Overview

Dataset statistics

Number of variables30
Number of observations57
Missing cells479
Missing cells (%)28.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory260.3 B

Variable types

Categorical10
Numeric6
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18517/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
축산일련번호 is highly imbalanced (51.5%)Imbalance
총인원 is highly imbalanced (51.5%)Imbalance
인허가취소일자 has 57 (100.0%) missing valuesMissing
폐업일자 has 44 (77.2%) missing valuesMissing
휴업시작일자 has 57 (100.0%) missing valuesMissing
휴업종료일자 has 57 (100.0%) missing valuesMissing
재개업일자 has 57 (100.0%) missing valuesMissing
전화번호 has 19 (33.3%) missing valuesMissing
소재지우편번호 has 57 (100.0%) missing valuesMissing
도로명우편번호 has 9 (15.8%) missing valuesMissing
업태구분명 has 57 (100.0%) missing valuesMissing
좌표정보(X) has 4 (7.0%) missing valuesMissing
좌표정보(Y) has 4 (7.0%) missing valuesMissing
축산물가공업구분명 has 57 (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 13 (22.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:37:53.268084
Analysis finished2024-05-11 05:37:53.900733
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
3150000
57 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 57
100.0%

Length

2024-05-11T14:37:54.350369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:54.509683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 57
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.15 × 1017
Minimum3.15 × 1017
Maximum3.15 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:37:54.713287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.15 × 1017
5-th percentile3.15 × 1017
Q13.15 × 1017
median3.15 × 1017
Q33.15 × 1017
95-th percentile3.15 × 1017
Maximum3.15 × 1017
Range200000
Interquartile range (IQR)89984

Descriptive statistics

Standard deviation57123.496
Coefficient of variation (CV)1.8134443 × 10-13
Kurtosis-0.91657746
Mean3.15 × 1017
Median Absolute Deviation (MAD)49984
Skewness-0.41151258
Sum-4.9174403 × 1017
Variance3.2630938 × 109
MonotonicityStrictly increasing
2024-05-11T14:37:55.037895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
315000000820040001 1
 
1.8%
315000000820210003 1
 
1.8%
315000000820170003 1
 
1.8%
315000000820170004 1
 
1.8%
315000000820180001 1
 
1.8%
315000000820190001 1
 
1.8%
315000000820190002 1
 
1.8%
315000000820190003 1
 
1.8%
315000000820190004 1
 
1.8%
315000000820190005 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
315000000820040001 1
1.8%
315000000820060001 1
1.8%
315000000820060002 1
1.8%
315000000820060003 1
1.8%
315000000820060004 1
1.8%
315000000820070001 1
1.8%
315000000820070002 1
1.8%
315000000820070003 1
1.8%
315000000820070004 1
1.8%
315000000820090001 1
1.8%
ValueCountFrequency (%)
315000000820240001 1
1.8%
315000000820230008 1
1.8%
315000000820230007 1
1.8%
315000000820230006 1
1.8%
315000000820230005 1
1.8%
315000000820230004 1
1.8%
315000000820230003 1
1.8%
315000000820230002 1
1.8%
315000000820230001 1
1.8%
315000000820220003 1
1.8%

인허가일자
Date

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2004-07-03 00:00:00
Maximum2024-03-25 00:00:00
2024-05-11T14:37:55.274963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:37:55.498043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
1
44 
3
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 44
77.2%
3 13
 
22.8%

Length

2024-05-11T14:37:55.770781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:55.989749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 44
77.2%
3 13
 
22.8%

영업상태명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
영업/정상
44 
폐업
13 

Length

Max length5
Median length5
Mean length4.3157895
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 44
77.2%
폐업 13
 
22.8%

Length

2024-05-11T14:37:56.183668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:56.383745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 44
77.2%
폐업 13
 
22.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
0
44 
2
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 44
77.2%
2 13
 
22.8%

Length

2024-05-11T14:37:56.574233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:56.734248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
77.2%
2 13
 
22.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
정상
44 
폐업
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 44
77.2%
폐업 13
 
22.8%

Length

2024-05-11T14:37:56.926176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:37:57.101981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 44
77.2%
폐업 13
 
22.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)92.3%
Missing44
Missing (%)77.2%
Infinite0
Infinite (%)0.0%
Mean20154389
Minimum20051111
Maximum20220405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:37:57.308054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20051111
5-th percentile20092579
Q120120508
median20160406
Q320190402
95-th percentile20208824
Maximum20220405
Range169294
Interquartile range (IQR)69894

Descriptive statistics

Standard deviation45865.281
Coefficient of variation (CV)0.0022756969
Kurtosis0.6913381
Mean20154389
Median Absolute Deviation (MAD)39898
Skewness-0.70511344
Sum2.6200706 × 108
Variance2.103624 × 109
MonotonicityNot monotonic
2024-05-11T14:37:57.528909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20120224 2
 
3.5%
20051111 1
 
1.8%
20170718 1
 
1.8%
20220405 1
 
1.8%
20120508 1
 
1.8%
20201104 1
 
1.8%
20190402 1
 
1.8%
20160406 1
 
1.8%
20200521 1
 
1.8%
20130605 1
 
1.8%
Other values (2) 2
 
3.5%
(Missing) 44
77.2%
ValueCountFrequency (%)
20051111 1
1.8%
20120224 2
3.5%
20120508 1
1.8%
20130605 1
1.8%
20150720 1
1.8%
20160406 1
1.8%
20170113 1
1.8%
20170718 1
1.8%
20190402 1
1.8%
20200521 1
1.8%
ValueCountFrequency (%)
20220405 1
1.8%
20201104 1
1.8%
20200521 1
1.8%
20190402 1
1.8%
20170718 1
1.8%
20170113 1
1.8%
20160406 1
1.8%
20150720 1
1.8%
20130605 1
1.8%
20120508 1
1.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

전화번호
Text

MISSING 

Distinct35
Distinct (%)92.1%
Missing19
Missing (%)33.3%
Memory size588.0 B
2024-05-11T14:37:57.984673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length9.3421053
Min length7

Characters and Unicode

Total characters355
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

Unique32 ?
Unique (%)84.2%

Sample

1st row2607-6503,2607-6501
2nd row2666-6427
3rd row3664-5060
4th row766-4078
5th row0226577737
ValueCountFrequency (%)
02-3665-0374 2
 
5.3%
7743112 2
 
5.3%
2658-1451 2
 
5.3%
3331490 1
 
2.6%
62040000 1
 
2.6%
26610935 1
 
2.6%
02-2661-9700 1
 
2.6%
21387801 1
 
2.6%
3331491 1
 
2.6%
2607-6503,2607-6501 1
 
2.6%
Other values (25) 25
65.8%
2024-05-11T14:37:58.522605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 57
16.1%
0 49
13.8%
2 42
11.8%
3 36
10.1%
1 35
9.9%
7 30
8.5%
4 27
7.6%
- 26
7.3%
8 21
 
5.9%
5 20
 
5.6%
Other values (2) 12
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 328
92.4%
Dash Punctuation 26
 
7.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 57
17.4%
0 49
14.9%
2 42
12.8%
3 36
11.0%
1 35
10.7%
7 30
9.1%
4 27
8.2%
8 21
 
6.4%
5 20
 
6.1%
9 11
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 57
16.1%
0 49
13.8%
2 42
11.8%
3 36
10.1%
1 35
9.9%
7 30
8.5%
4 27
7.6%
- 26
7.3%
8 21
 
5.9%
5 20
 
5.6%
Other values (2) 12
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 57
16.1%
0 49
13.8%
2 42
11.8%
3 36
10.1%
1 35
9.9%
7 30
8.5%
4 27
7.6%
- 26
7.3%
8 21
 
5.9%
5 20
 
5.6%
Other values (2) 12
 
3.4%

소재지면적
Real number (ℝ)

ZEROS 

Distinct43
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.367018
Minimum0
Maximum133
Zeros13
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:37:58.784662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median26.22
Q350
95-th percentile111.838
Maximum133
Range133
Interquartile range (IQR)46

Descriptive statistics

Standard deviation36.314231
Coefficient of variation (CV)1.0566594
Kurtosis0.4361694
Mean34.367018
Median Absolute Deviation (MAD)22.92
Skewness1.1173281
Sum1958.92
Variance1318.7234
MonotonicityNot monotonic
2024-05-11T14:37:59.017588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 13
 
22.8%
9.9 2
 
3.5%
30.0 2
 
3.5%
23.1 1
 
1.8%
26.22 1
 
1.8%
77.0 1
 
1.8%
39.0 1
 
1.8%
70.0 1
 
1.8%
80.0 1
 
1.8%
40.0 1
 
1.8%
Other values (33) 33
57.9%
ValueCountFrequency (%)
0.0 13
22.8%
3.3 1
 
1.8%
4.0 1
 
1.8%
5.0 1
 
1.8%
6.6 1
 
1.8%
7.92 1
 
1.8%
8.0 1
 
1.8%
9.9 2
 
3.5%
10.0 1
 
1.8%
12.32 1
 
1.8%
ValueCountFrequency (%)
133.0 1
1.8%
124.6 1
1.8%
119.31 1
1.8%
109.97 1
1.8%
95.94 1
1.8%
90.72 1
1.8%
86.16 1
1.8%
80.0 1
1.8%
77.04 1
1.8%
77.0 1
1.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

지번주소
Text

Distinct47
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-05-11T14:37:59.332428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length26.157895
Min length18

Characters and Unicode

Total characters1491
Distinct characters91
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)71.9%

Sample

1st row서울특별시 강서구 방화동 ***-**번지 한양빌딩 ***
2nd row서울특별시 강서구 가양동 ***-*번지 *층
3rd row서울특별시 강서구 공항동 ****-* *층
4th row서울특별시 강서구 염창동 ***-**
5th row서울특별시 강서구 방화동 ***-*번지 방화샤르망오피스텔 *동 ***호
ValueCountFrequency (%)
서울특별시 57
19.8%
강서구 57
19.8%
35
12.2%
호 23
8.0%
번지 22
 
7.6%
마곡동 21
 
7.3%
화곡동 10
 
3.5%
층 7
 
2.4%
공항동 7
 
2.4%
등촌동 7
 
2.4%
Other values (30) 42
14.6%
2024-05-11T14:37:59.949185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 351
23.5%
255
17.1%
서 114
 
7.6%
동 62
 
4.2%
특 57
 
3.8%
별 57
 
3.8%
시 57
 
3.8%
강 57
 
3.8%
구 57
 
3.8%
울 57
 
3.8%
Other values (81) 367
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 813
54.5%
Other Punctuation 351
23.5%
Space Separator 255
 
17.1%
Dash Punctuation 54
 
3.6%
Uppercase Letter 9
 
0.6%
Decimal Number 7
 
0.5%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 114
14.0%
동 62
 
7.6%
특 57
 
7.0%
별 57
 
7.0%
시 57
 
7.0%
강 57
 
7.0%
구 57
 
7.0%
울 57
 
7.0%
곡 31
 
3.8%
호 26
 
3.2%
Other values (66) 238
29.3%
Decimal Number
ValueCountFrequency (%)
7 2
28.6%
0 1
14.3%
1 1
14.3%
3 1
14.3%
8 1
14.3%
2 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 4
44.4%
M 2
22.2%
C 1
 
11.1%
B 1
 
11.1%
R 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 351
100.0%
Space Separator
ValueCountFrequency (%)
255
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 813
54.5%
Common 667
44.7%
Latin 11
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 114
14.0%
동 62
 
7.6%
특 57
 
7.0%
별 57
 
7.0%
시 57
 
7.0%
강 57
 
7.0%
구 57
 
7.0%
울 57
 
7.0%
곡 31
 
3.8%
호 26
 
3.2%
Other values (66) 238
29.3%
Common
ValueCountFrequency (%)
* 351
52.6%
255
38.2%
- 54
 
8.1%
7 2
 
0.3%
0 1
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
8 1
 
0.1%
2 1
 
0.1%
Latin
ValueCountFrequency (%)
A 4
36.4%
Ⅱ 2
18.2%
M 2
18.2%
C 1
 
9.1%
B 1
 
9.1%
R 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 813
54.5%
ASCII 676
45.3%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 351
51.9%
255
37.7%
- 54
 
8.0%
A 4
 
0.6%
7 2
 
0.3%
M 2
 
0.3%
C 1
 
0.1%
0 1
 
0.1%
B 1
 
0.1%
1 1
 
0.1%
Other values (4) 4
 
0.6%
Hangul
ValueCountFrequency (%)
서 114
14.0%
동 62
 
7.6%
특 57
 
7.0%
별 57
 
7.0%
시 57
 
7.0%
강 57
 
7.0%
구 57
 
7.0%
울 57
 
7.0%
곡 31
 
3.8%
호 26
 
3.2%
Other values (66) 238
29.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명주소
Text

Distinct49
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-05-11T14:38:00.384389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length35.982456
Min length23

Characters and Unicode

Total characters2051
Distinct characters121
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)75.4%

Sample

1st row서울특별시 강서구 방화대로**길 ** (방화동,한양빌딩 ***)
2nd row서울특별시 강서구 양천로**나길 **-* (가양동,*층)
3rd row서울특별시 강서구 방화대로*바길 ** (공항동,*층)
4th row서울특별시 강서구 양천로**길 ** (염창동,*층)
5th row서울특별시 강서구 금낭화로 *** (방화동,방화샤르망오피스텔 *동 ***호)
ValueCountFrequency (%)
58
15.2%
서울특별시 57
14.9%
강서구 57
14.9%
호 33
 
8.6%
마곡동 21
 
5.5%
층 16
 
4.2%
공항대로 11
 
2.9%
화곡동 9
 
2.4%
등촌동 7
 
1.8%
공항동 6
 
1.6%
Other values (72) 107
28.0%
2024-05-11T14:38:00.956677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 357
17.4%
325
 
15.8%
서 118
 
5.8%
동 67
 
3.3%
강 60
 
2.9%
, 60
 
2.9%
( 57
 
2.8%
특 57
 
2.8%
별 57
 
2.8%
시 57
 
2.8%
Other values (111) 836
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1154
56.3%
Other Punctuation 417
 
20.3%
Space Separator 325
 
15.8%
Open Punctuation 57
 
2.8%
Close Punctuation 57
 
2.8%
Dash Punctuation 19
 
0.9%
Uppercase Letter 11
 
0.5%
Decimal Number 7
 
0.3%
Letter Number 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 118
 
10.2%
동 67
 
5.8%
강 60
 
5.2%
특 57
 
4.9%
별 57
 
4.9%
시 57
 
4.9%
구 57
 
4.9%
울 57
 
4.9%
로 57
 
4.9%
곡 47
 
4.1%
Other values (92) 520
45.1%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
3 1
14.3%
8 1
14.3%
2 1
14.3%
0 1
14.3%
6 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 5
45.5%
M 2
 
18.2%
C 2
 
18.2%
R 1
 
9.1%
B 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
* 357
85.6%
, 60
 
14.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Space Separator
ValueCountFrequency (%)
325
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1154
56.3%
Common 882
43.0%
Latin 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 118
 
10.2%
동 67
 
5.8%
강 60
 
5.2%
특 57
 
4.9%
별 57
 
4.9%
시 57
 
4.9%
구 57
 
4.9%
울 57
 
4.9%
로 57
 
4.9%
곡 47
 
4.1%
Other values (92) 520
45.1%
Common
ValueCountFrequency (%)
* 357
40.5%
325
36.8%
, 60
 
6.8%
( 57
 
6.5%
) 57
 
6.5%
- 19
 
2.2%
1 2
 
0.2%
3 1
 
0.1%
8 1
 
0.1%
2 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
A 5
33.3%
M 2
 
13.3%
Ⅱ 2
 
13.3%
Ⅰ 2
 
13.3%
C 2
 
13.3%
R 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1154
56.3%
ASCII 893
43.5%
Number Forms 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 357
40.0%
325
36.4%
, 60
 
6.7%
( 57
 
6.4%
) 57
 
6.4%
- 19
 
2.1%
A 5
 
0.6%
M 2
 
0.2%
1 2
 
0.2%
C 2
 
0.2%
Other values (7) 7
 
0.8%
Hangul
ValueCountFrequency (%)
서 118
 
10.2%
동 67
 
5.8%
강 60
 
5.2%
특 57
 
4.9%
별 57
 
4.9%
시 57
 
4.9%
구 57
 
4.9%
울 57
 
4.9%
로 57
 
4.9%
곡 47
 
4.1%
Other values (92) 520
45.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)50.0%
Missing9
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean7679.2292
Minimum7527
Maximum7805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:38:01.146407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7527
5-th percentile7551.35
Q17628
median7651.5
Q37788
95-th percentile7803
Maximum7805
Range278
Interquartile range (IQR)160

Descriptive statistics

Standard deviation92.497784
Coefficient of variation (CV)0.012045191
Kurtosis-1.3587116
Mean7679.2292
Median Absolute Deviation (MAD)70.5
Skewness0.19683982
Sum368603
Variance8555.84
MonotonicityNot monotonic
2024-05-11T14:38:01.362478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
7788 6
 
10.5%
7631 5
 
8.8%
7654 5
 
8.8%
7803 4
 
7.0%
7628 3
 
5.3%
7690 2
 
3.5%
7645 2
 
3.5%
7802 2
 
3.5%
7563 2
 
3.5%
7805 2
 
3.5%
Other values (14) 15
26.3%
(Missing) 9
15.8%
ValueCountFrequency (%)
7527 1
1.8%
7530 1
1.8%
7551 1
1.8%
7552 1
1.8%
7563 2
3.5%
7569 1
1.8%
7571 1
1.8%
7591 1
1.8%
7592 1
1.8%
7619 1
1.8%
ValueCountFrequency (%)
7805 2
 
3.5%
7803 4
7.0%
7802 2
 
3.5%
7801 2
 
3.5%
7788 6
10.5%
7712 1
 
1.8%
7690 2
 
3.5%
7654 5
8.8%
7649 1
 
1.8%
7645 2
 
3.5%

사업장명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-05-11T14:38:01.773422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.5614035
Min length2

Characters and Unicode

Total characters431
Distinct characters114
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

Unique57 ?
Unique (%)100.0%

Sample

1st row정명물류주식회사
2nd row(주)마라식품
3rd row강서급식영업점(주)
4th row하림학교급식사업단
5th row청원
ValueCountFrequency (%)
정명물류주식회사 1
 
1.7%
한국냉동냉장협동조합 1
 
1.7%
주)경세물류 1
 
1.7%
주)경세 1
 
1.7%
은성운수 1
 
1.7%
주)케이엘씨냉동물류 1
 
1.7%
주)바벨 1
 
1.7%
주)비와이로지스 1
 
1.7%
에스앤샤(주 1
 
1.7%
주)지앤샤 1
 
1.7%
Other values (48) 48
82.8%
2024-05-11T14:38:02.307366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 46
 
10.7%
( 40
 
9.3%
) 40
 
9.3%
스 17
 
3.9%
물 11
 
2.6%
운 10
 
2.3%
지 10
 
2.3%
이 9
 
2.1%
통 9
 
2.1%
류 9
 
2.1%
Other values (104) 230
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 350
81.2%
Open Punctuation 40
 
9.3%
Close Punctuation 40
 
9.3%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 46
 
13.1%
스 17
 
4.9%
물 11
 
3.1%
운 10
 
2.9%
지 10
 
2.9%
이 9
 
2.6%
통 9
 
2.6%
류 9
 
2.6%
에 8
 
2.3%
로 8
 
2.3%
Other values (101) 213
60.9%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
81.2%
Common 81
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 46
 
13.1%
스 17
 
4.9%
물 11
 
3.1%
운 10
 
2.9%
지 10
 
2.9%
이 9
 
2.6%
통 9
 
2.6%
류 9
 
2.6%
에 8
 
2.3%
로 8
 
2.3%
Other values (101) 213
60.9%
Common
ValueCountFrequency (%)
( 40
49.4%
) 40
49.4%
1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 350
81.2%
ASCII 81
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 46
 
13.1%
스 17
 
4.9%
물 11
 
3.1%
운 10
 
2.9%
지 10
 
2.9%
이 9
 
2.6%
통 9
 
2.6%
류 9
 
2.6%
에 8
 
2.3%
로 8
 
2.3%
Other values (101) 213
60.9%
ASCII
ValueCountFrequency (%)
( 40
49.4%
) 40
49.4%
1
 
1.2%

최종수정일자
Date

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2005-11-11 11:03:33
Maximum2024-05-08 13:51:10
2024-05-11T14:38:02.565255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:02.772504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
U
30 
I
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 30
52.6%
I 27
47.4%

Length

2024-05-11T14:38:03.011667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:03.181493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 30
52.6%
i 27
47.4%

데이터갱신일자
Date

Distinct39
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T14:38:03.316016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:03.492741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)79.2%
Missing4
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean185523.46
Minimum183396
Maximum188835.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:38:03.700802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183396
5-th percentile183532.11
Q1184555.69
median185365
Q3186915.48
95-th percentile187885.26
Maximum188835.4
Range5439.4054
Interquartile range (IQR)2359.7908

Descriptive statistics

Standard deviation1453.5521
Coefficient of variation (CV)0.0078348696
Kurtosis-0.9107875
Mean185523.46
Median Absolute Deviation (MAD)1360.2625
Skewness0.36404554
Sum9832743.5
Variance2112813.8
MonotonicityNot monotonic
2024-05-11T14:38:03.996361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
187020.691251664 5
 
8.8%
184555.689189052 3
 
5.3%
183532.107955654 3
 
5.3%
184785.483493825 2
 
3.5%
186059.567733485 2
 
3.5%
185365.0 2
 
3.5%
185796.522248947 1
 
1.8%
183821.918422459 1
 
1.8%
183829.89036961 1
 
1.8%
184786.585 1
 
1.8%
Other values (32) 32
56.1%
(Missing) 4
 
7.0%
ValueCountFrequency (%)
183395.997199242 1
 
1.8%
183410.412077203 1
 
1.8%
183532.107955654 3
5.3%
183813.857453649 1
 
1.8%
183821.918422459 1
 
1.8%
183829.396063757 1
 
1.8%
183829.89036961 1
 
1.8%
183846.868344957 1
 
1.8%
184004.737526946 1
 
1.8%
184270.416522537 1
 
1.8%
ValueCountFrequency (%)
188835.402562736 1
 
1.8%
187999.32555627 1
 
1.8%
187917.439597431 1
 
1.8%
187863.804689352 1
 
1.8%
187846.66220879 1
 
1.8%
187727.758706201 1
 
1.8%
187318.537784364 1
 
1.8%
187197.468812217 1
 
1.8%
187020.691251664 5
8.8%
186915.480005327 1
 
1.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)79.2%
Missing4
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean450706.58
Minimum448054.79
Maximum452801.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-05-11T14:38:04.253675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448054.79
5-th percentile449557.73
Q1450220.36
median450520
Q3451161.11
95-th percentile452156.83
Maximum452801.71
Range4746.9196
Interquartile range (IQR)940.75129

Descriptive statistics

Standard deviation890.92787
Coefficient of variation (CV)0.0019767359
Kurtosis1.0791536
Mean450706.58
Median Absolute Deviation (MAD)376.12733
Skewness0.021579968
Sum23887449
Variance793752.48
MonotonicityNot monotonic
2024-05-11T14:38:04.499049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
450220.360286033 5
 
8.8%
451767.833497048 3
 
5.3%
450264.094106506 3
 
5.3%
450767.258354567 2
 
3.5%
449557.727951319 2
 
3.5%
450789.0 2
 
3.5%
450735.884713387 1
 
1.8%
452094.702492877 1
 
1.8%
450302.641275788 1
 
1.8%
450708.875 1
 
1.8%
Other values (32) 32
56.1%
(Missing) 4
 
7.0%
ValueCountFrequency (%)
448054.788172052 1
 
1.8%
448774.26092327 1
 
1.8%
449557.727951319 2
 
3.5%
449786.155926625 1
 
1.8%
449920.361168751 1
 
1.8%
449984.307330522 1
 
1.8%
450046.501440984 1
 
1.8%
450106.568603944 1
 
1.8%
450143.872075084 1
 
1.8%
450220.360286033 5
8.8%
ValueCountFrequency (%)
452801.707821111 1
 
1.8%
452730.209311733 1
 
1.8%
452250.028523129 1
 
1.8%
452094.702492877 1
 
1.8%
451831.218540076 1
 
1.8%
451822.756997863 1
 
1.8%
451811.54803411 1
 
1.8%
451767.833497048 3
5.3%
451722.650631223 1
 
1.8%
451274.550746832 1
 
1.8%

축산업무구분명
Categorical

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
축산물운반업
32 
<NA>
25 

Length

Max length6
Median length6
Mean length5.122807
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물운반업 32
56.1%
<NA> 25
43.9%

Length

2024-05-11T14:38:04.772351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:04.937551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물운반업 32
56.1%
na 25
43.9%

축산물가공업구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing57
Missing (%)100.0%
Memory size645.0 B

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
51 
0
6 

Length

Max length4
Median length4
Mean length3.6842105
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
89.5%
0 6
 
10.5%

Length

2024-05-11T14:38:05.064724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:05.206867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
89.5%
0 6
 
10.5%

권리주체일련번호
Categorical

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
25 
L00
21 
000
11 

Length

Max length4
Median length3
Mean length3.4385965
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
43.9%
L00 21
36.8%
000 11
19.3%

Length

2024-05-11T14:38:05.352787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:05.487878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
43.9%
l00 21
36.8%
000 11
19.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
51 
0
6 

Length

Max length4
Median length4
Mean length3.6842105
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
89.5%
0 6
 
10.5%

Length

2024-05-11T14:38:05.627432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:06.065995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
89.5%
0 6
 
10.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0315000031500000082004000120040703<NA>3폐업2폐업20051111<NA><NA><NA><NA>23.1<NA>서울특별시 강서구 방화동 ***-**번지 한양빌딩 ***서울특별시 강서구 방화대로**길 ** (방화동,한양빌딩 ***)<NA>정명물류주식회사2005-11-11 11:03:33I2018-08-31 23:59:59.0<NA>183846.868345452730.209312축산물운반업<NA><NA>L00<NA>
1315000031500000082006000120060614<NA>3폐업2폐업20170718<NA><NA><NA>2607-6503,2607-650155.2<NA>서울특별시 강서구 가양동 ***-*번지 *층서울특별시 강서구 양천로**나길 **-* (가양동,*층)<NA>(주)마라식품2017-07-18 17:05:44I2018-08-31 23:59:59.0<NA>185826.642871452250.028523축산물운반업<NA><NA>L00<NA>
2315000031500000082006000220060704<NA>1영업/정상0정상<NA><NA><NA><NA>2666-642765.32<NA>서울특별시 강서구 공항동 ****-* *층서울특별시 강서구 방화대로*바길 ** (공항동,*층)<NA>강서급식영업점(주)2021-04-22 16:36:48U2021-04-24 02:40:00.0<NA>184004.737527450404.836134축산물운반업<NA><NA>L00<NA>
3315000031500000082006000320060706<NA>3폐업2폐업20220405<NA><NA><NA>3664-506040.92<NA>서울특별시 강서구 염창동 ***-**서울특별시 강서구 양천로**길 ** (염창동,*층)<NA>하림학교급식사업단2022-04-05 15:38:24U2021-12-04 00:07:00.0<NA>188835.402563450046.501441<NA><NA><NA><NA><NA>
4315000031500000082006000420060926<NA>1영업/정상0정상<NA><NA><NA><NA>766-407816.8<NA>서울특별시 강서구 방화동 ***-*번지 방화샤르망오피스텔 *동 ***호서울특별시 강서구 금낭화로 *** (방화동,방화샤르망오피스텔 *동 ***호)<NA>청원2006-09-26 18:32:02I2018-08-31 23:59:59.0<NA>183410.412077452801.707821축산물운반업<NA><NA>000<NA>
5315000031500000082007000120070511<NA>3폐업2폐업20120508<NA><NA><NA><NA>90.72<NA>서울특별시 강서구 화곡동 ***-**번지 *층서울특별시 강서구 등촌로 ** (화곡동,*층)<NA>임박사축산물유통2012-05-08 11:21:32I2018-08-31 23:59:59.0<NA>187846.662209448054.788172축산물운반업<NA><NA>000<NA>
6315000031500000082007000220070605<NA>3폐업2폐업20201104<NA><NA><NA>022657773723.76<NA>서울특별시 강서구 등촌동 ***서울특별시 강서구 양천로 *** (등촌동)7552씨제이대한통운(주)2020-11-04 16:30:08U2020-11-06 02:40:00.0<NA>187863.804689450427.696055축산물운반업<NA><NA>L00<NA>
7315000031500000082007000320071106<NA>3폐업2폐업20120224<NA><NA><NA>02-3663-1045124.6<NA>서울특별시 강서구 가양동 ****-*번지 이천이프라자 ***호서울특별시 강서구 공항대로 *** (가양동,이천이프라자 ***호)<NA>성주로지스틱(주)2012-02-24 19:18:15I2018-08-31 23:59:59.0<NA>185667.855229451058.435888축산물운반업<NA><NA>L00<NA>
8315000031500000082007000420071106<NA>3폐업2폐업20120224<NA><NA><NA>02-3663-720034.0<NA>서울특별시 강서구 가양동 ****-*번지 이스타빌*차 ***호서울특별시 강서구 양천로**길 **-** (가양동,이스타빌*차 ***호)<NA>정방특송운수(주)2012-02-24 19:19:46I2018-08-31 23:59:59.0<NA>186915.480005451230.088219축산물운반업<NA><NA>L00<NA>
9315000031500000082009000120090918<NA>3폐업2폐업20190402<NA><NA><NA>2657711413.15<NA>서울특별시 강서구 등촌동 ***-*번지서울특별시 강서구 양천로 *** (등촌동)7551서울축협축산유통본부2019-04-02 17:32:18U2019-04-04 02:40:00.0<NA>187727.758706450500.126507축산물운반업<NA><NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
47315000031500000082022000320221116<NA>1영업/정상0정상<NA><NA><NA><NA>02-3665-037430.0<NA>서울특별시 강서구 마곡동 ***-* 퀸즈파크나인 C동 ****호서울특별시 강서구 공항대로 ***, 퀸즈파크나인 C동 ****호 (마곡동)7803(주)부스터스주원2022-11-16 15:47:12I2021-10-31 23:08:00.0<NA>185365.0450789.0<NA><NA><NA><NA><NA>
4831500003150000008202300012023-05-12<NA>1영업/정상0정상<NA><NA><NA><NA>02-3665-348041.65<NA>서울특별시 강서구 마곡동 ***-* ***호서울특별시 강서구 공항대로 ***, 보타닉파크타워* ***호 (마곡동)7802(주)제이디아이로지스2023-07-20 15:03:29U2022-12-06 22:02:00.0<NA>185032.421148450836.071292<NA><NA><NA><NA><NA>
4931500003150000008202300022023-06-14<NA>1영업/정상0정상<NA><NA><NA><NA><NA>8.0<NA>서울특별시 강서구 내발산동 ***-** 신원메디칼프라자 *층 ***호 R*서울특별시 강서구 강서로**길 ***, 신원메디칼프라자 *층 ***호 R*호 (내발산동)7635(주)신한디앤엘2023-06-14 13:14:08I2022-12-05 23:07:00.0<NA>184636.533441450143.872075<NA><NA><NA><NA><NA>
5031500003150000008202300032023-07-26<NA>1영업/정상0정상<NA><NA><NA><NA>02-3665-037443.9<NA>서울특별시 강서구 마곡동 ***-*서울특별시 강서구 공항대로 ***, 퀸즈파크나인 C동 ****호 (마곡동)7803(주)삼마통운2023-07-26 15:50:34I2022-12-06 22:08:00.0<NA>185371.298774450793.771245<NA><NA><NA><NA><NA>
5131500003150000008202300042022-11-08<NA>1영업/정상0정상<NA><NA><NA><NA><NA>95.94<NA>서울특별시 강서구 공항동 **-**서울특별시 강서구 공항대로*길 **, ***, ***호 (공항동, 청성스카이)7619(주)오케이씨물류2023-08-02 13:30:43I2022-12-08 00:04:00.0<NA>183395.997199451161.111575<NA><NA><NA><NA><NA>
5231500003150000008202300052023-09-13<NA>1영업/정상0정상<NA><NA><NA><NA>02-3662-99095.0<NA>서울특별시 강서구 마곡동 ***-*서울특별시 강서구 마곡중앙*로 **, 리더스퀘어마곡 *층 ***-에이*호 (마곡동)7802더한솔씨앤에스(주)2023-09-13 15:23:38I2022-12-08 23:07:00.0<NA>185127.285385450939.221091<NA><NA><NA><NA><NA>
5331500003150000008202300062023-10-05<NA>1영업/정상0정상<NA><NA><NA><NA>02-3663-7878109.97<NA>서울특별시 강서구 등촌동 ***-* 비원오피스텔 ***호서울특별시 강서구 공항대로 ***, 비원오피스텔 ***호 (등촌동)7563한국냉동운수 주식회사2023-10-05 11:49:38I2022-10-31 00:07:00.0<NA>187999.325556449920.361169<NA><NA><NA><NA><NA>
5431500003150000008202300072021-07-29<NA>1영업/정상0정상<NA><NA><NA><NA>6080323335.65<NA>서울특별시 강서구 마곡동 ***-*서울특별시 강서구 마곡서로 ***, 두산더랜드타워 비동 ***호 (마곡동)7788(주)스카이엠2023-11-16 14:36:32I2022-10-31 23:08:00.0<NA>184526.084368451722.650631<NA><NA><NA><NA><NA>
5531500003150000008202300082023-12-07<NA>1영업/정상0정상<NA><NA><NA><NA>0253847236.6<NA>서울특별시 강서구 화곡동 ****-*서울특별시 강서구 까치산로 ***-*, *층 일부호 (화곡동)7654(주)대한물류2024-04-29 09:58:02U2023-12-05 00:01:00.0<NA>187020.691252450220.360286<NA><NA><NA><NA><NA>
5631500003150000008202400012024-03-25<NA>1영업/정상0정상<NA><NA><NA><NA><NA>77.04<NA>서울특별시 강서구 마곡동 ***-*서울특별시 강서구 마곡중앙로 ***, 프라이빗타워타워*차 ****호 (마곡동)7788(주)하나로통운2024-03-27 11:28:40U2023-12-02 21:00:00.0<NA>184708.916316451822.756998<NA><NA><NA><NA><NA>