Overview

Dataset statistics

Number of variables30
Number of observations32
Missing cells172
Missing cells (%)17.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory258.1 B

Variable types

Categorical12
Numeric5
DateTime5
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
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-18113/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (79.9%)Imbalance
축산물가공업구분명 is highly imbalanced (53.4%)Imbalance
축산일련번호 is highly imbalanced (79.9%)Imbalance
총인원 is highly imbalanced (79.9%)Imbalance
인허가취소일자 has 32 (100.0%) missing valuesMissing
폐업일자 has 5 (15.6%) missing valuesMissing
휴업시작일자 has 32 (100.0%) missing valuesMissing
휴업종료일자 has 32 (100.0%) missing valuesMissing
재개업일자 has 17 (53.1%) missing valuesMissing
전화번호 has 8 (25.0%) missing valuesMissing
소재지우편번호 has 32 (100.0%) missing valuesMissing
도로명주소 has 7 (21.9%) missing valuesMissing
도로명우편번호 has 7 (21.9%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 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
소재지면적 has 23 (71.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:36:40.538829
Analysis finished2024-04-29 19:36:41.153956
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
3110000
32 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 32
100.0%

Length

2024-04-30T04:36:41.214856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:41.285258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 32
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.11 × 1017
Minimum3.11 × 1017
Maximum3.11 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T04:36:41.360458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.11 × 1017
5-th percentile3.11 × 1017
Q13.11 × 1017
median3.11 × 1017
Q33.11 × 1017
95-th percentile3.11 × 1017
Maximum3.11 × 1017
Range230000
Interquartile range (IQR)69952

Descriptive statistics

Standard deviation58024.479
Coefficient of variation (CV)1.8657389 × 10-13
Kurtosis-0.50985719
Mean3.11 × 1017
Median Absolute Deviation (MAD)40000
Skewness-0.17005904
Sum-8.4947441 × 1018
Variance3.3668401 × 109
MonotonicityStrictly increasing
2024-04-30T04:36:41.467541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
311000000419990001 1
 
3.1%
311000000420130001 1
 
3.1%
311000000420220001 1
 
3.1%
311000000420200001 1
 
3.1%
311000000420170001 1
 
3.1%
311000000420160002 1
 
3.1%
311000000420160001 1
 
3.1%
311000000420150001 1
 
3.1%
311000000420140001 1
 
3.1%
311000000420130008 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
311000000419990001 1
3.1%
311000000419990002 1
3.1%
311000000420010001 1
3.1%
311000000420030001 1
3.1%
311000000420030002 1
3.1%
311000000420040001 1
3.1%
311000000420050001 1
3.1%
311000000420060003 1
3.1%
311000000420060004 1
3.1%
311000000420060006 1
3.1%
ValueCountFrequency (%)
311000000420220001 1
3.1%
311000000420200001 1
3.1%
311000000420170001 1
3.1%
311000000420160002 1
3.1%
311000000420160001 1
3.1%
311000000420150001 1
3.1%
311000000420140001 1
3.1%
311000000420130008 1
3.1%
311000000420130007 1
3.1%
311000000420130006 1
3.1%

인허가일자
Date

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum1999-06-02 00:00:00
Maximum2022-10-17 00:00:00
2024-04-30T04:36:41.565077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:41.676092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
3
27 
1
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 27
84.4%
1 5
 
15.6%

Length

2024-04-30T04:36:41.792938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:41.868807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 27
84.4%
1 5
 
15.6%

영업상태명
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
폐업
27 
영업/정상
5 

Length

Max length5
Median length2
Mean length2.46875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 27
84.4%
영업/정상 5
 
15.6%

Length

2024-04-30T04:36:41.955562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:42.060419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 27
84.4%
영업/정상 5
 
15.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
2
27 
0
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 27
84.4%
0 5
 
15.6%

Length

2024-04-30T04:36:42.197428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:42.330424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 27
84.4%
0 5
 
15.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
폐업
27 
정상
5 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 27
84.4%
정상 5
 
15.6%

Length

2024-04-30T04:36:42.473775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:42.577435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 27
84.4%
정상 5
 
15.6%

폐업일자
Date

MISSING 

Distinct27
Distinct (%)100.0%
Missing5
Missing (%)15.6%
Memory size388.0 B
Minimum2003-11-11 00:00:00
Maximum2023-06-23 00:00:00
2024-04-30T04:36:42.655876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:42.750435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

재개업일자
Date

MISSING 

Distinct15
Distinct (%)100.0%
Missing17
Missing (%)53.1%
Memory size388.0 B
Minimum2017-01-24 00:00:00
Maximum2023-06-23 00:00:00
2024-04-30T04:36:42.838506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:42.928624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

전화번호
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing8
Missing (%)25.0%
Memory size388.0 B
2024-04-30T04:36:43.089162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.9166667
Min length8

Characters and Unicode

Total characters238
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

Unique24 ?
Unique (%)100.0%

Sample

1st row353-0092
2nd row383-1277
3rd row2291-8167
4th row359-6560
5th row376-0980
ValueCountFrequency (%)
3838-3838 1
 
4.2%
2291-8167 1
 
4.2%
02-2231-8801 1
 
4.2%
02-359-1754 1
 
4.2%
02-6012-3392 1
 
4.2%
02-383-8592 1
 
4.2%
02-306-4993 1
 
4.2%
02-389-3397 1
 
4.2%
02-303-0985 1
 
4.2%
070-8623-4627 1
 
4.2%
Other values (14) 14
58.3%
2024-04-30T04:36:43.352438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 37
15.5%
3 34
14.3%
0 33
13.9%
2 28
11.8%
8 20
8.4%
5 20
8.4%
7 16
6.7%
9 15
6.3%
1 14
 
5.9%
4 12
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
84.5%
Dash Punctuation 37
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 34
16.9%
0 33
16.4%
2 28
13.9%
8 20
10.0%
5 20
10.0%
7 16
8.0%
9 15
7.5%
1 14
7.0%
4 12
 
6.0%
6 9
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 37
15.5%
3 34
14.3%
0 33
13.9%
2 28
11.8%
8 20
8.4%
5 20
8.4%
7 16
6.7%
9 15
6.3%
1 14
 
5.9%
4 12
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 37
15.5%
3 34
14.3%
0 33
13.9%
2 28
11.8%
8 20
8.4%
5 20
8.4%
7 16
6.7%
9 15
6.3%
1 14
 
5.9%
4 12
 
5.0%

소재지면적
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.019375
Minimum0
Maximum748.4
Zeros23
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T04:36:43.450618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q345.735
95-th percentile567.4525
Maximum748.4
Range748.4
Interquartile range (IQR)45.735

Descriptive statistics

Standard deviation198.39428
Coefficient of variation (CV)2.1796929
Kurtosis5.1603397
Mean91.019375
Median Absolute Deviation (MAD)0
Skewness2.415588
Sum2912.62
Variance39360.291
MonotonicityNot monotonic
2024-04-30T04:36:43.530922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 23
71.9%
125.37 1
 
3.1%
680.56 1
 
3.1%
50.4 1
 
3.1%
44.18 1
 
3.1%
474.91 1
 
3.1%
214.9 1
 
3.1%
235.0 1
 
3.1%
338.9 1
 
3.1%
748.4 1
 
3.1%
ValueCountFrequency (%)
0.0 23
71.9%
44.18 1
 
3.1%
50.4 1
 
3.1%
125.37 1
 
3.1%
214.9 1
 
3.1%
235.0 1
 
3.1%
338.9 1
 
3.1%
474.91 1
 
3.1%
680.56 1
 
3.1%
748.4 1
 
3.1%
ValueCountFrequency (%)
748.4 1
 
3.1%
680.56 1
 
3.1%
474.91 1
 
3.1%
338.9 1
 
3.1%
235.0 1
 
3.1%
214.9 1
 
3.1%
125.37 1
 
3.1%
50.4 1
 
3.1%
44.18 1
 
3.1%
0.0 23
71.9%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

지번주소
Text

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-30T04:36:43.704277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length22.875
Min length20

Characters and Unicode

Total characters732
Distinct characters40
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)71.9%

Sample

1st row서울특별시 은평구 역촌동 20-49번지
2nd row서울특별시 은평구 녹번동 118-48번지
3rd row서울특별시 은평구 증산동 181-18번지
4th row서울특별시 은평구 응암동 97-9번지
5th row서울특별시 은평구 응암동 732-9번지
ValueCountFrequency (%)
서울특별시 32
23.0%
은평구 32
23.0%
응암동 15
10.8%
1층 5
 
3.6%
증산동 4
 
2.9%
역촌동 4
 
2.9%
97-9번지 3
 
2.2%
녹번동 3
 
2.2%
110-5 2
 
1.4%
갈현동 2
 
1.4%
Other values (33) 37
26.6%
2024-04-30T04:36:44.018885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
18.4%
1 39
 
5.3%
구 34
 
4.6%
동 33
 
4.5%
서 32
 
4.4%
- 32
 
4.4%
특 32
 
4.4%
별 32
 
4.4%
시 32
 
4.4%
은 32
 
4.4%
Other values (30) 299
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 416
56.8%
Decimal Number 148
 
20.2%
Space Separator 135
 
18.4%
Dash Punctuation 32
 
4.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 34
 
8.2%
동 33
 
7.9%
서 32
 
7.7%
특 32
 
7.7%
별 32
 
7.7%
시 32
 
7.7%
은 32
 
7.7%
평 32
 
7.7%
울 32
 
7.7%
번 28
 
6.7%
Other values (17) 97
23.3%
Decimal Number
ValueCountFrequency (%)
1 39
26.4%
9 21
14.2%
5 18
12.2%
2 14
 
9.5%
3 13
 
8.8%
7 12
 
8.1%
0 11
 
7.4%
6 8
 
5.4%
4 7
 
4.7%
8 5
 
3.4%
Space Separator
ValueCountFrequency (%)
135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
56.8%
Common 315
43.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 34
 
8.2%
동 33
 
7.9%
서 32
 
7.7%
특 32
 
7.7%
별 32
 
7.7%
시 32
 
7.7%
은 32
 
7.7%
평 32
 
7.7%
울 32
 
7.7%
번 28
 
6.7%
Other values (17) 97
23.3%
Common
ValueCountFrequency (%)
135
42.9%
1 39
 
12.4%
- 32
 
10.2%
9 21
 
6.7%
5 18
 
5.7%
2 14
 
4.4%
3 13
 
4.1%
7 12
 
3.8%
0 11
 
3.5%
6 8
 
2.5%
Other values (2) 12
 
3.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
56.8%
ASCII 316
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
42.7%
1 39
 
12.3%
- 32
 
10.1%
9 21
 
6.6%
5 18
 
5.7%
2 14
 
4.4%
3 13
 
4.1%
7 12
 
3.8%
0 11
 
3.5%
6 8
 
2.5%
Other values (3) 13
 
4.1%
Hangul
ValueCountFrequency (%)
구 34
 
8.2%
동 33
 
7.9%
서 32
 
7.7%
특 32
 
7.7%
별 32
 
7.7%
시 32
 
7.7%
은 32
 
7.7%
평 32
 
7.7%
울 32
 
7.7%
번 28
 
6.7%
Other values (17) 97
23.3%

도로명주소
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing7
Missing (%)21.9%
Memory size388.0 B
2024-04-30T04:36:44.219231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length26.68
Min length22

Characters and Unicode

Total characters667
Distinct characters64
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row서울특별시 은평구 증산로1길 18 (증산동)
2nd row서울특별시 은평구 가좌로7다길 7 (응암동)
3rd row서울특별시 은평구 증산로 327, 1층 (증산동)
4th row서울특별시 은평구 응암로9길 5-1 (응암동)
5th row서울특별시 은평구 서오릉로7길 7 (역촌동)
ValueCountFrequency (%)
서울특별시 25
18.1%
은평구 25
18.1%
응암동 11
 
8.0%
1층 6
 
4.3%
증산동 4
 
2.9%
응암로9길 3
 
2.2%
역촌동 3
 
2.2%
백련산로 2
 
1.4%
갈현동 2
 
1.4%
19 2
 
1.4%
Other values (51) 55
39.9%
2024-04-30T04:36:44.513429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
16.9%
1 32
 
4.8%
서 30
 
4.5%
은 27
 
4.0%
평 27
 
4.0%
구 26
 
3.9%
동 26
 
3.9%
특 25
 
3.7%
별 25
 
3.7%
시 25
 
3.7%
Other values (54) 311
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
59.1%
Space Separator 113
 
16.9%
Decimal Number 92
 
13.8%
Close Punctuation 25
 
3.7%
Open Punctuation 25
 
3.7%
Other Punctuation 11
 
1.6%
Dash Punctuation 6
 
0.9%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 30
 
7.6%
은 27
 
6.9%
평 27
 
6.9%
구 26
 
6.6%
동 26
 
6.6%
특 25
 
6.3%
별 25
 
6.3%
시 25
 
6.3%
울 25
 
6.3%
로 24
 
6.1%
Other values (38) 134
34.0%
Decimal Number
ValueCountFrequency (%)
1 32
34.8%
7 14
15.2%
5 9
 
9.8%
2 8
 
8.7%
3 7
 
7.6%
9 7
 
7.6%
6 5
 
5.4%
8 4
 
4.3%
0 3
 
3.3%
4 3
 
3.3%
Space Separator
ValueCountFrequency (%)
113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
59.1%
Common 272
40.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 30
 
7.6%
은 27
 
6.9%
평 27
 
6.9%
구 26
 
6.6%
동 26
 
6.6%
특 25
 
6.3%
별 25
 
6.3%
시 25
 
6.3%
울 25
 
6.3%
로 24
 
6.1%
Other values (38) 134
34.0%
Common
ValueCountFrequency (%)
113
41.5%
1 32
 
11.8%
) 25
 
9.2%
( 25
 
9.2%
7 14
 
5.1%
, 11
 
4.0%
5 9
 
3.3%
2 8
 
2.9%
3 7
 
2.6%
9 7
 
2.6%
Other values (5) 21
 
7.7%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
59.1%
ASCII 273
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
41.4%
1 32
 
11.7%
) 25
 
9.2%
( 25
 
9.2%
7 14
 
5.1%
, 11
 
4.0%
5 9
 
3.3%
2 8
 
2.9%
3 7
 
2.6%
9 7
 
2.6%
Other values (6) 22
 
8.1%
Hangul
ValueCountFrequency (%)
서 30
 
7.6%
은 27
 
6.9%
평 27
 
6.9%
구 26
 
6.6%
동 26
 
6.6%
특 25
 
6.3%
별 25
 
6.3%
시 25
 
6.3%
울 25
 
6.3%
로 24
 
6.1%
Other values (38) 134
34.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)84.0%
Missing7
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean3441.04
Minimum3314
Maximum3506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T04:36:44.622468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3314
5-th percentile3334
Q13404
median3462
Q33485
95-th percentile3497
Maximum3506
Range192
Interquartile range (IQR)81

Descriptive statistics

Standard deviation56.24091
Coefficient of variation (CV)0.016344161
Kurtosis-0.2076874
Mean3441.04
Median Absolute Deviation (MAD)34
Skewness-0.94212669
Sum86026
Variance3163.04
MonotonicityNot monotonic
2024-04-30T04:36:44.722842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3485 3
 
9.4%
3497 2
 
6.2%
3462 2
 
6.2%
3411 1
 
3.1%
3375 1
 
3.1%
3479 1
 
3.1%
3419 1
 
3.1%
3496 1
 
3.1%
3455 1
 
3.1%
3446 1
 
3.1%
Other values (11) 11
34.4%
(Missing) 7
21.9%
ValueCountFrequency (%)
3314 1
3.1%
3332 1
3.1%
3342 1
3.1%
3375 1
3.1%
3382 1
3.1%
3402 1
3.1%
3404 1
3.1%
3411 1
3.1%
3419 1
3.1%
3446 1
3.1%
ValueCountFrequency (%)
3506 1
 
3.1%
3497 2
6.2%
3496 1
 
3.1%
3485 3
9.4%
3481 1
 
3.1%
3479 1
 
3.1%
3473 1
 
3.1%
3472 1
 
3.1%
3464 1
 
3.1%
3462 2
6.2%

사업장명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-30T04:36:44.910746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.34375
Min length3

Characters and Unicode

Total characters171
Distinct characters96
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row삼영식품
2nd row한국식품
3rd row산들식품
4th row(주)일가네
5th row백암미트
ValueCountFrequency (%)
삼영식품 1
 
2.9%
주)처음마음 1
 
2.9%
에프엔씨 1
 
2.9%
임비스 1
 
2.9%
신영유통 1
 
2.9%
성진유통 1
 
2.9%
컨츄리유통 1
 
2.9%
마로소시지 1
 
2.9%
이탈리아나파브리카 1
 
2.9%
한국식품 1
 
2.9%
Other values (24) 24
70.6%
2024-04-30T04:36:45.219335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 10
 
5.8%
품 8
 
4.7%
미 6
 
3.5%
주 6
 
3.5%
유 5
 
2.9%
통 5
 
2.9%
( 5
 
2.9%
) 5
 
2.9%
리 4
 
2.3%
아 3
 
1.8%
Other values (86) 114
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
91.2%
Open Punctuation 5
 
2.9%
Close Punctuation 5
 
2.9%
Space Separator 2
 
1.2%
Uppercase Letter 2
 
1.2%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 10
 
6.4%
품 8
 
5.1%
미 6
 
3.8%
주 6
 
3.8%
유 5
 
3.2%
통 5
 
3.2%
리 4
 
2.6%
아 3
 
1.9%
세 3
 
1.9%
드 3
 
1.9%
Other values (80) 103
66.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
S 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
91.2%
Common 13
 
7.6%
Latin 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 10
 
6.4%
품 8
 
5.1%
미 6
 
3.8%
주 6
 
3.8%
유 5
 
3.2%
통 5
 
3.2%
리 4
 
2.6%
아 3
 
1.9%
세 3
 
1.9%
드 3
 
1.9%
Other values (80) 103
66.0%
Common
ValueCountFrequency (%)
( 5
38.5%
) 5
38.5%
2
 
15.4%
1 1
 
7.7%
Latin
ValueCountFrequency (%)
M 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
91.2%
ASCII 15
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 10
 
6.4%
품 8
 
5.1%
미 6
 
3.8%
주 6
 
3.8%
유 5
 
3.2%
통 5
 
3.2%
리 4
 
2.6%
아 3
 
1.9%
세 3
 
1.9%
드 3
 
1.9%
Other values (80) 103
66.0%
ASCII
ValueCountFrequency (%)
( 5
33.3%
) 5
33.3%
2
 
13.3%
1 1
 
6.7%
M 1
 
6.7%
S 1
 
6.7%

최종수정일자
Date

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2003-11-11 13:01:04
Maximum2023-06-23 14:45:54
2024-04-30T04:36:45.342113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:45.447898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
I
21 
U
11 

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 21
65.6%
U 11
34.4%

Length

2024-04-30T04:36:45.567233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:45.655506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 21
65.6%
u 11
34.4%

데이터갱신일자
Date

Distinct14
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-05 22:05:00
2024-04-30T04:36:45.742977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:45.846032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
식육가공업
31 
알가공업
 
1

Length

Max length5
Median length5
Mean length4.96875
Min length4

Unique

Unique1 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 31
96.9%
알가공업 1
 
3.1%

Length

2024-04-30T04:36:45.981394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:46.068633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 31
96.9%
알가공업 1
 
3.1%

좌표정보(X)
Real number (ℝ)

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192768.98
Minimum191344.67
Maximum194324.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T04:36:46.154841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191344.67
5-th percentile191735.91
Q1192383.16
median192670.9
Q3193392.04
95-th percentile193821.11
Maximum194324.5
Range2979.8326
Interquartile range (IQR)1008.8841

Descriptive statistics

Standard deviation688.78013
Coefficient of variation (CV)0.003573086
Kurtosis-0.11091694
Mean192768.98
Median Absolute Deviation (MAD)370.38658
Skewness0.19322925
Sum6168607.2
Variance474418.07
MonotonicityNot monotonic
2024-04-30T04:36:46.443534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
193421.278274753 3
 
9.4%
192555.254305767 2
 
6.2%
192722.280120502 2
 
6.2%
192391.619418954 2
 
6.2%
193757.229475194 1
 
3.1%
193571.313403468 1
 
3.1%
192963.352888976 1
 
3.1%
192163.142684738 1
 
3.1%
192103.774425108 1
 
3.1%
192524.213614382 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
191344.669604533 1
3.1%
191476.852501832 1
3.1%
191947.869610858 1
3.1%
192101.220573074 1
3.1%
192103.774425108 1
3.1%
192163.142684738 1
3.1%
192264.478872802 1
3.1%
192357.764421076 1
3.1%
192391.619418954 2
6.2%
192458.897918779 1
3.1%
ValueCountFrequency (%)
194324.502180001 1
 
3.1%
193899.175175275 1
 
3.1%
193757.229475194 1
 
3.1%
193720.686869626 1
 
3.1%
193571.313403468 1
 
3.1%
193421.278274753 3
9.4%
193382.293567906 1
 
3.1%
193005.252023357 1
 
3.1%
192986.206305609 1
 
3.1%
192963.352888976 1
 
3.1%

좌표정보(Y)
Real number (ℝ)

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455127.82
Minimum453069.28
Maximum458284.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T04:36:46.544378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453069.28
5-th percentile453663.48
Q1453908.68
median455225.23
Q3456030.97
95-th percentile457499.48
Maximum458284.45
Range5215.1692
Interquartile range (IQR)2122.2891

Descriptive statistics

Standard deviation1313.3734
Coefficient of variation (CV)0.0028857242
Kurtosis-0.3121214
Mean455127.82
Median Absolute Deviation (MAD)1053.9791
Skewness0.53020135
Sum14564090
Variance1724949.6
MonotonicityNot monotonic
2024-04-30T04:36:46.647050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
455337.301951236 3
 
9.4%
455943.377640928 2
 
6.2%
453669.747463863 2
 
6.2%
453912.933931827 2
 
6.2%
455236.157359822 1
 
3.1%
456247.361459174 1
 
3.1%
453826.739106498 1
 
3.1%
455613.681284671 1
 
3.1%
453984.366836106 1
 
3.1%
454887.466719339 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
453069.284009484 1
3.1%
453655.824112866 1
3.1%
453669.747463863 2
6.2%
453737.567360709 1
3.1%
453818.675397979 1
3.1%
453826.739106498 1
3.1%
453895.90775095 1
3.1%
453912.933931827 2
6.2%
453984.366836106 1
3.1%
454139.403173834 1
3.1%
ValueCountFrequency (%)
458284.453164488 1
3.1%
457720.562843798 1
3.1%
457318.595371119 1
3.1%
456494.299634587 1
3.1%
456247.361459174 1
3.1%
456208.576787153 1
3.1%
456147.677977004 1
3.1%
456048.014625429 1
3.1%
456025.283773724 1
3.1%
455943.377640928 2
6.2%

축산업무구분명
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
축산물가공업
28 
<NA>
4 

Length

Max length6
Median length6
Mean length5.75
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 28
87.5%
<NA> 4
 
12.5%

Length

2024-04-30T04:36:46.757546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:46.845859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 28
87.5%
na 4
 
12.5%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
식육가공업
27 
<NA>
4 
알가공업
 
1

Length

Max length5
Median length5
Mean length4.84375
Min length4

Unique

Unique1 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 27
84.4%
<NA> 4
 
12.5%
알가공업 1
 
3.1%

Length

2024-04-30T04:36:46.934085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:47.015717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 27
84.4%
na 4
 
12.5%
알가공업 1
 
3.1%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
31 
0
 
1

Length

Max length4
Median length4
Mean length3.90625
Min length1

Unique

Unique1 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
96.9%
0 1
 
3.1%

Length

2024-04-30T04:36:47.104721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:47.207353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
96.9%
0 1
 
3.1%

권리주체일련번호
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
000
22 
L00
6 
<NA>
4 

Length

Max length4
Median length3
Mean length3.125
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 22
68.8%
L00 6
 
18.8%
<NA> 4
 
12.5%

Length

2024-04-30T04:36:47.300046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:47.396472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 22
68.8%
l00 6
 
18.8%
na 4
 
12.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
31 
0
 
1

Length

Max length4
Median length4
Mean length3.90625
Min length1

Unique

Unique1 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
96.9%
0 1
 
3.1%

Length

2024-04-30T04:36:47.487683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:47.566045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
96.9%
0 1
 
3.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0311000031100000041999000119990602<NA>3폐업2폐업20080403<NA><NA><NA>353-00920.0<NA>서울특별시 은평구 역촌동 20-49번지<NA><NA>삼영식품2008-04-03 16:16:25I2018-08-31 23:59:59.0식육가공업192555.254306455943.377641축산물가공업식육가공업<NA>000<NA>
1311000031100000041999000219991106<NA>3폐업2폐업20031111<NA><NA><NA>383-12770.0<NA>서울특별시 은평구 녹번동 118-48번지<NA><NA>한국식품2003-11-11 13:01:04I2018-08-31 23:59:59.0식육가공업193720.68687456208.576787축산물가공업식육가공업<NA>000<NA>
2311000031100000042001000120010503<NA>3폐업2폐업20171011<NA><NA>201710112291-81670.0<NA>서울특별시 은평구 증산동 181-18번지서울특별시 은평구 증산로1길 18 (증산동)3506산들식품2017-10-11 17:11:47I2018-08-31 23:59:59.0식육가공업191344.669605453069.284009축산물가공업식육가공업<NA>000<NA>
3311000031100000042003000120030523<NA>3폐업2폐업20080623<NA><NA><NA>359-6560125.37<NA>서울특별시 은평구 응암동 97-9번지<NA><NA>(주)일가네2008-06-23 16:52:26I2018-08-31 23:59:59.0식육가공업193421.278275455337.301951축산물가공업식육가공업<NA>L00<NA>
4311000031100000042003000220030609<NA>3폐업2폐업20040507<NA><NA><NA>376-0980680.56<NA>서울특별시 은평구 응암동 732-9번지서울특별시 은평구 가좌로7다길 7 (응암동)3481백암미트2015-08-07 15:57:33I2018-08-31 23:59:59.0식육가공업192722.280121453669.747464축산물가공업식육가공업<NA>000<NA>
5311000031100000042004000120041123<NA>3폐업2폐업20050310<NA><NA><NA><NA>50.4<NA>서울특별시 은평구 응암동 732-9번지<NA><NA>수성미트2005-03-10 09:34:15I2018-08-31 23:59:59.0식육가공업192722.280121453669.747464축산물가공업식육가공업<NA>000<NA>
6311000031100000042005000120050607<NA>3폐업2폐업20140901<NA><NA><NA>307-100444.18<NA>서울특별시 은평구 증산동 163-10번지 1층서울특별시 은평구 증산로 327, 1층 (증산동)3497숲풀림식품2014-09-01 16:42:24I2018-08-31 23:59:59.0식육가공업192101.220573453737.567361축산물가공업식육가공업<NA>L00<NA>
7311000031100000042006000320060502<NA>3폐업2폐업20150227<NA><NA><NA><NA>0.0<NA>서울특별시 은평구 응암동 595-59번지서울특별시 은평구 응암로9길 5-1 (응암동)3485경이상회2015-02-27 17:51:09I2018-08-31 23:59:59.0알가공업192486.27008453895.907751축산물가공업알가공업<NA>000<NA>
8311000031100000042006000420060516<NA>3폐업2폐업20170331<NA><NA>20170331<NA>0.0<NA>서울특별시 은평구 역촌동 16-15번지서울특별시 은평구 서오릉로7길 7 (역촌동)3404만미육가공2017-04-04 10:12:56I2018-08-31 23:59:59.0식육가공업193005.252023456048.014625축산물가공업식육가공업<NA>000<NA>
9311000031100000042006000620060706<NA>3폐업2폐업20170421<NA><NA>20170421309-5515474.91<NA>서울특별시 은평구 응암동 590-27번지<NA><NA>해광외식산업(주)2017-04-21 09:42:25I2018-08-31 23:59:59.0식육가공업192458.897919454139.403174축산물가공업식육가공업<NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
2231100003110000004201300062013-08-05<NA>3폐업2폐업2023-04-04<NA><NA>2023-04-04<NA>0.0<NA>서울특별시 은평구 구산동 7-5 102호서울특별시 은평구 서오릉로11길 20-1, 102호 (구산동)3411컨츄리유통2023-04-04 14:04:57U2022-12-04 00:06:00.0식육가공업192357.764421456494.299635<NA><NA><NA><NA><NA>
23311000031100000042013000720131008<NA>1영업/정상0정상<NA><NA><NA><NA>070-8623-46270.0<NA>서울특별시 은평구 녹번동 110-5 1층서울특별시 은평구 녹번로 66-1 (녹번동)3382마로소시지2022-05-19 15:33:40U2021-12-04 22:01:00.0식육가공업193899.175175456025.283774<NA><NA><NA><NA><NA>
24311000031100000042013000820131107<NA>3폐업2폐업20211118<NA><NA>2021111802-303-09850.0<NA>서울특별시 은평구 신사동 191-39 1층서울특별시 은평구 은평터널로7길 19, 1층 (신사동)3446(주)처음마음2021-11-19 17:08:48U2021-11-21 02:40:00.0식육가공업191476.852502454444.281976축산물가공업식육가공업0L000
25311000031100000042014000120140331<NA>3폐업2폐업20190104<NA><NA>2019010402-389-3397338.9<NA>서울특별시 은평구 응암동 122-12번지 B동 1층 1호서울특별시 은평구 불광천길 502-1, B동 1층 1호 (응암동)3455이탈리아나파브리카2019-01-04 16:49:44U2019-01-06 02:40:00.0식육가공업192524.213614454887.466719축산물가공업식육가공업<NA>000<NA>
26311000031100000042015000120150527<NA>3폐업2폐업20170124<NA><NA>2017012402-306-49930.0<NA>서울특별시 은평구 응암동 595-34번지서울특별시 은평구 응암로9길 15, 1층 (응암동)3485참그린2017-01-24 17:40:57I2018-08-31 23:59:59.0식육가공업192391.619419453912.933932축산물가공업식육가공업<NA>000<NA>
27311000031100000042016000120160615<NA>3폐업2폐업20180131<NA><NA>2018013102-383-85920.0<NA>서울특별시 은평구 증산동 194-29번지서울특별시 은평구 증산로13길 13 (증산동)3496한돈코리아2018-02-01 11:21:22I2018-08-31 23:59:59.0식육가공업192103.774425453984.366836축산물가공업식육가공업<NA>000<NA>
28311000031100000042016000220161129<NA>1영업/정상0정상<NA><NA><NA><NA>02-6012-33920.0<NA>서울특별시 은평구 응암동 595-34번지서울특별시 은평구 응암로9길 15, 1층 (응암동, 하림빌딩)3485태방푸드2020-01-02 13:35:54U2020-01-04 02:40:00.0식육가공업192391.619419453912.933932축산물가공업식육가공업<NA>L00<NA>
29311000031100000042017000120170410<NA>1영업/정상0정상<NA><NA><NA><NA>02-359-1754748.4<NA>서울특별시 은평구 역촌동 68-56번지서울특별시 은평구 연서로3길 36 (역촌동)3419맛뜰애푸드2017-04-10 14:28:32I2018-08-31 23:59:59.0식육가공업192163.142685455613.681285축산물가공업식육가공업<NA>000<NA>
30311000031100000042020000120200618<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 은평구 응암동 747-10번지 2층서울특별시 은평구 가좌로 175, 2층 (응암동)3479우대감식품2020-06-18 14:55:08I2020-06-20 00:23:17.0식육가공업192963.352889453826.739106축산물가공업식육가공업<NA>000<NA>
31311000031100000042022000120221017<NA>1영업/정상0정상<NA><NA><NA><NA>02-354-88110.0<NA>서울특별시 은평구 녹번동 131-77 1층서울특별시 은평구 진흥로 168, 1층 (녹번동)3375(주)아소정 은평1공장2022-10-17 10:53:32I2021-10-30 23:09:00.0식육가공업193571.313403456247.361459<NA><NA><NA><NA><NA>