Overview

Dataset statistics

Number of variables47
Number of observations1978
Missing cells21965
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory784.4 KiB
Average record size in memory406.1 B

Variable types

Numeric11
Categorical19
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_08_P_식품소분업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085858&dataSetDetailId=DDI_0000085907&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (99.4%)Imbalance
위생업태명 is highly imbalanced (98.8%)Imbalance
남성종사자수 is highly imbalanced (96.2%)Imbalance
여성종사자수 is highly imbalanced (96.2%)Imbalance
본사종업원수 is highly imbalanced (58.5%)Imbalance
공장사무직종업원수 is highly imbalanced (58.1%)Imbalance
보증액 is highly imbalanced (89.0%)Imbalance
월세액 is highly imbalanced (93.9%)Imbalance
홈페이지 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 1978 (100.0%) missing valuesMissing
폐업일자 has 502 (25.4%) missing valuesMissing
휴업시작일자 has 1978 (100.0%) missing valuesMissing
휴업종료일자 has 1978 (100.0%) missing valuesMissing
재개업일자 has 1978 (100.0%) missing valuesMissing
소재지전화 has 710 (35.9%) missing valuesMissing
소재지면적 has 341 (17.2%) missing valuesMissing
도로명전체주소 has 908 (45.9%) missing valuesMissing
도로명우편번호 has 919 (46.5%) missing valuesMissing
좌표정보(X) has 86 (4.3%) missing valuesMissing
좌표정보(Y) has 86 (4.3%) missing valuesMissing
영업장주변구분명 has 1978 (100.0%) missing valuesMissing
등급구분명 has 1978 (100.0%) missing valuesMissing
총종업원수 has 1978 (100.0%) missing valuesMissing
공장생산직종업원수 has 589 (29.8%) missing valuesMissing
전통업소지정번호 has 1978 (100.0%) missing valuesMissing
전통업소주된음식 has 1978 (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
총종업원수 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
공장생산직종업원수 has 1194 (60.4%) zerosZeros
시설총규모 has 1906 (96.4%) zerosZeros

Reproduction

Analysis started2023-12-10 20:25:53.107381
Analysis finished2023-12-10 20:25:55.088968
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1978
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean989.5
Minimum1
Maximum1978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:25:55.223809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile99.85
Q1495.25
median989.5
Q31483.75
95-th percentile1879.15
Maximum1978
Range1977
Interquartile range (IQR)988.5

Descriptive statistics

Standard deviation571.14374
Coefficient of variation (CV)0.57720438
Kurtosis-1.2
Mean989.5
Median Absolute Deviation (MAD)494.5
Skewness0
Sum1957231
Variance326205.17
MonotonicityStrictly increasing
2023-12-11T05:25:55.450646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1330 1
 
0.1%
1328 1
 
0.1%
1327 1
 
0.1%
1326 1
 
0.1%
1325 1
 
0.1%
1324 1
 
0.1%
1323 1
 
0.1%
1322 1
 
0.1%
1321 1
 
0.1%
Other values (1968) 1968
99.5%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1978 1
0.1%
1977 1
0.1%
1976 1
0.1%
1975 1
0.1%
1974 1
0.1%
1973 1
0.1%
1972 1
0.1%
1971 1
0.1%
1970 1
0.1%
1969 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
식품소분업
1978 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1978
100.0%

Length

2023-12-11T05:25:55.685170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:55.841900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1978
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
07_22_08_P
1978 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_08_P
2nd row07_22_08_P
3rd row07_22_08_P
4th row07_22_08_P
5th row07_22_08_P

Common Values

ValueCountFrequency (%)
07_22_08_P 1978
100.0%

Length

2023-12-11T05:25:56.015911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:56.167400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 1978
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447922.1
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:25:56.296408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21576.229
Coefficient of variation (CV)0.0062577482
Kurtosis-1.0448935
Mean3447922.1
Median Absolute Deviation (MAD)20000
Skewness-0.36123564
Sum6.81999 × 109
Variance4.6553364 × 108
MonotonicityIncreasing
2023-12-11T05:25:56.448395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 435
22.0%
3470000 389
19.7%
3460000 285
14.4%
3420000 217
11.0%
3410000 205
10.4%
3430000 176
8.9%
3480000 155
 
7.8%
3440000 116
 
5.9%
ValueCountFrequency (%)
3410000 205
10.4%
3420000 217
11.0%
3430000 176
8.9%
3440000 116
 
5.9%
3450000 435
22.0%
3460000 285
14.4%
3470000 389
19.7%
3480000 155
 
7.8%
ValueCountFrequency (%)
3480000 155
 
7.8%
3470000 389
19.7%
3460000 285
14.4%
3450000 435
22.0%
3440000 116
 
5.9%
3430000 176
8.9%
3420000 217
11.0%
3410000 205
10.4%

관리번호
Text

UNIQUE 

Distinct1978
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-11T05:25:56.719496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters43516
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

Unique1978 ?
Unique (%)100.0%

Sample

1st row3410000-109-2009-00006
2nd row3410000-109-2014-00003
3rd row3410000-109-2014-00007
4th row3410000-109-2016-00004
5th row3410000-109-2017-00001
ValueCountFrequency (%)
3410000-109-2009-00006 1
 
0.1%
3460000-109-2002-00004 1
 
0.1%
3460000-109-2006-00004 1
 
0.1%
3460000-109-2015-00008 1
 
0.1%
3460000-109-2009-00004 1
 
0.1%
3460000-109-2009-00003 1
 
0.1%
3460000-109-2009-00002 1
 
0.1%
3460000-109-2009-00001 1
 
0.1%
3460000-109-2008-00008 1
 
0.1%
3460000-109-2008-00007 1
 
0.1%
Other values (1968) 1968
99.5%
2023-12-11T05:25:57.207570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20365
46.8%
- 5934
 
13.6%
1 4054
 
9.3%
2 2729
 
6.3%
3 2653
 
6.1%
4 2576
 
5.9%
9 2503
 
5.8%
5 858
 
2.0%
7 707
 
1.6%
6 673
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37582
86.4%
Dash Punctuation 5934
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20365
54.2%
1 4054
 
10.8%
2 2729
 
7.3%
3 2653
 
7.1%
4 2576
 
6.9%
9 2503
 
6.7%
5 858
 
2.3%
7 707
 
1.9%
6 673
 
1.8%
8 464
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 5934
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20365
46.8%
- 5934
 
13.6%
1 4054
 
9.3%
2 2729
 
6.3%
3 2653
 
6.1%
4 2576
 
5.9%
9 2503
 
5.8%
5 858
 
2.0%
7 707
 
1.6%
6 673
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20365
46.8%
- 5934
 
13.6%
1 4054
 
9.3%
2 2729
 
6.3%
3 2653
 
6.1%
4 2576
 
5.9%
9 2503
 
5.8%
5 858
 
2.0%
7 707
 
1.6%
6 673
 
1.5%

인허가일자
Real number (ℝ)

Distinct1597
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20081348
Minimum19790523
Maximum20200727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:25:57.442715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790523
5-th percentile19991120
Q120031031
median20080114
Q320131016
95-th percentile20190128
Maximum20200727
Range410204
Interquartile range (IQR)99985.5

Descriptive statistics

Standard deviation63565.125
Coefficient of variation (CV)0.0031653813
Kurtosis-0.12980893
Mean20081348
Median Absolute Deviation (MAD)49699.5
Skewness-0.10894913
Sum3.9720907 × 1010
Variance4.0405251 × 109
MonotonicityNot monotonic
2023-12-11T05:25:57.989294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030219 6
 
0.3%
20091015 5
 
0.3%
20131126 5
 
0.3%
20040827 5
 
0.3%
20021127 5
 
0.3%
20020404 4
 
0.2%
20140421 4
 
0.2%
20010910 4
 
0.2%
20040910 4
 
0.2%
20001124 4
 
0.2%
Other values (1587) 1932
97.7%
ValueCountFrequency (%)
19790523 1
0.1%
19791213 1
0.1%
19810727 1
0.1%
19850905 1
0.1%
19870905 1
0.1%
19890315 1
0.1%
19890318 1
0.1%
19900707 1
0.1%
19900711 1
0.1%
19900818 1
0.1%
ValueCountFrequency (%)
20200727 1
0.1%
20200723 1
0.1%
20200721 1
0.1%
20200715 1
0.1%
20200707 1
0.1%
20200706 1
0.1%
20200702 1
0.1%
20200630 1
0.1%
20200625 1
0.1%
20200622 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
3
1476 
1
502 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1476
74.6%
1 502
 
25.4%

Length

2023-12-11T05:25:58.190376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:58.320310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1476
74.6%
1 502
 
25.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
폐업
1476 
영업/정상
502 

Length

Max length5
Median length2
Mean length2.7613751
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1476
74.6%
영업/정상 502
 
25.4%

Length

2023-12-11T05:25:58.500060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:58.682162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1476
74.6%
영업/정상 502
 
25.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2
1476 
1
502 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1476
74.6%
1 502
 
25.4%

Length

2023-12-11T05:25:58.850209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:58.978085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1476
74.6%
1 502
 
25.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
폐업
1476 
영업
502 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1476
74.6%
영업 502
 
25.4%

Length

2023-12-11T05:25:59.116659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:59.247121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1476
74.6%
영업 502
 
25.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct1146
Distinct (%)77.6%
Missing502
Missing (%)25.4%
Infinite0
Infinite (%)0.0%
Mean20102481
Minimum20000919
Maximum20200831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:25:59.427223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000919
5-th percentile20030522
Q120060102
median20100204
Q320150118
95-th percentile20190710
Maximum20200831
Range199912
Interquartile range (IQR)90016.5

Descriptive statistics

Standard deviation51615.632
Coefficient of variation (CV)0.002567625
Kurtosis-1.1486578
Mean20102481
Median Absolute Deviation (MAD)48977
Skewness0.25539064
Sum2.9671262 × 1010
Variance2.6641735 × 109
MonotonicityNot monotonic
2023-12-11T05:25:59.701416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100512 8
 
0.4%
20080213 7
 
0.4%
20021224 6
 
0.3%
20050331 5
 
0.3%
20181227 5
 
0.3%
20051117 4
 
0.2%
20110620 4
 
0.2%
20050620 4
 
0.2%
20070306 4
 
0.2%
20040623 4
 
0.2%
Other values (1136) 1425
72.0%
(Missing) 502
 
25.4%
ValueCountFrequency (%)
20000919 1
0.1%
20010108 1
0.1%
20011017 1
0.1%
20020115 1
0.1%
20020128 1
0.1%
20020131 1
0.1%
20020219 1
0.1%
20020321 1
0.1%
20020403 1
0.1%
20020408 2
0.1%
ValueCountFrequency (%)
20200831 1
0.1%
20200826 1
0.1%
20200819 2
0.1%
20200811 1
0.1%
20200810 1
0.1%
20200724 1
0.1%
20200714 1
0.1%
20200709 1
0.1%
20200630 1
0.1%
20200626 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

소재지전화
Text

MISSING 

Distinct1157
Distinct (%)91.2%
Missing710
Missing (%)35.9%
Memory size15.6 KiB
2023-12-11T05:26:00.216396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.560726
Min length3

Characters and Unicode

Total characters13391
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

Unique1079 ?
Unique (%)85.1%

Sample

1st row053 5544411
2nd row07077179000
3rd row053 4247724
4th row053 7610600
5th row053 2533800
ValueCountFrequency (%)
053 879
33.2%
070 26
 
1.0%
312 13
 
0.5%
1234 10
 
0.4%
6602001 8
 
0.3%
313 8
 
0.3%
765 7
 
0.3%
986 7
 
0.3%
031 7
 
0.3%
625 6
 
0.2%
Other values (1307) 1675
63.3%
2023-12-11T05:26:01.017886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2100
15.7%
5 2050
15.3%
3 1858
13.9%
1385
10.3%
2 1042
7.8%
6 990
7.4%
1 882
6.6%
7 878
6.6%
8 798
 
6.0%
4 763
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12006
89.7%
Space Separator 1385
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2100
17.5%
5 2050
17.1%
3 1858
15.5%
2 1042
8.7%
6 990
8.2%
1 882
7.3%
7 878
7.3%
8 798
 
6.6%
4 763
 
6.4%
9 645
 
5.4%
Space Separator
ValueCountFrequency (%)
1385
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2100
15.7%
5 2050
15.3%
3 1858
13.9%
1385
10.3%
2 1042
7.8%
6 990
7.4%
1 882
6.6%
7 878
6.6%
8 798
 
6.0%
4 763
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2100
15.7%
5 2050
15.3%
3 1858
13.9%
1385
10.3%
2 1042
7.8%
6 990
7.4%
1 882
6.6%
7 878
6.6%
8 798
 
6.0%
4 763
 
5.7%

소재지면적
Text

MISSING 

Distinct858
Distinct (%)52.4%
Missing341
Missing (%)17.2%
Memory size15.6 KiB
2023-12-11T05:26:01.739733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.7080024
Min length3

Characters and Unicode

Total characters7707
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

Unique670 ?
Unique (%)40.9%

Sample

1st row24.79
2nd row43.50
3rd row.00
4th row3.30
5th row.00
ValueCountFrequency (%)
3.30 37
 
2.3%
4.00 36
 
2.2%
6.00 34
 
2.1%
6.60 32
 
2.0%
00 29
 
1.8%
3.00 29
 
1.8%
20.00 27
 
1.6%
12.00 26
 
1.6%
30.00 24
 
1.5%
33.00 22
 
1.3%
Other values (848) 1341
81.9%
2023-12-11T05:26:02.675177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1883
24.4%
. 1637
21.2%
1 653
 
8.5%
2 614
 
8.0%
3 544
 
7.1%
6 503
 
6.5%
4 461
 
6.0%
5 452
 
5.9%
9 335
 
4.3%
7 321
 
4.2%
Other values (2) 304
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6069
78.7%
Other Punctuation 1638
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1883
31.0%
1 653
 
10.8%
2 614
 
10.1%
3 544
 
9.0%
6 503
 
8.3%
4 461
 
7.6%
5 452
 
7.4%
9 335
 
5.5%
7 321
 
5.3%
8 303
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 1637
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 7707
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1883
24.4%
. 1637
21.2%
1 653
 
8.5%
2 614
 
8.0%
3 544
 
7.1%
6 503
 
6.5%
4 461
 
6.0%
5 452
 
5.9%
9 335
 
4.3%
7 321
 
4.2%
Other values (2) 304
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1883
24.4%
. 1637
21.2%
1 653
 
8.5%
2 614
 
8.0%
3 544
 
7.1%
6 503
 
6.5%
4 461
 
6.0%
5 452
 
5.9%
9 335
 
4.3%
7 321
 
4.2%
Other values (2) 304
 
3.9%

소재지우편번호
Real number (ℝ)

Distinct447
Distinct (%)22.8%
Missing16
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean704299.45
Minimum700040
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:02.987054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700040
5-th percentile700424.8
Q1702746
median703832.5
Q3705812.5
95-th percentile711832
Maximum711892
Range11852
Interquartile range (IQR)3066.5

Descriptive statistics

Standard deviation2825.886
Coefficient of variation (CV)0.0040123359
Kurtosis1.2235337
Mean704299.45
Median Absolute Deviation (MAD)1771.5
Skewness1.0895404
Sum1.3818355 × 109
Variance7985631.5
MonotonicityNot monotonic
2023-12-11T05:26:03.262493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 61
 
3.1%
704923 56
 
2.8%
702746 31
 
1.6%
704722 29
 
1.5%
700718 27
 
1.4%
700811 25
 
1.3%
700070 24
 
1.2%
702853 23
 
1.2%
706813 22
 
1.1%
711852 22
 
1.1%
Other values (437) 1642
83.0%
ValueCountFrequency (%)
700040 1
 
0.1%
700060 1
 
0.1%
700070 24
1.2%
700082 4
 
0.2%
700092 21
1.1%
700093 1
 
0.1%
700111 3
 
0.2%
700180 12
0.6%
700191 1
 
0.1%
700192 1
 
0.1%
ValueCountFrequency (%)
711892 3
0.2%
711891 1
 
0.1%
711874 3
0.2%
711873 1
 
0.1%
711872 1
 
0.1%
711864 3
0.2%
711863 1
 
0.1%
711861 1
 
0.1%
711858 1
 
0.1%
711855 5
0.3%
Distinct1666
Distinct (%)84.4%
Missing4
Missing (%)0.2%
Memory size15.6 KiB
2023-12-11T05:26:03.775382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length26.605876
Min length17

Characters and Unicode

Total characters52520
Distinct characters290
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1512 ?
Unique (%)76.6%

Sample

1st row대구광역시 중구 대신동 0115-0030번지 동산상가1층 139,140호
2nd row대구광역시 중구 달성동 0285-0006번지 지상1층
3rd row대구광역시 중구 대신동 1603번지 지상1층
4th row대구광역시 중구 삼덕동2가 0210-0001번지 진석타워 902호(S7호)
5th row대구광역시 중구 대봉동 0013-0007 지상1층
ValueCountFrequency (%)
대구광역시 1974
 
20.8%
북구 435
 
4.6%
달서구 388
 
4.1%
수성구 284
 
3.0%
동구 218
 
2.3%
중구 205
 
2.2%
서구 176
 
1.9%
달성군 154
 
1.6%
남구 114
 
1.2%
지상1층 94
 
1.0%
Other values (1980) 5431
57.3%
2023-12-11T05:26:04.763189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9430
18.0%
3880
 
7.4%
2548
 
4.9%
1 2440
 
4.6%
2301
 
4.4%
2292
 
4.4%
2025
 
3.9%
1976
 
3.8%
1976
 
3.8%
1951
 
3.7%
Other values (280) 21701
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30084
57.3%
Decimal Number 10771
 
20.5%
Space Separator 9430
 
18.0%
Dash Punctuation 1510
 
2.9%
Open Punctuation 255
 
0.5%
Close Punctuation 251
 
0.5%
Other Punctuation 110
 
0.2%
Uppercase Letter 102
 
0.2%
Math Symbol 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3880
 
12.9%
2548
 
8.5%
2301
 
7.6%
2292
 
7.6%
2025
 
6.7%
1976
 
6.6%
1976
 
6.6%
1951
 
6.5%
726
 
2.4%
648
 
2.2%
Other values (249) 9761
32.4%
Uppercase Letter
ValueCountFrequency (%)
A 54
52.9%
B 33
32.4%
C 5
 
4.9%
T 2
 
2.0%
S 2
 
2.0%
E 1
 
1.0%
G 1
 
1.0%
L 1
 
1.0%
K 1
 
1.0%
M 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 2440
22.7%
0 1728
16.0%
2 1442
13.4%
3 1051
9.8%
5 919
 
8.5%
4 721
 
6.7%
7 666
 
6.2%
6 665
 
6.2%
8 604
 
5.6%
9 535
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 99
90.0%
. 10
 
9.1%
@ 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
9430
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1510
100.0%
Open Punctuation
ValueCountFrequency (%)
( 255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 251
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30082
57.3%
Common 22331
42.5%
Latin 105
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3880
 
12.9%
2548
 
8.5%
2301
 
7.6%
2292
 
7.6%
2025
 
6.7%
1976
 
6.6%
1976
 
6.6%
1951
 
6.5%
726
 
2.4%
648
 
2.2%
Other values (248) 9759
32.4%
Common
ValueCountFrequency (%)
9430
42.2%
1 2440
 
10.9%
0 1728
 
7.7%
- 1510
 
6.8%
2 1442
 
6.5%
3 1051
 
4.7%
5 919
 
4.1%
4 721
 
3.2%
7 666
 
3.0%
6 665
 
3.0%
Other values (8) 1759
 
7.9%
Latin
ValueCountFrequency (%)
A 54
51.4%
B 33
31.4%
C 5
 
4.8%
T 2
 
1.9%
e 2
 
1.9%
S 2
 
1.9%
E 1
 
1.0%
G 1
 
1.0%
L 1
 
1.0%
K 1
 
1.0%
Other values (3) 3
 
2.9%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30082
57.3%
ASCII 22436
42.7%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9430
42.0%
1 2440
 
10.9%
0 1728
 
7.7%
- 1510
 
6.7%
2 1442
 
6.4%
3 1051
 
4.7%
5 919
 
4.1%
4 721
 
3.2%
7 666
 
3.0%
6 665
 
3.0%
Other values (21) 1864
 
8.3%
Hangul
ValueCountFrequency (%)
3880
 
12.9%
2548
 
8.5%
2301
 
7.6%
2292
 
7.6%
2025
 
6.7%
1976
 
6.6%
1976
 
6.6%
1951
 
6.5%
726
 
2.4%
648
 
2.2%
Other values (248) 9759
32.4%
CJK
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct1035
Distinct (%)96.7%
Missing908
Missing (%)45.9%
Memory size15.6 KiB
2023-12-11T05:26:05.441844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length29.205607
Min length19

Characters and Unicode

Total characters31250
Distinct characters303
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1006 ?
Unique (%)94.0%

Sample

1st row대구광역시 중구 큰장로26길 65 (대신동, 동산상가1층 139,140호)
2nd row대구광역시 중구 달성공원로10길 11 (달성동, 지상1층)
3rd row대구광역시 중구 큰장로 52, 지상1층 (대신동)
4th row대구광역시 중구 동덕로 115 (삼덕동2가, 진석타워 902호(S7호))
5th row대구광역시 중구 달구벌대로 2220 (대봉동, 지상1층)
ValueCountFrequency (%)
대구광역시 1070
 
17.1%
1층 293
 
4.7%
북구 231
 
3.7%
달서구 220
 
3.5%
동구 148
 
2.4%
수성구 142
 
2.3%
달성군 91
 
1.5%
서구 87
 
1.4%
남구 81
 
1.3%
2층 71
 
1.1%
Other values (1516) 3810
61.0%
2023-12-11T05:26:06.386301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5175
 
16.6%
2178
 
7.0%
1395
 
4.5%
1378
 
4.4%
1 1373
 
4.4%
1117
 
3.6%
1076
 
3.4%
1072
 
3.4%
( 1058
 
3.4%
) 1058
 
3.4%
Other values (293) 14370
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18023
57.7%
Space Separator 5175
 
16.6%
Decimal Number 4838
 
15.5%
Open Punctuation 1058
 
3.4%
Close Punctuation 1058
 
3.4%
Other Punctuation 792
 
2.5%
Dash Punctuation 205
 
0.7%
Uppercase Letter 95
 
0.3%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2178
 
12.1%
1395
 
7.7%
1378
 
7.6%
1117
 
6.2%
1076
 
6.0%
1072
 
5.9%
1031
 
5.7%
597
 
3.3%
571
 
3.2%
445
 
2.5%
Other values (265) 7163
39.7%
Uppercase Letter
ValueCountFrequency (%)
A 47
49.5%
B 32
33.7%
C 4
 
4.2%
E 3
 
3.2%
T 3
 
3.2%
S 1
 
1.1%
R 1
 
1.1%
W 1
 
1.1%
M 1
 
1.1%
P 1
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 1373
28.4%
2 715
14.8%
3 547
 
11.3%
4 393
 
8.1%
5 345
 
7.1%
0 336
 
6.9%
6 318
 
6.6%
7 297
 
6.1%
8 275
 
5.7%
9 239
 
4.9%
Space Separator
ValueCountFrequency (%)
5175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1058
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1058
100.0%
Other Punctuation
ValueCountFrequency (%)
, 792
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18023
57.7%
Common 13130
42.0%
Latin 97
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2178
 
12.1%
1395
 
7.7%
1378
 
7.6%
1117
 
6.2%
1076
 
6.0%
1072
 
5.9%
1031
 
5.7%
597
 
3.3%
571
 
3.2%
445
 
2.5%
Other values (265) 7163
39.7%
Common
ValueCountFrequency (%)
5175
39.4%
1 1373
 
10.5%
( 1058
 
8.1%
) 1058
 
8.1%
, 792
 
6.0%
2 715
 
5.4%
3 547
 
4.2%
4 393
 
3.0%
5 345
 
2.6%
0 336
 
2.6%
Other values (6) 1338
 
10.2%
Latin
ValueCountFrequency (%)
A 47
48.5%
B 32
33.0%
C 4
 
4.1%
E 3
 
3.1%
T 3
 
3.1%
e 2
 
2.1%
S 1
 
1.0%
R 1
 
1.0%
W 1
 
1.0%
M 1
 
1.0%
Other values (2) 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18023
57.7%
ASCII 13227
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5175
39.1%
1 1373
 
10.4%
( 1058
 
8.0%
) 1058
 
8.0%
, 792
 
6.0%
2 715
 
5.4%
3 547
 
4.1%
4 393
 
3.0%
5 345
 
2.6%
0 336
 
2.5%
Other values (18) 1435
 
10.8%
Hangul
ValueCountFrequency (%)
2178
 
12.1%
1395
 
7.7%
1378
 
7.6%
1117
 
6.2%
1076
 
6.0%
1072
 
5.9%
1031
 
5.7%
597
 
3.3%
571
 
3.2%
445
 
2.5%
Other values (265) 7163
39.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct581
Distinct (%)54.9%
Missing919
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean42031.94
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:06.678539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41091
Q141488
median41965
Q342637
95-th percentile42945.1
Maximum43024
Range2024
Interquartile range (IQR)1149

Descriptive statistics

Standard deviation605.81683
Coefficient of variation (CV)0.014413249
Kurtosis-1.311979
Mean42031.94
Median Absolute Deviation (MAD)507
Skewness0.016877537
Sum44511824
Variance367014.03
MonotonicityNot monotonic
2023-12-11T05:26:06.943726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41488 27
 
1.4%
42637 24
 
1.2%
41485 21
 
1.1%
41490 15
 
0.8%
41557 12
 
0.6%
41936 8
 
0.4%
41927 7
 
0.4%
42945 7
 
0.4%
41582 7
 
0.4%
41581 6
 
0.3%
Other values (571) 925
46.8%
(Missing) 919
46.5%
ValueCountFrequency (%)
41000 3
0.2%
41001 1
 
0.1%
41002 3
0.2%
41007 1
 
0.1%
41009 3
0.2%
41020 2
0.1%
41026 4
0.2%
41028 1
 
0.1%
41035 1
 
0.1%
41036 1
 
0.1%
ValueCountFrequency (%)
43024 1
 
0.1%
43023 2
0.1%
43013 1
 
0.1%
43011 3
0.2%
43005 1
 
0.1%
43004 1
 
0.1%
43003 2
0.1%
42993 1
 
0.1%
42989 1
 
0.1%
42986 2
0.1%
Distinct1548
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-11T05:26:07.440879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length5.9782609
Min length2

Characters and Unicode

Total characters11825
Distinct characters563
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1341 ?
Unique (%)67.8%

Sample

1st row대성수입
2nd row정선양봉원
3rd row(주)오성에프디
4th row(주)에이지블루
5th row최고식품
ValueCountFrequency (%)
주식회사 25
 
1.2%
대백마트 20
 
0.9%
개미농특산 14
 
0.7%
궁전방식품 11
 
0.5%
일해식품(주 9
 
0.4%
조은식품 9
 
0.4%
서문떡방 9
 
0.4%
주)바다누리 8
 
0.4%
우리농수산 8
 
0.4%
오케이포인트마트 7
 
0.3%
Other values (1608) 2009
94.4%
2023-12-11T05:26:08.288767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469
 
4.0%
) 404
 
3.4%
( 400
 
3.4%
392
 
3.3%
384
 
3.2%
358
 
3.0%
356
 
3.0%
219
 
1.9%
210
 
1.8%
202
 
1.7%
Other values (553) 8431
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10656
90.1%
Close Punctuation 404
 
3.4%
Open Punctuation 400
 
3.4%
Space Separator 151
 
1.3%
Uppercase Letter 108
 
0.9%
Lowercase Letter 54
 
0.5%
Decimal Number 34
 
0.3%
Other Punctuation 11
 
0.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
469
 
4.4%
392
 
3.7%
384
 
3.6%
358
 
3.4%
356
 
3.3%
219
 
2.1%
210
 
2.0%
202
 
1.9%
200
 
1.9%
165
 
1.5%
Other values (499) 7701
72.3%
Uppercase Letter
ValueCountFrequency (%)
S 13
12.0%
O 13
12.0%
D 13
12.0%
K 11
10.2%
F 10
9.3%
G 7
 
6.5%
C 6
 
5.6%
M 5
 
4.6%
B 5
 
4.6%
N 4
 
3.7%
Other values (11) 21
19.4%
Lowercase Letter
ValueCountFrequency (%)
o 10
18.5%
e 8
14.8%
n 5
9.3%
y 5
9.3%
d 4
 
7.4%
s 3
 
5.6%
t 3
 
5.6%
a 3
 
5.6%
l 3
 
5.6%
w 3
 
5.6%
Other values (6) 7
13.0%
Decimal Number
ValueCountFrequency (%)
1 7
20.6%
2 5
14.7%
0 5
14.7%
4 4
11.8%
9 4
11.8%
3 3
8.8%
7 3
8.8%
8 1
 
2.9%
5 1
 
2.9%
6 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 5
45.5%
& 5
45.5%
, 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 404
100.0%
Open Punctuation
ValueCountFrequency (%)
( 400
100.0%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10656
90.1%
Common 1007
 
8.5%
Latin 162
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
469
 
4.4%
392
 
3.7%
384
 
3.6%
358
 
3.4%
356
 
3.3%
219
 
2.1%
210
 
2.0%
202
 
1.9%
200
 
1.9%
165
 
1.5%
Other values (499) 7701
72.3%
Latin
ValueCountFrequency (%)
S 13
 
8.0%
O 13
 
8.0%
D 13
 
8.0%
K 11
 
6.8%
o 10
 
6.2%
F 10
 
6.2%
e 8
 
4.9%
G 7
 
4.3%
C 6
 
3.7%
M 5
 
3.1%
Other values (27) 66
40.7%
Common
ValueCountFrequency (%)
) 404
40.1%
( 400
39.7%
151
 
15.0%
- 7
 
0.7%
1 7
 
0.7%
2 5
 
0.5%
0 5
 
0.5%
. 5
 
0.5%
& 5
 
0.5%
4 4
 
0.4%
Other values (7) 14
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10655
90.1%
ASCII 1169
 
9.9%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
469
 
4.4%
392
 
3.7%
384
 
3.6%
358
 
3.4%
356
 
3.3%
219
 
2.1%
210
 
2.0%
202
 
1.9%
200
 
1.9%
165
 
1.5%
Other values (498) 7700
72.3%
ASCII
ValueCountFrequency (%)
) 404
34.6%
( 400
34.2%
151
 
12.9%
S 13
 
1.1%
O 13
 
1.1%
D 13
 
1.1%
K 11
 
0.9%
o 10
 
0.9%
F 10
 
0.9%
e 8
 
0.7%
Other values (44) 136
 
11.6%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1660
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0107322 × 1013
Minimum2.0010823 × 1013
Maximum2.0200831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:08.543476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0020725 × 1013
Q12.0050324 × 1013
median2.0110218 × 1013
Q32.0170215 × 1013
95-th percentile2.0191231 × 1013
Maximum2.0200831 × 1013
Range1.9000814 × 1011
Interquartile range (IQR)1.1989117 × 1011

Descriptive statistics

Standard deviation6.0352303 × 1010
Coefficient of variation (CV)0.0030015087
Kurtosis-1.4223908
Mean2.0107322 × 1013
Median Absolute Deviation (MAD)5.9896167 × 1010
Skewness0.053438259
Sum3.9772283 × 1016
Variance3.6424005 × 1021
MonotonicityNot monotonic
2023-12-11T05:26:08.823782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041011000000 34
 
1.7%
20020124000000 29
 
1.5%
20020725000000 13
 
0.7%
20050322000000 11
 
0.6%
20020527000000 10
 
0.5%
20021121000000 10
 
0.5%
20021012000000 10
 
0.5%
20030612000000 10
 
0.5%
20020528000000 10
 
0.5%
20010823000000 9
 
0.5%
Other values (1650) 1832
92.6%
ValueCountFrequency (%)
20010823000000 9
 
0.5%
20020124000000 29
1.5%
20020125000000 2
 
0.1%
20020207000000 1
 
0.1%
20020226000000 1
 
0.1%
20020228000000 1
 
0.1%
20020307000000 1
 
0.1%
20020320000000 1
 
0.1%
20020403000000 1
 
0.1%
20020413000000 2
 
0.1%
ValueCountFrequency (%)
20200831141445 1
0.1%
20200826113746 1
0.1%
20200824175738 1
0.1%
20200819153421 1
0.1%
20200819110204 1
0.1%
20200818151401 1
0.1%
20200811145521 1
0.1%
20200811113510 1
0.1%
20200811103013 1
0.1%
20200810162228 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
I
1700 
U
278 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1700
85.9%
U 278
 
14.1%

Length

2023-12-11T05:26:09.051597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:09.221980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1700
85.9%
u 278
 
14.1%
Distinct250
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Minimum2018-08-31 23:59:59
Maximum2020-09-02 02:40:00
2023-12-11T05:26:09.408494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:26:09.686134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
식품소분업
1977 
<NA>
 
1

Length

Max length5
Median length5
Mean length4.9994944
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1977
99.9%
<NA> 1
 
0.1%

Length

2023-12-11T05:26:09.903938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:10.065431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1977
99.9%
na 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1256
Distinct (%)66.4%
Missing86
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean342435.15
Minimum326848.48
Maximum356370.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:10.237287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326848.48
5-th percentile334094.08
Q1339047.79
median341881.01
Q3345663.6
95-th percentile353146.82
Maximum356370.49
Range29522.008
Interquartile range (IQR)6615.8065

Descriptive statistics

Standard deviation5282.503
Coefficient of variation (CV)0.015426287
Kurtosis0.30073083
Mean342435.15
Median Absolute Deviation (MAD)3151.2291
Skewness0.172987
Sum6.4788731 × 108
Variance27904838
MonotonicityNot monotonic
2023-12-11T05:26:10.479351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
345032.238221 51
 
2.6%
339047.793379 46
 
2.3%
339243.983122 30
 
1.5%
348194.499421 29
 
1.5%
338123.173581 29
 
1.5%
337916.079938 25
 
1.3%
343705.561002 22
 
1.1%
345663.599839 19
 
1.0%
344047.164924 16
 
0.8%
344066.98467 16
 
0.8%
Other values (1246) 1609
81.3%
(Missing) 86
 
4.3%
ValueCountFrequency (%)
326848.481791 1
0.1%
327437.783351 1
0.1%
327489.324167 1
0.1%
327531.565421 1
0.1%
327605.063942 1
0.1%
327637.398011 1
0.1%
328311.018298 1
0.1%
328332.000154 1
0.1%
328493.333555 1
0.1%
328797.873691 1
0.1%
ValueCountFrequency (%)
356370.489825 1
 
0.1%
356351.617491 1
 
0.1%
356347.076958 1
 
0.1%
356327.570046 1
 
0.1%
356325.339359 1
 
0.1%
356222.826617 1
 
0.1%
356082.08851 1
 
0.1%
355939.362329 7
0.4%
355875.122869 1
 
0.1%
355787.841952 2
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1256
Distinct (%)66.4%
Missing86
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean263339.64
Minimum238813.23
Maximum277755.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:10.734953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238813.23
5-th percentile256744.43
Q1261135.84
median263506.5
Q3265605.88
95-th percentile270820.4
Maximum277755.21
Range38941.98
Interquartile range (IQR)4470.0368

Descriptive statistics

Standard deviation4549.6119
Coefficient of variation (CV)0.017276594
Kurtosis4.1430652
Mean263339.64
Median Absolute Deviation (MAD)2191.7379
Skewness-0.92071245
Sum4.9823859 × 108
Variance20698969
MonotonicityNot monotonic
2023-12-11T05:26:10.935311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262949.871621 51
 
2.6%
258741.90218 46
 
2.3%
268026.454531 30
 
1.5%
259144.519321 29
 
1.5%
262253.34421 29
 
1.5%
262111.061698 25
 
1.3%
264056.630949 22
 
1.1%
263506.50013 19
 
1.0%
265132.987974 16
 
0.8%
264414.299416 16
 
0.8%
Other values (1246) 1609
81.3%
(Missing) 86
 
4.3%
ValueCountFrequency (%)
238813.226712 1
0.1%
238824.505921 1
0.1%
238893.362765 1
0.1%
238893.829912 1
0.1%
239536.919741 1
0.1%
242349.0 1
0.1%
243088.915629 2
0.1%
244299.117529 1
0.1%
244666.651946 1
0.1%
244744.379191 1
0.1%
ValueCountFrequency (%)
277755.206408 1
0.1%
277673.246368 1
0.1%
277008.50814 1
0.1%
276811.276708 1
0.1%
275582.004218 1
0.1%
274822.293106 1
0.1%
274594.894588 1
0.1%
274508.218106 2
0.1%
274053.957157 1
0.1%
274035.207096 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
식품소분업
1976 
<NA>
 
2

Length

Max length5
Median length5
Mean length4.9989889
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1976
99.9%
<NA> 2
 
0.1%

Length

2023-12-11T05:26:11.168050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:11.323308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1976
99.9%
na 2
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1970 
0
 
8

Length

Max length4
Median length4
Mean length3.9878665
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> 1970
99.6%
0 8
 
0.4%

Length

2023-12-11T05:26:11.463313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:12.002132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1970
99.6%
0 8
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1970 
0
 
8

Length

Max length4
Median length4
Mean length3.9878665
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> 1970
99.6%
0 8
 
0.4%

Length

2023-12-11T05:26:12.168122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:12.311751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1970
99.6%
0 8
 
0.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1294 
상수도전용
683 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.3458038
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1294
65.4%
상수도전용 683
34.5%
지하수전용 1
 
0.1%

Length

2023-12-11T05:26:12.490693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:12.661689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1294
65.4%
상수도전용 683
34.5%
지하수전용 1
 
0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1333 
<NA>
590 
1
 
45
2
 
6
3
 
3

Length

Max length4
Median length1
Mean length1.8948433
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1333
67.4%
<NA> 590
29.8%
1 45
 
2.3%
2 6
 
0.3%
3 3
 
0.2%
6 1
 
0.1%

Length

2023-12-11T05:26:12.823356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:13.041470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1333
67.4%
na 590
29.8%
1 45
 
2.3%
2 6
 
0.3%
3 3
 
0.2%
6 1
 
0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1364 
<NA>
590 
1
 
22
2
 
1
13
 
1

Length

Max length4
Median length1
Mean length1.8953488
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1364
69.0%
<NA> 590
29.8%
1 22
 
1.1%
2 1
 
0.1%
13 1
 
0.1%

Length

2023-12-11T05:26:13.320530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:13.507450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1364
69.0%
na 590
29.8%
1 22
 
1.1%
2 1
 
0.1%
13 1
 
0.1%
Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1227 
<NA>
591 
1
140 
2
 
15
3
 
4

Length

Max length4
Median length1
Mean length1.89636
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2
2nd row<NA>
3rd row<NA>
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 1227
62.0%
<NA> 591
29.9%
1 140
 
7.1%
2 15
 
0.8%
3 4
 
0.2%
4 1
 
0.1%

Length

2023-12-11T05:26:13.770931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:13.979888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1227
62.0%
na 591
29.9%
1 140
 
7.1%
2 15
 
0.8%
3 4
 
0.2%
4 1
 
0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing589
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean0.19942405
Minimum0
Maximum5
Zeros1194
Zeros (%)60.4%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:14.180435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55514332
Coefficient of variation (CV)2.7837331
Kurtosis12.75827
Mean0.19942405
Median Absolute Deviation (MAD)0
Skewness3.3065432
Sum277
Variance0.30818411
MonotonicityNot monotonic
2023-12-11T05:26:14.363379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1194
60.4%
1 130
 
6.6%
2 51
 
2.6%
3 12
 
0.6%
5 1
 
0.1%
4 1
 
0.1%
(Missing) 589
29.8%
ValueCountFrequency (%)
0 1194
60.4%
1 130
 
6.6%
2 51
 
2.6%
3 12
 
0.6%
4 1
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 1
 
0.1%
3 12
 
0.6%
2 51
 
2.6%
1 130
 
6.6%
0 1194
60.4%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1320 
임대
402 
자가
256 

Length

Max length4
Median length4
Mean length3.3346815
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1320
66.7%
임대 402
 
20.3%
자가 256
 
12.9%

Length

2023-12-11T05:26:14.593739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:14.841127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1320
66.7%
임대 402
 
20.3%
자가 256
 
12.9%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1949 
0
 
29

Length

Max length4
Median length4
Mean length3.9560162
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> 1949
98.5%
0 29
 
1.5%

Length

2023-12-11T05:26:15.088510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:15.285583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1949
98.5%
0 29
 
1.5%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1947 
0
 
29
1000000
 
1
1200000
 
1

Length

Max length7
Median length4
Mean length3.9590495
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1947
98.4%
0 29
 
1.5%
1000000 1
 
0.1%
1200000 1
 
0.1%

Length

2023-12-11T05:26:15.477524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:15.734027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1947
98.4%
0 29
 
1.5%
1000000 1
 
0.1%
1200000 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing1
Missing (%)0.1%
Memory size4.0 KiB
False
1977 
(Missing)
 
1
ValueCountFrequency (%)
False 1977
99.9%
(Missing) 1
 
0.1%
2023-12-11T05:26:15.882143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)3.2%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.69691452
Minimum0
Maximum122.56
Zeros1906
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T05:26:16.096264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum122.56
Range122.56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.7901621
Coefficient of variation (CV)8.3082817
Kurtosis207.41932
Mean0.69691452
Median Absolute Deviation (MAD)0
Skewness13.088178
Sum1377.8
Variance33.525978
MonotonicityNot monotonic
2023-12-11T05:26:16.344855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1906
96.4%
6.0 3
 
0.2%
3.3 3
 
0.2%
10.0 3
 
0.2%
3.0 2
 
0.1%
9.9 2
 
0.1%
9.2 1
 
0.1%
2.02 1
 
0.1%
3.75 1
 
0.1%
15.65 1
 
0.1%
Other values (54) 54
 
2.7%
ValueCountFrequency (%)
0.0 1906
96.4%
2.0 1
 
0.1%
2.02 1
 
0.1%
2.18 1
 
0.1%
2.53 1
 
0.1%
2.56 1
 
0.1%
2.7 1
 
0.1%
3.0 2
 
0.1%
3.3 3
 
0.2%
3.4 1
 
0.1%
ValueCountFrequency (%)
122.56 1
0.1%
104.92 1
0.1%
76.57 1
0.1%
72.46 1
0.1%
70.0 1
0.1%
66.0 1
0.1%
56.16 1
0.1%
53.22 1
0.1%
35.5 1
0.1%
34.7 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1978
Missing (%)100.0%
Memory size17.5 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1977 
53
 
1

Length

Max length4
Median length4
Mean length3.9989889
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1977
99.9%
53 1
 
0.1%

Length

2023-12-11T05:26:16.583335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:26:16.778230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1977
99.9%
53 1
 
0.1%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품소분업07_22_08_P34100003410000-109-2009-0000620090806<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.79700320대구광역시 중구 대신동 0115-0030번지 동산상가1층 139,140호대구광역시 중구 큰장로26길 65 (대신동, 동산상가1층 139,140호)41926대성수입20120723131146I2018-08-31 23:59:59.0식품소분업342780.445665264345.364396식품소분업<NA><NA><NA><NA><NA><NA>0020<NA><NA><NA>N0.0<NA><NA><NA>
12식품소분업07_22_08_P34100003410000-109-2014-0000320140926<NA>1영업/정상1영업<NA><NA><NA><NA>053 554441143.50700380대구광역시 중구 달성동 0285-0006번지 지상1층대구광역시 중구 달성공원로10길 11 (달성동, 지상1층)41923정선양봉원20140926100717I2018-08-31 23:59:59.0식품소분업342670.112565264925.063129식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23식품소분업07_22_08_P34100003410000-109-2014-0000720141216<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00700819대구광역시 중구 대신동 1603번지 지상1층대구광역시 중구 큰장로 52, 지상1층 (대신동)41930(주)오성에프디20191023171829U2019-10-25 02:40:00.0식품소분업342585.32336265118.16837식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
34식품소분업07_22_08_P34100003410000-109-2016-0000420160922<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30700412대구광역시 중구 삼덕동2가 0210-0001번지 진석타워 902호(S7호)대구광역시 중구 동덕로 115 (삼덕동2가, 진석타워 902호(S7호))41940(주)에이지블루20161108112424I2018-08-31 23:59:59.0식품소분업344686.259338263958.880864식품소분업<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
45식품소분업07_22_08_P34100003410000-109-2017-0000120170517<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00700809대구광역시 중구 대봉동 0013-0007 지상1층대구광역시 중구 달구벌대로 2220 (대봉동, 지상1층)41951최고식품20200715142254U2020-07-17 02:40:00.0식품소분업344979.554445263648.222881식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
56식품소분업07_22_08_P34100003410000-109-2017-0000220170518<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.52700320대구광역시 중구 대신동 0115-0364번지 지상1층대구광역시 중구 큰장로26길 40 (대신동, 지상1층)41927해청건어물백화점20170605103102I2018-08-31 23:59:59.0식품소분업342667.413894264279.131167식품소분업<NA><NA><NA><NA><NA><NA>0020<NA><NA><NA>N0.0<NA><NA><NA>
67식품소분업07_22_08_P34100003410000-109-2017-0000420170828<NA>1영업/정상1영업<NA><NA><NA><NA><NA>213.44700440대구광역시 중구 남산동 3006번지 반월당효성해링턴플레이스 301동 지하2층대구광역시 중구 중앙대로66길 20 (남산동, 반월당효성해링턴플레이스 301동 지하2층)41961(주)서원유통 탑마트 대구점20170828110052I2018-08-31 23:59:59.0식품소분업343902.080116263530.809939식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78식품소분업07_22_08_P34100003410000-109-2018-0000120180212<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.80700818대구광역시 중구 대신동 0876번지 지상 1층대구광역시 중구 달성로 5, 지상 1층 (대신동)41927대한농산20180212110340I2018-08-31 23:59:59.0식품소분업342823.541819263962.479035식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
89식품소분업07_22_08_P34100003410000-109-2018-0000220180605<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.00700230대구광역시 중구 남성로 0118번지 지상 2층대구광역시 중구 약령길 42, 지상 2층 (남성로)41933다소목20180612161553I2018-08-31 23:59:59.0식품소분업343453.665498264264.14957식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
910식품소분업07_22_08_P34100003410000-109-2018-0000320180713<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.00700111대구광역시 중구 태평로1가 0023-0001번지 태평아파트 1동 22호대구광역시 중구 태평로 205, 1동 지상 1층 22호 (태평로1가, 태평아파트)41903농업회사법인사계절주식회사20190607155216U2019-06-09 02:40:00.0식품소분업344466.007838264977.009084식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
19681969식품소분업07_22_08_P34800003480000-109-2006-0000620060703<NA>3폐업2폐업20120913<NA><NA><NA>053 61526337.00711874대구광역시 달성군 현풍면 원교리 16-2번지대구광역시 달성군 현풍면 비슬로128길 2143003자모건어물20060703000000I2018-08-31 23:59:59.0식품소분업330324.023854244744.379191식품소분업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
19691970식품소분업07_22_08_P34800003480000-109-2007-0000120070103<NA>3폐업2폐업20080612<NA><NA><NA><NA>116.50711833대구광역시 달성군 화원읍 설화리 523-2번지<NA><NA>주원푸드20080305140332I2018-08-31 23:59:59.0식품소분업334195.832289256467.905075식품소분업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
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19711972식품소분업07_22_08_P34800003480000-109-2007-0000320070412<NA>3폐업2폐업20070425<NA><NA><NA>053 6159441<NA>711842대구광역시 달성군 옥포면 강림리 473-3번지<NA><NA>가야푸드20070412000000I2018-08-31 23:59:59.0식품소분업329276.252773254407.881547식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
19721973식품소분업07_22_08_P34800003480000-109-2007-0000420070516<NA>3폐업2폐업20070530<NA><NA><NA>053 587669112.00711833대구광역시 달성군 화원읍 설화리 555번지<NA><NA>남해식품20070516000000I2018-08-31 23:59:59.0식품소분업334363.502587256515.655111식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
19731974식품소분업07_22_08_P34800003480000-109-2007-0000520070607<NA>3폐업2폐업20080514<NA><NA><NA><NA>3.20711833대구광역시 달성군 화원읍 설화리 555번지<NA><NA>재우종합식품20070607000000I2018-08-31 23:59:59.0식품소분업334363.502587256515.655111식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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19751976식품소분업07_22_08_P34800003480000-109-2007-0000720070911<NA>3폐업2폐업20091111<NA><NA><NA>053 616 000511.41711831대구광역시 달성군 화원읍 구라리 970번지<NA><NA>우리가20090710164014I2018-08-31 23:59:59.0식품소분업334572.761283258065.034099식품소분업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
19761977식품소분업07_22_08_P34800003480000-109-2007-0000820070918<NA>3폐업2폐업20111201<NA><NA><NA>053 641828212.00711831대구광역시 달성군 화원읍 구라리 1717번지 A동<NA><NA>대백마트(유천점)20101102150031I2018-08-31 23:59:59.0식품소분업336514.720192257816.048278식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
19771978식품소분업07_22_08_P34800003480000-109-2007-0000920071227<NA>3폐업2폐업20190417<NA><NA><NA>053 617755718.00<NA>대구광역시 달성군 현풍읍 하리 246-4번지 외 4필지대구광역시 달성군 현풍읍 현풍중앙로 40 (외 4필지)43005(주)서원유통 탑마트 현풍점20190417154716U2019-04-19 02:40:00.0식품소분업330717.496695244666.651946식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>