Overview

Dataset statistics

Number of variables30
Number of observations47
Missing cells238
Missing cells (%)16.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory258.8 B

Variable types

Categorical13
Numeric5
DateTime4
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18136/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (85.1%)Imbalance
휴업종료일자 is highly imbalanced (85.1%)Imbalance
축산일련번호 is highly imbalanced (74.6%)Imbalance
총인원 is highly imbalanced (74.6%)Imbalance
인허가취소일자 has 47 (100.0%) missing valuesMissing
폐업일자 has 14 (29.8%) missing valuesMissing
재개업일자 has 47 (100.0%) missing valuesMissing
전화번호 has 18 (38.3%) missing valuesMissing
소재지우편번호 has 47 (100.0%) missing valuesMissing
도로명주소 has 4 (8.5%) missing valuesMissing
도로명우편번호 has 14 (29.8%) missing valuesMissing
업태구분명 has 47 (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 39 (83.0%) zerosZeros

Reproduction

Analysis started2024-04-17 09:41:44.482045
Analysis finished2024-04-17 09:41:44.797289
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
3090000
47 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 47
100.0%

Length

2024-04-17T18:41:44.845476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:44.915420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 47
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0900001 × 1017
Minimum3.09 × 1017
Maximum3.0900001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-04-17T18:41:45.000412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.09 × 1017
5-th percentile3.09 × 1017
Q13.0900001 × 1017
median3.0900001 × 1017
Q33.0900001 × 1017
95-th percentile3.0900001 × 1017
Maximum3.0900001 × 1017
Range1.000024 × 1010
Interquartile range (IQR)5.00006 × 109

Descriptive statistics

Standard deviation4.4075795 × 109
Coefficient of variation (CV)1.4264011 × 10-8
Kurtosis-0.68634924
Mean3.0900001 × 1017
Median Absolute Deviation (MAD)40000
Skewness-1.1596275
Sum-3.9237437 × 1018
Variance1.9426757 × 1019
MonotonicityStrictly increasing
2024-04-17T18:41:45.134632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
309000000420000001 1
 
2.1%
309000000420040010 1
 
2.1%
309000010420130001 1
 
2.1%
309000010420130002 1
 
2.1%
309000010420140001 1
 
2.1%
309000010420140002 1
 
2.1%
309000010420140003 1
 
2.1%
309000010420140004 1
 
2.1%
309000010420150001 1
 
2.1%
309000010420150002 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
309000000420000001 1
2.1%
309000000420040010 1
2.1%
309000000420050005 1
2.1%
309000000420060003 1
2.1%
309000000420060004 1
2.1%
309000000420070002 1
2.1%
309000000420070003 1
2.1%
309000000420080003 1
2.1%
309000000420080005 1
2.1%
309000000420080006 1
2.1%
ValueCountFrequency (%)
309000010420240001 1
2.1%
309000010420220001 1
2.1%
309000010420200001 1
2.1%
309000010420190002 1
2.1%
309000010420190001 1
2.1%
309000010420180001 1
2.1%
309000010420170002 1
2.1%
309000010420170001 1
2.1%
309000010420160002 1
2.1%
309000010420160001 1
2.1%

인허가일자
Date

Distinct45
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2004-12-15 00:00:00
Maximum2024-01-30 00:00:00
2024-04-17T18:41:45.239559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:41:45.341441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)100.0%
Memory size555.0 B

영업상태코드
Categorical

Distinct4
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
3
31 
1
11 
4
4 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
3 31
66.0%
1 11
 
23.4%
4 4
 
8.5%
2 1
 
2.1%

Length

2024-04-17T18:41:45.443653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:45.520775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 31
66.0%
1 11
 
23.4%
4 4
 
8.5%
2 1
 
2.1%

영업상태명
Categorical

Distinct4
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
폐업
31 
영업/정상
11 
취소/말소/만료/정지/중지
4 
휴업
 
1

Length

Max length14
Median length2
Mean length3.7234043
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 31
66.0%
영업/정상 11
 
23.4%
취소/말소/만료/정지/중지 4
 
8.5%
휴업 1
 
2.1%

Length

2024-04-17T18:41:45.612921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:45.715743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 31
66.0%
영업/정상 11
 
23.4%
취소/말소/만료/정지/중지 4
 
8.5%
휴업 1
 
2.1%

상세영업상태코드
Categorical

Distinct5
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size508.0 B
2
31 
0
11 
4
 
2
3
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
2 31
66.0%
0 11
 
23.4%
4 2
 
4.3%
3 2
 
4.3%
1 1
 
2.1%

Length

2024-04-17T18:41:45.821367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:45.902202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 31
66.0%
0 11
 
23.4%
4 2
 
4.3%
3 2
 
4.3%
1 1
 
2.1%

상세영업상태명
Categorical

Distinct5
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size508.0 B
폐업
31 
정상
11 
말소
 
2
행정처분
 
2
휴업
 
1

Length

Max length4
Median length2
Mean length2.0851064
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 31
66.0%
정상 11
 
23.4%
말소 2
 
4.3%
행정처분 2
 
4.3%
휴업 1
 
2.1%

Length

2024-04-17T18:41:46.002469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:46.093634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 31
66.0%
정상 11
 
23.4%
말소 2
 
4.3%
행정처분 2
 
4.3%
휴업 1
 
2.1%

폐업일자
Date

MISSING 

Distinct33
Distinct (%)100.0%
Missing14
Missing (%)29.8%
Memory size508.0 B
Minimum2005-12-19 00:00:00
Maximum2023-07-25 00:00:00
2024-04-17T18:41:46.183980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:41:46.277180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
<NA>
46 
20190402
 
1

Length

Max length8
Median length4
Mean length4.0851064
Min length4

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
97.9%
20190402 1
 
2.1%

Length

2024-04-17T18:41:46.395550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:46.480834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
97.9%
20190402 1
 
2.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
<NA>
46 
20221230
 
1

Length

Max length8
Median length4
Mean length4.0851064
Min length4

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
97.9%
20221230 1
 
2.1%

Length

2024-04-17T18:41:46.567507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:46.652702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
97.9%
20221230 1
 
2.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)100.0%
Memory size555.0 B

전화번호
Text

MISSING 

Distinct28
Distinct (%)96.6%
Missing18
Missing (%)38.3%
Memory size508.0 B
2024-04-17T18:41:46.789536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length9.3448276
Min length8

Characters and Unicode

Total characters271
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

Unique27 ?
Unique (%)93.1%

Sample

1st row3499-6000
2nd row907-5253
3rd row900-1119
4th row956-1124
5th row955-9644
ValueCountFrequency (%)
900-1119 2
 
6.2%
02 2
 
6.2%
903-6969 1
 
3.1%
3499-6000 1
 
3.1%
908-8892 1
 
3.1%
02-954-8951 1
 
3.1%
02-907-6255 1
 
3.1%
9078631 1
 
3.1%
20382061 1
 
3.1%
029024569 1
 
3.1%
Other values (20) 20
62.5%
2024-04-17T18:41:47.064106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 47
17.3%
0 44
16.2%
- 34
12.5%
2 29
10.7%
5 24
8.9%
3 20
7.4%
6 17
 
6.3%
1 16
 
5.9%
8 15
 
5.5%
7 11
 
4.1%
Other values (2) 14
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 234
86.3%
Dash Punctuation 34
 
12.5%
Space Separator 3
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 47
20.1%
0 44
18.8%
2 29
12.4%
5 24
10.3%
3 20
8.5%
6 17
 
7.3%
1 16
 
6.8%
8 15
 
6.4%
7 11
 
4.7%
4 11
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 47
17.3%
0 44
16.2%
- 34
12.5%
2 29
10.7%
5 24
8.9%
3 20
7.4%
6 17
 
6.3%
1 16
 
5.9%
8 15
 
5.5%
7 11
 
4.1%
Other values (2) 14
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 47
17.3%
0 44
16.2%
- 34
12.5%
2 29
10.7%
5 24
8.9%
3 20
7.4%
6 17
 
6.3%
1 16
 
5.9%
8 15
 
5.5%
7 11
 
4.1%
Other values (2) 14
 
5.2%

소재지면적
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.924894
Minimum0
Maximum414
Zeros39
Zeros (%)83.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-04-17T18:41:47.167118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile131.3
Maximum414
Range414
Interquartile range (IQR)0

Descriptive statistics

Standard deviation68.706907
Coefficient of variation (CV)3.1337396
Kurtosis23.708412
Mean21.924894
Median Absolute Deviation (MAD)0
Skewness4.5346212
Sum1030.47
Variance4720.6391
MonotonicityNot monotonic
2024-04-17T18:41:47.250677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 39
83.0%
152.8 1
 
2.1%
31.65 1
 
2.1%
143.0 1
 
2.1%
104.0 1
 
2.1%
61.7 1
 
2.1%
35.96 1
 
2.1%
87.36 1
 
2.1%
414.0 1
 
2.1%
ValueCountFrequency (%)
0.0 39
83.0%
31.65 1
 
2.1%
35.96 1
 
2.1%
61.7 1
 
2.1%
87.36 1
 
2.1%
104.0 1
 
2.1%
143.0 1
 
2.1%
152.8 1
 
2.1%
414.0 1
 
2.1%
ValueCountFrequency (%)
414.0 1
 
2.1%
152.8 1
 
2.1%
143.0 1
 
2.1%
104.0 1
 
2.1%
87.36 1
 
2.1%
61.7 1
 
2.1%
35.96 1
 
2.1%
31.65 1
 
2.1%
0.0 39
83.0%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)100.0%
Memory size555.0 B

지번주소
Text

Distinct45
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-04-17T18:41:47.428963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length23.787234
Min length14

Characters and Unicode

Total characters1118
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)91.5%

Sample

1st row서울특별시 도봉구 창동 1-10번지
2nd row서울특별시 도봉구 쌍문동 36-8번지
3rd row서울특별시 도봉구 방학동 307-2번지 주상복합 102호
4th row서울특별시 도봉구 방학동 307-2번지 주상복합 102호
5th row서울특별시 도봉구 쌍문동 103-200번지 지층
ValueCountFrequency (%)
서울특별시 47
22.0%
도봉구 47
22.0%
창동 18
 
8.4%
쌍문동 14
 
6.5%
1층 10
 
4.7%
방학동 8
 
3.7%
도봉동 7
 
3.3%
749-9번지 2
 
0.9%
102호 2
 
0.9%
307-2번지 2
 
0.9%
Other values (54) 57
26.6%
2024-04-17T18:41:47.743518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
18.1%
도 54
 
4.8%
봉 54
 
4.8%
동 52
 
4.7%
서 47
 
4.2%
특 47
 
4.2%
별 47
 
4.2%
시 47
 
4.2%
구 47
 
4.2%
울 47
 
4.2%
Other values (43) 474
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 616
55.1%
Decimal Number 246
 
22.0%
Space Separator 202
 
18.1%
Dash Punctuation 45
 
4.0%
Other Punctuation 5
 
0.4%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 54
 
8.8%
봉 54
 
8.8%
동 52
 
8.4%
서 47
 
7.6%
특 47
 
7.6%
별 47
 
7.6%
시 47
 
7.6%
구 47
 
7.6%
울 47
 
7.6%
지 35
 
5.7%
Other values (27) 139
22.6%
Decimal Number
ValueCountFrequency (%)
1 47
19.1%
2 35
14.2%
3 28
11.4%
0 25
10.2%
6 24
9.8%
7 23
9.3%
5 19
7.7%
4 16
 
6.5%
9 15
 
6.1%
8 14
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 616
55.1%
Common 502
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 54
 
8.8%
봉 54
 
8.8%
동 52
 
8.4%
서 47
 
7.6%
특 47
 
7.6%
별 47
 
7.6%
시 47
 
7.6%
구 47
 
7.6%
울 47
 
7.6%
지 35
 
5.7%
Other values (27) 139
22.6%
Common
ValueCountFrequency (%)
202
40.2%
1 47
 
9.4%
- 45
 
9.0%
2 35
 
7.0%
3 28
 
5.6%
0 25
 
5.0%
6 24
 
4.8%
7 23
 
4.6%
5 19
 
3.8%
4 16
 
3.2%
Other values (6) 38
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 616
55.1%
ASCII 502
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
40.2%
1 47
 
9.4%
- 45
 
9.0%
2 35
 
7.0%
3 28
 
5.6%
0 25
 
5.0%
6 24
 
4.8%
7 23
 
4.6%
5 19
 
3.8%
4 16
 
3.2%
Other values (6) 38
 
7.6%
Hangul
ValueCountFrequency (%)
도 54
 
8.8%
봉 54
 
8.8%
동 52
 
8.4%
서 47
 
7.6%
특 47
 
7.6%
별 47
 
7.6%
시 47
 
7.6%
구 47
 
7.6%
울 47
 
7.6%
지 35
 
5.7%
Other values (27) 139
22.6%

도로명주소
Text

MISSING 

Distinct40
Distinct (%)93.0%
Missing4
Missing (%)8.5%
Memory size508.0 B
2024-04-17T18:41:47.963300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length35
Mean length28.232558
Min length22

Characters and Unicode

Total characters1214
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)86.0%

Sample

1st row서울특별시 도봉구 마들로11길 20 (창동)
2nd row서울특별시 도봉구 방학로5길 76 (쌍문동)
3rd row서울특별시 도봉구 시루봉로 149, 102호 (방학동,주상복합)
4th row서울특별시 도봉구 시루봉로 149, 102호 (방학동,주상복합)
5th row서울특별시 도봉구 도봉로103길 23 (쌍문동,지층)
ValueCountFrequency (%)
서울특별시 43
18.3%
도봉구 43
18.3%
창동 16
 
6.8%
쌍문동 12
 
5.1%
1층 9
 
3.8%
방학동 5
 
2.1%
도봉동 4
 
1.7%
덕릉로60길 4
 
1.7%
우이천로 3
 
1.3%
도당로13길 3
 
1.3%
Other values (76) 93
39.6%
2024-04-17T18:41:48.288385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
192
 
15.8%
도 69
 
5.7%
봉 65
 
5.4%
1 62
 
5.1%
동 45
 
3.7%
시 45
 
3.7%
로 44
 
3.6%
) 44
 
3.6%
( 44
 
3.6%
울 43
 
3.5%
Other values (61) 561
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
56.2%
Decimal Number 218
 
18.0%
Space Separator 192
 
15.8%
Close Punctuation 44
 
3.6%
Open Punctuation 44
 
3.6%
Other Punctuation 25
 
2.1%
Dash Punctuation 9
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 69
 
10.1%
봉 65
 
9.5%
동 45
 
6.6%
시 45
 
6.6%
로 44
 
6.5%
울 43
 
6.3%
서 43
 
6.3%
특 43
 
6.3%
구 43
 
6.3%
별 43
 
6.3%
Other values (45) 199
29.2%
Decimal Number
ValueCountFrequency (%)
1 62
28.4%
3 24
 
11.0%
5 22
 
10.1%
2 22
 
10.1%
4 20
 
9.2%
0 19
 
8.7%
6 19
 
8.7%
7 12
 
5.5%
9 11
 
5.0%
8 7
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
. 1
 
4.0%
Space Separator
ValueCountFrequency (%)
192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 682
56.2%
Common 532
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 69
 
10.1%
봉 65
 
9.5%
동 45
 
6.6%
시 45
 
6.6%
로 44
 
6.5%
울 43
 
6.3%
서 43
 
6.3%
특 43
 
6.3%
구 43
 
6.3%
별 43
 
6.3%
Other values (45) 199
29.2%
Common
ValueCountFrequency (%)
192
36.1%
1 62
 
11.7%
) 44
 
8.3%
( 44
 
8.3%
, 24
 
4.5%
3 24
 
4.5%
5 22
 
4.1%
2 22
 
4.1%
4 20
 
3.8%
0 19
 
3.6%
Other values (6) 59
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 682
56.2%
ASCII 532
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
36.1%
1 62
 
11.7%
) 44
 
8.3%
( 44
 
8.3%
, 24
 
4.5%
3 24
 
4.5%
5 22
 
4.1%
2 22
 
4.1%
4 20
 
3.8%
0 19
 
3.6%
Other values (6) 59
 
11.1%
Hangul
ValueCountFrequency (%)
도 69
 
10.1%
봉 65
 
9.5%
동 45
 
6.6%
시 45
 
6.6%
로 44
 
6.5%
울 43
 
6.3%
서 43
 
6.3%
특 43
 
6.3%
구 43
 
6.3%
별 43
 
6.3%
Other values (45) 199
29.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)78.8%
Missing14
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean9375.8788
Minimum1303
Maximum132928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-04-17T18:41:48.402115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1303
5-th percentile1305
Q11368
median1405
Q31463
95-th percentile54060.4
Maximum132928
Range131625
Interquartile range (IQR)95

Descriptive statistics

Standard deviation31868.896
Coefficient of variation (CV)3.3990303
Kurtosis13.735587
Mean9375.8788
Median Absolute Deviation (MAD)51
Skewness3.8607359
Sum309404
Variance1.0156265 × 109
MonotonicityNot monotonic
2024-04-17T18:41:48.523416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1357 3
 
6.4%
132928 2
 
4.3%
1391 2
 
4.3%
1305 2
 
4.3%
1463 2
 
4.3%
1394 2
 
4.3%
1392 1
 
2.1%
1368 1
 
2.1%
1437 1
 
2.1%
1456 1
 
2.1%
Other values (16) 16
34.0%
(Missing) 14
29.8%
ValueCountFrequency (%)
1303 1
 
2.1%
1305 2
4.3%
1307 1
 
2.1%
1339 1
 
2.1%
1357 3
6.4%
1368 1
 
2.1%
1371 1
 
2.1%
1378 1
 
2.1%
1391 2
4.3%
1392 1
 
2.1%
ValueCountFrequency (%)
132928 2
4.3%
1482 1
2.1%
1480 1
2.1%
1475 1
2.1%
1473 1
2.1%
1468 1
2.1%
1467 1
2.1%
1463 2
4.3%
1462 1
2.1%
1456 1
2.1%

사업장명
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-04-17T18:41:48.713269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.5106383
Min length2

Characters and Unicode

Total characters306
Distinct characters101
Distinct categories4 ?
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 (%)95.7%

Sample

1st row(주)농협유통창동농산물종합유통센터
2nd row원일
3rd row두영푸드
4th row아침을여는소리
5th row(주)초램푸드
ValueCountFrequency (%)
주)청풍에프앤비 2
 
4.2%
계림푸드 1
 
2.1%
엠티엠코리아 1
 
2.1%
고려푸드 1
 
2.1%
다복식품 1
 
2.1%
진흥유통 1
 
2.1%
주)초램에프앤비 1
 
2.1%
우진축산유통 1
 
2.1%
한국푸드 1
 
2.1%
대영식품 1
 
2.1%
Other values (37) 37
77.1%
2024-04-17T18:41:49.038246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 22
 
7.2%
) 22
 
7.2%
주 21
 
6.9%
드 15
 
4.9%
푸 15
 
4.9%
유 9
 
2.9%
통 9
 
2.9%
산 8
 
2.6%
에 8
 
2.6%
이 7
 
2.3%
Other values (91) 170
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
85.3%
Open Punctuation 22
 
7.2%
Close Punctuation 22
 
7.2%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 21
 
8.0%
드 15
 
5.7%
푸 15
 
5.7%
유 9
 
3.4%
통 9
 
3.4%
산 8
 
3.1%
에 8
 
3.1%
이 7
 
2.7%
축 7
 
2.7%
프 6
 
2.3%
Other values (88) 156
59.8%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
85.3%
Common 45
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 21
 
8.0%
드 15
 
5.7%
푸 15
 
5.7%
유 9
 
3.4%
통 9
 
3.4%
산 8
 
3.1%
에 8
 
3.1%
이 7
 
2.7%
축 7
 
2.7%
프 6
 
2.3%
Other values (88) 156
59.8%
Common
ValueCountFrequency (%)
( 22
48.9%
) 22
48.9%
1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
85.3%
ASCII 45
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 22
48.9%
) 22
48.9%
1
 
2.2%
Hangul
ValueCountFrequency (%)
주 21
 
8.0%
드 15
 
5.7%
푸 15
 
5.7%
유 9
 
3.4%
통 9
 
3.4%
산 8
 
3.1%
에 8
 
3.1%
이 7
 
2.7%
축 7
 
2.7%
프 6
 
2.3%
Other values (88) 156
59.8%

최종수정일자
Date

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2005-12-19 17:11:14
Maximum2024-01-30 10:37:52
2024-04-17T18:41:49.150968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:41:49.289253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
I
24 
U
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 24
51.1%
U 23
48.9%

Length

2024-04-17T18:41:49.422313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:49.523691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 24
51.1%
u 23
48.9%

데이터갱신일자
Date

Distinct26
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:01:00
2024-04-17T18:41:49.604422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:41:49.707235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)100.0%
Memory size555.0 B

좌표정보(X)
Real number (ℝ)

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203199.91
Minimum201081.92
Maximum204413.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-04-17T18:41:49.816317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201081.92
5-th percentile202009.59
Q1202965.14
median203343.89
Q3203659.99
95-th percentile203956.4
Maximum204413.62
Range3331.7013
Interquartile range (IQR)694.85431

Descriptive statistics

Standard deviation672.96218
Coefficient of variation (CV)0.0033118233
Kurtosis1.6849689
Mean203199.91
Median Absolute Deviation (MAD)333.98233
Skewness-1.1208194
Sum9550395.6
Variance452878.1
MonotonicityNot monotonic
2024-04-17T18:41:49.951247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
202965.140259028 3
 
6.4%
202416.898467468 2
 
4.3%
202653.936948157 2
 
4.3%
203263.492432035 2
 
4.3%
203679.797117952 2
 
4.3%
204413.616574592 1
 
2.1%
203960.176959544 1
 
2.1%
203593.652658526 1
 
2.1%
203755.716811907 1
 
2.1%
203277.211111661 1
 
2.1%
Other values (31) 31
66.0%
ValueCountFrequency (%)
201081.915285607 1
 
2.1%
201476.197702978 1
 
2.1%
201982.940320854 1
 
2.1%
202071.777661249 1
 
2.1%
202086.916519443 1
 
2.1%
202416.898467468 2
4.3%
202653.936948157 2
4.3%
202774.049156763 1
 
2.1%
202965.140259028 3
6.4%
202969.88787309 1
 
2.1%
ValueCountFrequency (%)
204413.616574592 1
2.1%
204335.318536601 1
2.1%
203960.176959544 1
2.1%
203947.573077127 1
2.1%
203820.343025697 1
2.1%
203798.027921181 1
2.1%
203755.716811907 1
2.1%
203679.797117952 2
4.3%
203677.876735134 1
2.1%
203674.053106921 1
2.1%

좌표정보(Y)
Real number (ℝ)

Distinct41
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean461554.3
Minimum458968.63
Maximum464725.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-04-17T18:41:50.078001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum458968.63
5-th percentile459289.64
Q1460339.53
median461886.03
Q3462513.84
95-th percentile464069.25
Maximum464725.2
Range5756.5773
Interquartile range (IQR)2174.3075

Descriptive statistics

Standard deviation1451.5728
Coefficient of variation (CV)0.0031449666
Kurtosis-0.60049286
Mean461554.3
Median Absolute Deviation (MAD)1003.8356
Skewness0.12725471
Sum21693052
Variance2107063.7
MonotonicityNot monotonic
2024-04-17T18:41:50.188963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
462601.382384114 3
 
6.4%
462426.291677059 2
 
4.3%
460273.492375925 2
 
4.3%
461886.031581086 2
 
4.3%
462001.107837054 2
 
4.3%
461378.588676784 1
 
2.1%
464725.202550965 1
 
2.1%
464139.818411299 1
 
2.1%
459047.53542317 1
 
2.1%
462040.42369558 1
 
2.1%
Other values (31) 31
66.0%
ValueCountFrequency (%)
458968.625259996 1
2.1%
459047.53542317 1
2.1%
459243.225833224 1
2.1%
459397.936022073 1
2.1%
459591.562029978 1
2.1%
459652.383093424 1
2.1%
459750.995837076 1
2.1%
460093.406417139 1
2.1%
460135.037622894 1
2.1%
460217.962531613 1
2.1%
ValueCountFrequency (%)
464725.202550965 1
 
2.1%
464139.818411299 1
 
2.1%
464134.681988189 1
 
2.1%
463916.564720703 1
 
2.1%
463892.861101303 1
 
2.1%
463122.733898401 1
 
2.1%
463112.28908706 1
 
2.1%
462889.867202427 1
 
2.1%
462678.710083685 1
 
2.1%
462601.382384114 3
6.4%

축산업무구분명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
식육포장처리업
37 
<NA>
10 

Length

Max length7
Median length7
Mean length6.3617021
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 37
78.7%
<NA> 10
 
21.3%

Length

2024-04-17T18:41:50.598695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:50.675298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 37
78.7%
na 10
 
21.3%

축산물가공업구분명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
식육포장처리업
37 
<NA>
10 

Length

Max length7
Median length7
Mean length6.3617021
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 37
78.7%
<NA> 10
 
21.3%

Length

2024-04-17T18:41:50.777899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:50.861206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 37
78.7%
na 10
 
21.3%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
<NA>
45 
0
 
2

Length

Max length4
Median length4
Mean length3.8723404
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> 45
95.7%
0 2
 
4.3%

Length

2024-04-17T18:41:50.944786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:51.034940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
95.7%
0 2
 
4.3%

권리주체일련번호
Categorical

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
000
22 
L00
15 
<NA>
10 

Length

Max length4
Median length3
Mean length3.212766
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 22
46.8%
L00 15
31.9%
<NA> 10
21.3%

Length

2024-04-17T18:41:51.121320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:51.212515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 22
46.8%
l00 15
31.9%
na 10
21.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
<NA>
45 
0
 
2

Length

Max length4
Median length4
Mean length3.8723404
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> 45
95.7%
0 2
 
4.3%

Length

2024-04-17T18:41:51.303320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:41:51.388507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
95.7%
0 2
 
4.3%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0309000030900000042000000120050507<NA>3폐업2폐업20051219<NA><NA><NA>3499-6000152.8<NA>서울특별시 도봉구 창동 1-10번지서울특별시 도봉구 마들로11길 20 (창동)<NA>(주)농협유통창동농산물종합유통센터2005-12-19 17:11:14I2018-08-31 23:59:59.0<NA>204413.616575461378.588677식육포장처리업식육포장처리업<NA>L00<NA>
1309000030900000042004001020041215<NA>3폐업2폐업20190927<NA><NA><NA><NA>31.65<NA>서울특별시 도봉구 쌍문동 36-8번지서울특별시 도봉구 방학로5길 76 (쌍문동)1394원일2019-09-27 14:22:00U2019-09-29 02:40:00.0<NA>203263.492432461886.031581식육포장처리업식육포장처리업<NA>000<NA>
2309000030900000042005000520051014<NA>3폐업2폐업20060411<NA><NA><NA>907-5253143.0<NA>서울특별시 도봉구 방학동 307-2번지 주상복합 102호서울특별시 도봉구 시루봉로 149, 102호 (방학동,주상복합)<NA>두영푸드2006-04-11 11:36:37I2018-08-31 23:59:59.0<NA>202416.898467462426.291677식육포장처리업식육포장처리업<NA>000<NA>
3309000030900000042006000320060726<NA>3폐업2폐업20130219<NA><NA><NA><NA>104.0<NA>서울특별시 도봉구 방학동 307-2번지 주상복합 102호서울특별시 도봉구 시루봉로 149, 102호 (방학동,주상복합)<NA>아침을여는소리2013-02-19 14:41:40I2018-08-31 23:59:59.0<NA>202416.898467462426.291677식육포장처리업식육포장처리업<NA>000<NA>
4309000030900000042006000420061212<NA>3폐업2폐업20140318<NA><NA><NA>900-11190.0<NA>서울특별시 도봉구 쌍문동 103-200번지 지층서울특별시 도봉구 도봉로103길 23 (쌍문동,지층)<NA>(주)초램푸드2014-03-18 13:34:50I2018-08-31 23:59:59.0<NA>202653.936948460273.492376식육포장처리업식육포장처리업<NA>L00<NA>
5309000030900000042007000220070206<NA>2휴업1휴업<NA>2019040220221230<NA>956-11240.0<NA>서울특별시 도봉구 방학동 622-37번지서울특별시 도봉구 도당로13바길 45 (방학동)<NA>광석유통2019-04-02 16:35:33U2019-04-04 02:40:00.0<NA>203092.920212462889.867202식육포장처리업식육포장처리업<NA>000<NA>
6309000030900000042007000320070416<NA>3폐업2폐업20180919<NA><NA><NA><NA>61.7<NA>서울특별시 도봉구 쌍문동 709-23번지서울특별시 도봉구 도봉로141길 39 (쌍문동)<NA>대진유통2018-09-19 14:48:25U2018-09-19 23:59:59.0<NA>203442.818959462131.221765식육포장처리업식육포장처리업<NA>000<NA>
7309000030900000042008000320080519<NA>3폐업2폐업20150526<NA><NA><NA>955-96440.0<NA>서울특별시 도봉구 방학동 462-1번지 ,465-5(1동)서울특별시 도봉구 방학로15길 5 (방학동,,465-5(1동))<NA>혜성유통2015-05-26 17:02:38I2018-08-31 23:59:59.0<NA>202071.777661462086.586268식육포장처리업식육포장처리업<NA>000<NA>
8309000030900000042008000520080618<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 창동 715-45번지서울특별시 도봉구 도봉로130길 13-13 (창동)<NA>파인앤푸드2016-04-07 16:56:35I2018-08-31 23:59:59.0<NA>203411.604483461427.640258식육포장처리업식육포장처리업<NA>000<NA>
9309000030900000042008000620080930<NA>3폐업2폐업20100804<NA><NA><NA>070-8283-63210.0<NA>서울특별시 도봉구 도봉동 619-11번지 1층서울특별시 도봉구 도당로29길 72 (도봉동,1층)<NA>(주)서울이푸드2010-08-04 13:55:54I2018-08-31 23:59:59.0<NA>203674.053107463112.289087식육포장처리업식육포장처리업<NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
37309000030900001042016000120160608<NA>3폐업2폐업20180709<NA><NA><NA>02 90786310.0<NA>서울특별시 도봉구 쌍문동 103-222번지서울특별시 도봉구 우이천로24길 64 (쌍문동)1448원푸드2018-07-09 13:36:52I2018-08-31 23:59:59.0<NA>202774.049157460405.566754식육포장처리업식육포장처리업<NA>000<NA>
38309000030900001042016000220160624<NA>1영업/정상0정상<NA><NA><NA><NA>02-907-62550.0<NA>서울특별시 도봉구 창동 562-27서울특별시 도봉구 덕릉로60다길 4 (창동)1473진축산물유통2020-11-03 14:01:08U2020-11-05 02:40:00.0<NA>203466.566466459591.56203식육포장처리업식육포장처리업<NA>000<NA>
3930900003090000104201700012017-01-12<NA>3폐업2폐업2023-07-21<NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 창동 609-57 지1층서울특별시 도봉구 덕릉로63길 65, 지1층 (창동)1463제이제이미트2023-07-21 13:31:13U2022-12-06 22:03:00.0<NA>203482.417062460217.962532<NA><NA><NA><NA><NA>
40309000030900001042017000220171222<NA>3폐업2폐업20190808<NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 방학동 701-9번지서울특별시 도봉구 도당로 110, 1층 (방학동)1339한울축산2019-08-08 13:23:27U2019-08-10 02:40:00.0<NA>203343.894408462678.710084식육포장처리업식육포장처리업<NA>000<NA>
41309000030900001042018000120181207<NA>4취소/말소/만료/정지/중지3행정처분20221226<NA><NA><NA>02-954-89510.0<NA>서울특별시 도봉구 도봉동 596-9 퍼스트빌오피스텔 101호, 102호일부서울특별시 도봉구 도봉로165길 14, 1층 101,102 일부호 (도봉동, 퍼스트빌오피스텔)1307(주)천지향2022-12-27 10:44:50U2021-11-01 22:09:00.0<NA>203820.343026463892.861101<NA><NA><NA><NA><NA>
42309000030900001042019000120111116<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 방학동 632-38번지 1층서울특별시 도봉구 도당로13길 29-8, 1층 (방학동)1357(주)청풍에프앤비2019-01-24 09:55:53I2019-01-26 02:21:01.0<NA>202965.140259462601.382384식육포장처리업식육포장처리업<NA>L00<NA>
43309000030900001042019000220191022<NA>3폐업2폐업20210128<NA><NA><NA>02-991-20180.0<NA>서울특별시 도봉구 쌍문동 36-8 1층서울특별시 도봉구 방학로5길 76, 1층 (쌍문동)1394성은유통2021-01-28 14:58:15U2021-01-30 02:40:00.0<NA>203263.492432461886.031581식육포장처리업식육포장처리업<NA>000<NA>
44309000030900001042020000120200217<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 창동 664-44 1층 (창1동)서울특별시 도봉구 노해로62길 58, 1층 (창동)1456(주)신선엘앤비2021-11-10 13:45:17U2021-11-12 02:40:00.0<NA>203278.298075460698.606968식육포장처리업식육포장처리업0L000
45309000030900001042022000120111116<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 방학동 632-38 1층서울특별시 도봉구 도당로13길 29-8, 1층 (방학동)1357(주) 엠티엠코리아2022-09-13 09:34:21U2021-12-08 23:05:00.0<NA>202965.140259462601.382384<NA><NA><NA><NA><NA>
4630900003090000104202400012024-01-30<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 도봉구 쌍문동 81-202서울특별시 도봉구 도봉로123길 8, 1층 (쌍문동)1437수미트정육2024-01-30 10:37:52I2023-12-02 00:01:00.0<NA>203150.611964461151.1386<NA><NA><NA><NA><NA>