Overview

Dataset statistics

Number of variables30
Number of observations35
Missing cells247
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory259.8 B

Variable types

Categorical12
Numeric5
DateTime3
Unsupported6
Text4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),축산업무구분명,축산물가공업구분명,축산일련번호,권리주체일련번호,총인원
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18128/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 35 (100.0%) missing valuesMissing
폐업일자 has 13 (37.1%) missing valuesMissing
휴업시작일자 has 35 (100.0%) missing valuesMissing
휴업종료일자 has 35 (100.0%) missing valuesMissing
재개업일자 has 35 (100.0%) missing valuesMissing
전화번호 has 13 (37.1%) missing valuesMissing
소재지우편번호 has 35 (100.0%) missing valuesMissing
도로명주소 has 3 (8.6%) missing valuesMissing
도로명우편번호 has 6 (17.1%) missing valuesMissing
업태구분명 has 35 (100.0%) missing valuesMissing
좌표정보(X) has 1 (2.9%) missing valuesMissing
좌표정보(Y) has 1 (2.9%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 23 (65.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:49:55.629992
Analysis finished2024-05-11 06:49:56.186919
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
3010000
35 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 35
100.0%

Length

2024-05-11T15:49:56.291708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:56.471163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 35
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0100001 × 1017
Minimum3.01 × 1017
Maximum3.0100001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T15:49:56.656928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.01 × 1017
5-th percentile3.01 × 1017
Q13.0100001 × 1017
median3.0100001 × 1017
Q33.0100001 × 1017
95-th percentile3.0100001 × 1017
Maximum3.0100001 × 1017
Range1.000018 × 1010
Interquartile range (IQR)94976

Descriptive statistics

Standard deviation4.0584352 × 109
Coefficient of variation (CV)1.3483173 × 10-8
Kurtosis0.48295455
Mean3.0100001 × 1017
Median Absolute Deviation (MAD)70016
Skewness-1.5680171
Sum-7.9117438 × 1018
Variance1.6470896 × 1019
MonotonicityStrictly increasing
2024-05-11T15:49:56.891712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
301000000420050002 1
 
2.9%
301000000420050003 1
 
2.9%
301000010420130003 1
 
2.9%
301000010420130004 1
 
2.9%
301000010420170001 1
 
2.9%
301000010420170002 1
 
2.9%
301000010420190001 1
 
2.9%
301000010420190002 1
 
2.9%
301000010420200001 1
 
2.9%
301000010420200002 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
301000000420050002 1
2.9%
301000000420050003 1
2.9%
301000000420060001 1
2.9%
301000000420060002 1
2.9%
301000000420060003 1
2.9%
301000000420070001 1
2.9%
301000000420090001 1
2.9%
301000010420100001 1
2.9%
301000010420100002 1
2.9%
301000010420100003 1
2.9%
ValueCountFrequency (%)
301000010420230001 1
2.9%
301000010420220006 1
2.9%
301000010420220005 1
2.9%
301000010420220004 1
2.9%
301000010420220003 1
2.9%
301000010420220002 1
2.9%
301000010420220001 1
2.9%
301000010420200002 1
2.9%
301000010420200001 1
2.9%
301000010420190002 1
2.9%

인허가일자
Date

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2005-03-22 00:00:00
Maximum2023-01-06 00:00:00
2024-05-11T15:49:57.129236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:49:57.373217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
3
22 
1
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 22
62.9%
1 13
37.1%

Length

2024-05-11T15:49:57.623805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:57.822565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 22
62.9%
1 13
37.1%

영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
22 
영업/정상
13 

Length

Max length5
Median length2
Mean length3.1142857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
62.9%
영업/정상 13
37.1%

Length

2024-05-11T15:49:58.052316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:58.258538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
62.9%
영업/정상 13
37.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
2
22 
0
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 22
62.9%
0 13
37.1%

Length

2024-05-11T15:49:58.431437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:58.590326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 22
62.9%
0 13
37.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
22 
정상
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
62.9%
정상 13
37.1%

Length

2024-05-11T15:49:58.779859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:58.980999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
62.9%
정상 13
37.1%

폐업일자
Date

MISSING 

Distinct21
Distinct (%)95.5%
Missing13
Missing (%)37.1%
Memory size412.0 B
Minimum2005-12-09 00:00:00
Maximum2023-08-21 00:00:00
2024-05-11T15:49:59.153180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:49:59.347441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

전화번호
Text

MISSING 

Distinct19
Distinct (%)86.4%
Missing13
Missing (%)37.1%
Memory size412.0 B
2024-05-11T15:49:59.665591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.8181818
Min length8

Characters and Unicode

Total characters216
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

Unique16 ?
Unique (%)72.7%

Sample

1st row2238-5416
2nd row310-7399
3rd row317-0063
4th row2238-1961
5th row759-7115
ValueCountFrequency (%)
02-2234-3873 2
 
9.1%
2238-5416 2
 
9.1%
02-2238-5542 2
 
9.1%
2238-4476 1
 
4.5%
02-2232-1961 1
 
4.5%
02-2256-7134 1
 
4.5%
2238-0008 1
 
4.5%
2237-4042 1
 
4.5%
2236-3044 1
 
4.5%
2238-9866 1
 
4.5%
Other values (9) 9
40.9%
2024-05-11T15:50:00.284823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 50
23.1%
3 33
15.3%
- 29
13.4%
0 16
 
7.4%
4 15
 
6.9%
8 15
 
6.9%
7 14
 
6.5%
1 14
 
6.5%
5 12
 
5.6%
6 11
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 187
86.6%
Dash Punctuation 29
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 50
26.7%
3 33
17.6%
0 16
 
8.6%
4 15
 
8.0%
8 15
 
8.0%
7 14
 
7.5%
1 14
 
7.5%
5 12
 
6.4%
6 11
 
5.9%
9 7
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 50
23.1%
3 33
15.3%
- 29
13.4%
0 16
 
7.4%
4 15
 
6.9%
8 15
 
6.9%
7 14
 
6.5%
1 14
 
6.5%
5 12
 
5.6%
6 11
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 50
23.1%
3 33
15.3%
- 29
13.4%
0 16
 
7.4%
4 15
 
6.9%
8 15
 
6.9%
7 14
 
6.5%
1 14
 
6.5%
5 12
 
5.6%
6 11
 
5.1%

소재지면적
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.03
Minimum0
Maximum773
Zeros23
Zeros (%)65.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T15:50:00.558801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q360.91
95-th percentile267.316
Maximum773
Range773
Interquartile range (IQR)60.91

Descriptive statistics

Standard deviation146.36814
Coefficient of variation (CV)2.3982982
Kurtosis16.786674
Mean61.03
Median Absolute Deviation (MAD)0
Skewness3.7986915
Sum2136.05
Variance21423.632
MonotonicityNot monotonic
2024-05-11T15:50:00.783718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 23
65.7%
49.14 1
 
2.9%
60.32 1
 
2.9%
253.44 1
 
2.9%
27.5 1
 
2.9%
77.1 1
 
2.9%
62.53 1
 
2.9%
68.8 1
 
2.9%
61.5 1
 
2.9%
265.0 1
 
2.9%
Other values (3) 3
 
8.6%
ValueCountFrequency (%)
0.0 23
65.7%
27.5 1
 
2.9%
49.14 1
 
2.9%
60.32 1
 
2.9%
61.5 1
 
2.9%
62.53 1
 
2.9%
68.8 1
 
2.9%
77.1 1
 
2.9%
165.0 1
 
2.9%
253.44 1
 
2.9%
ValueCountFrequency (%)
773.0 1
2.9%
272.72 1
2.9%
265.0 1
2.9%
253.44 1
2.9%
165.0 1
2.9%
77.1 1
2.9%
68.8 1
2.9%
62.53 1
2.9%
61.5 1
2.9%
60.32 1
2.9%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

지번주소
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-05-11T15:50:01.136583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.028571
Min length16

Characters and Unicode

Total characters666
Distinct characters41
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

Unique31 ?
Unique (%)88.6%

Sample

1st row서울특별시 중구 황학동 556번지
2nd row서울특별시 중구 황학동 398번지
3rd row서울특별시 중구 태평로2가 23번지
4th row서울특별시 중구 소공동 87번지
5th row서울특별시 중구 황학동 565번지 지하1층, 1층
ValueCountFrequency (%)
서울특별시 35
23.5%
중구 35
23.5%
황학동 29
19.5%
1층 5
 
3.4%
556번지 2
 
1.3%
581 2
 
1.3%
582 2
 
1.3%
신당동 2
 
1.3%
소공동 2
 
1.3%
지하1층 2
 
1.3%
Other values (32) 33
22.1%
2024-05-11T15:50:01.714414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
20.6%
서 35
 
5.3%
특 35
 
5.3%
별 35
 
5.3%
시 35
 
5.3%
중 35
 
5.3%
구 35
 
5.3%
울 35
 
5.3%
동 34
 
5.1%
황 29
 
4.4%
Other values (31) 221
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 407
61.1%
Space Separator 137
 
20.6%
Decimal Number 116
 
17.4%
Dash Punctuation 5
 
0.8%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 35
8.6%
특 35
8.6%
별 35
8.6%
시 35
8.6%
중 35
8.6%
구 35
8.6%
울 35
8.6%
동 34
8.4%
황 29
7.1%
학 29
7.1%
Other values (18) 70
17.2%
Decimal Number
ValueCountFrequency (%)
1 20
17.2%
5 18
15.5%
6 13
11.2%
3 13
11.2%
2 11
9.5%
8 11
9.5%
0 9
7.8%
4 8
 
6.9%
9 7
 
6.0%
7 6
 
5.2%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 407
61.1%
Common 259
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 35
8.6%
특 35
8.6%
별 35
8.6%
시 35
8.6%
중 35
8.6%
구 35
8.6%
울 35
8.6%
동 34
8.4%
황 29
7.1%
학 29
7.1%
Other values (18) 70
17.2%
Common
ValueCountFrequency (%)
137
52.9%
1 20
 
7.7%
5 18
 
6.9%
6 13
 
5.0%
3 13
 
5.0%
2 11
 
4.2%
8 11
 
4.2%
0 9
 
3.5%
4 8
 
3.1%
9 7
 
2.7%
Other values (3) 12
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 407
61.1%
ASCII 259
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
52.9%
1 20
 
7.7%
5 18
 
6.9%
6 13
 
5.0%
3 13
 
5.0%
2 11
 
4.2%
8 11
 
4.2%
0 9
 
3.5%
4 8
 
3.1%
9 7
 
2.7%
Other values (3) 12
 
4.6%
Hangul
ValueCountFrequency (%)
서 35
8.6%
특 35
8.6%
별 35
8.6%
시 35
8.6%
중 35
8.6%
구 35
8.6%
울 35
8.6%
동 34
8.4%
황 29
7.1%
학 29
7.1%
Other values (18) 70
17.2%

도로명주소
Text

MISSING 

Distinct31
Distinct (%)96.9%
Missing3
Missing (%)8.6%
Memory size412.0 B
2024-05-11T15:50:02.088235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length33
Mean length28.5625
Min length21

Characters and Unicode

Total characters914
Distinct characters47
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

Unique30 ?
Unique (%)93.8%

Sample

1st row서울특별시 중구 퇴계로87길 39-4 (황학동)
2nd row서울특별시 중구 소공로 119 (태평로2가)
3rd row서울특별시 중구 퇴계로87길 39-5, 지하1층, 1층 (황학동)
4th row서울특별시 중구 퇴계로87길 15-24 (황학동)
5th row서울특별시 중구 퇴계로87길 29-3 (황학동)
ValueCountFrequency (%)
서울특별시 32
17.9%
중구 32
17.9%
퇴계로87길 28
15.6%
황학동 28
15.6%
1층 10
 
5.6%
35-3 4
 
2.2%
35-5 2
 
1.1%
17-1 2
 
1.1%
23-5 2
 
1.1%
신당동 2
 
1.1%
Other values (35) 37
20.7%
2024-05-11T15:50:02.722036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
 
16.1%
로 33
 
3.6%
서 32
 
3.5%
( 32
 
3.5%
특 32
 
3.5%
별 32
 
3.5%
시 32
 
3.5%
중 32
 
3.5%
구 32
 
3.5%
울 32
 
3.5%
Other values (37) 478
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
52.6%
Decimal Number 177
 
19.4%
Space Separator 147
 
16.1%
Open Punctuation 32
 
3.5%
Close Punctuation 32
 
3.5%
Dash Punctuation 27
 
3.0%
Other Punctuation 18
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 33
 
6.9%
서 32
 
6.7%
특 32
 
6.7%
별 32
 
6.7%
시 32
 
6.7%
중 32
 
6.7%
구 32
 
6.7%
울 32
 
6.7%
동 32
 
6.7%
길 29
 
6.0%
Other values (22) 163
33.9%
Decimal Number
ValueCountFrequency (%)
8 31
17.5%
7 31
17.5%
3 27
15.3%
1 26
14.7%
2 24
13.6%
5 16
9.0%
9 9
 
5.1%
4 7
 
4.0%
6 3
 
1.7%
0 3
 
1.7%
Space Separator
ValueCountFrequency (%)
147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 481
52.6%
Common 433
47.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 33
 
6.9%
서 32
 
6.7%
특 32
 
6.7%
별 32
 
6.7%
시 32
 
6.7%
중 32
 
6.7%
구 32
 
6.7%
울 32
 
6.7%
동 32
 
6.7%
길 29
 
6.0%
Other values (22) 163
33.9%
Common
ValueCountFrequency (%)
147
33.9%
( 32
 
7.4%
) 32
 
7.4%
8 31
 
7.2%
7 31
 
7.2%
3 27
 
6.2%
- 27
 
6.2%
1 26
 
6.0%
2 24
 
5.5%
, 18
 
4.2%
Other values (5) 38
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 481
52.6%
ASCII 433
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
33.9%
( 32
 
7.4%
) 32
 
7.4%
8 31
 
7.2%
7 31
 
7.2%
3 27
 
6.2%
- 27
 
6.2%
1 26
 
6.0%
2 24
 
5.5%
, 18
 
4.2%
Other values (5) 38
 
8.8%
Hangul
ValueCountFrequency (%)
로 33
 
6.9%
서 32
 
6.7%
특 32
 
6.7%
별 32
 
6.7%
시 32
 
6.7%
중 32
 
6.7%
구 32
 
6.7%
울 32
 
6.7%
동 32
 
6.7%
길 29
 
6.0%
Other values (22) 163
33.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)20.7%
Missing6
Missing (%)17.1%
Infinite0
Infinite (%)0.0%
Mean4576.1034
Minimum4525
Maximum4606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T15:50:02.949817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4525
5-th percentile4575.4
Q14576
median4576
Q34576
95-th percentile4590.6
Maximum4606
Range81
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.004002
Coefficient of variation (CV)0.0026231928
Kurtosis13.476969
Mean4576.1034
Median Absolute Deviation (MAD)0
Skewness-2.100786
Sum132707
Variance144.09606
MonotonicityNot monotonic
2024-05-11T15:50:03.168960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4576 24
68.6%
4525 1
 
2.9%
4599 1
 
2.9%
4578 1
 
2.9%
4575 1
 
2.9%
4606 1
 
2.9%
(Missing) 6
 
17.1%
ValueCountFrequency (%)
4525 1
 
2.9%
4575 1
 
2.9%
4576 24
68.6%
4578 1
 
2.9%
4599 1
 
2.9%
4606 1
 
2.9%
ValueCountFrequency (%)
4606 1
 
2.9%
4599 1
 
2.9%
4578 1
 
2.9%
4576 24
68.6%
4575 1
 
2.9%
4525 1
 
2.9%

사업장명
Text

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-05-11T15:50:03.540082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length4
Mean length5.9142857
Min length2

Characters and Unicode

Total characters207
Distinct characters86
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

Unique27 ?
Unique (%)77.1%

Sample

1st row춘천상회
2nd row송닭
3rd row한화개발(주)
4th row주식회사신세계조선호텔
5th row아이엠(IM)
ValueCountFrequency (%)
춘천상회 2
 
5.0%
해성상회 2
 
5.0%
신흥상회 2
 
5.0%
경북상회 2
 
5.0%
주)호박패밀리 1
 
2.5%
한성상회 1
 
2.5%
트레이딩 1
 
2.5%
에스아이 1
 
2.5%
디(the 1
 
2.5%
안성유통 1
 
2.5%
Other values (26) 26
65.0%
2024-05-11T15:50:04.178694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 13
 
6.3%
상 11
 
5.3%
( 9
 
4.3%
주 9
 
4.3%
) 9
 
4.3%
이 8
 
3.9%
유 8
 
3.9%
통 8
 
3.9%
성 6
 
2.9%
아 5
 
2.4%
Other values (76) 121
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
83.6%
Open Punctuation 9
 
4.3%
Close Punctuation 9
 
4.3%
Uppercase Letter 9
 
4.3%
Space Separator 5
 
2.4%
Other Punctuation 1
 
0.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 13
 
7.5%
상 11
 
6.4%
주 9
 
5.2%
이 8
 
4.6%
유 8
 
4.6%
통 8
 
4.6%
성 6
 
3.5%
아 5
 
2.9%
드 4
 
2.3%
호 4
 
2.3%
Other values (63) 97
56.1%
Uppercase Letter
ValueCountFrequency (%)
G 2
22.2%
B 1
11.1%
K 1
11.1%
T 1
11.1%
H 1
11.1%
E 1
11.1%
I 1
11.1%
M 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
83.6%
Common 25
 
12.1%
Latin 9
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 13
 
7.5%
상 11
 
6.4%
주 9
 
5.2%
이 8
 
4.6%
유 8
 
4.6%
통 8
 
4.6%
성 6
 
3.5%
아 5
 
2.9%
드 4
 
2.3%
호 4
 
2.3%
Other values (63) 97
56.1%
Latin
ValueCountFrequency (%)
G 2
22.2%
B 1
11.1%
K 1
11.1%
T 1
11.1%
H 1
11.1%
E 1
11.1%
I 1
11.1%
M 1
11.1%
Common
ValueCountFrequency (%)
( 9
36.0%
) 9
36.0%
5
20.0%
& 1
 
4.0%
2 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
83.6%
ASCII 34
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 13
 
7.5%
상 11
 
6.4%
주 9
 
5.2%
이 8
 
4.6%
유 8
 
4.6%
통 8
 
4.6%
성 6
 
3.5%
아 5
 
2.9%
드 4
 
2.3%
호 4
 
2.3%
Other values (63) 97
56.1%
ASCII
ValueCountFrequency (%)
( 9
26.5%
) 9
26.5%
5
14.7%
G 2
 
5.9%
B 1
 
2.9%
K 1
 
2.9%
& 1
 
2.9%
T 1
 
2.9%
H 1
 
2.9%
E 1
 
2.9%
Other values (3) 3
 
8.8%

최종수정일자
Date

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2005-12-09 11:30:47
Maximum2023-08-21 10:29:02
2024-05-11T15:50:04.419047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:04.637910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
I
23 
U
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 23
65.7%
U 12
34.3%

Length

2024-05-11T15:50:04.918264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:05.121735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 23
65.7%
u 12
34.3%

데이터갱신일자
Categorical

Distinct17
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
2018-08-31 23:59:59.0
17 
2021-12-06 22:09:00.0
2 
2022-11-30 23:03:00.0
2 
2022-12-03 23:04:00.0
 
1
2022-12-07 22:03:00.0
 
1
Other values (12)
12 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique14 ?
Unique (%)40.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 17
48.6%
2021-12-06 22:09:00.0 2
 
5.7%
2022-11-30 23:03:00.0 2
 
5.7%
2022-12-03 23:04:00.0 1
 
2.9%
2022-12-07 22:03:00.0 1
 
2.9%
2018-10-06 02:37:00.0 1
 
2.9%
2020-12-10 02:40:00.0 1
 
2.9%
2020-05-15 02:40:00.0 1
 
2.9%
2022-12-06 22:06:00.0 1
 
2.9%
2020-12-11 00:23:07.0 1
 
2.9%
Other values (7) 7
20.0%

Length

2024-05-11T15:50:05.336406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 17
24.3%
23:59:59.0 17
24.3%
2021-12-06 3
 
4.3%
02:40:00.0 3
 
4.3%
22:09:00.0 2
 
2.9%
2022-11-30 2
 
2.9%
23:03:00.0 2
 
2.9%
22:06:00.0 2
 
2.9%
2022-12-07 2
 
2.9%
21:01:00.0 1
 
1.4%
Other values (19) 19
27.1%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean201474.24
Minimum197979.02
Maximum201861.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T15:50:05.544739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197979.02
5-th percentile199778.02
Q1201713
median201758.69
Q3201774.01
95-th percentile201785.61
Maximum201861.48
Range3882.4638
Interquartile range (IQR)61.015646

Descriptive statistics

Standard deviation894.4519
Coefficient of variation (CV)0.0044395347
Kurtosis11.319017
Mean201474.24
Median Absolute Deviation (MAD)18.699886
Skewness-3.4403834
Sum6850124.3
Variance800044.21
MonotonicityNot monotonic
2024-05-11T15:50:05.790603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
201775.537390563 4
 
11.4%
201769.444016831 2
 
5.7%
201756.660329003 2
 
5.7%
201769.020969121 2
 
5.7%
201779.001961336 2
 
5.7%
201696.529975213 2
 
5.7%
201689.592966448 1
 
2.9%
200595.595396617 1
 
2.9%
201699.450199909 1
 
2.9%
201711.550895212 1
 
2.9%
Other values (16) 16
45.7%
ValueCountFrequency (%)
197979.021229862 1
2.9%
198259.65357739 1
2.9%
200595.595396617 1
2.9%
200648.629568653 1
2.9%
201689.592966448 1
2.9%
201696.529975213 2
5.7%
201699.450199909 1
2.9%
201711.550895212 1
2.9%
201717.340920376 1
2.9%
201720.850271273 1
2.9%
ValueCountFrequency (%)
201861.484999629 1
 
2.9%
201797.872285138 1
 
2.9%
201779.001961336 2
5.7%
201775.768406933 1
 
2.9%
201775.537390563 4
11.4%
201769.444016831 2
5.7%
201769.172163749 1
 
2.9%
201769.020969121 2
5.7%
201767.48508967 1
 
2.9%
201763.072484991 1
 
2.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean451519.93
Minimum449991.9
Maximum451679.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-05-11T15:50:06.035199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449991.9
5-th percentile451149.86
Q1451577.11
median451600.22
Q3451638.52
95-th percentile451670.07
Maximum451679.97
Range1688.0724
Interquartile range (IQR)61.408674

Descriptive statistics

Standard deviation316.25933
Coefficient of variation (CV)0.0007004327
Kurtosis17.961043
Mean451519.93
Median Absolute Deviation (MAD)33.268435
Skewness-4.1097625
Sum15351678
Variance100019.96
MonotonicityNot monotonic
2024-05-11T15:50:06.272025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
451638.555518062 4
 
11.4%
451679.967881989 2
 
5.7%
451638.515468422 2
 
5.7%
451586.459143385 2
 
5.7%
451556.93850436 2
 
5.7%
451600.128787117 2
 
5.7%
451600.026058007 1
 
2.9%
450728.433219248 1
 
2.9%
451574.159101387 1
 
2.9%
451600.319685417 1
 
2.9%
Other values (16) 16
45.7%
ValueCountFrequency (%)
449991.895498034 1
2.9%
450728.433219248 1
2.9%
451376.783371586 1
2.9%
451392.198218657 1
2.9%
451393.00519364 1
2.9%
451556.93850436 2
5.7%
451572.458464245 1
2.9%
451574.159101387 1
2.9%
451585.94987454 1
2.9%
451586.279676386 1
2.9%
ValueCountFrequency (%)
451679.967881989 2
5.7%
451664.745496196 1
 
2.9%
451653.532244586 1
 
2.9%
451638.555518062 4
11.4%
451638.515468422 2
5.7%
451628.469874125 1
 
2.9%
451627.226022892 1
 
2.9%
451624.58847622 1
 
2.9%
451612.220168178 1
 
2.9%
451600.446443249 1
 
2.9%

축산업무구분명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
식육포장처리업
23 
<NA>
12 

Length

Max length7
Median length7
Mean length5.9714286
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 23
65.7%
<NA> 12
34.3%

Length

2024-05-11T15:50:06.801218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:06.956966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 23
65.7%
na 12
34.3%

축산물가공업구분명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
식육포장처리업
23 
<NA>
12 

Length

Max length7
Median length7
Mean length5.9714286
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 23
65.7%
<NA> 12
34.3%

Length

2024-05-11T15:50:07.157650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:07.431758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 23
65.7%
na 12
34.3%

축산일련번호
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
23 
<NA>
12 

Length

Max length4
Median length1
Mean length2.0285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
65.7%
<NA> 12
34.3%

Length

2024-05-11T15:50:07.647883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:07.860539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
65.7%
na 12
34.3%

권리주체일련번호
Categorical

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
000
15 
<NA>
12 
L00
8 

Length

Max length4
Median length3
Mean length3.3428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 15
42.9%
<NA> 12
34.3%
L00 8
22.9%

Length

2024-05-11T15:50:08.054696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:08.288908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 15
42.9%
na 12
34.3%
l00 8
22.9%

총인원
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
23 
<NA>
12 

Length

Max length4
Median length1
Mean length2.0285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
65.7%
<NA> 12
34.3%

Length

2024-05-11T15:50:08.493881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:08.698758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
65.7%
na 12
34.3%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0301000030100000042005000220050322<NA>3폐업2폐업20090331<NA><NA><NA>2238-541649.14<NA>서울특별시 중구 황학동 556번지서울특별시 중구 퇴계로87길 39-4 (황학동)<NA>춘천상회2011-02-09 16:32:50I2018-08-31 23:59:59.0<NA>201769.444017451679.967882식육포장처리업식육포장처리업00000
1301000030100000042005000320050330<NA>3폐업2폐업20051209<NA><NA><NA><NA>60.32<NA>서울특별시 중구 황학동 398번지<NA><NA>송닭2005-12-09 11:30:47I2018-08-31 23:59:59.0<NA>201696.529975451600.128787식육포장처리업식육포장처리업00000
2301000030100000042006000120060824<NA>3폐업2폐업20140225<NA><NA><NA>310-7399253.44<NA>서울특별시 중구 태평로2가 23번지서울특별시 중구 소공로 119 (태평로2가)4525한화개발(주)2014-02-25 16:53:48I2018-08-31 23:59:59.0<NA>197979.02123451376.783372식육포장처리업식육포장처리업0L000
3301000030100000042006000220061012<NA>3폐업2폐업20130927<NA><NA><NA>317-006327.5<NA>서울특별시 중구 소공동 87번지<NA><NA>주식회사신세계조선호텔2013-09-27 09:52:16I2018-08-31 23:59:59.0<NA><NA><NA>식육포장처리업식육포장처리업0L000
4301000030100000042006000320061123<NA>1영업/정상0정상<NA><NA><NA><NA>2238-196177.1<NA>서울특별시 중구 황학동 565번지 지하1층, 1층서울특별시 중구 퇴계로87길 39-5, 지하1층, 1층 (황학동)4576아이엠(IM)2017-05-25 08:55:33I2018-08-31 23:59:59.0<NA>201759.33003451664.745496식육포장처리업식육포장처리업00000
5301000030100000042007000120070126<NA>3폐업2폐업20131231<NA><NA><NA>759-71150.0<NA>서울특별시 중구 소공동 1번지<NA><NA>(주)호텔롯데2013-12-31 15:27:29I2018-08-31 23:59:59.0<NA>198259.653577451392.198219식육포장처리업식육포장처리업0L000
6301000030100000042009000120090306<NA>3폐업2폐업20131008<NA><NA><NA>2232-75910.0<NA>서울특별시 중구 황학동 394번지서울특별시 중구 퇴계로87길 15-24 (황학동)<NA>동양상회2013-10-08 17:54:25I2018-08-31 23:59:59.0<NA>201720.850271451572.458464식육포장처리업식육포장처리업00000
7301000030100001042010000120101020<NA>3폐업2폐업20141127<NA><NA><NA>2235-67870.0<NA>서울특별시 중구 황학동 592번지서울특별시 중구 퇴계로87길 29-3 (황학동)4576주식회사오케이푸드2014-11-27 12:02:03I2018-08-31 23:59:59.0<NA>201769.172164451612.220168식육포장처리업식육포장처리업0L000
8301000030100001042010000220101123<NA>3폐업2폐업20141121<NA><NA><NA>2234-38730.0<NA>서울특별시 중구 황학동 604번지서울특별시 중구 퇴계로87길 23-5 (황학동)4576경북상회2014-11-21 15:08:58I2018-08-31 23:59:59.0<NA>201769.020969451586.459143식육포장처리업식육포장처리업00000
9301000030100001042010000320101227<NA>3폐업2폐업20140714<NA><NA><NA>2238-44760.0<NA>서울특별시 중구 황학동 603-4번지서울특별시 중구 퇴계로87길 23-7 (황학동)4576창현유통2014-07-14 11:27:06I2018-08-31 23:59:59.0<NA>201763.072485451586.385523식육포장처리업식육포장처리업00000
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
25301000030100001042019000220190517<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 603-3서울특별시 중구 퇴계로87길 23-9 (황학동)4576(주)다온식품2020-09-16 15:08:18U2020-09-18 02:40:00.0<NA>201758.040566451586.279676식육포장처리업식육포장처리업0L000
26301000030100001042020000120200727<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 641서울특별시 중구 퇴계로87길 32, 1층 (황학동)4575제이제이푸드시스템2020-07-27 09:16:33I2020-07-29 00:23:15.0<NA>201797.872285451628.469874식육포장처리업식육포장처리업00000
27301000030100001042020000220201209<NA>1영업/정상0정상<NA><NA><NA><NA>02-2238-5542773.0<NA>서울특별시 중구 황학동 582 지하 1층서울특별시 중구 퇴계로87길 35-3, 지하 1층 (황학동)4576디(THE) 에스아이 트레이딩2020-12-09 14:38:55I2020-12-11 00:23:07.0<NA>201775.537391451638.555518식육포장처리업식육포장처리업00000
28301000030100001042022000120220415<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 627서울특별시 중구 퇴계로87길 17-1, 1층 (황학동)4576신흥상회2022-04-15 18:21:38I2021-12-03 23:07:00.0<NA>201779.001961451556.938504<NA><NA><NA><NA><NA>
29301000030100001042022000220220704<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 400서울특별시 중구 퇴계로87길 23-20, 1층 (황학동)4576한성상회2022-07-29 15:42:33U2021-12-06 21:01:00.0<NA>201711.550895451600.319685<NA><NA><NA><NA><NA>
30301000030100001042022000320220727<NA>1영업/정상0정상<NA><NA><NA><NA>02-2234-38730.0<NA>서울특별시 중구 황학동 581서울특별시 중구 퇴계로87길 35-5, 2층 (황학동)4576경북상회2022-07-27 17:41:35I2021-12-06 22:09:00.0<NA>201756.660329451638.515468<NA><NA><NA><NA><NA>
31301000030100001042022000420220727<NA>1영업/정상0정상<NA><NA><NA><NA>02-2234-38730.0<NA>서울특별시 중구 황학동 581서울특별시 중구 퇴계로87길 35-5, 지하층 (황학동)4576KB푸드2022-07-27 17:35:46I2021-12-06 22:09:00.0<NA>201756.660329451638.515468<NA><NA><NA><NA><NA>
32301000030100001042022000520220906<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 392서울특별시 중구 퇴계로87길 15-22, 1층 (황학동)4576해성상회2022-09-06 13:32:29I2021-12-09 00:08:00.0<NA>201699.4502451574.159101<NA><NA><NA><NA><NA>
33301000030100001042022000620220915<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 중구 황학동 604서울특별시 중구 퇴계로87길 23-5, 1층 (황학동)4576안성유통2022-11-24 14:29:00U2021-10-31 22:06:00.0<NA>201769.020969451586.459143<NA><NA><NA><NA><NA>
3430100003010000104202300012023-01-06<NA>1영업/정상0정상<NA><NA><NA><NA>02-2234-11050.0<NA>서울특별시 중구 장충동1가 119 일산빌딩서울특별시 중구 동호로 238, 일산빌딩 지하4층 (장충동1가)4606(주)호박패밀리 호박라인스2023-08-17 10:34:47U2022-12-07 23:09:00.0<NA>200595.595397450728.433219<NA><NA><NA><NA><NA>