Overview

Dataset statistics

Number of variables30
Number of observations51
Missing cells273
Missing cells (%)17.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.9 KiB
Average record size in memory258.6 B

Variable types

Categorical14
Numeric5
DateTime3
Unsupported4
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18142/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (82.5%)Imbalance
휴업종료일자 is highly imbalanced (86.1%)Imbalance
축산일련번호 is highly imbalanced (76.1%)Imbalance
총인원 is highly imbalanced (76.1%)Imbalance
인허가취소일자 has 51 (100.0%) missing valuesMissing
폐업일자 has 16 (31.4%) missing valuesMissing
재개업일자 has 51 (100.0%) missing valuesMissing
전화번호 has 18 (35.3%) missing valuesMissing
소재지우편번호 has 51 (100.0%) missing valuesMissing
도로명주소 has 4 (7.8%) missing valuesMissing
도로명우편번호 has 25 (49.0%) missing valuesMissing
업태구분명 has 51 (100.0%) missing valuesMissing
좌표정보(X) has 3 (5.9%) missing valuesMissing
좌표정보(Y) has 3 (5.9%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 30 (58.8%) zerosZeros

Reproduction

Analysis started2024-05-11 01:45:02.954892
Analysis finished2024-05-11 01:45:03.778509
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
3150000
51 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 51
100.0%

Length

2024-05-11T01:45:03.952128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:04.282473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 51
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1500001 × 1017
Minimum3.15 × 1017
Maximum3.1500001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-05-11T01:45:04.882567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.15 × 1017
5-th percentile3.15 × 1017
Q13.15 × 1017
median3.15 × 1017
Q33.1500001 × 1017
95-th percentile3.1500001 × 1017
Maximum3.1500001 × 1017
Range1.000018 × 1010
Interquartile range (IQR)1.00001 × 1010

Descriptive statistics

Standard deviation5.0488326 × 109
Coefficient of variation (CV)1.602804 × 10-8
Kurtosis-2.0816327
Mean3.1500001 × 1017
Median Absolute Deviation (MAD)49984
Skewness0.040421941
Sum-2.3817438 × 1018
Variance2.5490711 × 1019
MonotonicityStrictly increasing
2024-05-11T01:45:05.536207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
315000000420040003 1
 
2.0%
315000000420040004 1
 
2.0%
315000010420100003 1
 
2.0%
315000010420110001 1
 
2.0%
315000010420110002 1
 
2.0%
315000010420120001 1
 
2.0%
315000010420120002 1
 
2.0%
315000010420120003 1
 
2.0%
315000010420120004 1
 
2.0%
315000010420130001 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
315000000420040003 1
2.0%
315000000420040004 1
2.0%
315000000420040005 1
2.0%
315000000420040006 1
2.0%
315000000420040007 1
2.0%
315000000420040008 1
2.0%
315000000420040009 1
2.0%
315000000420040010 1
2.0%
315000000420040011 1
2.0%
315000000420040012 1
2.0%
ValueCountFrequency (%)
315000010420220004 1
2.0%
315000010420220003 1
2.0%
315000010420220002 1
2.0%
315000010420220001 1
2.0%
315000010420210001 1
2.0%
315000010420200001 1
2.0%
315000010420190002 1
2.0%
315000010420190001 1
2.0%
315000010420160002 1
2.0%
315000010420160001 1
2.0%

인허가일자
Date

Distinct38
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2004-09-13 00:00:00
Maximum2022-12-12 00:00:00
2024-05-11T01:45:05.946166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:45:06.355405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

영업상태코드
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
3
34 
1
13 
4
 
2
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 34
66.7%
1 13
 
25.5%
4 2
 
3.9%
2 2
 
3.9%

Length

2024-05-11T01:45:06.830967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:07.223595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 34
66.7%
1 13
 
25.5%
4 2
 
3.9%
2 2
 
3.9%

영업상태명
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
폐업
34 
영업/정상
13 
취소/말소/만료/정지/중지
 
2
휴업
 
2

Length

Max length14
Median length2
Mean length3.2352941
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 34
66.7%
영업/정상 13
 
25.5%
취소/말소/만료/정지/중지 2
 
3.9%
휴업 2
 
3.9%

Length

2024-05-11T01:45:07.743500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:08.190928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 34
66.7%
영업/정상 13
 
25.5%
취소/말소/만료/정지/중지 2
 
3.9%
휴업 2
 
3.9%

상세영업상태코드
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
2
34 
0
13 
4
 
2
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 34
66.7%
0 13
 
25.5%
4 2
 
3.9%
1 2
 
3.9%

Length

2024-05-11T01:45:08.573107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:08.879855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 34
66.7%
0 13
 
25.5%
4 2
 
3.9%
1 2
 
3.9%

상세영업상태명
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
폐업
34 
정상
13 
말소
 
2
휴업
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 34
66.7%
정상 13
 
25.5%
말소 2
 
3.9%
휴업 2
 
3.9%

Length

2024-05-11T01:45:09.262448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:09.609847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 34
66.7%
정상 13
 
25.5%
말소 2
 
3.9%
휴업 2
 
3.9%

폐업일자
Date

MISSING 

Distinct35
Distinct (%)100.0%
Missing16
Missing (%)31.4%
Memory size540.0 B
Minimum2005-06-02 00:00:00
Maximum2023-12-18 00:00:00
2024-05-11T01:45:09.969951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:45:10.417797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
<NA>
49 
20200818
 
1
20200723
 
1

Length

Max length8
Median length4
Mean length4.1568627
Min length4

Unique

Unique2 ?
Unique (%)3.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 49
96.1%
20200818 1
 
2.0%
20200723 1
 
2.0%

Length

2024-05-11T01:45:10.873568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:11.304158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
96.1%
20200818 1
 
2.0%
20200723 1
 
2.0%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
<NA>
50 
20201230
 
1

Length

Max length8
Median length4
Mean length4.0784314
Min length4

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
98.0%
20201230 1
 
2.0%

Length

2024-05-11T01:45:11.834532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:12.220485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
98.0%
20201230 1
 
2.0%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

전화번호
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing18
Missing (%)35.3%
Memory size540.0 B
2024-05-11T01:45:12.679672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9.6363636
Min length8

Characters and Unicode

Total characters318
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

Unique33 ?
Unique (%)100.0%

Sample

1st row2693-7116
2nd row3661-2760
3rd row2666-106
4th row2654-9293
5th row2662-8264
ValueCountFrequency (%)
2657-7153 1
 
3.0%
2666-9454 1
 
3.0%
02-2644-4933 1
 
3.0%
0226638881 1
 
3.0%
2663-9884 1
 
3.0%
2662-1999 1
 
3.0%
2665-7773 1
 
3.0%
2640-6240 1
 
3.0%
2668-2018 1
 
3.0%
070-8659-2759 1
 
3.0%
Other values (23) 23
69.7%
2024-05-11T01:45:13.632146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 61
19.2%
2 54
17.0%
- 39
12.3%
0 28
8.8%
3 25
7.9%
4 25
7.9%
8 19
 
6.0%
1 18
 
5.7%
9 17
 
5.3%
5 16
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 279
87.7%
Dash Punctuation 39
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 61
21.9%
2 54
19.4%
0 28
10.0%
3 25
9.0%
4 25
9.0%
8 19
 
6.8%
1 18
 
6.5%
9 17
 
6.1%
5 16
 
5.7%
7 16
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 61
19.2%
2 54
17.0%
- 39
12.3%
0 28
8.8%
3 25
7.9%
4 25
7.9%
8 19
 
6.0%
1 18
 
5.7%
9 17
 
5.3%
5 16
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 61
19.2%
2 54
17.0%
- 39
12.3%
0 28
8.8%
3 25
7.9%
4 25
7.9%
8 19
 
6.0%
1 18
 
5.7%
9 17
 
5.3%
5 16
 
5.0%

소재지면적
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.888235
Minimum0
Maximum429.74
Zeros30
Zeros (%)58.8%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-05-11T01:45:14.017394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q370.64
95-th percentile204.325
Maximum429.74
Range429.74
Interquartile range (IQR)70.64

Descriptive statistics

Standard deviation90.62562
Coefficient of variation (CV)1.7135308
Kurtosis6.208761
Mean52.888235
Median Absolute Deviation (MAD)0
Skewness2.3348731
Sum2697.3
Variance8213.003
MonotonicityNot monotonic
2024-05-11T01:45:14.366843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 30
58.8%
169.0 1
 
2.0%
330.0 1
 
2.0%
142.0 1
 
2.0%
64.0 1
 
2.0%
94.8 1
 
2.0%
77.28 1
 
2.0%
119.31 1
 
2.0%
142.83 1
 
2.0%
42.18 1
 
2.0%
Other values (12) 12
 
23.5%
ValueCountFrequency (%)
0.0 30
58.8%
29.48 1
 
2.0%
37.8 1
 
2.0%
40.02 1
 
2.0%
42.18 1
 
2.0%
47.55 1
 
2.0%
49.91 1
 
2.0%
53.7 1
 
2.0%
64.0 1
 
2.0%
77.28 1
 
2.0%
ValueCountFrequency (%)
429.74 1
2.0%
330.0 1
2.0%
234.0 1
2.0%
174.65 1
2.0%
169.0 1
2.0%
149.94 1
2.0%
142.83 1
2.0%
142.0 1
2.0%
139.48 1
2.0%
129.63 1
2.0%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

지번주소
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-05-11T01:45:15.073202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length25.901961
Min length14

Characters and Unicode

Total characters1321
Distinct characters90
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row서울특별시 강서구 화곡동 886-20번지
2nd row서울특별시 강서구 가양동 194-2 번지
3rd row서울특별시 강서구 내발산동 700번지 지층
4th row서울특별시 강서구 화곡동 797-1번지
5th row서울특별시 강서구 방화동 564-85번지
ValueCountFrequency (%)
서울특별시 51
20.5%
강서구 51
20.5%
방화동 16
 
6.4%
1층 13
 
5.2%
화곡동 12
 
4.8%
등촌동 7
 
2.8%
공항동 4
 
1.6%
내발산동 4
 
1.6%
631-5 3
 
1.2%
외발산동 3
 
1.2%
Other values (73) 85
34.1%
2024-05-11T01:45:16.410183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
18.3%
서 107
 
8.1%
1 65
 
4.9%
울 55
 
4.2%
동 53
 
4.0%
시 52
 
3.9%
강 52
 
3.9%
특 51
 
3.9%
별 51
 
3.9%
구 51
 
3.9%
Other values (80) 542
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 764
57.8%
Decimal Number 258
 
19.5%
Space Separator 242
 
18.3%
Dash Punctuation 44
 
3.3%
Uppercase Letter 11
 
0.8%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 107
14.0%
울 55
 
7.2%
동 53
 
6.9%
시 52
 
6.8%
강 52
 
6.8%
특 51
 
6.7%
별 51
 
6.7%
구 51
 
6.7%
지 40
 
5.2%
번 35
 
4.6%
Other values (64) 217
28.4%
Decimal Number
ValueCountFrequency (%)
1 65
25.2%
6 28
10.9%
3 28
10.9%
7 27
10.5%
5 25
 
9.7%
8 21
 
8.1%
4 20
 
7.8%
0 19
 
7.4%
2 16
 
6.2%
9 9
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
N 4
36.4%
H 4
36.4%
B 3
27.3%
Space Separator
ValueCountFrequency (%)
242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 764
57.8%
Common 546
41.3%
Latin 11
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 107
14.0%
울 55
 
7.2%
동 53
 
6.9%
시 52
 
6.8%
강 52
 
6.8%
특 51
 
6.7%
별 51
 
6.7%
구 51
 
6.7%
지 40
 
5.2%
번 35
 
4.6%
Other values (64) 217
28.4%
Common
ValueCountFrequency (%)
242
44.3%
1 65
 
11.9%
- 44
 
8.1%
6 28
 
5.1%
3 28
 
5.1%
7 27
 
4.9%
5 25
 
4.6%
8 21
 
3.8%
4 20
 
3.7%
0 19
 
3.5%
Other values (3) 27
 
4.9%
Latin
ValueCountFrequency (%)
N 4
36.4%
H 4
36.4%
B 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 764
57.8%
ASCII 557
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
43.4%
1 65
 
11.7%
- 44
 
7.9%
6 28
 
5.0%
3 28
 
5.0%
7 27
 
4.8%
5 25
 
4.5%
8 21
 
3.8%
4 20
 
3.6%
0 19
 
3.4%
Other values (6) 38
 
6.8%
Hangul
ValueCountFrequency (%)
서 107
14.0%
울 55
 
7.2%
동 53
 
6.9%
시 52
 
6.8%
강 52
 
6.8%
특 51
 
6.7%
별 51
 
6.7%
구 51
 
6.7%
지 40
 
5.2%
번 35
 
4.6%
Other values (64) 217
28.4%

도로명주소
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing4
Missing (%)7.8%
Memory size540.0 B
2024-05-11T01:45:17.211715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length30.638298
Min length22

Characters and Unicode

Total characters1440
Distinct characters111
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row서울특별시 강서구 국회대로 159 (화곡동)
2nd row서울특별시 강서구 강서로47길 19 (내발산동,지층)
3rd row서울특별시 강서구 곰달래로57길 7 (화곡동)
4th row서울특별시 강서구 금낭화로 62 (방화동)
5th row서울특별시 강서구 양천로28길 13 (방화동)
ValueCountFrequency (%)
서울특별시 47
 
17.0%
강서구 47
 
17.0%
방화동 12
 
4.3%
화곡동 11
 
4.0%
1층 11
 
4.0%
등촌동 6
 
2.2%
양천로 5
 
1.8%
양천로18길 3
 
1.1%
지하1층 3
 
1.1%
570 3
 
1.1%
Other values (102) 129
46.6%
2024-05-11T01:45:18.488098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
230
 
16.0%
서 102
 
7.1%
1 58
 
4.0%
동 53
 
3.7%
강 51
 
3.5%
울 51
 
3.5%
시 48
 
3.3%
로 48
 
3.3%
( 47
 
3.3%
특 47
 
3.3%
Other values (101) 705
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 865
60.1%
Space Separator 230
 
16.0%
Decimal Number 204
 
14.2%
Open Punctuation 47
 
3.3%
Close Punctuation 47
 
3.3%
Other Punctuation 31
 
2.2%
Uppercase Letter 11
 
0.8%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 102
 
11.8%
동 53
 
6.1%
강 51
 
5.9%
울 51
 
5.9%
시 48
 
5.5%
로 48
 
5.5%
특 47
 
5.4%
별 47
 
5.4%
구 47
 
5.4%
화 40
 
4.6%
Other values (83) 331
38.3%
Decimal Number
ValueCountFrequency (%)
1 58
28.4%
5 27
13.2%
2 22
 
10.8%
3 17
 
8.3%
7 16
 
7.8%
8 15
 
7.4%
0 14
 
6.9%
9 12
 
5.9%
4 12
 
5.9%
6 11
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
H 4
36.4%
N 4
36.4%
B 3
27.3%
Space Separator
ValueCountFrequency (%)
230
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 865
60.1%
Common 564
39.2%
Latin 11
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 102
 
11.8%
동 53
 
6.1%
강 51
 
5.9%
울 51
 
5.9%
시 48
 
5.5%
로 48
 
5.5%
특 47
 
5.4%
별 47
 
5.4%
구 47
 
5.4%
화 40
 
4.6%
Other values (83) 331
38.3%
Common
ValueCountFrequency (%)
230
40.8%
1 58
 
10.3%
( 47
 
8.3%
) 47
 
8.3%
, 31
 
5.5%
5 27
 
4.8%
2 22
 
3.9%
3 17
 
3.0%
7 16
 
2.8%
8 15
 
2.7%
Other values (5) 54
 
9.6%
Latin
ValueCountFrequency (%)
H 4
36.4%
N 4
36.4%
B 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 865
60.1%
ASCII 575
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
230
40.0%
1 58
 
10.1%
( 47
 
8.2%
) 47
 
8.2%
, 31
 
5.4%
5 27
 
4.7%
2 22
 
3.8%
3 17
 
3.0%
7 16
 
2.8%
8 15
 
2.6%
Other values (8) 65
 
11.3%
Hangul
ValueCountFrequency (%)
서 102
 
11.8%
동 53
 
6.1%
강 51
 
5.9%
울 51
 
5.9%
시 48
 
5.5%
로 48
 
5.5%
특 47
 
5.4%
별 47
 
5.4%
구 47
 
5.4%
화 40
 
4.6%
Other values (83) 331
38.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)73.1%
Missing25
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean7628.5385
Minimum7516
Maximum7787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-05-11T01:45:19.312018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7516
5-th percentile7551
Q17559.5
median7613
Q37650
95-th percentile7756.75
Maximum7787
Range271
Interquartile range (IQR)90.5

Descriptive statistics

Standard deviation75.018521
Coefficient of variation (CV)0.009833931
Kurtosis-0.53307666
Mean7628.5385
Median Absolute Deviation (MAD)49
Skewness0.64202693
Sum198342
Variance5627.7785
MonotonicityNot monotonic
2024-05-11T01:45:20.001813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
7551 5
 
9.8%
7604 2
 
3.9%
7741 2
 
3.9%
7644 2
 
3.9%
7516 1
 
2.0%
7642 1
 
2.0%
7590 1
 
2.0%
7555 1
 
2.0%
7621 1
 
2.0%
7762 1
 
2.0%
Other values (9) 9
 
17.6%
(Missing) 25
49.0%
ValueCountFrequency (%)
7516 1
 
2.0%
7551 5
9.8%
7555 1
 
2.0%
7573 1
 
2.0%
7590 1
 
2.0%
7604 2
 
3.9%
7607 1
 
2.0%
7612 1
 
2.0%
7614 1
 
2.0%
7621 1
 
2.0%
ValueCountFrequency (%)
7787 1
2.0%
7762 1
2.0%
7741 2
3.9%
7721 1
2.0%
7716 1
2.0%
7652 1
2.0%
7644 2
3.9%
7642 1
2.0%
7641 1
2.0%
7621 1
2.0%

사업장명
Text

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-05-11T01:45:20.706917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length6.9411765
Min length2

Characters and Unicode

Total characters354
Distinct characters129
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)88.2%

Sample

1st row다우들
2nd row(주)미트밴
3rd row해드람
4th row방주유통
5th row마그마유통
ValueCountFrequency (%)
주)미트밴 2
 
3.4%
청계식품 2
 
3.4%
주식회사 2
 
3.4%
방주유통 2
 
3.4%
후드뱅크코리아 1
 
1.7%
본점 1
 
1.7%
주)희락 1
 
1.7%
신한길미트유통 1
 
1.7%
청풍명월조합공동사업법인 1
 
1.7%
서울지점 1
 
1.7%
Other values (45) 45
76.3%
2024-05-11T01:45:22.150674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 19
 
5.4%
( 15
 
4.2%
) 15
 
4.2%
축 12
 
3.4%
유 10
 
2.8%
트 10
 
2.8%
통 10
 
2.8%
미 9
 
2.5%
드 9
 
2.5%
8
 
2.3%
Other values (119) 237
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 304
85.9%
Open Punctuation 15
 
4.2%
Close Punctuation 15
 
4.2%
Decimal Number 12
 
3.4%
Space Separator 8
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 19
 
6.2%
축 12
 
3.9%
유 10
 
3.3%
트 10
 
3.3%
통 10
 
3.3%
미 9
 
3.0%
드 9
 
3.0%
산 8
 
2.6%
식 7
 
2.3%
푸 7
 
2.3%
Other values (107) 203
66.8%
Decimal Number
ValueCountFrequency (%)
3 2
16.7%
1 2
16.7%
8 2
16.7%
4 1
8.3%
0 1
8.3%
9 1
8.3%
2 1
8.3%
6 1
8.3%
7 1
8.3%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 304
85.9%
Common 50
 
14.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 19
 
6.2%
축 12
 
3.9%
유 10
 
3.3%
트 10
 
3.3%
통 10
 
3.3%
미 9
 
3.0%
드 9
 
3.0%
산 8
 
2.6%
식 7
 
2.3%
푸 7
 
2.3%
Other values (107) 203
66.8%
Common
ValueCountFrequency (%)
( 15
30.0%
) 15
30.0%
8
16.0%
3 2
 
4.0%
1 2
 
4.0%
8 2
 
4.0%
4 1
 
2.0%
0 1
 
2.0%
9 1
 
2.0%
2 1
 
2.0%
Other values (2) 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 304
85.9%
ASCII 50
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 19
 
6.2%
축 12
 
3.9%
유 10
 
3.3%
트 10
 
3.3%
통 10
 
3.3%
미 9
 
3.0%
드 9
 
3.0%
산 8
 
2.6%
식 7
 
2.3%
푸 7
 
2.3%
Other values (107) 203
66.8%
ASCII
ValueCountFrequency (%)
( 15
30.0%
) 15
30.0%
8
16.0%
3 2
 
4.0%
1 2
 
4.0%
8 2
 
4.0%
4 1
 
2.0%
0 1
 
2.0%
9 1
 
2.0%
2 1
 
2.0%
Other values (2) 2
 
4.0%

최종수정일자
Date

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2004-12-23 11:21:20
Maximum2023-12-18 15:17:54
2024-05-11T01:45:22.750687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:45:23.206899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
I
35 
U
16 

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 35
68.6%
U 16
31.4%

Length

2024-05-11T01:45:23.672591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:23.974023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 35
68.6%
u 16
31.4%

데이터갱신일자
Categorical

Distinct19
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Memory size540.0 B
2018-08-31 23:59:59.0
33 
2021-12-08 00:07:00.0
 
1
2019-04-04 02:40:00.0
 
1
2022-12-09 00:06:00.0
 
1
2019-03-31 02:40:00.0
 
1
Other values (14)
14 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique18 ?
Unique (%)35.3%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 33
64.7%
2021-12-08 00:07:00.0 1
 
2.0%
2019-04-04 02:40:00.0 1
 
2.0%
2022-12-09 00:06:00.0 1
 
2.0%
2019-03-31 02:40:00.0 1
 
2.0%
2019-06-29 02:40:00.0 1
 
2.0%
2022-12-07 23:09:00.0 1
 
2.0%
2022-10-30 23:03:00.0 1
 
2.0%
2020-12-24 02:40:00.0 1
 
2.0%
2022-12-04 00:01:00.0 1
 
2.0%
Other values (9) 9
 
17.6%

Length

2024-05-11T01:45:24.330381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 33
32.4%
23:59:59.0 33
32.4%
02:40:00.0 7
 
6.9%
2021-11-01 1
 
1.0%
22:02:00.0 1
 
1.0%
2022-11-30 1
 
1.0%
23:05:00.0 1
 
1.0%
2022-12-01 1
 
1.0%
2020-08-20 1
 
1.0%
2022-11-01 1
 
1.0%
Other values (22) 22
21.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)87.5%
Missing3
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean185211.47
Minimum182830.37
Maximum188844.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-05-11T01:45:24.655010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182830.37
5-th percentile182979.72
Q1183511.1
median184403.27
Q3186903.55
95-th percentile187845.61
Maximum188844.99
Range6014.6165
Interquartile range (IQR)3392.4562

Descriptive statistics

Standard deviation1868.0193
Coefficient of variation (CV)0.010085873
Kurtosis-1.2808121
Mean185211.47
Median Absolute Deviation (MAD)1186.3836
Skewness0.43426932
Sum8890150.5
Variance3489496.1
MonotonicityNot monotonic
2024-05-11T01:45:25.056947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
187727.758706201 3
 
5.9%
187845.607491496 2
 
3.9%
183439.821678848 2
 
3.9%
186903.554606002 2
 
3.9%
183311.359819791 2
 
3.9%
188844.987211885 1
 
2.0%
183214.010884834 1
 
2.0%
184148.571466974 1
 
2.0%
185566.38894215 1
 
2.0%
187701.852157255 1
 
2.0%
Other values (32) 32
62.7%
(Missing) 3
 
5.9%
ValueCountFrequency (%)
182830.370717987 1
2.0%
182910.321027025 1
2.0%
182912.435007001 1
2.0%
183104.683616607 1
2.0%
183117.281621173 1
2.0%
183214.010884834 1
2.0%
183311.359819791 2
3.9%
183398.86411064 1
2.0%
183439.821678848 2
3.9%
183449.691708771 1
2.0%
ValueCountFrequency (%)
188844.987211885 1
 
2.0%
188692.033242329 1
 
2.0%
187845.607491496 2
3.9%
187767.235792494 1
 
2.0%
187727.758706201 3
5.9%
187725.107808052 1
 
2.0%
187717.026139694 1
 
2.0%
187701.852157255 1
 
2.0%
186903.554606002 2
3.9%
186491.528412383 1
 
2.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)87.5%
Missing3
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean450346.77
Minimum447398.2
Maximum452423.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-05-11T01:45:25.560240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447398.2
5-th percentile447764.89
Q1449448.56
median450353.52
Q3451605.91
95-th percentile452265.82
Maximum452423.95
Range5025.7529
Interquartile range (IQR)2157.35

Descriptive statistics

Standard deviation1469.464
Coefficient of variation (CV)0.0032629612
Kurtosis-0.76265262
Mean450346.77
Median Absolute Deviation (MAD)1190.4108
Skewness-0.37973391
Sum21616645
Variance2159324.6
MonotonicityNot monotonic
2024-05-11T01:45:25.983721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
450500.126506809 3
 
5.9%
448071.203005256 2
 
3.9%
452244.255479429 2
 
3.9%
447398.196837221 2
 
3.9%
452096.514044913 2
 
3.9%
450059.462578835 1
 
2.0%
452423.949709228 1
 
2.0%
450166.360534543 1
 
2.0%
450307.59522532 1
 
2.0%
447815.251576342 1
 
2.0%
Other values (32) 32
62.7%
(Missing) 3
 
5.9%
ValueCountFrequency (%)
447398.196837221 2
3.9%
447737.778609237 1
2.0%
447815.251576342 1
2.0%
448071.203005256 2
3.9%
448312.700882575 1
2.0%
448562.567348407 1
2.0%
448920.021239558 1
2.0%
448970.111453654 1
2.0%
449172.117589125 1
2.0%
449353.127781049 1
2.0%
ValueCountFrequency (%)
452423.949709228 1
2.0%
452286.258452633 1
2.0%
452267.450544749 1
2.0%
452262.7871049 1
2.0%
452262.236128508 1
2.0%
452244.255479429 2
3.9%
452096.514044913 2
3.9%
452007.480315664 1
2.0%
451650.055066907 1
2.0%
451616.886688 1
2.0%

축산업무구분명
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
식육포장처리업
41 
<NA>
10 

Length

Max length7
Median length7
Mean length6.4117647
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 41
80.4%
<NA> 10
 
19.6%

Length

2024-05-11T01:45:26.386126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:26.804175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 41
80.4%
na 10
 
19.6%

축산물가공업구분명
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
식육포장처리업
41 
<NA>
10 

Length

Max length7
Median length7
Mean length6.4117647
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 41
80.4%
<NA> 10
 
19.6%

Length

2024-05-11T01:45:27.161855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:27.569241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 41
80.4%
na 10
 
19.6%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
<NA>
49 
0
 
2

Length

Max length4
Median length4
Mean length3.8823529
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> 49
96.1%
0 2
 
3.9%

Length

2024-05-11T01:45:28.081590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:28.480339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
96.1%
0 2
 
3.9%

권리주체일련번호
Categorical

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
000
25 
L00
16 
<NA>
10 

Length

Max length4
Median length3
Mean length3.1960784
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowL00
2nd rowL00
3rd row000
4th row000
5th row000

Common Values

ValueCountFrequency (%)
000 25
49.0%
L00 16
31.4%
<NA> 10
 
19.6%

Length

2024-05-11T01:45:28.850085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:29.196718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 25
49.0%
l00 16
31.4%
na 10
 
19.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
<NA>
49 
0
 
2

Length

Max length4
Median length4
Mean length3.8823529
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> 49
96.1%
0 2
 
3.9%

Length

2024-05-11T01:45:29.787132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:30.214931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
96.1%
0 2
 
3.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0315000031500000042004000320040913<NA>3폐업2폐업20110722<NA><NA><NA>2693-71160.0<NA>서울특별시 강서구 화곡동 886-20번지서울특별시 강서구 국회대로 159 (화곡동)<NA>다우들2011-07-22 15:41:36I2018-08-31 23:59:59.0<NA>186903.554606447398.196837식육포장처리업식육포장처리업<NA>L00<NA>
1315000031500000042004000420041222<NA>1영업/정상0정상<NA><NA><NA><NA>3661-27600.0<NA>서울특별시 강서구 가양동 194-2 번지<NA><NA>(주)미트밴2004-12-23 11:21:20I2018-08-31 23:59:59.0<NA><NA><NA>식육포장처리업식육포장처리업<NA>L00<NA>
2315000031500000042004000520041222<NA>3폐업2폐업20050602<NA><NA><NA>2666-1060.0<NA>서울특별시 강서구 내발산동 700번지 지층서울특별시 강서구 강서로47길 19 (내발산동,지층)<NA>해드람2005-06-02 13:57:16I2018-08-31 23:59:59.0<NA>185359.452822450031.249165식육포장처리업식육포장처리업<NA>000<NA>
3315000031500000042004000620041222<NA>3폐업2폐업20100913<NA><NA><NA>2654-92930.0<NA>서울특별시 강서구 화곡동 797-1번지서울특별시 강서구 곰달래로57길 7 (화곡동)<NA>방주유통2010-09-13 13:20:55I2018-08-31 23:59:59.0<NA>187701.852157447815.251576식육포장처리업식육포장처리업<NA>000<NA>
4315000031500000042004000720041222<NA>3폐업2폐업20130905<NA><NA><NA>2662-82640.0<NA>서울특별시 강서구 방화동 564-85번지서울특별시 강서구 금낭화로 62 (방화동)<NA>마그마유통2013-09-05 17:55:12I2018-08-31 23:59:59.0<NA>183311.35982452096.514045식육포장처리업식육포장처리업<NA>000<NA>
5315000031500000042004000820041222<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 등촌동 631-5 번지<NA><NA>서울축협단체급식가공센타2004-12-23 11:48:26I2018-08-31 23:59:59.0<NA><NA><NA>식육포장처리업식육포장처리업<NA>L00<NA>
6315000031500000042004000920041222<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 방화동 189-15 번지<NA><NA>청계식품2004-12-23 11:51:26I2018-08-31 23:59:59.0<NA><NA><NA>식육포장처리업식육포장처리업<NA>000<NA>
7315000031500000042004001020041222<NA>4취소/말소/만료/정지/중지4말소<NA><NA><NA><NA>2661-70500.0<NA>서울특별시 강서구 방화동 189-15번지서울특별시 강서구 양천로28길 13 (방화동)<NA>청계식품2016-03-09 11:43:49I2018-08-31 23:59:59.0<NA>184082.021734452262.787105식육포장처리업식육포장처리업<NA>000<NA>
8315000031500000042004001120041222<NA>3폐업2폐업20220805<NA><NA><NA><NA>53.7<NA>서울특별시 강서구 염창동 110-13서울특별시 강서구 양천로73길 56-5 (염창동)<NA>대원미트(1388147629)2022-08-05 15:42:40U2021-12-08 00:07:00.0<NA>188844.987212450059.462579<NA><NA><NA><NA><NA>
9315000031500000042004001220041222<NA>3폐업2폐업20070223<NA><NA><NA>2607-35880.0<NA>서울특별시 강서구 화곡동 1016-33번지서울특별시 강서구 화곡로13길 138 (화곡동)<NA>신손2007-02-23 15:24:33I2018-08-31 23:59:59.0<NA>185309.127346449172.117589식육포장처리업식육포장처리업<NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
4131500003150000104201600012016-04-15<NA>3폐업2폐업2023-03-30<NA><NA><NA>2666-36340.0<NA>서울특별시 강서구 방화동 575-20 1층서울특별시 강서구 양천로18길 15, 1층 (방화동)7604주식회사 축심푸드2023-03-29 11:32:04U2022-12-04 00:01:00.0<NA>183398.864111452286.258453<NA><NA><NA><NA><NA>
42315000031500001042016000220161220<NA>2휴업1휴업<NA>2020081820201230<NA>2601-824877.28<NA>서울특별시 강서구 화곡동 98-45 지층서울특별시 강서구 까치산로 35, 지층 (화곡동)7721자연축산2020-08-18 13:35:45U2020-08-20 02:40:00.0<NA>186156.455439448970.111454식육포장처리업식육포장처리업<NA>L00<NA>
4331500003150000104201900012019-05-23<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 화곡동 371-33 우성테마빌서울특별시 강서구 가로공원로 196, 102호 (화곡동, 우성테마빌)7762(주)미트302023-03-02 10:47:00U2022-12-03 00:04:00.0<NA>185586.777988448312.700883<NA><NA><NA><NA><NA>
44315000031500001042019000220130823<NA>2휴업1휴업<NA>20200723<NA><NA>2644-493394.8<NA>서울특별시 강서구 화곡동 772-71 신진통상빌딩서울특별시 강서구 등촌로 55, 신진통상빌딩 1층 (화곡동)7741(주)임박사2020-11-27 10:29:12U2020-11-29 02:40:00.0<NA>187845.607491448071.203005식육포장처리업식육포장처리업<NA>L00<NA>
45315000031500001042020000120200410<NA>3폐업2폐업20220119<NA><NA><NA><NA>64.0<NA>서울특별시 강서구 방화동 614-8 대희빌딩서울특별시 강서구 개화동로27길 55, 대희빌딩 1층 (방화동)7621임자축산물센터2022-01-19 13:47:45U2022-01-21 02:40:00.0<NA>183117.281621451398.804775식육포장처리업식육포장처리업00000
46315000031500001042021000120210727<NA>1영업/정상0정상<NA><NA><NA><NA><NA>142.0<NA>서울특별시 강서구 염창동 264-18 송촌스페이스향 1층1호서울특별시 강서구 공항대로71길 49, 1층 1호 (염창동, 송촌스페이스향)7555쏘킹인삼한우2021-07-27 13:40:13I2021-07-29 00:22:51.0<NA>188692.033242449699.832585식육포장처리업식육포장처리업0L000
4731500003150000104202200012022-04-07<NA>3폐업2폐업2023-12-18<NA><NA><NA>02-6094-79060.0<NA>서울특별시 강서구 등촌동 661-1 키모코리아빌딩서울특별시 강서구 공항대로 351, 키모코리아빌딩 지하1층 (등촌동)7590주식회사 한우연 숙성고(등촌점)2023-12-18 15:17:54U2022-11-01 22:00:00.0<NA>186398.338369450646.647499<NA><NA><NA><NA><NA>
4831500003150000104202200022022-05-13<NA>3폐업2폐업2023-02-13<NA><NA><NA><NA>330.0<NA>서울특별시 강서구 내발산동 755-4 1층서울특별시 강서구 남부순환로 205, 1층 (내발산동)7642서현푸드2023-02-13 16:26:33U2022-12-01 23:05:00.0<NA>184136.545386449480.365146<NA><NA><NA><NA><NA>
49315000031500001042022000320221212<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 등촌동 631-5 NH서울축산농협 NH서울타워 B104호서울특별시 강서구 양천로 570, NH서울축산농협 NH서울타워 지하1층 B104호 (등촌동)7551하나로마트 본점2023-01-20 15:59:44U2022-11-30 22:02:00.0<NA>187727.758706450500.126507<NA><NA><NA><NA><NA>
50315000031500001042022000420221212<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 등촌동 631-5 NH서울축산농협 NH서울타워 B105호서울특별시 강서구 양천로 570, NH서울축산농협 NH서울타워 지하1층 B105호 (등촌동)7551축산유통본부 가공장2022-12-12 13:20:06I2021-11-01 23:04:00.0<NA>187727.758706450500.126507<NA><NA><NA><NA><NA>