Overview

Dataset statistics

Number of variables30
Number of observations44
Missing cells366
Missing cells (%)27.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.2 KiB
Average record size in memory260.0 B

Variable types

Categorical11
Numeric5
DateTime3
Unsupported7
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-18520/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
축산일련번호 is highly imbalanced (64.1%)Imbalance
총인원 is highly imbalanced (64.1%)Imbalance
인허가취소일자 has 44 (100.0%) missing valuesMissing
폐업일자 has 31 (70.5%) missing valuesMissing
휴업시작일자 has 44 (100.0%) missing valuesMissing
휴업종료일자 has 44 (100.0%) missing valuesMissing
재개업일자 has 44 (100.0%) missing valuesMissing
전화번호 has 8 (18.2%) missing valuesMissing
소재지우편번호 has 44 (100.0%) missing valuesMissing
도로명주소 has 3 (6.8%) missing valuesMissing
도로명우편번호 has 16 (36.4%) missing valuesMissing
업태구분명 has 44 (100.0%) missing valuesMissing
축산물가공업구분명 has 44 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
축산물가공업구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 24 (54.5%) zerosZeros

Reproduction

Analysis started2024-05-11 08:44:11.165692
Analysis finished2024-05-11 08:44:12.048420
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
3180000
44 

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 44
100.0%

Length

2024-05-11T08:44:12.283514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:12.623111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 44
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct44
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 size528.0 B
2024-05-11T08:44:13.184335image/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
Range210000
Interquartile range (IQR)112512

Descriptive statistics

Standard deviation61134.367
Coefficient of variation (CV)1.9224644 × 10-13
Kurtosis-1.1917958
Mean3.18 × 1017
Median Absolute Deviation (MAD)40000
Skewness0.19387293
Sum-4.454744 × 1018
Variance3.7374108 × 109
MonotonicityStrictly increasing
2024-05-11T08:44:13.612388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
318000000820030001 1
 
2.3%
318000000820120002 1
 
2.3%
318000000820140002 1
 
2.3%
318000000820140003 1
 
2.3%
318000000820150001 1
 
2.3%
318000000820150002 1
 
2.3%
318000000820170001 1
 
2.3%
318000000820170002 1
 
2.3%
318000000820180001 1
 
2.3%
318000000820200001 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
318000000820030001 1
2.3%
318000000820040001 1
2.3%
318000000820040002 1
2.3%
318000000820040003 1
2.3%
318000000820060001 1
2.3%
318000000820070001 1
2.3%
318000000820070002 1
2.3%
318000000820080001 1
2.3%
318000000820080002 1
2.3%
318000000820080003 1
2.3%
ValueCountFrequency (%)
318000000820240001 1
2.3%
318000000820230001 1
2.3%
318000000820220003 1
2.3%
318000000820220002 1
2.3%
318000000820220001 1
2.3%
318000000820210005 1
2.3%
318000000820210004 1
2.3%
318000000820210003 1
2.3%
318000000820210002 1
2.3%
318000000820210001 1
2.3%

인허가일자
Date

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2003-07-01 00:00:00
Maximum2024-03-20 00:00:00
2024-05-11T08:44:14.049780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:44:14.582848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
1
31 
3
11 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row4
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 31
70.5%
3 11
 
25.0%
4 2
 
4.5%

Length

2024-05-11T08:44:15.558911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:16.154352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
70.5%
3 11
 
25.0%
4 2
 
4.5%

영업상태명
Categorical

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
영업/정상
31 
폐업
11 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length4.6590909
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row취소/말소/만료/정지/중지
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 31
70.5%
폐업 11
 
25.0%
취소/말소/만료/정지/중지 2
 
4.5%

Length

2024-05-11T08:44:16.623450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:16.952773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 31
70.5%
폐업 11
 
25.0%
취소/말소/만료/정지/중지 2
 
4.5%

상세영업상태코드
Categorical

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
31 
2
11 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row2
3rd row4
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 31
70.5%
2 11
 
25.0%
4 2
 
4.5%

Length

2024-05-11T08:44:17.588416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:18.116767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 31
70.5%
2 11
 
25.0%
4 2
 
4.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
정상
31 
폐업
11 
말소
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 31
70.5%
폐업 11
 
25.0%
말소 2
 
4.5%

Length

2024-05-11T08:44:18.733115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:19.335341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 31
70.5%
폐업 11
 
25.0%
말소 2
 
4.5%

폐업일자
Date

MISSING 

Distinct12
Distinct (%)92.3%
Missing31
Missing (%)70.5%
Memory size484.0 B
Minimum2005-07-07 00:00:00
Maximum2023-06-16 00:00:00
2024-05-11T08:44:19.758616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:44:20.273988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

전화번호
Text

MISSING 

Distinct35
Distinct (%)97.2%
Missing8
Missing (%)18.2%
Memory size484.0 B
2024-05-11T08:44:20.922582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.4444444
Min length7

Characters and Unicode

Total characters340
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

Unique34 ?
Unique (%)94.4%

Sample

1st row2632-4581
2nd row831-8111
3rd row2676-2695
4th row2634-7788
5th row1544-2911
ValueCountFrequency (%)
26370633 2
 
5.6%
4346181 1
 
2.8%
02-2637-5772 1
 
2.8%
02)8348900 1
 
2.8%
0226366193 1
 
2.8%
6297-5771 1
 
2.8%
02-841-5276 1
 
2.8%
02-2677-3396 1
 
2.8%
02-2010-2956 1
 
2.8%
2677-0233 1
 
2.8%
Other values (25) 25
69.4%
2024-05-11T08:44:22.088690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 54
15.9%
3 42
12.4%
6 40
11.8%
0 37
10.9%
7 36
10.6%
- 36
10.6%
1 22
6.5%
8 20
 
5.9%
9 18
 
5.3%
5 17
 
5.0%
Other values (2) 18
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 303
89.1%
Dash Punctuation 36
 
10.6%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 54
17.8%
3 42
13.9%
6 40
13.2%
0 37
12.2%
7 36
11.9%
1 22
7.3%
8 20
 
6.6%
9 18
 
5.9%
5 17
 
5.6%
4 17
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 54
15.9%
3 42
12.4%
6 40
11.8%
0 37
10.9%
7 36
10.6%
- 36
10.6%
1 22
6.5%
8 20
 
5.9%
9 18
 
5.3%
5 17
 
5.0%
Other values (2) 18
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 54
15.9%
3 42
12.4%
6 40
11.8%
0 37
10.9%
7 36
10.6%
- 36
10.6%
1 22
6.5%
8 20
 
5.9%
9 18
 
5.3%
5 17
 
5.0%
Other values (2) 18
 
5.3%

소재지면적
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.018636
Minimum0
Maximum132
Zeros24
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T08:44:22.580151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q315.15
95-th percentile94.05
Maximum132
Range132
Interquartile range (IQR)15.15

Descriptive statistics

Standard deviation30.360766
Coefficient of variation (CV)1.8953403
Kurtosis5.9136392
Mean16.018636
Median Absolute Deviation (MAD)0
Skewness2.4786278
Sum704.82
Variance921.77614
MonotonicityNot monotonic
2024-05-11T08:44:23.016185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 24
54.5%
32.9 2
 
4.5%
3.0 2
 
4.5%
15.0 2
 
4.5%
14.7 1
 
2.3%
15.6 1
 
2.3%
2.0 1
 
2.3%
29.2 1
 
2.3%
31.08 1
 
2.3%
66.0 1
 
2.3%
Other values (8) 8
 
18.2%
ValueCountFrequency (%)
0.0 24
54.5%
2.0 1
 
2.3%
3.0 2
 
4.5%
10.0 1
 
2.3%
10.7 1
 
2.3%
13.12 1
 
2.3%
14.7 1
 
2.3%
15.0 2
 
4.5%
15.6 1
 
2.3%
18.9 1
 
2.3%
ValueCountFrequency (%)
132.0 1
2.3%
100.0 1
2.3%
99.0 1
2.3%
66.0 1
2.3%
60.72 1
2.3%
32.9 2
4.5%
31.08 1
2.3%
29.2 1
2.3%
18.9 1
2.3%
15.6 1
2.3%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

지번주소
Text

Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-05-11T08:44:23.411422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length25.818182
Min length18

Characters and Unicode

Total characters1136
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)84.1%

Sample

1st row서울특별시 영등포구 도림동 ***
2nd row서울특별시 영등포구 양평동*가 **-*번지 삼성아파트상가 ***호
3rd row서울특별시 영등포구 신길동 ***-**
4th row서울특별시 영등포구 양평동*가 **-**번지
5th row서울특별시 영등포구 영등포동*가 **-***
ValueCountFrequency (%)
서울특별시 44
20.6%
영등포구 44
20.6%
32
15.0%
호 17
 
7.9%
번지 13
 
6.1%
양평동*가 12
 
5.6%
당산동*가 10
 
4.7%
문래동*가 8
 
3.7%
신길동 5
 
2.3%
영등포동*가 4
 
1.9%
Other values (17) 25
11.7%
2024-05-11T08:44:24.276985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 237
20.9%
185
16.3%
영 49
 
4.3%
등 49
 
4.3%
포 49
 
4.3%
동 48
 
4.2%
서 46
 
4.0%
구 45
 
4.0%
특 44
 
3.9%
별 44
 
3.9%
Other values (52) 340
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 684
60.2%
Other Punctuation 237
 
20.9%
Space Separator 185
 
16.3%
Dash Punctuation 30
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 49
 
7.2%
등 49
 
7.2%
포 49
 
7.2%
동 48
 
7.0%
서 46
 
6.7%
구 45
 
6.6%
특 44
 
6.4%
별 44
 
6.4%
시 44
 
6.4%
울 44
 
6.4%
Other values (49) 222
32.5%
Other Punctuation
ValueCountFrequency (%)
* 237
100.0%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 684
60.2%
Common 452
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 49
 
7.2%
등 49
 
7.2%
포 49
 
7.2%
동 48
 
7.0%
서 46
 
6.7%
구 45
 
6.6%
특 44
 
6.4%
별 44
 
6.4%
시 44
 
6.4%
울 44
 
6.4%
Other values (49) 222
32.5%
Common
ValueCountFrequency (%)
* 237
52.4%
185
40.9%
- 30
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 684
60.2%
ASCII 452
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 237
52.4%
185
40.9%
- 30
 
6.6%
Hangul
ValueCountFrequency (%)
영 49
 
7.2%
등 49
 
7.2%
포 49
 
7.2%
동 48
 
7.0%
서 46
 
6.7%
구 45
 
6.6%
특 44
 
6.4%
별 44
 
6.4%
시 44
 
6.4%
울 44
 
6.4%
Other values (49) 222
32.5%

도로명주소
Text

MISSING 

Distinct40
Distinct (%)97.6%
Missing3
Missing (%)6.8%
Memory size484.0 B
2024-05-11T08:44:24.899470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length38.243902
Min length23

Characters and Unicode

Total characters1568
Distinct characters107
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

Unique39 ?
Unique (%)95.1%

Sample

1st row서울특별시 영등포구 도영로 ** (도림동)
2nd row서울특별시 영등포구 신길로 *** (신길동,기계회관 *층)
3rd row서울특별시 영등포구 문래북로 **-* (양평동*가)
4th row서울특별시 영등포구 버드나루로 ** (영등포동*가)
5th row서울특별시 영등포구 선유로 ***, ***호 (양평동*가, 양평동 *차 현대아파트 상가동)
ValueCountFrequency (%)
42
14.6%
서울특별시 41
14.3%
영등포구 41
14.3%
호 22
 
7.7%
양평동*가 11
 
3.8%
층 11
 
3.8%
문래동*가 7
 
2.4%
당산동*가 6
 
2.1%
양평로**길 4
 
1.4%
당산로 4
 
1.4%
Other values (63) 98
34.1%
2024-05-11T08:44:26.034605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 255
 
16.3%
246
 
15.7%
영 56
 
3.6%
동 56
 
3.6%
포 54
 
3.4%
등 54
 
3.4%
, 44
 
2.8%
구 43
 
2.7%
가 43
 
2.7%
서 43
 
2.7%
Other values (97) 674
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 928
59.2%
Other Punctuation 300
 
19.1%
Space Separator 246
 
15.7%
Close Punctuation 42
 
2.7%
Open Punctuation 42
 
2.7%
Dash Punctuation 7
 
0.4%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 56
 
6.0%
동 56
 
6.0%
포 54
 
5.8%
등 54
 
5.8%
구 43
 
4.6%
가 43
 
4.6%
서 43
 
4.6%
시 42
 
4.5%
울 41
 
4.4%
로 41
 
4.4%
Other values (87) 455
49.0%
Other Punctuation
ValueCountFrequency (%)
* 255
85.0%
, 44
 
14.7%
/ 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
246
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 928
59.2%
Common 637
40.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 56
 
6.0%
동 56
 
6.0%
포 54
 
5.8%
등 54
 
5.8%
구 43
 
4.6%
가 43
 
4.6%
서 43
 
4.6%
시 42
 
4.5%
울 41
 
4.4%
로 41
 
4.4%
Other values (87) 455
49.0%
Common
ValueCountFrequency (%)
* 255
40.0%
246
38.6%
, 44
 
6.9%
) 42
 
6.6%
( 42
 
6.6%
- 7
 
1.1%
/ 1
 
0.2%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 928
59.2%
ASCII 640
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 255
39.8%
246
38.4%
, 44
 
6.9%
) 42
 
6.6%
( 42
 
6.6%
- 7
 
1.1%
A 1
 
0.2%
B 1
 
0.2%
/ 1
 
0.2%
D 1
 
0.2%
Hangul
ValueCountFrequency (%)
영 56
 
6.0%
동 56
 
6.0%
포 54
 
5.8%
등 54
 
5.8%
구 43
 
4.6%
가 43
 
4.6%
서 43
 
4.6%
시 42
 
4.5%
울 41
 
4.4%
로 41
 
4.4%
Other values (87) 455
49.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)75.0%
Missing16
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean7269.4643
Minimum7203
Maximum7387
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T08:44:26.422522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7203
5-th percentile7204
Q17236.5
median7264
Q37289
95-th percentile7364.1
Maximum7387
Range184
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation49.957376
Coefficient of variation (CV)0.0068722225
Kurtosis0.10075687
Mean7269.4643
Median Absolute Deviation (MAD)25
Skewness0.58641367
Sum203545
Variance2495.7394
MonotonicityNot monotonic
2024-05-11T08:44:26.802125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
7289 3
 
6.8%
7264 2
 
4.5%
7287 2
 
4.5%
7204 2
 
4.5%
7260 2
 
4.5%
7211 2
 
4.5%
7285 1
 
2.3%
7355 1
 
2.3%
7203 1
 
2.3%
7252 1
 
2.3%
Other values (11) 11
25.0%
(Missing) 16
36.4%
ValueCountFrequency (%)
7203 1
2.3%
7204 2
4.5%
7208 1
2.3%
7209 1
2.3%
7211 2
4.5%
7245 1
2.3%
7252 1
2.3%
7256 1
2.3%
7259 1
2.3%
7260 2
4.5%
ValueCountFrequency (%)
7387 1
 
2.3%
7369 1
 
2.3%
7355 1
 
2.3%
7325 1
 
2.3%
7319 1
 
2.3%
7289 3
6.8%
7287 2
4.5%
7285 1
 
2.3%
7278 1
 
2.3%
7276 1
 
2.3%

사업장명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-05-11T08:44:27.328566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.9545455
Min length3

Characters and Unicode

Total characters306
Distinct characters106
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

Unique44 ?
Unique (%)100.0%

Sample

1st row한우정육점
2nd row개별화물
3rd row(주)삼신물류
4th row개별용달 6지부
5th row백송상사
ValueCountFrequency (%)
한우정육점 1
 
2.1%
풍전할인마트 1
 
2.1%
잇츠온 1
 
2.1%
주)사러가 1
 
2.1%
한마루 1
 
2.1%
주)더블유디이 1
 
2.1%
대림상사 1
 
2.1%
주)우리종합물류 1
 
2.1%
이진광 1
 
2.1%
유성민 1
 
2.1%
Other values (37) 37
78.7%
2024-05-11T08:44:28.219830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 29
 
9.5%
) 25
 
8.2%
( 25
 
8.2%
스 13
 
4.2%
물 13
 
4.2%
류 12
 
3.9%
지 9
 
2.9%
사 6
 
2.0%
운 6
 
2.0%
로 6
 
2.0%
Other values (96) 162
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
82.4%
Close Punctuation 25
 
8.2%
Open Punctuation 25
 
8.2%
Space Separator 3
 
1.0%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
11.5%
스 13
 
5.2%
물 13
 
5.2%
류 12
 
4.8%
지 9
 
3.6%
사 6
 
2.4%
운 6
 
2.4%
로 6
 
2.4%
성 6
 
2.4%
수 5
 
2.0%
Other values (92) 147
58.3%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
82.4%
Common 54
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
11.5%
스 13
 
5.2%
물 13
 
5.2%
류 12
 
4.8%
지 9
 
3.6%
사 6
 
2.4%
운 6
 
2.4%
로 6
 
2.4%
성 6
 
2.4%
수 5
 
2.0%
Other values (92) 147
58.3%
Common
ValueCountFrequency (%)
) 25
46.3%
( 25
46.3%
3
 
5.6%
6 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
82.4%
ASCII 54
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 29
 
11.5%
스 13
 
5.2%
물 13
 
5.2%
류 12
 
4.8%
지 9
 
3.6%
사 6
 
2.4%
운 6
 
2.4%
로 6
 
2.4%
성 6
 
2.4%
수 5
 
2.0%
Other values (92) 147
58.3%
ASCII
ValueCountFrequency (%)
) 25
46.3%
( 25
46.3%
3
 
5.6%
6 1
 
1.9%

최종수정일자
Date

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2005-07-07 18:16:23
Maximum2024-03-20 17:36:16
2024-05-11T08:44:28.613221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:44:29.054453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
U
29 
I
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 29
65.9%
I 15
34.1%

Length

2024-05-11T08:44:29.541989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:29.871046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 29
65.9%
i 15
34.1%

데이터갱신일자
Categorical

Distinct16
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
2018-08-31 23:59:59.0
12 
2022-12-07 23:07:00.0
12 
2022-12-07 23:03:00.0
6 
2021-07-10 02:40:00.0
2 
2023-12-02 22:01:00.0
 
1
Other values (11)
11 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique12 ?
Unique (%)27.3%

Sample

1st row2022-12-07 23:03:00.0
2nd row2018-08-31 23:59:59.0
3rd row2021-07-10 02:40:00.0
4th row2018-08-31 23:59:59.0
5th row2022-12-07 23:03:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 12
27.3%
2022-12-07 23:07:00.0 12
27.3%
2022-12-07 23:03:00.0 6
13.6%
2021-07-10 02:40:00.0 2
 
4.5%
2023-12-02 22:01:00.0 1
 
2.3%
2023-12-01 22:05:00.0 1
 
2.3%
2021-01-23 02:40:00.0 1
 
2.3%
2021-05-12 02:40:00.0 1
 
2.3%
2019-02-01 02:40:00.0 1
 
2.3%
2020-12-13 00:23:06.0 1
 
2.3%
Other values (6) 6
13.6%

Length

2024-05-11T08:44:30.239692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-07 18
20.5%
2018-08-31 12
13.6%
23:07:00.0 12
13.6%
23:59:59.0 12
13.6%
23:03:00.0 6
 
6.8%
02:40:00.0 6
 
6.8%
2021-07-10 2
 
2.3%
2023-12-02 2
 
2.3%
22:01:00.0 2
 
2.3%
2023-12-01 2
 
2.3%
Other values (14) 14
15.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

좌표정보(X)
Real number (ℝ)

Distinct36
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190986.47
Minimum189549.85
Maximum193616.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T08:44:30.593563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile189734.38
Q1190394.57
median190661.85
Q3191479.04
95-th percentile193164.18
Maximum193616.8
Range4066.9489
Interquartile range (IQR)1084.4724

Descriptive statistics

Standard deviation1011.6412
Coefficient of variation (CV)0.0052969262
Kurtosis0.76171331
Mean190986.47
Median Absolute Deviation (MAD)339.14905
Skewness1.1563475
Sum8403404.6
Variance1023418
MonotonicityNot monotonic
2024-05-11T08:44:31.127721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
190079.219797466 2
 
4.5%
189549.847307536 2
 
4.5%
190821.206721583 2
 
4.5%
190517.88054611 2
 
4.5%
190783.606940757 2
 
4.5%
190394.571819262 2
 
4.5%
190555.768991595 2
 
4.5%
190346.552309665 2
 
4.5%
190942.214933014 1
 
2.3%
190555.798778664 1
 
2.3%
Other values (26) 26
59.1%
ValueCountFrequency (%)
189549.847307536 2
4.5%
189683.355756096 1
2.3%
190023.48828661 1
2.3%
190079.219797466 2
4.5%
190132.04325297 1
2.3%
190298.841931736 1
2.3%
190346.552309665 2
4.5%
190394.571819262 2
4.5%
190417.056808292 1
2.3%
190436.133898757 1
2.3%
ValueCountFrequency (%)
193616.796239252 1
2.3%
193389.462376889 1
2.3%
193165.490137352 1
2.3%
193156.760224416 1
2.3%
192786.528526157 1
2.3%
192041.032768335 1
2.3%
191994.312102226 1
2.3%
191939.897780759 1
2.3%
191886.239501417 1
2.3%
191579.852908309 1
2.3%

좌표정보(Y)
Real number (ℝ)

Distinct36
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean446575.15
Minimum442756.53
Maximum448906.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2024-05-11T08:44:31.771131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442756.53
5-th percentile445235.32
Q1445776.92
median446709.14
Q3447127.91
95-th percentile448586.92
Maximum448906.42
Range6149.889
Interquartile range (IQR)1350.9863

Descriptive statistics

Standard deviation1143.4106
Coefficient of variation (CV)0.0025603992
Kurtosis1.795374
Mean446575.15
Median Absolute Deviation (MAD)803.07176
Skewness-0.50090867
Sum19649306
Variance1307387.9
MonotonicityNot monotonic
2024-05-11T08:44:32.168975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
445778.895201988 2
 
4.5%
446913.092679857 2
 
4.5%
447023.185320259 2
 
4.5%
447739.172359225 2
 
4.5%
447179.012459191 2
 
4.5%
448656.726986041 2
 
4.5%
446698.814322782 2
 
4.5%
445601.663339218 2
 
4.5%
445332.134603849 1
 
2.3%
448010.484614217 1
 
2.3%
Other values (26) 26
59.1%
ValueCountFrequency (%)
442756.531513655 1
2.3%
444884.804266378 1
2.3%
445223.036233003 1
2.3%
445304.905654932 1
2.3%
445332.134603849 1
2.3%
445469.918626807 1
2.3%
445533.73645091 1
2.3%
445579.286473669 1
2.3%
445601.663339218 2
4.5%
445771.005816995 1
2.3%
ValueCountFrequency (%)
448906.42052912 1
2.3%
448656.726986041 2
4.5%
448191.347586673 1
2.3%
448010.484614217 1
2.3%
447739.896956998 1
2.3%
447739.172359225 2
4.5%
447179.012459191 2
4.5%
447154.728694696 1
2.3%
447118.969319485 1
2.3%
447035.487279032 1
2.3%

축산업무구분명
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
25 
축산물운반업
19 

Length

Max length6
Median length4
Mean length4.8636364
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
56.8%
축산물운반업 19
43.2%

Length

2024-05-11T08:44:32.740352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:33.263287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
56.8%
축산물운반업 19
43.2%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing44
Missing (%)100.0%
Memory size528.0 B

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
41 
0
 
3

Length

Max length4
Median length4
Mean length3.7954545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
93.2%
0 3
 
6.8%

Length

2024-05-11T08:44:33.756908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:34.085372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
93.2%
0 3
 
6.8%

권리주체일련번호
Categorical

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
25 
L00
12 
000
7 

Length

Max length4
Median length4
Mean length3.5681818
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
56.8%
L00 12
27.3%
000 7
 
15.9%

Length

2024-05-11T08:44:34.624800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:35.209780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
56.8%
l00 12
27.3%
000 7
 
15.9%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
41 
0
 
3

Length

Max length4
Median length4
Mean length3.7954545
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 41
93.2%
0 3
 
6.8%

Length

2024-05-11T08:44:35.583086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:44:35.964685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 41
93.2%
0 3
 
6.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
031800003180000008200300012003-07-01<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 영등포구 도림동 ***서울특별시 영등포구 도영로 ** (도림동)<NA>한우정육점2023-08-11 16:43:55U2022-12-07 23:03:00.0<NA>190942.214933445332.134604<NA><NA><NA><NA><NA>
1318000031800000082004000120040624<NA>3폐업2폐업20050805<NA><NA><NA>2632-45810.0<NA>서울특별시 영등포구 양평동*가 **-*번지 삼성아파트상가 ***호<NA><NA>개별화물2005-08-05 11:19:49I2018-08-31 23:59:59.0<NA>189549.847308446913.09268축산물운반업<NA><NA>000<NA>
2318000031800000082004000220040713<NA>4취소/말소/만료/정지/중지4말소20210707<NA><NA><NA>831-81110.0<NA>서울특별시 영등포구 신길동 ***-**서울특별시 영등포구 신길로 *** (신길동,기계회관 *층)<NA>(주)삼신물류2021-07-08 11:36:34U2021-07-10 02:40:00.0<NA>191994.312102445304.905655축산물운반업<NA>0L000
3318000031800000082004000320040902<NA>3폐업2폐업20050707<NA><NA><NA>2676-26950.0<NA>서울특별시 영등포구 양평동*가 **-**번지서울특별시 영등포구 문래북로 **-* (양평동*가)<NA>개별용달 6지부2005-07-07 18:16:23I2018-08-31 23:59:59.0<NA>190132.043253446569.870982축산물운반업<NA><NA>000<NA>
431800003180000008200600012006-01-12<NA>1영업/정상0정상<NA><NA><NA><NA>2634-77880.0<NA>서울특별시 영등포구 영등포동*가 **-***서울특별시 영등포구 버드나루로 ** (영등포동*가)<NA>백송상사2023-08-11 16:45:31U2022-12-07 23:03:00.0<NA>191939.897781447035.487279<NA><NA><NA><NA><NA>
5318000031800000082007000120070719<NA>1영업/정상0정상<NA><NA><NA><NA>1544-29110.0<NA>서울특별시 영등포구 당산동*가 ***번지 우미빌딩 ***호<NA><NA>(주)티오물류2008-12-15 13:26:06I2018-08-31 23:59:59.0<NA>190821.206722447023.18532축산물운반업<NA><NA>L00<NA>
6318000031800000082007000220071008<NA>4취소/말소/만료/정지/중지4말소20210707<NA><NA><NA>6326-99700.0<NA>서울특별시 영등포구 문래동*가 **-*<NA><NA>성운로지스2021-07-08 11:37:56U2021-07-10 02:40:00.0<NA>190449.201893446022.033746축산물운반업<NA>0L000
731800003180000008200800012008-02-11<NA>1영업/정상0정상<NA><NA><NA><NA>2637063332.9<NA>서울특별시 영등포구 양평동*가 *** ***호서울특별시 영등포구 선유로 ***, ***호 (양평동*가, 양평동 *차 현대아파트 상가동)7211(주)명민로지스2024-03-19 14:48:55U2023-12-02 22:01:00.0<NA>190517.880546447739.172359<NA><NA><NA><NA><NA>
8318000031800000082008000220080912<NA>1영업/정상0정상<NA><NA><NA><NA>2267255330.0<NA>서울특별시 영등포구 당산동*가 ***-*번지 서림빌딩 ***호서울특별시 영등포구 당산로 ***, ***호 (당산동*가, 서림빌딩)7256(주)삼성운수2013-08-23 09:54:18I2018-08-31 23:59:59.0<NA>190783.606941447179.012459축산물운반업<NA><NA>L00<NA>
9318000031800000082008000320080912<NA>3폐업2폐업20100104<NA><NA><NA>2672-79000.0<NA>서울특별시 영등포구 당산동*가 ***-*번지 서림빌딩 ***호서울특별시 영등포구 당산로 ***, ***호 (당산동*가,서림빌딩)<NA>(주)에스에스티 물류2010-01-04 20:14:31I2018-08-31 23:59:59.0<NA>190783.606941447179.012459축산물운반업<NA><NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
34318000031800000082021000120210202<NA>1영업/정상0정상<NA><NA><NA><NA>02-2631-2350132.0<NA>서울특별시 영등포구 양평동*가 **서울특별시 영등포구 양평로**길 *, 상가 ***동 *-*호 (양평동*가, 양평동한신아파트)7204(주)용인특수운송2022-01-05 14:16:27U2022-01-07 02:40:00.0<NA>190394.571819448656.726986축산물운반업<NA>0L000
35318000031800000082021000220210720<NA>1영업/정상0정상<NA><NA><NA><NA>02-2637-577218.9<NA>서울특별시 영등포구 당산동*가 **-* 바역 **호서울특별시 영등포구 영등포로 ***, 영등포유통상가 *층 바열 **호 (당산동*가)7264온누리물류2022-06-03 13:13:19U2021-12-06 00:08:00.0<NA>190555.768992446698.814323<NA><NA><NA><NA><NA>
3631800003180000008202100032021-08-06<NA>1영업/정상0정상<NA><NA><NA><NA>434618110.0<NA>서울특별시 영등포구 양평동*가 ** ***동 *-*호서울특별시 영등포구 양평로**길 *, ***동 *-*호 (양평동*가, 양평동한신아파트)7204(주)경세산업2024-02-22 20:23:26U2023-12-01 22:04:00.0<NA>190394.571819448656.726986<NA><NA><NA><NA><NA>
3731800003180000008202100042021-08-18<NA>1영업/정상0정상<NA><NA><NA><NA>02-2637-223899.0<NA>서울특별시 영등포구 당산동*가 *** ***호서울특별시 영등포구 당산로 ***, 우미빌딩 ***호 (당산동*가)7259(주)씨엔케이물류2023-08-14 13:45:44U2022-12-07 23:07:00.0<NA>190821.206722447023.18532<NA><NA><NA><NA><NA>
3831800003180000008202100052021-09-14<NA>1영업/정상0정상<NA><NA><NA><NA>02-2679-0741100.0<NA>서울특별시 영등포구 당산동*가 ***-* ***호서울특별시 영등포구 양산로 ***, 인곡빌딩 *층 ***호 (당산동*가)7260(주)경안인터내셔날2023-08-14 13:50:31U2022-12-07 23:07:00.0<NA>190656.664971446933.516159<NA><NA><NA><NA><NA>
3931800003180000008202200012022-07-04<NA>1영업/정상0정상<NA><NA><NA><NA>02-833-378060.72<NA>서울특별시 영등포구 신길동 ****-* **호서울특별시 영등포구 여의대방로**길 *, 천록빌딩 *층 **호 (신길동)7319에스앤에스로지스주식회사2023-08-14 14:02:26U2022-12-07 23:07:00.0<NA>193389.462377445790.101524<NA><NA><NA><NA><NA>
4031800003180000008202200022022-07-15<NA>3폐업2폐업2023-06-16<NA><NA><NA>02-857-95093.0<NA>서울특별시 영등포구 문래동*가 ** 리버뷰 신안인스빌 *층 상가동서울특별시 영등포구 경인로**길 **, 상가동 *층 (문래동*가, 리버뷰 신안인스빌)7287아워박스주식회사2023-06-19 10:44:49U2022-12-05 22:01:00.0<NA>190079.219797445778.895202<NA><NA><NA><NA><NA>
4131800003180000008202200032017-06-26<NA>1영업/정상0정상<NA><NA><NA><NA>2643771415.0<NA>서울특별시 영등포구 양평동*가 **-* 상가동 ***호서울특별시 영등포구 영등포로*길 *, 양평동삼성아파트 상가동 ***호 (양평동*가)7276(주)대륜물류2023-08-14 13:54:08U2022-12-07 23:07:00.0<NA>189549.847308446913.09268<NA><NA><NA><NA><NA>
4231800003180000008202300012023-09-12<NA>1영업/정상0정상<NA><NA><NA><NA>02-2010-29560.0<NA>서울특별시 영등포구 여의도동 **-*서울특별시 영등포구 의사당대로 **, 오투타워 **층 (여의도동)7325피앤에스로지스2023-09-12 10:31:34I2022-12-08 23:04:00.0<NA>193165.490137446797.341447<NA><NA><NA><NA><NA>
4331800003180000008202400012024-03-20<NA>1영업/정상0정상<NA><NA><NA><NA>02-858-95063.0<NA>서울특별시 영등포구 문래동*가 ** 리버뷰 신안인스빌서울특별시 영등포구 경인로**길 **, ***동 상가*층 ***-**호 (문래동*가, 리버뷰 신안인스빌)7287아워박스 주식회사2024-03-20 17:36:16I2023-12-02 22:02:00.0<NA>190079.219797445778.895202<NA><NA><NA><NA><NA>