Overview

Dataset statistics

Number of variables47
Number of observations167
Missing cells2345
Missing cells (%)29.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.3 KiB
Average record size in memory406.8 B

Variable types

Numeric11
Categorical16
Text6
Unsupported12
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_09_P_식품운반업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000067918&dataSetDetailId=DDI_0000067975&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
보증액 is highly imbalanced (58.4%)Imbalance
월세액 is highly imbalanced (58.4%)Imbalance
시설총규모 is highly imbalanced (90.9%)Imbalance
인허가취소일자 has 167 (100.0%) missing valuesMissing
폐업일자 has 63 (37.7%) missing valuesMissing
휴업시작일자 has 167 (100.0%) missing valuesMissing
휴업종료일자 has 167 (100.0%) missing valuesMissing
재개업일자 has 167 (100.0%) missing valuesMissing
소재지전화 has 44 (26.3%) missing valuesMissing
소재지면적 has 17 (10.2%) missing valuesMissing
소재지우편번호 has 3 (1.8%) missing valuesMissing
도로명전체주소 has 56 (33.5%) missing valuesMissing
도로명우편번호 has 57 (34.1%) missing valuesMissing
좌표정보(X) has 9 (5.4%) missing valuesMissing
좌표정보(Y) has 9 (5.4%) missing valuesMissing
남성종사자수 has 167 (100.0%) missing valuesMissing
여성종사자수 has 167 (100.0%) missing valuesMissing
영업장주변구분명 has 167 (100.0%) missing valuesMissing
등급구분명 has 167 (100.0%) missing valuesMissing
총종업원수 has 167 (100.0%) missing valuesMissing
공장판매직종업원수 has 41 (24.6%) missing valuesMissing
공장생산직종업원수 has 42 (25.1%) missing valuesMissing
전통업소지정번호 has 167 (100.0%) missing valuesMissing
전통업소주된음식 has 167 (100.0%) missing valuesMissing
홈페이지 has 167 (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
남성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장판매직종업원수 has 108 (64.7%) zerosZeros
공장생산직종업원수 has 111 (66.5%) zerosZeros

Reproduction

Analysis started2023-12-10 20:05:13.885259
Analysis finished2023-12-10 20:05:14.891907
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84
Minimum1
Maximum167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:14.998300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.3
Q142.5
median84
Q3125.5
95-th percentile158.7
Maximum167
Range166
Interquartile range (IQR)83

Descriptive statistics

Standard deviation48.35287
Coefficient of variation (CV)0.5756294
Kurtosis-1.2
Mean84
Median Absolute Deviation (MAD)42
Skewness0
Sum14028
Variance2338
MonotonicityStrictly increasing
2023-12-11T05:05:15.202551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
116 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
Other values (157) 157
94.0%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
167 1
0.6%
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
식품운반업
167 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 167
100.0%

Length

2023-12-11T05:05:15.396724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:15.552517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 167
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
07_22_09_P
167 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_09_P
2nd row07_22_09_P
3rd row07_22_09_P
4th row07_22_09_P
5th row07_22_09_P

Common Values

ValueCountFrequency (%)
07_22_09_P 167
100.0%

Length

2023-12-11T05:05:15.715986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:15.859217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_09_p 167
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449101.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:15.999376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation20084.951
Coefficient of variation (CV)0.0058232409
Kurtosis-0.81829462
Mean3449101.8
Median Absolute Deviation (MAD)20000
Skewness-0.29079509
Sum5.76 × 108
Variance4.0340524 × 108
MonotonicityIncreasing
2023-12-11T05:05:16.189923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 58
34.7%
3470000 27
16.2%
3420000 24
14.4%
3480000 17
 
10.2%
3460000 14
 
8.4%
3430000 11
 
6.6%
3410000 8
 
4.8%
3440000 8
 
4.8%
ValueCountFrequency (%)
3410000 8
 
4.8%
3420000 24
14.4%
3430000 11
 
6.6%
3440000 8
 
4.8%
3450000 58
34.7%
3460000 14
 
8.4%
3470000 27
16.2%
3480000 17
 
10.2%
ValueCountFrequency (%)
3480000 17
 
10.2%
3470000 27
16.2%
3460000 14
 
8.4%
3450000 58
34.7%
3440000 8
 
4.8%
3430000 11
 
6.6%
3420000 24
14.4%
3410000 8
 
4.8%

관리번호
Text

UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T05:05:16.435114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3674
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

Unique167 ?
Unique (%)100.0%

Sample

1st row3410000-117-2004-00001
2nd row3410000-117-2005-00001
3rd row3410000-117-2005-00002
4th row3410000-117-2008-00001
5th row3410000-117-2008-00002
ValueCountFrequency (%)
3410000-117-2004-00001 1
 
0.6%
3470000-117-2015-00003 1
 
0.6%
3450000-117-2018-00005 1
 
0.6%
3450000-117-2018-00006 1
 
0.6%
3460000-117-2014-00001 1
 
0.6%
3460000-117-2011-00001 1
 
0.6%
3460000-117-2018-00001 1
 
0.6%
3460000-117-2015-00001 1
 
0.6%
3460000-117-2014-00002 1
 
0.6%
3460000-117-2008-00001 1
 
0.6%
Other values (157) 157
94.0%
2023-12-11T05:05:16.917928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1594
43.4%
1 506
 
13.8%
- 501
 
13.6%
2 230
 
6.3%
7 221
 
6.0%
3 217
 
5.9%
4 213
 
5.8%
5 83
 
2.3%
8 52
 
1.4%
6 42
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3173
86.4%
Dash Punctuation 501
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1594
50.2%
1 506
 
15.9%
2 230
 
7.2%
7 221
 
7.0%
3 217
 
6.8%
4 213
 
6.7%
5 83
 
2.6%
8 52
 
1.6%
6 42
 
1.3%
9 15
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 501
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3674
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1594
43.4%
1 506
 
13.8%
- 501
 
13.6%
2 230
 
6.3%
7 221
 
6.0%
3 217
 
5.9%
4 213
 
5.8%
5 83
 
2.3%
8 52
 
1.4%
6 42
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3674
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1594
43.4%
1 506
 
13.8%
- 501
 
13.6%
2 230
 
6.3%
7 221
 
6.0%
3 217
 
5.9%
4 213
 
5.8%
5 83
 
2.3%
8 52
 
1.4%
6 42
 
1.1%

인허가일자
Real number (ℝ)

Distinct157
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100377
Minimum19930205
Maximum20190725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:17.173247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930205
5-th percentile20031017
Q120060262
median20081112
Q320150203
95-th percentile20181211
Maximum20190725
Range260520
Interquartile range (IQR)89940.5

Descriptive statistics

Standard deviation54215
Coefficient of variation (CV)0.0026972131
Kurtosis-0.87618229
Mean20100377
Median Absolute Deviation (MAD)40606
Skewness0.16208132
Sum3.3567629 × 109
Variance2.9392662 × 109
MonotonicityNot monotonic
2023-12-11T05:05:17.812684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140113 4
 
2.4%
20031021 3
 
1.8%
20190628 2
 
1.2%
20181105 2
 
1.2%
20100210 2
 
1.2%
20150203 2
 
1.2%
20060508 2
 
1.2%
20181113 1
 
0.6%
20140619 1
 
0.6%
20111227 1
 
0.6%
Other values (147) 147
88.0%
ValueCountFrequency (%)
19930205 1
 
0.6%
20030320 1
 
0.6%
20030522 1
 
0.6%
20030721 1
 
0.6%
20030731 1
 
0.6%
20030806 1
 
0.6%
20030906 1
 
0.6%
20031006 1
 
0.6%
20031015 1
 
0.6%
20031021 3
1.8%
ValueCountFrequency (%)
20190725 1
0.6%
20190628 2
1.2%
20190613 1
0.6%
20190321 1
0.6%
20190128 1
0.6%
20190115 1
0.6%
20181217 1
0.6%
20181213 1
0.6%
20181205 1
0.6%
20181129 1
0.6%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
104 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 104
62.3%
1 63
37.7%

Length

2023-12-11T05:05:18.048318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:18.202384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 104
62.3%
1 63
37.7%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
104 
영업/정상
63 

Length

Max length5
Median length2
Mean length3.1317365
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 104
62.3%
영업/정상 63
37.7%

Length

2023-12-11T05:05:18.367008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:18.575678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 104
62.3%
영업/정상 63
37.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
104 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 104
62.3%
1 63
37.7%

Length

2023-12-11T05:05:18.754178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:18.925430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 104
62.3%
1 63
37.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
104 
영업
63 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 104
62.3%
영업 63
37.7%

Length

2023-12-11T05:05:19.097377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:19.276118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 104
62.3%
영업 63
37.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct99
Distinct (%)95.2%
Missing63
Missing (%)37.7%
Infinite0
Infinite (%)0.0%
Mean20120781
Minimum20040603
Maximum20190729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:19.454988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040603
5-th percentile20051046
Q120080737
median20111066
Q320161108
95-th percentile20190211
Maximum20190729
Range150126
Interquartile range (IQR)80370.75

Descriptive statistics

Standard deviation45412.069
Coefficient of variation (CV)0.0022569735
Kurtosis-1.2627742
Mean20120781
Median Absolute Deviation (MAD)39960.5
Skewness-0.0071894822
Sum2.0925613 × 109
Variance2.062256 × 109
MonotonicityNot monotonic
2023-12-11T05:05:19.669513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20181031 2
 
1.2%
20161122 2
 
1.2%
20100706 2
 
1.2%
20080909 2
 
1.2%
20161102 2
 
1.2%
20151027 1
 
0.6%
20080219 1
 
0.6%
20100304 1
 
0.6%
20120926 1
 
0.6%
20110718 1
 
0.6%
Other values (89) 89
53.3%
(Missing) 63
37.7%
ValueCountFrequency (%)
20040603 1
0.6%
20041126 1
0.6%
20041201 1
0.6%
20041229 1
0.6%
20050324 1
0.6%
20051017 1
0.6%
20051207 1
0.6%
20060109 1
0.6%
20060124 1
0.6%
20060328 1
0.6%
ValueCountFrequency (%)
20190729 1
0.6%
20190625 1
0.6%
20190531 1
0.6%
20190517 1
0.6%
20190510 1
0.6%
20190227 1
0.6%
20190123 1
0.6%
20190121 1
0.6%
20190114 1
0.6%
20181226 1
0.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

소재지전화
Text

MISSING 

Distinct114
Distinct (%)92.7%
Missing44
Missing (%)26.3%
Memory size1.4 KiB
2023-12-11T05:05:20.160839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.544715
Min length7

Characters and Unicode

Total characters1297
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

Unique107 ?
Unique (%)87.0%

Sample

1st row053 5875605
2nd row053 9549460
3rd row053 250 2024
4th row053 4262669
5th row053 4223753
ValueCountFrequency (%)
053 89
34.0%
070 4
 
1.5%
954 3
 
1.1%
5252113 3
 
1.1%
294 3
 
1.1%
7301 3
 
1.1%
6357280 2
 
0.8%
0059 2
 
0.8%
583 2
 
0.8%
313 2
 
0.8%
Other values (144) 149
56.9%
2023-12-11T05:05:20.840466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 209
16.1%
0 207
16.0%
3 203
15.7%
139
10.7%
2 103
7.9%
1 90
6.9%
6 79
 
6.1%
4 75
 
5.8%
8 72
 
5.6%
9 60
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1158
89.3%
Space Separator 139
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 209
18.0%
0 207
17.9%
3 203
17.5%
2 103
8.9%
1 90
7.8%
6 79
 
6.8%
4 75
 
6.5%
8 72
 
6.2%
9 60
 
5.2%
7 60
 
5.2%
Space Separator
ValueCountFrequency (%)
139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1297
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 209
16.1%
0 207
16.0%
3 203
15.7%
139
10.7%
2 103
7.9%
1 90
6.9%
6 79
 
6.1%
4 75
 
5.8%
8 72
 
5.6%
9 60
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1297
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 209
16.1%
0 207
16.0%
3 203
15.7%
139
10.7%
2 103
7.9%
1 90
6.9%
6 79
 
6.1%
4 75
 
5.8%
8 72
 
5.6%
9 60
 
4.6%

소재지면적
Text

MISSING 

Distinct117
Distinct (%)78.0%
Missing17
Missing (%)10.2%
Memory size1.4 KiB
2023-12-11T05:05:21.353132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0733333
Min length3

Characters and Unicode

Total characters761
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

Unique103 ?
Unique (%)68.7%

Sample

1st row66.04
2nd row65.60
3rd row26.44
4th row19.95
5th row66.00
ValueCountFrequency (%)
10.00 7
 
4.7%
49.50 5
 
3.3%
6.60 5
 
3.3%
9.90 4
 
2.7%
20.00 4
 
2.7%
50.00 3
 
2.0%
30.00 3
 
2.0%
58.95 3
 
2.0%
16.50 3
 
2.0%
84.67 2
 
1.3%
Other values (107) 111
74.0%
2023-12-11T05:05:22.040521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 179
23.5%
. 150
19.7%
1 63
 
8.3%
6 57
 
7.5%
2 52
 
6.8%
4 48
 
6.3%
3 48
 
6.3%
5 47
 
6.2%
9 46
 
6.0%
8 42
 
5.5%
Other values (2) 29
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 609
80.0%
Other Punctuation 152
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 179
29.4%
1 63
 
10.3%
6 57
 
9.4%
2 52
 
8.5%
4 48
 
7.9%
3 48
 
7.9%
5 47
 
7.7%
9 46
 
7.6%
8 42
 
6.9%
7 27
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 150
98.7%
, 2
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 761
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 179
23.5%
. 150
19.7%
1 63
 
8.3%
6 57
 
7.5%
2 52
 
6.8%
4 48
 
6.3%
3 48
 
6.3%
5 47
 
6.2%
9 46
 
6.0%
8 42
 
5.5%
Other values (2) 29
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 179
23.5%
. 150
19.7%
1 63
 
8.3%
6 57
 
7.5%
2 52
 
6.8%
4 48
 
6.3%
3 48
 
6.3%
5 47
 
6.2%
9 46
 
6.0%
8 42
 
5.5%
Other values (2) 29
 
3.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)65.2%
Missing3
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean704182.15
Minimum700082
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:22.280259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700082
5-th percentile701141.5
Q1702802
median702903
Q3704944
95-th percentile711822.7
Maximum711891
Range11809
Interquartile range (IQR)2142

Descriptive statistics

Standard deviation2830.5161
Coefficient of variation (CV)0.0040195795
Kurtosis2.011759
Mean704182.15
Median Absolute Deviation (MAD)1068
Skewness1.5539324
Sum1.1548587 × 108
Variance8011821.5
MonotonicityNot monotonic
2023-12-11T05:05:22.541776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702903 12
 
7.2%
702825 6
 
3.6%
702300 4
 
2.4%
711821 4
 
2.4%
701835 3
 
1.8%
704932 3
 
1.8%
705840 3
 
1.8%
704944 3
 
1.8%
704830 3
 
1.8%
702867 3
 
1.8%
Other values (97) 120
71.9%
ValueCountFrequency (%)
700082 1
0.6%
700192 1
0.6%
700810 1
0.6%
700823 1
0.6%
700826 1
0.6%
700845 2
1.2%
700847 1
0.6%
701140 1
0.6%
701150 1
0.6%
701804 2
1.2%
ValueCountFrequency (%)
711891 1
 
0.6%
711874 1
 
0.6%
711852 1
 
0.6%
711842 1
 
0.6%
711833 2
1.2%
711832 2
1.2%
711823 1
 
0.6%
711821 4
2.4%
711814 1
 
0.6%
706852 2
1.2%

소재지전체주소
Text

Distinct146
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T05:05:23.136031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length23.826347
Min length18

Characters and Unicode

Total characters3979
Distinct characters142
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

Unique130 ?
Unique (%)77.8%

Sample

1st row대구광역시 중구 동인동4가 0420번지 (1층)
2nd row대구광역시 중구 종로2가 0038번지
3rd row대구광역시 중구 대봉동 55-50번지 (65,66호)
4th row대구광역시 중구 동인동3가 0240-0006번지 지상1층
5th row대구광역시 중구 남산동 2110-0009번지 지상1층
ValueCountFrequency (%)
대구광역시 167
22.1%
북구 58
 
7.7%
달서구 26
 
3.4%
동구 24
 
3.2%
달성군 17
 
2.3%
수성구 14
 
1.9%
팔달동 14
 
1.9%
서구 11
 
1.5%
230-3번지 10
 
1.3%
남구 9
 
1.2%
Other values (259) 404
53.6%
2023-12-11T05:05:23.897572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
762
19.2%
구 323
 
8.1%
지 197
 
5.0%
동 185
 
4.6%
대 179
 
4.5%
역 168
 
4.2%
광 167
 
4.2%
시 167
 
4.2%
번 167
 
4.2%
1 147
 
3.7%
Other values (132) 1517
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2251
56.6%
Decimal Number 806
 
20.3%
Space Separator 762
 
19.2%
Dash Punctuation 134
 
3.4%
Close Punctuation 9
 
0.2%
Open Punctuation 9
 
0.2%
Other Punctuation 6
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 323
14.3%
지 197
 
8.8%
동 185
 
8.2%
대 179
 
8.0%
역 168
 
7.5%
광 167
 
7.4%
시 167
 
7.4%
번 167
 
7.4%
북 59
 
2.6%
달 57
 
2.5%
Other values (114) 582
25.9%
Decimal Number
ValueCountFrequency (%)
1 147
18.2%
2 108
13.4%
0 91
11.3%
3 85
10.5%
4 79
9.8%
6 69
8.6%
7 59
7.3%
5 58
 
7.2%
9 55
 
6.8%
8 55
 
6.8%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 2
33.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
762
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2251
56.6%
Common 1726
43.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 323
14.3%
지 197
 
8.8%
동 185
 
8.2%
대 179
 
8.0%
역 168
 
7.5%
광 167
 
7.4%
시 167
 
7.4%
번 167
 
7.4%
북 59
 
2.6%
달 57
 
2.5%
Other values (114) 582
25.9%
Common
ValueCountFrequency (%)
762
44.1%
1 147
 
8.5%
- 134
 
7.8%
2 108
 
6.3%
0 91
 
5.3%
3 85
 
4.9%
4 79
 
4.6%
6 69
 
4.0%
7 59
 
3.4%
5 58
 
3.4%
Other values (6) 134
 
7.8%
Latin
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2251
56.6%
ASCII 1728
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
762
44.1%
1 147
 
8.5%
- 134
 
7.8%
2 108
 
6.2%
0 91
 
5.3%
3 85
 
4.9%
4 79
 
4.6%
6 69
 
4.0%
7 59
 
3.4%
5 58
 
3.4%
Other values (8) 136
 
7.9%
Hangul
ValueCountFrequency (%)
구 323
14.3%
지 197
 
8.8%
동 185
 
8.2%
대 179
 
8.0%
역 168
 
7.5%
광 167
 
7.4%
시 167
 
7.4%
번 167
 
7.4%
북 59
 
2.6%
달 57
 
2.5%
Other values (114) 582
25.9%

도로명전체주소
Text

MISSING 

Distinct96
Distinct (%)86.5%
Missing56
Missing (%)33.5%
Memory size1.4 KiB
2023-12-11T05:05:24.334341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length27.099099
Min length20

Characters and Unicode

Total characters3008
Distinct characters168
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

Unique84 ?
Unique (%)75.7%

Sample

1st row대구광역시 중구 중앙대로77길 43 (종로2가)
2nd row대구광역시 중구 동덕로38길 93-1, 1층 (동인동3가)
3rd row대구광역시 중구 봉산문화1길 5, 1층 (봉산동)
4th row대구광역시 중구 달구벌대로 2077 (계산동2가, 지하3층)
5th row대구광역시 중구 국채보상로143길 65 (동인동3가)
ValueCountFrequency (%)
대구광역시 111
 
17.8%
북구 30
 
4.8%
1층 25
 
4.0%
달서구 20
 
3.2%
동구 20
 
3.2%
달성군 13
 
2.1%
서구 9
 
1.4%
15 9
 
1.4%
팔달동 8
 
1.3%
남구 8
 
1.3%
Other values (250) 370
59.4%
2023-12-11T05:05:24.923161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
512
 
17.0%
구 218
 
7.2%
동 135
 
4.5%
대 131
 
4.4%
1 120
 
4.0%
시 114
 
3.8%
역 112
 
3.7%
광 111
 
3.7%
로 100
 
3.3%
( 99
 
3.3%
Other values (158) 1356
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1734
57.6%
Space Separator 512
 
17.0%
Decimal Number 478
 
15.9%
Open Punctuation 99
 
3.3%
Close Punctuation 99
 
3.3%
Other Punctuation 58
 
1.9%
Dash Punctuation 26
 
0.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 218
 
12.6%
동 135
 
7.8%
대 131
 
7.6%
시 114
 
6.6%
역 112
 
6.5%
광 111
 
6.4%
로 100
 
5.8%
길 71
 
4.1%
층 48
 
2.8%
달 46
 
2.7%
Other values (141) 648
37.4%
Decimal Number
ValueCountFrequency (%)
1 120
25.1%
3 75
15.7%
2 67
14.0%
5 37
 
7.7%
4 37
 
7.7%
6 33
 
6.9%
0 33
 
6.9%
7 31
 
6.5%
8 25
 
5.2%
9 20
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
512
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1734
57.6%
Common 1272
42.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 218
 
12.6%
동 135
 
7.8%
대 131
 
7.6%
시 114
 
6.6%
역 112
 
6.5%
광 111
 
6.4%
로 100
 
5.8%
길 71
 
4.1%
층 48
 
2.8%
달 46
 
2.7%
Other values (141) 648
37.4%
Common
ValueCountFrequency (%)
512
40.3%
1 120
 
9.4%
( 99
 
7.8%
) 99
 
7.8%
3 75
 
5.9%
2 67
 
5.3%
, 58
 
4.6%
5 37
 
2.9%
4 37
 
2.9%
6 33
 
2.6%
Other values (5) 135
 
10.6%
Latin
ValueCountFrequency (%)
C 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1734
57.6%
ASCII 1274
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
512
40.2%
1 120
 
9.4%
( 99
 
7.8%
) 99
 
7.8%
3 75
 
5.9%
2 67
 
5.3%
, 58
 
4.6%
5 37
 
2.9%
4 37
 
2.9%
6 33
 
2.6%
Other values (7) 137
 
10.8%
Hangul
ValueCountFrequency (%)
구 218
 
12.6%
동 135
 
7.8%
대 131
 
7.6%
시 114
 
6.6%
역 112
 
6.5%
광 111
 
6.4%
로 100
 
5.8%
길 71
 
4.1%
층 48
 
2.8%
달 46
 
2.7%
Other values (141) 648
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct82
Distinct (%)74.5%
Missing57
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean41972.064
Minimum41042
Maximum43010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:25.085526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41042
5-th percentile41082
Q141479
median41754
Q342676.75
95-th percentile42957
Maximum43010
Range1968
Interquartile range (IQR)1197.75

Descriptive statistics

Standard deviation654.94182
Coefficient of variation (CV)0.015604232
Kurtosis-1.4767366
Mean41972.064
Median Absolute Deviation (MAD)583
Skewness0.20818338
Sum4616927
Variance428948.79
MonotonicityNot monotonic
2023-12-11T05:05:25.310439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 8
 
4.8%
42904 3
 
1.8%
41082 3
 
1.8%
42500 3
 
1.8%
41754 3
 
1.8%
41750 2
 
1.2%
42957 2
 
1.2%
42968 2
 
1.2%
42946 2
 
1.2%
42788 2
 
1.2%
Other values (72) 80
47.9%
(Missing) 57
34.1%
ValueCountFrequency (%)
41042 1
 
0.6%
41046 1
 
0.6%
41051 1
 
0.6%
41055 1
 
0.6%
41078 1
 
0.6%
41082 3
1.8%
41124 1
 
0.6%
41129 2
1.2%
41143 1
 
0.6%
41163 2
1.2%
ValueCountFrequency (%)
43010 1
 
0.6%
43003 1
 
0.6%
42974 1
 
0.6%
42968 2
1.2%
42957 2
1.2%
42946 2
1.2%
42922 1
 
0.6%
42904 3
1.8%
42819 1
 
0.6%
42815 1
 
0.6%

사업장명
Text

Distinct155
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T05:05:25.656358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.4610778
Min length2

Characters and Unicode

Total characters1079
Distinct characters198
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)86.2%

Sample

1st row사옹원
2nd row(주)일성화물
3rd row아진식품
4th row박통식품
5th row대구우체국
ValueCountFrequency (%)
주식회사 6
 
3.3%
베스트바이 3
 
1.6%
박통식품 2
 
1.1%
주 2
 
1.1%
가야푸드 2
 
1.1%
주)그린물류 2
 
1.1%
주)센트랄푸드시스템 2
 
1.1%
주)정우운수 2
 
1.1%
개인용달 2
 
1.1%
주)바다플러스 2
 
1.1%
Other values (155) 158
86.3%
2023-12-11T05:05:26.181904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 76
 
7.0%
) 67
 
6.2%
( 66
 
6.1%
스 33
 
3.1%
식 32
 
3.0%
물 26
 
2.4%
드 26
 
2.4%
대 25
 
2.3%
푸 24
 
2.2%
통 22
 
2.0%
Other values (188) 682
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 925
85.7%
Close Punctuation 67
 
6.2%
Open Punctuation 66
 
6.1%
Space Separator 16
 
1.5%
Uppercase Letter 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 76
 
8.2%
스 33
 
3.6%
식 32
 
3.5%
물 26
 
2.8%
드 26
 
2.8%
대 25
 
2.7%
푸 24
 
2.6%
통 22
 
2.4%
성 21
 
2.3%
품 20
 
2.2%
Other values (180) 620
67.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
20.0%
F 1
20.0%
T 1
20.0%
G 1
20.0%
S 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 925
85.7%
Common 149
 
13.8%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 76
 
8.2%
스 33
 
3.6%
식 32
 
3.5%
물 26
 
2.8%
드 26
 
2.8%
대 25
 
2.7%
푸 24
 
2.6%
통 22
 
2.4%
성 21
 
2.3%
품 20
 
2.2%
Other values (180) 620
67.0%
Latin
ValueCountFrequency (%)
C 1
20.0%
F 1
20.0%
T 1
20.0%
G 1
20.0%
S 1
20.0%
Common
ValueCountFrequency (%)
) 67
45.0%
( 66
44.3%
16
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 925
85.7%
ASCII 154
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 76
 
8.2%
스 33
 
3.6%
식 32
 
3.5%
물 26
 
2.8%
드 26
 
2.8%
대 25
 
2.7%
푸 24
 
2.6%
통 22
 
2.4%
성 21
 
2.3%
품 20
 
2.2%
Other values (180) 620
67.0%
ASCII
ValueCountFrequency (%)
) 67
43.5%
( 66
42.9%
16
 
10.4%
C 1
 
0.6%
F 1
 
0.6%
T 1
 
0.6%
G 1
 
0.6%
S 1
 
0.6%

최종수정시점
Real number (ℝ)

Distinct161
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0125011 × 1013
Minimum2.0031121 × 1013
Maximum2.0190823 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:26.377141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0031121 × 1013
5-th percentile2.0040871 × 1013
Q12.0075671 × 1013
median2.014011 × 1013
Q32.0171229 × 1013
95-th percentile2.0190531 × 1013
Maximum2.0190823 × 1013
Range1.5970217 × 1011
Interquartile range (IQR)9.5557976 × 1010

Descriptive statistics

Standard deviation5.2452906 × 1010
Coefficient of variation (CV)0.0026063541
Kurtosis-1.3701169
Mean2.0125011 × 1013
Median Absolute Deviation (MAD)4.0920992 × 1010
Skewness-0.28824903
Sum3.3608769 × 1015
Variance2.7513074 × 1021
MonotonicityNot monotonic
2023-12-11T05:05:26.577778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041011000000 6
 
3.6%
20161122170313 2
 
1.2%
20031215000000 1
 
0.6%
20120110104710 1
 
0.6%
20190517154812 1
 
0.6%
20180206143523 1
 
0.6%
20141210093840 1
 
0.6%
20081007154212 1
 
0.6%
20090216112521 1
 
0.6%
20061127000000 1
 
0.6%
Other values (151) 151
90.4%
ValueCountFrequency (%)
20031121000000 1
 
0.6%
20031215000000 1
 
0.6%
20040107000000 1
 
0.6%
20040114000000 1
 
0.6%
20040204000000 1
 
0.6%
20040212000000 1
 
0.6%
20040401000000 1
 
0.6%
20040506000000 1
 
0.6%
20040811000000 1
 
0.6%
20041011000000 6
3.6%
ValueCountFrequency (%)
20190823174859 1
0.6%
20190807172241 1
0.6%
20190807172026 1
0.6%
20190801105416 1
0.6%
20190729163938 1
0.6%
20190725145009 1
0.6%
20190625143205 1
0.6%
20190604135553 1
0.6%
20190531152839 1
0.6%
20190529121156 1
0.6%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
144 
U
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 144
86.2%
U 23
 
13.8%

Length

2023-12-11T05:05:26.798090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:26.924159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 144
86.2%
u 23
 
13.8%

데이터갱신일자
Date

Distinct28
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2018-08-31 23:59:59
Maximum2019-08-25 02:40:00
2023-12-11T05:05:27.066102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:05:27.253376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
식품운반업
167 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 167
100.0%

Length

2023-12-11T05:05:27.460357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:27.623048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 167
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct128
Distinct (%)81.0%
Missing9
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean341359.2
Minimum327299.69
Maximum355567.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:27.786736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327299.69
5-th percentile330087.93
Q1338505.48
median340233.33
Q3345318.89
95-th percentile352668.15
Maximum355567.69
Range28268.001
Interquartile range (IQR)6813.4105

Descriptive statistics

Standard deviation5929.6467
Coefficient of variation (CV)0.017370695
Kurtosis0.23343383
Mean341359.2
Median Absolute Deviation (MAD)3331.6458
Skewness0.10691931
Sum53934754
Variance35160710
MonotonicityNot monotonic
2023-12-11T05:05:27.962636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338985.366314 10
 
6.0%
327735.044524 3
 
1.8%
340946.597285 3
 
1.8%
339388.690364 3
 
1.8%
337140.428534 2
 
1.2%
338509.064125 2
 
1.2%
340246.984304 2
 
1.2%
339120.646244 2
 
1.2%
340411.771764 2
 
1.2%
347483.915581 2
 
1.2%
Other values (118) 127
76.0%
(Missing) 9
 
5.4%
ValueCountFrequency (%)
327299.692057 1
 
0.6%
327735.044524 3
1.8%
329271.879011 2
1.2%
329604.038183 1
 
0.6%
329859.122079 1
 
0.6%
330128.30921 1
 
0.6%
330388.015281 1
 
0.6%
330706.421358 1
 
0.6%
333070.51248 1
 
0.6%
333920.60853 2
1.2%
ValueCountFrequency (%)
355567.693374 2
1.2%
355474.652805 1
0.6%
354790.108191 1
0.6%
354215.082384 1
0.6%
353414.507288 1
0.6%
352803.154449 2
1.2%
352644.320881 1
0.6%
351788.563589 1
0.6%
350504.394278 1
0.6%
350394.523064 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct128
Distinct (%)81.0%
Missing9
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean264350.43
Minimum240636.85
Maximum273735.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:28.150712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240636.85
5-th percentile256052.54
Q1261850.04
median264841.41
Q3267354.45
95-th percentile271842.15
Maximum273735.13
Range33098.279
Interquartile range (IQR)5504.4103

Descriptive statistics

Standard deviation4938.6227
Coefficient of variation (CV)0.018682106
Kurtosis4.2187292
Mean264350.43
Median Absolute Deviation (MAD)2636.5907
Skewness-1.3142015
Sum41767367
Variance24389994
MonotonicityNot monotonic
2023-12-11T05:05:28.368355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
267354.446312 10
 
6.0%
263479.562399 3
 
1.8%
259953.127592 3
 
1.8%
269664.126149 3
 
1.8%
267197.245937 2
 
1.2%
264361.827835 2
 
1.2%
270847.157898 2
 
1.2%
269054.376386 2
 
1.2%
272600.063881 2
 
1.2%
266103.178136 2
 
1.2%
Other values (118) 127
76.0%
(Missing) 9
 
5.4%
ValueCountFrequency (%)
240636.852024 1
0.6%
244838.382091 1
0.6%
248561.77396 1
0.6%
254017.803261 1
0.6%
254171.232318 1
0.6%
254619.354156 2
1.2%
255771.102947 1
0.6%
256102.203744 1
0.6%
256643.317146 2
1.2%
257765.775409 1
0.6%
ValueCountFrequency (%)
273735.131409 1
0.6%
273355.790439 1
0.6%
273296.193994 1
0.6%
272745.678782 1
0.6%
272600.063881 2
1.2%
272092.19703 1
0.6%
271937.692097 1
0.6%
271825.291142 1
0.6%
270847.157898 2
1.2%
270477.697377 1
0.6%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
식품운반업
167 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 167
100.0%

Length

2023-12-11T05:05:28.610285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:28.779517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 167
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
117 
상수도전용
50 

Length

Max length5
Median length4
Mean length4.2994012
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 117
70.1%
상수도전용 50
29.9%

Length

2023-12-11T05:05:28.914611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:29.056675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
70.1%
상수도전용 50
29.9%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

본사종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
124 
<NA>
42 
3
 
1

Length

Max length4
Median length1
Mean length1.754491
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 124
74.3%
<NA> 42
 
25.1%
3 1
 
0.6%

Length

2023-12-11T05:05:29.563429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:29.728578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 124
74.3%
na 42
 
25.1%
3 1
 
0.6%

공장사무직종업원수
Categorical

Distinct6
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
106 
<NA>
41 
1
12 
2
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.7365269
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row1
2nd row2
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 106
63.5%
<NA> 41
 
24.6%
1 12
 
7.2%
2 5
 
3.0%
3 2
 
1.2%
5 1
 
0.6%

Length

2023-12-11T05:05:29.917049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:30.092636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 106
63.5%
na 41
 
24.6%
1 12
 
7.2%
2 5
 
3.0%
3 2
 
1.2%
5 1
 
0.6%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)5.6%
Missing41
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean0.33333333
Minimum0
Maximum7
Zeros108
Zeros (%)64.7%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:30.345510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.75
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0430724
Coefficient of variation (CV)3.1292172
Kurtosis18.065913
Mean0.33333333
Median Absolute Deviation (MAD)0
Skewness4.0208358
Sum42
Variance1.088
MonotonicityNot monotonic
2023-12-11T05:05:30.509475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 108
64.7%
1 9
 
5.4%
3 3
 
1.8%
2 2
 
1.2%
4 2
 
1.2%
7 1
 
0.6%
5 1
 
0.6%
(Missing) 41
 
24.6%
ValueCountFrequency (%)
0 108
64.7%
1 9
 
5.4%
2 2
 
1.2%
3 3
 
1.8%
4 2
 
1.2%
5 1
 
0.6%
7 1
 
0.6%
ValueCountFrequency (%)
7 1
 
0.6%
5 1
 
0.6%
4 2
 
1.2%
3 3
 
1.8%
2 2
 
1.2%
1 9
 
5.4%
0 108
64.7%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)4.8%
Missing42
Missing (%)25.1%
Infinite0
Infinite (%)0.0%
Mean0.28
Minimum0
Maximum7
Zeros111
Zeros (%)66.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T05:05:30.666918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.99676897
Coefficient of variation (CV)3.5598892
Kurtosis23.785731
Mean0.28
Median Absolute Deviation (MAD)0
Skewness4.6241425
Sum35
Variance0.99354839
MonotonicityNot monotonic
2023-12-11T05:05:30.845707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 111
66.5%
2 5
 
3.0%
1 5
 
3.0%
5 2
 
1.2%
3 1
 
0.6%
7 1
 
0.6%
(Missing) 42
 
25.1%
ValueCountFrequency (%)
0 111
66.5%
1 5
 
3.0%
2 5
 
3.0%
3 1
 
0.6%
5 2
 
1.2%
7 1
 
0.6%
ValueCountFrequency (%)
7 1
 
0.6%
5 2
 
1.2%
3 1
 
0.6%
2 5
 
3.0%
1 5
 
3.0%
0 111
66.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
70 
자가
55 
임대
42 

Length

Max length4
Median length2
Mean length2.8383234
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
41.9%
자가 55
32.9%
임대 42
25.1%

Length

2023-12-11T05:05:31.086953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:31.280011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
41.9%
자가 55
32.9%
임대 42
25.1%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
153 
0
 
14

Length

Max length4
Median length4
Mean length3.748503
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> 153
91.6%
0 14
 
8.4%

Length

2023-12-11T05:05:31.451126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:31.605412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
91.6%
0 14
 
8.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
153 
0
 
14

Length

Max length4
Median length4
Mean length3.748503
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> 153
91.6%
0 14
 
8.4%

Length

2023-12-11T05:05:31.801202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:31.970919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
91.6%
0 14
 
8.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size299.0 B
False
167 
ValueCountFrequency (%)
False 167
100.0%
2023-12-11T05:05:32.116585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0.0
163 
134.13
 
1
10.37
 
1
3.0
 
1
2.46
 
1

Length

Max length6
Median length3
Mean length3.0359281
Min length3

Unique

Unique4 ?
Unique (%)2.4%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 163
97.6%
134.13 1
 
0.6%
10.37 1
 
0.6%
3.0 1
 
0.6%
2.46 1
 
0.6%

Length

2023-12-11T05:05:32.305075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:32.480006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 163
97.6%
134.13 1
 
0.6%
10.37 1
 
0.6%
3.0 1
 
0.6%
2.46 1
 
0.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품운반업07_22_09_P34100003410000-117-2004-0000120040114<NA>3폐업2폐업20080225<NA><NA><NA><NA>66.04700847대구광역시 중구 동인동4가 0420번지 (1층)<NA><NA>사옹원20040204000000I2018-08-31 23:59:59.0식품운반업345414.421341264120.775769식품운반업<NA><NA><NA><NA><NA><NA>0110자가<NA><NA>N0.0<NA><NA><NA>
12식품운반업07_22_09_P34100003410000-117-2005-0000120050324<NA>3폐업2폐업20150916<NA><NA><NA>053 587560565.60700192대구광역시 중구 종로2가 0038번지대구광역시 중구 중앙대로77길 43 (종로2가)41934(주)일성화물20120504134608I2018-08-31 23:59:59.0식품운반업343638.059396264281.159118식품운반업<NA><NA><NA><NA>상수도전용<NA>0200임대<NA><NA>N0.0<NA><NA><NA>
23식품운반업07_22_09_P34100003410000-117-2005-0000220050719<NA>3폐업2폐업20051017<NA><NA><NA><NA>26.44700810대구광역시 중구 대봉동 55-50번지 (65,66호)<NA><NA>아진식품20050719000000I2018-08-31 23:59:59.0식품운반업344625.726336263421.522163식품운반업<NA><NA><NA><NA><NA><NA>0110임대<NA><NA>N0.0<NA><NA><NA>
34식품운반업07_22_09_P34100003410000-117-2008-0000120080805<NA>3폐업2폐업20140306<NA><NA><NA>053 954946019.95700845대구광역시 중구 동인동3가 0240-0006번지 지상1층대구광역시 중구 동덕로38길 93-1, 1층 (동인동3가)41906박통식품20131206104127I2018-08-31 23:59:59.0식품운반업345292.345402264638.147502식품운반업<NA><NA><NA><NA>상수도전용<NA>0030<NA><NA><NA>N0.0<NA><NA><NA>
45식품운반업07_22_09_P34100003410000-117-2008-0000220081112<NA>3폐업2폐업20111230<NA><NA><NA>053 250 202466.00700826대구광역시 중구 남산동 2110-0009번지 지상1층<NA><NA>대구우체국20100709163030I2018-08-31 23:59:59.0식품운반업343570.613158263072.964308식품운반업<NA><NA><NA><NA>상수도전용<NA>0110<NA><NA><NA>N0.0<NA><NA><NA>
56식품운반업07_22_09_P34100003410000-117-2010-0000120100210<NA>3폐업2폐업20140319<NA><NA><NA>053 426266927.69700823대구광역시 중구 봉산동 0222-0037번지 지상1층대구광역시 중구 봉산문화1길 5, 1층 (봉산동)41959남양유업 동성로대리점20120201161346I2018-08-31 23:59:59.0식품운반업344241.713047263665.761646식품운반업<NA><NA><NA><NA><NA><NA>0010<NA><NA><NA>N0.0<NA><NA><NA>
67식품운반업07_22_09_P34100003410000-117-2014-0000120140313<NA>3폐업2폐업20160223<NA><NA><NA><NA>26.00700082대구광역시 중구 계산동2가 0200번지 지하3층대구광역시 중구 달구벌대로 2077 (계산동2가, 지하3층)41936(주)코리아택배물류20160224112705I2018-08-31 23:59:59.0식품운반업343588.735555264119.01075식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78식품운반업07_22_09_P34100003410000-117-2011-0000120110920<NA>1영업/정상1영업<NA><NA><NA><NA>053 422375384.20700845대구광역시 중구 동인동3가 0271-0212번지대구광역시 중구 국채보상로143길 65 (동인동3가)41905(주) 전진통운20120201161419I2018-08-31 23:59:59.0식품운반업345197.150819264705.746035식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
89식품운반업07_22_09_P34200003420000-117-2003-0000220031021<NA>3폐업2폐업20171229<NA><NA><NA>053 9610935382.80701848대구광역시 동구 동호동 98-10번지대구광역시 동구 안심로53길 48 (동호동)41078동원물산20171229104139I2018-08-31 23:59:59.0식품운반업354790.108191264731.243907식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
910식품운반업07_22_09_P34200003420000-117-2008-0000220080327<NA>1영업/정상1영업<NA><NA><NA><NA>053 957 04246.60701817대구광역시 동구 신암동 460-9번지대구광역시 동구 신암로20길 57 (신암동)41202현지상회20171229170526I2018-08-31 23:59:59.0식품운반업345599.909137265378.669775식품운반업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
157158식품운반업07_22_09_P34800003480000-117-2006-0000120060808<NA>3폐업2폐업20110808<NA><NA><NA>053 582164735.00711821대구광역시 달성군 하빈면 현내리 572번지<NA><NA>창성산업주식회사20071121132429I2018-08-31 23:59:59.0식품운반업330388.015281268137.397927식품운반업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
158159식품운반업07_22_09_P34800003480000-117-2017-0000120171211<NA>1영업/정상1영업<NA><NA><NA><NA>070 412299956.60711821대구광역시 달성군 하빈면 동곡리 627번지 1층대구광역시 달성군 하빈면 하빈남로 171-1, 1층42904(주)대구유통20171211101032I2018-08-31 23:59:59.0식품운반업327735.044524263479.562399식품운반업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
159160식품운반업07_22_09_P34800003480000-117-2016-0000120160930<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.00711821대구광역시 달성군 하빈면 동곡리 627번지대구광역시 달성군 하빈면 하빈남로 171-142904(주)달성푸드20160930140346I2018-08-31 23:59:59.0식품운반업327735.044524263479.562399식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
160161식품운반업07_22_09_P34800003480000-117-2015-0000120150827<NA>1영업/정상1영업<NA><NA><NA><NA>053 555 229910.40711833대구광역시 달성군 화원읍 설화리 736-3번지대구광역시 달성군 화원읍 류목정길 56, 1층42957미곤종합식품20150903201639I2018-08-31 23:59:59.0식품운반업334255.076962255771.102947식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
161162식품운반업07_22_09_P34800003480000-117-2008-0000120080404<NA>3폐업2폐업20080414<NA><NA><NA>053 3121656<NA>711852대구광역시 달성군 논공읍 북리 824-35번지 외 1필지 111호<NA><NA>남경식품20080404093827I2018-08-31 23:59:59.0식품운반업330706.421358248561.77396식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
162163식품운반업07_22_09_P34800003480000-117-2008-0000220080516<NA>3폐업2폐업20180528<NA><NA><NA>053 635728049.50711832대구광역시 달성군 화원읍 명곡리 198-4번지대구광역시 달성군 화원읍 성화로 1142946(주)하나통운20180528111732I2018-08-31 23:59:59.0식품운반업334750.422674256643.317146식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
163164식품운반업07_22_09_P34800003480000-117-2008-0000320081127<NA>3폐업2폐업20170510<NA><NA><NA>053 614300750.00711874대구광역시 달성군 현풍면 원교리 94번지대구광역시 달성군 현풍면 비슬로130길 743003달성우체국20170510164444I2018-08-31 23:59:59.0식품운반업330128.30921244838.382091식품운반업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
164165식품운반업07_22_09_P34800003480000-117-2013-0000120130117<NA>3폐업2폐업20140804<NA><NA><NA>070 44178456256.00711833대구광역시 달성군 화원읍 설화리 616-1번지 . 1층대구광역시 달성군 화원읍 옥터길 10, 1층42957싱싱푸드20130214095247I2018-08-31 23:59:59.0식품운반업334264.122637256102.203744식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
165166식품운반업07_22_09_P34800003480000-117-2014-0000120140113<NA>3폐업2폐업20161202<NA><NA><NA>070 4122999570.00711821대구광역시 달성군 하빈면 동곡리 627번지대구광역시 달성군 하빈면 하빈남로 171-1, 1층42904주식회사 광림유통20160624152311I2018-08-31 23:59:59.0식품운반업327735.044524263479.562399식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
166167식품운반업07_22_09_P34800003480000-117-2007-0000120070824<NA>1영업/정상1영업<NA><NA><NA><NA>053 586758414.80711814대구광역시 달성군 다사읍 세천리 870-1번지대구광역시 달성군 다사읍 세천북로 7342922토마토푸드20070904162736I2018-08-31 23:59:59.0식품운반업333070.51248265157.989806식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>