Overview

Dataset statistics

Number of variables30
Number of observations60
Missing cells353
Missing cells (%)19.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.0 KiB
Average record size in memory256.2 B

Variable types

Categorical13
Numeric5
DateTime4
Unsupported4
Text4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),축산업무구분명,축산물가공업구분명,축산일련번호,권리주체일련번호,총인원
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18120/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (56.2%)Imbalance
영업상태명 is highly imbalanced (56.2%)Imbalance
상세영업상태코드 is highly imbalanced (56.2%)Imbalance
상세영업상태명 is highly imbalanced (56.2%)Imbalance
데이터갱신일자 is highly imbalanced (51.4%)Imbalance
업태구분명 is highly imbalanced (64.7%)Imbalance
축산업무구분명 is highly imbalanced (53.1%)Imbalance
축산물가공업구분명 is highly imbalanced (52.8%)Imbalance
축산일련번호 is highly imbalanced (53.1%)Imbalance
총인원 is highly imbalanced (53.1%)Imbalance
인허가취소일자 has 60 (100.0%) missing valuesMissing
폐업일자 has 3 (5.0%) missing valuesMissing
휴업시작일자 has 60 (100.0%) missing valuesMissing
휴업종료일자 has 60 (100.0%) missing valuesMissing
재개업일자 has 41 (68.3%) missing valuesMissing
전화번호 has 18 (30.0%) missing valuesMissing
소재지우편번호 has 60 (100.0%) missing valuesMissing
도로명주소 has 8 (13.3%) missing valuesMissing
도로명우편번호 has 37 (61.7%) missing valuesMissing
좌표정보(X) has 3 (5.0%) missing valuesMissing
좌표정보(Y) has 3 (5.0%) 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
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 44 (73.3%) zerosZeros

Reproduction

Analysis started2024-04-06 11:59:00.578319
Analysis finished2024-04-06 11:59:01.285224
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
3180000
60 

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 60
100.0%

Length

2024-04-06T20:59:01.415259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:01.590026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 60
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.18 × 1017
Minimum3.18 × 1017
Maximum3.18 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T20:59:01.771261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.18 × 1017
5-th percentile3.18 × 1017
Q13.18 × 1017
median3.18 × 1017
Q33.18 × 1017
95-th percentile3.18 × 1017
Maximum3.18 × 1017
Range560000
Interquartile range (IQR)130048

Descriptive statistics

Standard deviation113645.69
Coefficient of variation (CV)3.5737639 × 10-13
Kurtosis3.9251084
Mean3.18 × 1017
Median Absolute Deviation (MAD)60032
Skewness-1.7412918
Sum6.3325595 × 1017
Variance1.2915343 × 1010
MonotonicityStrictly increasing
2024-04-06T20:59:02.023512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
318000000419660001 1
 
1.7%
318000000420070007 1
 
1.7%
318000000420080001 1
 
1.7%
318000000420080003 1
 
1.7%
318000000420080004 1
 
1.7%
318000000420080005 1
 
1.7%
318000000420090001 1
 
1.7%
318000000420090004 1
 
1.7%
318000000420090005 1
 
1.7%
318000000420090007 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
318000000419660001 1
1.7%
318000000419690001 1
1.7%
318000000419690002 1
1.7%
318000000419860001 1
1.7%
318000000419880001 1
1.7%
318000000419900001 1
1.7%
318000000419940001 1
1.7%
318000000419980001 1
1.7%
318000000419980002 1
1.7%
318000000420000002 1
1.7%
ValueCountFrequency (%)
318000000420220001 1
1.7%
318000000420210001 1
1.7%
318000000420190001 1
1.7%
318000000420170001 1
1.7%
318000000420160002 1
1.7%
318000000420160001 1
1.7%
318000000420150002 1
1.7%
318000000420150001 1
1.7%
318000000420140008 1
1.7%
318000000420140007 1
1.7%

인허가일자
Date

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum1966-06-20 00:00:00
Maximum2022-11-25 00:00:00
2024-04-06T20:59:02.358953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:59:03.004913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
3
52 
4
 
5
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 52
86.7%
4 5
 
8.3%
1 3
 
5.0%

Length

2024-04-06T20:59:03.346807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:03.605014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 52
86.7%
4 5
 
8.3%
1 3
 
5.0%

영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
폐업
52 
취소/말소/만료/정지/중지
 
5
영업/정상
 
3

Length

Max length14
Median length2
Mean length3.15
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
86.7%
취소/말소/만료/정지/중지 5
 
8.3%
영업/정상 3
 
5.0%

Length

2024-04-06T20:59:03.827851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:04.084708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
86.7%
취소/말소/만료/정지/중지 5
 
8.3%
영업/정상 3
 
5.0%

상세영업상태코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2
52 
4
 
5
0
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 52
86.7%
4 5
 
8.3%
0 3
 
5.0%

Length

2024-04-06T20:59:04.361079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:04.594965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 52
86.7%
4 5
 
8.3%
0 3
 
5.0%

상세영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
폐업
52 
말소
 
5
정상
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
86.7%
말소 5
 
8.3%
정상 3
 
5.0%

Length

2024-04-06T20:59:04.780408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:05.015019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
86.7%
말소 5
 
8.3%
정상 3
 
5.0%

폐업일자
Date

MISSING 

Distinct53
Distinct (%)93.0%
Missing3
Missing (%)5.0%
Memory size612.0 B
Minimum2004-02-11 00:00:00
Maximum2023-02-13 00:00:00
2024-04-06T20:59:05.280784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:59:05.546571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

재개업일자
Date

MISSING 

Distinct19
Distinct (%)100.0%
Missing41
Missing (%)68.3%
Memory size612.0 B
Minimum2010-08-12 00:00:00
Maximum2023-02-13 00:00:00
2024-04-06T20:59:05.786058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:59:06.011251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

전화번호
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing18
Missing (%)30.0%
Memory size612.0 B
2024-04-06T20:59:06.370488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.7380952
Min length8

Characters and Unicode

Total characters409
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row2670-6651
2nd row2629-0121~2
3rd row2637-5111
4th row2633-6694
5th row2675-1115
ValueCountFrequency (%)
842-9526 1
 
2.4%
6406-7433 1
 
2.4%
2679-9249 1
 
2.4%
835-2545 1
 
2.4%
832-2336 1
 
2.4%
832-2313 1
 
2.4%
070-8770-0007 1
 
2.4%
02-6380-1100 1
 
2.4%
1688-4124 1
 
2.4%
02-831-4403 1
 
2.4%
Other values (32) 32
76.2%
2024-04-06T20:59:07.119622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 57
13.9%
2 55
13.4%
3 51
12.5%
6 41
10.0%
0 41
10.0%
8 34
8.3%
1 34
8.3%
7 27
6.6%
4 25
6.1%
9 24
5.9%
Other values (2) 20
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 351
85.8%
Dash Punctuation 57
 
13.9%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 55
15.7%
3 51
14.5%
6 41
11.7%
0 41
11.7%
8 34
9.7%
1 34
9.7%
7 27
7.7%
4 25
7.1%
9 24
6.8%
5 19
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 409
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 57
13.9%
2 55
13.4%
3 51
12.5%
6 41
10.0%
0 41
10.0%
8 34
8.3%
1 34
8.3%
7 27
6.6%
4 25
6.1%
9 24
5.9%
Other values (2) 20
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 409
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 57
13.9%
2 55
13.4%
3 51
12.5%
6 41
10.0%
0 41
10.0%
8 34
8.3%
1 34
8.3%
7 27
6.6%
4 25
6.1%
9 24
5.9%
Other values (2) 20
 
4.9%

소재지면적
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.074333
Minimum0
Maximum1912
Zeros44
Zeros (%)73.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T20:59:07.366703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q324.975
95-th percentile175.5085
Maximum1912
Range1912
Interquartile range (IQR)24.975

Descriptive statistics

Standard deviation269.71906
Coefficient of variation (CV)3.9047653
Kurtosis38.855487
Mean69.074333
Median Absolute Deviation (MAD)0
Skewness5.9773495
Sum4144.46
Variance72748.371
MonotonicityNot monotonic
2024-04-06T20:59:07.599129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 44
73.3%
810.0 1
 
1.7%
98.0 1
 
1.7%
140.5 1
 
1.7%
84.5 1
 
1.7%
400.82 1
 
1.7%
27.0 1
 
1.7%
91.04 1
 
1.7%
55.0 1
 
1.7%
24.3 1
 
1.7%
Other values (7) 7
 
11.7%
ValueCountFrequency (%)
0.0 44
73.3%
24.3 1
 
1.7%
27.0 1
 
1.7%
29.25 1
 
1.7%
36.0 1
 
1.7%
45.2 1
 
1.7%
55.0 1
 
1.7%
84.5 1
 
1.7%
91.04 1
 
1.7%
98.0 1
 
1.7%
ValueCountFrequency (%)
1912.0 1
1.7%
810.0 1
1.7%
400.82 1
1.7%
163.65 1
1.7%
140.5 1
1.7%
117.2 1
1.7%
110.0 1
1.7%
98.0 1
1.7%
91.04 1
1.7%
84.5 1
1.7%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

지번주소
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-06T20:59:08.104863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length25.6
Min length21

Characters and Unicode

Total characters1536
Distinct characters69
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

Unique58 ?
Unique (%)96.7%

Sample

1st row서울특별시 영등포구 문래동6가 21번지
2nd row서울특별시 영등포구 양평동4가 20번지
3rd row서울특별시 영등포구 양평동4가 16-1
4th row서울특별시 영등포구 문래동6가 21번지
5th row서울특별시 영등포구 양평동3가 3-1번지
ValueCountFrequency (%)
서울특별시 60
22.1%
영등포구 60
22.1%
신길동 15
 
5.5%
대림동 13
 
4.8%
지하 6
 
2.2%
당산동2가 3
 
1.1%
21번지 3
 
1.1%
문래동3가 3
 
1.1%
1층 3
 
1.1%
지하1층 3
 
1.1%
Other values (90) 102
37.6%
2024-04-06T20:59:08.945562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
 
17.2%
1 79
 
5.1%
영 66
 
4.3%
등 66
 
4.3%
포 66
 
4.3%
동 64
 
4.2%
지 62
 
4.0%
시 61
 
4.0%
서 60
 
3.9%
특 60
 
3.9%
Other values (59) 688
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 935
60.9%
Decimal Number 285
 
18.6%
Space Separator 264
 
17.2%
Dash Punctuation 44
 
2.9%
Uppercase Letter 5
 
0.3%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 66
 
7.1%
등 66
 
7.1%
포 66
 
7.1%
동 64
 
6.8%
지 62
 
6.6%
시 61
 
6.5%
서 60
 
6.4%
특 60
 
6.4%
별 60
 
6.4%
구 60
 
6.4%
Other values (43) 310
33.2%
Decimal Number
ValueCountFrequency (%)
1 79
27.7%
2 38
13.3%
3 32
11.2%
4 24
 
8.4%
5 21
 
7.4%
6 20
 
7.0%
9 20
 
7.0%
7 19
 
6.7%
0 18
 
6.3%
8 14
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
K 1
 
20.0%
S 1
 
20.0%
Space Separator
ValueCountFrequency (%)
264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 935
60.9%
Common 596
38.8%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 66
 
7.1%
등 66
 
7.1%
포 66
 
7.1%
동 64
 
6.8%
지 62
 
6.6%
시 61
 
6.5%
서 60
 
6.4%
특 60
 
6.4%
별 60
 
6.4%
구 60
 
6.4%
Other values (43) 310
33.2%
Common
ValueCountFrequency (%)
264
44.3%
1 79
 
13.3%
- 44
 
7.4%
2 38
 
6.4%
3 32
 
5.4%
4 24
 
4.0%
5 21
 
3.5%
6 20
 
3.4%
9 20
 
3.4%
7 19
 
3.2%
Other values (3) 35
 
5.9%
Latin
ValueCountFrequency (%)
B 3
60.0%
K 1
 
20.0%
S 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 935
60.9%
ASCII 601
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
43.9%
1 79
 
13.1%
- 44
 
7.3%
2 38
 
6.3%
3 32
 
5.3%
4 24
 
4.0%
5 21
 
3.5%
6 20
 
3.3%
9 20
 
3.3%
7 19
 
3.2%
Other values (6) 40
 
6.7%
Hangul
ValueCountFrequency (%)
영 66
 
7.1%
등 66
 
7.1%
포 66
 
7.1%
동 64
 
6.8%
지 62
 
6.6%
시 61
 
6.5%
서 60
 
6.4%
특 60
 
6.4%
별 60
 
6.4%
구 60
 
6.4%
Other values (43) 310
33.2%

도로명주소
Text

MISSING 

Distinct51
Distinct (%)98.1%
Missing8
Missing (%)13.3%
Memory size612.0 B
2024-04-06T20:59:09.543338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length30.538462
Min length23

Characters and Unicode

Total characters1588
Distinct characters93
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

Unique50 ?
Unique (%)96.2%

Sample

1st row서울특별시 영등포구 선유로9길 30 (문래동6가)
2nd row서울특별시 영등포구 양평로21길 25 (양평동4가)
3rd row서울특별시 영등포구 선유로9길 30 (문래동6가)
4th row서울특별시 영등포구 선유동1로 37 (양평동3가)
5th row서울특별시 영등포구 선유로 11 (문래동5가)
ValueCountFrequency (%)
서울특별시 52
 
18.1%
영등포구 52
 
18.1%
대림동 11
 
3.8%
신길동 11
 
3.8%
1층 6
 
2.1%
5 5
 
1.7%
지하1층 3
 
1.0%
당산동2가 3
 
1.0%
문래동3가 3
 
1.0%
영등포로28길 2
 
0.7%
Other values (123) 140
48.6%
2024-04-06T20:59:10.403201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
236
 
14.9%
영 67
 
4.2%
1 66
 
4.2%
등 64
 
4.0%
포 64
 
4.0%
동 57
 
3.6%
시 53
 
3.3%
로 52
 
3.3%
울 52
 
3.3%
) 52
 
3.3%
Other values (83) 825
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 967
60.9%
Space Separator 236
 
14.9%
Decimal Number 235
 
14.8%
Close Punctuation 52
 
3.3%
Open Punctuation 52
 
3.3%
Other Punctuation 29
 
1.8%
Dash Punctuation 10
 
0.6%
Uppercase Letter 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 67
 
6.9%
등 64
 
6.6%
포 64
 
6.6%
동 57
 
5.9%
시 53
 
5.5%
로 52
 
5.4%
울 52
 
5.4%
서 52
 
5.4%
별 52
 
5.4%
특 52
 
5.4%
Other values (64) 402
41.6%
Decimal Number
ValueCountFrequency (%)
1 66
28.1%
2 32
13.6%
3 26
 
11.1%
4 21
 
8.9%
5 19
 
8.1%
0 19
 
8.1%
8 17
 
7.2%
6 12
 
5.1%
7 12
 
5.1%
9 11
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
K 2
28.6%
M 1
 
14.3%
S 1
 
14.3%
Space Separator
ValueCountFrequency (%)
236
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 967
60.9%
Common 614
38.7%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 67
 
6.9%
등 64
 
6.6%
포 64
 
6.6%
동 57
 
5.9%
시 53
 
5.5%
로 52
 
5.4%
울 52
 
5.4%
서 52
 
5.4%
별 52
 
5.4%
특 52
 
5.4%
Other values (64) 402
41.6%
Common
ValueCountFrequency (%)
236
38.4%
1 66
 
10.7%
) 52
 
8.5%
( 52
 
8.5%
2 32
 
5.2%
, 29
 
4.7%
3 26
 
4.2%
4 21
 
3.4%
5 19
 
3.1%
0 19
 
3.1%
Other values (5) 62
 
10.1%
Latin
ValueCountFrequency (%)
B 3
42.9%
K 2
28.6%
M 1
 
14.3%
S 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 967
60.9%
ASCII 621
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
236
38.0%
1 66
 
10.6%
) 52
 
8.4%
( 52
 
8.4%
2 32
 
5.2%
, 29
 
4.7%
3 26
 
4.2%
4 21
 
3.4%
5 19
 
3.1%
0 19
 
3.1%
Other values (9) 69
 
11.1%
Hangul
ValueCountFrequency (%)
영 67
 
6.9%
등 64
 
6.6%
포 64
 
6.6%
동 57
 
5.9%
시 53
 
5.5%
로 52
 
5.4%
울 52
 
5.4%
서 52
 
5.4%
별 52
 
5.4%
특 52
 
5.4%
Other values (64) 402
41.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)95.7%
Missing37
Missing (%)61.7%
Infinite0
Infinite (%)0.0%
Mean7325.6957
Minimum7201
Maximum7439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T20:59:10.737247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7201
5-th percentile7209.5
Q17262.5
median7299
Q37401
95-th percentile7435.6
Maximum7439
Range238
Interquartile range (IQR)138.5

Descriptive statistics

Standard deviation80.447857
Coefficient of variation (CV)0.0109816
Kurtosis-1.441399
Mean7325.6957
Median Absolute Deviation (MAD)80
Skewness0.052389969
Sum168491
Variance6471.8577
MonotonicityNot monotonic
2024-04-06T20:59:11.088048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
7299 2
 
3.3%
7432 1
 
1.7%
7274 1
 
1.7%
7257 1
 
1.7%
7332 1
 
1.7%
7262 1
 
1.7%
7419 1
 
1.7%
7285 1
 
1.7%
7381 1
 
1.7%
7439 1
 
1.7%
Other values (12) 12
 
20.0%
(Missing) 37
61.7%
ValueCountFrequency (%)
7201 1
1.7%
7209 1
1.7%
7214 1
1.7%
7245 1
1.7%
7257 1
1.7%
7262 1
1.7%
7263 1
1.7%
7274 1
1.7%
7282 1
1.7%
7285 1
1.7%
ValueCountFrequency (%)
7439 1
1.7%
7436 1
1.7%
7432 1
1.7%
7429 1
1.7%
7419 1
1.7%
7411 1
1.7%
7391 1
1.7%
7381 1
1.7%
7379 1
1.7%
7352 1
1.7%

사업장명
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-06T20:59:11.557760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.5
Min length2

Characters and Unicode

Total characters390
Distinct characters143
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)96.7%

Sample

1st row(주)롯데삼강
2nd row롯데제과(주)
3rd row롯데웰푸드(주)
4th row(주)롯데삼강
5th row신진푸드
ValueCountFrequency (%)
주식회사 4
 
6.1%
주)롯데삼강 2
 
3.0%
윤수 1
 
1.5%
주)조은장터 1
 
1.5%
푸드텍 1
 
1.5%
윤가성신식품 1
 
1.5%
농가식품 1
 
1.5%
수원성갈비유통 1
 
1.5%
장터 1
 
1.5%
티바에프엔비 1
 
1.5%
Other values (52) 52
78.8%
2024-04-06T20:59:12.420321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 26
 
6.7%
( 21
 
5.4%
) 21
 
5.4%
드 19
 
4.9%
식 15
 
3.8%
푸 13
 
3.3%
통 11
 
2.8%
품 10
 
2.6%
유 10
 
2.6%
사 9
 
2.3%
Other values (133) 235
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
87.2%
Open Punctuation 21
 
5.4%
Close Punctuation 21
 
5.4%
Space Separator 6
 
1.5%
Dash Punctuation 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 26
 
7.6%
드 19
 
5.6%
식 15
 
4.4%
푸 13
 
3.8%
통 11
 
3.2%
품 10
 
2.9%
유 10
 
2.9%
사 9
 
2.6%
성 6
 
1.8%
한 6
 
1.8%
Other values (128) 215
63.2%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
87.2%
Common 50
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 26
 
7.6%
드 19
 
5.6%
식 15
 
4.4%
푸 13
 
3.8%
통 11
 
3.2%
품 10
 
2.9%
유 10
 
2.9%
사 9
 
2.6%
성 6
 
1.8%
한 6
 
1.8%
Other values (128) 215
63.2%
Common
ValueCountFrequency (%)
( 21
42.0%
) 21
42.0%
6
 
12.0%
- 1
 
2.0%
. 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
87.2%
ASCII 50
 
12.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 26
 
7.6%
드 19
 
5.6%
식 15
 
4.4%
푸 13
 
3.8%
통 11
 
3.2%
품 10
 
2.9%
유 10
 
2.9%
사 9
 
2.6%
성 6
 
1.8%
한 6
 
1.8%
Other values (128) 215
63.2%
ASCII
ValueCountFrequency (%)
( 21
42.0%
) 21
42.0%
6
 
12.0%
- 1
 
2.0%
. 1
 
2.0%

최종수정일자
Date

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum2004-02-11 16:31:43
Maximum2024-02-05 09:17:49
2024-04-06T20:59:12.652157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:59:12.884688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
I
43 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 43
71.7%
U 17
 
28.3%

Length

2024-04-06T20:59:13.173494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:13.391145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 43
71.7%
u 17
 
28.3%

데이터갱신일자
Categorical

IMBALANCE 

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2018-08-31 23:59:59.0
43 
2019-05-16 02:40:00.0
 
2
2019-02-01 02:40:00.0
 
1
2021-12-04 22:01:00.0
 
1
2019-03-14 02:40:00.0
 
1
Other values (12)
12 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique15 ?
Unique (%)25.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2022-12-03 22:00:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 43
71.7%
2019-05-16 02:40:00.0 2
 
3.3%
2019-02-01 02:40:00.0 1
 
1.7%
2021-12-04 22:01:00.0 1
 
1.7%
2019-03-14 02:40:00.0 1
 
1.7%
2020-11-04 02:40:00.0 1
 
1.7%
2021-01-02 02:40:00.0 1
 
1.7%
2021-12-08 00:07:00.0 1
 
1.7%
2022-12-03 22:00:00.0 1
 
1.7%
2023-12-02 00:07:00.0 1
 
1.7%
Other values (7) 7
 
11.7%

Length

2024-04-06T20:59:13.657199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 43
35.8%
23:59:59.0 43
35.8%
02:40:00.0 10
 
8.3%
2019-05-16 2
 
1.7%
2022-12-01 2
 
1.7%
00:07:00.0 2
 
1.7%
2023-12-02 1
 
0.8%
2020-12-25 1
 
0.8%
22:05:00.0 1
 
0.8%
2021-10-28 1
 
0.8%
Other values (14) 14
 
11.7%

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
식육가공업
56 
유가공업
 
4

Length

Max length5
Median length5
Mean length4.9333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 56
93.3%
유가공업 4
 
6.7%

Length

2024-04-06T20:59:13.844309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:14.043332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 56
93.3%
유가공업 4
 
6.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)96.5%
Missing3
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean191340.92
Minimum189764.48
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T20:59:14.325582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189764.48
5-th percentile189900.31
Q1190615.29
median191082.3
Q3191836.54
95-th percentile193054.74
Maximum194632.53
Range4868.0489
Interquartile range (IQR)1221.2448

Descriptive statistics

Standard deviation1038.8297
Coefficient of variation (CV)0.0054292084
Kurtosis0.67579245
Mean191340.92
Median Absolute Deviation (MAD)707.93978
Skewness0.81118894
Sum10906433
Variance1079167.2
MonotonicityNot monotonic
2024-04-06T20:59:14.567286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191024.651979979 2
 
3.3%
189814.860666388 2
 
3.3%
189986.498936099 1
 
1.7%
191236.216659536 1
 
1.7%
190700.452096017 1
 
1.7%
190947.496460148 1
 
1.7%
191453.509900117 1
 
1.7%
191629.115278781 1
 
1.7%
192226.019831033 1
 
1.7%
191908.495385118 1
 
1.7%
Other values (45) 45
75.0%
(Missing) 3
 
5.0%
ValueCountFrequency (%)
189764.477432316 1
1.7%
189814.860666388 2
3.3%
189921.671894763 1
1.7%
189986.498936099 1
1.7%
190053.217608387 1
1.7%
190147.9337831 1
1.7%
190244.612135535 1
1.7%
190298.841931736 1
1.7%
190374.363134139 1
1.7%
190402.238394045 1
1.7%
ValueCountFrequency (%)
194632.526367463 1
1.7%
193565.856956811 1
1.7%
193310.621023674 1
1.7%
192990.764629293 1
1.7%
192985.89393686 1
1.7%
192910.201811963 1
1.7%
192773.803537193 1
1.7%
192740.987211207 1
1.7%
192498.960983466 1
1.7%
192226.019831033 1
1.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)96.5%
Missing3
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean445508.3
Minimum442988.41
Maximum448966.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T20:59:14.823889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442988.41
5-th percentile443387.06
Q1444424.07
median445738.54
Q3446496.46
95-th percentile447308.24
Maximum448966.46
Range5978.0506
Interquartile range (IQR)2072.3941

Descriptive statistics

Standard deviation1368.9124
Coefficient of variation (CV)0.0030726978
Kurtosis-0.60651874
Mean445508.3
Median Absolute Deviation (MAD)1131.8666
Skewness0.063580718
Sum25393973
Variance1873921.1
MonotonicityNot monotonic
2024-04-06T20:59:15.117092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446421.72002587 2
 
3.3%
446221.013701754 2
 
3.3%
445955.499303479 1
 
1.7%
446066.47341564 1
 
1.7%
444818.181074076 1
 
1.7%
443598.689799608 1
 
1.7%
443520.607560922 1
 
1.7%
446068.386837855 1
 
1.7%
444226.330065013 1
 
1.7%
444076.518827512 1
 
1.7%
Other values (45) 45
75.0%
(Missing) 3
 
5.0%
ValueCountFrequency (%)
442988.409457455 1
1.7%
443009.331056058 1
1.7%
443365.164071781 1
1.7%
443392.532730331 1
1.7%
443520.607560922 1
1.7%
443598.689799608 1
1.7%
443641.853087923 1
1.7%
443878.031701894 1
1.7%
444076.518827512 1
1.7%
444147.011022522 1
1.7%
ValueCountFrequency (%)
448966.460102132 1
1.7%
448107.484024722 1
1.7%
447739.896956998 1
1.7%
447200.319546861 1
1.7%
447023.441993034 1
1.7%
447020.956097736 1
1.7%
446900.264400435 1
1.7%
446900.060108156 1
1.7%
446897.452489918 1
1.7%
446872.921161646 1
1.7%

축산업무구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
축산물가공업
54 
<NA>
6 

Length

Max length6
Median length6
Mean length5.8
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 54
90.0%
<NA> 6
 
10.0%

Length

2024-04-06T20:59:15.439960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:15.670262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 54
90.0%
na 6
 
10.0%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
식육가공업
51 
<NA>
6 
유가공업
 
3

Length

Max length5
Median length5
Mean length4.85
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 51
85.0%
<NA> 6
 
10.0%
유가공업 3
 
5.0%

Length

2024-04-06T20:59:15.970826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:16.240622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 51
85.0%
na 6
 
10.0%
유가공업 3
 
5.0%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
54 
<NA>
6 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 54
90.0%
<NA> 6
 
10.0%

Length

2024-04-06T20:59:16.569042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:16.804734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
90.0%
na 6
 
10.0%

권리주체일련번호
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
000
29 
L00
25 
<NA>
6 

Length

Max length4
Median length3
Mean length3.1
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 29
48.3%
L00 25
41.7%
<NA> 6
 
10.0%

Length

2024-04-06T20:59:17.033687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:17.246326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 29
48.3%
l00 25
41.7%
na 6
 
10.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
54 
<NA>
6 

Length

Max length4
Median length1
Mean length1.3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 54
90.0%
<NA> 6
 
10.0%

Length

2024-04-06T20:59:17.448900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:59:17.646706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
90.0%
na 6
 
10.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0318000031800000041966000119660620<NA>3폐업2폐업20051216<NA><NA><NA><NA>810.0<NA>서울특별시 영등포구 문래동6가 21번지서울특별시 영등포구 선유로9길 30 (문래동6가)7282(주)롯데삼강2011-10-30 15:44:29I2018-08-31 23:59:59.0유가공업189814.860666446221.013702축산물가공업유가공업0L000
1318000031800000041969000119690307<NA>3폐업2폐업20140113<NA><NA><NA><NA>1912.0<NA>서울특별시 영등포구 양평동4가 20번지<NA><NA>롯데제과(주)2014-01-13 09:05:17I2018-08-31 23:59:59.0유가공업<NA><NA>축산물가공업유가공업0L000
231800003180000004196900021969-03-07<NA>1영업/정상0정상<NA><NA><NA><NA>2670-66510.0<NA>서울특별시 영등포구 양평동4가 16-1서울특별시 영등포구 양평로21길 25 (양평동4가)7209롯데웰푸드(주)2023-04-18 10:32:15U2022-12-03 22:00:00.0유가공업190452.870314448107.484025<NA><NA><NA><NA><NA>
3318000031800000041986000119860506<NA>3폐업2폐업20051216<NA><NA><NA>2629-0121~20.0<NA>서울특별시 영등포구 문래동6가 21번지서울특별시 영등포구 선유로9길 30 (문래동6가)<NA>(주)롯데삼강2005-12-16 17:02:30I2018-08-31 23:59:59.0식육가공업189814.860666446221.013702축산물가공업식육가공업0L000
4318000031800000041988000119880511<NA>3폐업2폐업20040402<NA><NA><NA>2637-51110.0<NA>서울특별시 영등포구 양평동3가 3-1번지서울특별시 영등포구 선유동1로 37 (양평동3가)<NA>신진푸드2004-04-02 08:40:05I2018-08-31 23:59:59.0식육가공업190374.363134447023.441993축산물가공업식육가공업00000
5318000031800000041990000119901207<NA>3폐업2폐업20070718<NA><NA><NA>2633-66940.0<NA>서울특별시 영등포구 문래동5가 4-1번지서울특별시 영등포구 선유로 11 (문래동5가)<NA>제니코식품(주)2007-07-18 18:09:32I2018-08-31 23:59:59.0식육가공업189986.498936445955.499303축산물가공업식육가공업0L000
6318000031800000041994000119940826<NA>3폐업2폐업20040226<NA><NA><NA><NA>117.2<NA>서울특별시 영등포구 영등포동4가 441-21번지<NA><NA>(주)경방유통 경방필백화점2004-04-28 11:05:05I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업0L000
7318000031800000041998000119980610<NA>3폐업2폐업20060516<NA><NA><NA>2675-11150.0<NA>서울특별시 영등포구 당산동2가 12-2번지서울특별시 영등포구 영등포로22길 5 (당산동2가)<NA>한양유통2006-05-16 18:22:26I2018-08-31 23:59:59.0식육가공업190598.753325446522.187023축산물가공업식육가공업00000
8318000031800000041998000219980910<NA>4취소/말소/만료/정지/중지4말소20100812<NA><NA>20100812<NA>110.0<NA>서울특별시 영등포구 양평동4가 21번지<NA><NA>개성유통 체인사업본부2011-10-31 14:38:42I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업00000
9318000031800000042000000220000914<NA>3폐업2폐업20110831<NA><NA><NA>789-576436.0<NA>서울특별시 영등포구 여의도동 60번지서울특별시 영등포구 63로 50 (여의도동)<NA>한화호텔앤드리조트(주)2011-08-31 18:12:08I2018-08-31 23:59:59.0식육가공업194632.526367446401.926526축산물가공업식육가공업0L000
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
5031800003180000004201400072014-10-22<NA>1영업/정상0정상<NA><NA><NA><NA>02-2633-06660.0<NA>서울특별시 영등포구 당산동2가 162-13 4층서울특별시 영등포구 선유동1로 24, 4층 (당산동2가)7263당산동부여집포장판매사업부2024-02-05 09:17:49U2023-12-02 00:07:00.0식육가공업190402.238394446900.2644<NA><NA><NA><NA><NA>
51318000031800000042014000820141222<NA>3폐업2폐업20161227<NA><NA>2016122702-2685-54330.0<NA>서울특별시 영등포구 대림동 877-4번지서울특별시 영등포구 디지털로 406-4, 1층 (대림동)7439초원식품2016-12-27 16:00:14I2018-08-31 23:59:59.0식육가공업191441.861979443392.53273축산물가공업식육가공업0L000
52318000031800000042015000120150317<NA>3폐업2폐업20181106<NA><NA>20181106<NA>0.0<NA>서울특별시 영등포구 대림동 668-13번지서울특별시 영등포구 가마산로 383, 1층 (대림동)7381보성식품2018-11-06 13:36:25U2018-11-08 02:36:50.0식육가공업191082.30291444516.923618축산물가공업식육가공업00000
53318000031800000042015000220150907<NA>3폐업2폐업20190903<NA><NA>2019090302-2633-33600.0<NA>서울특별시 영등포구 문래동5가 10번지 B111,B112서울특별시 영등포구 선유로3길 10, B111,B112호 (문래동5가, 하우스디비즈)7285(주)아이딜홈2019-09-03 17:18:44U2019-09-05 02:40:00.0식육가공업189921.671895445990.538307축산물가공업식육가공업0L000
54318000031800000042016000120160913<NA>3폐업2폐업20170111<NA><NA>2017011102-836-78880.0<NA>서울특별시 영등포구 대림동 1039-13번지 지하1층서울특별시 영등포구 디지털로53길 23, 지하1층 (대림동, 한송빌딩)7419형제유통2017-01-12 10:20:42I2018-08-31 23:59:59.0식육가공업191070.076823443365.164072축산물가공업식육가공업00000
55318000031800000042016000220161214<NA>4취소/말소/만료/정지/중지4말소20190513<NA><NA><NA>02-3689-13370.0<NA>서울특별시 영등포구 양평동1가 31-10번지 지하1층서울특별시 영등포구 선유로 102, 지하1층 (양평동1가, MK빌딩)7262더클리버2019-05-14 10:39:55U2019-05-16 02:40:00.0식육가공업190244.612136446755.219714축산물가공업식육가공업00000
56318000031800000042017000120170822<NA>3폐업2폐업20190207<NA><NA>2019020702-334-33780.0<NA>서울특별시 영등포구 문래동3가 58-2번지 2층서울특별시 영등포구 도림로128길 21, 2층 (문래동3가)7299주식회사 차차2019-02-07 18:27:19U2019-02-09 02:40:00.0식육가공업190615.290861445911.295447축산물가공업식육가공업0L000
57318000031800000042019000120190718<NA>3폐업2폐업20211025<NA><NA>20211025070-8822-24300.0<NA>서울특별시 영등포구 여의도동 45-1 SK증권빌딩서울특별시 영등포구 국제금융로8길 31, SK증권빌딩 지하2층 (여의도동)7332플랜트아이스크림2021-10-26 17:17:12U2021-10-28 02:40:00.0유가공업193565.856957446399.54937축산물가공업유가공업0L000
5831800003180000004202100012021-08-23<NA>1영업/정상0정상<NA><NA><NA><NA><NA>140.5<NA>서울특별시 영등포구 당산동3가 135 지하1층서울특별시 영등포구 국회대로36길 4, 지하1층 (당산동3가)7257주식회사 대만족2023-02-23 11:20:36U2022-12-01 22:05:00.0식육가공업190915.009275447200.319547<NA><NA><NA><NA><NA>
5931800003180000004202200012022-11-25<NA>3폐업2폐업2023-02-13<NA><NA>2023-02-1302-3667-35570.0<NA>서울특별시 영등포구 양평동2가 33-77서울특별시 영등포구 영등포로5길 48(양평동2가)7274딩동댕2023-02-13 15:32:33U2022-12-01 23:05:00.0식육가공업189764.477432447020.956098<NA><NA><NA><NA><NA>