Overview

Dataset statistics

Number of variables47
Number of observations40
Missing cells426
Missing cells (%)22.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory409.3 B

Variable types

Numeric11
Categorical20
Text6
Unsupported9
Boolean1

Dataset

Description22년06월_6270000_대구광역시_07_22_12_P_식품첨가물제조업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093750&dataSetDetailId=DDI_0000093768&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (53.1%)Imbalance
여성종사자수 is highly imbalanced (53.1%)Imbalance
총종업원수 is highly imbalanced (53.1%)Imbalance
인허가취소일자 has 40 (100.0%) missing valuesMissing
폐업일자 has 17 (42.5%) missing valuesMissing
휴업시작일자 has 40 (100.0%) missing valuesMissing
휴업종료일자 has 40 (100.0%) missing valuesMissing
재개업일자 has 40 (100.0%) missing valuesMissing
소재지전화 has 9 (22.5%) missing valuesMissing
소재지면적 has 2 (5.0%) missing valuesMissing
소재지우편번호 has 1 (2.5%) missing valuesMissing
도로명전체주소 has 8 (20.0%) missing valuesMissing
도로명우편번호 has 8 (20.0%) missing valuesMissing
좌표정보(X) has 5 (12.5%) missing valuesMissing
좌표정보(Y) has 5 (12.5%) missing valuesMissing
영업장주변구분명 has 40 (100.0%) missing valuesMissing
등급구분명 has 40 (100.0%) missing valuesMissing
공장생산직종업원수 has 11 (27.5%) missing valuesMissing
전통업소지정번호 has 40 (100.0%) missing valuesMissing
전통업소주된음식 has 40 (100.0%) missing valuesMissing
홈페이지 has 40 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장생산직종업원수 has 16 (40.0%) zerosZeros
시설총규모 has 33 (82.5%) zerosZeros

Reproduction

Analysis started2023-12-10 18:12:44.840441
Analysis finished2023-12-10 18:12:45.602014
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:45.688547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-11T03:12:45.901237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
식품첨가물제조업
40 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

Length

2023-12-11T03:12:46.114519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:46.270277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
07_22_12_P
40 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_12_P
2nd row07_22_12_P
3rd row07_22_12_P
4th row07_22_12_P
5th row07_22_12_P

Common Values

ValueCountFrequency (%)
07_22_12_P 40
100.0%

Length

2023-12-11T03:12:46.453952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:46.595416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_12_p 40
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3458750
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:46.716027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3429500
Q13440000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range60000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation20278.51
Coefficient of variation (CV)0.005862959
Kurtosis-1.1927073
Mean3458750
Median Absolute Deviation (MAD)10000
Skewness-0.50098191
Sum1.3835 × 108
Variance4.1121795 × 108
MonotonicityIncreasing
2023-12-11T03:12:46.864383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3480000 12
30.0%
3470000 9
22.5%
3430000 6
15.0%
3450000 6
15.0%
3440000 3
 
7.5%
3420000 2
 
5.0%
3460000 2
 
5.0%
ValueCountFrequency (%)
3420000 2
 
5.0%
3430000 6
15.0%
3440000 3
 
7.5%
3450000 6
15.0%
3460000 2
 
5.0%
3470000 9
22.5%
3480000 12
30.0%
ValueCountFrequency (%)
3480000 12
30.0%
3470000 9
22.5%
3460000 2
 
5.0%
3450000 6
15.0%
3440000 3
 
7.5%
3430000 6
15.0%
3420000 2
 
5.0%

관리번호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-11T03:12:47.152216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters880
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

Unique40 ?
Unique (%)100.0%

Sample

1st row3420000-108-2011-00001
2nd row3420000-108-2014-00001
3rd row3430000-108-2011-00002
4th row3430000-108-2019-00001
5th row3430000-108-2019-00002
ValueCountFrequency (%)
3420000-108-2011-00001 1
 
2.5%
3420000-108-2014-00001 1
 
2.5%
3480000-108-2011-00004 1
 
2.5%
3470000-108-2016-00001 1
 
2.5%
3470000-108-2011-00001 1
 
2.5%
3470000-108-2014-00002 1
 
2.5%
3470000-108-2012-00001 1
 
2.5%
3470000-108-2011-00002 1
 
2.5%
3470000-108-2015-00001 1
 
2.5%
3480000-108-2019-00001 1
 
2.5%
Other values (30) 30
75.0%
2023-12-11T03:12:47.657745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 404
45.9%
- 120
 
13.6%
1 119
 
13.5%
2 59
 
6.7%
8 55
 
6.2%
3 49
 
5.6%
4 48
 
5.5%
7 10
 
1.1%
5 8
 
0.9%
6 5
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 760
86.4%
Dash Punctuation 120
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 404
53.2%
1 119
 
15.7%
2 59
 
7.8%
8 55
 
7.2%
3 49
 
6.4%
4 48
 
6.3%
7 10
 
1.3%
5 8
 
1.1%
6 5
 
0.7%
9 3
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 404
45.9%
- 120
 
13.6%
1 119
 
13.5%
2 59
 
6.7%
8 55
 
6.2%
3 49
 
5.6%
4 48
 
5.5%
7 10
 
1.1%
5 8
 
0.9%
6 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 404
45.9%
- 120
 
13.6%
1 119
 
13.5%
2 59
 
6.7%
8 55
 
6.2%
3 49
 
5.6%
4 48
 
5.5%
7 10
 
1.1%
5 8
 
0.9%
6 5
 
0.6%

인허가일자
Real number (ℝ)

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20111639
Minimum19890829
Maximum20211210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:47.894589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19890829
5-th percentile19980576
Q120057821
median20120617
Q320182937
95-th percentile20210251
Maximum20211210
Range320381
Interquartile range (IQR)125116

Descriptive statistics

Standard deviation79037.888
Coefficient of variation (CV)0.0039299575
Kurtosis0.011675115
Mean20111639
Median Absolute Deviation (MAD)64950
Skewness-0.68764493
Sum8.0446558 × 108
Variance6.2469877 × 109
MonotonicityNot monotonic
2023-12-11T03:12:48.123520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20141113 2
 
5.0%
20070726 2
 
5.0%
20120313 2
 
5.0%
20200214 1
 
2.5%
20160615 1
 
2.5%
20120921 1
 
2.5%
20070920 1
 
2.5%
20150701 1
 
2.5%
20190704 1
 
2.5%
20050323 1
 
2.5%
Other values (27) 27
67.5%
ValueCountFrequency (%)
19890829 1
2.5%
19970410 1
2.5%
19981111 1
2.5%
19990422 1
2.5%
20020103 1
2.5%
20021024 1
2.5%
20030123 1
2.5%
20040705 1
2.5%
20050120 1
2.5%
20050323 1
2.5%
ValueCountFrequency (%)
20211210 1
2.5%
20211118 1
2.5%
20210205 1
2.5%
20200721 1
2.5%
20200624 1
2.5%
20200305 1
2.5%
20200214 1
2.5%
20190926 1
2.5%
20190704 1
2.5%
20190220 1
2.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
3
23 
1
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 23
57.5%
1 17
42.5%

Length

2023-12-11T03:12:48.276075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:48.428510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 23
57.5%
1 17
42.5%

영업상태명
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
폐업
23 
영업/정상
17 

Length

Max length5
Median length2
Mean length3.275
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 23
57.5%
영업/정상 17
42.5%

Length

2023-12-11T03:12:48.603936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:48.756012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 23
57.5%
영업/정상 17
42.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2
23 
1
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 23
57.5%
1 17
42.5%

Length

2023-12-11T03:12:48.912551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:49.050360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 23
57.5%
1 17
42.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
폐업
23 
영업
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 23
57.5%
영업 17
42.5%

Length

2023-12-11T03:12:49.228741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:49.398729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 23
57.5%
영업 17
42.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)100.0%
Missing17
Missing (%)42.5%
Infinite0
Infinite (%)0.0%
Mean20132934
Minimum20040914
Maximum20211115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:49.549186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040914
5-th percentile20043160
Q120090913
median20131106
Q320175717
95-th percentile20200568
Maximum20211115
Range170201
Interquartile range (IQR)84804

Descriptive statistics

Standard deviation54276.126
Coefficient of variation (CV)0.0026958876
Kurtosis-1.1688908
Mean20132934
Median Absolute Deviation (MAD)49222
Skewness-0.31229119
Sum4.6305748 × 108
Variance2.9458979 × 109
MonotonicityNot monotonic
2023-12-11T03:12:49.734797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20170731 1
 
2.5%
20041231 1
 
2.5%
20080625 1
 
2.5%
20040914 1
 
2.5%
20060526 1
 
2.5%
20171106 1
 
2.5%
20110727 1
 
2.5%
20131106 1
 
2.5%
20160203 1
 
2.5%
20131104 1
 
2.5%
Other values (13) 13
32.5%
(Missing) 17
42.5%
ValueCountFrequency (%)
20040914 1
2.5%
20041231 1
2.5%
20060526 1
2.5%
20060612 1
2.5%
20071026 1
2.5%
20080625 1
2.5%
20101201 1
2.5%
20110126 1
2.5%
20110727 1
2.5%
20130906 1
2.5%
ValueCountFrequency (%)
20211115 1
2.5%
20200619 1
2.5%
20200110 1
2.5%
20191209 1
2.5%
20190129 1
2.5%
20180328 1
2.5%
20171106 1
2.5%
20170731 1
2.5%
20161124 1
2.5%
20160203 1
2.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

소재지전화
Text

MISSING 

Distinct29
Distinct (%)93.5%
Missing9
Missing (%)22.5%
Memory size452.0 B
2023-12-11T03:12:50.009076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.741935
Min length8

Characters and Unicode

Total characters333
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

Unique27 ?
Unique (%)87.1%

Sample

1st row053 981 3886
2nd row053 965 6581
3rd row053 5237589
4th row0535656597
5th row053 5652600
ValueCountFrequency (%)
053 15
24.6%
15662723 3
 
4.9%
616 3
 
4.9%
592 2
 
3.3%
0661 2
 
3.3%
614 1
 
1.6%
0535923110 1
 
1.6%
18001836 1
 
1.6%
610 1
 
1.6%
0154 1
 
1.6%
Other values (31) 31
50.8%
2023-12-11T03:12:50.474197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
15.6%
5 49
14.7%
3 47
14.1%
6 37
11.1%
1 34
10.2%
32
9.6%
2 21
6.3%
7 18
 
5.4%
4 17
 
5.1%
9 13
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 301
90.4%
Space Separator 32
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
17.3%
5 49
16.3%
3 47
15.6%
6 37
12.3%
1 34
11.3%
2 21
7.0%
7 18
 
6.0%
4 17
 
5.6%
9 13
 
4.3%
8 13
 
4.3%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 333
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
15.6%
5 49
14.7%
3 47
14.1%
6 37
11.1%
1 34
10.2%
32
9.6%
2 21
6.3%
7 18
 
5.4%
4 17
 
5.1%
9 13
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
15.6%
5 49
14.7%
3 47
14.1%
6 37
11.1%
1 34
10.2%
32
9.6%
2 21
6.3%
7 18
 
5.4%
4 17
 
5.1%
9 13
 
3.9%

소재지면적
Text

MISSING 

Distinct37
Distinct (%)97.4%
Missing2
Missing (%)5.0%
Memory size452.0 B
2023-12-11T03:12:50.722304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3947368
Min length3

Characters and Unicode

Total characters205
Distinct characters12
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

Unique36 ?
Unique (%)94.7%

Sample

1st row29.00
2nd row305.00
3rd row59.51
4th row60.48
5th row494.00
ValueCountFrequency (%)
00 2
 
5.3%
120.00 1
 
2.6%
29.00 1
 
2.6%
150.37 1
 
2.6%
61.20 1
 
2.6%
68.50 1
 
2.6%
152.10 1
 
2.6%
50.00 1
 
2.6%
556.80 1
 
2.6%
51.00 1
 
2.6%
Other values (27) 27
71.1%
2023-12-11T03:12:51.131266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49
23.9%
. 38
18.5%
5 20
9.8%
1 18
 
8.8%
2 15
 
7.3%
6 14
 
6.8%
8 12
 
5.9%
9 11
 
5.4%
3 11
 
5.4%
4 10
 
4.9%
Other values (2) 7
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 166
81.0%
Other Punctuation 39
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
29.5%
5 20
12.0%
1 18
 
10.8%
2 15
 
9.0%
6 14
 
8.4%
8 12
 
7.2%
9 11
 
6.6%
3 11
 
6.6%
4 10
 
6.0%
7 6
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 38
97.4%
, 1
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 205
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 49
23.9%
. 38
18.5%
5 20
9.8%
1 18
 
8.8%
2 15
 
7.3%
6 14
 
6.8%
8 12
 
5.9%
9 11
 
5.4%
3 11
 
5.4%
4 10
 
4.9%
Other values (2) 7
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49
23.9%
. 38
18.5%
5 20
9.8%
1 18
 
8.8%
2 15
 
7.3%
6 14
 
6.8%
8 12
 
5.9%
9 11
 
5.4%
3 11
 
5.4%
4 10
 
4.9%
Other values (2) 7
 
3.4%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)64.1%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean706477.62
Minimum701260
Maximum711864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:51.322683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum701260
5-th percentile702016.7
Q1703830
median704833
Q3711832.5
95-th percentile711855
Maximum711864
Range10604
Interquartile range (IQR)8002.5

Descriptive statistics

Standard deviation3814.2475
Coefficient of variation (CV)0.0053989645
Kurtosis-1.3724944
Mean706477.62
Median Absolute Deviation (MAD)2015
Skewness0.55597335
Sum27552627
Variance14548484
MonotonicityNot monotonic
2023-12-11T03:12:51.511710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
711855 6
 
15.0%
704833 3
 
7.5%
706848 2
 
5.0%
703833 2
 
5.0%
703830 2
 
5.0%
711843 2
 
5.0%
702800 2
 
5.0%
704900 2
 
5.0%
704801 2
 
5.0%
704826 1
 
2.5%
Other values (15) 15
37.5%
ValueCountFrequency (%)
701260 1
2.5%
701807 1
2.5%
702040 1
2.5%
702800 2
5.0%
702805 1
2.5%
702852 1
2.5%
702862 1
2.5%
703110 1
2.5%
703830 2
5.0%
703831 1
2.5%
ValueCountFrequency (%)
711864 1
 
2.5%
711855 6
15.0%
711852 1
 
2.5%
711843 2
 
5.0%
711822 1
 
2.5%
711811 1
 
2.5%
706848 2
 
5.0%
705826 1
 
2.5%
705800 1
 
2.5%
704920 1
 
2.5%

소재지전체주소
Text

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-11T03:12:51.793296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length26
Mean length22.625
Min length7

Characters and Unicode

Total characters905
Distinct characters75
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)85.0%

Sample

1st row대구광역시 동구 불로동 1074-6번지
2nd row대구광역시 동구 율암동 1103-13번지
3rd row대구광역시 서구 중리동 40-13번지
4th row대구광역시 서구 중리동 1066
5th row대구광역시 서구 중리동 905-10번지
ValueCountFrequency (%)
대구광역시 40
23.3%
달성군 12
 
7.0%
달서구 9
 
5.2%
논공읍 7
 
4.1%
서구 6
 
3.5%
본리리 6
 
3.5%
북구 6
 
3.5%
월암동 3
 
1.7%
이현동 3
 
1.7%
중리동 3
 
1.7%
Other values (64) 77
44.8%
2023-12-11T03:12:52.257884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
19.1%
구 68
 
7.5%
대 44
 
4.9%
1 43
 
4.8%
광 40
 
4.4%
역 40
 
4.4%
시 40
 
4.4%
- 33
 
3.6%
동 29
 
3.2%
지 28
 
3.1%
Other values (65) 367
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
57.2%
Decimal Number 181
 
20.0%
Space Separator 173
 
19.1%
Dash Punctuation 33
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 68
13.1%
대 44
 
8.5%
광 40
 
7.7%
역 40
 
7.7%
시 40
 
7.7%
동 29
 
5.6%
지 28
 
5.4%
번 28
 
5.4%
리 22
 
4.2%
달 21
 
4.1%
Other values (53) 158
30.5%
Decimal Number
ValueCountFrequency (%)
1 43
23.8%
2 26
14.4%
0 17
 
9.4%
8 16
 
8.8%
9 15
 
8.3%
5 15
 
8.3%
3 14
 
7.7%
7 14
 
7.7%
4 12
 
6.6%
6 9
 
5.0%
Space Separator
ValueCountFrequency (%)
173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
57.2%
Common 387
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 68
13.1%
대 44
 
8.5%
광 40
 
7.7%
역 40
 
7.7%
시 40
 
7.7%
동 29
 
5.6%
지 28
 
5.4%
번 28
 
5.4%
리 22
 
4.2%
달 21
 
4.1%
Other values (53) 158
30.5%
Common
ValueCountFrequency (%)
173
44.7%
1 43
 
11.1%
- 33
 
8.5%
2 26
 
6.7%
0 17
 
4.4%
8 16
 
4.1%
9 15
 
3.9%
5 15
 
3.9%
3 14
 
3.6%
7 14
 
3.6%
Other values (2) 21
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
57.2%
ASCII 387
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
44.7%
1 43
 
11.1%
- 33
 
8.5%
2 26
 
6.7%
0 17
 
4.4%
8 16
 
4.1%
9 15
 
3.9%
5 15
 
3.9%
3 14
 
3.6%
7 14
 
3.6%
Other values (2) 21
 
5.4%
Hangul
ValueCountFrequency (%)
구 68
13.1%
대 44
 
8.5%
광 40
 
7.7%
역 40
 
7.7%
시 40
 
7.7%
동 29
 
5.6%
지 28
 
5.4%
번 28
 
5.4%
리 22
 
4.2%
달 21
 
4.1%
Other values (53) 158
30.5%

도로명전체주소
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing8
Missing (%)20.0%
Memory size452.0 B
2023-12-11T03:12:52.586448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length26.96875
Min length21

Characters and Unicode

Total characters863
Distinct characters90
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

Unique32 ?
Unique (%)100.0%

Sample

1st row대구광역시 동구 방천로6길 36 (불로동)
2nd row대구광역시 동구 매여로 62, 1층 (율암동)
3rd row대구광역시 서구 서대구로25길 19 (중리동)
4th row대구광역시 서구 국채보상로20길 32 (중리동)
5th row대구광역시 서구 와룡로73길 57-6 (중리동)
ValueCountFrequency (%)
대구광역시 32
 
18.0%
1층 10
 
5.6%
달서구 8
 
4.5%
달성군 8
 
4.5%
북구 6
 
3.4%
논공읍 5
 
2.8%
서구 4
 
2.2%
중리동 3
 
1.7%
동구 2
 
1.1%
38 2
 
1.1%
Other values (83) 98
55.1%
2023-12-11T03:12:53.113798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
 
16.9%
구 60
 
7.0%
대 41
 
4.8%
로 33
 
3.8%
광 32
 
3.7%
역 32
 
3.7%
시 32
 
3.7%
동 30
 
3.5%
1 30
 
3.5%
( 25
 
2.9%
Other values (80) 402
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 513
59.4%
Space Separator 146
 
16.9%
Decimal Number 134
 
15.5%
Open Punctuation 25
 
2.9%
Close Punctuation 25
 
2.9%
Other Punctuation 15
 
1.7%
Dash Punctuation 4
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 60
 
11.7%
대 41
 
8.0%
로 33
 
6.4%
광 32
 
6.2%
역 32
 
6.2%
시 32
 
6.2%
동 30
 
5.8%
길 24
 
4.7%
서 21
 
4.1%
성 18
 
3.5%
Other values (64) 190
37.0%
Decimal Number
ValueCountFrequency (%)
1 30
22.4%
2 21
15.7%
5 20
14.9%
3 15
11.2%
6 14
10.4%
7 8
 
6.0%
0 8
 
6.0%
8 7
 
5.2%
4 6
 
4.5%
9 5
 
3.7%
Space Separator
ValueCountFrequency (%)
146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
59.4%
Common 349
40.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 60
 
11.7%
대 41
 
8.0%
로 33
 
6.4%
광 32
 
6.2%
역 32
 
6.2%
시 32
 
6.2%
동 30
 
5.8%
길 24
 
4.7%
서 21
 
4.1%
성 18
 
3.5%
Other values (64) 190
37.0%
Common
ValueCountFrequency (%)
146
41.8%
1 30
 
8.6%
( 25
 
7.2%
) 25
 
7.2%
2 21
 
6.0%
5 20
 
5.7%
3 15
 
4.3%
, 15
 
4.3%
6 14
 
4.0%
7 8
 
2.3%
Other values (5) 30
 
8.6%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 513
59.4%
ASCII 350
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
41.7%
1 30
 
8.6%
( 25
 
7.1%
) 25
 
7.1%
2 21
 
6.0%
5 20
 
5.7%
3 15
 
4.3%
, 15
 
4.3%
6 14
 
4.0%
7 8
 
2.3%
Other values (6) 31
 
8.9%
Hangul
ValueCountFrequency (%)
구 60
 
11.7%
대 41
 
8.0%
로 33
 
6.4%
광 32
 
6.2%
역 32
 
6.2%
시 32
 
6.2%
동 30
 
5.8%
길 24
 
4.7%
서 21
 
4.1%
성 18
 
3.5%
Other values (64) 190
37.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)87.5%
Missing8
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean42287.344
Minimum41042
Maximum42983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:53.290966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41042
5-th percentile41288.85
Q141711.25
median42565.5
Q342781.75
95-th percentile42983
Maximum42983
Range1941
Interquartile range (IQR)1070.5

Descriptive statistics

Standard deviation636.07834
Coefficient of variation (CV)0.015041814
Kurtosis-1.2219646
Mean42287.344
Median Absolute Deviation (MAD)416
Skewness-0.50384481
Sum1353195
Variance404595.65
MonotonicityNot monotonic
2023-12-11T03:12:53.450918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
42983 3
 
7.5%
42721 2
 
5.0%
42230 2
 
5.0%
41755 1
 
2.5%
42704 1
 
2.5%
42982 1
 
2.5%
42934 1
 
2.5%
42981 1
 
2.5%
42907 1
 
2.5%
42901 1
 
2.5%
Other values (18) 18
45.0%
(Missing) 8
20.0%
ValueCountFrequency (%)
41042 1
2.5%
41065 1
2.5%
41472 1
2.5%
41512 1
2.5%
41521 1
2.5%
41546 1
2.5%
41572 1
2.5%
41580 1
2.5%
41755 1
2.5%
41758 1
2.5%
ValueCountFrequency (%)
42983 3
7.5%
42982 1
 
2.5%
42981 1
 
2.5%
42934 1
 
2.5%
42907 1
 
2.5%
42901 1
 
2.5%
42742 1
 
2.5%
42721 2
5.0%
42720 1
 
2.5%
42718 1
 
2.5%

사업장명
Text

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-11T03:12:53.703941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8.5
Mean length6
Min length2

Characters and Unicode

Total characters240
Distinct characters111
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

Unique31 ?
Unique (%)77.5%

Sample

1st row매봉산야초건강원
2nd row(주)프리나
3rd row생림목초
4th row일지스타치
5th row뉴트리디언
ValueCountFrequency (%)
주)자숨 3
 
7.1%
미남메디칼 2
 
4.8%
태경농산(주 2
 
4.8%
동창c&f 2
 
4.8%
오메가화학 1
 
2.4%
주)멀티바이오 1
 
2.4%
주)일동플러스팜 1
 
2.4%
미성 1
 
2.4%
주)에코앤파워 1
 
2.4%
명성식품 1
 
2.4%
Other values (27) 27
64.3%
2023-12-11T03:12:54.165357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
7.5%
( 17
 
7.1%
) 17
 
7.1%
산 7
 
2.9%
이 5
 
2.1%
오 5
 
2.1%
성 5
 
2.1%
리 4
 
1.7%
바 4
 
1.7%
디 4
 
1.7%
Other values (101) 154
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
82.5%
Open Punctuation 17
 
7.1%
Close Punctuation 17
 
7.1%
Uppercase Letter 4
 
1.7%
Space Separator 2
 
0.8%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
9.1%
산 7
 
3.5%
이 5
 
2.5%
오 5
 
2.5%
성 5
 
2.5%
리 4
 
2.0%
바 4
 
2.0%
디 4
 
2.0%
태 4
 
2.0%
식 4
 
2.0%
Other values (95) 138
69.7%
Uppercase Letter
ValueCountFrequency (%)
F 2
50.0%
C 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
82.5%
Common 38
 
15.8%
Latin 4
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
9.1%
산 7
 
3.5%
이 5
 
2.5%
오 5
 
2.5%
성 5
 
2.5%
리 4
 
2.0%
바 4
 
2.0%
디 4
 
2.0%
태 4
 
2.0%
식 4
 
2.0%
Other values (95) 138
69.7%
Common
ValueCountFrequency (%)
( 17
44.7%
) 17
44.7%
2
 
5.3%
& 2
 
5.3%
Latin
ValueCountFrequency (%)
F 2
50.0%
C 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
82.5%
ASCII 42
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
9.1%
산 7
 
3.5%
이 5
 
2.5%
오 5
 
2.5%
성 5
 
2.5%
리 4
 
2.0%
바 4
 
2.0%
디 4
 
2.0%
태 4
 
2.0%
식 4
 
2.0%
Other values (95) 138
69.7%
ASCII
ValueCountFrequency (%)
( 17
40.5%
) 17
40.5%
F 2
 
4.8%
2
 
4.8%
C 2
 
4.8%
& 2
 
4.8%

최종수정시점
Real number (ℝ)

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0158457 × 1013
Minimum2.0060818 × 1013
Maximum2.021121 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:54.696131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0060818 × 1013
5-th percentile2.0060818 × 1013
Q12.0120812 × 1013
median2.0175717 × 1013
Q32.020062 × 1013
95-th percentile2.0211123 × 1013
Maximum2.021121 × 1013
Range1.5039195 × 1011
Interquartile range (IQR)7.9808308 × 1010

Descriptive statistics

Standard deviation5.0110891 × 1010
Coefficient of variation (CV)0.0024858495
Kurtosis-0.62247514
Mean2.0158457 × 1013
Median Absolute Deviation (MAD)2.993749 × 1010
Skewness-0.81766861
Sum8.0633827 × 1014
Variance2.5111014 × 1021
MonotonicityNot monotonic
2023-12-11T03:12:54.866540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20060818222941 4
 
10.0%
20120213102837 1
 
2.5%
20211210173449 1
 
2.5%
20180328145458 1
 
2.5%
20120125113609 1
 
2.5%
20141113125327 1
 
2.5%
20121011115222 1
 
2.5%
20110113112657 1
 
2.5%
20171106143720 1
 
2.5%
20190705142649 1
 
2.5%
Other values (27) 27
67.5%
ValueCountFrequency (%)
20060818222941 4
10.0%
20071228112953 1
 
2.5%
20080625180001 1
 
2.5%
20101202230409 1
 
2.5%
20110113112657 1
 
2.5%
20120125113609 1
 
2.5%
20120213102837 1
 
2.5%
20121011115222 1
 
2.5%
20130416103429 1
 
2.5%
20140113104126 1
 
2.5%
ValueCountFrequency (%)
20211210173449 1
2.5%
20211210165951 1
2.5%
20211118103446 1
2.5%
20211115094821 1
2.5%
20210623100751 1
2.5%
20210205104753 1
2.5%
20201104165418 1
2.5%
20200921112048 1
2.5%
20200721170231 1
2.5%
20200625162324 1
2.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
I
28 
U
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 28
70.0%
U 12
30.0%

Length

2023-12-11T03:12:55.042348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:55.171128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 28
70.0%
u 12
30.0%

데이터갱신일자
Categorical

Distinct19
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2018-08-31 23:59:59.0
22 
2020-11-06 02:40:00.0
 
1
2019-09-28 02:22:39.0
 
1
2020-06-20 02:40:00.0
 
1
2021-12-12 00:22:53.0
 
1
Other values (14)
14 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique18 ?
Unique (%)45.0%

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 row2020-11-06 02:40:00.0
5th row2019-09-28 02:22:39.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 22
55.0%
2020-11-06 02:40:00.0 1
 
2.5%
2019-09-28 02:22:39.0 1
 
2.5%
2020-06-20 02:40:00.0 1
 
2.5%
2021-12-12 00:22:53.0 1
 
2.5%
2020-01-12 02:40:00.0 1
 
2.5%
2021-11-17 02:40:00.0 1
 
2.5%
2019-12-11 02:40:00.0 1
 
2.5%
2021-11-20 00:22:44.0 1
 
2.5%
2021-02-07 02:40:00.0 1
 
2.5%
Other values (9) 9
22.5%

Length

2023-12-11T03:12:55.323057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 22
27.5%
23:59:59.0 22
27.5%
02:40:00.0 12
15.0%
2021-12-12 2
 
2.5%
2019-01-31 1
 
1.2%
2020-09-23 1
 
1.2%
2019-07-10 1
 
1.2%
00:23:33.0 1
 
1.2%
2020-07-23 1
 
1.2%
02:21:29.0 1
 
1.2%
Other values (16) 16
20.0%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
식품첨가물제조업
40 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

Length

2023-12-11T03:12:55.499980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:55.660751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)91.4%
Missing5
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean339078.83
Minimum330023.3
Maximum354057.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:55.806379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330023.3
5-th percentile331091.92
Q1334294.92
median338792.59
Q3344200.36
95-th percentile347074.26
Maximum354057.06
Range24033.762
Interquartile range (IQR)9905.4378

Descriptive statistics

Standard deviation6040.3768
Coefficient of variation (CV)0.017814078
Kurtosis-0.61220113
Mean339078.83
Median Absolute Deviation (MAD)5526.9277
Skewness0.39280841
Sum11867759
Variance36486151
MonotonicityNot monotonic
2023-12-11T03:12:55.988646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
330023.299301 2
 
5.0%
345860.31498 2
 
5.0%
336398.016153 2
 
5.0%
335504.298406 1
 
2.5%
335660.262521 1
 
2.5%
335334.429366 1
 
2.5%
332716.315723 1
 
2.5%
332256.882943 1
 
2.5%
339604.060667 1
 
2.5%
333265.664044 1
 
2.5%
Other values (22) 22
55.0%
(Missing) 5
 
12.5%
ValueCountFrequency (%)
330023.299301 2
5.0%
331549.895399 1
2.5%
332256.882943 1
2.5%
332289.538416 1
2.5%
332506.529811 1
2.5%
332716.315723 1
2.5%
332803.386147 1
2.5%
333265.664044 1
2.5%
335324.183515 1
2.5%
335334.429366 1
2.5%
ValueCountFrequency (%)
354057.061461 1
2.5%
347546.799156 1
2.5%
346871.742988 1
2.5%
346717.496771 1
2.5%
346695.65185 1
2.5%
345860.31498 2
5.0%
344778.061422 1
2.5%
344360.92096 1
2.5%
344039.802161 1
2.5%
343831.4029 1
2.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)91.4%
Missing5
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean261184.54
Minimum249041.86
Maximum271660.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:56.181577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249041.86
5-th percentile249347.45
Q1258731.02
median261606.57
Q3265718.43
95-th percentile269314.12
Maximum271660.6
Range22618.745
Interquartile range (IQR)6987.4022

Descriptive statistics

Standard deviation6219.4685
Coefficient of variation (CV)0.023812545
Kurtosis-0.3533469
Mean261184.54
Median Absolute Deviation (MAD)3678.0037
Skewness-0.56594767
Sum9141458.9
Variance38681789
MonotonicityNot monotonic
2023-12-11T03:12:56.343408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
255804.872552 2
 
5.0%
258731.024724 2
 
5.0%
260311.428495 2
 
5.0%
261606.568343 1
 
2.5%
258963.271546 1
 
2.5%
261589.453297 1
 
2.5%
249300.581566 1
 
2.5%
269547.192353 1
 
2.5%
259439.182384 1
 
2.5%
250134.80573 1
 
2.5%
Other values (22) 22
55.0%
(Missing) 5
 
12.5%
ValueCountFrequency (%)
249041.859159 1
2.5%
249300.581566 1
2.5%
249367.53852 1
2.5%
250052.269534 1
2.5%
250134.80573 1
2.5%
255804.872552 2
5.0%
256884.837128 1
2.5%
258731.024724 2
5.0%
258963.271546 1
2.5%
259383.277395 1
2.5%
ValueCountFrequency (%)
271660.604411 1
2.5%
269547.192353 1
2.5%
269214.234995 1
2.5%
269165.84039 1
2.5%
267516.161613 1
2.5%
267419.098375 1
2.5%
266670.09756 1
2.5%
266430.044264 1
2.5%
266152.28177 1
2.5%
265284.572044 1
2.5%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
식품첨가물제조업
40 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

Length

2023-12-11T03:12:56.501426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:56.640192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품첨가물제조업 40
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
36 
0
4 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
90.0%
0 4
 
10.0%

Length

2023-12-11T03:12:56.815572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:57.000561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
90.0%
0 4
 
10.0%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
36 
0
4 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
90.0%
0 4
 
10.0%

Length

2023-12-11T03:12:57.164735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:57.325372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
90.0%
0 4
 
10.0%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

급수시설구분명
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
21 
상수도전용
19 

Length

Max length5
Median length4
Mean length4.475
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
52.5%
상수도전용 19
47.5%

Length

2023-12-11T03:12:57.487092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:57.626099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
52.5%
상수도전용 19
47.5%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
36 
0
4 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
90.0%
0 4
 
10.0%

Length

2023-12-11T03:12:57.791298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:57.917272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
90.0%
0 4
 
10.0%

본사종업원수
Categorical

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
25 
<NA>
14 
1
 
1

Length

Max length4
Median length1
Mean length2.05
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 25
62.5%
<NA> 14
35.0%
1 1
 
2.5%

Length

2023-12-11T03:12:58.037044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:58.161525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
62.5%
na 14
35.0%
1 1
 
2.5%

공장사무직종업원수
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
18 
<NA>
11 
1
6 
2
4 
9
 
1

Length

Max length4
Median length1
Mean length1.825
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row0
2nd row2
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 18
45.0%
<NA> 11
27.5%
1 6
 
15.0%
2 4
 
10.0%
9 1
 
2.5%

Length

2023-12-11T03:12:58.280710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:58.439263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
45.0%
na 11
27.5%
1 6
 
15.0%
2 4
 
10.0%
9 1
 
2.5%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
23 
<NA>
14 
1
 
2
5
 
1

Length

Max length4
Median length1
Mean length2.05
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
57.5%
<NA> 14
35.0%
1 2
 
5.0%
5 1
 
2.5%

Length

2023-12-11T03:12:58.589993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:58.725583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
57.5%
na 14
35.0%
1 2
 
5.0%
5 1
 
2.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)20.7%
Missing11
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean1.862069
Minimum0
Maximum19
Zeros16
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:12:58.877231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8.4
Maximum19
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.0242492
Coefficient of variation (CV)2.1611708
Kurtosis12.080198
Mean1.862069
Median Absolute Deviation (MAD)0
Skewness3.3007084
Sum54
Variance16.194581
MonotonicityNot monotonic
2023-12-11T03:12:59.022653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 16
40.0%
1 5
 
12.5%
2 4
 
10.0%
6 2
 
5.0%
19 1
 
2.5%
10 1
 
2.5%
(Missing) 11
27.5%
ValueCountFrequency (%)
0 16
40.0%
1 5
 
12.5%
2 4
 
10.0%
6 2
 
5.0%
10 1
 
2.5%
19 1
 
2.5%
ValueCountFrequency (%)
19 1
 
2.5%
10 1
 
2.5%
6 2
 
5.0%
2 4
 
10.0%
1 5
 
12.5%
0 16
40.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
28 
임대
8 
자가
4 

Length

Max length4
Median length4
Mean length3.4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
70.0%
임대 8
 
20.0%
자가 4
 
10.0%

Length

2023-12-11T03:12:59.191613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:59.344615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
70.0%
임대 8
 
20.0%
자가 4
 
10.0%

보증액
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
25 
0
13 
500000
 
1
13000000
 
1

Length

Max length8
Median length4
Mean length3.175
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row500000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
62.5%
0 13
32.5%
500000 1
 
2.5%
13000000 1
 
2.5%

Length

2023-12-11T03:12:59.531734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:59.692008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
62.5%
0 13
32.5%
500000 1
 
2.5%
13000000 1
 
2.5%

월세액
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
25 
0
13 
250000
 
1
1300000
 
1

Length

Max length7
Median length4
Mean length3.15
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row250000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
62.5%
0 13
32.5%
250000 1
 
2.5%
1300000 1
 
2.5%

Length

2023-12-11T03:12:59.864736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:13:00.003537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
62.5%
0 13
32.5%
250000 1
 
2.5%
1300000 1
 
2.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size172.0 B
False
40 
ValueCountFrequency (%)
False 40
100.0%
2023-12-11T03:13:00.174585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.42
Minimum0
Maximum299.3
Zeros33
Zeros (%)82.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T03:13:00.289150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile37.375
Maximum299.3
Range299.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47.958584
Coefficient of variation (CV)4.6025513
Kurtosis36.152845
Mean10.42
Median Absolute Deviation (MAD)0
Skewness5.9141345
Sum416.8
Variance2300.0258
MonotonicityNot monotonic
2023-12-11T03:13:00.429141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 33
82.5%
299.3 1
 
2.5%
54.0 1
 
2.5%
6.46 1
 
2.5%
2.5 1
 
2.5%
7.5 1
 
2.5%
36.5 1
 
2.5%
10.54 1
 
2.5%
ValueCountFrequency (%)
0.0 33
82.5%
2.5 1
 
2.5%
6.46 1
 
2.5%
7.5 1
 
2.5%
10.54 1
 
2.5%
36.5 1
 
2.5%
54.0 1
 
2.5%
299.3 1
 
2.5%
ValueCountFrequency (%)
299.3 1
 
2.5%
54.0 1
 
2.5%
36.5 1
 
2.5%
10.54 1
 
2.5%
7.5 1
 
2.5%
6.46 1
 
2.5%
2.5 1
 
2.5%
0.0 33
82.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)100.0%
Memory size492.0 B

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품첨가물제조업07_22_12_P34200003420000-108-2011-0000120111229<NA>3폐업2폐업20130906<NA><NA><NA>053 981 388629.00701807대구광역시 동구 불로동 1074-6번지대구광역시 동구 방천로6길 36 (불로동)41042매봉산야초건강원20120213102837I2018-08-31 23:59:59.0식품첨가물제조업347546.799156267516.161613식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
12식품첨가물제조업07_22_12_P34200003420000-108-2014-0000120141113<NA>3폐업2폐업20170731<NA><NA><NA>053 965 6581305.00701260대구광역시 동구 율암동 1103-13번지대구광역시 동구 매여로 62, 1층 (율암동)41065(주)프리나20170731092211I2018-08-31 23:59:59.0식품첨가물제조업354057.061461266430.044264식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0201임대<NA><NA>N0.0<NA><NA><NA>
23식품첨가물제조업07_22_12_P34300003430000-108-2011-0000220040705<NA>1영업/정상1영업<NA><NA><NA><NA>053 523758959.51703831대구광역시 서구 중리동 40-13번지대구광역시 서구 서대구로25길 19 (중리동)41833생림목초20140113104126I2018-08-31 23:59:59.0식품첨가물제조업340106.419865264328.378105식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA>500000250000N0.0<NA><NA><NA>
34식품첨가물제조업07_22_12_P34300003430000-108-2019-0000120190220<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.48703833대구광역시 서구 중리동 1066대구광역시 서구 국채보상로20길 32 (중리동)41841일지스타치20201104165418U2020-11-06 02:40:00.0식품첨가물제조업339071.996961263926.624081식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45식품첨가물제조업07_22_12_P34300003430000-108-2019-0000220190926<NA>1영업/정상1영업<NA><NA><NA><NA><NA>494.00703833대구광역시 서구 중리동 905-10번지대구광역시 서구 와룡로73길 57-6 (중리동)41755뉴트리디언20190926175229I2019-09-28 02:22:39.0식품첨가물제조업338275.809658264083.230571식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N299.3<NA><NA><NA>
56식품첨가물제조업07_22_12_P34300003430000-108-2011-0000420091231<NA>3폐업2폐업20101201<NA><NA><NA>0535656597580.00703830대구광역시 서구 이현동 42-432번지 1층<NA><NA>(주)에듀커뮤니티20101202230409I2018-08-31 23:59:59.0식품첨가물제조업338792.591731264580.761583식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA>00N0.0<NA><NA><NA>
67식품첨가물제조업07_22_12_P34300003430000-108-2011-0000320060320<NA>3폐업2폐업20200619<NA><NA><NA>053 56526001,252.25703830대구광역시 서구 이현동 42-82번지대구광역시 서구 문화로 121 (이현동)41758감로바이오산업(주)20200618172638U2020-06-20 02:40:00.0식품첨가물제조업339525.522508264887.686661식품첨가물제조업<NA><NA><NA><NA><NA><NA>01019<NA><NA><NA>N54.0<NA><NA><NA>
78식품첨가물제조업07_22_12_P34300003430000-108-2011-0000119981111<NA>3폐업2폐업20071026<NA><NA><NA>0535671635.00703110대구광역시 서구 이현동 44-33번지<NA><NA>감로바이오산업20071228112953I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
89식품첨가물제조업07_22_12_P34400003440000-108-2011-0000119990422<NA>3폐업2폐업20060612<NA><NA><NA><NA><NA><NA>대구광역시<NA><NA>삼진식품20060818222941I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA>00N0.0<NA><NA><NA>
910식품첨가물제조업07_22_12_P34400003440000-108-2012-0000120120313<NA>3폐업2폐업20161124<NA><NA><NA>1566272366.49705800대구광역시 남구 대명동 2014-203번지대구광역시 남구 중앙대로48길 35-6, 1층 (대명동)42424미남메디칼20160526145651I2018-08-31 23:59:59.0식품첨가물제조업343831.4029262564.892455식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N6.46<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
3031식품첨가물제조업07_22_12_P34800003480000-108-2020-0000120200214<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.50711822대구광역시 달성군 하빈면 무등리 587-5대구광역시 달성군 하빈면 하빈로140길 62-5, 1층42901대광바이오20211210173449U2021-12-12 02:40:00.0식품첨가물제조업332256.882943269547.192353식품첨가물제조업00<NA><NA>상수도전용01101임대00N0.0<NA><NA><NA>
3132식품첨가물제조업07_22_12_P34800003480000-108-2020-0000220200721<NA>1영업/정상1영업<NA><NA><NA><NA>053 616 5171183.25711855대구광역시 달성군 논공읍 본리리 29-69대구광역시 달성군 논공읍 논공중앙로 40642983(주)피앤디코스켐20200721170231I2020-07-23 00:23:33.0식품첨가물제조업333265.664044250134.80573식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA><NA>9<NA>10자가<NA><NA>N0.0<NA><NA><NA>
3233식품첨가물제조업07_22_12_P34800003480000-108-2011-0000820070726<NA>1영업/정상1영업<NA><NA><NA><NA>053 592 066163.00711811대구광역시 달성군 다사읍 이천리 568-2번지대구광역시 달성군 다사읍 다사로71길 3942907동창C&F20160422161623I2018-08-31 23:59:59.0식품첨가물제조업332289.538416266670.09756식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
3334식품첨가물제조업07_22_12_P34800003480000-108-2018-0000120180306<NA>1영업/정상1영업<NA><NA><NA><NA>053 614 1331443.66711855대구광역시 달성군 논공읍 본리리 1189-10번지대구광역시 달성군 논공읍 논공로 63142981태성푸드20190708111912U2019-07-10 02:40:00.0식품첨가물제조업331549.895399249367.53852식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N10.54<NA><NA><NA>
3435식품첨가물제조업07_22_12_P34800003480000-108-2011-0000219970410<NA>1영업/정상1영업<NA><NA><NA><NA>053 616 4454396.00711852대구광역시 달성군 논공읍 북리 1-59대구광역시 달성군 논공읍 논공중앙로54길 3842983유청식품20200921112048U2020-09-23 02:40:00.0식품첨가물제조업332506.529811249041.859159식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0116자가00N0.0<NA><NA><NA>
3536식품첨가물제조업07_22_12_P34800003480000-108-2011-0000320021024<NA>1영업/정상1영업<NA><NA><NA><NA>053 767 3385118.50711864대구광역시 달성군 가창면 용계리 95-2번지 1층대구광역시 달성군 가창면 가창로216길 11 (1층)42934한솔푸드테크놀로지20160128191758I2018-08-31 23:59:59.0식품첨가물제조업346695.65185256884.837128식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA>00N0.0<NA><NA><NA>
3637식품첨가물제조업07_22_12_P34800003480000-108-2011-0000720030123<NA>3폐업2폐업20040914<NA><NA><NA>0536156904.00711843대구광역시 달성군 옥포면 교항리 1068번지<NA><NA>명성식품20060818222941I2018-08-31 23:59:59.0식품첨가물제조업330023.299301255804.872552식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3738식품첨가물제조업07_22_12_P34800003480000-108-2011-0000520050120<NA>1영업/정상1영업<NA><NA><NA><NA>053 616 0432120.00711855대구광역시 달성군 논공읍 본리리 29-53번지대구광역시 달성군 논공읍 논공로71길 2742982미성20190816150339U2019-08-18 02:40:00.0식품첨가물제조업332803.386147250052.269534식품첨가물제조업<NA><NA><NA><NA>상수도전용<NA>0102임대<NA><NA>N0.0<NA><NA><NA>
3839식품첨가물제조업07_22_12_P34800003480000-108-2011-0000119890829<NA>3폐업2폐업20080625<NA><NA><NA>0536418493290.80711855대구광역시 달성군 논공읍 본리리 29-74번지<NA><NA>태경농산(주)20080625180001I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00N0.0<NA><NA><NA>
3940식품첨가물제조업07_22_12_P34800003480000-108-2011-0000620020103<NA>3폐업2폐업20041231<NA><NA><NA>0536100114<NA>711855대구광역시 달성군 논공읍 본리리<NA><NA>태경농산(주)20060818222941I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA>00N0.0<NA><NA><NA>