Overview

Dataset statistics

Number of variables30
Number of observations28
Missing cells150
Missing cells (%)17.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory260.7 B

Variable types

Categorical14
Numeric6
DateTime2
Unsupported4
Text4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),축산업무구분명,축산물가공업구분명,축산일련번호,권리주체일련번호,총인원
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18122/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 is highly imbalanced (62.2%)Imbalance
업태구분명 is highly imbalanced (62.8%)Imbalance
축산일련번호 is highly imbalanced (77.8%)Imbalance
총인원 is highly imbalanced (77.8%)Imbalance
인허가취소일자 has 28 (100.0%) missing valuesMissing
폐업일자 has 6 (21.4%) missing valuesMissing
휴업시작일자 has 28 (100.0%) missing valuesMissing
휴업종료일자 has 28 (100.0%) missing valuesMissing
전화번호 has 7 (25.0%) missing valuesMissing
소재지우편번호 has 28 (100.0%) missing valuesMissing
지번주소 has 3 (10.7%) missing valuesMissing
도로명우편번호 has 22 (78.6%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 10 (35.7%) zerosZeros

Reproduction

Analysis started2024-05-11 03:44:03.756427
Analysis finished2024-05-11 03:44:04.691915
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
3200000
28 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 28
100.0%

Length

2024-05-11T03:44:04.909258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:05.237888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 28
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2 × 1017
Minimum3.2 × 1017
Maximum3.2 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:05.649022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2 × 1017
5-th percentile3.2 × 1017
Q13.2 × 1017
median3.2 × 1017
Q33.2 × 1017
95-th percentile3.2 × 1017
Maximum3.2 × 1017
Range280000
Interquartile range (IQR)44992

Descriptive statistics

Standard deviation57081.282
Coefficient of variation (CV)1.7837901 × 10-13
Kurtosis1.4269262
Mean3.2 × 1017
Median Absolute Deviation (MAD)25024
Skewness0.44064593
Sum8.96 × 1018
Variance3.2582727 × 109
MonotonicityStrictly increasing
2024-05-11T03:44:06.079406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
320000000419920001 1
 
3.6%
320000000420060002 1
 
3.6%
320000000420200001 1
 
3.6%
320000000420160002 1
 
3.6%
320000000420160001 1
 
3.6%
320000000420150001 1
 
3.6%
320000000420090003 1
 
3.6%
320000000420090002 1
 
3.6%
320000000420090001 1
 
3.6%
320000000420070003 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
320000000419920001 1
3.6%
320000000419980001 1
3.6%
320000000420010001 1
3.6%
320000000420020001 1
3.6%
320000000420020002 1
3.6%
320000000420020003 1
3.6%
320000000420030001 1
3.6%
320000000420030002 1
3.6%
320000000420030003 1
3.6%
320000000420040001 1
3.6%
ValueCountFrequency (%)
320000000420200001 1
3.6%
320000000420160002 1
3.6%
320000000420160001 1
3.6%
320000000420150001 1
3.6%
320000000420090003 1
3.6%
320000000420090002 1
3.6%
320000000420090001 1
3.6%
320000000420070003 1
3.6%
320000000420070001 1
3.6%
320000000420060005 1
3.6%

인허가일자
Date

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum1992-03-13 00:00:00
Maximum2020-02-19 00:00:00
2024-05-11T03:44:06.627347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:07.012780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
3
22 
1
5 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
3 22
78.6%
1 5
 
17.9%
4 1
 
3.6%

Length

2024-05-11T03:44:07.494841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:07.865668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 22
78.6%
1 5
 
17.9%
4 1
 
3.6%

영업상태명
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
폐업
22 
영업/정상
5 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length2.9642857
Min length2

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
78.6%
영업/정상 5
 
17.9%
취소/말소/만료/정지/중지 1
 
3.6%

Length

2024-05-11T03:44:08.220115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:08.567921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
78.6%
영업/정상 5
 
17.9%
취소/말소/만료/정지/중지 1
 
3.6%

상세영업상태코드
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2
22 
0
5 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
2 22
78.6%
0 5
 
17.9%
4 1
 
3.6%

Length

2024-05-11T03:44:09.058292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:09.472258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 22
78.6%
0 5
 
17.9%
4 1
 
3.6%

상세영업상태명
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
폐업
22 
정상
5 
말소
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
78.6%
정상 5
 
17.9%
말소 1
 
3.6%

Length

2024-05-11T03:44:09.929722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:10.285644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
78.6%
정상 5
 
17.9%
말소 1
 
3.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)100.0%
Missing6
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean20092975
Minimum20030513
Maximum20220303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:10.643921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030513
5-th percentile20031700
Q120060634
median20071074
Q320108099
95-th percentile20199332
Maximum20220303
Range189790
Interquartile range (IQR)47464.75

Descriptive statistics

Standard deviation55733.758
Coefficient of variation (CV)0.0027737933
Kurtosis0.24839795
Mean20092975
Median Absolute Deviation (MAD)20339.5
Skewness1.1573773
Sum4.4204544 × 108
Variance3.1062518 × 109
MonotonicityNot monotonic
2024-05-11T03:44:11.105604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20070703 1
 
3.6%
20220303 1
 
3.6%
20180220 1
 
3.6%
20180821 1
 
3.6%
20140702 1
 
3.6%
20070919 1
 
3.6%
20080108 1
 
3.6%
20061024 1
 
3.6%
20070518 1
 
3.6%
20071029 1
 
3.6%
Other values (12) 12
42.9%
(Missing) 6
21.4%
ValueCountFrequency (%)
20030513 1
3.6%
20031231 1
3.6%
20040605 1
3.6%
20041202 1
3.6%
20060123 1
3.6%
20060504 1
3.6%
20061024 1
3.6%
20070518 1
3.6%
20070703 1
3.6%
20070919 1
3.6%
ValueCountFrequency (%)
20220303 1
3.6%
20200306 1
3.6%
20180821 1
3.6%
20180220 1
3.6%
20140702 1
3.6%
20110531 1
3.6%
20100802 1
3.6%
20081031 1
3.6%
20080108 1
3.6%
20071128 1
3.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

재개업일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
24 
20200306
 
1
20180821
 
1
20180220
 
1
20220303
 
1

Length

Max length8
Median length4
Mean length4.5714286
Min length4

Unique

Unique4 ?
Unique (%)14.3%

Sample

1st row20200306
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 24
85.7%
20200306 1
 
3.6%
20180821 1
 
3.6%
20180220 1
 
3.6%
20220303 1
 
3.6%

Length

2024-05-11T03:44:11.864022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:12.268221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
85.7%
20200306 1
 
3.6%
20180821 1
 
3.6%
20180220 1
 
3.6%
20220303 1
 
3.6%

전화번호
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing7
Missing (%)25.0%
Memory size356.0 B
2024-05-11T03:44:12.809457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.2857143
Min length8

Characters and Unicode

Total characters174
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

Unique17 ?
Unique (%)81.0%

Sample

1st row884-2411
2nd row889-1815
3rd row837-2220
4th row875-9571
5th row883-2090
ValueCountFrequency (%)
871-5900 2
 
9.5%
837-2220 2
 
9.5%
593-8484 1
 
4.8%
884-2411 1
 
4.8%
02-855-2772 1
 
4.8%
864-7490 1
 
4.8%
884-6229 1
 
4.8%
871-6789 1
 
4.8%
888-6556 1
 
4.8%
02-882-1791 1
 
4.8%
Other values (9) 9
42.9%
2024-05-11T03:44:13.983004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 35
20.1%
- 23
13.2%
2 19
10.9%
5 15
8.6%
7 14
 
8.0%
1 14
 
8.0%
0 14
 
8.0%
9 12
 
6.9%
4 10
 
5.7%
6 10
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 151
86.8%
Dash Punctuation 23
 
13.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 35
23.2%
2 19
12.6%
5 15
9.9%
7 14
 
9.3%
1 14
 
9.3%
0 14
 
9.3%
9 12
 
7.9%
4 10
 
6.6%
6 10
 
6.6%
3 8
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 174
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 35
20.1%
- 23
13.2%
2 19
10.9%
5 15
8.6%
7 14
 
8.0%
1 14
 
8.0%
0 14
 
8.0%
9 12
 
6.9%
4 10
 
5.7%
6 10
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 35
20.1%
- 23
13.2%
2 19
10.9%
5 15
8.6%
7 14
 
8.0%
1 14
 
8.0%
0 14
 
8.0%
9 12
 
6.9%
4 10
 
5.7%
6 10
 
5.7%

소재지면적
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.744643
Minimum0
Maximum123.6
Zeros10
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:14.479959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median33.975
Q376.0175
95-th percentile104.287
Maximum123.6
Range123.6
Interquartile range (IQR)76.0175

Descriptive statistics

Standard deviation40.864741
Coefficient of variation (CV)0.95602018
Kurtosis-1.2471152
Mean42.744643
Median Absolute Deviation (MAD)33.975
Skewness0.3980655
Sum1196.85
Variance1669.9271
MonotonicityNot monotonic
2024-05-11T03:44:14.984674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 10
35.7%
95.81 1
 
3.6%
62.85 1
 
3.6%
93.88 1
 
3.6%
17.34 1
 
3.6%
30.6 1
 
3.6%
54.73 1
 
3.6%
26.83 1
 
3.6%
36.8 1
 
3.6%
108.34 1
 
3.6%
Other values (9) 9
32.1%
ValueCountFrequency (%)
0.0 10
35.7%
17.34 1
 
3.6%
26.83 1
 
3.6%
30.6 1
 
3.6%
31.15 1
 
3.6%
36.8 1
 
3.6%
41.04 1
 
3.6%
54.73 1
 
3.6%
59.73 1
 
3.6%
62.85 1
 
3.6%
ValueCountFrequency (%)
123.6 1
3.6%
108.34 1
3.6%
96.76 1
3.6%
95.81 1
3.6%
93.88 1
3.6%
88.0 1
3.6%
85.13 1
3.6%
72.98 1
3.6%
71.28 1
3.6%
62.85 1
3.6%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

지번주소
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing3
Missing (%)10.7%
Memory size356.0 B
2024-05-11T03:44:15.603666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length24.16
Min length21

Characters and Unicode

Total characters604
Distinct characters40
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

Unique25 ?
Unique (%)100.0%

Sample

1st row서울특별시 관악구 봉천동 955-8번지
2nd row서울특별시 관악구 봉천동 704-1번지 당곡시장 2층
3rd row서울특별시 관악구 신림동 524-2번지
4th row서울특별시 관악구 봉천동 932-1번지 지1층
5th row서울특별시 관악구 봉천동 957-46번지
ValueCountFrequency (%)
서울특별시 25
22.7%
관악구 25
22.7%
봉천동 14
12.7%
신림동 11
10.0%
지하1층 3
 
2.7%
1517-8번지 2
 
1.8%
21-25번지 1
 
0.9%
1529-67번지 1
 
0.9%
611-7번지 1
 
0.9%
지층 1
 
0.9%
Other values (26) 26
23.6%
2024-05-11T03:44:16.782704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
17.5%
1 31
 
5.1%
시 26
 
4.3%
동 26
 
4.3%
서 25
 
4.1%
- 25
 
4.1%
특 25
 
4.1%
별 25
 
4.1%
관 25
 
4.1%
악 25
 
4.1%
Other values (30) 265
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
56.6%
Decimal Number 130
 
21.5%
Space Separator 106
 
17.5%
Dash Punctuation 25
 
4.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 26
 
7.6%
동 26
 
7.6%
서 25
 
7.3%
특 25
 
7.3%
별 25
 
7.3%
관 25
 
7.3%
악 25
 
7.3%
구 25
 
7.3%
울 25
 
7.3%
지 25
 
7.3%
Other values (17) 90
26.3%
Decimal Number
ValueCountFrequency (%)
1 31
23.8%
4 15
11.5%
5 15
11.5%
9 13
10.0%
2 12
 
9.2%
7 11
 
8.5%
6 11
 
8.5%
3 8
 
6.2%
8 8
 
6.2%
0 6
 
4.6%
Space Separator
ValueCountFrequency (%)
106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
56.6%
Common 262
43.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 26
 
7.6%
동 26
 
7.6%
서 25
 
7.3%
특 25
 
7.3%
별 25
 
7.3%
관 25
 
7.3%
악 25
 
7.3%
구 25
 
7.3%
울 25
 
7.3%
지 25
 
7.3%
Other values (17) 90
26.3%
Common
ValueCountFrequency (%)
106
40.5%
1 31
 
11.8%
- 25
 
9.5%
4 15
 
5.7%
5 15
 
5.7%
9 13
 
5.0%
2 12
 
4.6%
7 11
 
4.2%
6 11
 
4.2%
3 8
 
3.1%
Other values (3) 15
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
56.6%
ASCII 262
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
40.5%
1 31
 
11.8%
- 25
 
9.5%
4 15
 
5.7%
5 15
 
5.7%
9 13
 
5.0%
2 12
 
4.6%
7 11
 
4.2%
6 11
 
4.2%
3 8
 
3.1%
Other values (3) 15
 
5.7%
Hangul
ValueCountFrequency (%)
시 26
 
7.6%
동 26
 
7.6%
서 25
 
7.3%
특 25
 
7.3%
별 25
 
7.3%
관 25
 
7.3%
악 25
 
7.3%
구 25
 
7.3%
울 25
 
7.3%
지 25
 
7.3%
Other values (17) 90
26.3%

도로명주소
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T03:44:17.493934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length29
Mean length26.571429
Min length21

Characters and Unicode

Total characters744
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row서울특별시 관악구 은천로 9 (봉천동)
2nd row서울특별시 관악구 당곡길 25 (봉천동,당곡시장 2층)
3rd row서울특별시 관악구 남부순환로151길 63 (신림동)
4th row서울특별시 관악구 봉천로31길 6 (봉천동,지1층)
5th row서울특별시 관악구 봉천로 319 (봉천동)
ValueCountFrequency (%)
서울특별시 28
19.2%
관악구 28
19.2%
신림동 11
 
7.5%
봉천동 9
 
6.2%
75 3
 
2.1%
봉천동,지하1층 3
 
2.1%
봉천로31길 2
 
1.4%
지하1층 2
 
1.4%
9 2
 
1.4%
양녕로6길 2
 
1.4%
Other values (49) 56
38.4%
2024-05-11T03:44:18.590522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
15.9%
관 30
 
4.0%
악 30
 
4.0%
동 29
 
3.9%
시 29
 
3.9%
서 28
 
3.8%
구 28
 
3.8%
( 28
 
3.8%
울 28
 
3.8%
별 28
 
3.8%
Other values (56) 368
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
60.9%
Space Separator 118
 
15.9%
Decimal Number 99
 
13.3%
Open Punctuation 28
 
3.8%
Close Punctuation 28
 
3.8%
Other Punctuation 14
 
1.9%
Dash Punctuation 3
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 30
 
6.6%
악 30
 
6.6%
동 29
 
6.4%
시 29
 
6.4%
서 28
 
6.2%
구 28
 
6.2%
울 28
 
6.2%
별 28
 
6.2%
특 28
 
6.2%
로 23
 
5.1%
Other values (40) 172
38.0%
Decimal Number
ValueCountFrequency (%)
1 26
26.3%
3 14
14.1%
6 12
12.1%
5 11
11.1%
2 10
 
10.1%
4 7
 
7.1%
8 6
 
6.1%
0 6
 
6.1%
7 4
 
4.0%
9 3
 
3.0%
Space Separator
ValueCountFrequency (%)
118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
60.9%
Common 291
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 30
 
6.6%
악 30
 
6.6%
동 29
 
6.4%
시 29
 
6.4%
서 28
 
6.2%
구 28
 
6.2%
울 28
 
6.2%
별 28
 
6.2%
특 28
 
6.2%
로 23
 
5.1%
Other values (40) 172
38.0%
Common
ValueCountFrequency (%)
118
40.5%
( 28
 
9.6%
) 28
 
9.6%
1 26
 
8.9%
, 14
 
4.8%
3 14
 
4.8%
6 12
 
4.1%
5 11
 
3.8%
2 10
 
3.4%
4 7
 
2.4%
Other values (6) 23
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
60.9%
ASCII 291
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
40.5%
( 28
 
9.6%
) 28
 
9.6%
1 26
 
8.9%
, 14
 
4.8%
3 14
 
4.8%
6 12
 
4.1%
5 11
 
3.8%
2 10
 
3.4%
4 7
 
2.4%
Other values (6) 23
 
7.9%
Hangul
ValueCountFrequency (%)
관 30
 
6.6%
악 30
 
6.6%
동 29
 
6.4%
시 29
 
6.4%
서 28
 
6.2%
구 28
 
6.2%
울 28
 
6.2%
별 28
 
6.2%
특 28
 
6.2%
로 23
 
5.1%
Other values (40) 172
38.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing22
Missing (%)78.6%
Infinite0
Infinite (%)0.0%
Mean8768.8333
Minimum8706
Maximum8865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:19.028728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8706
5-th percentile8709.25
Q18721
median8735.5
Q38825
95-th percentile8861.75
Maximum8865
Range159
Interquartile range (IQR)104

Descriptive statistics

Standard deviation70.658097
Coefficient of variation (CV)0.0080578675
Kurtosis-1.7969889
Mean8768.8333
Median Absolute Deviation (MAD)23
Skewness0.85403345
Sum52613
Variance4992.5667
MonotonicityNot monotonic
2024-05-11T03:44:19.489108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
8719 1
 
3.6%
8727 1
 
3.6%
8865 1
 
3.6%
8852 1
 
3.6%
8706 1
 
3.6%
8744 1
 
3.6%
(Missing) 22
78.6%
ValueCountFrequency (%)
8706 1
3.6%
8719 1
3.6%
8727 1
3.6%
8744 1
3.6%
8852 1
3.6%
8865 1
3.6%
ValueCountFrequency (%)
8865 1
3.6%
8852 1
3.6%
8744 1
3.6%
8727 1
3.6%
8719 1
3.6%
8706 1
3.6%

사업장명
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T03:44:20.178737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length5.5357143
Min length2

Characters and Unicode

Total characters155
Distinct characters89
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row동림식품
2nd row승필유통
3rd row나이스푸드
4th row부림푸드
5th row동현통상
ValueCountFrequency (%)
나이스푸드 2
 
6.5%
관악소상공인축산협동조합(우가유통 1
 
3.2%
하진산업 1
 
3.2%
푸른들p&b 1
 
3.2%
청하유통 1
 
3.2%
달인족발 1
 
3.2%
문영순 1
 
3.2%
영송혜물산 1
 
3.2%
중앙푸드시시템 1
 
3.2%
펠리치따 1
 
3.2%
Other values (20) 20
64.5%
2024-05-11T03:44:21.530936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
푸 7
 
4.5%
통 6
 
3.9%
드 6
 
3.9%
유 5
 
3.2%
동 4
 
2.6%
산 4
 
2.6%
이 3
 
1.9%
진 3
 
1.9%
인 3
 
1.9%
리 3
 
1.9%
Other values (79) 111
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145
93.5%
Space Separator 3
 
1.9%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%
Uppercase Letter 2
 
1.3%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
푸 7
 
4.8%
통 6
 
4.1%
드 6
 
4.1%
유 5
 
3.4%
동 4
 
2.8%
산 4
 
2.8%
이 3
 
2.1%
진 3
 
2.1%
인 3
 
2.1%
리 3
 
2.1%
Other values (73) 101
69.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
93.5%
Common 8
 
5.2%
Latin 2
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
푸 7
 
4.8%
통 6
 
4.1%
드 6
 
4.1%
유 5
 
3.4%
동 4
 
2.8%
산 4
 
2.8%
이 3
 
2.1%
진 3
 
2.1%
인 3
 
2.1%
리 3
 
2.1%
Other values (73) 101
69.7%
Common
ValueCountFrequency (%)
3
37.5%
( 2
25.0%
) 2
25.0%
& 1
 
12.5%
Latin
ValueCountFrequency (%)
B 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145
93.5%
ASCII 10
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
푸 7
 
4.8%
통 6
 
4.1%
드 6
 
4.1%
유 5
 
3.4%
동 4
 
2.8%
산 4
 
2.8%
이 3
 
2.1%
진 3
 
2.1%
인 3
 
2.1%
리 3
 
2.1%
Other values (73) 101
69.7%
ASCII
ValueCountFrequency (%)
3
30.0%
( 2
20.0%
) 2
20.0%
& 1
 
10.0%
B 1
 
10.0%
P 1
 
10.0%

최종수정일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2003-05-14 09:44:55
Maximum2023-02-13 13:26:15
2024-05-11T03:44:22.144949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:22.631827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

데이터갱신구분
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
I
21 
U
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 21
75.0%
U 7
 
25.0%

Length

2024-05-11T03:44:23.224987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:23.627511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 21
75.0%
u 7
 
25.0%

데이터갱신일자
Categorical

Distinct7
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2018-08-31 23:59:59.0
21 
2021-11-02 00:01:00.0
 
2
2020-03-08 02:40:00.0
 
1
2021-12-08 00:07:00.0
 
1
2021-12-06 00:08:00.0
 
1
Other values (2)
 
2

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique5 ?
Unique (%)17.9%

Sample

1st row2020-03-08 02:40:00.0
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 21
75.0%
2021-11-02 00:01:00.0 2
 
7.1%
2020-03-08 02:40:00.0 1
 
3.6%
2021-12-08 00:07:00.0 1
 
3.6%
2021-12-06 00:08:00.0 1
 
3.6%
2022-12-04 22:06:00.0 1
 
3.6%
2022-03-05 02:40:00.0 1
 
3.6%

Length

2024-05-11T03:44:23.956605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:24.468895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 21
37.5%
23:59:59.0 21
37.5%
2021-11-02 2
 
3.6%
00:01:00.0 2
 
3.6%
02:40:00.0 2
 
3.6%
2020-03-08 1
 
1.8%
2021-12-08 1
 
1.8%
00:07:00.0 1
 
1.8%
2021-12-06 1
 
1.8%
00:08:00.0 1
 
1.8%
Other values (3) 3
 
5.4%

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
식육가공업
25 
유가공업
 
2
알가공업
 
1

Length

Max length5
Median length5
Mean length4.8928571
Min length4

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 25
89.3%
유가공업 2
 
7.1%
알가공업 1
 
3.6%

Length

2024-05-11T03:44:25.240047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:26.123337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 25
89.3%
유가공업 2
 
7.1%
알가공업 1
 
3.6%

좌표정보(X)
Real number (ℝ)

Distinct25
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194174.46
Minimum191128.31
Maximum196653.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:26.919947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191128.31
5-th percentile192215.94
Q1192829.34
median194266.7
Q3195574.06
95-th percentile196474.01
Maximum196653.72
Range5525.4095
Interquartile range (IQR)2744.7216

Descriptive statistics

Standard deviation1499.1538
Coefficient of variation (CV)0.007720654
Kurtosis-0.86145538
Mean194174.46
Median Absolute Deviation (MAD)1370.5737
Skewness-0.055487851
Sum5436884.9
Variance2247462.2
MonotonicityNot monotonic
2024-05-11T03:44:27.663605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
195574.058979405 2
 
7.1%
192829.337382373 2
 
7.1%
196653.718247243 2
 
7.1%
194303.129719451 1
 
3.6%
194020.771233224 1
 
3.6%
195818.375707958 1
 
3.6%
194403.690313353 1
 
3.6%
192334.409097688 1
 
3.6%
192619.386252366 1
 
3.6%
196140.260379618 1
 
3.6%
Other values (15) 15
53.6%
ValueCountFrequency (%)
191128.308770063 1
3.6%
192152.154579587 1
3.6%
192334.409097688 1
3.6%
192385.909059469 1
3.6%
192401.353217655 1
3.6%
192619.386252366 1
3.6%
192829.337382373 2
7.1%
193199.495141371 1
3.6%
193537.537979405 1
3.6%
193621.578820594 1
3.6%
ValueCountFrequency (%)
196653.718247243 2
7.1%
196140.260379618 1
3.6%
196113.094849269 1
3.6%
195818.375707958 1
3.6%
195700.496821353 1
3.6%
195574.058979405 2
7.1%
194762.666316633 1
3.6%
194732.805902735 1
3.6%
194675.913292608 1
3.6%
194403.690313353 1
3.6%

좌표정보(Y)
Real number (ℝ)

Distinct25
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442175.35
Minimum440853.28
Maximum443130.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T03:44:28.342076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440853.28
5-th percentile441115.95
Q1441783.31
median442389.49
Q3442605.02
95-th percentile442982.2
Maximum443130.61
Range2277.3267
Interquartile range (IQR)821.70936

Descriptive statistics

Standard deviation610.43214
Coefficient of variation (CV)0.0013805205
Kurtosis-0.50038095
Mean442175.35
Median Absolute Deviation (MAD)423.9437
Skewness-0.55025088
Sum12380910
Variance372627.4
MonotonicityNot monotonic
2024-05-11T03:44:29.227517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
442389.487116945 2
 
7.1%
441346.648938961 2
 
7.1%
441783.313825707 2
 
7.1%
442701.32983155 1
 
3.6%
441043.782645398 1
 
3.6%
442641.385577331 1
 
3.6%
442592.902385055 1
 
3.6%
441249.980766361 1
 
3.6%
442988.196037338 1
 
3.6%
442971.065859133 1
 
3.6%
Other values (15) 15
53.6%
ValueCountFrequency (%)
440853.280867814 1
3.6%
441043.782645398 1
3.6%
441249.980766361 1
3.6%
441346.648938961 2
7.1%
441731.215618968 1
3.6%
441783.313825707 2
7.1%
441905.023214971 1
3.6%
441927.092401282 1
3.6%
441998.263546442 1
3.6%
442018.522632073 1
3.6%
ValueCountFrequency (%)
443130.607614887 1
3.6%
442988.196037338 1
3.6%
442971.065859133 1
3.6%
442846.150949029 1
3.6%
442701.32983155 1
3.6%
442655.253687619 1
3.6%
442641.385577331 1
3.6%
442592.902385055 1
3.6%
442518.099074716 1
3.6%
442497.764655945 1
3.6%

축산업무구분명
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
축산물가공업
23 
<NA>
5 

Length

Max length6
Median length6
Mean length5.6428571
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 23
82.1%
<NA> 5
 
17.9%

Length

2024-05-11T03:44:29.711514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:30.057527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 23
82.1%
na 5
 
17.9%

축산물가공업구분명
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
식육가공업
21 
<NA>
5 
유가공업
 
1
알가공업
 
1

Length

Max length5
Median length5
Mean length4.75
Min length4

Unique

Unique2 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
식육가공업 21
75.0%
<NA> 5
 
17.9%
유가공업 1
 
3.6%
알가공업 1
 
3.6%

Length

2024-05-11T03:44:30.426302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:30.767239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 21
75.0%
na 5
 
17.9%
유가공업 1
 
3.6%
알가공업 1
 
3.6%

축산일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
27 
0
 
1

Length

Max length4
Median length4
Mean length3.8928571
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
96.4%
0 1
 
3.6%

Length

2024-05-11T03:44:31.138466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:31.530751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
96.4%
0 1
 
3.6%

권리주체일련번호
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
000
20 
<NA>
5 
L00
3 

Length

Max length4
Median length3
Mean length3.1785714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 20
71.4%
<NA> 5
 
17.9%
L00 3
 
10.7%

Length

2024-05-11T03:44:31.923740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:32.359659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 20
71.4%
na 5
 
17.9%
l00 3
 
10.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
27 
0
 
1

Length

Max length4
Median length4
Mean length3.8928571
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
96.4%
0 1
 
3.6%

Length

2024-05-11T03:44:32.757099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:33.083260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
96.4%
0 1
 
3.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0320000032000000041992000119920313<NA>3폐업2폐업20200306<NA><NA>20200306884-241195.81<NA>서울특별시 관악구 봉천동 955-8번지서울특별시 관악구 은천로 9 (봉천동)8719동림식품2020-03-06 11:13:52U2020-03-08 02:40:00.0식육가공업194303.129719442701.329832축산물가공업식육가공업<NA>000<NA>
1320000032000000041998000119980729<NA>3폐업2폐업20071120<NA><NA><NA>889-18150.0<NA>서울특별시 관악구 봉천동 704-1번지 당곡시장 2층서울특별시 관악구 당곡길 25 (봉천동,당곡시장 2층)<NA>승필유통2007-11-20 17:20:06I2018-08-31 23:59:59.0식육가공업193621.578821443130.607615축산물가공업식육가공업<NA>000<NA>
2320000032000000042001000120010402<NA>3폐업2폐업20031231<NA><NA><NA>837-222059.73<NA>서울특별시 관악구 신림동 524-2번지서울특별시 관악구 남부순환로151길 63 (신림동)<NA>나이스푸드2003-12-31 14:28:23I2018-08-31 23:59:59.0식육가공업192401.353218442447.902966축산물가공업식육가공업<NA>000<NA>
3320000032000000042002000120020821<NA>3폐업2폐업20110531<NA><NA><NA>875-957185.13<NA>서울특별시 관악구 봉천동 932-1번지 지1층서울특별시 관악구 봉천로31길 6 (봉천동,지1층)<NA>부림푸드2011-06-01 09:22:25I2018-08-31 23:59:59.0식육가공업194762.666317442428.312037축산물가공업식육가공업<NA>000<NA>
4320000032000000042002000220020117<NA>3폐업2폐업20041202<NA><NA><NA>883-209096.76<NA>서울특별시 관악구 봉천동 957-46번지서울특별시 관악구 봉천로 319 (봉천동)<NA>동현통상2004-12-02 11:55:43I2018-08-31 23:59:59.0식육가공업194289.731067442655.253688축산물가공업식육가공업<NA>000<NA>
5320000032000000042002000320020816<NA>3폐업2폐업20030513<NA><NA><NA>854-1473123.6<NA>서울특별시 관악구 신림동 1476-10번지서울특별시 관악구 난곡로 285-1 (신림동)<NA>경북육가공2003-05-14 09:44:55I2018-08-31 23:59:59.0식육가공업192385.909059441927.092401축산물가공업식육가공업<NA>000<NA>
6320000032000000042003000120030217<NA>3폐업2폐업20060504<NA><NA><NA>882-245641.04<NA>서울특별시 관악구 신림동 92-275번지서울특별시 관악구 신림로 232 (신림동)<NA>신수유통2006-05-04 09:53:06I2018-08-31 23:59:59.0식육가공업194243.677304441731.215619축산물가공업식육가공업<NA>000<NA>
7320000032000000042003000220030217<NA>3폐업2폐업20040605<NA><NA><NA>861-019571.28<NA>서울특별시 관악구 신림동 1604-35번지서울특별시 관악구 신원로 9 (신림동)<NA>코리아푸드뱅크2004-06-05 15:01:49I2018-08-31 23:59:59.0식육가공업193537.537979442018.522632축산물가공업식육가공업<NA>000<NA>
8320000032000000042003000320030218<NA>3폐업2폐업20081031<NA><NA><NA>886-923372.98<NA>서울특별시 관악구 신림동 10-518번지서울특별시 관악구 남부순환로 1660 (신림동)<NA>강강술래 신림본동점2008-10-31 17:27:51I2018-08-31 23:59:59.0식육가공업194185.896993442487.424654축산물가공업식육가공업<NA>L00<NA>
9320000032000000042004000120040712<NA>3폐업2폐업20071128<NA><NA><NA>837-222031.15<NA>서울특별시 관악구 신림동 646-399번지서울특별시 관악구 난곡로26길 75 (신림동)<NA>나이스푸드2007-11-28 20:07:51I2018-08-31 23:59:59.0식육가공업193199.495141440853.280868축산물가공업식육가공업<NA>000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
18320000032000000042006000520060908<NA>3폐업2폐업20080108<NA><NA><NA>864-749093.88<NA>서울특별시 관악구 신림동 611-7번지 지층서울특별시 관악구 법원단지길 38 (신림동,지층)<NA>청송2008-01-08 19:23:23I2018-08-31 23:59:59.0식육가공업192829.337382441346.648939축산물가공업식육가공업<NA>000<NA>
19320000032000000042007000120070430<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 관악구 봉천동 1689-9 지하1층서울특별시 관악구 솔밭로 8 (봉천동,지하1층)<NA>우진코리아2022-08-05 13:27:11U2021-12-08 00:07:00.0식육가공업196653.718247441783.313826<NA><NA><NA><NA><NA>
20320000032000000042007000320070531<NA>3폐업2폐업20070919<NA><NA><NA>871-59000.0<NA>서울특별시 관악구 봉천동 1517-8번지서울특별시 관악구 양녕로6길 75 (봉천동)<NA>중앙제분2007-09-19 13:37:37I2018-08-31 23:59:59.0식육가공업195574.058979442389.487117축산물가공업식육가공업<NA>000<NA>
21320000032000000042009000120090409<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 관악구 봉천동 7-312 동아타운21서울특별시 관악구 관악로37길 15, 비02호~비06호 (봉천동, 동아타운21)8727주식회사 펠리치따2022-06-03 16:35:02U2021-12-06 00:08:00.0유가공업196140.26038442971.065859<NA><NA><NA><NA><NA>
22320000032000000042009000220090921<NA>3폐업2폐업20140702<NA><NA><NA>871-59000.0<NA>서울특별시 관악구 봉천동 1517-8번지 지하1층,서울특별시 관악구 양녕로6길 75 (봉천동,지하1층,)<NA>중앙푸드시시템2014-07-02 13:46:39I2018-08-31 23:59:59.0식육가공업195574.058979442389.487117축산물가공업식육가공업<NA>000<NA>
23320000032000000042009000320091118<NA>1영업/정상0정상<NA><NA><NA><NA>867-258862.85<NA>서울특별시 관악구 신림동 475-41 영송빌딩서울특별시 관악구 신사로 140-1 (신림동,영송빌딩)<NA>영송혜물산2022-11-29 10:40:48U2021-11-02 00:01:00.0식육가공업192619.386252442988.196037<NA><NA><NA><NA><NA>
24320000032000000042015000120150410<NA>3폐업2폐업20180821<NA><NA>20180821<NA>0.0<NA><NA>서울특별시 관악구 미성5길 40 (신림동)8865문영순 달인족발2018-08-21 15:51:06I2018-08-31 23:59:59.0식육가공업192334.409098441249.980766축산물가공업식육가공업<NA>000<NA>
25320000032000000042016000120160520<NA>3폐업2폐업20180220<NA><NA>20180220<NA>0.0<NA><NA>서울특별시 관악구 법원단지길 38, 지하1층 (신림동)8852청하유통2018-02-20 16:10:04I2018-08-31 23:59:59.0식육가공업192829.337382441346.648939축산물가공업식육가공업<NA>000<NA>
2632000003200000004201600022016-08-17<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA><NA>서울특별시 관악구 봉천로 331-1, 지하1층 (신림동)8706푸른들P&B2023-02-13 13:26:15U2022-12-04 22:06:00.0식육가공업194403.690313442592.902385<NA><NA><NA><NA><NA>
27320000032000000042020000120200219<NA>3폐업2폐업20220303<NA><NA>20220303<NA>0.0<NA>서울특별시 관악구 봉천동 41-848서울특별시 관악구 은천로 166, 지1층 (봉천동)8744로이푸드시스템2022-03-03 13:38:50U2022-03-05 02:40:00.0식육가공업195818.375708442641.385577축산물가공업식육가공업00000