Overview

Dataset statistics

Number of variables47
Number of observations195
Missing cells2153
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.4 KiB
Average record size in memory406.7 B

Variable types

Numeric12
Categorical18
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_09_P_식품운반업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000090638&dataSetDetailId=DDI_0000090686&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
남성종사자수 is highly imbalanced (95.4%)Imbalance
여성종사자수 is highly imbalanced (95.4%)Imbalance
총종업원수 is highly imbalanced (95.4%)Imbalance
본사종업원수 is highly imbalanced (51.7%)Imbalance
보증액 is highly imbalanced (60.9%)Imbalance
월세액 is highly imbalanced (60.9%)Imbalance
인허가취소일자 has 195 (100.0%) missing valuesMissing
폐업일자 has 74 (37.9%) missing valuesMissing
휴업시작일자 has 195 (100.0%) missing valuesMissing
휴업종료일자 has 195 (100.0%) missing valuesMissing
재개업일자 has 195 (100.0%) missing valuesMissing
소재지전화 has 60 (30.8%) missing valuesMissing
소재지면적 has 25 (12.8%) missing valuesMissing
소재지우편번호 has 3 (1.5%) missing valuesMissing
도로명전체주소 has 56 (28.7%) missing valuesMissing
도로명우편번호 has 57 (29.2%) missing valuesMissing
좌표정보(X) has 9 (4.6%) missing valuesMissing
좌표정보(Y) has 9 (4.6%) missing valuesMissing
영업장주변구분명 has 195 (100.0%) missing valuesMissing
등급구분명 has 195 (100.0%) missing valuesMissing
공장판매직종업원수 has 52 (26.7%) missing valuesMissing
공장생산직종업원수 has 53 (27.2%) missing valuesMissing
전통업소지정번호 has 195 (100.0%) missing valuesMissing
전통업소주된음식 has 195 (100.0%) missing valuesMissing
홈페이지 has 195 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장판매직종업원수 has 125 (64.1%) zerosZeros
공장생산직종업원수 has 128 (65.6%) zerosZeros
시설총규모 has 190 (97.4%) zerosZeros

Reproduction

Analysis started2023-12-10 18:39:41.995015
Analysis finished2023-12-10 18:39:43.390428
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:43.519800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.7
Q149.5
median98
Q3146.5
95-th percentile185.3
Maximum195
Range194
Interquartile range (IQR)97

Descriptive statistics

Standard deviation56.435804
Coefficient of variation (CV)0.57587555
Kurtosis-1.2
Mean98
Median Absolute Deviation (MAD)49
Skewness0
Sum19110
Variance3185
MonotonicityStrictly increasing
2023-12-11T03:39:43.812008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
124 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
식품운반업
195 

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 195
100.0%

Length

2023-12-11T03:39:44.037750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:44.203460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 195
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
07_22_09_P
195 

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 195
100.0%

Length

2023-12-11T03:39:44.360339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:44.532039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_09_p 195
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449128.2
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:44.690602image/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 deviation20045.283
Coefficient of variation (CV)0.0058116956
Kurtosis-0.87729209
Mean3449128.2
Median Absolute Deviation (MAD)20000
Skewness-0.29032357
Sum6.7258 × 108
Variance4.0181338 × 108
MonotonicityIncreasing
2023-12-11T03:39:44.922430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 64
32.8%
3470000 32
16.4%
3420000 30
15.4%
3460000 20
 
10.3%
3480000 19
 
9.7%
3430000 14
 
7.2%
3410000 8
 
4.1%
3440000 8
 
4.1%
ValueCountFrequency (%)
3410000 8
 
4.1%
3420000 30
15.4%
3430000 14
 
7.2%
3440000 8
 
4.1%
3450000 64
32.8%
3460000 20
 
10.3%
3470000 32
16.4%
3480000 19
 
9.7%
ValueCountFrequency (%)
3480000 19
 
9.7%
3470000 32
16.4%
3460000 20
 
10.3%
3450000 64
32.8%
3440000 8
 
4.1%
3430000 14
 
7.2%
3420000 30
15.4%
3410000 8
 
4.1%

관리번호
Text

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:39:45.275798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4290
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

Unique195 ?
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
 
0.5%
3450000-117-2003-00014 1
 
0.5%
3460000-117-2015-00001 1
 
0.5%
3460000-117-2015-00002 1
 
0.5%
3460000-117-2008-00001 1
 
0.5%
3460000-117-2020-00001 1
 
0.5%
3460000-117-2021-00001 1
 
0.5%
3460000-117-2020-00002 1
 
0.5%
3460000-117-2020-00003 1
 
0.5%
3460000-117-2011-00001 1
 
0.5%
Other values (185) 185
94.9%
2023-12-11T03:39:45.853742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1857
43.3%
1 592
 
13.8%
- 585
 
13.6%
2 292
 
6.8%
7 254
 
5.9%
3 253
 
5.9%
4 242
 
5.6%
5 91
 
2.1%
8 55
 
1.3%
6 48
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3705
86.4%
Dash Punctuation 585
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1857
50.1%
1 592
 
16.0%
2 292
 
7.9%
7 254
 
6.9%
3 253
 
6.8%
4 242
 
6.5%
5 91
 
2.5%
8 55
 
1.5%
6 48
 
1.3%
9 21
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 585
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1857
43.3%
1 592
 
13.8%
- 585
 
13.6%
2 292
 
6.8%
7 254
 
5.9%
3 253
 
5.9%
4 242
 
5.6%
5 91
 
2.1%
8 55
 
1.3%
6 48
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1857
43.3%
1 592
 
13.8%
- 585
 
13.6%
2 292
 
6.8%
7 254
 
5.9%
3 253
 
5.9%
4 242
 
5.6%
5 91
 
2.1%
8 55
 
1.3%
6 48
 
1.1%

인허가일자
Real number (ℝ)

Distinct180
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20114280
Minimum19930205
Maximum20210727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:46.081838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930205
5-th percentile20031021
Q120060708
median20100917
Q320180212
95-th percentile20201151
Maximum20210727
Range280522
Interquartile range (IQR)119505

Descriptive statistics

Standard deviation60884.634
Coefficient of variation (CV)0.0030269358
Kurtosis-1.1565378
Mean20114280
Median Absolute Deviation (MAD)50287
Skewness0.018681166
Sum3.9222845 × 109
Variance3.7069387 × 109
MonotonicityNot monotonic
2023-12-11T03:39:46.320110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140113 4
 
2.1%
20031021 3
 
1.5%
20150203 3
 
1.5%
20190725 2
 
1.0%
20190628 2
 
1.0%
20060508 2
 
1.0%
20150915 2
 
1.0%
20181105 2
 
1.0%
20100210 2
 
1.0%
20181217 2
 
1.0%
Other values (170) 171
87.7%
ValueCountFrequency (%)
19930205 1
 
0.5%
20030320 1
 
0.5%
20030522 1
 
0.5%
20030721 1
 
0.5%
20030731 1
 
0.5%
20030806 1
 
0.5%
20030906 1
 
0.5%
20031006 1
 
0.5%
20031015 1
 
0.5%
20031021 3
1.5%
ValueCountFrequency (%)
20210727 1
0.5%
20210616 1
0.5%
20210608 1
0.5%
20210524 1
0.5%
20210517 1
0.5%
20210511 1
0.5%
20210506 1
0.5%
20210126 1
0.5%
20201210 1
0.5%
20201207 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
121 
1
74 

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 (%)
3 121
62.1%
1 74
37.9%

Length

2023-12-11T03:39:46.539295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:46.706222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 121
62.1%
1 74
37.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
121 
영업/정상
74 

Length

Max length5
Median length2
Mean length3.1384615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 121
62.1%
영업/정상 74
37.9%

Length

2023-12-11T03:39:46.882902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:47.061447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 121
62.1%
영업/정상 74
37.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
121 
1
74 

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 (%)
2 121
62.1%
1 74
37.9%

Length

2023-12-11T03:39:47.230379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:47.414630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 121
62.1%
1 74
37.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
121 
영업
74 

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 121
62.1%
영업 74
37.9%

Length

2023-12-11T03:39:47.575441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:47.745146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 121
62.1%
영업 74
37.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)95.0%
Missing74
Missing (%)37.9%
Infinite0
Infinite (%)0.0%
Mean20131848
Minimum20040603
Maximum20210402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:47.952137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040603
5-th percentile20051207
Q120081010
median20140306
Q320180528
95-th percentile20200611
Maximum20210402
Range169799
Interquartile range (IQR)99518

Descriptive statistics

Standard deviation50313.602
Coefficient of variation (CV)0.0024992044
Kurtosis-1.3096887
Mean20131848
Median Absolute Deviation (MAD)49378
Skewness-0.12249925
Sum2.4359536 × 109
Variance2.5314585 × 109
MonotonicityNot monotonic
2023-12-11T03:39:48.207784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080909 2
 
1.0%
20181031 2
 
1.0%
20161102 2
 
1.0%
20100706 2
 
1.0%
20210219 2
 
1.0%
20161122 2
 
1.0%
20070125 1
 
0.5%
20080219 1
 
0.5%
20100304 1
 
0.5%
20120926 1
 
0.5%
Other values (105) 105
53.8%
(Missing) 74
37.9%
ValueCountFrequency (%)
20040603 1
0.5%
20041126 1
0.5%
20041201 1
0.5%
20041229 1
0.5%
20050324 1
0.5%
20051017 1
0.5%
20051207 1
0.5%
20060109 1
0.5%
20060124 1
0.5%
20060328 1
0.5%
ValueCountFrequency (%)
20210402 1
0.5%
20210219 2
1.0%
20201229 1
0.5%
20201214 1
0.5%
20200707 1
0.5%
20200611 1
0.5%
20200512 1
0.5%
20200501 1
0.5%
20200413 1
0.5%
20200210 1
0.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

소재지전화
Text

MISSING 

Distinct121
Distinct (%)89.6%
Missing60
Missing (%)30.8%
Memory size1.7 KiB
2023-12-11T03:39:48.725672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.614815
Min length7

Characters and Unicode

Total characters1433
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

Unique110 ?
Unique (%)81.5%

Sample

1st row053 5875605
2nd row053 9549460
3rd row053 250 2024
4th row053 4262669
5th row053 4223753
ValueCountFrequency (%)
053 98
33.8%
070 4
 
1.4%
5252113 4
 
1.4%
954 3
 
1.0%
294 3
 
1.0%
7301 3
 
1.0%
583 2
 
0.7%
956 2
 
0.7%
313 2
 
0.7%
0080 2
 
0.7%
Other values (153) 167
57.6%
2023-12-11T03:39:49.594802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 236
16.5%
0 233
16.3%
3 218
15.2%
155
10.8%
2 110
7.7%
1 96
6.7%
6 89
 
6.2%
8 83
 
5.8%
4 81
 
5.7%
9 67
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1278
89.2%
Space Separator 155
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 236
18.5%
0 233
18.2%
3 218
17.1%
2 110
8.6%
1 96
7.5%
6 89
 
7.0%
8 83
 
6.5%
4 81
 
6.3%
9 67
 
5.2%
7 65
 
5.1%
Space Separator
ValueCountFrequency (%)
155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1433
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 236
16.5%
0 233
16.3%
3 218
15.2%
155
10.8%
2 110
7.7%
1 96
6.7%
6 89
 
6.2%
8 83
 
5.8%
4 81
 
5.7%
9 67
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 236
16.5%
0 233
16.3%
3 218
15.2%
155
10.8%
2 110
7.7%
1 96
6.7%
6 89
 
6.2%
8 83
 
5.8%
4 81
 
5.7%
9 67
 
4.7%

소재지면적
Text

MISSING 

Distinct127
Distinct (%)74.7%
Missing25
Missing (%)12.8%
Memory size1.7 KiB
2023-12-11T03:39:50.208641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0294118
Min length3

Characters and Unicode

Total characters855
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

Unique111 ?
Unique (%)65.3%

Sample

1st row66.04
2nd row65.60
3rd row26.44
4th row19.95
5th row66.00
ValueCountFrequency (%)
10.00 8
 
4.7%
49.50 6
 
3.5%
9.90 6
 
3.5%
20.00 5
 
2.9%
6.60 5
 
2.9%
3.30 4
 
2.4%
30.00 3
 
1.8%
50.00 3
 
1.8%
00 3
 
1.8%
16.50 3
 
1.8%
Other values (117) 124
72.9%
2023-12-11T03:39:51.023071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202
23.6%
. 170
19.9%
1 68
 
8.0%
2 64
 
7.5%
6 59
 
6.9%
4 56
 
6.5%
3 55
 
6.4%
5 53
 
6.2%
9 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 683
79.9%
Other Punctuation 172
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202
29.6%
1 68
 
10.0%
2 64
 
9.4%
6 59
 
8.6%
4 56
 
8.2%
3 55
 
8.1%
5 53
 
7.8%
9 52
 
7.6%
8 46
 
6.7%
7 28
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 170
98.8%
, 2
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202
23.6%
. 170
19.9%
1 68
 
8.0%
2 64
 
7.5%
6 59
 
6.9%
4 56
 
6.5%
3 55
 
6.4%
5 53
 
6.2%
9 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202
23.6%
. 170
19.9%
1 68
 
8.0%
2 64
 
7.5%
6 59
 
6.9%
4 56
 
6.5%
3 55
 
6.4%
5 53
 
6.2%
9 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct124
Distinct (%)64.6%
Missing3
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean704224.2
Minimum700082
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:51.312954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700082
5-th percentile701210.5
Q1702307.5
median702903
Q3704944
95-th percentile711821.9
Maximum711891
Range11809
Interquartile range (IQR)2636.5

Descriptive statistics

Standard deviation2817.3362
Coefficient of variation (CV)0.0040006239
Kurtosis1.8688948
Mean704224.2
Median Absolute Deviation (MAD)1086.5
Skewness1.5024365
Sum1.3521105 × 108
Variance7937383.1
MonotonicityNot monotonic
2023-12-11T03:39:51.640157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702903 11
 
5.6%
704830 7
 
3.6%
702300 6
 
3.1%
711821 4
 
2.1%
701804 4
 
2.1%
702825 4
 
2.1%
702865 3
 
1.5%
704944 3
 
1.5%
705840 3
 
1.5%
702845 3
 
1.5%
Other values (114) 144
73.8%
ValueCountFrequency (%)
700082 1
0.5%
700192 1
0.5%
700810 1
0.5%
700823 1
0.5%
700826 1
0.5%
700845 2
1.0%
700847 1
0.5%
701140 1
0.5%
701150 1
0.5%
701260 1
0.5%
ValueCountFrequency (%)
711891 1
 
0.5%
711874 1
 
0.5%
711852 1
 
0.5%
711842 1
 
0.5%
711839 1
 
0.5%
711833 2
1.0%
711832 2
1.0%
711823 1
 
0.5%
711821 4
2.1%
711814 1
 
0.5%

소재지전체주소
Text

Distinct157
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:39:52.215937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length23.769231
Min length17

Characters and Unicode

Total characters4635
Distinct characters159
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)66.2%

Sample

1st row대구광역시 중구 동인동*가 ****번지 (*층)
2nd row대구광역시 중구 종로*가 ****번지
3rd row대구광역시 중구 대봉동 **-**번지 (**,**호)
4th row대구광역시 중구 동인동*가 ****-****번지 지상*층
5th row대구광역시 중구 남산동 ****-****번지 지상*층
ValueCountFrequency (%)
대구광역시 195
21.9%
번지 160
17.9%
북구 64
 
7.2%
44
 
4.9%
달서구 31
 
3.5%
동구 30
 
3.4%
수성구 20
 
2.2%
달성군 19
 
2.1%
층 17
 
1.9%
서구 14
 
1.6%
Other values (127) 298
33.4%
2023-12-11T03:39:52.997882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 945
20.4%
895
19.3%
구 380
 
8.2%
동 221
 
4.8%
대 209
 
4.5%
역 196
 
4.2%
시 196
 
4.2%
광 195
 
4.2%
지 193
 
4.2%
번 160
 
3.5%
Other values (149) 1045
22.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2619
56.5%
Other Punctuation 951
 
20.5%
Space Separator 895
 
19.3%
Dash Punctuation 149
 
3.2%
Open Punctuation 9
 
0.2%
Close Punctuation 9
 
0.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 380
14.5%
동 221
 
8.4%
대 209
 
8.0%
역 196
 
7.5%
시 196
 
7.5%
광 195
 
7.4%
지 193
 
7.4%
번 160
 
6.1%
북 65
 
2.5%
달 64
 
2.4%
Other values (140) 740
28.3%
Other Punctuation
ValueCountFrequency (%)
* 945
99.4%
, 4
 
0.4%
. 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
895
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2619
56.5%
Common 2013
43.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 380
14.5%
동 221
 
8.4%
대 209
 
8.0%
역 196
 
7.5%
시 196
 
7.5%
광 195
 
7.4%
지 193
 
7.4%
번 160
 
6.1%
북 65
 
2.5%
달 64
 
2.4%
Other values (140) 740
28.3%
Common
ValueCountFrequency (%)
* 945
46.9%
895
44.5%
- 149
 
7.4%
( 9
 
0.4%
) 9
 
0.4%
, 4
 
0.2%
. 2
 
0.1%
Latin
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2619
56.5%
ASCII 2016
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 945
46.9%
895
44.4%
- 149
 
7.4%
( 9
 
0.4%
) 9
 
0.4%
, 4
 
0.2%
. 2
 
0.1%
A 2
 
0.1%
C 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
구 380
14.5%
동 221
 
8.4%
대 209
 
8.0%
역 196
 
7.5%
시 196
 
7.5%
광 195
 
7.4%
지 193
 
7.4%
번 160
 
6.1%
북 65
 
2.5%
달 64
 
2.4%
Other values (140) 740
28.3%

도로명전체주소
Text

MISSING 

Distinct121
Distinct (%)87.1%
Missing56
Missing (%)28.7%
Memory size1.7 KiB
2023-12-11T03:39:53.507759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length28.913669
Min length20

Characters and Unicode

Total characters4019
Distinct characters187
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)77.0%

Sample

1st row대구광역시 중구 중앙대로**길 ** (종로*가)
2nd row대구광역시 중구 동덕로**길 **-*, *층 (동인동*가)
3rd row대구광역시 중구 봉산문화*길 *, *층 (봉산동)
4th row대구광역시 중구 달구벌대로 **** (계산동*가, 지하*층)
5th row대구광역시 중구 국채보상로***길 ** (동인동*가)
ValueCountFrequency (%)
대구광역시 139
16.9%
139
16.9%
층 65
 
7.9%
북구 36
 
4.4%
동구 26
 
3.2%
달서구 25
 
3.0%
호 21
 
2.5%
달성군 15
 
1.8%
수성구 12
 
1.5%
서구 12
 
1.5%
Other values (198) 334
40.5%
2023-12-11T03:39:54.241449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
685
17.0%
* 657
16.3%
구 280
 
7.0%
동 187
 
4.7%
대 171
 
4.3%
시 143
 
3.6%
역 141
 
3.5%
광 139
 
3.5%
) 127
 
3.2%
로 127
 
3.2%
Other values (177) 1362
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2289
57.0%
Other Punctuation 754
 
18.8%
Space Separator 685
 
17.0%
Close Punctuation 127
 
3.2%
Open Punctuation 127
 
3.2%
Dash Punctuation 33
 
0.8%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 280
 
12.2%
동 187
 
8.2%
대 171
 
7.5%
시 143
 
6.2%
역 141
 
6.2%
광 139
 
6.1%
로 127
 
5.5%
길 84
 
3.7%
층 71
 
3.1%
서 56
 
2.4%
Other values (169) 890
38.9%
Other Punctuation
ValueCountFrequency (%)
* 657
87.1%
, 97
 
12.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
C 1
 
25.0%
Space Separator
ValueCountFrequency (%)
685
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2289
57.0%
Common 1726
42.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 280
 
12.2%
동 187
 
8.2%
대 171
 
7.5%
시 143
 
6.2%
역 141
 
6.2%
광 139
 
6.1%
로 127
 
5.5%
길 84
 
3.7%
층 71
 
3.1%
서 56
 
2.4%
Other values (169) 890
38.9%
Common
ValueCountFrequency (%)
685
39.7%
* 657
38.1%
) 127
 
7.4%
( 127
 
7.4%
, 97
 
5.6%
- 33
 
1.9%
Latin
ValueCountFrequency (%)
A 3
75.0%
C 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2289
57.0%
ASCII 1730
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
685
39.6%
* 657
38.0%
) 127
 
7.3%
( 127
 
7.3%
, 97
 
5.6%
- 33
 
1.9%
A 3
 
0.2%
C 1
 
0.1%
Hangul
ValueCountFrequency (%)
구 280
 
12.2%
동 187
 
8.2%
대 171
 
7.5%
시 143
 
6.2%
역 141
 
6.2%
광 139
 
6.1%
로 127
 
5.5%
길 84
 
3.7%
층 71
 
3.1%
서 56
 
2.4%
Other values (169) 890
38.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct103
Distinct (%)74.6%
Missing57
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean41956.638
Minimum41042
Maximum43010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:54.493955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41042
5-th percentile41082
Q141468.25
median41754.5
Q342658
95-th percentile42947.65
Maximum43010
Range1968
Interquartile range (IQR)1189.75

Descriptive statistics

Standard deviation645.59498
Coefficient of variation (CV)0.015387195
Kurtosis-1.4306514
Mean41956.638
Median Absolute Deviation (MAD)562.5
Skewness0.22706975
Sum5790016
Variance416792.88
MonotonicityNot monotonic
2023-12-11T03:39:54.768349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 7
 
3.6%
42722 6
 
3.1%
42500 3
 
1.5%
42904 3
 
1.5%
41163 3
 
1.5%
41754 3
 
1.5%
41491 3
 
1.5%
41082 3
 
1.5%
41459 2
 
1.0%
41504 2
 
1.0%
Other values (93) 103
52.8%
(Missing) 57
29.2%
ValueCountFrequency (%)
41042 1
 
0.5%
41046 1
 
0.5%
41051 1
 
0.5%
41055 1
 
0.5%
41065 1
 
0.5%
41078 1
 
0.5%
41082 3
1.5%
41085 1
 
0.5%
41119 1
 
0.5%
41124 1
 
0.5%
ValueCountFrequency (%)
43010 1
 
0.5%
43003 1
 
0.5%
42974 1
 
0.5%
42968 2
1.0%
42957 2
1.0%
42946 2
1.0%
42943 1
 
0.5%
42922 1
 
0.5%
42914 1
 
0.5%
42904 3
1.5%

사업장명
Text

Distinct177
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:39:55.261191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.4512821
Min length2

Characters and Unicode

Total characters1258
Distinct characters204
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

Unique162 ?
Unique (%)83.1%

Sample

1st row사옹원
2nd row(주)일성화물
3rd row아진식품
4th row박통식품
5th row대구우체국
ValueCountFrequency (%)
주식회사 6
 
2.8%
개인용달 4
 
1.9%
주)정우운수 3
 
1.4%
베스트바이 3
 
1.4%
개별화물 3
 
1.4%
주 3
 
1.4%
김태복 2
 
0.9%
주)일성화물 2
 
0.9%
가야푸드 2
 
0.9%
미소물류 2
 
0.9%
Other values (178) 186
86.1%
2023-12-11T03:39:55.934770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 91
 
7.2%
) 79
 
6.3%
( 78
 
6.2%
스 39
 
3.1%
물 38
 
3.0%
식 35
 
2.8%
드 29
 
2.3%
류 28
 
2.2%
대 27
 
2.1%
푸 27
 
2.1%
Other values (194) 787
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1072
85.2%
Close Punctuation 79
 
6.3%
Open Punctuation 78
 
6.2%
Space Separator 21
 
1.7%
Uppercase Letter 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 91
 
8.5%
스 39
 
3.6%
물 38
 
3.5%
식 35
 
3.3%
드 29
 
2.7%
류 28
 
2.6%
대 27
 
2.5%
푸 27
 
2.5%
성 25
 
2.3%
통 22
 
2.1%
Other values (184) 711
66.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
25.0%
F 1
12.5%
C 1
12.5%
M 1
12.5%
D 1
12.5%
T 1
12.5%
S 1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1072
85.2%
Common 178
 
14.1%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 91
 
8.5%
스 39
 
3.6%
물 38
 
3.5%
식 35
 
3.3%
드 29
 
2.7%
류 28
 
2.6%
대 27
 
2.5%
푸 27
 
2.5%
성 25
 
2.3%
통 22
 
2.1%
Other values (184) 711
66.3%
Latin
ValueCountFrequency (%)
G 2
25.0%
F 1
12.5%
C 1
12.5%
M 1
12.5%
D 1
12.5%
T 1
12.5%
S 1
12.5%
Common
ValueCountFrequency (%)
) 79
44.4%
( 78
43.8%
21
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1072
85.2%
ASCII 186
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 91
 
8.5%
스 39
 
3.6%
물 38
 
3.5%
식 35
 
3.3%
드 29
 
2.7%
류 28
 
2.6%
대 27
 
2.5%
푸 27
 
2.5%
성 25
 
2.3%
통 22
 
2.1%
Other values (184) 711
66.3%
ASCII
ValueCountFrequency (%)
) 79
42.5%
( 78
41.9%
21
 
11.3%
G 2
 
1.1%
F 1
 
0.5%
C 1
 
0.5%
M 1
 
0.5%
D 1
 
0.5%
T 1
 
0.5%
S 1
 
0.5%

최종수정시점
Real number (ℝ)

Distinct189
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0142825 × 1013
Minimum2.0031121 × 1013
Maximum2.021073 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:56.187973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0031121 × 1013
5-th percentile2.0041011 × 1013
Q12.0090211 × 1013
median2.0161116 × 1013
Q32.0191215 × 1013
95-th percentile2.0210442 × 1013
Maximum2.021073 × 1013
Range1.7960911 × 1011
Interquartile range (IQR)1.0100354 × 1011

Descriptive statistics

Standard deviation5.9153816 × 1010
Coefficient of variation (CV)0.002936719
Kurtosis-1.2688339
Mean2.0142825 × 1013
Median Absolute Deviation (MAD)4.0092011 × 1010
Skewness-0.50390008
Sum3.9278508 × 1015
Variance3.499174 × 1021
MonotonicityNot monotonic
2023-12-11T03:39:56.444860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041011000000 6
 
3.1%
20161122170313 2
 
1.0%
20040204000000 1
 
0.5%
20210608175550 1
 
0.5%
20201005150455 1
 
0.5%
20201211094457 1
 
0.5%
20200413152039 1
 
0.5%
20200210153155 1
 
0.5%
20141210093840 1
 
0.5%
20180206143523 1
 
0.5%
Other values (179) 179
91.8%
ValueCountFrequency (%)
20031121000000 1
 
0.5%
20031215000000 1
 
0.5%
20040107000000 1
 
0.5%
20040114000000 1
 
0.5%
20040204000000 1
 
0.5%
20040212000000 1
 
0.5%
20040401000000 1
 
0.5%
20040506000000 1
 
0.5%
20040811000000 1
 
0.5%
20041011000000 6
3.1%
ValueCountFrequency (%)
20210730114928 1
0.5%
20210727134453 1
0.5%
20210623111545 1
0.5%
20210616134232 1
0.5%
20210610155632 1
0.5%
20210609094156 1
0.5%
20210608175550 1
0.5%
20210604160905 1
0.5%
20210524175136 1
0.5%
20210506171955 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
132 
U
63 

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 132
67.7%
U 63
32.3%

Length

2023-12-11T03:39:56.709809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:56.868885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 132
67.7%
u 63
32.3%

데이터갱신일자
Date

Distinct75
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-08-01 02:40:00
2023-12-11T03:39:57.524471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:39:57.816293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
식품운반업
195 

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 195
100.0%

Length

2023-12-11T03:39:58.052341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:58.270890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 195
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct151
Distinct (%)81.2%
Missing9
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean341585.89
Minimum327299.69
Maximum355567.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:58.455467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327299.69
5-th percentile330467.62
Q1338432.76
median340246.98
Q3345815.32
95-th percentile352803.15
Maximum355567.69
Range28268.001
Interquartile range (IQR)7382.5531

Descriptive statistics

Standard deviation5992.4345
Coefficient of variation (CV)0.01754298
Kurtosis0.077301513
Mean341585.89
Median Absolute Deviation (MAD)3423.0909
Skewness0.1617918
Sum63534976
Variance35909271
MonotonicityNot monotonic
2023-12-11T03:39:58.697141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338985.366314 9
 
4.6%
337329.213273 6
 
3.1%
340946.597285 3
 
1.5%
327735.044524 3
 
1.5%
339388.690364 3
 
1.5%
337698.438286 2
 
1.0%
338167.933836 2
 
1.0%
329271.879011 2
 
1.0%
334750.422674 2
 
1.0%
339421.284861 2
 
1.0%
Other values (141) 152
77.9%
(Missing) 9
 
4.6%
ValueCountFrequency (%)
327299.692057 1
 
0.5%
327735.044524 3
1.5%
329271.879011 2
1.0%
329604.038183 1
 
0.5%
329882.0 1
 
0.5%
330128.30921 1
 
0.5%
330388.015281 1
 
0.5%
330706.421358 1
 
0.5%
332426.0567 1
 
0.5%
333070.51248 1
 
0.5%
ValueCountFrequency (%)
355567.693374 2
1.0%
355474.652805 1
0.5%
355444.760056 1
0.5%
354790.108191 1
0.5%
354215.082384 1
0.5%
353971.781376 1
0.5%
353414.507288 1
0.5%
353325.435461 1
0.5%
352803.154449 2
1.0%
352644.320881 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct151
Distinct (%)81.2%
Missing9
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean264322.59
Minimum240636.85
Maximum273735.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:39:58.994887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240636.85
5-th percentile256643.32
Q1261818.39
median264718.49
Q3267354.45
95-th percentile271580.76
Maximum273735.13
Range33098.279
Interquartile range (IQR)5536.0599

Descriptive statistics

Standard deviation4734.1026
Coefficient of variation (CV)0.017910321
Kurtosis4.3017006
Mean264322.59
Median Absolute Deviation (MAD)2715.4224
Skewness-1.2366874
Sum49164002
Variance22411727
MonotonicityNot monotonic
2023-12-11T03:39:59.271634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
267354.446312 9
 
4.6%
260416.780233 6
 
3.1%
259953.127592 3
 
1.5%
263479.562399 3
 
1.5%
269664.126149 3
 
1.5%
267627.426015 2
 
1.0%
265608.87802 2
 
1.0%
254619.354156 2
 
1.0%
256643.317146 2
 
1.0%
269777.145939 2
 
1.0%
Other values (141) 152
77.9%
(Missing) 9
 
4.6%
ValueCountFrequency (%)
240636.852024 1
0.5%
244838.382091 1
0.5%
248561.77396 1
0.5%
253989.0 1
0.5%
254171.232318 1
0.5%
254619.354156 2
1.0%
255771.102947 1
0.5%
256102.203744 1
0.5%
256643.317146 2
1.0%
257516.968663 1
0.5%
ValueCountFrequency (%)
273735.131409 1
0.5%
273355.790439 1
0.5%
273296.193994 1
0.5%
272745.678782 1
0.5%
272600.063881 2
1.0%
272219.113572 1
0.5%
272092.19703 1
0.5%
271937.692097 1
0.5%
271825.291142 1
0.5%
270847.157898 2
1.0%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
식품운반업
195 

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 195
100.0%

Length

2023-12-11T03:39:59.540277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:39:59.696586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 195
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
194 
0
 
1

Length

Max length4
Median length4
Mean length3.9846154
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 194
99.5%
0 1
 
0.5%

Length

2023-12-11T03:39:59.864911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:00.055951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
99.5%
0 1
 
0.5%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
194 
0
 
1

Length

Max length4
Median length4
Mean length3.9846154
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 194
99.5%
0 1
 
0.5%

Length

2023-12-11T03:40:00.257382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:00.454307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
99.5%
0 1
 
0.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
141 
상수도전용
54 

Length

Max length5
Median length4
Mean length4.2769231
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 141
72.3%
상수도전용 54
 
27.7%

Length

2023-12-11T03:40:00.632216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:00.837453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
72.3%
상수도전용 54
 
27.7%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
194 
0
 
1

Length

Max length4
Median length4
Mean length3.9846154
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 194
99.5%
0 1
 
0.5%

Length

2023-12-11T03:40:01.028470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:01.208807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
99.5%
0 1
 
0.5%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
139 
<NA>
53 
3
 
2
1
 
1

Length

Max length4
Median length1
Mean length1.8153846
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 139
71.3%
<NA> 53
 
27.2%
3 2
 
1.0%
1 1
 
0.5%

Length

2023-12-11T03:40:01.443553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:01.635237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 139
71.3%
na 53
 
27.2%
3 2
 
1.0%
1 1
 
0.5%

공장사무직종업원수
Categorical

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
121 
<NA>
52 
1
14 
2
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.8
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 121
62.1%
<NA> 52
26.7%
1 14
 
7.2%
2 5
 
2.6%
3 2
 
1.0%
5 1
 
0.5%

Length

2023-12-11T03:40:01.823981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:02.029674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 121
62.1%
na 52
26.7%
1 14
 
7.2%
2 5
 
2.6%
3 2
 
1.0%
5 1
 
0.5%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)4.9%
Missing52
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean0.29370629
Minimum0
Maximum7
Zeros125
Zeros (%)64.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:40:02.231256image/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 deviation0.98461523
Coefficient of variation (CV)3.3523804
Kurtosis20.944785
Mean0.29370629
Median Absolute Deviation (MAD)0
Skewness4.3178114
Sum42
Variance0.96946715
MonotonicityNot monotonic
2023-12-11T03:40:02.489171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 125
64.1%
1 9
 
4.6%
3 3
 
1.5%
2 2
 
1.0%
4 2
 
1.0%
7 1
 
0.5%
5 1
 
0.5%
(Missing) 52
26.7%
ValueCountFrequency (%)
0 125
64.1%
1 9
 
4.6%
2 2
 
1.0%
3 3
 
1.5%
4 2
 
1.0%
5 1
 
0.5%
7 1
 
0.5%
ValueCountFrequency (%)
7 1
 
0.5%
5 1
 
0.5%
4 2
 
1.0%
3 3
 
1.5%
2 2
 
1.0%
1 9
 
4.6%
0 125
64.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)4.2%
Missing53
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean0.24647887
Minimum0
Maximum7
Zeros128
Zeros (%)65.6%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:40:02.741723image/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 deviation0.93919099
Coefficient of variation (CV)3.810432
Kurtosis27.450437
Mean0.24647887
Median Absolute Deviation (MAD)0
Skewness4.9573004
Sum35
Variance0.88207971
MonotonicityNot monotonic
2023-12-11T03:40:02.923313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 128
65.6%
2 5
 
2.6%
1 5
 
2.6%
5 2
 
1.0%
7 1
 
0.5%
3 1
 
0.5%
(Missing) 53
27.2%
ValueCountFrequency (%)
0 128
65.6%
1 5
 
2.6%
2 5
 
2.6%
3 1
 
0.5%
5 2
 
1.0%
7 1
 
0.5%
ValueCountFrequency (%)
7 1
 
0.5%
5 2
 
1.0%
3 1
 
0.5%
2 5
 
2.6%
1 5
 
2.6%
0 128
65.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
87 
자가
64 
임대
44 

Length

Max length4
Median length2
Mean length2.8923077
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 87
44.6%
자가 64
32.8%
임대 44
22.6%

Length

2023-12-11T03:40:03.161220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:03.375254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
44.6%
자가 64
32.8%
임대 44
22.6%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
180 
0
 
15

Length

Max length4
Median length4
Mean length3.7692308
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> 180
92.3%
0 15
 
7.7%

Length

2023-12-11T03:40:03.589065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:03.792948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 180
92.3%
0 15
 
7.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
180 
0
 
15

Length

Max length4
Median length4
Mean length3.7692308
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> 180
92.3%
0 15
 
7.7%

Length

2023-12-11T03:40:03.988831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:40:04.172052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 180
92.3%
0 15
 
7.7%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size327.0 B
False
195 
ValueCountFrequency (%)
False 195
100.0%
2023-12-11T03:40:04.330694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.78594872
Minimum0
Maximum134.13
Zeros190
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T03:40:04.543161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum134.13
Range134.13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.6334578
Coefficient of variation (CV)12.257107
Kurtosis192.12076
Mean0.78594872
Median Absolute Deviation (MAD)0
Skewness13.816562
Sum153.26
Variance92.80351
MonotonicityNot monotonic
2023-12-11T03:40:04.892940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 190
97.4%
134.13 1
 
0.5%
10.37 1
 
0.5%
3.3 1
 
0.5%
3.0 1
 
0.5%
2.46 1
 
0.5%
ValueCountFrequency (%)
0.0 190
97.4%
2.46 1
 
0.5%
3.0 1
 
0.5%
3.3 1
 
0.5%
10.37 1
 
0.5%
134.13 1
 
0.5%
ValueCountFrequency (%)
134.13 1
 
0.5%
10.37 1
 
0.5%
3.3 1
 
0.5%
3.0 1
 
0.5%
2.46 1
 
0.5%
0.0 190
97.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing195
Missing (%)100.0%
Memory size1.8 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품운반업07_22_09_P34100003410000-117-2004-0000120040114<NA>3폐업2폐업20080225<NA><NA><NA><NA>66.04700847대구광역시 중구 동인동*가 ****번지 (*층)<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 종로*가 ****번지대구광역시 중구 중앙대로**길 ** (종로*가)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 **-**번지 (**,**호)<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 동인동*가 ****-****번지 지상*층대구광역시 중구 동덕로**길 **-*, *층 (동인동*가)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 ****-****번지 지상*층<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 ****-****번지 지상*층대구광역시 중구 봉산문화*길 *, *층 (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 계산동*가 ****번지 지하*층대구광역시 중구 달구벌대로 **** (계산동*가, 지하*층)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 동인동*가 ****-****번지대구광역시 중구 국채보상로***길 ** (동인동*가)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_P34200003420000-117-2008-0000120080214<NA>1영업/정상1영업<NA><NA><NA><NA>053 759 482849.50701804대구광역시 동구 방촌동 ****-*** *층대구광역시 동구 화랑로 *** (방촌동,*층)41163(주)성진냉동20201125102623U2020-11-27 02:40:00.0식품운반업350504.394278265405.168322식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><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 ***-*번지대구광역시 동구 신암로**길 ** (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
185186식품운반업07_22_09_P34800003480000-117-2017-0000120171211<NA>1영업/정상1영업<NA><NA><NA><NA>070 412299956.60711821대구광역시 달성군 하빈면 동곡리 ***번지 *층대구광역시 달성군 하빈면 하빈남로 ***-*, *층42904(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>
186187식품운반업07_22_09_P34800003480000-117-2004-0000220040107<NA>3폐업2폐업20110621<NA><NA><NA>053 616336341.85711842대구광역시 달성군 옥포면 강림리 ***번지<NA><NA>(주)굿모닝로지스20040107000000I2018-08-31 23:59:59.0식품운반업329604.038183254171.232318식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
187188식품운반업07_22_09_P34800003480000-117-2006-0000120060808<NA>3폐업2폐업20110808<NA><NA><NA>053 582164735.00711821대구광역시 달성군 하빈면 현내리 ***번지<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>
188189식품운반업07_22_09_P34800003480000-117-2008-0000120080404<NA>3폐업2폐업20080414<NA><NA><NA>053 3121656<NA>711852대구광역시 달성군 논공읍 북리 ***-**번지 외 *필지 ***호<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>
189190식품운반업07_22_09_P34800003480000-117-2008-0000220080516<NA>3폐업2폐업20180528<NA><NA><NA>053 635728049.50711832대구광역시 달성군 화원읍 명곡리 ***-*번지대구광역시 달성군 화원읍 성화로 **42946(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>
190191식품운반업07_22_09_P34800003480000-117-2008-0000320081127<NA>3폐업2폐업20170510<NA><NA><NA>053 614300750.00711874대구광역시 달성군 현풍면 원교리 **번지대구광역시 달성군 현풍면 비슬로***길 *43003달성우체국20170510164444I2018-08-31 23:59:59.0식품운반업330128.30921244838.382091식품운반업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
191192식품운반업07_22_09_P34800003480000-117-2013-0000120130117<NA>3폐업2폐업20140804<NA><NA><NA>070 44178456256.00711833대구광역시 달성군 화원읍 설화리 ***-*번지 . *층대구광역시 달성군 화원읍 옥터길 **, *층42957싱싱푸드20130214095247I2018-08-31 23:59:59.0식품운반업334264.122637256102.203744식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
192193식품운반업07_22_09_P34800003480000-117-2014-0000120140113<NA>3폐업2폐업20161202<NA><NA><NA>070 4122999570.00711821대구광역시 달성군 하빈면 동곡리 ***번지대구광역시 달성군 하빈면 하빈남로 ***-*, *층42904주식회사 광림유통20160624152311I2018-08-31 23:59:59.0식품운반업327735.044524263479.562399식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
193194식품운반업07_22_09_P34800003480000-117-2016-0000120160930<NA>3폐업2폐업20191211<NA><NA><NA><NA>70.00711821대구광역시 달성군 하빈면 동곡리 ***번지대구광역시 달성군 하빈면 하빈남로 ***-*42904(주)달성푸드20191211143011U2019-12-13 02:40:00.0식품운반업327735.044524263479.562399식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
194195식품운반업07_22_09_P34800003480000-117-2019-0000220190628<NA>1영업/정상1영업<NA><NA><NA><NA>053 313 303520.00<NA>대구광역시 달성군 옥포읍 강림리 ***-*번지대구광역시 달성군 옥포읍 시저로*길 **-*42968백제농산20190807172026U2019-08-09 02:40:00.0식품운반업329271.879011254619.354156식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>