Overview

Dataset statistics

Number of variables30
Number of observations28
Missing cells203
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory260.7 B

Variable types

Categorical13
Numeric5
DateTime2
Unsupported6
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18121/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (62.8%)Imbalance
영업상태명 is highly imbalanced (62.8%)Imbalance
상세영업상태코드 is highly imbalanced (62.8%)Imbalance
상세영업상태명 is highly imbalanced (62.8%)Imbalance
재개업일자 is highly imbalanced (72.1%)Imbalance
소재지면적 is highly imbalanced (62.2%)Imbalance
데이터갱신구분 is highly imbalanced (50.9%)Imbalance
데이터갱신일자 is highly imbalanced (66.9%)Imbalance
업태구분명 is highly imbalanced (77.8%)Imbalance
축산업무구분명 is highly imbalanced (77.8%)Imbalance
축산물가공업구분명 is highly imbalanced (72.1%)Imbalance
인허가취소일자 has 28 (100.0%) missing valuesMissing
폐업일자 has 1 (3.6%) missing valuesMissing
휴업시작일자 has 28 (100.0%) missing valuesMissing
휴업종료일자 has 28 (100.0%) missing valuesMissing
전화번호 has 2 (7.1%) missing valuesMissing
소재지우편번호 has 28 (100.0%) missing valuesMissing
도로명주소 has 4 (14.3%) missing valuesMissing
도로명우편번호 has 20 (71.4%) missing valuesMissing
좌표정보(X) has 4 (14.3%) missing valuesMissing
좌표정보(Y) has 4 (14.3%) missing valuesMissing
축산일련번호 has 28 (100.0%) missing valuesMissing
총인원 has 28 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
축산일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 07:39:40.593765
Analysis finished2024-05-11 07:39:41.246124
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
3190000
28 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 28
100.0%

Length

2024-05-11T07:39:41.436067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:41.792176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 28
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.19 × 1017
Minimum3.19 × 1017
Maximum3.19 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T07:39:42.154046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.19 × 1017
5-th percentile3.19 × 1017
Q13.19 × 1017
median3.19 × 1017
Q33.19 × 1017
95-th percentile3.19 × 1017
Maximum3.19 × 1017
Range380000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation74200.384
Coefficient of variation (CV)2.3260308 × 10-13
Kurtosis6.4072141
Mean3.19 × 1017
Median Absolute Deviation (MAD)44992
Skewness-1.9025615
Sum8.932 × 1018
Variance5.505697 × 109
MonotonicityStrictly increasing
2024-05-11T07:39:42.671650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
319000000419780001 1
 
3.6%
319000000420080003 1
 
3.6%
319000000420160001 1
 
3.6%
319000000420150002 1
 
3.6%
319000000420150001 1
 
3.6%
319000000420130001 1
 
3.6%
319000000420120001 1
 
3.6%
319000000420100004 1
 
3.6%
319000000420100003 1
 
3.6%
319000000420100002 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
319000000419780001 1
3.6%
319000000419960001 1
3.6%
319000000419990001 1
3.6%
319000000420010001 1
3.6%
319000000420020001 1
3.6%
319000000420020002 1
3.6%
319000000420020003 1
3.6%
319000000420020004 1
3.6%
319000000420020005 1
3.6%
319000000420030001 1
3.6%
ValueCountFrequency (%)
319000000420160001 1
3.6%
319000000420150002 1
3.6%
319000000420150001 1
3.6%
319000000420130001 1
3.6%
319000000420120001 1
3.6%
319000000420100004 1
3.6%
319000000420100003 1
3.6%
319000000420100002 1
3.6%
319000000420100001 1
3.6%
319000000420090004 1
3.6%

인허가일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum1978-12-30 00:00:00
Maximum2016-04-27 00:00:00
2024-05-11T07:39:43.092533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:39:43.649181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
3
25 
4
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
3 25
89.3%
4 2
 
7.1%
1 1
 
3.6%

Length

2024-05-11T07:39:44.009727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:44.396482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 25
89.3%
4 2
 
7.1%
1 1
 
3.6%

영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
폐업
25 
취소/말소/만료/정지/중지
 
2
영업/정상
 
1

Length

Max length14
Median length2
Mean length2.9642857
Min length2

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 25
89.3%
취소/말소/만료/정지/중지 2
 
7.1%
영업/정상 1
 
3.6%

Length

2024-05-11T07:39:44.798311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:45.160226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 25
89.3%
취소/말소/만료/정지/중지 2
 
7.1%
영업/정상 1
 
3.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2
25 
3
 
2
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
2 25
89.3%
3 2
 
7.1%
0 1
 
3.6%

Length

2024-05-11T07:39:45.619446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:45.948943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 25
89.3%
3 2
 
7.1%
0 1
 
3.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
폐업
25 
행정처분
 
2
정상
 
1

Length

Max length4
Median length2
Mean length2.1428571
Min length2

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 25
89.3%
행정처분 2
 
7.1%
정상 1
 
3.6%

Length

2024-05-11T07:39:46.297769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:46.680216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 25
89.3%
행정처분 2
 
7.1%
정상 1
 
3.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)96.3%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean20093551
Minimum20020718
Maximum20201105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T07:39:46.998693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020718
5-th percentile20021009
Q120050130
median20100420
Q320125460
95-th percentile20181280
Maximum20201105
Range180387
Interquartile range (IQR)75329.5

Descriptive statistics

Standard deviation52578.069
Coefficient of variation (CV)0.0026166639
Kurtosis-0.79886008
Mean20093551
Median Absolute Deviation (MAD)40289
Skewness0.26737474
Sum5.4252587 × 108
Variance2.7644534 × 109
MonotonicityNot monotonic
2024-05-11T07:39:47.682259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
20040130 2
 
7.1%
20020718 1
 
3.6%
20110527 1
 
3.6%
20190225 1
 
3.6%
20160407 1
 
3.6%
20201105 1
 
3.6%
20130503 1
 
3.6%
20110630 1
 
3.6%
20120417 1
 
3.6%
20150428 1
 
3.6%
Other values (16) 16
57.1%
ValueCountFrequency (%)
20020718 1
3.6%
20020926 1
3.6%
20021204 1
3.6%
20030410 1
3.6%
20030616 1
3.6%
20040130 2
7.1%
20060131 1
3.6%
20060303 1
3.6%
20060510 1
3.6%
20060705 1
3.6%
ValueCountFrequency (%)
20201105 1
3.6%
20190225 1
3.6%
20160407 1
3.6%
20151229 1
3.6%
20150428 1
3.6%
20141226 1
3.6%
20130503 1
3.6%
20120417 1
3.6%
20120125 1
3.6%
20110804 1
3.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

재개업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
26 
20201105
 
1
20190225
 
1

Length

Max length8
Median length4
Mean length4.2857143
Min length4

Unique

Unique2 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 26
92.9%
20201105 1
 
3.6%
20190225 1
 
3.6%

Length

2024-05-11T07:39:48.205501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:48.615845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
92.9%
20201105 1
 
3.6%
20190225 1
 
3.6%

전화번호
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing2
Missing (%)7.1%
Memory size356.0 B
2024-05-11T07:39:49.008046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length9.1153846
Min length8

Characters and Unicode

Total characters237
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row814-2211
2nd row814-0532
3rd row823-6196
4th row584-2354
5th row812-4414
ValueCountFrequency (%)
02-2102-4527 2
 
7.4%
814-0532 1
 
3.7%
823-6196 1
 
3.7%
834-5987 1
 
3.7%
02-1644-1628 1
 
3.7%
584-9688 1
 
3.7%
6013-5900 1
 
3.7%
02-597-7741 1
 
3.7%
2102-4595 1
 
3.7%
02-3280-1560 1
 
3.7%
Other values (16) 16
59.3%
2024-05-11T07:39:50.124628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 34
14.3%
- 31
13.1%
5 26
11.0%
8 22
9.3%
4 21
8.9%
1 20
8.4%
0 19
8.0%
7 18
7.6%
6 16
6.8%
3 15
6.3%
Other values (3) 15
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
86.1%
Dash Punctuation 31
 
13.1%
Other Punctuation 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 34
16.7%
5 26
12.7%
8 22
10.8%
4 21
10.3%
1 20
9.8%
0 19
9.3%
7 18
8.8%
6 16
7.8%
3 15
7.4%
9 13
 
6.4%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 34
14.3%
- 31
13.1%
5 26
11.0%
8 22
9.3%
4 21
8.9%
1 20
8.4%
0 19
8.0%
7 18
7.6%
6 16
6.8%
3 15
6.3%
Other values (3) 15
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 34
14.3%
- 31
13.1%
5 26
11.0%
8 22
9.3%
4 21
8.9%
1 20
8.4%
0 19
8.0%
7 18
7.6%
6 16
6.8%
3 15
6.3%
Other values (3) 15
6.3%

소재지면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
24 
392.0
 
1
166.87
 
1
5158.0
 
1
251.0
 
1

Length

Max length6
Median length3
Mean length3.3571429
Min length3

Unique

Unique4 ?
Unique (%)14.3%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 24
85.7%
392.0 1
 
3.6%
166.87 1
 
3.6%
5158.0 1
 
3.6%
251.0 1
 
3.6%

Length

2024-05-11T07:39:50.642806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:51.005545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 24
85.7%
392.0 1
 
3.6%
166.87 1
 
3.6%
5158.0 1
 
3.6%
251.0 1
 
3.6%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

지번주소
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T07:39:51.564318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length26.392857
Min length22

Characters and Unicode

Total characters739
Distinct characters49
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

Unique26 ?
Unique (%)92.9%

Sample

1st row서울특별시 동작구 노량진동 13-8 번지
2nd row서울특별시 동작구 노량진동 13-8번지 지층
3rd row서울특별시 동작구 상도동 324-45번지 지층
4th row서울특별시 동작구 사당동 1031-35 번지
5th row서울특별시 동작구 상도동 204-17번지 지하1층
ValueCountFrequency (%)
서울특별시 28
19.6%
동작구 28
19.6%
사당동 9
 
6.3%
노량진동 8
 
5.6%
지하1층 6
 
4.2%
상도동 6
 
4.2%
1층 5
 
3.5%
13-8번지 4
 
2.8%
19-6번지 3
 
2.1%
번지 3
 
2.1%
Other values (38) 43
30.1%
2024-05-11T07:39:52.811306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
19.6%
동 61
 
8.3%
지 36
 
4.9%
1 34
 
4.6%
작 29
 
3.9%
서 28
 
3.8%
특 28
 
3.8%
별 28
 
3.8%
시 28
 
3.8%
구 28
 
3.8%
Other values (39) 294
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
57.0%
Space Separator 145
 
19.6%
Decimal Number 145
 
19.6%
Dash Punctuation 27
 
3.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 61
14.5%
지 36
 
8.6%
작 29
 
6.9%
서 28
 
6.7%
특 28
 
6.7%
별 28
 
6.7%
시 28
 
6.7%
구 28
 
6.7%
울 28
 
6.7%
번 26
 
6.2%
Other values (26) 101
24.0%
Decimal Number
ValueCountFrequency (%)
1 34
23.4%
3 26
17.9%
2 21
14.5%
6 11
 
7.6%
8 11
 
7.6%
5 10
 
6.9%
9 9
 
6.2%
4 8
 
5.5%
0 8
 
5.5%
7 7
 
4.8%
Space Separator
ValueCountFrequency (%)
145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
57.0%
Common 318
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 61
14.5%
지 36
 
8.6%
작 29
 
6.9%
서 28
 
6.7%
특 28
 
6.7%
별 28
 
6.7%
시 28
 
6.7%
구 28
 
6.7%
울 28
 
6.7%
번 26
 
6.2%
Other values (26) 101
24.0%
Common
ValueCountFrequency (%)
145
45.6%
1 34
 
10.7%
- 27
 
8.5%
3 26
 
8.2%
2 21
 
6.6%
6 11
 
3.5%
8 11
 
3.5%
5 10
 
3.1%
9 9
 
2.8%
4 8
 
2.5%
Other values (3) 16
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
57.0%
ASCII 318
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
45.6%
1 34
 
10.7%
- 27
 
8.5%
3 26
 
8.2%
2 21
 
6.6%
6 11
 
3.5%
8 11
 
3.5%
5 10
 
3.1%
9 9
 
2.8%
4 8
 
2.5%
Other values (3) 16
 
5.0%
Hangul
ValueCountFrequency (%)
동 61
14.5%
지 36
 
8.6%
작 29
 
6.9%
서 28
 
6.7%
특 28
 
6.7%
별 28
 
6.7%
시 28
 
6.7%
구 28
 
6.7%
울 28
 
6.7%
번 26
 
6.2%
Other values (26) 101
24.0%

도로명주소
Text

MISSING 

Distinct22
Distinct (%)91.7%
Missing4
Missing (%)14.3%
Memory size356.0 B
2024-05-11T07:39:53.498487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length30.041667
Min length25

Characters and Unicode

Total characters721
Distinct characters63
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

Unique20 ?
Unique (%)83.3%

Sample

1st row서울특별시 동작구 노들로 688 (노량진동,지층)
2nd row서울특별시 동작구 상도로12길 1 (상도동,지층)
3rd row서울특별시 동작구 장승배기로 35 (상도동,지하1층)
4th row서울특별시 동작구 사당로23나길 32 (사당동,지하)
5th row서울특별시 동작구 노들로 688 (노량진동,2동)
ValueCountFrequency (%)
서울특별시 24
17.8%
동작구 24
17.8%
1층 4
 
3.0%
노들로 4
 
3.0%
688 4
 
3.0%
사당동 4
 
3.0%
노들로2길 3
 
2.2%
44 3
 
2.2%
노량진동 3
 
2.2%
상도동,지하1층 3
 
2.2%
Other values (49) 59
43.7%
2024-05-11T07:39:54.807041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
15.4%
동 55
 
7.6%
2 28
 
3.9%
작 26
 
3.6%
1 25
 
3.5%
) 24
 
3.3%
울 24
 
3.3%
( 24
 
3.3%
서 24
 
3.3%
구 24
 
3.3%
Other values (53) 356
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
59.6%
Space Separator 111
 
15.4%
Decimal Number 109
 
15.1%
Close Punctuation 24
 
3.3%
Open Punctuation 24
 
3.3%
Other Punctuation 22
 
3.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 55
 
12.8%
작 26
 
6.0%
울 24
 
5.6%
서 24
 
5.6%
구 24
 
5.6%
시 24
 
5.6%
별 24
 
5.6%
특 24
 
5.6%
로 22
 
5.1%
길 19
 
4.4%
Other values (39) 164
38.1%
Decimal Number
ValueCountFrequency (%)
2 28
25.7%
1 25
22.9%
4 17
15.6%
3 11
 
10.1%
8 9
 
8.3%
6 8
 
7.3%
7 5
 
4.6%
5 4
 
3.7%
0 2
 
1.8%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 430
59.6%
Common 291
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 55
 
12.8%
작 26
 
6.0%
울 24
 
5.6%
서 24
 
5.6%
구 24
 
5.6%
시 24
 
5.6%
별 24
 
5.6%
특 24
 
5.6%
로 22
 
5.1%
길 19
 
4.4%
Other values (39) 164
38.1%
Common
ValueCountFrequency (%)
111
38.1%
2 28
 
9.6%
1 25
 
8.6%
) 24
 
8.2%
( 24
 
8.2%
, 22
 
7.6%
4 17
 
5.8%
3 11
 
3.8%
8 9
 
3.1%
6 8
 
2.7%
Other values (4) 12
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 430
59.6%
ASCII 291
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
38.1%
2 28
 
9.6%
1 25
 
8.6%
) 24
 
8.2%
( 24
 
8.2%
, 22
 
7.6%
4 17
 
5.8%
3 11
 
3.8%
8 9
 
3.1%
6 8
 
2.7%
Other values (4) 12
 
4.1%
Hangul
ValueCountFrequency (%)
동 55
 
12.8%
작 26
 
6.0%
울 24
 
5.6%
서 24
 
5.6%
구 24
 
5.6%
시 24
 
5.6%
별 24
 
5.6%
특 24
 
5.6%
로 22
 
5.1%
길 19
 
4.4%
Other values (39) 164
38.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing20
Missing (%)71.4%
Infinite0
Infinite (%)0.0%
Mean6970.875
Minimum6900
Maximum7056
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T07:39:55.336082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6900
5-th percentile6900
Q16900
median6986
Q37018.25
95-th percentile7044.1
Maximum7056
Range156
Interquartile range (IQR)118.25

Descriptive statistics

Standard deviation63.692201
Coefficient of variation (CV)0.0091369019
Kurtosis-1.9568047
Mean6970.875
Median Absolute Deviation (MAD)53
Skewness-0.12718971
Sum55767
Variance4056.6964
MonotonicityNot monotonic
2024-05-11T07:39:55.806127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6900 3
 
10.7%
6965 1
 
3.6%
7017 1
 
3.6%
7022 1
 
3.6%
7007 1
 
3.6%
7056 1
 
3.6%
(Missing) 20
71.4%
ValueCountFrequency (%)
6900 3
10.7%
6965 1
 
3.6%
7007 1
 
3.6%
7017 1
 
3.6%
7022 1
 
3.6%
7056 1
 
3.6%
ValueCountFrequency (%)
7056 1
 
3.6%
7022 1
 
3.6%
7017 1
 
3.6%
7007 1
 
3.6%
6965 1
 
3.6%
6900 3
10.7%

사업장명
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T07:39:56.468572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length6.4285714
Min length3

Characters and Unicode

Total characters180
Distinct characters94
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row노량진수산(주)
2nd row(주)창성유통냉장
3rd row탑유통
4th row과연유통
5th row아이푸드시스템
ValueCountFrequency (%)
탑유통 2
 
6.2%
주식회사 2
 
6.2%
두영푸드 1
 
3.1%
주)옥스팜 1
 
3.1%
주)케이미트리테일 1
 
3.1%
형성푸드 1
 
3.1%
주)만덕 1
 
3.1%
아놀드식품 1
 
3.1%
f&c 1
 
3.1%
선단 1
 
3.1%
Other values (20) 20
62.5%
2024-05-11T07:39:57.548380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 15
 
8.3%
) 11
 
6.1%
( 11
 
6.1%
유 8
 
4.4%
통 7
 
3.9%
4
 
2.2%
푸 4
 
2.2%
드 4
 
2.2%
식 4
 
2.2%
진 3
 
1.7%
Other values (84) 109
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143
79.4%
Close Punctuation 11
 
6.1%
Open Punctuation 11
 
6.1%
Uppercase Letter 6
 
3.3%
Space Separator 4
 
2.2%
Lowercase Letter 4
 
2.2%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 15
 
10.5%
유 8
 
5.6%
통 7
 
4.9%
푸 4
 
2.8%
드 4
 
2.8%
식 4
 
2.8%
진 3
 
2.1%
스 3
 
2.1%
에 3
 
2.1%
사 3
 
2.1%
Other values (71) 89
62.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
F 1
16.7%
T 1
16.7%
O 1
16.7%
B 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
a 1
25.0%
d 1
25.0%
r 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143
79.4%
Common 27
 
15.0%
Latin 10
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 15
 
10.5%
유 8
 
5.6%
통 7
 
4.9%
푸 4
 
2.8%
드 4
 
2.8%
식 4
 
2.8%
진 3
 
2.1%
스 3
 
2.1%
에 3
 
2.1%
사 3
 
2.1%
Other values (71) 89
62.2%
Latin
ValueCountFrequency (%)
C 2
20.0%
e 1
10.0%
F 1
10.0%
a 1
10.0%
d 1
10.0%
r 1
10.0%
T 1
10.0%
O 1
10.0%
B 1
10.0%
Common
ValueCountFrequency (%)
) 11
40.7%
( 11
40.7%
4
 
14.8%
& 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143
79.4%
ASCII 37
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 15
 
10.5%
유 8
 
5.6%
통 7
 
4.9%
푸 4
 
2.8%
드 4
 
2.8%
식 4
 
2.8%
진 3
 
2.1%
스 3
 
2.1%
에 3
 
2.1%
사 3
 
2.1%
Other values (71) 89
62.2%
ASCII
ValueCountFrequency (%)
) 11
29.7%
( 11
29.7%
4
 
10.8%
C 2
 
5.4%
& 1
 
2.7%
e 1
 
2.7%
F 1
 
2.7%
a 1
 
2.7%
d 1
 
2.7%
r 1
 
2.7%
Other values (3) 3
 
8.1%

최종수정일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2003-04-23 13:32:07
Maximum2023-11-24 09:25:49
2024-05-11T07:39:58.001165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:39:58.389528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
I
25 
U
3 

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 25
89.3%
U 3
 
10.7%

Length

2024-05-11T07:39:58.821392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:39:59.129511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 25
89.3%
u 3
 
10.7%

데이터갱신일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2018-08-31 23:59:59.0
25 
2022-10-31 22:06:00.0
 
1
2020-11-08 02:40:00.0
 
1
2019-03-29 02:40:00.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique3 ?
Unique (%)10.7%

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 25
89.3%
2022-10-31 22:06:00.0 1
 
3.6%
2020-11-08 02:40:00.0 1
 
3.6%
2019-03-29 02:40:00.0 1
 
3.6%

Length

2024-05-11T07:39:59.660282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:40:00.101534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 25
44.6%
23:59:59.0 25
44.6%
02:40:00.0 2
 
3.6%
2022-10-31 1
 
1.8%
22:06:00.0 1
 
1.8%
2020-11-08 1
 
1.8%
2019-03-29 1
 
1.8%

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
식육가공업
27 
유가공업
 
1

Length

Max length5
Median length5
Mean length4.9642857
Min length4

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 27
96.4%
유가공업 1
 
3.6%

Length

2024-05-11T07:40:00.584488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:40:01.058728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 27
96.4%
유가공업 1
 
3.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)75.0%
Missing4
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean195192.12
Minimum191934.54
Maximum198309.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T07:40:01.536364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191934.54
5-th percentile192989.3
Q1194164.6
median194807.85
Q3196836.24
95-th percentile197773.76
Maximum198309.48
Range6374.9486
Interquartile range (IQR)2671.6387

Descriptive statistics

Standard deviation1737.0489
Coefficient of variation (CV)0.0088991751
Kurtosis-0.78503862
Mean195192.12
Median Absolute Deviation (MAD)1044.726
Skewness0.33679373
Sum4684610.9
Variance3017338.7
MonotonicityNot monotonic
2024-05-11T07:40:02.249547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
194807.845295028 4
14.3%
194164.599446001 3
 
10.7%
193763.119312416 2
 
7.1%
194717.085222389 1
 
3.6%
195108.679841021 1
 
3.6%
192949.075285477 1
 
3.6%
197755.308447853 1
 
3.6%
197476.079374251 1
 
3.6%
194422.119122943 1
 
3.6%
197443.32517735 1
 
3.6%
Other values (8) 8
28.6%
(Missing) 4
14.3%
ValueCountFrequency (%)
191934.535683403 1
 
3.6%
192949.075285477 1
 
3.6%
193217.235162753 1
 
3.6%
193763.119312416 2
7.1%
194164.599446001 3
10.7%
194371.731980389 1
 
3.6%
194422.119122943 1
 
3.6%
194717.085222389 1
 
3.6%
194807.845295028 4
14.3%
195108.679841021 1
 
3.6%
ValueCountFrequency (%)
198309.48428538 1
 
3.6%
197777.011469613 1
 
3.6%
197755.308447853 1
 
3.6%
197476.079374251 1
 
3.6%
197443.32517735 1
 
3.6%
197343.9236695 1
 
3.6%
196667.009683215 1
 
3.6%
195866.875661685 1
 
3.6%
195108.679841021 1
 
3.6%
194807.845295028 4
14.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)75.0%
Missing4
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean444267.63
Minimum441783.94
Maximum445901.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T07:40:02.981949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441783.94
5-th percentile442080.99
Q1443234.36
median444234.97
Q3445820.88
95-th percentile445901.41
Maximum445901.41
Range4117.4718
Interquartile range (IQR)2586.5217

Descriptive statistics

Standard deviation1351.107
Coefficient of variation (CV)0.0030412006
Kurtosis-1.0940254
Mean444267.63
Median Absolute Deviation (MAD)1328.2835
Skewness-0.24139933
Sum10662423
Variance1825490.1
MonotonicityNot monotonic
2024-05-11T07:40:03.590125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
445901.413432497 4
14.3%
445820.883711428 3
 
10.7%
444141.345270519 2
 
7.1%
444328.602132261 1
 
3.6%
444600.535977835 1
 
3.6%
443988.889876564 1
 
3.6%
442816.510442795 1
 
3.6%
441783.941628155 1
 
3.6%
443649.637984534 1
 
3.6%
442045.629562077 1
 
3.6%
Other values (8) 8
28.6%
(Missing) 4
14.3%
ValueCountFrequency (%)
441783.941628155 1
3.6%
442045.629562077 1
3.6%
442281.380042586 1
3.6%
442816.510442795 1
3.6%
442837.646055861 1
3.6%
443046.068752519 1
3.6%
443297.126419923 1
3.6%
443649.637984534 1
3.6%
443857.95106714 1
3.6%
443988.889876564 1
3.6%
ValueCountFrequency (%)
445901.413432497 4
14.3%
445820.883711428 3
10.7%
445494.213046084 1
 
3.6%
444639.881380692 1
 
3.6%
444600.535977835 1
 
3.6%
444404.199767662 1
 
3.6%
444328.602132261 1
 
3.6%
444141.345270519 2
7.1%
443988.889876564 1
 
3.6%
443857.95106714 1
 
3.6%

축산업무구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
축산물가공업
27 
<NA>
 
1

Length

Max length6
Median length6
Mean length5.9285714
Min length4

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 27
96.4%
<NA> 1
 
3.6%

Length

2024-05-11T07:40:04.160879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:40:04.622546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 27
96.4%
na 1
 
3.6%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
식육가공업
26 
유가공업
 
1
<NA>
 
1

Length

Max length5
Median length5
Mean length4.9285714
Min length4

Unique

Unique2 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 26
92.9%
유가공업 1
 
3.6%
<NA> 1
 
3.6%

Length

2024-05-11T07:40:04.962434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:40:05.305589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 26
92.9%
유가공업 1
 
3.6%
na 1
 
3.6%

축산일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

권리주체일련번호
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
000
16 
L00
11 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0357143
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
000 16
57.1%
L00 11
39.3%
<NA> 1
 
3.6%

Length

2024-05-11T07:40:05.678903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:40:06.067529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 16
57.1%
l00 11
39.3%
na 1
 
3.6%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0319000031900000041978000119781230<NA>3폐업2폐업20020718<NA><NA><NA>814-22110.0<NA>서울특별시 동작구 노량진동 13-8 번지<NA><NA>노량진수산(주)2003-04-23 13:39:51I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>L00<NA>
1319000031900000041996000119961226<NA>3폐업2폐업20030616<NA><NA><NA>814-05320.0<NA>서울특별시 동작구 노량진동 13-8번지 지층서울특별시 동작구 노들로 688 (노량진동,지층)<NA>(주)창성유통냉장2003-06-16 17:58:42I2018-08-31 23:59:59.0식육가공업194807.845295445901.413432축산물가공업식육가공업<NA>000<NA>
2319000031900000041999000119990401<NA>3폐업2폐업20060303<NA><NA><NA>823-61960.0<NA>서울특별시 동작구 상도동 324-45번지 지층서울특별시 동작구 상도로12길 1 (상도동,지층)<NA>탑유통2006-03-03 18:10:10I2018-08-31 23:59:59.0식육가공업193763.119312444141.345271축산물가공업식육가공업<NA>000<NA>
3319000031900000042001000120011123<NA>3폐업2폐업20020926<NA><NA><NA>584-23540.0<NA>서울특별시 동작구 사당동 1031-35 번지<NA><NA>과연유통2003-04-23 13:35:46I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
4319000031900000042002000120020501<NA>3폐업2폐업20090310<NA><NA><NA>812-44140.0<NA>서울특별시 동작구 상도동 204-17번지 지하1층서울특별시 동작구 장승배기로 35 (상도동,지하1층)<NA>아이푸드시스템2015-07-31 13:05:05I2018-08-31 23:59:59.0식육가공업194717.085222444328.602132축산물가공업식육가공업<NA>000<NA>
5319000031900000042002000220020827<NA>3폐업2폐업20060510<NA><NA><NA>536-71520.0<NA>서울특별시 동작구 사당동 39-4번지 18<NA><NA>(주)제주흑돼지유통2006-05-10 18:07:38I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>L00<NA>
6319000031900000042002000320021113<NA>3폐업2폐업20040130<NA><NA><NA>3477-66680.0<NA>서울특별시 동작구 사당동 162-95번지 지하서울특별시 동작구 사당로23나길 32 (사당동,지하)<NA>우사랑2004-01-30 11:29:58I2018-08-31 23:59:59.0식육가공업197777.01147442837.646056축산물가공업식육가공업<NA>000<NA>
7319000031900000042002000420020821<NA>3폐업2폐업20030410<NA><NA><NA>598-71290.0<NA>서울특별시 동작구 사당동 272-35 번지<NA><NA>일등유통2003-04-23 13:32:07I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
8319000031900000042002000520020724<NA>3폐업2폐업20021204<NA><NA><NA>823-55580.0<NA>서울특별시 동작구 노량진동 13-8번지 2동서울특별시 동작구 노들로 688 (노량진동,2동)<NA>(주)한국해큰물냉장2003-04-23 13:36:13I2018-08-31 23:59:59.0식육가공업194807.845295445901.413432축산물가공업식육가공업<NA>L00<NA>
9319000031900000042003000120030130<NA>3폐업2폐업20040130<NA><NA><NA>823-70700.0<NA>서울특별시 동작구 노량진동 13-8번지 3동서울특별시 동작구 노들로 688 (노량진동,3동)<NA>(주)견우마을2004-01-30 16:35:12I2018-08-31 23:59:59.0식육가공업194807.845295445901.413432축산물가공업식육가공업<NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
18319000031900000042009000420091023<NA>3폐업2폐업20100420<NA><NA><NA><NA>166.87<NA>서울특별시 동작구 상도동 196-56번지서울특별시 동작구 상도로22길 34 (상도동)<NA>담양궁중떡갈비2010-04-21 12:50:23I2018-08-31 23:59:59.0식육가공업194371.73198444404.199768축산물가공업식육가공업<NA>000<NA>
19319000031900000042010000120100129<NA>3폐업2폐업20151229<NA><NA><NA>02-3280-15600.0<NA>서울특별시 동작구 상도동 155-7번지 2층 203호서울특별시 동작구 상도로34길 27, 2층 203호 (상도동)6965호연유가공2015-12-29 15:04:07I2018-08-31 23:59:59.0유가공업195108.679841444600.535978축산물가공업유가공업<NA>000<NA>
20319000031900000042010000220100421<NA>3폐업2폐업20150428<NA><NA><NA>2102-45955158.0<NA>서울특별시 동작구 노량진동 19-6번지 한냉빌딩 1층서울특별시 동작구 노들로2길 44, 1층 (노량진동)6900주식회사 푸주2015-04-28 15:15:01I2018-08-31 23:59:59.0식육가공업194164.599446445820.883711축산물가공업식육가공업<NA>L00<NA>
21319000031900000042010000320100707<NA>3폐업2폐업20120417<NA><NA><NA>02-597-77410.0<NA>서울특별시 동작구 사당동 309-3번지서울특별시 동작구 사당로16길 71 (사당동)7017(주)청산리벽계수2012-04-17 19:17:41I2018-08-31 23:59:59.0식육가공업197443.325177442045.629562축산물가공업식육가공업<NA>L00<NA>
22319000031900000042010000420101109<NA>3폐업2폐업20110630<NA><NA><NA>6013-5900251.0<NA>서울특별시 동작구 상도동 279-433번지 지하1층서울특별시 동작구 성대로12길 74 (상도동,지하1층)<NA>선단 F&C2011-06-30 15:08:11I2018-08-31 23:59:59.0식육가공업194422.119123443649.637985축산물가공업식육가공업<NA>000<NA>
23319000031900000042012000120120525<NA>3폐업2폐업20130503<NA><NA><NA>584-96880.0<NA>서울특별시 동작구 사당동 303-73번지 지하1층 및 1층서울특별시 동작구 남부순환로255다길 41 (사당동, 지하1층 및 1층)7022아놀드식품2013-05-03 16:03:32I2018-08-31 23:59:59.0식육가공업197476.079374441783.941628축산물가공업식육가공업<NA>000<NA>
2431900003190000004201300012013-07-01<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 동작구 사당동 162-63 지하2층서울특별시 동작구 사당로23나길 24, 지하2층 (사당동)7007(주)만덕2023-11-24 09:25:49U2022-10-31 22:06:00.0식육가공업197755.308448442816.510443<NA><NA><NA><NA><NA>
25319000031900000042015000120150203<NA>3폐업2폐업20201105<NA><NA>2020110502-1644-16280.0<NA>서울특별시 동작구 신대방동 362-28 2층서울특별시 동작구 여의대방로24길 14, 2층 (신대방동)7056형성푸드2020-11-06 12:23:27U2020-11-08 02:40:00.0식육가공업192949.075285443988.889877축산물가공업식육가공업<NA>000<NA>
26319000031900000042015000220151112<NA>3폐업2폐업20160407<NA><NA><NA>02-2102-45270.0<NA>서울특별시 동작구 노량진동 19-6번지 1층서울특별시 동작구 노들로2길 44, 1층 (노량진동, 케이미트)6900(주)케이미트리테일2016-04-07 13:03:05I2018-08-31 23:59:59.0식육가공업194164.599446445820.883711축산물가공업식육가공업<NA>L00<NA>
27319000031900000042016000120160427<NA>3폐업2폐업20190225<NA><NA>2019022502-2102-4527, 44220.0<NA>서울특별시 동작구 노량진동 19-6번지 1층 좌측서울특별시 동작구 노들로2길 44, 1층 (노량진동, 케이미트)6900주식회사 선왕2019-03-27 12:19:22U2019-03-29 02:40:00.0식육가공업194164.599446445820.883711축산물가공업식육가공업<NA>L00<NA>