Overview

Dataset statistics

Number of variables30
Number of observations66
Missing cells375
Missing cells (%)18.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory258.0 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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18151/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (64.5%)Imbalance
영업상태명 is highly imbalanced (64.5%)Imbalance
상세영업상태코드 is highly imbalanced (64.5%)Imbalance
상세영업상태명 is highly imbalanced (64.5%)Imbalance
휴업시작일자 is highly imbalanced (88.7%)Imbalance
휴업종료일자 is highly imbalanced (88.7%)Imbalance
축산업무구분명 is highly imbalanced (51.2%)Imbalance
축산물가공업구분명 is highly imbalanced (51.2%)Imbalance
축산일련번호 is highly imbalanced (61.3%)Imbalance
총인원 is highly imbalanced (61.3%)Imbalance
인허가취소일자 has 66 (100.0%) missing valuesMissing
폐업일자 has 8 (12.1%) missing valuesMissing
재개업일자 has 66 (100.0%) missing valuesMissing
전화번호 has 24 (36.4%) missing valuesMissing
소재지우편번호 has 66 (100.0%) missing valuesMissing
지번주소 has 3 (4.5%) missing valuesMissing
도로명주소 has 38 (57.6%) missing valuesMissing
도로명우편번호 has 38 (57.6%) missing valuesMissing
업태구분명 has 66 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 36 (54.5%) zerosZeros

Reproduction

Analysis started2024-05-11 09:19:49.723827
Analysis finished2024-05-11 09:19:50.577722
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
3240000
66 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 66
100.0%

Length

2024-05-11T09:19:50.777035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:51.305567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 66
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2400001 × 1017
Minimum3.24 × 1017
Maximum3.2400001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T09:19:51.861452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.24 × 1017
5-th percentile3.24 × 1017
Q13.24 × 1017
median3.24 × 1017
Q33.2400001 × 1017
95-th percentile3.2400001 × 1017
Maximum3.2400001 × 1017
Range1.000017 × 1010
Interquartile range (IQR)1.000008 × 1010

Descriptive statistics

Standard deviation5.0360399 × 109
Coefficient of variation (CV)1.5543333 × 10-8
Kurtosis-2.0595211
Mean3.2400001 × 1017
Median Absolute Deviation (MAD)40000
Skewness0.062053205
Sum2.9372563 × 1018
Variance2.5361698 × 1019
MonotonicityStrictly increasing
2024-05-11T09:19:52.399895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
324000000420050002 1
 
1.5%
324000010420140001 1
 
1.5%
324000010420100001 1
 
1.5%
324000010420100002 1
 
1.5%
324000010420100003 1
 
1.5%
324000010420110001 1
 
1.5%
324000010420110002 1
 
1.5%
324000010420110003 1
 
1.5%
324000010420110004 1
 
1.5%
324000010420110005 1
 
1.5%
Other values (56) 56
84.8%
ValueCountFrequency (%)
324000000420050002 1
1.5%
324000000420050003 1
1.5%
324000000420050004 1
1.5%
324000000420050005 1
1.5%
324000000420050006 1
1.5%
324000000420050007 1
1.5%
324000000420050008 1
1.5%
324000000420050009 1
1.5%
324000000420050010 1
1.5%
324000000420050011 1
1.5%
ValueCountFrequency (%)
324000010420220001 1
1.5%
324000010420200001 1
1.5%
324000010420190001 1
1.5%
324000010420180003 1
1.5%
324000010420180002 1
1.5%
324000010420180001 1
1.5%
324000010420170002 1
1.5%
324000010420170001 1
1.5%
324000010420160003 1
1.5%
324000010420160002 1
1.5%

인허가일자
Date

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size660.0 B
Minimum2005-01-13 00:00:00
Maximum2022-04-15 00:00:00
2024-05-11T09:19:52.826029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:19:53.647048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
3
57 
1
7 
2
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 57
86.4%
1 7
 
10.6%
2 1
 
1.5%
4 1
 
1.5%

Length

2024-05-11T09:19:54.374994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:54.712168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 57
86.4%
1 7
 
10.6%
2 1
 
1.5%
4 1
 
1.5%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
폐업
57 
영업/정상
7 
휴업
 
1
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length2.5
Min length2

Unique

Unique2 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 57
86.4%
영업/정상 7
 
10.6%
휴업 1
 
1.5%
취소/말소/만료/정지/중지 1
 
1.5%

Length

2024-05-11T09:19:55.283851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:55.712054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 57
86.4%
영업/정상 7
 
10.6%
휴업 1
 
1.5%
취소/말소/만료/정지/중지 1
 
1.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
2
57 
0
7 
1
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 57
86.4%
0 7
 
10.6%
1 1
 
1.5%
4 1
 
1.5%

Length

2024-05-11T09:19:56.041322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:56.355688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 57
86.4%
0 7
 
10.6%
1 1
 
1.5%
4 1
 
1.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
폐업
57 
정상
7 
휴업
 
1
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 57
86.4%
정상 7
 
10.6%
휴업 1
 
1.5%
말소 1
 
1.5%

Length

2024-05-11T09:19:56.833524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:57.276958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 57
86.4%
정상 7
 
10.6%
휴업 1
 
1.5%
말소 1
 
1.5%

폐업일자
Date

MISSING 

Distinct53
Distinct (%)91.4%
Missing8
Missing (%)12.1%
Memory size660.0 B
Minimum2005-09-07 00:00:00
Maximum2024-01-15 00:00:00
2024-05-11T09:19:57.632286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:19:58.059874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
65 
20180529
 
1

Length

Max length8
Median length4
Mean length4.0606061
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 65
98.5%
20180529 1
 
1.5%

Length

2024-05-11T09:19:58.534424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:58.976106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
98.5%
20180529 1
 
1.5%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
65 
20180727
 
1

Length

Max length8
Median length4
Mean length4.0606061
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 65
98.5%
20180727 1
 
1.5%

Length

2024-05-11T09:19:59.532953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:19:59.915892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
98.5%
20180727 1
 
1.5%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

전화번호
Text

MISSING 

Distinct41
Distinct (%)97.6%
Missing24
Missing (%)36.4%
Memory size660.0 B
2024-05-11T09:20:00.510386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.6190476
Min length7

Characters and Unicode

Total characters362
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

Unique40 ?
Unique (%)95.2%

Sample

1st row476-0475
2nd row426-2661
3rd row442-3364
4th row478-5802
5th row475-1692
ValueCountFrequency (%)
475-8430 2
 
4.8%
02-489-5588 1
 
2.4%
476-0475 1
 
2.4%
070-7433-1853 1
 
2.4%
416-4224 1
 
2.4%
484-8776 1
 
2.4%
442-7001 1
 
2.4%
420-1005 1
 
2.4%
02-482-3407 1
 
2.4%
024289129 1
 
2.4%
Other values (31) 31
73.8%
2024-05-11T09:20:01.571937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 63
17.4%
2 47
13.0%
- 44
12.2%
7 41
11.3%
8 40
11.0%
0 33
9.1%
6 29
8.0%
3 17
 
4.7%
1 17
 
4.7%
5 16
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 318
87.8%
Dash Punctuation 44
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 63
19.8%
2 47
14.8%
7 41
12.9%
8 40
12.6%
0 33
10.4%
6 29
9.1%
3 17
 
5.3%
1 17
 
5.3%
5 16
 
5.0%
9 15
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 362
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 63
17.4%
2 47
13.0%
- 44
12.2%
7 41
11.3%
8 40
11.0%
0 33
9.1%
6 29
8.0%
3 17
 
4.7%
1 17
 
4.7%
5 16
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 63
17.4%
2 47
13.0%
- 44
12.2%
7 41
11.3%
8 40
11.0%
0 33
9.1%
6 29
8.0%
3 17
 
4.7%
1 17
 
4.7%
5 16
 
4.4%

소재지면적
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.217879
Minimum0
Maximum1186.5
Zeros36
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T09:20:02.016038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q369.06
95-th percentile297
Maximum1186.5
Range1186.5
Interquartile range (IQR)69.06

Descriptive statistics

Standard deviation165.84056
Coefficient of variation (CV)2.2048025
Kurtosis31.209961
Mean75.217879
Median Absolute Deviation (MAD)0
Skewness4.9466827
Sum4964.38
Variance27503.093
MonotonicityNot monotonic
2024-05-11T09:20:02.460863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 36
54.5%
200.0 3
 
4.5%
300.0 2
 
3.0%
32.88 1
 
1.5%
155.92 1
 
1.5%
1186.5 1
 
1.5%
336.98 1
 
1.5%
220.3 1
 
1.5%
195.0 1
 
1.5%
50.0 1
 
1.5%
Other values (18) 18
27.3%
ValueCountFrequency (%)
0.0 36
54.5%
14.06 1
 
1.5%
32.88 1
 
1.5%
33.64 1
 
1.5%
36.04 1
 
1.5%
44.66 1
 
1.5%
49.04 1
 
1.5%
49.41 1
 
1.5%
50.0 1
 
1.5%
55.08 1
 
1.5%
ValueCountFrequency (%)
1186.5 1
 
1.5%
336.98 1
 
1.5%
300.0 2
3.0%
288.0 1
 
1.5%
221.64 1
 
1.5%
220.3 1
 
1.5%
200.0 3
4.5%
195.0 1
 
1.5%
175.13 1
 
1.5%
155.92 1
 
1.5%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

지번주소
Text

MISSING 

Distinct60
Distinct (%)95.2%
Missing3
Missing (%)4.5%
Memory size660.0 B
2024-05-11T09:20:03.166008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length23.079365
Min length13

Characters and Unicode

Total characters1454
Distinct characters50
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

Unique58 ?
Unique (%)92.1%

Sample

1st row서울특별시 강동구 성내동 503-4번지
2nd row서울특별시 강동구 암사동 496-3번지 1층
3rd row서울특별시 강동구 암사동 414-2번지 강동(아)가상가 지하2호
4th row서울특별시 강동구 길동 152번지
5th row서울특별시 강동구 둔촌동 611-1번지 지하
ValueCountFrequency (%)
서울특별시 63
22.3%
강동구 63
22.3%
천호동 16
 
5.7%
길동 16
 
5.7%
성내동 11
 
3.9%
고덕동 6
 
2.1%
1층 6
 
2.1%
암사동 5
 
1.8%
상일동 5
 
1.8%
160번지 4
 
1.4%
Other values (75) 87
30.9%
2024-05-11T09:20:04.457925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
18.9%
동 131
 
9.0%
서 64
 
4.4%
시 64
 
4.4%
강 64
 
4.4%
특 63
 
4.3%
별 63
 
4.3%
구 63
 
4.3%
울 63
 
4.3%
지 56
 
3.9%
Other values (40) 548
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 855
58.8%
Space Separator 275
 
18.9%
Decimal Number 261
 
18.0%
Dash Punctuation 50
 
3.4%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 131
15.3%
서 64
 
7.5%
시 64
 
7.5%
강 64
 
7.5%
특 63
 
7.4%
별 63
 
7.4%
구 63
 
7.4%
울 63
 
7.4%
지 56
 
6.5%
번 47
 
5.5%
Other values (24) 177
20.7%
Decimal Number
ValueCountFrequency (%)
1 44
16.9%
3 41
15.7%
4 39
14.9%
2 35
13.4%
5 26
10.0%
6 22
8.4%
9 19
7.3%
0 15
 
5.7%
8 12
 
4.6%
7 8
 
3.1%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 855
58.8%
Common 596
41.0%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 131
15.3%
서 64
 
7.5%
시 64
 
7.5%
강 64
 
7.5%
특 63
 
7.4%
별 63
 
7.4%
구 63
 
7.4%
울 63
 
7.4%
지 56
 
6.5%
번 47
 
5.5%
Other values (24) 177
20.7%
Common
ValueCountFrequency (%)
275
46.1%
- 50
 
8.4%
1 44
 
7.4%
3 41
 
6.9%
4 39
 
6.5%
2 35
 
5.9%
5 26
 
4.4%
6 22
 
3.7%
9 19
 
3.2%
0 15
 
2.5%
Other values (5) 30
 
5.0%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 855
58.8%
ASCII 599
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
45.9%
- 50
 
8.3%
1 44
 
7.3%
3 41
 
6.8%
4 39
 
6.5%
2 35
 
5.8%
5 26
 
4.3%
6 22
 
3.7%
9 19
 
3.2%
0 15
 
2.5%
Other values (6) 33
 
5.5%
Hangul
ValueCountFrequency (%)
동 131
15.3%
서 64
 
7.5%
시 64
 
7.5%
강 64
 
7.5%
특 63
 
7.4%
별 63
 
7.4%
구 63
 
7.4%
울 63
 
7.4%
지 56
 
6.5%
번 47
 
5.5%
Other values (24) 177
20.7%

도로명주소
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing38
Missing (%)57.6%
Memory size660.0 B
2024-05-11T09:20:05.340571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length28.107143
Min length23

Characters and Unicode

Total characters787
Distinct characters63
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)85.7%

Sample

1st row서울특별시 강동구 구천면로31길 39 (천호동)
2nd row서울특별시 강동구 성안로3길 69 (성내동, 다영빌딩)
3rd row서울특별시 강동구 양재대로124길 40(길동)
4th row서울특별시 강동구 고덕로61길 148, 지하1층 (고덕동)
5th row서울특별시 강동구 양재대로110길 29, 1층 (길동)
ValueCountFrequency (%)
서울특별시 28
17.9%
강동구 28
17.9%
천호동 9
 
5.8%
1층 7
 
4.5%
고덕동 4
 
2.6%
길동 4
 
2.6%
지하1층 4
 
2.6%
명일동 3
 
1.9%
성내동 3
 
1.9%
29 3
 
1.9%
Other values (56) 63
40.4%
2024-05-11T09:20:06.399709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
 
16.3%
동 61
 
7.8%
1 39
 
5.0%
구 32
 
4.1%
서 29
 
3.7%
시 29
 
3.7%
( 28
 
3.6%
특 28
 
3.6%
별 28
 
3.6%
강 28
 
3.6%
Other values (53) 357
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 465
59.1%
Space Separator 128
 
16.3%
Decimal Number 123
 
15.6%
Open Punctuation 28
 
3.6%
Close Punctuation 28
 
3.6%
Other Punctuation 15
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 61
13.1%
구 32
 
6.9%
서 29
 
6.2%
시 29
 
6.2%
특 28
 
6.0%
별 28
 
6.0%
강 28
 
6.0%
울 28
 
6.0%
로 28
 
6.0%
길 26
 
5.6%
Other values (39) 148
31.8%
Decimal Number
ValueCountFrequency (%)
1 39
31.7%
3 16
13.0%
2 14
 
11.4%
9 11
 
8.9%
8 10
 
8.1%
4 8
 
6.5%
5 8
 
6.5%
0 7
 
5.7%
6 6
 
4.9%
7 4
 
3.3%
Space Separator
ValueCountFrequency (%)
128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 465
59.1%
Common 322
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 61
13.1%
구 32
 
6.9%
서 29
 
6.2%
시 29
 
6.2%
특 28
 
6.0%
별 28
 
6.0%
강 28
 
6.0%
울 28
 
6.0%
로 28
 
6.0%
길 26
 
5.6%
Other values (39) 148
31.8%
Common
ValueCountFrequency (%)
128
39.8%
1 39
 
12.1%
( 28
 
8.7%
) 28
 
8.7%
3 16
 
5.0%
, 15
 
4.7%
2 14
 
4.3%
9 11
 
3.4%
8 10
 
3.1%
4 8
 
2.5%
Other values (4) 25
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 465
59.1%
ASCII 322
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
39.8%
1 39
 
12.1%
( 28
 
8.7%
) 28
 
8.7%
3 16
 
5.0%
, 15
 
4.7%
2 14
 
4.3%
9 11
 
3.4%
8 10
 
3.1%
4 8
 
2.5%
Other values (4) 25
 
7.8%
Hangul
ValueCountFrequency (%)
동 61
13.1%
구 32
 
6.9%
서 29
 
6.2%
시 29
 
6.2%
특 28
 
6.0%
별 28
 
6.0%
강 28
 
6.0%
울 28
 
6.0%
로 28
 
6.0%
길 26
 
5.6%
Other values (39) 148
31.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)75.0%
Missing38
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean5307.8214
Minimum5226
Maximum5403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T09:20:06.908233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5226
5-th percentile5226.35
Q15267.75
median5318.5
Q35350
95-th percentile5391.95
Maximum5403
Range177
Interquartile range (IQR)82.25

Descriptive statistics

Standard deviation52.73066
Coefficient of variation (CV)0.0099345203
Kurtosis-0.85921626
Mean5307.8214
Median Absolute Deviation (MAD)34
Skewness-0.060519601
Sum148619
Variance2780.5225
MonotonicityNot monotonic
2024-05-11T09:20:07.479437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5350 3
 
4.5%
5326 3
 
4.5%
5227 2
 
3.0%
5226 2
 
3.0%
5269 2
 
3.0%
5403 1
 
1.5%
5264 1
 
1.5%
5323 1
 
1.5%
5251 1
 
1.5%
5284 1
 
1.5%
Other values (11) 11
 
16.7%
(Missing) 38
57.6%
ValueCountFrequency (%)
5226 2
3.0%
5227 2
3.0%
5244 1
1.5%
5251 1
1.5%
5264 1
1.5%
5269 2
3.0%
5284 1
1.5%
5299 1
1.5%
5303 1
1.5%
5308 1
1.5%
ValueCountFrequency (%)
5403 1
 
1.5%
5400 1
 
1.5%
5377 1
 
1.5%
5372 1
 
1.5%
5352 1
 
1.5%
5350 3
4.5%
5330 1
 
1.5%
5326 3
4.5%
5323 1
 
1.5%
5322 1
 
1.5%

사업장명
Text

Distinct64
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-05-11T09:20:08.246444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.6969697
Min length3

Characters and Unicode

Total characters442
Distinct characters140
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

Unique62 ?
Unique (%)93.9%

Sample

1st row목우촌천호대리점
2nd row푸드엠
3rd row(주)다모아축산
4th row(주)FK유통
5th row일호유통
ValueCountFrequency (%)
주)선진 2
 
2.7%
주식회사 2
 
2.7%
한우리축산유통 2
 
2.7%
길동점 1
 
1.4%
888fnc 1
 
1.4%
하늘미트 1
 
1.4%
태양축산 1
 
1.4%
cm스타 1
 
1.4%
엔식품 1
 
1.4%
주선진 1
 
1.4%
Other values (60) 60
82.2%
2024-05-11T09:20:09.782321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 29
 
6.6%
( 24
 
5.4%
) 23
 
5.2%
축 13
 
2.9%
산 13
 
2.9%
드 12
 
2.7%
통 12
 
2.7%
유 11
 
2.5%
이 10
 
2.3%
푸 9
 
2.0%
Other values (130) 286
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
83.9%
Open Punctuation 24
 
5.4%
Close Punctuation 23
 
5.2%
Uppercase Letter 8
 
1.8%
Space Separator 7
 
1.6%
Decimal Number 6
 
1.4%
Other Punctuation 2
 
0.5%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
7.8%
축 13
 
3.5%
산 13
 
3.5%
드 12
 
3.2%
통 12
 
3.2%
유 11
 
3.0%
이 10
 
2.7%
푸 9
 
2.4%
스 9
 
2.4%
리 9
 
2.4%
Other values (118) 244
65.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
37.5%
K 2
25.0%
F 2
25.0%
M 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
8 4
66.7%
1 1
 
16.7%
6 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
83.9%
Common 62
 
14.0%
Latin 9
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
7.8%
축 13
 
3.5%
산 13
 
3.5%
드 12
 
3.2%
통 12
 
3.2%
유 11
 
3.0%
이 10
 
2.7%
푸 9
 
2.4%
스 9
 
2.4%
리 9
 
2.4%
Other values (118) 244
65.8%
Common
ValueCountFrequency (%)
( 24
38.7%
) 23
37.1%
7
 
11.3%
8 4
 
6.5%
. 2
 
3.2%
1 1
 
1.6%
6 1
 
1.6%
Latin
ValueCountFrequency (%)
C 3
33.3%
K 2
22.2%
F 2
22.2%
M 1
 
11.1%
n 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
83.9%
ASCII 71
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 29
 
7.8%
축 13
 
3.5%
산 13
 
3.5%
드 12
 
3.2%
통 12
 
3.2%
유 11
 
3.0%
이 10
 
2.7%
푸 9
 
2.4%
스 9
 
2.4%
리 9
 
2.4%
Other values (118) 244
65.8%
ASCII
ValueCountFrequency (%)
( 24
33.8%
) 23
32.4%
7
 
9.9%
8 4
 
5.6%
C 3
 
4.2%
. 2
 
2.8%
K 2
 
2.8%
F 2
 
2.8%
1 1
 
1.4%
M 1
 
1.4%
Other values (2) 2
 
2.8%

최종수정일자
Date

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
Minimum2005-09-07 14:33:07
Maximum2024-01-15 17:06:52
2024-05-11T09:20:10.243215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:20:10.696799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
I
47 
U
19 

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 47
71.2%
U 19
28.8%

Length

2024-05-11T09:20:11.149348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:11.483997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 47
71.2%
u 19
28.8%

데이터갱신일자
Categorical

Distinct18
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size660.0 B
2018-08-31 23:59:59.0
46 
2021-07-07 02:40:00.0
 
3
2020-01-25 02:40:00.0
 
2
2021-03-27 02:40:00.0
 
1
2022-12-03 00:09:00.0
 
1
Other values (13)
13 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique15 ?
Unique (%)22.7%

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 46
69.7%
2021-07-07 02:40:00.0 3
 
4.5%
2020-01-25 02:40:00.0 2
 
3.0%
2021-03-27 02:40:00.0 1
 
1.5%
2022-12-03 00:09:00.0 1
 
1.5%
2020-11-28 02:40:00.0 1
 
1.5%
2019-01-31 02:40:00.0 1
 
1.5%
2021-10-31 23:08:00.0 1
 
1.5%
2023-11-30 23:07:00.0 1
 
1.5%
2022-03-17 02:40:00.0 1
 
1.5%
Other values (8) 8
 
12.1%

Length

2024-05-11T09:20:11.788340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 46
34.8%
23:59:59.0 46
34.8%
02:40:00.0 13
 
9.8%
2021-07-07 3
 
2.3%
2020-01-25 2
 
1.5%
2022-12-03 2
 
1.5%
22:01:00.0 2
 
1.5%
23:07:00.0 2
 
1.5%
2021-07-25 1
 
0.8%
22:09:00.0 1
 
0.8%
Other values (14) 14
 
10.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

좌표정보(X)
Real number (ℝ)

Distinct58
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212383.44
Minimum210566.88
Maximum215149.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T09:20:12.261139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile211032.07
Q1211397.36
median212271.78
Q3213070.5
95-th percentile214952.11
Maximum215149.29
Range4582.4126
Interquartile range (IQR)1673.1356

Descriptive statistics

Standard deviation1143.684
Coefficient of variation (CV)0.005384996
Kurtosis0.070255285
Mean212383.44
Median Absolute Deviation (MAD)798.71777
Skewness0.7913525
Sum14017307
Variance1308013
MonotonicityNot monotonic
2024-05-11T09:20:12.798079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213070.495037105 4
 
6.1%
211853.659176909 3
 
4.5%
211478.363444563 2
 
3.0%
211213.095443058 2
 
3.0%
213582.043238143 2
 
3.0%
211466.10518838 1
 
1.5%
211715.11839931 1
 
1.5%
211309.086363507 1
 
1.5%
211786.650277068 1
 
1.5%
211810.896881259 1
 
1.5%
Other values (48) 48
72.7%
ValueCountFrequency (%)
210566.875626134 1
1.5%
210890.528800677 1
1.5%
210977.256530413 1
1.5%
211019.483493473 1
1.5%
211069.812258216 1
1.5%
211159.42900767 1
1.5%
211213.095443058 2
3.0%
211231.741493664 1
1.5%
211252.735515916 1
1.5%
211274.418466732 1
1.5%
ValueCountFrequency (%)
215149.288222193 1
1.5%
215137.810171285 1
1.5%
215129.842193761 1
1.5%
214973.32588151 1
1.5%
214888.465504117 1
1.5%
213751.225969745 1
1.5%
213702.581702681 1
1.5%
213660.978068863 1
1.5%
213582.043238143 2
3.0%
213575.253808884 1
1.5%

좌표정보(Y)
Real number (ℝ)

Distinct58
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449005.01
Minimum447040.07
Maximum451024.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T09:20:13.325494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447040.07
5-th percentile447383.78
Q1448173.27
median448972.92
Q3449412.33
95-th percentile450967.02
Maximum451024.3
Range3984.2336
Interquartile range (IQR)1239.057

Descriptive statistics

Standard deviation1020.939
Coefficient of variation (CV)0.0022737808
Kurtosis-0.40672694
Mean449005.01
Median Absolute Deviation (MAD)718.32612
Skewness0.137976
Sum29634331
Variance1042316.4
MonotonicityNot monotonic
2024-05-11T09:20:13.928857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448552.7479101 4
 
6.1%
449388.465849174 3
 
4.5%
448139.428399099 2
 
3.0%
448824.475991234 2
 
3.0%
450060.273410647 2
 
3.0%
447743.191816769 1
 
1.5%
447763.588160928 1
 
1.5%
449394.263347689 1
 
1.5%
449401.043695265 1
 
1.5%
449360.762636795 1
 
1.5%
Other values (48) 48
72.7%
ValueCountFrequency (%)
447040.070086074 1
1.5%
447191.968639032 1
1.5%
447276.508702471 1
1.5%
447381.743610803 1
1.5%
447389.893201561 1
1.5%
447402.629676369 1
1.5%
447405.859084035 1
1.5%
447734.899992198 1
1.5%
447743.191816769 1
1.5%
447763.588160928 1
1.5%
ValueCountFrequency (%)
451024.303683723 1
1.5%
451010.585461397 1
1.5%
450991.031680959 1
1.5%
450974.056567516 1
1.5%
450945.892844006 1
1.5%
450879.963361697 1
1.5%
450472.374955204 1
1.5%
450207.018195483 1
1.5%
450060.273410647 2
3.0%
449952.244469763 1
1.5%

축산업무구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
식육포장처리업
59 
<NA>
7 

Length

Max length7
Median length7
Mean length6.6818182
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 59
89.4%
<NA> 7
 
10.6%

Length

2024-05-11T09:20:14.568626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:14.975405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 59
89.4%
na 7
 
10.6%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
식육포장처리업
59 
<NA>
7 

Length

Max length7
Median length7
Mean length6.6818182
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 59
89.4%
<NA> 7
 
10.6%

Length

2024-05-11T09:20:15.528077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:15.935447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 59
89.4%
na 7
 
10.6%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
61 
0
 
5

Length

Max length4
Median length4
Mean length3.7727273
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> 61
92.4%
0 5
 
7.6%

Length

2024-05-11T09:20:16.411141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:16.721271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
92.4%
0 5
 
7.6%

권리주체일련번호
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
000
33 
L00
26 
<NA>
7 

Length

Max length4
Median length3
Mean length3.1060606
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 33
50.0%
L00 26
39.4%
<NA> 7
 
10.6%

Length

2024-05-11T09:20:17.049964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:17.421813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 33
50.0%
l00 26
39.4%
na 7
 
10.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
61 
0
 
5

Length

Max length4
Median length4
Mean length3.7727273
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> 61
92.4%
0 5
 
7.6%

Length

2024-05-11T09:20:17.830460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:20:18.163682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
92.4%
0 5
 
7.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0324000032400000042005000220050113<NA>3폐업2폐업20110516<NA><NA><NA>476-047532.88<NA>서울특별시 강동구 성내동 503-4번지<NA><NA>목우촌천호대리점2011-05-16 14:47:41I2018-08-31 23:59:59.0<NA>211466.105188447743.191817식육포장처리업식육포장처리업<NA>000<NA>
1324000032400000042005000320050302<NA>3폐업2폐업20070105<NA><NA><NA>426-266161.5<NA>서울특별시 강동구 암사동 496-3번지 1층<NA><NA>푸드엠2007-01-05 16:55:52I2018-08-31 23:59:59.0<NA>211364.053528449831.029844식육포장처리업식육포장처리업<NA>000<NA>
2324000032400000042005000420050113<NA>3폐업2폐업20051101<NA><NA><NA>442-33640.0<NA>서울특별시 강동구 암사동 414-2번지 강동(아)가상가 지하2호<NA><NA>(주)다모아축산2005-11-03 17:44:26I2018-08-31 23:59:59.0<NA>212480.463676450472.374955식육포장처리업식육포장처리업<NA>L00<NA>
3324000032400000042005000520050113<NA>3폐업2폐업20070302<NA><NA><NA>478-580255.08<NA>서울특별시 강동구 길동 152번지<NA><NA>(주)FK유통2007-03-02 10:25:05I2018-08-31 23:59:59.0<NA>212605.702433448143.62781식육포장처리업식육포장처리업<NA>L00<NA>
4324000032400000042005000620050113<NA>3폐업2폐업20120330<NA><NA><NA>475-169265.79<NA>서울특별시 강동구 둔촌동 611-1번지 지하<NA><NA>일호유통2012-03-30 12:41:51I2018-08-31 23:59:59.0<NA>213016.69417448042.306203식육포장처리업식육포장처리업<NA>000<NA>
5324000032400000042005000720050113<NA>3폐업2폐업20060112<NA><NA><NA><NA>44.66<NA>서울특별시 강동구 암사동 499-1번지<NA><NA>하나축산2006-01-12 17:20:04I2018-08-31 23:59:59.0<NA>211374.444251449952.24447식육포장처리업식육포장처리업<NA>L00<NA>
6324000032400000042005000820050113<NA>3폐업2폐업20150406<NA><NA><NA>428-2852175.13<NA>서울특별시 강동구 상일동 287번지 ,287-1 지하<NA><NA>상일축산유통2015-04-07 09:33:18I2018-08-31 23:59:59.0<NA>215137.810171449599.942909식육포장처리업식육포장처리업<NA>000<NA>
7324000032400000042005000920050113<NA>3폐업2폐업20061025<NA><NA><NA>479-167649.41<NA>서울특별시 강동구 성내동 469-9번지 1층<NA><NA>(주)에스.엠.프렌차이즈2006-11-23 10:30:45I2018-08-31 23:59:59.0<NA>211274.418467447040.070086식육포장처리업식육포장처리업<NA>L00<NA>
8324000032400000042005001020050113<NA>3폐업2폐업20060630<NA><NA><NA>429-687014.06<NA>서울특별시 강동구 상일동 457-4번지<NA><NA>한마루2006-07-03 11:25:58I2018-08-31 23:59:59.0<NA>214973.325882449332.185967식육포장처리업식육포장처리업<NA>000<NA>
9324000032400000042005001120050113<NA>3폐업2폐업20210705<NA><NA><NA>487-700469.47<NA>서울특별시 강동구 천호동서울특별시 강동구 구천면로31길 39 (천호동)5326(주)빠보로꼬2021-07-05 15:33:17U2021-07-07 02:40:00.0<NA>211213.095443448824.475991식육포장처리업식육포장처리업0L000
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
56324000032400001042016000220160530<NA>3폐업2폐업20170720<NA><NA><NA><NA>0.0<NA>서울특별시 강동구 고덕동 529-5번지서울특별시 강동구 동남로85길 22, 1층 (고덕동)5226동선축산2017-07-20 09:59:22I2018-08-31 23:59:59.0<NA>213660.978069451024.303684식육포장처리업식육포장처리업<NA>000<NA>
57324000032400001042016000320160721<NA>3폐업2폐업20200121<NA><NA><NA>0242816900.0<NA>서울특별시 강동구 명일동 48-1번지서울특별시 강동구 동남로73길 31 (명일동)5269(주)휴먼메쯔거라이2020-01-23 16:17:50U2020-01-25 02:40:00.0<NA>213582.043238450060.273411식육포장처리업식육포장처리업<NA>L00<NA>
58324000032400001042017000120170215<NA>3폐업2폐업20210723<NA><NA><NA>02-6423-37020.0<NA>서울특별시 강동구 둔촌동 518-4서울특별시 강동구 풍성로 235, 지하1층 (둔촌동, 하이랜드빌딩)5372(주)하이랜드 이노베이션2021-07-23 14:00:02U2021-07-25 02:40:00.0<NA>212119.359749447389.893202식육포장처리업식육포장처리업0L000
59324000032400001042017000220110907<NA>3폐업2폐업20201123<NA><NA><NA><NA>195.0<NA>서울특별시 강동구 천호동 21-206서울특별시 강동구 상암로 141 (천호동)5308삼우유통2020-11-23 10:15:44U2020-11-25 02:40:00.0<NA>212150.012937449307.36107식육포장처리업식육포장처리업<NA>000<NA>
60324000032400001042018000120180131<NA>1영업/정상0정상<NA><NA><NA><NA><NA>220.3<NA>서울특별시 강동구 상일동 454번지서울특별시 강동구 상암로81길 50, 지하1및1층 (상일동)5284성농찬2018-01-31 10:04:57I2018-08-31 23:59:59.0<NA>214888.465504449334.414422식육포장처리업식육포장처리업<NA>000<NA>
61324000032400001042018000220181011<NA>1영업/정상0정상<NA><NA><NA><NA><NA>336.98<NA>서울특별시 강동구 암사동 462-3번지 서연빌딩서울특별시 강동구 올림픽로 820, 서연빌딩 지하1층 (암사동)5251(주)플랜비에프에스2019-06-03 14:44:17U2019-06-05 02:40:00.0<NA>211349.725354450207.018195식육포장처리업식육포장처리업<NA>L00<NA>
62324000032400001042018000320181129<NA>3폐업2폐업20200128<NA><NA><NA><NA>0.0<NA>서울특별시 강동구 천호동 312-26번지서울특별시 강동구 올림픽로88길 25, 1층 (천호동)5323농업회사법인 제주원2020-01-28 15:01:23U2020-01-30 02:40:00.0<NA>211231.741494449361.733806식육포장처리업식육포장처리업<NA>L00<NA>
6332400003240000104201900012019-11-14<NA>3폐업2폐업2023-12-19<NA><NA><NA>02-489-55881186.5<NA>서울특별시 강동구 길동 228-1서울특별시 강동구 천호대로 1193, 1층 (길동)5350(주)선우프레시 앵거스박 길동점2023-12-19 15:34:19U2022-11-01 22:01:00.0<NA>212616.96006448087.909554<NA><NA><NA><NA><NA>
6432400003240000104202000012020-01-31<NA>3폐업2폐업2023-04-19<NA><NA><NA>02-428-16900.0<NA>서울특별시 강동구 명일동 48-1서울특별시 강동구 동남로73길 31 (명일동)5269(주)훔메플라이셔라이2023-04-19 16:46:10U2022-12-03 22:01:00.0<NA>213582.043238450060.273411<NA><NA><NA><NA><NA>
65324000032400001042022000120220415<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강동구 암사동 501-16서울특별시 강동구 상암로11길 29, 지하1층 101호 (암사동)5264신진푸드 팩토리2022-04-15 16:10:09I2021-12-03 23:07:00.0<NA>211317.640531449871.521385<NA><NA><NA><NA><NA>