식육가공업190089.848501441320.867321축산물가공업식육가공업00000
12231700003170000004202100042021-10-05<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 독산동 293-9서울특별시 금천구 범안로19길 26, 1층, 지하1층 (독산동)8585주식회사 보경미트2023-05-24 15:51:21U2022-12-04 22:06:00.0식육가공업190702.92629440624.758875<NA><NA><NA><NA><NA>
123317000031700000042021000520211101<NA>3폐업2폐업20221111<NA><NA>2022111102-6952-12320.0<NA>서울특별시 금천구 독산동 299-55서울특별시 금천구 두산로13길 31, 1층 (독산동)8524홍언니고기 푸드2022-11-11 13:19:44U2021-10-31 23:03:00.0식육가공업190614.189128441054.793434<NA><NA><NA><NA><NA>
124317000031700000042021000620210526<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 가산동 327-32 대륭테크노타운12차서울특별시 금천구 가산디지털2로 14, 대륭테크노타운12차 B1층 117호 (가산동)8592육수온2021-11-17 14:07:08I2021-11-19 00:22:44.0식육가공업189686.475440870.092609축산물가공업식육가공업00000
12531700003170000004202100072021-11-18<NA>3폐업2폐업2024-04-25<NA><NA>2024-04-25<NA>0.0<NA>서울특별시 금천구 가산동 327-32 대륭테크노타운12차서울특별시 금천구 가산디지털2로 14, 대륭테크노타운12차 B2층 205호 (가산동)8592(주)케이제이푸드2024-04-25 17:46:09U2023-12-03 22:07:00.0식육가공업189686.475440870.092609<NA><NA><NA><NA><NA>
12631700003170000004202200012022-01-13<NA>3폐업2폐업2023-10-11<NA><NA>2023-10-11<NA>0.0<NA>서울특별시 금천구 독산동 336-23서울특별시 금천구 벚꽃로 190, 4층 (독산동)8526썸푸드(SOMEFOOD)2023-10-20 14:00:28U2022-10-30 22:02:00.0식육가공업189972.552916441080.376789<NA><NA><NA><NA><NA>
127317000031700000042022000220220719<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 가산동 60-25 에이스하이엔드타워6차서울특별시 금천구 벚꽃로 234, 에이스하이엔드타워6차 B103~B104호 (가산동)8513주식회사 에이스뉴식품2022-07-19 09:19:22I2021-12-06 22:01:00.0알가공업189855.309927441540.894602<NA><NA><NA><NA><NA>
128317000031700000042022000320221108<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 금천구 시흥동 995-19서울특별시 금천구 시흥대로59길 30, 1층 104호 (시흥동)8632족이당2022-11-08 09:46:52I2021-10-31 23:00:00.0식육가공업190998.785109439029.823242<NA><NA><NA><NA><NA>
12931700003170000004202300012023-12-28<NA>1영업/정상0정상<NA><NA><NA><NA><NA>8503.0<NA>서울특별시 금천구 가산동 60-73 벽산디지털밸리5차 512호서울특별시 금천구 벚꽃로 244, 벽산디지털밸리5차 512호 (가산동)8513클로버 에프엔비2023-12-28 13:54:15I2022-11-01 21:00:00.0유가공업189829.504143441618.071647<NA><NA><NA><NA><NA>