Overview

Dataset statistics

Number of variables30
Number of observations69
Missing cells336
Missing cells (%)16.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.2 KiB
Average record size in memory255.9 B

Variable types

Categorical13
Numeric5
DateTime5
Unsupported3
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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18108/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (56.3%)Imbalance
영업상태명 is highly imbalanced (56.3%)Imbalance
상세영업상태코드 is highly imbalanced (56.3%)Imbalance
상세영업상태명 is highly imbalanced (56.3%)Imbalance
휴업시작일자 is highly imbalanced (83.7%)Imbalance
업태구분명 is highly imbalanced (81.1%)Imbalance
축산업무구분명 is highly imbalanced (57.4%)Imbalance
축산물가공업구분명 is highly imbalanced (66.3%)Imbalance
축산일련번호 is highly imbalanced (62.5%)Imbalance
총인원 is highly imbalanced (62.5%)Imbalance
인허가취소일자 has 69 (100.0%) missing valuesMissing
폐업일자 has 11 (15.9%) missing valuesMissing
휴업종료일자 has 69 (100.0%) missing valuesMissing
재개업일자 has 52 (75.4%) missing valuesMissing
전화번호 has 24 (34.8%) missing valuesMissing
소재지우편번호 has 69 (100.0%) missing valuesMissing
도로명주소 has 1 (1.4%) missing valuesMissing
도로명우편번호 has 37 (53.6%) missing valuesMissing
좌표정보(X) has 2 (2.9%) missing valuesMissing
좌표정보(Y) has 2 (2.9%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
소재지면적 has 62 (89.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:30:10.872522
Analysis finished2024-05-11 06:30:11.656532
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
3060000
69 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 69
100.0%

Length

2024-05-11T15:30:11.768722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:11.940246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 69
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.06 × 1017
Minimum3.06 × 1017
Maximum3.06 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T15:30:12.160179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.06 × 1017
5-th percentile3.06 × 1017
Q13.06 × 1017
median3.06 × 1017
Q33.06 × 1017
95-th percentile3.06 × 1017
Maximum3.06 × 1017
Range240001
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation56749.353
Coefficient of variation (CV)1.854554 × 10-13
Kurtosis0.061282657
Mean3.06 × 1017
Median Absolute Deviation (MAD)40000
Skewness0.56993979
Sum2.667256 × 1018
Variance3.2204891 × 109
MonotonicityStrictly increasing
2024-05-11T15:30:12.417856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306000000419990001 1
 
1.4%
306000000420100005 1
 
1.4%
306000000420120004 1
 
1.4%
306000000420120003 1
 
1.4%
306000000420120002 1
 
1.4%
306000000420120001 1
 
1.4%
306000000420110002 1
 
1.4%
306000000420110001 1
 
1.4%
306000000420100004 1
 
1.4%
306000000420130002 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
306000000419990001 1
1.4%
306000000420000001 1
1.4%
306000000420000002 1
1.4%
306000000420010001 1
1.4%
306000000420010002 1
1.4%
306000000420010004 1
1.4%
306000000420020001 1
1.4%
306000000420020003 1
1.4%
306000000420020004 1
1.4%
306000000420030001 1
1.4%
ValueCountFrequency (%)
306000000420230002 1
1.4%
306000000420230001 1
1.4%
306000000420220001 1
1.4%
306000000420210001 1
1.4%
306000000420200001 1
1.4%
306000000420170001 1
1.4%
306000000420160002 1
1.4%
306000000420160001 1
1.4%
306000000420150002 1
1.4%
306000000420150001 1
1.4%

인허가일자
Date

Distinct66
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum1999-09-10 00:00:00
Maximum2023-05-28 00:00:00
2024-05-11T15:30:12.660622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:12.908540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
3
57 
1
8 
2
 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
3 57
82.6%
1 8
 
11.6%
2 3
 
4.3%
4 1
 
1.4%

Length

2024-05-11T15:30:13.135150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:13.321125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 57
82.6%
1 8
 
11.6%
2 3
 
4.3%
4 1
 
1.4%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
폐업
57 
영업/정상
8 
휴업
 
3
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length2.5217391
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 57
82.6%
영업/정상 8
 
11.6%
휴업 3
 
4.3%
취소/말소/만료/정지/중지 1
 
1.4%

Length

2024-05-11T15:30:13.505862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:13.668513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 57
82.6%
영업/정상 8
 
11.6%
휴업 3
 
4.3%
취소/말소/만료/정지/중지 1
 
1.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
2
57 
0
8 
1
 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
2 57
82.6%
0 8
 
11.6%
1 3
 
4.3%
4 1
 
1.4%

Length

2024-05-11T15:30:13.838256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:14.017591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 57
82.6%
0 8
 
11.6%
1 3
 
4.3%
4 1
 
1.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
폐업
57 
정상
8 
휴업
 
3
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 57
82.6%
정상 8
 
11.6%
휴업 3
 
4.3%
말소 1
 
1.4%

Length

2024-05-11T15:30:14.211745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:14.422625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 57
82.6%
정상 8
 
11.6%
휴업 3
 
4.3%
말소 1
 
1.4%

폐업일자
Date

MISSING 

Distinct55
Distinct (%)94.8%
Missing11
Missing (%)15.9%
Memory size684.0 B
Minimum2004-01-15 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T15:30:14.629487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:14.840798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
<NA>
66 
20210226
 
1
20140429
 
1
20160307
 
1

Length

Max length8
Median length4
Mean length4.173913
Min length4

Unique

Unique3 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
95.7%
20210226 1
 
1.4%
20140429 1
 
1.4%
20160307 1
 
1.4%

Length

2024-05-11T15:30:15.067481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:15.676238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
95.7%
20210226 1
 
1.4%
20140429 1
 
1.4%
20160307 1
 
1.4%

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

재개업일자
Date

MISSING 

Distinct17
Distinct (%)100.0%
Missing52
Missing (%)75.4%
Memory size684.0 B
Minimum2016-11-23 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T15:30:15.833279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:16.022762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

전화번호
Text

MISSING 

Distinct44
Distinct (%)97.8%
Missing24
Missing (%)34.8%
Memory size684.0 B
2024-05-11T15:30:16.397864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length9.2444444
Min length8

Characters and Unicode

Total characters416
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

Unique43 ?
Unique (%)95.6%

Sample

1st row437-1322
2nd row434-7300
3rd row433-1949
4th row495-8293
5th row975-6381
ValueCountFrequency (%)
02-2208-5678 2
 
4.4%
2246-6634 1
 
2.2%
437-8727 1
 
2.2%
2207-6668 1
 
2.2%
968-6166 1
 
2.2%
2208-2959 1
 
2.2%
070-8163-3886 1
 
2.2%
070-8822-9989 1
 
2.2%
493-8918 1
 
2.2%
2207-3680 1
 
2.2%
Other values (34) 34
75.6%
2024-05-11T15:30:17.048167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
13.9%
2 47
11.3%
4 46
11.1%
9 46
11.1%
0 45
10.8%
3 45
10.8%
8 44
10.6%
6 30
7.2%
7 22
 
5.3%
5 18
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 358
86.1%
Dash Punctuation 58
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 47
13.1%
4 46
12.8%
9 46
12.8%
0 45
12.6%
3 45
12.6%
8 44
12.3%
6 30
8.4%
7 22
6.1%
5 18
 
5.0%
1 15
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 416
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
13.9%
2 47
11.3%
4 46
11.1%
9 46
11.1%
0 45
10.8%
3 45
10.8%
8 44
10.6%
6 30
7.2%
7 22
 
5.3%
5 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
13.9%
2 47
11.3%
4 46
11.1%
9 46
11.1%
0 45
10.8%
3 45
10.8%
8 44
10.6%
6 30
7.2%
7 22
 
5.3%
5 18
 
4.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.901159
Minimum0
Maximum292
Zeros62
Zeros (%)89.9%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T15:30:17.241040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile139.52
Maximum292
Range292
Interquartile range (IQR)0

Descriptive statistics

Standard deviation59.610539
Coefficient of variation (CV)3.329982
Kurtosis12.215375
Mean17.901159
Median Absolute Deviation (MAD)0
Skewness3.5603232
Sum1235.18
Variance3553.4164
MonotonicityNot monotonic
2024-05-11T15:30:17.443422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 62
89.9%
241.6 1
 
1.4%
140.0 1
 
1.4%
95.44 1
 
1.4%
67.34 1
 
1.4%
138.8 1
 
1.4%
292.0 1
 
1.4%
260.0 1
 
1.4%
ValueCountFrequency (%)
0.0 62
89.9%
67.34 1
 
1.4%
95.44 1
 
1.4%
138.8 1
 
1.4%
140.0 1
 
1.4%
241.6 1
 
1.4%
260.0 1
 
1.4%
292.0 1
 
1.4%
ValueCountFrequency (%)
292.0 1
 
1.4%
260.0 1
 
1.4%
241.6 1
 
1.4%
140.0 1
 
1.4%
138.8 1
 
1.4%
95.44 1
 
1.4%
67.34 1
 
1.4%
0.0 62
89.9%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

지번주소
Text

Distinct67
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T15:30:17.879831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length35
Mean length23.115942
Min length18

Characters and Unicode

Total characters1595
Distinct characters57
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)94.2%

Sample

1st row서울특별시 중랑구 묵동 108-3번지
2nd row서울특별시 중랑구 면목동 485-8번지
3rd row서울특별시 중랑구 면목동 148-31번지
4th row서울특별시 중랑구 망우동 444-33번지
5th row서울특별시 중랑구 망우동 184-19
ValueCountFrequency (%)
서울특별시 69
23.2%
중랑구 69
23.2%
면목동 27
 
9.1%
망우동 14
 
4.7%
상봉동 12
 
4.0%
1층 8
 
2.7%
중화동 6
 
2.0%
묵동 5
 
1.7%
신내동 5
 
1.7%
지하 4
 
1.3%
Other values (76) 79
26.5%
2024-05-11T15:30:18.660109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
292
18.3%
1 80
 
5.0%
중 75
 
4.7%
서 70
 
4.4%
랑 69
 
4.3%
동 69
 
4.3%
구 69
 
4.3%
울 69
 
4.3%
시 69
 
4.3%
별 69
 
4.3%
Other values (47) 664
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 899
56.4%
Decimal Number 325
 
20.4%
Space Separator 292
 
18.3%
Dash Punctuation 67
 
4.2%
Lowercase Letter 6
 
0.4%
Uppercase Letter 3
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 75
 
8.3%
서 70
 
7.8%
랑 69
 
7.7%
동 69
 
7.7%
구 69
 
7.7%
울 69
 
7.7%
시 69
 
7.7%
별 69
 
7.7%
특 69
 
7.7%
지 59
 
6.6%
Other values (24) 212
23.6%
Decimal Number
ValueCountFrequency (%)
1 80
24.6%
2 45
13.8%
3 44
13.5%
4 34
10.5%
8 27
 
8.3%
7 22
 
6.8%
6 20
 
6.2%
5 20
 
6.2%
0 19
 
5.8%
9 14
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
t 1
16.7%
c 1
16.7%
n 1
16.7%
r 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
S 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
292
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 899
56.4%
Common 687
43.1%
Latin 9
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 75
 
8.3%
서 70
 
7.8%
랑 69
 
7.7%
동 69
 
7.7%
구 69
 
7.7%
울 69
 
7.7%
시 69
 
7.7%
별 69
 
7.7%
특 69
 
7.7%
지 59
 
6.6%
Other values (24) 212
23.6%
Common
ValueCountFrequency (%)
292
42.5%
1 80
 
11.6%
- 67
 
9.8%
2 45
 
6.6%
3 44
 
6.4%
4 34
 
4.9%
8 27
 
3.9%
7 22
 
3.2%
6 20
 
2.9%
5 20
 
2.9%
Other values (5) 36
 
5.2%
Latin
ValueCountFrequency (%)
e 2
22.2%
V 1
11.1%
S 1
11.1%
K 1
11.1%
t 1
11.1%
c 1
11.1%
n 1
11.1%
r 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 899
56.4%
ASCII 696
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
292
42.0%
1 80
 
11.5%
- 67
 
9.6%
2 45
 
6.5%
3 44
 
6.3%
4 34
 
4.9%
8 27
 
3.9%
7 22
 
3.2%
6 20
 
2.9%
5 20
 
2.9%
Other values (13) 45
 
6.5%
Hangul
ValueCountFrequency (%)
중 75
 
8.3%
서 70
 
7.8%
랑 69
 
7.7%
동 69
 
7.7%
구 69
 
7.7%
울 69
 
7.7%
시 69
 
7.7%
별 69
 
7.7%
특 69
 
7.7%
지 59
 
6.6%
Other values (24) 212
23.6%

도로명주소
Text

MISSING 

Distinct67
Distinct (%)98.5%
Missing1
Missing (%)1.4%
Memory size684.0 B
2024-05-11T15:30:19.115568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length36
Mean length27.5
Min length22

Characters and Unicode

Total characters1870
Distinct characters85
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row서울특별시 중랑구 숙선옹주로3길 20-37 (묵동)
2nd row서울특별시 중랑구 용마산로72길 26 (면목동)
3rd row서울특별시 중랑구 겸재로 135 (면목동)
4th row서울특별시 중랑구 용마산로100길 7-9 (망우동)
5th row서울특별시 중랑구 용마산로114길 35 (망우동)
ValueCountFrequency (%)
서울특별시 68
18.9%
중랑구 68
18.9%
면목동 21
 
5.8%
망우동 13
 
3.6%
상봉동 9
 
2.5%
1층 9
 
2.5%
중화동 6
 
1.7%
신내동 5
 
1.4%
망우로 4
 
1.1%
묵동 4
 
1.1%
Other values (123) 152
42.3%
2024-05-11T15:30:19.819287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
291
 
15.6%
중 84
 
4.5%
랑 76
 
4.1%
동 75
 
4.0%
서 69
 
3.7%
( 69
 
3.7%
) 69
 
3.7%
특 68
 
3.6%
별 68
 
3.6%
시 68
 
3.6%
Other values (75) 933
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1092
58.4%
Decimal Number 294
 
15.7%
Space Separator 291
 
15.6%
Open Punctuation 69
 
3.7%
Close Punctuation 69
 
3.7%
Other Punctuation 27
 
1.4%
Dash Punctuation 14
 
0.7%
Uppercase Letter 8
 
0.4%
Lowercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 84
 
7.7%
랑 76
 
7.0%
동 75
 
6.9%
서 69
 
6.3%
특 68
 
6.2%
별 68
 
6.2%
시 68
 
6.2%
구 68
 
6.2%
울 68
 
6.2%
로 67
 
6.1%
Other values (50) 381
34.9%
Decimal Number
ValueCountFrequency (%)
1 66
22.4%
3 35
11.9%
2 34
11.6%
6 28
9.5%
0 26
 
8.8%
5 25
 
8.5%
9 25
 
8.5%
7 24
 
8.2%
4 16
 
5.4%
8 15
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 4
50.0%
V 1
 
12.5%
K 1
 
12.5%
S 1
 
12.5%
F 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
r 1
16.7%
t 1
16.7%
n 1
16.7%
c 1
16.7%
Space Separator
ValueCountFrequency (%)
291
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1092
58.4%
Common 764
40.9%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 84
 
7.7%
랑 76
 
7.0%
동 75
 
6.9%
서 69
 
6.3%
특 68
 
6.2%
별 68
 
6.2%
시 68
 
6.2%
구 68
 
6.2%
울 68
 
6.2%
로 67
 
6.1%
Other values (50) 381
34.9%
Common
ValueCountFrequency (%)
291
38.1%
( 69
 
9.0%
) 69
 
9.0%
1 66
 
8.6%
3 35
 
4.6%
2 34
 
4.5%
6 28
 
3.7%
, 27
 
3.5%
0 26
 
3.4%
5 25
 
3.3%
Other values (5) 94
 
12.3%
Latin
ValueCountFrequency (%)
B 4
28.6%
e 2
14.3%
r 1
 
7.1%
t 1
 
7.1%
n 1
 
7.1%
c 1
 
7.1%
V 1
 
7.1%
K 1
 
7.1%
S 1
 
7.1%
F 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1092
58.4%
ASCII 778
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
291
37.4%
( 69
 
8.9%
) 69
 
8.9%
1 66
 
8.5%
3 35
 
4.5%
2 34
 
4.4%
6 28
 
3.6%
, 27
 
3.5%
0 26
 
3.3%
5 25
 
3.2%
Other values (15) 108
 
13.9%
Hangul
ValueCountFrequency (%)
중 84
 
7.7%
랑 76
 
7.0%
동 75
 
6.9%
서 69
 
6.3%
특 68
 
6.2%
별 68
 
6.2%
시 68
 
6.2%
구 68
 
6.2%
울 68
 
6.2%
로 67
 
6.1%
Other values (50) 381
34.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)90.6%
Missing37
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean2138.6562
Minimum2009
Maximum2262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T15:30:20.057009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2049.75
Q12075.25
median2143.5
Q32191.5
95-th percentile2239.45
Maximum2262
Range253
Interquartile range (IQR)116.25

Descriptive statistics

Standard deviation70.934595
Coefficient of variation (CV)0.033167834
Kurtosis-1.1619738
Mean2138.6562
Median Absolute Deviation (MAD)63.5
Skewness0.045929514
Sum68437
Variance5031.7167
MonotonicityNot monotonic
2024-05-11T15:30:20.323521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2151 2
 
2.9%
2239 2
 
2.9%
2052 2
 
2.9%
2188 1
 
1.4%
2210 1
 
1.4%
2055 1
 
1.4%
2262 1
 
1.4%
2123 1
 
1.4%
2064 1
 
1.4%
2100 1
 
1.4%
Other values (19) 19
27.5%
(Missing) 37
53.6%
ValueCountFrequency (%)
2009 1
1.4%
2047 1
1.4%
2052 2
2.9%
2055 1
1.4%
2057 1
1.4%
2060 1
1.4%
2064 1
1.4%
2079 1
1.4%
2081 1
1.4%
2090 1
1.4%
ValueCountFrequency (%)
2262 1
1.4%
2240 1
1.4%
2239 2
2.9%
2235 1
1.4%
2223 1
1.4%
2210 1
1.4%
2202 1
1.4%
2188 1
1.4%
2180 1
1.4%
2177 1
1.4%

사업장명
Text

Distinct66
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-05-11T15:30:20.752788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.826087
Min length2

Characters and Unicode

Total characters402
Distinct characters154
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)91.3%

Sample

1st row내츄럴코리아
2nd row나래실업
3rd row한국식품
4th row대화식품
5th row(주)토담푸드시스템
ValueCountFrequency (%)
피그뱅크 2
 
2.6%
또바기c&f 2
 
2.6%
한국식품 2
 
2.6%
외식사업부 2
 
2.6%
food 2
 
2.6%
미트 1
 
1.3%
명성유통 1
 
1.3%
육쌈fㆍs 1
 
1.3%
최가네 1
 
1.3%
빽가네 1
 
1.3%
Other values (61) 61
80.3%
2024-05-11T15:30:21.392091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 18
 
4.5%
드 15
 
3.7%
푸 14
 
3.5%
주 14
 
3.5%
품 14
 
3.5%
) 13
 
3.2%
( 13
 
3.2%
스 9
 
2.2%
통 8
 
2.0%
조 8
 
2.0%
Other values (144) 276
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
83.6%
Uppercase Letter 17
 
4.2%
Close Punctuation 13
 
3.2%
Open Punctuation 13
 
3.2%
Lowercase Letter 11
 
2.7%
Space Separator 7
 
1.7%
Other Punctuation 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 18
 
5.4%
드 15
 
4.5%
푸 14
 
4.2%
주 14
 
4.2%
품 14
 
4.2%
스 9
 
2.7%
통 8
 
2.4%
조 8
 
2.4%
유 8
 
2.4%
가 6
 
1.8%
Other values (124) 222
66.1%
Uppercase Letter
ValueCountFrequency (%)
F 6
35.3%
C 3
17.6%
S 2
 
11.8%
J 2
 
11.8%
A 1
 
5.9%
K 1
 
5.9%
R 1
 
5.9%
H 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o 4
36.4%
d 2
18.2%
p 1
 
9.1%
m 1
 
9.1%
a 1
 
9.1%
b 1
 
9.1%
i 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
& 4
80.0%
; 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
83.6%
Common 38
 
9.5%
Latin 28
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 18
 
5.4%
드 15
 
4.5%
푸 14
 
4.2%
주 14
 
4.2%
품 14
 
4.2%
스 9
 
2.7%
통 8
 
2.4%
조 8
 
2.4%
유 8
 
2.4%
가 6
 
1.8%
Other values (124) 222
66.1%
Latin
ValueCountFrequency (%)
F 6
21.4%
o 4
14.3%
C 3
10.7%
S 2
 
7.1%
J 2
 
7.1%
d 2
 
7.1%
A 1
 
3.6%
K 1
 
3.6%
p 1
 
3.6%
m 1
 
3.6%
Other values (5) 5
17.9%
Common
ValueCountFrequency (%)
) 13
34.2%
( 13
34.2%
7
18.4%
& 4
 
10.5%
; 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
83.3%
ASCII 66
 
16.4%
Compat Jamo 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 18
 
5.4%
드 15
 
4.5%
푸 14
 
4.2%
주 14
 
4.2%
품 14
 
4.2%
스 9
 
2.7%
통 8
 
2.4%
조 8
 
2.4%
유 8
 
2.4%
가 6
 
1.8%
Other values (123) 221
66.0%
ASCII
ValueCountFrequency (%)
) 13
19.7%
( 13
19.7%
7
10.6%
F 6
9.1%
& 4
 
6.1%
o 4
 
6.1%
C 3
 
4.5%
S 2
 
3.0%
J 2
 
3.0%
d 2
 
3.0%
Other values (10) 10
15.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

최종수정일자
Date

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2004-01-15 16:19:52
Maximum2024-03-28 11:33:12
2024-05-11T15:30:21.620749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:21.812947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
I
50 
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 rowU

Common Values

ValueCountFrequency (%)
I 50
72.5%
U 19
 
27.5%

Length

2024-05-11T15:30:22.013107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:22.156504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 50
72.5%
u 19
 
27.5%

데이터갱신일자
Date

Distinct21
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 21:00:00
2024-05-11T15:30:22.321665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:22.539528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
식육가공업
67 
유가공업
 
2

Length

Max length5
Median length5
Mean length4.9710145
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 67
97.1%
유가공업 2
 
2.9%

Length

2024-05-11T15:30:22.827577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:22.993834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 67
97.1%
유가공업 2
 
2.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)92.5%
Missing2
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean207693.91
Minimum206427.61
Maximum209962.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T15:30:23.187230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206427.61
5-th percentile206460.91
Q1206950.53
median207522.63
Q3208266.71
95-th percentile209126.19
Maximum209962.62
Range3535.0137
Interquartile range (IQR)1316.18

Descriptive statistics

Standard deviation900.00592
Coefficient of variation (CV)0.0043333284
Kurtosis-0.71845816
Mean207693.91
Median Absolute Deviation (MAD)666.08638
Skewness0.40936063
Sum13915492
Variance810010.65
MonotonicityNot monotonic
2024-05-11T15:30:23.435337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206459.826550004 2
 
2.9%
208057.253444122 2
 
2.9%
207492.994660644 2
 
2.9%
207240.203538516 2
 
2.9%
206552.009352104 2
 
2.9%
207833.758010423 1
 
1.4%
208264.133937348 1
 
1.4%
207028.807748135 1
 
1.4%
207451.84713864 1
 
1.4%
208988.782670363 1
 
1.4%
Other values (52) 52
75.4%
(Missing) 2
 
2.9%
ValueCountFrequency (%)
206427.607358 1
1.4%
206448.588999211 1
1.4%
206459.826550004 2
2.9%
206463.443740034 1
1.4%
206463.679691053 1
1.4%
206542.720631531 1
1.4%
206552.009352104 2
2.9%
206618.331572056 1
1.4%
206646.148252341 1
1.4%
206699.691110426 1
1.4%
ValueCountFrequency (%)
209962.62104219 1
1.4%
209438.885311392 1
1.4%
209273.955704494 1
1.4%
209143.442116387 1
1.4%
209085.926142332 1
1.4%
209033.513918057 1
1.4%
208988.782670363 1
1.4%
208959.348350532 1
1.4%
208927.261281462 1
1.4%
208891.219127331 1
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)92.5%
Missing2
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean454702.38
Minimum452208.73
Maximum457482.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-05-11T15:30:23.701911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452208.73
5-th percentile452866.52
Q1453909.79
median454667.03
Q3455497.8
95-th percentile457055.47
Maximum457482.82
Range5274.0953
Interquartile range (IQR)1588.0099

Descriptive statistics

Standard deviation1247.455
Coefficient of variation (CV)0.0027434539
Kurtosis-0.26289377
Mean454702.38
Median Absolute Deviation (MAD)823.80017
Skewness0.26564831
Sum30465060
Variance1556144
MonotonicityNot monotonic
2024-05-11T15:30:24.023169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454507.434629541 2
 
2.9%
455529.10588782 2
 
2.9%
452925.135117861 2
 
2.9%
453909.786684907 2
 
2.9%
457086.477069066 2
 
2.9%
454265.208696177 1
 
1.4%
455115.821921217 1
 
1.4%
455903.802240136 1
 
1.4%
452604.378404364 1
 
1.4%
455082.310320787 1
 
1.4%
Other values (52) 52
75.4%
(Missing) 2
 
2.9%
ValueCountFrequency (%)
452208.729385467 1
1.4%
452226.040112475 1
1.4%
452604.378404364 1
1.4%
452841.395493848 1
1.4%
452925.135117861 2
2.9%
453082.617210688 1
1.4%
453177.317399649 1
1.4%
453189.388414533 1
1.4%
453455.76151331 1
1.4%
453467.801145799 1
1.4%
ValueCountFrequency (%)
457482.82473114 1
1.4%
457283.215342184 1
1.4%
457086.477069066 2
2.9%
456983.124478907 1
1.4%
456970.943858708 1
1.4%
456744.005243414 1
1.4%
456260.349692319 1
1.4%
456210.158404317 1
1.4%
456080.632250222 1
1.4%
455903.802240136 1
1.4%

축산업무구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
축산물가공업
63 
<NA>
 
6

Length

Max length6
Median length6
Mean length5.826087
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 63
91.3%
<NA> 6
 
8.7%

Length

2024-05-11T15:30:24.254949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:24.463944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 63
91.3%
na 6
 
8.7%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size684.0 B
식육가공업
62 
<NA>
 
6
유가공업
 
1

Length

Max length5
Median length5
Mean length4.8985507
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 62
89.9%
<NA> 6
 
8.7%
유가공업 1
 
1.4%

Length

2024-05-11T15:30:24.685080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:24.893114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 62
89.9%
na 6
 
8.7%
유가공업 1
 
1.4%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
<NA>
64 
0
 
5

Length

Max length4
Median length4
Mean length3.7826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 64
92.8%
0 5
 
7.2%

Length

2024-05-11T15:30:25.123841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:25.294796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 64
92.8%
0 5
 
7.2%

권리주체일련번호
Categorical

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size684.0 B
000
48 
L00
15 
<NA>
6 

Length

Max length4
Median length3
Mean length3.0869565
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 48
69.6%
L00 15
 
21.7%
<NA> 6
 
8.7%

Length

2024-05-11T15:30:25.463460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:25.635273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 48
69.6%
l00 15
 
21.7%
na 6
 
8.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
<NA>
64 
0
 
5

Length

Max length4
Median length4
Mean length3.7826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 64
92.8%
0 5
 
7.2%

Length

2024-05-11T15:30:25.806236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:25.966187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 64
92.8%
0 5
 
7.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0306000030600000041999000119990910<NA>3폐업2폐업20040115<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 묵동 108-3번지서울특별시 중랑구 숙선옹주로3길 20-37 (묵동)<NA>내츄럴코리아2004-01-15 16:19:52I2018-08-31 23:59:59.0식육가공업207044.305767456970.943859축산물가공업식육가공업<NA>000<NA>
1306000030600000042000000120000302<NA>3폐업2폐업20050126<NA><NA><NA>437-13220.0<NA>서울특별시 중랑구 면목동 485-8번지서울특별시 중랑구 용마산로72길 26 (면목동)<NA>나래실업2005-01-26 10:09:30I2018-08-31 23:59:59.0식육가공업208340.817738453467.801146축산물가공업식육가공업<NA>000<NA>
2306000030600000042000000220000620<NA>3폐업2폐업20040315<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 148-31번지서울특별시 중랑구 겸재로 135 (면목동)<NA>한국식품2004-03-15 15:36:49I2018-08-31 23:59:59.0식육가공업207240.203539453909.786685축산물가공업식육가공업<NA>000<NA>
3306000030600000042001000120010113<NA>3폐업2폐업20040811<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 망우동 444-33번지서울특별시 중랑구 용마산로100길 7-9 (망우동)<NA>대화식품2004-08-11 13:28:06I2018-08-31 23:59:59.0식육가공업208660.50807454406.371956축산물가공업식육가공업<NA>000<NA>
4306000030600000042001000220010608<NA>3폐업2폐업20210715<NA><NA>20210715434-73000.0<NA>서울특별시 중랑구 망우동 184-19서울특별시 중랑구 용마산로114길 35 (망우동)2177(주)토담푸드시스템2021-07-15 16:03:48U2021-07-17 02:40:00.0식육가공업209033.513918455222.775712축산물가공업식육가공업0L000
5306000030600000042001000420010220<NA>3폐업2폐업20040315<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 148-31번지서울특별시 중랑구 겸재로 135 (면목동)<NA>한국식품2004-03-15 15:37:41I2018-08-31 23:59:59.0유가공업207240.203539453909.786685축산물가공업유가공업<NA>000<NA>
6306000030600000042002000120020524<NA>1영업/정상0정상<NA><NA><NA><NA>433-19490.0<NA>서울특별시 중랑구 면목동 170-7서울특별시 중랑구 동일로 569-3(면목동)2235(주)씨엠에프앤비2022-07-14 16:52:52U2021-12-06 23:06:00.0식육가공업206916.930437453189.388415<NA><NA><NA><NA><NA>
7306000030600000042002000320020725<NA>3폐업2폐업20040531<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 면목동 170-6번지서울특별시 중랑구 동일로 569-9 (면목동)<NA>서울유통2004-05-31 10:15:30I2018-08-31 23:59:59.0식육가공업206912.458822453177.3174축산물가공업식육가공업<NA>000<NA>
8306000030600000042002000420021017<NA>3폐업2폐업20040322<NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 중화동 320-123번지서울특별시 중랑구 중랑역로13길 13 (중화동)<NA>진성2004-03-22 09:24:58I2018-08-31 23:59:59.0식육가공업206542.720632454918.438455축산물가공업식육가공업<NA>000<NA>
9306000030600000042003000120030513<NA>3폐업2폐업20101108<NA><NA><NA>495-8293241.6<NA>서울특별시 중랑구 면목동 718-2번지 지하1층서울특별시 중랑구 동일로 467 (면목동,지하1층)<NA>진푸드시스템2010-11-09 10:59:13I2018-08-31 23:59:59.0식육가공업206984.138058452208.729385축산물가공업식육가공업<NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
59306000030600000042015000120150123<NA>2휴업1휴업<NA>20160307<NA><NA>433-49830.0<NA>서울특별시 중랑구 중화동 329-17번지 1층서울특별시 중랑구 봉화산로4길 16, 1층 (중화동)2100금바위2016-03-07 17:28:39I2018-08-31 23:59:59.0식육가공업206646.148252455392.54534축산물가공업식육가공업<NA>000<NA>
60306000030600000042015000220151218<NA>3폐업2폐업20161123<NA><NA>2016112302-2208-56780.0<NA>서울특별시 중랑구 면목동 632-2번지 1층서울특별시 중랑구 사가정로50길 51, 1층 (면목동)2239피그뱅크 외식사업부2016-11-23 17:41:23I2018-08-31 23:59:59.0식육가공업207492.994661452925.135118축산물가공업식육가공업<NA>L00<NA>
61306000030600000042016000120160613<NA>3폐업2폐업20161130<NA><NA>2016113002-434-33920.0<NA>서울특별시 중랑구 상봉동 88-38번지서울특별시 중랑구 상봉로25길 36, 1층 (상봉동)2151대신푸드2016-11-30 11:01:07I2018-08-31 23:59:59.0식육가공업207965.056021454740.589379축산물가공업식육가공업<NA>000<NA>
62306000030600000042016000220161213<NA>3폐업2폐업20180705<NA><NA>20180705070-8711-15800.0<NA>서울특별시 중랑구 망우동 136-19번지 1층서울특별시 중랑구 망우로81길 18, 1층 (망우동)2064일우푸드2018-07-05 10:40:56I2018-08-31 23:59:59.0식육가공업209438.885311455455.433742축산물가공업식육가공업<NA>000<NA>
63306000030600000042017000120170602<NA>3폐업2폐업20170927<NA><NA>2017092702-2208-56780.0<NA>서울특별시 중랑구 면목동 632-2번지서울특별시 중랑구 사가정로50길 51, 1층 (면목동, 열방교회)2239피그뱅크 외식사업부2017-09-27 11:37:07I2018-08-31 23:59:59.0식육가공업207492.994661452925.135118축산물가공업식육가공업<NA>L00<NA>
64306000030600000042020000120200107<NA>1영업/정상0정상<NA><NA><NA><NA>02-2208-29590.0<NA>서울특별시 중랑구 상봉동 127-1번지서울특별시 중랑구 동일로109가길 26 (상봉동)2123또바기C&F2020-01-07 14:38:36I2020-01-09 00:23:25.0식육가공업206895.707424454535.046493축산물가공업식육가공업<NA>000<NA>
65306000030600000042021000120191101<NA>1영업/정상0정상<NA><NA><NA><NA>02-6402-33090.0<NA>서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center B205,B206,B207호 (신내동)2262(주)헤비스테이크 헤비푸드2021-12-21 12:38:17I2021-12-23 00:22:42.0식육가공업<NA><NA>축산물가공업식육가공업0L000
6630600003060000004202200012022-06-07<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중랑구 신내동 262-1서울특별시 중랑구 신내역로3길 40-36, 지하2층 FB220호 (신내동)2055주식회사 몬스터플레이스2024-02-03 15:57:43U2023-12-02 00:05:00.0유가공업209085.926142457283.215342<NA><NA><NA><NA><NA>
6730600003060000004202300012023-01-02<NA>3폐업2폐업2024-03-28<NA><NA>2024-03-28<NA>0.0<NA>서울특별시 중랑구 면목동 428-3서울특별시 중랑구 면목로56길 22, 1층 (면목동)2210포정2024-03-28 11:33:12U2023-12-02 21:00:00.0식육가공업207846.361559453519.526878<NA><NA><NA><NA><NA>
6830600003060000004202300022023-05-28<NA>1영업/정상0정상<NA><NA><NA><NA>02-900-4569260.0<NA>서울특별시 중랑구 신내동 273-11서울특별시 중랑구 용마산로139나길 101, 2층 (신내동)2052좋은사람들협동조합2023-05-28 16:17:54I2022-12-04 21:01:00.0식육가공업209143.442116457482.824731<NA><NA><NA><NA><NA>