Overview

Dataset statistics

Number of variables30
Number of observations47
Missing cells332
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory258.8 B

Variable types

Categorical13
Numeric4
DateTime3
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18145/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
소재지면적 is highly imbalanced (74.6%)Imbalance
인허가취소일자 has 47 (100.0%) missing valuesMissing
폐업일자 has 12 (25.5%) missing valuesMissing
휴업시작일자 has 47 (100.0%) missing valuesMissing
휴업종료일자 has 47 (100.0%) missing valuesMissing
재개업일자 has 47 (100.0%) missing valuesMissing
전화번호 has 11 (23.4%) missing valuesMissing
소재지우편번호 has 47 (100.0%) missing valuesMissing
도로명주소 has 4 (8.5%) missing valuesMissing
도로명우편번호 has 17 (36.2%) missing valuesMissing
업태구분명 has 47 (100.0%) missing valuesMissing
좌표정보(X) has 3 (6.4%) missing valuesMissing
좌표정보(Y) has 3 (6.4%) missing valuesMissing
관리번호 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
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 04:08:52.864811
Analysis finished2024-05-11 04:08:54.101087
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
3180000
47 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 47
100.0%

Length

2024-05-11T04:08:54.469530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:55.242081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 47
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1800001 × 1017
Minimum3.18 × 1017
Maximum3.1800001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-11T04:08:56.081954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.18 × 1017
5-th percentile3.18 × 1017
Q13.18 × 1017
median3.1800001 × 1017
Q33.1800001 × 1017
95-th percentile3.1800001 × 1017
Maximum3.1800001 × 1017
Range1.000023 × 1010
Interquartile range (IQR)1.000007 × 1010

Descriptive statistics

Standard deviation4.9605734 × 109
Coefficient of variation (CV)1.5599287 × 10-8
Kurtosis-1.921121
Mean3.1800001 × 1017
Median Absolute Deviation (MAD)90048
Skewness-0.40318283
Sum-3.5007438 × 1018
Variance2.4607288 × 1019
MonotonicityStrictly increasing
2024-05-11T04:08:56.842908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
318000000420000001 1
 
2.1%
318000000420040002 1
 
2.1%
318000010420130005 1
 
2.1%
318000010420130006 1
 
2.1%
318000010420130007 1
 
2.1%
318000010420130008 1
 
2.1%
318000010420140001 1
 
2.1%
318000010420140002 1
 
2.1%
318000010420140003 1
 
2.1%
318000010420140004 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
318000000420000001 1
2.1%
318000000420040002 1
2.1%
318000000420050001 1
2.1%
318000000420050004 1
2.1%
318000000420060004 1
2.1%
318000000420060006 1
2.1%
318000000420060007 1
2.1%
318000000420060008 1
2.1%
318000000420070001 1
2.1%
318000000420070003 1
2.1%
ValueCountFrequency (%)
318000010420230001 1
2.1%
318000010420220004 1
2.1%
318000010420220003 1
2.1%
318000010420220002 1
2.1%
318000010420220001 1
2.1%
318000010420210001 1
2.1%
318000010420180001 1
2.1%
318000010420170001 1
2.1%
318000010420160001 1
2.1%
318000010420150002 1
2.1%

인허가일자
Date

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2000-02-24 00:00:00
Maximum2023-01-05 00:00:00
2024-05-11T04:08:57.264406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:08:57.781334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태코드
Categorical

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
3
34 
1
12 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 34
72.3%
1 12
 
25.5%
4 1
 
2.1%

Length

2024-05-11T04:08:58.322092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:58.685959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 34
72.3%
1 12
 
25.5%
4 1
 
2.1%

영업상태명
Categorical

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
폐업
34 
영업/정상
12 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length3.0212766
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 34
72.3%
영업/정상 12
 
25.5%
취소/말소/만료/정지/중지 1
 
2.1%

Length

2024-05-11T04:08:59.092650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:08:59.458145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 34
72.3%
영업/정상 12
 
25.5%
취소/말소/만료/정지/중지 1
 
2.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
2
34 
0
12 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row0

Common Values

ValueCountFrequency (%)
2 34
72.3%
0 12
 
25.5%
4 1
 
2.1%

Length

2024-05-11T04:08:59.820568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:00.093570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 34
72.3%
0 12
 
25.5%
4 1
 
2.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
폐업
34 
정상
12 
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 34
72.3%
정상 12
 
25.5%
말소 1
 
2.1%

Length

2024-05-11T04:09:00.537075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:00.858683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 34
72.3%
정상 12
 
25.5%
말소 1
 
2.1%

폐업일자
Date

MISSING 

Distinct35
Distinct (%)100.0%
Missing12
Missing (%)25.5%
Memory size508.0 B
Minimum2009-03-20 00:00:00
Maximum2023-11-08 00:00:00
2024-05-11T04:09:01.265766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:09:01.880479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전화번호
Text

MISSING 

Distinct34
Distinct (%)94.4%
Missing11
Missing (%)23.4%
Memory size508.0 B
2024-05-11T04:09:02.564068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.5555556
Min length8

Characters and Unicode

Total characters344
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

Unique32 ?
Unique (%)88.9%

Sample

1st row841-2284
2nd row02-2667-0737
3rd row831-1431
4th row2632-9420
5th row02-789-5725
ValueCountFrequency (%)
841-2284 2
 
5.6%
2678-3340 2
 
5.6%
1688-4124 1
 
2.8%
070-7565-3340 1
 
2.8%
02-2677-1184 1
 
2.8%
02-832-2313 1
 
2.8%
02-2676-7606 1
 
2.8%
02-2678-3340 1
 
2.8%
02-831-4403 1
 
2.8%
6406-7433 1
 
2.8%
Other values (24) 24
66.7%
2024-05-11T04:09:03.671200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
14.0%
2 45
13.1%
8 42
12.2%
3 39
11.3%
4 31
9.0%
6 30
8.7%
0 30
8.7%
1 26
7.6%
7 22
6.4%
9 17
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 296
86.0%
Dash Punctuation 48
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 45
15.2%
8 42
14.2%
3 39
13.2%
4 31
10.5%
6 30
10.1%
0 30
10.1%
1 26
8.8%
7 22
7.4%
9 17
 
5.7%
5 14
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 344
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
14.0%
2 45
13.1%
8 42
12.2%
3 39
11.3%
4 31
9.0%
6 30
8.7%
0 30
8.7%
1 26
7.6%
7 22
6.4%
9 17
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
14.0%
2 45
13.1%
8 42
12.2%
3 39
11.3%
4 31
9.0%
6 30
8.7%
0 30
8.7%
1 26
7.6%
7 22
6.4%
9 17
 
4.9%

소재지면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size508.0 B
0.0
43 
49.64
 
1
188.16
 
1
88.3
 
1
1546.4
 
1

Length

Max length6
Median length3
Mean length3.1914894
Min length3

Unique

Unique4 ?
Unique (%)8.5%

Sample

1st row0.0
2nd row0.0
3rd row49.64
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 43
91.5%
49.64 1
 
2.1%
188.16 1
 
2.1%
88.3 1
 
2.1%
1546.4 1
 
2.1%

Length

2024-05-11T04:09:04.228837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:04.579668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 43
91.5%
49.64 1
 
2.1%
188.16 1
 
2.1%
88.3 1
 
2.1%
1546.4 1
 
2.1%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

지번주소
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-05-11T04:09:05.403864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length26.617021
Min length21

Characters and Unicode

Total characters1251
Distinct characters66
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

Unique45 ?
Unique (%)95.7%

Sample

1st row서울특별시 영등포구 신길동 156-15번지
2nd row서울특별시 영등포구 당산동1가 9-1번지 코오롱주상복합상가1층
3rd row서울특별시 영등포구 대림동 732-5번지
4th row서울특별시 영등포구 영등포동7가 108-4번지 지하1층 및 1층
5th row서울특별시 영등포구 여의도동 60 지하1층
ValueCountFrequency (%)
서울특별시 47
20.8%
영등포구 47
20.8%
대림동 12
 
5.3%
신길동 10
 
4.4%
1층 10
 
4.4%
영등포동5가 5
 
2.2%
지하1층 4
 
1.8%
171-26번지 3
 
1.3%
5-4 2
 
0.9%
지하 2
 
0.9%
Other values (71) 84
37.2%
2024-05-11T04:09:06.761409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
 
16.9%
1 81
 
6.5%
영 55
 
4.4%
등 55
 
4.4%
포 55
 
4.4%
동 51
 
4.1%
시 50
 
4.0%
구 47
 
3.8%
울 47
 
3.8%
서 47
 
3.8%
Other values (56) 552
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 760
60.8%
Decimal Number 238
 
19.0%
Space Separator 211
 
16.9%
Dash Punctuation 38
 
3.0%
Uppercase Letter 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 55
 
7.2%
등 55
 
7.2%
포 55
 
7.2%
동 51
 
6.7%
시 50
 
6.6%
구 47
 
6.2%
울 47
 
6.2%
서 47
 
6.2%
별 47
 
6.2%
특 47
 
6.2%
Other values (42) 259
34.1%
Decimal Number
ValueCountFrequency (%)
1 81
34.0%
5 27
 
11.3%
7 25
 
10.5%
3 24
 
10.1%
2 22
 
9.2%
6 20
 
8.4%
9 12
 
5.0%
4 11
 
4.6%
0 10
 
4.2%
8 6
 
2.5%
Space Separator
ValueCountFrequency (%)
211
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 760
60.8%
Common 489
39.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 55
 
7.2%
등 55
 
7.2%
포 55
 
7.2%
동 51
 
6.7%
시 50
 
6.6%
구 47
 
6.2%
울 47
 
6.2%
서 47
 
6.2%
별 47
 
6.2%
특 47
 
6.2%
Other values (42) 259
34.1%
Common
ValueCountFrequency (%)
211
43.1%
1 81
 
16.6%
- 38
 
7.8%
5 27
 
5.5%
7 25
 
5.1%
3 24
 
4.9%
2 22
 
4.5%
6 20
 
4.1%
9 12
 
2.5%
4 11
 
2.2%
Other values (3) 18
 
3.7%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 760
60.8%
ASCII 491
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
43.0%
1 81
 
16.5%
- 38
 
7.7%
5 27
 
5.5%
7 25
 
5.1%
3 24
 
4.9%
2 22
 
4.5%
6 20
 
4.1%
9 12
 
2.4%
4 11
 
2.2%
Other values (4) 20
 
4.1%
Hangul
ValueCountFrequency (%)
영 55
 
7.2%
등 55
 
7.2%
포 55
 
7.2%
동 51
 
6.7%
시 50
 
6.6%
구 47
 
6.2%
울 47
 
6.2%
서 47
 
6.2%
별 47
 
6.2%
특 47
 
6.2%
Other values (42) 259
34.1%

도로명주소
Text

MISSING 

Distinct41
Distinct (%)95.3%
Missing4
Missing (%)8.5%
Memory size508.0 B
2024-05-11T04:09:07.556419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length31.790698
Min length25

Characters and Unicode

Total characters1367
Distinct characters82
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

Unique39 ?
Unique (%)90.7%

Sample

1st row서울특별시 영등포구 도신로56길 3 (신길동)
2nd row서울특별시 영등포구 영등포로28길 5 (당산동1가,코오롱주상복합상가1층)
3rd row서울특별시 영등포구 대림로31길 26 (대림동)
4th row서울특별시 영등포구 국회대로52길 13 (영등포동7가)
5th row서울특별시 영등포구 63로 50, 지하1층 (여의도동, 63한화생명빌딩)
ValueCountFrequency (%)
서울특별시 43
 
17.6%
영등포구 43
 
17.6%
대림동 11
 
4.5%
1층 9
 
3.7%
신길동 8
 
3.3%
영등포동5가 4
 
1.6%
대림로31길 3
 
1.2%
지하1층 3
 
1.2%
지층 3
 
1.2%
선유로 3
 
1.2%
Other values (98) 115
46.9%
2024-05-11T04:09:08.811971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
 
14.8%
영 61
 
4.5%
등 57
 
4.2%
포 57
 
4.2%
1 54
 
4.0%
동 47
 
3.4%
시 46
 
3.4%
서 44
 
3.2%
별 43
 
3.1%
구 43
 
3.1%
Other values (72) 713
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 820
60.0%
Decimal Number 217
 
15.9%
Space Separator 202
 
14.8%
Open Punctuation 43
 
3.1%
Close Punctuation 43
 
3.1%
Other Punctuation 26
 
1.9%
Dash Punctuation 14
 
1.0%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 61
 
7.4%
등 57
 
7.0%
포 57
 
7.0%
동 47
 
5.7%
시 46
 
5.6%
서 44
 
5.4%
별 43
 
5.2%
구 43
 
5.2%
로 43
 
5.2%
특 43
 
5.2%
Other values (56) 336
41.0%
Decimal Number
ValueCountFrequency (%)
1 54
24.9%
3 31
14.3%
2 29
13.4%
4 24
11.1%
5 22
10.1%
0 15
 
6.9%
7 13
 
6.0%
8 12
 
5.5%
6 11
 
5.1%
9 6
 
2.8%
Space Separator
ValueCountFrequency (%)
202
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 820
60.0%
Common 545
39.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 61
 
7.4%
등 57
 
7.0%
포 57
 
7.0%
동 47
 
5.7%
시 46
 
5.6%
서 44
 
5.4%
별 43
 
5.2%
구 43
 
5.2%
로 43
 
5.2%
특 43
 
5.2%
Other values (56) 336
41.0%
Common
ValueCountFrequency (%)
202
37.1%
1 54
 
9.9%
( 43
 
7.9%
) 43
 
7.9%
3 31
 
5.7%
2 29
 
5.3%
, 26
 
4.8%
4 24
 
4.4%
5 22
 
4.0%
0 15
 
2.8%
Other values (5) 56
 
10.3%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 820
60.0%
ASCII 547
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
36.9%
1 54
 
9.9%
( 43
 
7.9%
) 43
 
7.9%
3 31
 
5.7%
2 29
 
5.3%
, 26
 
4.8%
4 24
 
4.4%
5 22
 
4.0%
0 15
 
2.7%
Other values (6) 58
 
10.6%
Hangul
ValueCountFrequency (%)
영 61
 
7.4%
등 57
 
7.0%
포 57
 
7.0%
동 47
 
5.7%
시 46
 
5.6%
서 44
 
5.4%
별 43
 
5.2%
구 43
 
5.2%
로 43
 
5.2%
특 43
 
5.2%
Other values (56) 336
41.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)83.3%
Missing17
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean12077.9
Minimum7202
Maximum150037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-11T04:09:09.184595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7202
5-th percentile7236.2
Q17252.75
median7299.5
Q37410.5
95-th percentile7435.85
Maximum150037
Range142835
Interquartile range (IQR)157.75

Descriptive statistics

Standard deviation26056.422
Coefficient of variation (CV)2.1573636
Kurtosis29.999448
Mean12077.9
Median Absolute Deviation (MAD)51
Skewness5.4771525
Sum362337
Variance6.7893715 × 108
MonotonicityNot monotonic
2024-05-11T04:09:09.575192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
7250 4
 
8.5%
7411 2
 
4.3%
7255 2
 
4.3%
7379 1
 
2.1%
7274 1
 
2.1%
7272 1
 
2.1%
7300 1
 
2.1%
7263 1
 
2.1%
7414 1
 
2.1%
7418 1
 
2.1%
Other values (15) 15
31.9%
(Missing) 17
36.2%
ValueCountFrequency (%)
7202 1
 
2.1%
7229 1
 
2.1%
7245 1
 
2.1%
7250 4
8.5%
7252 1
 
2.1%
7255 2
4.3%
7263 1
 
2.1%
7272 1
 
2.1%
7274 1
 
2.1%
7275 1
 
2.1%
ValueCountFrequency (%)
150037 1
2.1%
7439 1
2.1%
7432 1
2.1%
7429 1
2.1%
7418 1
2.1%
7414 1
2.1%
7411 2
4.3%
7409 1
2.1%
7391 1
2.1%
7379 1
2.1%

사업장명
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-05-11T04:09:10.137916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.0212766
Min length3

Characters and Unicode

Total characters330
Distinct characters108
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

Unique45 ?
Unique (%)95.7%

Sample

1st row영등포축산유통
2nd row(주)한국푸드씨스템
3rd row동강축산유통
4th row(주)오성푸드
5th row한화푸드테크 주식회사
ValueCountFrequency (%)
주식회사 5
 
9.4%
주)엠케이팜스 2
 
3.8%
마니커서서울물류 1
 
1.9%
한우사랑 1
 
1.9%
농업회사법인 1
 
1.9%
엠케이팜스(주 1
 
1.9%
닭발집 1
 
1.9%
주)미트원푸드 1
 
1.9%
마리푸드 1
 
1.9%
윤수 1
 
1.9%
Other values (38) 38
71.7%
2024-05-11T04:09:11.319968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 23
 
7.0%
( 15
 
4.5%
) 15
 
4.5%
드 15
 
4.5%
식 13
 
3.9%
사 13
 
3.9%
푸 11
 
3.3%
유 10
 
3.0%
회 10
 
3.0%
통 9
 
2.7%
Other values (98) 196
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
88.8%
Open Punctuation 15
 
4.5%
Close Punctuation 15
 
4.5%
Space Separator 6
 
1.8%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 23
 
7.8%
드 15
 
5.1%
식 13
 
4.4%
사 13
 
4.4%
푸 11
 
3.8%
유 10
 
3.4%
회 10
 
3.4%
통 9
 
3.1%
산 8
 
2.7%
축 7
 
2.4%
Other values (94) 174
59.4%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
88.8%
Common 37
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 23
 
7.8%
드 15
 
5.1%
식 13
 
4.4%
사 13
 
4.4%
푸 11
 
3.8%
유 10
 
3.4%
회 10
 
3.4%
통 9
 
3.1%
산 8
 
2.7%
축 7
 
2.4%
Other values (94) 174
59.4%
Common
ValueCountFrequency (%)
( 15
40.5%
) 15
40.5%
6
 
16.2%
- 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
88.8%
ASCII 37
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 23
 
7.8%
드 15
 
5.1%
식 13
 
4.4%
사 13
 
4.4%
푸 11
 
3.8%
유 10
 
3.4%
회 10
 
3.4%
통 9
 
3.1%
산 8
 
2.7%
축 7
 
2.4%
Other values (94) 174
59.4%
ASCII
ValueCountFrequency (%)
( 15
40.5%
) 15
40.5%
6
 
16.2%
- 1
 
2.7%

최종수정일자
Date

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2009-03-20 16:57:35
Maximum2024-04-03 10:09:30
2024-05-11T04:09:11.953519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:09:12.893656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
I
27 
U
20 

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 27
57.4%
U 20
42.6%

Length

2024-05-11T04:09:13.319196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:13.676914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 27
57.4%
u 20
42.6%

데이터갱신일자
Categorical

Distinct21
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
2018-08-31 23:59:59.0
24 
2022-12-03 23:06:00.0
4 
2021-01-02 02:40:00.0
 
1
2019-03-14 02:40:00.0
 
1
2021-12-04 22:01:00.0
 
1
Other values (16)
16 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique19 ?
Unique (%)40.4%

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 row2023-12-01 22:03:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 24
51.1%
2022-12-03 23:06:00.0 4
 
8.5%
2021-01-02 02:40:00.0 1
 
2.1%
2019-03-14 02:40:00.0 1
 
2.1%
2021-12-04 22:01:00.0 1
 
2.1%
2020-11-01 02:40:00.0 1
 
2.1%
2023-12-04 00:05:00.0 1
 
2.1%
2021-12-09 00:03:00.0 1
 
2.1%
2021-12-05 00:05:00.0 1
 
2.1%
2019-05-16 02:40:00.0 1
 
2.1%
Other values (11) 11
23.4%

Length

2024-05-11T04:09:14.107346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 24
25.5%
23:59:59.0 24
25.5%
02:40:00.0 8
 
8.5%
2022-12-03 4
 
4.3%
23:06:00.0 4
 
4.3%
00:05:00.0 2
 
2.1%
2019-05-17 1
 
1.1%
2022-10-31 1
 
1.1%
23:00:00.0 1
 
1.1%
2022-03-10 1
 
1.1%
Other values (24) 24
25.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)90.9%
Missing3
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean191401.85
Minimum189764.48
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-11T04:09:14.498367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189764.48
5-th percentile190170.38
Q1190616.2
median191216.82
Q3191796.31
95-th percentile192889.74
Maximum194632.53
Range4868.0489
Interquartile range (IQR)1180.114

Descriptive statistics

Standard deviation1020.8043
Coefficient of variation (CV)0.0053333042
Kurtosis0.94046496
Mean191401.85
Median Absolute Deviation (MAD)593.1962
Skewness0.82214135
Sum8421681.2
Variance1042041.4
MonotonicityNot monotonic
2024-05-11T04:09:14.958557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
191783.244220575 2
 
4.3%
190325.849378028 2
 
4.3%
190616.195026806 2
 
4.3%
192510.916880502 2
 
4.3%
194632.526367463 1
 
2.1%
190592.238301027 1
 
2.1%
191192.778018993 1
 
2.1%
192910.201811963 1
 
2.1%
191503.853065177 1
 
2.1%
192740.987211207 1
 
2.1%
Other values (30) 30
63.8%
(Missing) 3
 
6.4%
ValueCountFrequency (%)
189764.477432316 1
2.1%
189807.876019391 1
2.1%
190161.744586039 1
2.1%
190219.297584691 1
2.1%
190287.011985933 1
2.1%
190298.841931736 1
2.1%
190325.849378028 2
4.3%
190442.51404709 1
2.1%
190592.238301027 1
2.1%
190616.195026806 2
4.3%
ValueCountFrequency (%)
194632.526367463 1
2.1%
193310.621023674 1
2.1%
192910.201811963 1
2.1%
192773.803537193 1
2.1%
192740.987211207 1
2.1%
192700.719241495 1
2.1%
192663.058748186 1
2.1%
192510.916880502 2
4.3%
191865.501455257 1
2.1%
191802.587427 1
2.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)93.2%
Missing3
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean445593.07
Minimum443138.33
Maximum448939.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-11T04:09:15.642917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443138.33
5-th percentile443424.59
Q1444127.59
median445789.96
Q3446804.47
95-th percentile447241.78
Maximum448939.21
Range5800.8835
Interquartile range (IQR)2676.8804

Descriptive statistics

Standard deviation1495.246
Coefficient of variation (CV)0.0033556313
Kurtosis-0.7046452
Mean445593.07
Median Absolute Deviation (MAD)1124.1855
Skewness0.10203662
Sum19606095
Variance2235760.7
MonotonicityNot monotonic
2024-05-11T04:09:16.159460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
446425.890090077 2
 
4.3%
447033.873479894 2
 
4.3%
445469.473683797 2
 
4.3%
446401.926526228 1
 
2.1%
446512.4697968 1
 
2.1%
443969.101717817 1
 
2.1%
444504.901949965 1
 
2.1%
446800.670780445 1
 
2.1%
445583.70466473 1
 
2.1%
444570.745937687 1
 
2.1%
Other values (31) 31
66.0%
(Missing) 3
 
6.4%
ValueCountFrequency (%)
443138.326499562 1
2.1%
443392.532730331 1
2.1%
443407.640817294 1
2.1%
443520.607560922 1
2.1%
443598.689799608 1
2.1%
443667.963292382 1
2.1%
443793.574807436 1
2.1%
443878.031701893 1
2.1%
443878.031701894 1
2.1%
443969.101717817 1
2.1%
ValueCountFrequency (%)
448939.210023947 1
2.1%
448923.480256794 1
2.1%
447278.469150353 1
2.1%
447033.873479894 2
4.3%
447020.956097736 1
2.1%
446924.170327295 1
2.1%
446904.115067936 1
2.1%
446900.060108156 1
2.1%
446897.452489918 1
2.1%
446815.865946146 1
2.1%

축산업무구분명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
식육포장처리업
33 
<NA>
14 

Length

Max length7
Median length7
Mean length6.106383
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 33
70.2%
<NA> 14
29.8%

Length

2024-05-11T04:09:16.772533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:17.177705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 33
70.2%
na 14
29.8%

축산물가공업구분명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
식육포장처리업
33 
<NA>
14 

Length

Max length7
Median length7
Mean length6.106383
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 33
70.2%
<NA> 14
29.8%

Length

2024-05-11T04:09:17.537147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:17.937121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 33
70.2%
na 14
29.8%

축산일련번호
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
0
33 
<NA>
14 

Length

Max length4
Median length1
Mean length1.893617
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 33
70.2%
<NA> 14
29.8%

Length

2024-05-11T04:09:18.445886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:18.837910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 33
70.2%
na 14
29.8%

권리주체일련번호
Categorical

Distinct4
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
000
16 
L00
16 
<NA>
14 
F00
 
1

Length

Max length4
Median length3
Mean length3.2978723
Min length3

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row000
2nd rowL00
3rd row000
4th rowL00
5th row<NA>

Common Values

ValueCountFrequency (%)
000 16
34.0%
L00 16
34.0%
<NA> 14
29.8%
F00 1
 
2.1%

Length

2024-05-11T04:09:19.220122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:19.729263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 16
34.0%
l00 16
34.0%
na 14
29.8%
f00 1
 
2.1%

총인원
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size508.0 B
0
33 
<NA>
14 

Length

Max length4
Median length1
Mean length1.893617
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 33
70.2%
<NA> 14
29.8%

Length

2024-05-11T04:09:20.250028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:09:20.684999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 33
70.2%
na 14
29.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0318000031800000042000000120000224<NA>3폐업2폐업20100121<NA><NA><NA>841-22840.0<NA>서울특별시 영등포구 신길동 156-15번지서울특별시 영등포구 도신로56길 3 (신길동)<NA>영등포축산유통2010-01-21 13:37:03I2018-08-31 23:59:59.0<NA>192510.916881445469.473684식육포장처리업식육포장처리업00000
1318000031800000042004000220040527<NA>3폐업2폐업20090320<NA><NA><NA>02-2667-07370.0<NA>서울특별시 영등포구 당산동1가 9-1번지 코오롱주상복합상가1층서울특별시 영등포구 영등포로28길 5 (당산동1가,코오롱주상복합상가1층)<NA>(주)한국푸드씨스템2009-03-20 16:57:35I2018-08-31 23:59:59.0<NA>191024.65198446421.720026식육포장처리업식육포장처리업0L000
2318000031800000042005000120050531<NA>3폐업2폐업20110307<NA><NA><NA>831-143149.64<NA>서울특별시 영등포구 대림동 732-5번지서울특별시 영등포구 대림로31길 26 (대림동)<NA>동강축산유통2011-03-07 18:30:21I2018-08-31 23:59:59.0<NA>190734.542571443793.574807식육포장처리업식육포장처리업00000
3318000031800000042005000420051018<NA>3폐업2폐업20140915<NA><NA><NA>2632-94200.0<NA>서울특별시 영등포구 영등포동7가 108-4번지 지하1층 및 1층서울특별시 영등포구 국회대로52길 13 (영등포동7가)150037(주)오성푸드2014-09-15 18:32:27I2018-08-31 23:59:59.0<NA>191745.610652446897.45249식육포장처리업식육포장처리업0L000
431800003180000004200600042006-09-14<NA>1영업/정상0정상<NA><NA><NA><NA>02-789-57250.0<NA>서울특별시 영등포구 여의도동 60 지하1층서울특별시 영등포구 63로 50, 지하1층 (여의도동, 63한화생명빌딩)7345한화푸드테크 주식회사2024-02-21 17:19:50U2023-12-01 22:03:00.0<NA>194632.526367446401.926526<NA><NA><NA><NA><NA>
5318000031800000042006000620060928<NA>1영업/정상0정상<NA><NA><NA><NA>2635-08470.0<NA>서울특별시 영등포구 영등포동5가 11번지서울특별시 영등포구 영중로14길 23-4 (영등포동5가)<NA>성원사2013-05-22 17:54:15I2018-08-31 23:59:59.0<NA>191783.244221446425.89009식육포장처리업식육포장처리업00000
6318000031800000042006000720060929<NA>3폐업2폐업20121015<NA><NA><NA>2636-39210.0<NA>서울특별시 영등포구 당산동2가 12-1번지서울특별시 영등포구 문래북로 81 (당산동2가)<NA>(주)농협유통외식사업분사2012-10-15 18:23:13I2018-08-31 23:59:59.0<NA>190592.238301446496.464342식육포장처리업식육포장처리업0L000
7318000031800000042006000820061213<NA>3폐업2폐업20100112<NA><NA><NA>2678-33400.0<NA>서울특별시 영등포구 당산동6가 171-26번지 송림빌딩 1층<NA><NA>(주)엠케이팜스2010-01-12 16:55:17I2018-08-31 23:59:59.0<NA><NA><NA>식육포장처리업식육포장처리업0L000
8318000031800000042007000120070115<NA>3폐업2폐업20090703<NA><NA><NA>843-17870.0<NA>서울특별시 영등포구 신길동 117-1번지서울특별시 영등포구 도신로60길 15-14 (신길동)<NA>신길축산육류직매장2009-07-03 17:56:37I2018-08-31 23:59:59.0<NA>192700.719241445393.496325식육포장처리업식육포장처리업00000
9318000031800000042007000320070215<NA>3폐업2폐업20091104<NA><NA><NA>844-85050.0<NA>서울특별시 영등포구 신길동 261-15번지서울특별시 영등포구 신길로33길 24-1 (신길동)<NA>바위솔푸드2009-11-05 09:25:51I2018-08-31 23:59:59.0<NA>191794.216292444818.296236식육포장처리업식육포장처리업00000
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
37318000031800001042015000220151105<NA>3폐업2폐업20220808<NA><NA><NA>02-848-88180.0<NA>서울특별시 영등포구 대림동 701 1층서울특별시 영등포구 대림로21길 5-1, 1층 (대림동)7418대광식품2022-08-10 08:53:19U2021-12-07 23:03:00.0<NA>191145.716447443407.640817<NA><NA><NA><NA><NA>
38318000031800001042016000120160819<NA>3폐업2폐업20190220<NA><NA><NA>02-848-99930.0<NA>서울특별시 영등포구 대림동 727-4번지 1층서울특별시 영등포구 대림로29길 22, 1층 (대림동)7414축산물도매센터2019-02-20 17:53:57U2019-02-22 02:40:00.0<NA>190827.5762443667.963292식육포장처리업식육포장처리업0F000
39318000031800001042017000120171120<NA>3폐업2폐업20220217<NA><NA><NA>1588-63570.0<NA>서울특별시 영등포구 대림동 777-1 신동아아파트상가 지하1층서울특별시 영등포구 대림로31길 40, 상가동 지하1층 (대림동)7411주식회사 유푸드2022-02-17 16:20:28U2022-02-19 02:40:00.0<NA>190616.195027443878.031702식육포장처리업식육포장처리업0L000
40318000031800001042018000120180220<NA>3폐업2폐업20190515<NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 당산동2가 161-20번지서울특별시 영등포구 양산로 88 (당산동2가)7263에이치엠푸드시스템2019-05-15 16:55:03U2019-05-17 02:40:00.0<NA>190442.514047446924.170327식육포장처리업식육포장처리업0L000
4131800003180000104202100012021-10-21<NA>3폐업2폐업2023-11-08<NA><NA><NA>02-3488-405688.3<NA>서울특별시 영등포구 양평동3가 5-4 에이스 하이테크시티3 315호서울특별시 영등포구 선유로 130, 에이스 하이테크시티3 315호 (양평동3가)7255주식회사닥터송코리아2023-11-08 11:04:27U2022-10-31 23:00:00.0<NA>190325.849378447033.87348<NA><NA><NA><NA><NA>
42318000031800001042022000120220308<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 영등포동5가 123-6서울특별시 영등포구 영등포로37길 14(영등포동5가)7250음성유통2022-03-08 11:31:15I2022-03-10 13:22:36.0<NA><NA><NA>식육포장처리업식육포장처리업00000
4331800003180000104202200022022-04-06<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 문래동3가 14-2 1층 3호서울특별시 영등포구 영신로25길 5, 1층 3호 (문래동3가)7300주식회사한국축산물유통2023-04-14 14:13:42U2022-12-03 23:06:00.0<NA>191214.458421446065.719247<NA><NA><NA><NA><NA>
44318000031800001042022000320220428<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 양평동3가 5-4 에이스 하이테크시티3 B114호서울특별시 영등포구 선유로 130, 에이스 하이테크시티3 B114호 (양평동3가)7255오뚜기에프에스주식회사2022-04-28 16:49:21I2021-12-03 21:00:00.0<NA>190325.849378447033.87348<NA><NA><NA><NA><NA>
45318000031800001042022000420221025<NA>1영업/정상0정상<NA><NA><NA><NA><NA>1546.4<NA>서울특별시 영등포구 양평동1가 119 5호서울특별시 영등포구 선유로 115, 5호 (양평동1가)7272한성미트2022-10-25 14:13:37I2021-10-30 22:07:00.0<NA>190219.297585446904.115068<NA><NA><NA><NA><NA>
4631800003180000104202300012023-01-05<NA>3폐업2폐업2023-02-13<NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 양평동2가 33-77 1층서울특별시 영등포구 영등포로5길 48, 1층 (양평동2가)7274딩동댕2023-02-13 15:33:36U2022-12-01 23:05:00.0<NA>189764.477432447020.956098<NA><NA><NA><NA><NA>