Overview

Dataset statistics

Number of variables30
Number of observations29
Missing cells257
Missing cells (%)29.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory261.6 B

Variable types

Categorical10
Numeric6
DateTime2
Unsupported8
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18137/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 29 (100.0%) missing valuesMissing
폐업일자 has 4 (13.8%) missing valuesMissing
휴업시작일자 has 29 (100.0%) missing valuesMissing
휴업종료일자 has 29 (100.0%) missing valuesMissing
재개업일자 has 29 (100.0%) missing valuesMissing
전화번호 has 9 (31.0%) missing valuesMissing
소재지우편번호 has 29 (100.0%) missing valuesMissing
도로명우편번호 has 12 (41.4%) missing valuesMissing
업태구분명 has 29 (100.0%) missing valuesMissing
축산일련번호 has 29 (100.0%) missing valuesMissing
총인원 has 29 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 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
축산일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 17 (58.6%) zerosZeros

Reproduction

Analysis started2024-05-11 08:21:38.249925
Analysis finished2024-05-11 08:21:38.924837
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
3100000
29 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 29
100.0%

Length

2024-05-11T08:21:39.215247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:39.537546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 29
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1000001 × 1017
Minimum3.1 × 1017
Maximum3.1000001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:39.903474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1 × 1017
5-th percentile3.1 × 1017
Q13.1 × 1017
median3.1000001 × 1017
Q33.1000001 × 1017
95-th percentile3.1000001 × 1017
Maximum3.1000001 × 1017
Range1.000018 × 1010
Interquartile range (IQR)1.000007 × 1010

Descriptive statistics

Standard deviation5.0612422 × 109
Coefficient of variation (CV)1.6326587 × 10-8
Kurtosis-2.102071
Mean3.1000001 × 1017
Median Absolute Deviation (MAD)49984
Skewness-0.21953506
Sum8.9900002 × 1018
Variance2.5616173 × 1019
MonotonicityStrictly increasing
2024-05-11T08:21:40.359783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
310000000420000001 1
 
3.4%
310000000420030004 1
 
3.4%
310000010420180001 1
 
3.4%
310000010420150002 1
 
3.4%
310000010420150001 1
 
3.4%
310000010420140004 1
 
3.4%
310000010420140003 1
 
3.4%
310000010420140002 1
 
3.4%
310000010420140001 1
 
3.4%
310000010420130004 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
310000000420000001 1
3.4%
310000000420030004 1
3.4%
310000000420040004 1
3.4%
310000000420040005 1
3.4%
310000000420050004 1
3.4%
310000000420050005 1
3.4%
310000000420050007 1
3.4%
310000000420060001 1
3.4%
310000000420060002 1
3.4%
310000000420060004 1
3.4%
ValueCountFrequency (%)
310000010420180001 1
3.4%
310000010420150002 1
3.4%
310000010420150001 1
3.4%
310000010420140004 1
3.4%
310000010420140003 1
3.4%
310000010420140002 1
3.4%
310000010420140001 1
3.4%
310000010420130004 1
3.4%
310000010420130003 1
3.4%
310000010420130002 1
3.4%

인허가일자
Date

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2000-09-19 00:00:00
Maximum2018-04-10 00:00:00
2024-05-11T08:21:40.728893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:21:41.120231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
3
25 
1
4 

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 25
86.2%
1 4
 
13.8%

Length

2024-05-11T08:21:41.540909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:41.866644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 25
86.2%
1 4
 
13.8%

영업상태명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
폐업
25 
영업/정상
4 

Length

Max length5
Median length2
Mean length2.4137931
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 25
86.2%
영업/정상 4
 
13.8%

Length

2024-05-11T08:21:42.245361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:42.523036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 25
86.2%
영업/정상 4
 
13.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
2
25 
0
4 

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 25
86.2%
0 4
 
13.8%

Length

2024-05-11T08:21:42.870975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:43.191485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 25
86.2%
0 4
 
13.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
폐업
25 
정상
4 

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 25
86.2%
정상 4
 
13.8%

Length

2024-05-11T08:21:43.537148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:43.888171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 25
86.2%
정상 4
 
13.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)100.0%
Missing4
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean20138661
Minimum20041223
Maximum20221229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:44.163095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20041223
5-th percentile20060340
Q120121211
median20150217
Q320170912
95-th percentile20198691
Maximum20221229
Range180006
Interquartile range (IQR)49701

Descriptive statistics

Standard deviation48572.322
Coefficient of variation (CV)0.0024118944
Kurtosis-0.34743818
Mean20138661
Median Absolute Deviation (MAD)21010
Skewness-0.66551774
Sum5.0346652 × 108
Variance2.3592705 × 109
MonotonicityNot monotonic
2024-05-11T08:21:44.524880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
20150603 1
 
3.4%
20200731 1
 
3.4%
20181114 1
 
3.4%
20180630 1
 
3.4%
20170912 1
 
3.4%
20190531 1
 
3.4%
20150210 1
 
3.4%
20140304 1
 
3.4%
20171227 1
 
3.4%
20170224 1
 
3.4%
Other values (15) 15
51.7%
(Missing) 4
 
13.8%
ValueCountFrequency (%)
20041223 1
3.4%
20060322 1
3.4%
20060410 1
3.4%
20060607 1
3.4%
20061114 1
3.4%
20100628 1
3.4%
20121211 1
3.4%
20140205 1
3.4%
20140304 1
3.4%
20140403 1
3.4%
ValueCountFrequency (%)
20221229 1
3.4%
20200731 1
3.4%
20190531 1
3.4%
20181114 1
3.4%
20180630 1
3.4%
20171227 1
3.4%
20170912 1
3.4%
20170224 1
3.4%
20151222 1
3.4%
20150629 1
3.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

전화번호
Text

MISSING 

Distinct18
Distinct (%)90.0%
Missing9
Missing (%)31.0%
Memory size364.0 B
2024-05-11T08:21:44.942605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.65
Min length8

Characters and Unicode

Total characters173
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 (%)80.0%

Sample

1st row3392-5277
2nd row952-9595
3rd row978-4690
4th row937-8169
5th row02-972-5252
ValueCountFrequency (%)
939-2155 2
 
10.0%
937-5500 2
 
10.0%
02-495-6720 1
 
5.0%
070-7671-1227 1
 
5.0%
971-3633 1
 
5.0%
975-3642 1
 
5.0%
990-6860 1
 
5.0%
937-3334 1
 
5.0%
3392-5277 1
 
5.0%
978-1503 1
 
5.0%
Other values (8) 8
40.0%
2024-05-11T08:21:45.715793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 27
15.6%
- 23
13.3%
3 22
12.7%
7 19
11.0%
2 18
10.4%
5 18
10.4%
0 16
9.2%
1 9
 
5.2%
6 9
 
5.2%
8 6
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
86.7%
Dash Punctuation 23
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 27
18.0%
3 22
14.7%
7 19
12.7%
2 18
12.0%
5 18
12.0%
0 16
10.7%
1 9
 
6.0%
6 9
 
6.0%
8 6
 
4.0%
4 6
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 27
15.6%
- 23
13.3%
3 22
12.7%
7 19
11.0%
2 18
10.4%
5 18
10.4%
0 16
9.2%
1 9
 
5.2%
6 9
 
5.2%
8 6
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 27
15.6%
- 23
13.3%
3 22
12.7%
7 19
11.0%
2 18
10.4%
5 18
10.4%
0 16
9.2%
1 9
 
5.2%
6 9
 
5.2%
8 6
 
3.5%

소재지면적
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.644483
Minimum0
Maximum237
Zeros17
Zeros (%)58.6%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:46.032445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q388.3
95-th percentile211.876
Maximum237
Range237
Interquartile range (IQR)88.3

Descriptive statistics

Standard deviation74.505138
Coefficient of variation (CV)1.4426544
Kurtosis0.71044681
Mean51.644483
Median Absolute Deviation (MAD)0
Skewness1.3174541
Sum1497.69
Variance5551.0156
MonotonicityNot monotonic
2024-05-11T08:21:46.414934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 17
58.6%
88.3 1
 
3.4%
230.46 1
 
3.4%
96.0 1
 
3.4%
56.0 1
 
3.4%
159.28 1
 
3.4%
135.85 1
 
3.4%
184.0 1
 
3.4%
86.0 1
 
3.4%
44.9 1
 
3.4%
Other values (3) 3
 
10.3%
ValueCountFrequency (%)
0.0 17
58.6%
44.9 1
 
3.4%
56.0 1
 
3.4%
84.0 1
 
3.4%
86.0 1
 
3.4%
88.3 1
 
3.4%
95.9 1
 
3.4%
96.0 1
 
3.4%
135.85 1
 
3.4%
159.28 1
 
3.4%
ValueCountFrequency (%)
237.0 1
3.4%
230.46 1
3.4%
184.0 1
3.4%
159.28 1
3.4%
135.85 1
3.4%
96.0 1
3.4%
95.9 1
3.4%
88.3 1
3.4%
86.0 1
3.4%
84.0 1
3.4%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

지번주소
Text

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T08:21:46.926908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length23.827586
Min length17

Characters and Unicode

Total characters691
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)79.3%

Sample

1st row서울특별시 노원구 상계동 399-2번지 지하1층
2nd row서울특별시 노원구 상계동 95-3번지 상계시장내
3rd row서울특별시 노원구 하계동 276-1번지
4th row서울특별시 노원구 상계동 389-555번지
5th row서울특별시 노원구 공릉동 351-2
ValueCountFrequency (%)
서울특별시 29
22.8%
노원구 29
22.8%
상계동 15
11.8%
공릉동 6
 
4.7%
중계동 4
 
3.1%
43-15번지 2
 
1.6%
하계동 2
 
1.6%
월계동 2
 
1.6%
84-7번지 2
 
1.6%
지하1층 2
 
1.6%
Other values (33) 34
26.8%
2024-05-11T08:21:48.124513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
17.5%
시 30
 
4.3%
서 29
 
4.2%
원 29
 
4.2%
동 29
 
4.2%
구 29
 
4.2%
울 29
 
4.2%
노 29
 
4.2%
별 29
 
4.2%
특 29
 
4.2%
Other values (38) 308
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 402
58.2%
Decimal Number 140
 
20.3%
Space Separator 121
 
17.5%
Dash Punctuation 26
 
3.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
 
7.5%
서 29
 
7.2%
원 29
 
7.2%
동 29
 
7.2%
구 29
 
7.2%
울 29
 
7.2%
노 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 26
 
6.5%
Other values (24) 114
28.4%
Decimal Number
ValueCountFrequency (%)
1 27
19.3%
3 18
12.9%
5 15
10.7%
0 14
10.0%
7 14
10.0%
2 14
10.0%
8 13
9.3%
4 13
9.3%
9 8
 
5.7%
6 4
 
2.9%
Space Separator
ValueCountFrequency (%)
121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 402
58.2%
Common 289
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
 
7.5%
서 29
 
7.2%
원 29
 
7.2%
동 29
 
7.2%
구 29
 
7.2%
울 29
 
7.2%
노 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 26
 
6.5%
Other values (24) 114
28.4%
Common
ValueCountFrequency (%)
121
41.9%
1 27
 
9.3%
- 26
 
9.0%
3 18
 
6.2%
5 15
 
5.2%
0 14
 
4.8%
7 14
 
4.8%
2 14
 
4.8%
8 13
 
4.5%
4 13
 
4.5%
Other values (4) 14
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 402
58.2%
ASCII 289
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
41.9%
1 27
 
9.3%
- 26
 
9.0%
3 18
 
6.2%
5 15
 
5.2%
0 14
 
4.8%
7 14
 
4.8%
2 14
 
4.8%
8 13
 
4.5%
4 13
 
4.5%
Other values (4) 14
 
4.8%
Hangul
ValueCountFrequency (%)
시 30
 
7.5%
서 29
 
7.2%
원 29
 
7.2%
동 29
 
7.2%
구 29
 
7.2%
울 29
 
7.2%
노 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 26
 
6.5%
Other values (24) 114
28.4%

도로명주소
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T08:21:48.767672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length28.551724
Min length23

Characters and Unicode

Total characters828
Distinct characters76
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row서울특별시 노원구 노원로 475 (상계동,지하1층)
2nd row서울특별시 노원구 덕릉로102길 5 (상계동,상계시장내)
3rd row서울특별시 노원구 공릉로59가길 9 (하계동)
4th row서울특별시 노원구 상계로17길 20 (상계동)
5th row서울특별시 노원구 공릉로39길 11 (공릉동, 주완위즈빌)
ValueCountFrequency (%)
서울특별시 29
18.6%
노원구 29
18.6%
상계동 11
 
7.1%
공릉동 5
 
3.2%
중계동 4
 
2.6%
1층 3
 
1.9%
하계동 2
 
1.3%
19 2
 
1.3%
139 2
 
1.3%
노원로26길 2
 
1.3%
Other values (59) 67
42.9%
2024-05-11T08:21:49.854532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
15.3%
1 38
 
4.6%
동 35
 
4.2%
노 33
 
4.0%
원 33
 
4.0%
계 31
 
3.7%
) 30
 
3.6%
시 30
 
3.6%
( 30
 
3.6%
서 29
 
3.5%
Other values (66) 412
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
58.3%
Decimal Number 137
 
16.5%
Space Separator 127
 
15.3%
Close Punctuation 30
 
3.6%
Open Punctuation 30
 
3.6%
Other Punctuation 14
 
1.7%
Dash Punctuation 6
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 35
 
7.2%
노 33
 
6.8%
원 33
 
6.8%
계 31
 
6.4%
시 30
 
6.2%
서 29
 
6.0%
로 29
 
6.0%
구 29
 
6.0%
별 29
 
6.0%
특 29
 
6.0%
Other values (50) 176
36.4%
Decimal Number
ValueCountFrequency (%)
1 38
27.7%
2 21
15.3%
3 12
 
8.8%
4 12
 
8.8%
5 11
 
8.0%
9 10
 
7.3%
7 10
 
7.3%
6 9
 
6.6%
8 7
 
5.1%
0 7
 
5.1%
Space Separator
ValueCountFrequency (%)
127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
58.3%
Common 344
41.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 35
 
7.2%
노 33
 
6.8%
원 33
 
6.8%
계 31
 
6.4%
시 30
 
6.2%
서 29
 
6.0%
로 29
 
6.0%
구 29
 
6.0%
별 29
 
6.0%
특 29
 
6.0%
Other values (50) 176
36.4%
Common
ValueCountFrequency (%)
127
36.9%
1 38
 
11.0%
) 30
 
8.7%
( 30
 
8.7%
2 21
 
6.1%
, 14
 
4.1%
3 12
 
3.5%
4 12
 
3.5%
5 11
 
3.2%
9 10
 
2.9%
Other values (5) 39
 
11.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
58.3%
ASCII 345
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
36.8%
1 38
 
11.0%
) 30
 
8.7%
( 30
 
8.7%
2 21
 
6.1%
, 14
 
4.1%
3 12
 
3.5%
4 12
 
3.5%
5 11
 
3.2%
9 10
 
2.9%
Other values (6) 40
 
11.6%
Hangul
ValueCountFrequency (%)
동 35
 
7.2%
노 33
 
6.8%
원 33
 
6.8%
계 31
 
6.4%
시 30
 
6.2%
서 29
 
6.0%
로 29
 
6.0%
구 29
 
6.0%
별 29
 
6.0%
특 29
 
6.0%
Other values (50) 176
36.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)76.5%
Missing12
Missing (%)41.4%
Infinite0
Infinite (%)0.0%
Mean1730.6471
Minimum1614
Maximum1854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:50.245053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1614
5-th percentile1614
Q11648
median1724
Q31809
95-th percentile1849.2
Maximum1854
Range240
Interquartile range (IQR)161

Descriptive statistics

Standard deviation86.770488
Coefficient of variation (CV)0.050137599
Kurtosis-1.4301243
Mean1730.6471
Median Absolute Deviation (MAD)83
Skewness0.16979295
Sum29421
Variance7529.1176
MonotonicityNot monotonic
2024-05-11T08:21:50.652690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1727 2
 
6.9%
1848 2
 
6.9%
1614 2
 
6.9%
1698 2
 
6.9%
1836 1
 
3.4%
1724 1
 
3.4%
1648 1
 
3.4%
1803 1
 
3.4%
1809 1
 
3.4%
1641 1
 
3.4%
Other values (3) 3
 
10.3%
(Missing) 12
41.4%
ValueCountFrequency (%)
1614 2
6.9%
1630 1
3.4%
1641 1
3.4%
1648 1
3.4%
1698 2
6.9%
1702 1
3.4%
1724 1
3.4%
1727 2
6.9%
1803 1
3.4%
1809 1
3.4%
ValueCountFrequency (%)
1854 1
3.4%
1848 2
6.9%
1836 1
3.4%
1809 1
3.4%
1803 1
3.4%
1727 2
6.9%
1724 1
3.4%
1702 1
3.4%
1698 2
6.9%
1648 1
3.4%

사업장명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T08:21:51.171779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length6.1034483
Min length2

Characters and Unicode

Total characters177
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

Unique29 ?
Unique (%)100.0%

Sample

1st row중앙 C?M
2nd row(주)청우푸드
3rd row대운유통
4th row원터축산
5th row주식회사 미앤팜농업회사법인
ValueCountFrequency (%)
중앙 1
 
3.2%
주)드림푸드시스템 1
 
3.2%
태양유통 1
 
3.2%
세라 1
 
3.2%
주)테슬러 1
 
3.2%
주)더커 1
 
3.2%
주)중앙에프앤비 1
 
3.2%
신도봉산식품 1
 
3.2%
주)앵거스월드미트 1
 
3.2%
제일푸드시스템 1
 
3.2%
Other values (21) 21
67.7%
2024-05-11T08:21:52.360651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 12
 
6.8%
) 11
 
6.2%
( 11
 
6.2%
드 8
 
4.5%
산 6
 
3.4%
푸 6
 
3.4%
식 5
 
2.8%
스 5
 
2.8%
에 4
 
2.3%
품 4
 
2.3%
Other values (79) 105
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
83.1%
Close Punctuation 11
 
6.2%
Open Punctuation 11
 
6.2%
Uppercase Letter 4
 
2.3%
Space Separator 2
 
1.1%
Other Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
8.2%
드 8
 
5.4%
산 6
 
4.1%
푸 6
 
4.1%
식 5
 
3.4%
스 5
 
3.4%
에 4
 
2.7%
품 4
 
2.7%
프 3
 
2.0%
축 3
 
2.0%
Other values (70) 91
61.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
M 1
25.0%
S 1
25.0%
F 1
25.0%
Other Punctuation
ValueCountFrequency (%)
? 1
50.0%
& 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
83.1%
Common 26
 
14.7%
Latin 4
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 12
 
8.2%
드 8
 
5.4%
산 6
 
4.1%
푸 6
 
4.1%
식 5
 
3.4%
스 5
 
3.4%
에 4
 
2.7%
품 4
 
2.7%
프 3
 
2.0%
축 3
 
2.0%
Other values (70) 91
61.9%
Common
ValueCountFrequency (%)
) 11
42.3%
( 11
42.3%
2
 
7.7%
? 1
 
3.8%
& 1
 
3.8%
Latin
ValueCountFrequency (%)
C 1
25.0%
M 1
25.0%
S 1
25.0%
F 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
83.1%
ASCII 30
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 12
 
8.2%
드 8
 
5.4%
산 6
 
4.1%
푸 6
 
4.1%
식 5
 
3.4%
스 5
 
3.4%
에 4
 
2.7%
품 4
 
2.7%
프 3
 
2.0%
축 3
 
2.0%
Other values (70) 91
61.9%
ASCII
ValueCountFrequency (%)
) 11
36.7%
( 11
36.7%
2
 
6.7%
C 1
 
3.3%
? 1
 
3.3%
M 1
 
3.3%
S 1
 
3.3%
F 1
 
3.3%
& 1
 
3.3%

최종수정일자
Date

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2004-12-23 13:55:01
Maximum2024-02-21 17:13:19
2024-05-11T08:21:52.931381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:21:53.470946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
I
21 
U
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 21
72.4%
U 8
 
27.6%

Length

2024-05-11T08:21:54.046820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:54.522342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 21
72.4%
u 8
 
27.6%

데이터갱신일자
Categorical

Distinct9
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2018-08-31 23:59:59.0
21 
2022-12-05 22:04:00.0
 
1
2021-11-01 21:01:00.0
 
1
2021-12-03 23:06:00.0
 
1
2019-06-02 02:40:00.0
 
1
Other values (4)
4 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique8 ?
Unique (%)27.6%

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 row2022-12-05 22:04:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 21
72.4%
2022-12-05 22:04:00.0 1
 
3.4%
2021-11-01 21:01:00.0 1
 
3.4%
2021-12-03 23:06:00.0 1
 
3.4%
2019-06-02 02:40:00.0 1
 
3.4%
2018-11-16 02:36:45.0 1
 
3.4%
2023-12-01 22:03:00.0 1
 
3.4%
2020-08-02 02:40:00.0 1
 
3.4%
2022-12-06 00:04:00.0 1
 
3.4%

Length

2024-05-11T08:21:55.150814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:55.656254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 21
36.2%
23:59:59.0 21
36.2%
02:40:00.0 2
 
3.4%
2022-12-06 1
 
1.7%
2020-08-02 1
 
1.7%
22:03:00.0 1
 
1.7%
2023-12-01 1
 
1.7%
02:36:45.0 1
 
1.7%
2018-11-16 1
 
1.7%
2019-06-02 1
 
1.7%
Other values (7) 7
 
12.1%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

좌표정보(X)
Real number (ℝ)

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206217.45
Minimum204454.15
Maximum207749.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:56.196813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204454.15
5-th percentile204623.75
Q1205659.95
median206243.04
Q3206873.34
95-th percentile207415.67
Maximum207749.31
Range3295.1619
Interquartile range (IQR)1213.3919

Descriptive statistics

Standard deviation903.58533
Coefficient of variation (CV)0.0043817112
Kurtosis-0.56962713
Mean206217.45
Median Absolute Deviation (MAD)583.09769
Skewness-0.39412292
Sum5980306.2
Variance816466.46
MonotonicityNot monotonic
2024-05-11T08:21:56.862297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
205659.945314658 2
 
6.9%
207415.665302618 2
 
6.9%
207105.241612335 2
 
6.9%
206243.043009388 2
 
6.9%
206727.227043397 1
 
3.4%
205987.412925896 1
 
3.4%
206132.370136946 1
 
3.4%
204878.051611685 1
 
3.4%
207385.380323557 1
 
3.4%
206414.974016875 1
 
3.4%
Other values (15) 15
51.7%
ValueCountFrequency (%)
204454.145658318 1
3.4%
204454.219222095 1
3.4%
204878.051611685 1
3.4%
204929.534452847 1
3.4%
205070.622667648 1
3.4%
205148.188748504 1
3.4%
205659.945314658 2
6.9%
205912.254205041 1
3.4%
205987.412925896 1
3.4%
206097.301988985 1
3.4%
ValueCountFrequency (%)
207749.307579592 1
3.4%
207415.665302618 2
6.9%
207385.380323557 1
3.4%
207105.241612335 2
6.9%
206883.987871913 1
3.4%
206873.337205167 1
3.4%
206799.020098051 1
3.4%
206727.227043397 1
3.4%
206625.665794345 1
3.4%
206539.157404229 1
3.4%

좌표정보(Y)
Real number (ℝ)

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean460711.56
Minimum457434.21
Maximum463537.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T08:21:57.704180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457434.21
5-th percentile457612.59
Q1458687.34
median461540.81
Q3462429.12
95-th percentile463479.3
Maximum463537.61
Range6103.3925
Interquartile range (IQR)3741.7877

Descriptive statistics

Standard deviation2103.0861
Coefficient of variation (CV)0.004564865
Kurtosis-1.3331277
Mean460711.56
Median Absolute Deviation (MAD)1841.8411
Skewness-0.28632613
Sum13360635
Variance4422971
MonotonicityNot monotonic
2024-05-11T08:21:58.412270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
461806.237949214 2
 
6.9%
460440.011514894 2
 
6.9%
460826.476802953 2
 
6.9%
461540.807727791 2
 
6.9%
462447.196614207 1
 
3.4%
458326.207832452 1
 
3.4%
461701.190221779 1
 
3.4%
463497.743108089 1
 
3.4%
463451.637795491 1
 
3.4%
459239.42095441 1
 
3.4%
Other values (15) 15
51.7%
ValueCountFrequency (%)
457434.214717297 1
3.4%
457593.754955577 1
3.4%
457640.840194694 1
3.4%
457735.45067157 1
3.4%
457813.581563405 1
3.4%
457913.95746077 1
3.4%
458326.207832452 1
3.4%
458687.336119097 1
3.4%
459064.752797491 1
3.4%
459239.42095441 1
3.4%
ValueCountFrequency (%)
463537.607226883 1
3.4%
463497.743108089 1
3.4%
463451.637795491 1
3.4%
463426.615582528 1
3.4%
463382.6488388 1
3.4%
462509.638445514 1
3.4%
462447.196614207 1
3.4%
462429.123801129 1
3.4%
461827.402394364 1
3.4%
461806.237949214 2
6.9%

축산업무구분명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
식육포장처리업
24 
<NA>
5 

Length

Max length7
Median length7
Mean length6.4827586
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 24
82.8%
<NA> 5
 
17.2%

Length

2024-05-11T08:21:58.930372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:21:59.453599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 24
82.8%
na 5
 
17.2%

축산물가공업구분명
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
식육포장처리업
24 
<NA>
5 

Length

Max length7
Median length7
Mean length6.4827586
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식육포장처리업 24
82.8%
<NA> 5
 
17.2%

Length

2024-05-11T08:22:00.001400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:22:00.371667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육포장처리업 24
82.8%
na 5
 
17.2%

축산일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

권리주체일련번호
Categorical

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
000
14 
L00
10 
<NA>
5 

Length

Max length4
Median length3
Mean length3.1724138
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
000 14
48.3%
L00 10
34.5%
<NA> 5
 
17.2%

Length

2024-05-11T08:22:00.724149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:22:01.213361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 14
48.3%
l00 10
34.5%
na 5
 
17.2%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
0310000031000000042000000120000919<NA>3폐업2폐업20060410<NA><NA><NA>3392-527788.3<NA>서울특별시 노원구 상계동 399-2번지 지하1층서울특별시 노원구 노원로 475 (상계동,지하1층)<NA>중앙 C?M2006-04-10 10:39:43I2018-08-31 23:59:59.0<NA>205659.945315461806.237949식육포장처리업식육포장처리업<NA>000<NA>
1310000031000000042003000420020722<NA>3폐업2폐업20150603<NA><NA><NA>952-9595230.46<NA>서울특별시 노원구 상계동 95-3번지 상계시장내서울특별시 노원구 덕릉로102길 5 (상계동,상계시장내)<NA>(주)청우푸드2015-06-03 15:43:16I2018-08-31 23:59:59.0<NA>206799.020098462509.638446식육포장처리업식육포장처리업<NA>L00<NA>
2310000031000000042004000420040423<NA>3폐업2폐업20100628<NA><NA><NA>978-469096.0<NA>서울특별시 노원구 하계동 276-1번지서울특별시 노원구 공릉로59가길 9 (하계동)<NA>대운유통2010-07-05 10:04:28I2018-08-31 23:59:59.0<NA>206201.840029459064.752797식육포장처리업식육포장처리업<NA>000<NA>
3310000031000000042004000520040924<NA>3폐업2폐업20041223<NA><NA><NA>937-816956.0<NA>서울특별시 노원구 상계동 389-555번지서울특별시 노원구 상계로17길 20 (상계동)<NA>원터축산2004-12-23 13:55:01I2018-08-31 23:59:59.0<NA>205912.254205461827.402394식육포장처리업식육포장처리업<NA>000<NA>
431000003100000004200500042005-04-30<NA>1영업/정상0정상<NA><NA><NA><NA>02-972-5252159.28<NA>서울특별시 노원구 공릉동 351-2서울특별시 노원구 공릉로39길 11 (공릉동, 주완위즈빌)1836주식회사 미앤팜농업회사법인2023-06-22 09:57:27U2022-12-05 22:04:00.0<NA>206883.987872457913.957461<NA><NA><NA><NA><NA>
5310000031000000042005000520050520<NA>3폐업2폐업20060322<NA><NA><NA>933-6947135.85<NA>서울특별시 노원구 상계동 151-4번지 흥봉빌딩2층서울특별시 노원구 한글비석로44길 31 (상계동,흥봉빌딩2층)<NA>(주)청솔지툰2006-03-22 15:53:40I2018-08-31 23:59:59.0<NA>206097.301989462429.123801식육포장처리업식육포장처리업<NA>L00<NA>
6310000031000000042005000720051216<NA>3폐업2폐업20140403<NA><NA><NA>937-5500184.0<NA>서울특별시 노원구 중계동 43-15번지서울특별시 노원구 중계로8길 48 (중계동)1727(주)제오식품2014-04-03 18:01:49I2018-08-31 23:59:59.0<NA>207415.665303460440.011515식육포장처리업식육포장처리업<NA>L00<NA>
7310000031000000042006000120060420<NA>3폐업2폐업20060607<NA><NA><NA>939-215586.0<NA>서울특별시 노원구 중계동 84-7번지서울특별시 노원구 중계로 162-11 (중계동)<NA>고원축산2006-06-07 14:58:19I2018-08-31 23:59:59.0<NA>207105.241612460826.476803식육포장처리업식육포장처리업<NA>000<NA>
8310000031000000042006000220060609<NA>3폐업2폐업20151222<NA><NA><NA>3451-222144.9<NA>서울특별시 노원구 공릉동 577-4번지 1층서울특별시 노원구 동일로178길 11-17, 1층 (공릉동)1848(주)에프씨자모리2015-12-22 14:30:08I2018-08-31 23:59:59.0<NA>206539.157404457735.450672식육포장처리업식육포장처리업<NA>L00<NA>
9310000031000000042006000420060801<NA>3폐업2폐업20150629<NA><NA><NA>939-215584.0<NA>서울특별시 노원구 중계동 84-7번지서울특별시 노원구 중계로 162-11 (중계동, 현대프라자 B102호)1724(주)한수식품2015-06-29 16:52:22I2018-08-31 23:59:59.0<NA>207105.241612460826.476803식육포장처리업식육포장처리업<NA>L00<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총인원
19310000031000001042013000220130819<NA>3폐업2폐업20140304<NA><NA><NA><NA>0.0<NA>서울특별시 노원구 공릉동 593-10번지서울특별시 노원구 동일로176길 19-13 (공릉동)1848아이비스푸드2014-03-05 08:49:34I2018-08-31 23:59:59.0<NA>206625.665794457593.754956식육포장처리업식육포장처리업<NA>L00<NA>
20310000031000001042013000320130821<NA>3폐업2폐업20150210<NA><NA><NA><NA>0.0<NA>서울특별시 노원구 공릉동 653-4번지서울특별시 노원구 공릉로20길 4 (공릉동)1803제일푸드시스템2015-02-10 16:52:47I2018-08-31 23:59:59.0<NA>206873.337205457434.214717식육포장처리업식육포장처리업<NA>000<NA>
21310000031000001042013000420131023<NA>1영업/정상0정상<NA><NA><NA><NA><NA>237.0<NA>서울특별시 노원구 상계동 387-213서울특별시 노원구 상계로26길 13, 지층 (상계동)1698(주)앵거스월드미트2022-04-14 09:22:02U2021-12-03 23:06:00.0<NA>206194.402376461747.923349<NA><NA><NA><NA><NA>
22310000031000001042014000120140328<NA>3폐업2폐업20190531<NA><NA><NA>971-36330.0<NA>서울특별시 노원구 하계동 164-2번지서울특별시 노원구 공릉로58길 90 (하계동)1809신도봉산식품2019-05-31 13:47:30U2019-06-02 02:40:00.0<NA>206414.974017459239.420954식육포장처리업식육포장처리업<NA>000<NA>
23310000031000001042014000220140409<NA>3폐업2폐업20170912<NA><NA><NA>937-55000.0<NA>서울특별시 노원구 중계동 43-15번지서울특별시 노원구 중계로8길 48 (중계동)1727(주)중앙에프앤비2017-09-13 11:12:01I2018-08-31 23:59:59.0<NA>207415.665303460440.011515식육포장처리업식육포장처리업<NA>L00<NA>
24310000031000001042014000320140724<NA>3폐업2폐업20180630<NA><NA><NA><NA>0.0<NA>서울특별시 노원구 상계동 43-27번지서울특별시 노원구 덕릉로134길 19, 1층 (상계동)1641(주)더커2018-07-17 17:59:13I2018-08-31 23:59:59.0<NA>207385.380324463451.637795식육포장처리업식육포장처리업<NA>L00<NA>
25310000031000001042014000420141002<NA>3폐업2폐업20181114<NA><NA><NA>070-7671-12270.0<NA>서울특별시 노원구 상계동 1025-4번지 4층서울특별시 노원구 동일로 1628, 4층 (상계동)1630(주)테슬러2018-11-14 12:56:14U2018-11-16 02:36:45.0<NA>204878.051612463497.743108식육포장처리업식육포장처리업<NA>L00<NA>
2631000003100000104201500012015-05-14<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 노원구 상계동 180-10서울특별시 노원구 노원로26길 139, 1층 (상계동)1702세라2024-02-21 17:13:19U2023-12-01 22:03:00.0<NA>206243.043009461540.807728<NA><NA><NA><NA><NA>
27310000031000001042015000220150629<NA>3폐업2폐업20200731<NA><NA><NA>933-02070.0<NA>서울특별시 노원구 상계동 387-28서울특별시 노원구 상계로24길 19 (상계동)1698태양유통2020-07-31 15:58:58U2020-08-02 02:40:00.0<NA>206132.370137461701.190222식육포장처리업식육포장처리업<NA>000<NA>
2831000003100000104201800012018-04-10<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>서울특별시 노원구 공릉동 715 공릉3단지아파트상가 103호서울특별시 노원구 섬밭로 125, 공릉3단지아파트상가 (공릉동)1854고친외양간2023-06-02 16:13:19U2022-12-06 00:04:00.0<NA>205987.412926458326.207832<NA><NA><NA><NA><NA>