Overview

Dataset statistics

Number of variables47
Number of observations191
Missing cells2682
Missing cells (%)29.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory75.9 KiB
Average record size in memory406.7 B

Variable types

Numeric12
Categorical15
Text6
Unsupported12
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_09_P_식품운반업_5월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000089629&dataSetDetailId=DDI_0000089686&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
본사종업원수 is highly imbalanced (50.9%)Imbalance
보증액 is highly imbalanced (62.2%)Imbalance
월세액 is highly imbalanced (62.2%)Imbalance
인허가취소일자 has 191 (100.0%) missing valuesMissing
폐업일자 has 70 (36.6%) missing valuesMissing
휴업시작일자 has 191 (100.0%) missing valuesMissing
휴업종료일자 has 191 (100.0%) missing valuesMissing
재개업일자 has 191 (100.0%) missing valuesMissing
소재지전화 has 58 (30.4%) missing valuesMissing
소재지면적 has 21 (11.0%) missing valuesMissing
소재지우편번호 has 3 (1.6%) missing valuesMissing
도로명전체주소 has 56 (29.3%) missing valuesMissing
도로명우편번호 has 57 (29.8%) missing valuesMissing
좌표정보(X) has 9 (4.7%) missing valuesMissing
좌표정보(Y) has 9 (4.7%) missing valuesMissing
남성종사자수 has 191 (100.0%) missing valuesMissing
여성종사자수 has 191 (100.0%) missing valuesMissing
영업장주변구분명 has 191 (100.0%) missing valuesMissing
등급구분명 has 191 (100.0%) missing valuesMissing
총종업원수 has 191 (100.0%) missing valuesMissing
공장판매직종업원수 has 53 (27.7%) missing valuesMissing
공장생산직종업원수 has 54 (28.3%) missing valuesMissing
전통업소지정번호 has 191 (100.0%) missing valuesMissing
전통업소주된음식 has 191 (100.0%) missing valuesMissing
홈페이지 has 191 (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 120 (62.8%) zerosZeros
공장생산직종업원수 has 123 (64.4%) zerosZeros
시설총규모 has 184 (96.3%) zerosZeros

Reproduction

Analysis started2024-04-21 13:34:48.025699
Analysis finished2024-04-21 13:34:49.049845
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96
Minimum1
Maximum191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:34:49.249650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.5
Q148.5
median96
Q3143.5
95-th percentile181.5
Maximum191
Range190
Interquartile range (IQR)95

Descriptive statistics

Standard deviation55.2811
Coefficient of variation (CV)0.57584479
Kurtosis-1.2
Mean96
Median Absolute Deviation (MAD)48
Skewness0
Sum18336
Variance3056
MonotonicityStrictly increasing
2024-04-21T22:34:49.701897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
2 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
Other values (181) 181
94.8%
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 (%)
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
식품운반업
191 

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 191
100.0%

Length

2024-04-21T22:34:50.116533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:50.415255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 191
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
07_22_09_P
191 

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 191
100.0%

Length

2024-04-21T22:34:50.729076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:51.029352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_09_p 191
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3448691.1
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:34:51.310764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3450000
Q33465000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)35000

Descriptive statistics

Standard deviation19943.707
Coefficient of variation (CV)0.0057829786
Kurtosis-0.88261406
Mean3448691.1
Median Absolute Deviation (MAD)20000
Skewness-0.28014927
Sum6.587 × 108
Variance3.9775145 × 108
MonotonicityIncreasing
2024-04-21T22:34:51.873385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 63
33.0%
3470000 31
16.2%
3420000 30
15.7%
3460000 20
 
10.5%
3480000 17
 
8.9%
3430000 14
 
7.3%
3410000 8
 
4.2%
3440000 8
 
4.2%
ValueCountFrequency (%)
3410000 8
 
4.2%
3420000 30
15.7%
3430000 14
 
7.3%
3440000 8
 
4.2%
3450000 63
33.0%
3460000 20
 
10.5%
3470000 31
16.2%
3480000 17
 
8.9%
ValueCountFrequency (%)
3480000 17
 
8.9%
3470000 31
16.2%
3460000 20
 
10.5%
3450000 63
33.0%
3440000 8
 
4.2%
3430000 14
 
7.3%
3420000 30
15.7%
3410000 8
 
4.2%

관리번호
Text

UNIQUE 

Distinct191
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T22:34:52.594201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4202
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

Unique191 ?
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%
3450000-117-2019-00001 1
 
0.5%
3450000-117-2018-00005 1
 
0.5%
3460000-117-2008-00001 1
 
0.5%
3460000-117-2015-00002 1
 
0.5%
3460000-117-2006-00003 1
 
0.5%
3460000-117-2006-00002 1
 
0.5%
3460000-117-2006-00001 1
 
0.5%
3460000-117-2004-00003 1
 
0.5%
3460000-117-2004-00002 1
 
0.5%
Other values (181) 181
94.8%
2024-04-21T22:34:53.676270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1821
43.3%
1 578
 
13.8%
- 573
 
13.6%
2 284
 
6.8%
7 249
 
5.9%
3 248
 
5.9%
4 238
 
5.7%
5 90
 
2.1%
8 53
 
1.3%
6 48
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3629
86.4%
Dash Punctuation 573
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1821
50.2%
1 578
 
15.9%
2 284
 
7.8%
7 249
 
6.9%
3 248
 
6.8%
4 238
 
6.6%
5 90
 
2.5%
8 53
 
1.5%
6 48
 
1.3%
9 20
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 573
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1821
43.3%
1 578
 
13.8%
- 573
 
13.6%
2 284
 
6.8%
7 249
 
5.9%
3 248
 
5.9%
4 238
 
5.7%
5 90
 
2.1%
8 53
 
1.3%
6 48
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1821
43.3%
1 578
 
13.8%
- 573
 
13.6%
2 284
 
6.8%
7 249
 
5.9%
3 248
 
5.9%
4 238
 
5.7%
5 90
 
2.1%
8 53
 
1.3%
6 48
 
1.1%

인허가일자
Real number (ℝ)

Distinct176
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20112369
Minimum19930205
Maximum20210524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:34:53.919322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930205
5-th percentile20031021
Q120060667
median20100212
Q320175668
95-th percentile20201066
Maximum20210524
Range280319
Interquartile range (IQR)115000.5

Descriptive statistics

Standard deviation60036.631
Coefficient of variation (CV)0.0029850601
Kurtosis-1.1281577
Mean20112369
Median Absolute Deviation (MAD)49991
Skewness0.039701956
Sum3.8414625 × 109
Variance3.6043971 × 109
MonotonicityNot monotonic
2024-04-21T22:34:54.163100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140113 4
 
2.1%
20031021 3
 
1.6%
20150203 3
 
1.6%
20181217 2
 
1.0%
20191001 2
 
1.0%
20060508 2
 
1.0%
20190628 2
 
1.0%
20150915 2
 
1.0%
20100210 2
 
1.0%
20181105 2
 
1.0%
Other values (166) 167
87.4%
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
1.6%
ValueCountFrequency (%)
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%
20201127 1
0.5%
20201126 1
0.5%
20201124 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
121 
1
70 

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
63.4%
1 70
36.6%

Length

2024-04-21T22:34:54.383902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:54.550770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 121
63.4%
1 70
36.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
121 
영업/정상
70 

Length

Max length5
Median length2
Mean length3.0994764
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 121
63.4%
영업/정상 70
36.6%

Length

2024-04-21T22:34:54.738807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:54.921424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 121
63.4%
영업/정상 70
36.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2
121 
1
70 

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
63.4%
1 70
36.6%

Length

2024-04-21T22:34:55.094328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:55.267223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 121
63.4%
1 70
36.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
121 
영업
70 

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
63.4%
영업 70
36.6%

Length

2024-04-21T22:34:55.437855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:34:55.612854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 121
63.4%
영업 70
36.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)95.0%
Missing70
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean20131848
Minimum20040603
Maximum20210402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:34:55.822189image/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
2024-04-21T22:34:56.083549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161102 2
 
1.0%
20100706 2
 
1.0%
20210219 2
 
1.0%
20181031 2
 
1.0%
20161122 2
 
1.0%
20080909 2
 
1.0%
20170510 1
 
0.5%
20190227 1
 
0.5%
20190517 1
 
0.5%
20110718 1
 
0.5%
Other values (105) 105
55.0%
(Missing) 70
36.6%
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 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

소재지전화
Text

MISSING 

Distinct119
Distinct (%)89.5%
Missing58
Missing (%)30.4%
Memory size1.6 KiB
2024-04-21T22:34:57.124662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.609023
Min length7

Characters and Unicode

Total characters1411
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

Unique108 ?
Unique (%)81.2%

Sample

1st row053 5875605
2nd row053 9549460
3rd row053 250 2024
4th row053 4262669
5th row053 4223753
ValueCountFrequency (%)
053 97
33.9%
5252113 4
 
1.4%
070 4
 
1.4%
294 3
 
1.0%
7301 3
 
1.0%
954 3
 
1.0%
313 2
 
0.7%
956 2
 
0.7%
583 2
 
0.7%
6323 2
 
0.7%
Other values (150) 164
57.3%
2024-04-21T22:34:58.373367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 232
16.4%
0 230
16.3%
3 216
15.3%
153
10.8%
2 110
7.8%
1 91
 
6.4%
6 88
 
6.2%
8 83
 
5.9%
4 79
 
5.6%
9 65
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1258
89.2%
Space Separator 153
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 232
18.4%
0 230
18.3%
3 216
17.2%
2 110
8.7%
1 91
 
7.2%
6 88
 
7.0%
8 83
 
6.6%
4 79
 
6.3%
9 65
 
5.2%
7 64
 
5.1%
Space Separator
ValueCountFrequency (%)
153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 232
16.4%
0 230
16.3%
3 216
15.3%
153
10.8%
2 110
7.8%
1 91
 
6.4%
6 88
 
6.2%
8 83
 
5.9%
4 79
 
5.6%
9 65
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 232
16.4%
0 230
16.3%
3 216
15.3%
153
10.8%
2 110
7.8%
1 91
 
6.4%
6 88
 
6.2%
8 83
 
5.9%
4 79
 
5.6%
9 65
 
4.6%

소재지면적
Text

MISSING 

Distinct126
Distinct (%)74.1%
Missing21
Missing (%)11.0%
Memory size1.6 KiB
2024-04-21T22:34:59.450039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0235294
Min length3

Characters and Unicode

Total characters854
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

Unique110 ?
Unique (%)64.7%

Sample

1st row66.04
2nd row65.60
3rd row26.44
4th row19.95
5th row66.00
ValueCountFrequency (%)
10.00 8
 
4.7%
9.90 6
 
3.5%
49.50 6
 
3.5%
20.00 5
 
2.9%
6.60 5
 
2.9%
00 4
 
2.4%
3.30 4
 
2.4%
16.50 3
 
1.8%
58.95 3
 
1.8%
30.00 3
 
1.8%
Other values (116) 123
72.4%
2024-04-21T22:35:00.756266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 203
23.8%
. 170
19.9%
1 68
 
8.0%
2 63
 
7.4%
6 59
 
6.9%
4 56
 
6.6%
3 55
 
6.4%
9 52
 
6.1%
5 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 682
79.9%
Other Punctuation 172
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 203
29.8%
1 68
 
10.0%
2 63
 
9.2%
6 59
 
8.7%
4 56
 
8.2%
3 55
 
8.1%
9 52
 
7.6%
5 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 854
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 203
23.8%
. 170
19.9%
1 68
 
8.0%
2 63
 
7.4%
6 59
 
6.9%
4 56
 
6.6%
3 55
 
6.4%
9 52
 
6.1%
5 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 203
23.8%
. 170
19.9%
1 68
 
8.0%
2 63
 
7.4%
6 59
 
6.9%
4 56
 
6.6%
3 55
 
6.4%
9 52
 
6.1%
5 52
 
6.1%
8 46
 
5.4%
Other values (2) 30
 
3.5%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)64.4%
Missing3
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean704147.38
Minimum700082
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:01.004440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700082
5-th percentile701188.5
Q1702300
median702903
Q3704944
95-th percentile711821
Maximum711891
Range11809
Interquartile range (IQR)2644

Descriptive statistics

Standard deviation2733.483
Coefficient of variation (CV)0.0038819756
Kurtosis2.1375287
Mean704147.38
Median Absolute Deviation (MAD)1079
Skewness1.5353418
Sum1.3237971 × 108
Variance7471929.2
MonotonicityNot monotonic
2024-04-21T22:35:01.339604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702903 11
 
5.8%
704830 7
 
3.7%
702300 6
 
3.1%
711821 4
 
2.1%
701804 4
 
2.1%
702825 4
 
2.1%
704932 3
 
1.6%
705840 3
 
1.6%
701870 3
 
1.6%
702865 3
 
1.6%
Other values (111) 140
73.3%
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%
711833 2
1.0%
711832 2
1.0%
711823 1
 
0.5%
711821 4
2.1%
711814 1
 
0.5%
706852 2
1.0%

소재지전체주소
Text

Distinct168
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T22:35:02.772884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length23.65445
Min length17

Characters and Unicode

Total characters4518
Distinct characters165
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

Unique152 ?
Unique (%)79.6%

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 191
22.0%
북구 63
 
7.3%
동구 30
 
3.5%
달서구 30
 
3.5%
수성구 20
 
2.3%
달성군 17
 
2.0%
팔달동 14
 
1.6%
서구 14
 
1.6%
230-3번지 9
 
1.0%
남구 9
 
1.0%
Other values (305) 471
54.3%
2024-04-21T22:35:04.318227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
873
19.3%
구 374
 
8.3%
동 218
 
4.8%
대 205
 
4.5%
지 194
 
4.3%
역 192
 
4.2%
광 191
 
4.2%
시 191
 
4.2%
1 169
 
3.7%
번 162
 
3.6%
Other values (155) 1749
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2553
56.5%
Decimal Number 918
 
20.3%
Space Separator 873
 
19.3%
Dash Punctuation 147
 
3.3%
Close Punctuation 9
 
0.2%
Open Punctuation 9
 
0.2%
Other Punctuation 6
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 374
14.6%
동 218
 
8.5%
대 205
 
8.0%
지 194
 
7.6%
역 192
 
7.5%
광 191
 
7.5%
시 191
 
7.5%
번 162
 
6.3%
북 64
 
2.5%
달 61
 
2.4%
Other values (137) 701
27.5%
Decimal Number
ValueCountFrequency (%)
1 169
18.4%
2 114
12.4%
0 106
11.5%
3 95
10.3%
4 84
9.2%
8 76
8.3%
6 75
8.2%
9 68
7.4%
7 66
 
7.2%
5 65
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 2
33.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
873
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2553
56.5%
Common 1962
43.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 374
14.6%
동 218
 
8.5%
대 205
 
8.0%
지 194
 
7.6%
역 192
 
7.5%
광 191
 
7.5%
시 191
 
7.5%
번 162
 
6.3%
북 64
 
2.5%
달 61
 
2.4%
Other values (137) 701
27.5%
Common
ValueCountFrequency (%)
873
44.5%
1 169
 
8.6%
- 147
 
7.5%
2 114
 
5.8%
0 106
 
5.4%
3 95
 
4.8%
4 84
 
4.3%
8 76
 
3.9%
6 75
 
3.8%
9 68
 
3.5%
Other values (6) 155
 
7.9%
Latin
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2553
56.5%
ASCII 1965
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
873
44.4%
1 169
 
8.6%
- 147
 
7.5%
2 114
 
5.8%
0 106
 
5.4%
3 95
 
4.8%
4 84
 
4.3%
8 76
 
3.9%
6 75
 
3.8%
9 68
 
3.5%
Other values (8) 158
 
8.0%
Hangul
ValueCountFrequency (%)
구 374
14.6%
동 218
 
8.5%
대 205
 
8.0%
지 194
 
7.6%
역 192
 
7.5%
광 191
 
7.5%
시 191
 
7.5%
번 162
 
6.3%
북 64
 
2.5%
달 61
 
2.4%
Other values (137) 701
27.5%

도로명전체주소
Text

MISSING 

Distinct120
Distinct (%)88.9%
Missing56
Missing (%)29.3%
Memory size1.6 KiB
2024-04-21T22:35:05.441598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length28.592593
Min length20

Characters and Unicode

Total characters3860
Distinct characters194
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

Unique108 ?
Unique (%)80.0%

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 135
 
17.0%
북구 35
 
4.4%
1층 29
 
3.6%
동구 26
 
3.3%
달서구 24
 
3.0%
2층 16
 
2.0%
달성군 13
 
1.6%
수성구 12
 
1.5%
서구 12
 
1.5%
3층 9
 
1.1%
Other values (323) 484
60.9%
2024-04-21T22:35:06.931144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
660
 
17.1%
구 274
 
7.1%
동 183
 
4.7%
대 165
 
4.3%
시 138
 
3.6%
1 137
 
3.5%
역 136
 
3.5%
광 135
 
3.5%
) 123
 
3.2%
로 123
 
3.2%
Other values (184) 1786
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2201
57.0%
Space Separator 660
 
17.1%
Decimal Number 625
 
16.2%
Close Punctuation 123
 
3.2%
Open Punctuation 123
 
3.2%
Other Punctuation 92
 
2.4%
Dash Punctuation 32
 
0.8%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 274
 
12.4%
동 183
 
8.3%
대 165
 
7.5%
시 138
 
6.3%
역 136
 
6.2%
광 135
 
6.1%
로 123
 
5.6%
길 81
 
3.7%
층 70
 
3.2%
서 54
 
2.5%
Other values (167) 842
38.3%
Decimal Number
ValueCountFrequency (%)
1 137
21.9%
2 99
15.8%
3 93
14.9%
4 53
 
8.5%
5 48
 
7.7%
0 48
 
7.7%
6 45
 
7.2%
8 36
 
5.8%
7 36
 
5.8%
9 30
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
C 1
 
25.0%
Space Separator
ValueCountFrequency (%)
660
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Other Punctuation
ValueCountFrequency (%)
, 92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2201
57.0%
Common 1655
42.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 274
 
12.4%
동 183
 
8.3%
대 165
 
7.5%
시 138
 
6.3%
역 136
 
6.2%
광 135
 
6.1%
로 123
 
5.6%
길 81
 
3.7%
층 70
 
3.2%
서 54
 
2.5%
Other values (167) 842
38.3%
Common
ValueCountFrequency (%)
660
39.9%
1 137
 
8.3%
) 123
 
7.4%
( 123
 
7.4%
2 99
 
6.0%
3 93
 
5.6%
, 92
 
5.6%
4 53
 
3.2%
5 48
 
2.9%
0 48
 
2.9%
Other values (5) 179
 
10.8%
Latin
ValueCountFrequency (%)
A 3
75.0%
C 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2201
57.0%
ASCII 1659
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
660
39.8%
1 137
 
8.3%
) 123
 
7.4%
( 123
 
7.4%
2 99
 
6.0%
3 93
 
5.6%
, 92
 
5.5%
4 53
 
3.2%
5 48
 
2.9%
0 48
 
2.9%
Other values (7) 183
 
11.0%
Hangul
ValueCountFrequency (%)
구 274
 
12.4%
동 183
 
8.3%
대 165
 
7.5%
시 138
 
6.3%
역 136
 
6.2%
광 135
 
6.1%
로 123
 
5.6%
길 81
 
3.7%
층 70
 
3.2%
서 54
 
2.5%
Other values (167) 842
38.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)74.6%
Missing57
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean41940.328
Minimum41042
Maximum43010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:07.346837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41042
5-th percentile41082
Q141468.25
median41754
Q342631.5
95-th percentile42949.85
Maximum43010
Range1968
Interquartile range (IQR)1163.25

Descriptive statistics

Standard deviation639.43836
Coefficient of variation (CV)0.015246384
Kurtosis-1.3934266
Mean41940.328
Median Absolute Deviation (MAD)551
Skewness0.25668661
Sum5620004
Variance408881.41
MonotonicityNot monotonic
2024-04-21T22:35:07.806864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 7
 
3.7%
42722 6
 
3.1%
41163 3
 
1.6%
42500 3
 
1.6%
41082 3
 
1.6%
41491 3
 
1.6%
42904 3
 
1.6%
41754 3
 
1.6%
42712 2
 
1.0%
41422 2
 
1.0%
Other values (90) 99
51.8%
(Missing) 57
29.8%
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
1.6%
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%
42922 1
 
0.5%
42904 3
1.6%
42819 1
 
0.5%
42815 1
 
0.5%

사업장명
Text

Distinct173
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T22:35:08.777059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.4764398
Min length2

Characters and Unicode

Total characters1237
Distinct characters203
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

Unique158 ?
Unique (%)82.7%

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%
주)능원통운 2
 
0.9%
주식회사그린로직스 2
 
0.9%
주)센트랄푸드시스템 2
 
0.9%
주)바다플러스 2
 
0.9%
Other values (174) 182
85.8%
2024-04-21T22:35:10.144280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 90
 
7.3%
) 78
 
6.3%
( 77
 
6.2%
스 39
 
3.2%
물 36
 
2.9%
식 35
 
2.8%
드 28
 
2.3%
류 28
 
2.3%
대 27
 
2.2%
푸 26
 
2.1%
Other values (193) 773
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1053
85.1%
Close Punctuation 78
 
6.3%
Open Punctuation 77
 
6.2%
Space Separator 21
 
1.7%
Uppercase Letter 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 90
 
8.5%
스 39
 
3.7%
물 36
 
3.4%
식 35
 
3.3%
드 28
 
2.7%
류 28
 
2.7%
대 27
 
2.6%
푸 26
 
2.5%
성 24
 
2.3%
통 22
 
2.1%
Other values (183) 698
66.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
25.0%
M 1
12.5%
D 1
12.5%
T 1
12.5%
S 1
12.5%
C 1
12.5%
F 1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1053
85.1%
Common 176
 
14.2%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 90
 
8.5%
스 39
 
3.7%
물 36
 
3.4%
식 35
 
3.3%
드 28
 
2.7%
류 28
 
2.7%
대 27
 
2.6%
푸 26
 
2.5%
성 24
 
2.3%
통 22
 
2.1%
Other values (183) 698
66.3%
Latin
ValueCountFrequency (%)
G 2
25.0%
M 1
12.5%
D 1
12.5%
T 1
12.5%
S 1
12.5%
C 1
12.5%
F 1
12.5%
Common
ValueCountFrequency (%)
) 78
44.3%
( 77
43.8%
21
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1053
85.1%
ASCII 184
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 90
 
8.5%
스 39
 
3.7%
물 36
 
3.4%
식 35
 
3.3%
드 28
 
2.7%
류 28
 
2.7%
대 27
 
2.6%
푸 26
 
2.5%
성 24
 
2.3%
통 22
 
2.1%
Other values (183) 698
66.3%
ASCII
ValueCountFrequency (%)
) 78
42.4%
( 77
41.8%
21
 
11.4%
G 2
 
1.1%
M 1
 
0.5%
D 1
 
0.5%
T 1
 
0.5%
S 1
 
0.5%
C 1
 
0.5%
F 1
 
0.5%

최종수정시점
Real number (ℝ)

Distinct185
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0141141 × 1013
Minimum2.0031121 × 1013
Maximum2.0210524 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:10.555429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0031121 × 1013
5-th percentile2.0041011 × 1013
Q12.0090206 × 1013
median2.0160907 × 1013
Q32.0191167 × 1013
95-th percentile2.0210253 × 1013
Maximum2.0210524 × 1013
Range1.7940318 × 1011
Interquartile range (IQR)1.00961 × 1011

Descriptive statistics

Standard deviation5.8703991 × 1010
Coefficient of variation (CV)0.0029146309
Kurtosis-1.2894711
Mean2.0141141 × 1013
Median Absolute Deviation (MAD)4.0100001 × 1010
Skewness-0.48322253
Sum3.8469579 × 1015
Variance3.4461586 × 1021
MonotonicityNot monotonic
2024-04-21T22:35:11.016564image/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%
20190517154812 1
 
0.5%
20191205095957 1
 
0.5%
20061127000000 1
 
0.5%
20090216112521 1
 
0.5%
20060131000000 1
 
0.5%
20040401000000 1
 
0.5%
20090216112446 1
 
0.5%
Other values (175) 175
91.6%
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 (%)
20210524175136 1
0.5%
20210517105321 1
0.5%
20210511121658 1
0.5%
20210506171955 1
0.5%
20210414151055 1
0.5%
20210414100817 1
0.5%
20210408175541 1
0.5%
20210402134912 1
0.5%
20210304113806 1
0.5%
20210304105146 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
I
132 
U
59 

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
69.1%
U 59
30.9%

Length

2024-04-21T22:35:11.433534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:11.738047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 132
69.1%
u 59
30.9%

데이터갱신일자
Date

Distinct70
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-26 00:22:56
2024-04-21T22:35:12.285742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:35:12.698851image/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 size1.6 KiB
식품운반업
191 

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 191
100.0%

Length

2024-04-21T22:35:13.081353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:13.379950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 191
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct148
Distinct (%)81.3%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean341732.6
Minimum327299.69
Maximum355567.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:13.692022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327299.69
5-th percentile330403.94
Q1338520.02
median340331.8
Q3345891.98
95-th percentile352803.15
Maximum355567.69
Range28268.001
Interquartile range (IQR)7371.9603

Descriptive statistics

Standard deviation5971.1427
Coefficient of variation (CV)0.017473143
Kurtosis0.12920557
Mean341732.6
Median Absolute Deviation (MAD)3357.3131
Skewness0.12847368
Sum62195334
Variance35654546
MonotonicityNot monotonic
2024-04-21T22:35:14.108006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338985.366314 10
 
5.2%
337329.213273 5
 
2.6%
339388.690364 3
 
1.6%
340946.597285 3
 
1.6%
327735.044524 3
 
1.6%
337140.428534 2
 
1.0%
345327.736683 2
 
1.0%
339120.646244 2
 
1.0%
340411.771764 2
 
1.0%
340246.984304 2
 
1.0%
Other values (138) 148
77.5%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
327299.692057 1
 
0.5%
327735.044524 3
1.6%
329271.879011 2
1.0%
329604.038183 1
 
0.5%
329859.122079 1
 
0.5%
330128.30921 1
 
0.5%
330388.015281 1
 
0.5%
330706.421358 1
 
0.5%
333070.51248 1
 
0.5%
333920.60853 2
1.0%
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 

Distinct148
Distinct (%)81.3%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean264352.42
Minimum240636.85
Maximum273735.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:14.507314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240636.85
5-th percentile256643.32
Q1261818.39
median264733.99
Q3267354.45
95-th percentile271776.38
Maximum273735.13
Range33098.279
Interquartile range (IQR)5536.0599

Descriptive statistics

Standard deviation4762.894
Coefficient of variation (CV)0.018017214
Kurtosis4.3047795
Mean264352.42
Median Absolute Deviation (MAD)2685.3762
Skewness-1.2524249
Sum48112141
Variance22685160
MonotonicityNot monotonic
2024-04-21T22:35:14.945472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
267354.446312 10
 
5.2%
260416.780233 5
 
2.6%
269664.126149 3
 
1.6%
259953.127592 3
 
1.6%
263479.562399 3
 
1.6%
267197.245937 2
 
1.0%
268763.26426 2
 
1.0%
269054.376386 2
 
1.0%
272600.063881 2
 
1.0%
270847.157898 2
 
1.0%
Other values (138) 148
77.5%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
240636.852024 1
0.5%
244838.382091 1
0.5%
248561.77396 1
0.5%
254017.803261 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%
257765.775409 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 size1.6 KiB
식품운반업
191 

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 191
100.0%

Length

2024-04-21T22:35:15.352200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:15.650180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 191
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
138 
상수도전용
53 

Length

Max length5
Median length4
Mean length4.2774869
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 138
72.3%
상수도전용 53
 
27.7%

Length

2024-04-21T22:35:15.988331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:16.312199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 138
72.3%
상수도전용 53
 
27.7%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
134 
<NA>
54 
3
 
2
1
 
1

Length

Max length4
Median length1
Mean length1.8481675
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 134
70.2%
<NA> 54
28.3%
3 2
 
1.0%
1 1
 
0.5%

Length

2024-04-21T22:35:16.676296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:17.015466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 134
70.2%
na 54
28.3%
3 2
 
1.0%
1 1
 
0.5%

공장사무직종업원수
Categorical

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
116 
<NA>
53 
1
14 
2
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.8324607
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 116
60.7%
<NA> 53
27.7%
1 14
 
7.3%
2 5
 
2.6%
3 2
 
1.0%
5 1
 
0.5%

Length

2024-04-21T22:35:17.397458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:17.745098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 116
60.7%
na 53
27.7%
1 14
 
7.3%
2 5
 
2.6%
3 2
 
1.0%
5 1
 
0.5%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)5.1%
Missing53
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean0.30434783
Minimum0
Maximum7
Zeros120
Zeros (%)62.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:18.061036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.15
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0007931
Coefficient of variation (CV)3.2883201
Kurtosis20.09778
Mean0.30434783
Median Absolute Deviation (MAD)0
Skewness4.2326083
Sum42
Variance1.0015868
MonotonicityNot monotonic
2024-04-21T22:35:18.406566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 120
62.8%
1 9
 
4.7%
3 3
 
1.6%
2 2
 
1.0%
4 2
 
1.0%
5 1
 
0.5%
7 1
 
0.5%
(Missing) 53
27.7%
ValueCountFrequency (%)
0 120
62.8%
1 9
 
4.7%
2 2
 
1.0%
3 3
 
1.6%
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
 
1.6%
2 2
 
1.0%
1 9
 
4.7%
0 120
62.8%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)4.4%
Missing54
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean0.25547445
Minimum0
Maximum7
Zeros123
Zeros (%)64.4%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:18.740249image/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 deviation0.95508852
Coefficient of variation (CV)3.7384893
Kurtosis26.372461
Mean0.25547445
Median Absolute Deviation (MAD)0
Skewness4.8616728
Sum35
Variance0.91219407
MonotonicityNot monotonic
2024-04-21T22:35:19.082444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 123
64.4%
2 5
 
2.6%
1 5
 
2.6%
5 2
 
1.0%
3 1
 
0.5%
7 1
 
0.5%
(Missing) 54
28.3%
ValueCountFrequency (%)
0 123
64.4%
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%
0 123
64.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
84 
자가
64 
임대
43 

Length

Max length4
Median length2
Mean length2.8795812
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
44.0%
자가 64
33.5%
임대 43
22.5%

Length

2024-04-21T22:35:19.506581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:19.851095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
44.0%
자가 64
33.5%
임대 43
22.5%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
14

Length

Max length4
Median length4
Mean length3.7801047
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> 177
92.7%
0 14
 
7.3%

Length

2024-04-21T22:35:20.230034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:20.558001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
92.7%
0 14
 
7.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
177 
0
 
14

Length

Max length4
Median length4
Mean length3.7801047
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> 177
92.7%
0 14
 
7.3%

Length

2024-04-21T22:35:20.914783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:35:21.243172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
92.7%
0 14
 
7.3%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size319.0 B
False
191 
ValueCountFrequency (%)
False 191
100.0%
2024-04-21T22:35:21.513600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9417801
Minimum0
Maximum134.13
Zeros184
Zeros (%)96.3%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T22:35:21.785038image/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 deviation14.708395
Coefficient of variation (CV)7.5746966
Kurtosis62.832837
Mean1.9417801
Median Absolute Deviation (MAD)0
Skewness7.9511582
Sum370.88
Variance216.33689
MonotonicityNot monotonic
2024-04-21T22:35:22.158021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 184
96.3%
3.3 1
 
0.5%
105.6 1
 
0.5%
134.13 1
 
0.5%
3.0 1
 
0.5%
10.37 1
 
0.5%
2.46 1
 
0.5%
112.02 1
 
0.5%
ValueCountFrequency (%)
0.0 184
96.3%
2.46 1
 
0.5%
3.0 1
 
0.5%
3.3 1
 
0.5%
10.37 1
 
0.5%
105.6 1
 
0.5%
112.02 1
 
0.5%
134.13 1
 
0.5%
ValueCountFrequency (%)
134.13 1
 
0.5%
112.02 1
 
0.5%
105.6 1
 
0.5%
10.37 1
 
0.5%
3.3 1
 
0.5%
3.0 1
 
0.5%
2.46 1
 
0.5%
0.0 184
96.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
Missing (%)100.0%
Memory size1.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing191
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 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_P34200003420000-117-2019-0000120191001<NA>3폐업2폐업20200707<NA><NA><NA><NA>3.30701804대구광역시 동구 방촌동 1084-13 방촌청구타운대구광역시 동구 화랑로73길 36, 102동 4층 408호 (방촌동, 방촌청구타운)41160개인용달 김태복20200707110955U2020-07-09 02:40:00.0식품운반업350130.296336265664.051744식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N3.3<NA><NA><NA>
910식품운반업07_22_09_P34200003420000-117-2020-0000120200218<NA>1영업/정상1영업<NA><NA><NA><NA>053962880054.72701849대구광역시 동구 동호동 379-1번지대구광역시 동구 동호로2길 2-1, 1층 (동호동)41085(주)디비로지스20200311183326U2020-03-13 02:40:00.0식품운반업355444.760056264104.497088식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
181182식품운반업07_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>
182183식품운반업07_22_09_P34800003480000-117-2004-0000220040107<NA>3폐업2폐업20110621<NA><NA><NA>053 616336341.85711842대구광역시 달성군 옥포면 강림리 580번지<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>
183184식품운반업07_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>
184185식품운반업07_22_09_P34800003480000-117-2015-0000120150827<NA>1영업/정상1영업<NA><NA><NA><NA>053 555 229910.40711833대구광역시 달성군 화원읍 설화리 736-3대구광역시 달성군 화원읍 류목정길 56, 1층42957DMG푸드20210408175541U2021-04-10 02:40:00.0식품운반업334255.076962255771.102947식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
185186식품운반업07_22_09_P34800003480000-117-2008-0000420081226<NA>1영업/정상1영업<NA><NA><NA><NA>053 615240489.28711891대구광역시 달성군 구지면 창리 541번지대구광역시 달성군 구지면 창리서로6길 4-543010(주)남경물류20090206105954I2018-08-31 23:59:59.0식품운반업327299.692057240636.852024식품운반업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
186187식품운반업07_22_09_P34800003480000-117-2007-0000120070824<NA>1영업/정상1영업<NA><NA><NA><NA>053 586758414.80711814대구광역시 달성군 다사읍 세천리 870-1번지대구광역시 달성군 다사읍 세천북로 7342922토마토푸드20191125153334U2019-11-27 02:40:00.0식품운반업333070.51248265157.989806식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
187188식품운반업07_22_09_P34800003480000-117-2004-0000120040102<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.93711823대구광역시 달성군 하빈면 봉촌리 768-30번지 외 5필지<NA><NA>화성물류(주)20170626164627I2018-08-31 23:59:59.0식품운반업<NA><NA>식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA>
188189식품운반업07_22_09_P34800003480000-117-2003-0000120031101<NA>1영업/정상1영업<NA><NA><NA><NA>053 635728049.50711832대구광역시 달성군 화원읍 명곡리 198-4번지대구광역시 달성군 화원읍 성화로 1142946(주)하나물류시스템20150415141724I2018-08-31 23:59:59.0식품운반업334750.422674256643.317146식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
189190식품운반업07_22_09_P34800003480000-117-2019-0000220190628<NA>1영업/정상1영업<NA><NA><NA><NA>053 313 303520.00<NA>대구광역시 달성군 옥포읍 강림리 528-4번지대구광역시 달성군 옥포읍 시저로2길 16-142968백제농산20190807172026U2019-08-09 02:40:00.0식품운반업329271.879011254619.354156식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
190191식품운반업07_22_09_P34800003480000-117-2016-0000120160930<NA>3폐업2폐업20191211<NA><NA><NA><NA>70.00711821대구광역시 달성군 하빈면 동곡리 627번지대구광역시 달성군 하빈면 하빈남로 171-142904(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>