Overview

Dataset statistics

Number of variables30
Number of observations36
Missing cells281
Missing cells (%)26.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory257.7 B

Variable types

Categorical10
Numeric5
DateTime5
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18116/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (57.0%)Imbalance
인허가취소일자 has 36 (100.0%) missing valuesMissing
폐업일자 has 8 (22.2%) missing valuesMissing
휴업시작일자 has 36 (100.0%) missing valuesMissing
휴업종료일자 has 36 (100.0%) missing valuesMissing
재개업일자 has 27 (75.0%) missing valuesMissing
전화번호 has 9 (25.0%) missing valuesMissing
소재지우편번호 has 36 (100.0%) missing valuesMissing
도로명주소 has 1 (2.8%) missing valuesMissing
도로명우편번호 has 20 (55.6%) missing valuesMissing
축산일련번호 has 36 (100.0%) missing valuesMissing
총인원 has 36 (100.0%) 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
축산일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 26 (72.2%) zerosZeros

Reproduction

Analysis started2024-05-11 03:58:50.941969
Analysis finished2024-05-11 03:58:51.834513
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
3140000
36 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 36
100.0%

Length

2024-05-11T03:58:52.098314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:52.462307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 36
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.14 × 1017
Minimum3.14 × 1017
Maximum3.14 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T03:58:52.811404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.14 × 1017
5-th percentile3.14 × 1017
Q13.14 × 1017
median3.14 × 1017
Q33.14 × 1017
95-th percentile3.14 × 1017
Maximum3.14 × 1017
Range250000
Interquartile range (IQR)89984

Descriptive statistics

Standard deviation66699.269
Coefficient of variation (CV)2.1241805 × 10-13
Kurtosis-0.28515905
Mean3.14 × 1017
Median Absolute Deviation (MAD)49984
Skewness0.60238302
Sum-7.1427441 × 1018
Variance4.4487925 × 109
MonotonicityStrictly increasing
2024-05-11T03:58:53.365973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
314000000419990001 1
 
2.8%
314000000420090001 1
 
2.8%
314000000420110001 1
 
2.8%
314000000420110002 1
 
2.8%
314000000420110003 1
 
2.8%
314000000420120001 1
 
2.8%
314000000420130001 1
 
2.8%
314000000420130002 1
 
2.8%
314000000420130003 1
 
2.8%
314000000420140001 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
314000000419990001 1
2.8%
314000000419990002 1
2.8%
314000000420010001 1
2.8%
314000000420010002 1
2.8%
314000000420020001 1
2.8%
314000000420020002 1
2.8%
314000000420030001 1
2.8%
314000000420030003 1
2.8%
314000000420040001 1
2.8%
314000000420040002 1
2.8%
ValueCountFrequency (%)
314000000420240001 1
2.8%
314000000420230001 1
2.8%
314000000420220001 1
2.8%
314000000420190001 1
2.8%
314000000420170001 1
2.8%
314000000420150001 1
2.8%
314000000420140002 1
2.8%
314000000420140001 1
2.8%
314000000420130003 1
2.8%
314000000420130002 1
2.8%

인허가일자
Date

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum1999-11-08 00:00:00
Maximum2024-02-05 00:00:00
2024-05-11T03:58:53.884410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:54.311858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
3
28 
1
8 

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 28
77.8%
1 8
 
22.2%

Length

2024-05-11T03:58:54.832026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:55.320027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 28
77.8%
1 8
 
22.2%

영업상태명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
폐업
28 
영업/정상
8 

Length

Max length5
Median length2
Mean length2.6666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 28
77.8%
영업/정상 8
 
22.2%

Length

2024-05-11T03:58:55.717860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:56.027403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 28
77.8%
영업/정상 8
 
22.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2
28 
0
8 

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 28
77.8%
0 8
 
22.2%

Length

2024-05-11T03:58:56.435306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:56.800772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 28
77.8%
0 8
 
22.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
폐업
28 
정상
8 

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 28
77.8%
정상 8
 
22.2%

Length

2024-05-11T03:58:57.294075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:57.651891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 28
77.8%
정상 8
 
22.2%

폐업일자
Date

MISSING 

Distinct27
Distinct (%)96.4%
Missing8
Missing (%)22.2%
Memory size420.0 B
Minimum2003-06-02 00:00:00
Maximum2023-12-26 00:00:00
2024-05-11T03:58:57.934404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:58.352026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

재개업일자
Date

MISSING 

Distinct8
Distinct (%)88.9%
Missing27
Missing (%)75.0%
Memory size420.0 B
Minimum2018-02-07 00:00:00
Maximum2023-12-26 00:00:00
2024-05-11T03:58:58.768983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:59.206051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

전화번호
Text

MISSING 

Distinct26
Distinct (%)96.3%
Missing9
Missing (%)25.0%
Memory size420.0 B
2024-05-11T03:58:59.872955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.9259259
Min length9

Characters and Unicode

Total characters268
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

Unique25 ?
Unique (%)92.6%

Sample

1st row2603-7108
2nd row2643-4161
3rd row2601-8236
4th row2690-3397
5th row2642-7624
ValueCountFrequency (%)
2603-7108 2
 
7.4%
3477-6272 1
 
3.7%
2654-9293 1
 
3.7%
070-8801-3029 1
 
3.7%
02-6956-8906 1
 
3.7%
2603-8838 1
 
3.7%
2603-0883 1
 
3.7%
3141-7201 1
 
3.7%
2692-3141 1
 
3.7%
2697-4492 1
 
3.7%
Other values (16) 16
59.3%
2024-05-11T03:59:00.993194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 43
16.0%
6 36
13.4%
- 35
13.1%
0 31
11.6%
3 24
9.0%
4 22
8.2%
9 19
7.1%
8 18
6.7%
7 17
 
6.3%
1 17
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 233
86.9%
Dash Punctuation 35
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 43
18.5%
6 36
15.5%
0 31
13.3%
3 24
10.3%
4 22
9.4%
9 19
8.2%
8 18
7.7%
7 17
 
7.3%
1 17
 
7.3%
5 6
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 268
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 43
16.0%
6 36
13.4%
- 35
13.1%
0 31
11.6%
3 24
9.0%
4 22
8.2%
9 19
7.1%
8 18
6.7%
7 17
 
6.3%
1 17
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 43
16.0%
6 36
13.4%
- 35
13.1%
0 31
11.6%
3 24
9.0%
4 22
8.2%
9 19
7.1%
8 18
6.7%
7 17
 
6.3%
1 17
 
6.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.8175
Minimum0
Maximum245.7
Zeros26
Zeros (%)72.2%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T03:59:01.411326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329.305
95-th percentile99.6275
Maximum245.7
Range245.7
Interquartile range (IQR)29.305

Descriptive statistics

Standard deviation50.249296
Coefficient of variation (CV)2.1097636
Kurtosis10.284388
Mean23.8175
Median Absolute Deviation (MAD)0
Skewness2.9147962
Sum857.43
Variance2524.9917
MonotonicityNot monotonic
2024-05-11T03:59:01.885886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 26
72.2%
44.0 1
 
2.8%
81.3 1
 
2.8%
27.9 1
 
2.8%
90.9 1
 
2.8%
245.7 1
 
2.8%
50.0 1
 
2.8%
97.7 1
 
2.8%
81.0 1
 
2.8%
33.52 1
 
2.8%
ValueCountFrequency (%)
0.0 26
72.2%
27.9 1
 
2.8%
33.52 1
 
2.8%
44.0 1
 
2.8%
50.0 1
 
2.8%
81.0 1
 
2.8%
81.3 1
 
2.8%
90.9 1
 
2.8%
97.7 1
 
2.8%
105.41 1
 
2.8%
ValueCountFrequency (%)
245.7 1
2.8%
105.41 1
2.8%
97.7 1
2.8%
90.9 1
2.8%
81.3 1
2.8%
81.0 1
2.8%
50.0 1
2.8%
44.0 1
2.8%
33.52 1
2.8%
27.9 1
2.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

지번주소
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-11T03:59:02.352288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length26.277778
Min length20

Characters and Unicode

Total characters946
Distinct characters54
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row서울특별시 양천구 신월동 136-5번지 지하1층
2nd row서울특별시 양천구 목동 406-68번지 ,78호(지하1층)
3rd row서울특별시 양천구 신월동 517-4번지 지하1층
4th row서울특별시 양천구 신월동 927-1번지 지하1층
5th row서울특별시 양천구 신정동 1052-3번지 상운프라자(104~106)
ValueCountFrequency (%)
서울특별시 36
20.3%
양천구 36
20.3%
신월동 17
 
9.6%
신정동 13
 
7.3%
지하1층 11
 
6.2%
목동 6
 
3.4%
1층 6
 
3.4%
지층 3
 
1.7%
927-1번지 2
 
1.1%
1052-3번지 2
 
1.1%
Other values (41) 45
25.4%
2024-05-11T03:59:03.605034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
 
18.0%
1 50
 
5.3%
지 44
 
4.7%
서 36
 
3.8%
울 36
 
3.8%
특 36
 
3.8%
별 36
 
3.8%
시 36
 
3.8%
양 36
 
3.8%
천 36
 
3.8%
Other values (44) 430
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 529
55.9%
Decimal Number 204
 
21.6%
Space Separator 170
 
18.0%
Dash Punctuation 36
 
3.8%
Close Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 44
 
8.3%
서 36
 
6.8%
울 36
 
6.8%
특 36
 
6.8%
별 36
 
6.8%
시 36
 
6.8%
양 36
 
6.8%
천 36
 
6.8%
구 36
 
6.8%
동 36
 
6.8%
Other values (28) 161
30.4%
Decimal Number
ValueCountFrequency (%)
1 50
24.5%
2 28
13.7%
0 21
10.3%
4 20
 
9.8%
5 19
 
9.3%
3 19
 
9.3%
7 15
 
7.4%
6 13
 
6.4%
9 10
 
4.9%
8 9
 
4.4%
Space Separator
ValueCountFrequency (%)
170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 529
55.9%
Common 417
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 44
 
8.3%
서 36
 
6.8%
울 36
 
6.8%
특 36
 
6.8%
별 36
 
6.8%
시 36
 
6.8%
양 36
 
6.8%
천 36
 
6.8%
구 36
 
6.8%
동 36
 
6.8%
Other values (28) 161
30.4%
Common
ValueCountFrequency (%)
170
40.8%
1 50
 
12.0%
- 36
 
8.6%
2 28
 
6.7%
0 21
 
5.0%
4 20
 
4.8%
5 19
 
4.6%
3 19
 
4.6%
7 15
 
3.6%
6 13
 
3.1%
Other values (6) 26
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 529
55.9%
ASCII 417
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
40.8%
1 50
 
12.0%
- 36
 
8.6%
2 28
 
6.7%
0 21
 
5.0%
4 20
 
4.8%
5 19
 
4.6%
3 19
 
4.6%
7 15
 
3.6%
6 13
 
3.1%
Other values (6) 26
 
6.2%
Hangul
ValueCountFrequency (%)
지 44
 
8.3%
서 36
 
6.8%
울 36
 
6.8%
특 36
 
6.8%
별 36
 
6.8%
시 36
 
6.8%
양 36
 
6.8%
천 36
 
6.8%
구 36
 
6.8%
동 36
 
6.8%
Other values (28) 161
30.4%

도로명주소
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing1
Missing (%)2.8%
Memory size420.0 B
2024-05-11T03:59:04.351677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length28.914286
Min length23

Characters and Unicode

Total characters1012
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row서울특별시 양천구 남부순환로 395, 지하1층 (신월동)
2nd row서울특별시 양천구 오목로 313-7 (목동,,78호(지하1층))
3rd row서울특별시 양천구 오목로 42 (신월동,지하1층)
4th row서울특별시 양천구 지양로10길 12 (신월동,지하1층)
5th row서울특별시 양천구 남부순환로 326 (신월동,지하1층)
ValueCountFrequency (%)
서울특별시 35
18.0%
양천구 35
18.0%
신정동 10
 
5.2%
신월동 10
 
5.2%
남부순환로 7
 
3.6%
신월동,지하1층 5
 
2.6%
중앙로 4
 
2.1%
230 3
 
1.5%
104호 3
 
1.5%
신월로 3
 
1.5%
Other values (63) 79
40.7%
2024-05-11T03:59:05.624252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
 
15.7%
1 42
 
4.2%
동 41
 
4.1%
양 37
 
3.7%
서 36
 
3.6%
) 36
 
3.6%
( 36
 
3.6%
천 35
 
3.5%
시 35
 
3.5%
울 35
 
3.5%
Other values (60) 520
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
60.1%
Space Separator 159
 
15.7%
Decimal Number 139
 
13.7%
Close Punctuation 36
 
3.6%
Open Punctuation 36
 
3.6%
Other Punctuation 31
 
3.1%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 41
 
6.7%
양 37
 
6.1%
서 36
 
5.9%
천 35
 
5.8%
시 35
 
5.8%
울 35
 
5.8%
구 35
 
5.8%
별 35
 
5.8%
신 35
 
5.8%
특 35
 
5.8%
Other values (45) 249
41.0%
Decimal Number
ValueCountFrequency (%)
1 42
30.2%
3 23
16.5%
2 19
13.7%
0 13
 
9.4%
4 12
 
8.6%
5 8
 
5.8%
9 7
 
5.0%
7 6
 
4.3%
6 5
 
3.6%
8 4
 
2.9%
Space Separator
ValueCountFrequency (%)
159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
60.1%
Common 404
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 41
 
6.7%
양 37
 
6.1%
서 36
 
5.9%
천 35
 
5.8%
시 35
 
5.8%
울 35
 
5.8%
구 35
 
5.8%
별 35
 
5.8%
신 35
 
5.8%
특 35
 
5.8%
Other values (45) 249
41.0%
Common
ValueCountFrequency (%)
159
39.4%
1 42
 
10.4%
) 36
 
8.9%
( 36
 
8.9%
, 31
 
7.7%
3 23
 
5.7%
2 19
 
4.7%
0 13
 
3.2%
4 12
 
3.0%
5 8
 
2.0%
Other values (5) 25
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
60.1%
ASCII 404
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
39.4%
1 42
 
10.4%
) 36
 
8.9%
( 36
 
8.9%
, 31
 
7.7%
3 23
 
5.7%
2 19
 
4.7%
0 13
 
3.2%
4 12
 
3.0%
5 8
 
2.0%
Other values (5) 25
 
6.2%
Hangul
ValueCountFrequency (%)
동 41
 
6.7%
양 37
 
6.1%
서 36
 
5.9%
천 35
 
5.8%
시 35
 
5.8%
울 35
 
5.8%
구 35
 
5.8%
별 35
 
5.8%
신 35
 
5.8%
특 35
 
5.8%
Other values (45) 249
41.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)81.2%
Missing20
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean7997.25
Minimum7900
Maximum8091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T03:59:06.237852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7912
Q17926.75
median7991.5
Q38083.25
95-th percentile8091
Maximum8091
Range191
Interquartile range (IQR)156.5

Descriptive statistics

Standard deviation76.18005
Coefficient of variation (CV)0.0095257807
Kurtosis-1.893403
Mean7997.25
Median Absolute Deviation (MAD)71.5
Skewness0.12890717
Sum127956
Variance5803.4
MonotonicityNot monotonic
2024-05-11T03:59:06.816527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8091 3
 
8.3%
7920 2
 
5.6%
7916 1
 
2.8%
7900 1
 
2.8%
8082 1
 
2.8%
8087 1
 
2.8%
8017 1
 
2.8%
7933 1
 
2.8%
8030 1
 
2.8%
8047 1
 
2.8%
Other values (3) 3
 
8.3%
(Missing) 20
55.6%
ValueCountFrequency (%)
7900 1
2.8%
7916 1
2.8%
7920 2
5.6%
7929 1
2.8%
7933 1
2.8%
7936 1
2.8%
7966 1
2.8%
8017 1
2.8%
8030 1
2.8%
8047 1
2.8%
ValueCountFrequency (%)
8091 3
8.3%
8087 1
 
2.8%
8082 1
 
2.8%
8047 1
 
2.8%
8030 1
 
2.8%
8017 1
 
2.8%
7966 1
 
2.8%
7936 1
 
2.8%
7933 1
 
2.8%
7929 1
 
2.8%

사업장명
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-05-11T03:59:07.404909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length6.7222222
Min length2

Characters and Unicode

Total characters242
Distinct characters124
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)88.9%

Sample

1st row근산식품
2nd row우성축산
3rd row국제유통
4th row거성종합식품
5th row(주)쉬드티롤 컴퍼니
ValueCountFrequency (%)
근산식품 2
 
5.0%
유신우(주 2
 
5.0%
주)라틴앤글로벌 1
 
2.5%
렌위치코리아 1
 
2.5%
공장 1
 
2.5%
주)비움랩스 1
 
2.5%
주)밸런스팩토리 1
 
2.5%
주)동인산업 1
 
2.5%
주)계원푸드 1
 
2.5%
주)벽제갈비신월씨케이지점 1
 
2.5%
Other values (28) 28
70.0%
2024-05-11T03:59:09.086504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 16
 
6.6%
( 15
 
6.2%
) 15
 
6.2%
드 9
 
3.7%
식 9
 
3.7%
품 8
 
3.3%
푸 7
 
2.9%
스 6
 
2.5%
유 5
 
2.1%
리 4
 
1.7%
Other values (114) 148
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
78.1%
Open Punctuation 15
 
6.2%
Close Punctuation 15
 
6.2%
Lowercase Letter 13
 
5.4%
Space Separator 4
 
1.7%
Uppercase Letter 3
 
1.2%
Other Punctuation 3
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 16
 
8.5%
드 9
 
4.8%
식 9
 
4.8%
품 8
 
4.2%
푸 7
 
3.7%
스 6
 
3.2%
유 5
 
2.6%
리 4
 
2.1%
산 4
 
2.1%
신 4
 
2.1%
Other values (95) 117
61.9%
Lowercase Letter
ValueCountFrequency (%)
m 2
15.4%
i 2
15.4%
s 1
7.7%
k 1
7.7%
t 1
7.7%
c 1
7.7%
h 1
7.7%
e 1
7.7%
n 1
7.7%
p 1
7.7%
Other Punctuation
ValueCountFrequency (%)
; 1
33.3%
& 1
33.3%
' 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
K 2
66.7%
C 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
78.1%
Common 37
 
15.3%
Latin 16
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 16
 
8.5%
드 9
 
4.8%
식 9
 
4.8%
품 8
 
4.2%
푸 7
 
3.7%
스 6
 
3.2%
유 5
 
2.6%
리 4
 
2.1%
산 4
 
2.1%
신 4
 
2.1%
Other values (95) 117
61.9%
Latin
ValueCountFrequency (%)
m 2
12.5%
K 2
12.5%
i 2
12.5%
s 1
 
6.2%
k 1
 
6.2%
t 1
 
6.2%
c 1
 
6.2%
h 1
 
6.2%
e 1
 
6.2%
n 1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
( 15
40.5%
) 15
40.5%
4
 
10.8%
; 1
 
2.7%
& 1
 
2.7%
' 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
78.1%
ASCII 53
 
21.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 16
 
8.5%
드 9
 
4.8%
식 9
 
4.8%
품 8
 
4.2%
푸 7
 
3.7%
스 6
 
3.2%
유 5
 
2.6%
리 4
 
2.1%
산 4
 
2.1%
신 4
 
2.1%
Other values (95) 117
61.9%
ASCII
ValueCountFrequency (%)
( 15
28.3%
) 15
28.3%
4
 
7.5%
m 2
 
3.8%
K 2
 
3.8%
i 2
 
3.8%
s 1
 
1.9%
k 1
 
1.9%
t 1
 
1.9%
c 1
 
1.9%
Other values (9) 9
17.0%

최종수정일자
Date

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2003-06-04 13:54:20
Maximum2024-02-05 10:20:30
2024-05-11T03:59:09.753247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:59:10.527182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
I
26 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 26
72.2%
U 10
 
27.8%

Length

2024-05-11T03:59:11.399811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:11.756484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 26
72.2%
u 10
 
27.8%

데이터갱신일자
Date

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:07:00
2024-05-11T03:59:12.033865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:59:12.640116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
식육가공업
31 
유가공업
4 
알가공업
 
1

Length

Max length5
Median length5
Mean length4.8611111
Min length4

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 31
86.1%
유가공업 4
 
11.1%
알가공업 1
 
2.8%

Length

2024-05-11T03:59:13.349763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:13.777432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 31
86.1%
유가공업 4
 
11.1%
알가공업 1
 
2.8%

좌표정보(X)
Real number (ℝ)

Distinct29
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186549.81
Minimum184540.01
Maximum189444.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T03:59:14.243315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184540.01
5-th percentile184908.39
Q1185268.66
median186085.01
Q3187280.45
95-th percentile188853.33
Maximum189444.83
Range4904.8214
Interquartile range (IQR)2011.7853

Descriptive statistics

Standard deviation1417.2159
Coefficient of variation (CV)0.0075969838
Kurtosis-0.93667863
Mean186549.81
Median Absolute Deviation (MAD)994.36973
Skewness0.50281234
Sum6715793.2
Variance2008500.9
MonotonicityNot monotonic
2024-05-11T03:59:14.667684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
187079.375126738 4
 
11.1%
185005.79221479 3
 
8.3%
185268.664167128 2
 
5.6%
185479.616483618 2
 
5.6%
185980.799038032 1
 
2.8%
187943.072003678 1
 
2.8%
185693.044094824 1
 
2.8%
186040.36 1
 
2.8%
186129.650799522 1
 
2.8%
186648.898214462 1
 
2.8%
Other values (19) 19
52.8%
ValueCountFrequency (%)
184540.012734091 1
 
2.8%
184616.195 1
 
2.8%
185005.79221479 3
8.3%
185199.742774581 1
 
2.8%
185233.191597169 1
 
2.8%
185253.95936223 1
 
2.8%
185268.664167128 2
5.6%
185458.613850038 1
 
2.8%
185479.616483618 2
5.6%
185693.044094824 1
 
2.8%
ValueCountFrequency (%)
189444.834114092 1
2.8%
189151.208015925 1
2.8%
188754.040095027 1
2.8%
188651.920733513 1
2.8%
188650.113584937 1
2.8%
188483.696639364 1
2.8%
188456.486375706 1
2.8%
187943.072003678 1
2.8%
187553.461499446 1
2.8%
187189.445443719 1
2.8%

좌표정보(Y)
Real number (ℝ)

Distinct29
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447033.79
Minimum444965.53
Maximum449254.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-05-11T03:59:15.048563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444965.53
5-th percentile445473.27
Q1446186.63
median446801.63
Q3447796.18
95-th percentile449146.49
Maximum449254.52
Range4288.9935
Interquartile range (IQR)1609.5439

Descriptive statistics

Standard deviation1085.5083
Coefficient of variation (CV)0.0024282465
Kurtosis-0.33004213
Mean447033.79
Median Absolute Deviation (MAD)685.00221
Skewness0.46182183
Sum16093217
Variance1178328.2
MonotonicityNot monotonic
2024-05-11T03:59:15.411291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
446116.629313272 4
 
11.1%
447796.176428261 3
 
8.3%
446801.631518906 2
 
5.6%
445976.962071391 2
 
5.6%
445487.569280509 1
 
2.8%
447573.99002822 1
 
2.8%
447076.595450556 1
 
2.8%
446753.795000001 1
 
2.8%
446424.107429543 1
 
2.8%
447060.449766431 1
 
2.8%
Other values (19) 19
52.8%
ValueCountFrequency (%)
444965.527121198 1
 
2.8%
445430.359091548 1
 
2.8%
445487.569280509 1
 
2.8%
445976.962071391 2
5.6%
446116.629313272 4
11.1%
446209.966949064 1
 
2.8%
446358.120598616 1
 
2.8%
446424.107429543 1
 
2.8%
446525.602276653 1
 
2.8%
446538.481314489 1
 
2.8%
ValueCountFrequency (%)
449254.5206484 1
 
2.8%
449247.302635213 1
 
2.8%
449112.890911306 1
 
2.8%
448667.450918409 1
 
2.8%
448399.055 1
 
2.8%
448357.938147537 1
 
2.8%
448200.067716589 1
 
2.8%
447796.176428261 3
8.3%
447573.99002822 1
 
2.8%
447283.533139106 1
 
2.8%

축산업무구분명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
축산물가공업
30 
<NA>
6 

Length

Max length6
Median length6
Mean length5.6666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 30
83.3%
<NA> 6
 
16.7%

Length

2024-05-11T03:59:15.822557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:16.210613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 30
83.3%
na 6
 
16.7%

축산물가공업구분명
Categorical

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
식육가공업
28 
<NA>
6 
알가공업
 
1
유가공업
 
1

Length

Max length5
Median length5
Mean length4.7777778
Min length4

Unique

Unique2 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 28
77.8%
<NA> 6
 
16.7%
알가공업 1
 
2.8%
유가공업 1
 
2.8%

Length

2024-05-11T03:59:16.596672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:17.067887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 28
77.8%
na 6
 
16.7%
알가공업 1
 
2.8%
유가공업 1
 
2.8%

축산일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

권리주체일련번호
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
000
20 
L00
10 
<NA>
6 

Length

Max length4
Median length3
Mean length3.1666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 20
55.6%
L00 10
27.8%
<NA> 6
 
16.7%

Length

2024-05-11T03:59:17.571743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:18.095836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 20
55.6%
l00 10
27.8%
na 6
 
16.7%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0314000031400000041999000119991108<NA>3폐업2폐업20200521<NA><NA>202005212603-71080.0<NA>서울특별시 양천구 신월동 136-5번지 지하1층서울특별시 양천구 남부순환로 395, 지하1층 (신월동)7920근산식품2020-05-21 11:43:17U2020-05-23 02:40:00.0알가공업185005.792215447796.176428축산물가공업알가공업<NA>000<NA>
1314000031400000041999000219991108<NA>3폐업2폐업20030602<NA><NA><NA>2643-41610.0<NA>서울특별시 양천구 목동 406-68번지 ,78호(지하1층)서울특별시 양천구 오목로 313-7 (목동,,78호(지하1층))<NA>우성축산2003-06-04 13:54:20I2018-08-31 23:59:59.0식육가공업188651.920734447058.617853축산물가공업식육가공업<NA>000<NA>
2314000031400000042001000120010825<NA>3폐업2폐업20070227<NA><NA><NA>2601-82360.0<NA>서울특별시 양천구 신월동 517-4번지 지하1층서울특별시 양천구 오목로 42 (신월동,지하1층)<NA>국제유통2007-02-27 14:43:42I2018-08-31 23:59:59.0식육가공업186000.07924446640.133624축산물가공업식육가공업<NA>000<NA>
3314000031400000042001000220011120<NA>3폐업2폐업20031231<NA><NA><NA>2690-33970.0<NA>서울특별시 양천구 신월동 927-1번지 지하1층서울특별시 양천구 지양로10길 12 (신월동,지하1층)<NA>거성종합식품2003-12-31 08:53:10I2018-08-31 23:59:59.0식육가공업185268.664167446801.631519축산물가공업식육가공업<NA>000<NA>
4314000031400000042002000120020716<NA>3폐업2폐업20160226<NA><NA><NA>2642-76240.0<NA>서울특별시 양천구 신정동 1052-3번지 상운프라자(104~106)<NA><NA>(주)쉬드티롤 컴퍼니2016-02-26 15:05:54I2018-08-31 23:59:59.0유가공업187079.375127446116.629313축산물가공업유가공업<NA>L00<NA>
5314000031400000042002000220021014<NA>3폐업2폐업20090311<NA><NA><NA><NA>0.0<NA>서울특별시 양천구 신월동 44-25번지 지하1층서울특별시 양천구 남부순환로 326 (신월동,지하1층)<NA>유신우(주)2009-03-11 10:52:42I2018-08-31 23:59:59.0식육가공업184616.195448399.055축산물가공업식육가공업<NA>L00<NA>
6314000031400000042003000120030313<NA>3폐업2폐업20030721<NA><NA><NA>2642-27410.0<NA>서울특별시 양천구 신정동 296-24번지 지하1층서울특별시 양천구 목동동로10길 24 (신정동,지하1층)<NA>두영종합식품2003-07-25 17:35:43I2018-08-31 23:59:59.0식육가공업188650.113585446358.120599축산물가공업식육가공업<NA>000<NA>
7314000031400000042003000320030618<NA>3폐업2폐업20040217<NA><NA><NA><NA>44.0<NA>서울특별시 양천구 신월동 217-21번지서울특별시 양천구 곰달래로2길 46 (신월동)<NA>신라푸드2004-02-17 13:04:06I2018-08-31 23:59:59.0식육가공업185458.61385447142.654719축산물가공업식육가공업<NA>000<NA>
831400003140000004200400012004-01-17<NA>1영업/정상0정상<NA><NA><NA><NA><NA>81.3<NA>서울특별시 양천구 신월동 207-44 1층서울특별시 양천구 남부순환로 452, 1층 (신월동)7916(주)종일푸드2023-06-20 14:25:57U2022-12-05 22:02:00.0식육가공업185199.742775447283.533139<NA><NA><NA><NA><NA>
9314000031400000042004000220040421<NA>3폐업2폐업20041222<NA><NA><NA>2651-07170.0<NA>서울특별시 양천구 목동 907번지 현대월드타워 지하 104-1,2호서울특별시 양천구 목동서로 77 (목동,현대월드타워 지하 104-1,2호)<NA>모코스2004-12-22 15:55:04I2018-08-31 23:59:59.0식육가공업189151.208016448200.067717축산물가공업식육가공업<NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
26314000031400000042013000220130823<NA>3폐업2폐업20140616<NA><NA><NA>2644-49330.0<NA>서울특별시 양천구 신월동 474-12번지 지층서울특별시 양천구 중앙로 333, 지층 (신월동)7933(주)임박사2014-06-16 16:11:56I2018-08-31 23:59:59.0식육가공업186648.898214447060.449766축산물가공업식육가공업<NA>L00<NA>
27314000031400000042013000320131226<NA>1영업/정상0정상<NA><NA><NA><NA>2697-44920.0<NA>서울특별시 양천구 신월동 534-25번지 2층서울특별시 양천구 신월로 191, 2층 (신월동)8030윈푸드시스템2017-02-06 16:02:01I2018-08-31 23:59:59.0식육가공업186129.6508446424.10743축산물가공업식육가공업<NA>000<NA>
28314000031400000042014000120140430<NA>3폐업2폐업20190125<NA><NA>201901252692-31410.0<NA>서울특별시 양천구 신월동 1003-3번지 지하1층서울특별시 양천구 신월로 112, 지하1층 (신월동)8047킴스키친(Kim's kitchen)2019-01-25 09:18:26U2019-01-27 02:40:00.0식육가공업185479.616484445976.962071축산물가공업식육가공업<NA>000<NA>
29314000031400000042014000220140729<NA>3폐업2폐업20200519<NA><NA>202005193141-72010.0<NA>서울특별시 양천구 신월동 445-9번지 3층일부서울특별시 양천구 월정로 34, 3층일부호 (신월동)7936(주)라틴앤글로벌2020-05-19 16:53:12U2020-05-21 02:40:00.0식육가공업186040.36446753.795축산물가공업식육가공업<NA>L00<NA>
30314000031400000042015000120150213<NA>3폐업2폐업20221020<NA><NA>202210202603-08830.0<NA>서울특별시 양천구 신월동 411-8 1층서울특별시 양천구 국회대로 36, 1층 (신월동)7929(주)계원푸드2022-10-20 17:49:41U2021-10-30 22:02:00.0식육가공업185693.044095447076.595451<NA><NA><NA><NA><NA>
31314000031400000042017000120170224<NA>3폐업2폐업20180207<NA><NA>201802072603-88380.0<NA>서울특별시 양천구 신정동 1052-3번지 상운프라자 104호서울특별시 양천구 중앙로 230, 104호 (신정동, 상운프라자)8091(주)동인산업2018-02-07 16:38:49I2018-08-31 23:59:59.0식육가공업187079.375127446116.629313축산물가공업식육가공업<NA>L00<NA>
3231400003140000004201900012019-07-16<NA>3폐업2폐업2023-12-26<NA><NA>2023-12-26<NA>0.0<NA>서울특별시 양천구 신정동 1052-3 104호서울특별시 양천구 중앙로 230, 104호 (신정동)8091(주)밸런스팩토리2023-12-27 13:48:12U2022-11-01 22:09:00.0유가공업187079.375127446116.629313<NA><NA><NA><NA><NA>
33314000031400000042022000120221104<NA>1영업/정상0정상<NA><NA><NA><NA>02-6956-89060.0<NA>서울특별시 양천구 신월동 136-5 지층서울특별시 양천구 남부순환로 395, 지층 (신월동)7920(주)비움랩스2022-11-04 09:59:30I2021-11-01 00:06:00.0유가공업185005.792215447796.176428<NA><NA><NA><NA><NA>
3431400003140000004202300012023-03-29<NA>1영업/정상0정상<NA><NA><NA><NA>070-8801-30290.0<NA>서울특별시 양천구 목동 807-5 가인빌딩 제비02호서울특별시 양천구 등촌로 2, 가인빌딩 제비02호 (목동)7966주식회사 렌위치코리아 공장2023-03-29 19:00:44I2022-12-04 00:01:00.0식육가공업187943.072004447573.990028<NA><NA><NA><NA><NA>
3531400003140000004202400012024-02-05<NA>1영업/정상0정상<NA><NA><NA><NA>02-6953-81280.0<NA>서울특별시 양천구 신정동 1052-3서울특별시 양천구 중앙로 230, 104호 (신정동)8091파인드2024-02-05 10:20:30I2023-12-02 00:07:00.0유가공업187079.375127446116.629313<NA><NA><NA><NA><NA>