Overview

Dataset statistics

Number of variables41
Number of observations40
Missing cells319
Missing cells (%)19.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory360.3 B

Variable types

Numeric13
Categorical16
Unsupported6
Text5
DateTime1

Dataset

Description22년07월_6270000_대구광역시_11_45_02_P_물류창고업체
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093997&dataSetDetailId=DDI_0000094029&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
냉동_냉장창고_동수 is highly imbalanced (60.0%)Imbalance
냉동_냉장창고_면적 is highly imbalanced (66.2%)Imbalance
법인여부명 is highly imbalanced (61.6%)Imbalance
인허가취소일자 has 40 (100.0%) missing valuesMissing
폐업일자 has 27 (67.5%) missing valuesMissing
휴업시작일자 has 40 (100.0%) missing valuesMissing
휴업종료일자 has 40 (100.0%) missing valuesMissing
재개업일자 has 40 (100.0%) missing valuesMissing
소재지전화 has 1 (2.5%) missing valuesMissing
소재지면적 has 40 (100.0%) missing valuesMissing
소재지우편번호 has 11 (27.5%) missing valuesMissing
도로명전체주소 has 1 (2.5%) missing valuesMissing
도로명우편번호 has 6 (15.0%) missing valuesMissing
업태구분명 has 40 (100.0%) missing valuesMissing
좌표정보(X) has 1 (2.5%) missing valuesMissing
좌표정보(Y) has 1 (2.5%) missing valuesMissing
직원수 has 5 (12.5%) missing valuesMissing
시설/장비현황 has 5 (12.5%) missing valuesMissing
보관요율 has 21 (52.5%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
일반창고_면적 has 3 (7.5%) zerosZeros
보관장소_면적 has 32 (80.0%) zerosZeros
보관요율 has 2 (5.0%) zerosZeros

Reproduction

Analysis started2023-12-10 20:44:31.112523
Analysis finished2023-12-10 20:44:31.869111
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:32.044085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-11T05:44:32.331378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

개방서비스명
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물류창고업체 40
100.0%

Length

2023-12-11T05:44:32.543438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:32.693518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물류창고업체 40
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
11_45_02_P
40 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_45_02_P
2nd row11_45_02_P
3rd row11_45_02_P
4th row11_45_02_P
5th row11_45_02_P

Common Values

ValueCountFrequency (%)
11_45_02_P 40
100.0%

Length

2023-12-11T05:44:32.845049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:32.990330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_45_02_p 40
100.0%

개방자치단체코드
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
3430000
11 
3480000
10 
3450000
8 
3420000
6 
3470000
5 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3420000
2nd row3420000
3rd row3420000
4th row3420000
5th row3420000

Common Values

ValueCountFrequency (%)
3430000 11
27.5%
3480000 10
25.0%
3450000 8
20.0%
3420000 6
15.0%
3470000 5
12.5%

Length

2023-12-11T05:44:33.175458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:33.369044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3430000 11
27.5%
3480000 10
25.0%
3450000 8
20.0%
3420000 6
15.0%
3470000 5
12.5%

관리번호
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.014395 × 1018
Minimum2.012343 × 1018
Maximum2.022348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:33.586241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.012343 × 1018
5-th percentile2.012343 × 1018
Q12.0130935 × 1018
median2.013345 × 1018
Q32.0138465 × 1018
95-th percentile2.0203931 × 1018
Maximum2.022348 × 1018
Range1.0005032 × 1016
Interquartile range (IQR)7.5301205 × 1014

Descriptive statistics

Standard deviation2.7361445 × 1015
Coefficient of variation (CV)0.0013582959
Kurtosis1.8866795
Mean2.014395 × 1018
Median Absolute Deviation (MAD)5 × 1014
Skewness1.7239782
Sum6.7888243 × 1018
Variance7.4864867 × 1030
MonotonicityNot monotonic
2023-12-11T05:44:33.804785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2013342009832500001 1
 
2.5%
2013345008532500002 1
 
2.5%
2013345008532500005 1
 
2.5%
2013345008532500007 1
 
2.5%
2013347008632500001 1
 
2.5%
2013347008632500002 1
 
2.5%
2013347008632500004 1
 
2.5%
2015347008632500001 1
 
2.5%
2013347008632500003 1
 
2.5%
2022348037032500001 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
2012343005332500001 1
2.5%
2012343005332500002 1
2.5%
2012343005332500003 1
2.5%
2012343005332500004 1
2.5%
2012343005332500005 1
2.5%
2012343005332500006 1
2.5%
2012343005332500007 1
2.5%
2012343005332500008 1
2.5%
2012348031332500001 1
2.5%
2012348031332500002 1
2.5%
ValueCountFrequency (%)
2022348037032500001 1
2.5%
2021345008532500001 1
2.5%
2020343010032500001 1
2.5%
2020342018032500001 1
2.5%
2018348037032500001 1
2.5%
2018345008532500001 1
2.5%
2017348031332500001 1
2.5%
2016348031332500001 1
2.5%
2015347008632500001 1
2.5%
2015342015032525800 1
2.5%

인허가일자
Real number (ℝ)

Distinct17
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20143606
Minimum20130226
Maximum20220302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:33.972371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130226
5-th percentile20130226
Q120130306
median20130311
Q320142628
95-th percentile20201379
Maximum20220302
Range90076
Interquartile range (IQR)12322

Descriptive statistics

Standard deviation25756.773
Coefficient of variation (CV)0.0012786575
Kurtosis2.2629106
Mean20143606
Median Absolute Deviation (MAD)84
Skewness1.863946
Sum8.0574424 × 108
Variance6.6341137 × 108
MonotonicityNot monotonic
2023-12-11T05:44:34.152655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20130311 13
32.5%
20130306 5
 
12.5%
20130227 5
 
12.5%
20130226 4
 
10.0%
20200709 1
 
2.5%
20130712 1
 
2.5%
20180426 1
 
2.5%
20210305 1
 
2.5%
20130305 1
 
2.5%
20150202 1
 
2.5%
Other values (7) 7
17.5%
ValueCountFrequency (%)
20130226 4
 
10.0%
20130227 5
 
12.5%
20130305 1
 
2.5%
20130306 5
 
12.5%
20130311 13
32.5%
20130712 1
 
2.5%
20140103 1
 
2.5%
20150202 1
 
2.5%
20150414 1
 
2.5%
20160830 1
 
2.5%
ValueCountFrequency (%)
20220302 1
2.5%
20210305 1
2.5%
20200909 1
2.5%
20200709 1
2.5%
20180503 1
2.5%
20180426 1
2.5%
20170904 1
2.5%
20160830 1
2.5%
20150414 1
2.5%
20150202 1
2.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태구분코드
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
26 
3
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 26
65.0%
3 14
35.0%

Length

2023-12-11T05:44:34.369430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:34.495099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 26
65.0%
3 14
35.0%

영업상태명
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
영업/정상
26 
폐업
14 

Length

Max length5
Median length5
Mean length3.95
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 26
65.0%
폐업 14
35.0%

Length

2023-12-11T05:44:34.672050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:34.828255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 26
65.0%
폐업 14
35.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
26 
3
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 26
65.0%
3 14
35.0%

Length

2023-12-11T05:44:34.991286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:35.122438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 26
65.0%
3 14
35.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
영업중
26 
폐업
14 

Length

Max length3
Median length3
Mean length2.65
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 26
65.0%
폐업 14
35.0%

Length

2023-12-11T05:44:35.266986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:35.405620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 26
65.0%
폐업 14
35.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)76.9%
Missing27
Missing (%)67.5%
Infinite0
Infinite (%)0.0%
Mean20182032
Minimum20160120
Maximum20200407
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:35.560808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20160120
5-th percentile20166411
Q120180402
median20180629
Q320190416
95-th percentile20200231
Maximum20200407
Range40287
Interquartile range (IQR)10014

Descriptive statistics

Standard deviation11402.296
Coefficient of variation (CV)0.00056497263
Kurtosis0.11261182
Mean20182032
Median Absolute Deviation (MAD)9787
Skewness-0.009464073
Sum2.6236642 × 108
Variance1.3001235 × 108
MonotonicityNot monotonic
2023-12-11T05:44:35.750495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20180629 4
 
10.0%
20170605 1
 
2.5%
20200114 1
 
2.5%
20180402 1
 
2.5%
20160120 1
 
2.5%
20190416 1
 
2.5%
20170717 1
 
2.5%
20180504 1
 
2.5%
20200407 1
 
2.5%
20190614 1
 
2.5%
(Missing) 27
67.5%
ValueCountFrequency (%)
20160120 1
 
2.5%
20170605 1
 
2.5%
20170717 1
 
2.5%
20180402 1
 
2.5%
20180504 1
 
2.5%
20180629 4
10.0%
20190416 1
 
2.5%
20190614 1
 
2.5%
20200114 1
 
2.5%
20200407 1
 
2.5%
ValueCountFrequency (%)
20200407 1
 
2.5%
20200114 1
 
2.5%
20190614 1
 
2.5%
20190416 1
 
2.5%
20180629 4
10.0%
20180504 1
 
2.5%
20180402 1
 
2.5%
20170717 1
 
2.5%
20170605 1
 
2.5%
20160120 1
 
2.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지전화
Text

MISSING 

Distinct38
Distinct (%)97.4%
Missing1
Missing (%)2.5%
Memory size452.0 B
2023-12-11T05:44:36.003395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.846154
Min length10

Characters and Unicode

Total characters462
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)94.9%

Sample

1st row053-211-3855
2nd row053-381-3355
3rd row053-965-2620
4th row053-963-8942
5th row053-351-0777
ValueCountFrequency (%)
053 11
 
19.3%
5620365 2
 
3.5%
053-644-3399 1
 
1.8%
053-211-3855 1
 
1.8%
0535935524 1
 
1.8%
356 1
 
1.8%
6888 1
 
1.8%
07071661033 1
 
1.8%
383 1
 
1.8%
4851 1
 
1.8%
Other values (36) 36
63.2%
2023-12-11T05:44:36.516936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 81
17.5%
0 70
15.2%
3 68
14.7%
- 50
10.8%
7 30
 
6.5%
1 28
 
6.1%
6 26
 
5.6%
8 24
 
5.2%
9 23
 
5.0%
21
 
4.5%
Other values (2) 41
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 391
84.6%
Dash Punctuation 50
 
10.8%
Space Separator 21
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 81
20.7%
0 70
17.9%
3 68
17.4%
7 30
 
7.7%
1 28
 
7.2%
6 26
 
6.6%
8 24
 
6.1%
9 23
 
5.9%
4 21
 
5.4%
2 20
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 462
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 81
17.5%
0 70
15.2%
3 68
14.7%
- 50
10.8%
7 30
 
6.5%
1 28
 
6.1%
6 26
 
5.6%
8 24
 
5.2%
9 23
 
5.0%
21
 
4.5%
Other values (2) 41
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 462
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 81
17.5%
0 70
15.2%
3 68
14.7%
- 50
10.8%
7 30
 
6.5%
1 28
 
6.1%
6 26
 
5.6%
8 24
 
5.2%
9 23
 
5.0%
21
 
4.5%
Other values (2) 41
8.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)58.6%
Missing11
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean705076.24
Minimum701170
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:36.745954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum701170
5-th percentile701526
Q1702872
median703830
Q3704833
95-th percentile711872.6
Maximum711891
Range10721
Interquartile range (IQR)1961

Descriptive statistics

Standard deviation3637.9634
Coefficient of variation (CV)0.0051596737
Kurtosis0.0480603
Mean705076.24
Median Absolute Deviation (MAD)985
Skewness1.2740754
Sum20447211
Variance13234777
MonotonicityNot monotonic
2023-12-11T05:44:36.969507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
703830 7
17.5%
702814 2
 
5.0%
711891 2
 
5.0%
711823 2
 
5.0%
702872 2
 
5.0%
701835 2
 
5.0%
703833 2
 
5.0%
702902 1
 
2.5%
702845 1
 
2.5%
701170 1
 
2.5%
Other values (7) 7
17.5%
(Missing) 11
27.5%
ValueCountFrequency (%)
701170 1
 
2.5%
701320 1
 
2.5%
701835 2
 
5.0%
702814 2
 
5.0%
702845 1
 
2.5%
702872 2
 
5.0%
702902 1
 
2.5%
703830 7
17.5%
703833 2
 
5.0%
704190 1
 
2.5%
ValueCountFrequency (%)
711891 2
 
5.0%
711845 1
 
2.5%
711823 2
 
5.0%
711822 1
 
2.5%
704948 1
 
2.5%
704833 1
 
2.5%
704390 1
 
2.5%
704190 1
 
2.5%
703833 2
 
5.0%
703830 7
17.5%

소재지전체주소
Text

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-11T05:44:37.320284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24
Mean length21.275
Min length17

Characters and Unicode

Total characters851
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)80.0%

Sample

1st row대구광역시 동구 용계동 854번지
2nd row대구광역시 동구 용계동 662번지 1호
3rd row대구광역시 동구 봉무동 1566번지
4th row대구광역시 동구 괴전동 258번지
5th row대구광역시 동구 율암동 1151
ValueCountFrequency (%)
대구광역시 40
21.3%
서구 11
 
5.9%
달성군 10
 
5.3%
북구 8
 
4.3%
이현동 8
 
4.3%
동구 6
 
3.2%
달서구 5
 
2.7%
하빈면 5
 
2.7%
45번지 4
 
2.1%
노원동3가 3
 
1.6%
Other values (68) 88
46.8%
2023-12-11T05:44:38.454866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
17.5%
구 72
 
8.5%
대 42
 
4.9%
광 40
 
4.7%
역 40
 
4.7%
시 40
 
4.7%
1 38
 
4.5%
동 35
 
4.1%
지 35
 
4.1%
번 33
 
3.9%
Other values (54) 327
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 527
61.9%
Decimal Number 167
 
19.6%
Space Separator 149
 
17.5%
Dash Punctuation 7
 
0.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 72
13.7%
대 42
 
8.0%
광 40
 
7.6%
역 40
 
7.6%
시 40
 
7.6%
동 35
 
6.6%
지 35
 
6.6%
번 33
 
6.3%
호 19
 
3.6%
서 16
 
3.0%
Other values (41) 155
29.4%
Decimal Number
ValueCountFrequency (%)
1 38
22.8%
4 27
16.2%
6 21
12.6%
0 16
9.6%
5 15
 
9.0%
2 14
 
8.4%
3 11
 
6.6%
8 10
 
6.0%
7 9
 
5.4%
9 6
 
3.6%
Space Separator
ValueCountFrequency (%)
149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 527
61.9%
Common 324
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 72
13.7%
대 42
 
8.0%
광 40
 
7.6%
역 40
 
7.6%
시 40
 
7.6%
동 35
 
6.6%
지 35
 
6.6%
번 33
 
6.3%
호 19
 
3.6%
서 16
 
3.0%
Other values (41) 155
29.4%
Common
ValueCountFrequency (%)
149
46.0%
1 38
 
11.7%
4 27
 
8.3%
6 21
 
6.5%
0 16
 
4.9%
5 15
 
4.6%
2 14
 
4.3%
3 11
 
3.4%
8 10
 
3.1%
7 9
 
2.8%
Other values (3) 14
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 527
61.9%
ASCII 324
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
46.0%
1 38
 
11.7%
4 27
 
8.3%
6 21
 
6.5%
0 16
 
4.9%
5 15
 
4.6%
2 14
 
4.3%
3 11
 
3.4%
8 10
 
3.1%
7 9
 
2.8%
Other values (3) 14
 
4.3%
Hangul
ValueCountFrequency (%)
구 72
13.7%
대 42
 
8.0%
광 40
 
7.6%
역 40
 
7.6%
시 40
 
7.6%
동 35
 
6.6%
지 35
 
6.6%
번 33
 
6.3%
호 19
 
3.6%
서 16
 
3.0%
Other values (41) 155
29.4%

도로명전체주소
Text

MISSING 

Distinct33
Distinct (%)84.6%
Missing1
Missing (%)2.5%
Memory size452.0 B
2023-12-11T05:44:38.825950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length27
Mean length24.179487
Min length21

Characters and Unicode

Total characters943
Distinct characters101
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)71.8%

Sample

1st row대구광역시 동구 금호강변로 57 (용계동)
2nd row대구광역시 동구 화랑로 584 (용계동)
3rd row대구광역시 동구 팔공로45길 11 (봉무동)
4th row대구광역시 동구 안심로102길 9 (괴전동)
5th row대구광역시 동구 혁신대로 85 (율암동)
ValueCountFrequency (%)
대구광역시 39
19.8%
서구 11
 
5.6%
이현동 9
 
4.6%
달성군 9
 
4.6%
북구 8
 
4.1%
동구 6
 
3.0%
하빈면 5
 
2.5%
달서구 5
 
2.5%
국채보상로 4
 
2.0%
노원로 4
 
2.0%
Other values (78) 97
49.2%
2023-12-11T05:44:39.389523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
 
16.8%
구 73
 
7.7%
대 43
 
4.6%
시 39
 
4.1%
로 39
 
4.1%
역 39
 
4.1%
광 39
 
4.1%
동 37
 
3.9%
) 31
 
3.3%
( 31
 
3.3%
Other values (91) 414
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 590
62.6%
Space Separator 158
 
16.8%
Decimal Number 129
 
13.7%
Close Punctuation 31
 
3.3%
Open Punctuation 31
 
3.3%
Dash Punctuation 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 73
 
12.4%
대 43
 
7.3%
시 39
 
6.6%
로 39
 
6.6%
역 39
 
6.6%
광 39
 
6.6%
동 37
 
6.3%
길 19
 
3.2%
달 19
 
3.2%
서 18
 
3.1%
Other values (76) 225
38.1%
Decimal Number
ValueCountFrequency (%)
2 22
17.1%
1 22
17.1%
5 19
14.7%
4 14
10.9%
8 11
8.5%
3 10
7.8%
7 10
7.8%
0 8
 
6.2%
6 8
 
6.2%
9 5
 
3.9%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 590
62.6%
Common 353
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 73
 
12.4%
대 43
 
7.3%
시 39
 
6.6%
로 39
 
6.6%
역 39
 
6.6%
광 39
 
6.6%
동 37
 
6.3%
길 19
 
3.2%
달 19
 
3.2%
서 18
 
3.1%
Other values (76) 225
38.1%
Common
ValueCountFrequency (%)
158
44.8%
) 31
 
8.8%
( 31
 
8.8%
2 22
 
6.2%
1 22
 
6.2%
5 19
 
5.4%
4 14
 
4.0%
8 11
 
3.1%
3 10
 
2.8%
7 10
 
2.8%
Other values (5) 25
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 590
62.6%
ASCII 353
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
44.8%
) 31
 
8.8%
( 31
 
8.8%
2 22
 
6.2%
1 22
 
6.2%
5 19
 
5.4%
4 14
 
4.0%
8 11
 
3.1%
3 10
 
2.8%
7 10
 
2.8%
Other values (5) 25
 
7.1%
Hangul
ValueCountFrequency (%)
구 73
 
12.4%
대 43
 
7.3%
시 39
 
6.6%
로 39
 
6.6%
역 39
 
6.6%
광 39
 
6.6%
동 37
 
6.3%
길 19
 
3.2%
달 19
 
3.2%
서 18
 
3.1%
Other values (76) 225
38.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)70.6%
Missing6
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean509060.65
Minimum41028
Maximum711845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:39.563804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41028
5-th percentile41351
Q142934.25
median702858.5
Q3703830
95-th percentile704873.25
Maximum711845
Range670817
Interquartile range (IQR)660895.75

Descriptive statistics

Standard deviation306018.51
Coefficient of variation (CV)0.60114352
Kurtosis-1.1781916
Mean509060.65
Median Absolute Deviation (MAD)1177.5
Skewness-0.94585286
Sum17308062
Variance9.3647327 × 1010
MonotonicityNot monotonic
2023-12-11T05:44:39.732358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
703830 7
17.5%
702872 2
 
5.0%
702814 2
 
5.0%
703833 2
 
5.0%
701835 2
 
5.0%
41759 1
 
2.5%
704948 1
 
2.5%
42901 1
 
2.5%
42905 1
 
2.5%
711845 1
 
2.5%
Other values (14) 14
35.0%
(Missing) 6
15.0%
ValueCountFrequency (%)
41028 1
2.5%
41065 1
2.5%
41505 1
2.5%
41555 1
2.5%
41758 1
2.5%
41759 1
2.5%
42603 1
2.5%
42901 1
2.5%
42905 1
2.5%
43022 1
2.5%
ValueCountFrequency (%)
711845 1
 
2.5%
704948 1
 
2.5%
704833 1
 
2.5%
704390 1
 
2.5%
704190 1
 
2.5%
703833 2
 
5.0%
703830 7
17.5%
702902 1
 
2.5%
702872 2
 
5.0%
702845 1
 
2.5%

사업장명
Text

Distinct27
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-11T05:44:40.048901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length8.4
Min length4

Characters and Unicode

Total characters336
Distinct characters87
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

Unique20 ?
Unique (%)50.0%

Sample

1st row씨제이대한통운(주)
2nd row롯데글로벌로지스(주)
3rd row(주)코리아대동
4th row한국농수산식품유통공사
5th row롯데글로벌로지스(주)
ValueCountFrequency (%)
주)한진 5
 
11.4%
롯데글로벌로지스(주 4
 
9.1%
씨제이대한통운(주 3
 
6.8%
한국농수산식품유통공사 2
 
4.5%
대상주식회사 2
 
4.5%
오뚜기물류서비스(주 2
 
4.5%
롯데로지스틱스(주 2
 
4.5%
투에버 1
 
2.3%
케이티링커스(주 1
 
2.3%
주)판토스 1
 
2.3%
Other values (21) 21
47.7%
2023-12-11T05:44:40.551886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 35
 
10.4%
( 32
 
9.5%
) 32
 
9.5%
스 14
 
4.2%
로 12
 
3.6%
한 12
 
3.6%
대 10
 
3.0%
지 9
 
2.7%
사 7
 
2.1%
데 6
 
1.8%
Other values (77) 167
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
78.0%
Open Punctuation 32
 
9.5%
Close Punctuation 32
 
9.5%
Uppercase Letter 6
 
1.8%
Space Separator 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 35
 
13.4%
스 14
 
5.3%
로 12
 
4.6%
한 12
 
4.6%
대 10
 
3.8%
지 9
 
3.4%
사 7
 
2.7%
데 6
 
2.3%
롯 6
 
2.3%
이 6
 
2.3%
Other values (69) 145
55.3%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
V 1
16.7%
T 1
16.7%
O 1
16.7%
R 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
78.0%
Common 68
 
20.2%
Latin 6
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 35
 
13.4%
스 14
 
5.3%
로 12
 
4.6%
한 12
 
4.6%
대 10
 
3.8%
지 9
 
3.4%
사 7
 
2.7%
데 6
 
2.3%
롯 6
 
2.3%
이 6
 
2.3%
Other values (69) 145
55.3%
Latin
ValueCountFrequency (%)
E 2
33.3%
V 1
16.7%
T 1
16.7%
O 1
16.7%
R 1
16.7%
Common
ValueCountFrequency (%)
( 32
47.1%
) 32
47.1%
4
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
78.0%
ASCII 74
 
22.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 35
 
13.4%
스 14
 
5.3%
로 12
 
4.6%
한 12
 
4.6%
대 10
 
3.8%
지 9
 
3.4%
사 7
 
2.7%
데 6
 
2.3%
롯 6
 
2.3%
이 6
 
2.3%
Other values (69) 145
55.3%
ASCII
ValueCountFrequency (%)
( 32
43.2%
) 32
43.2%
4
 
5.4%
E 2
 
2.7%
V 1
 
1.4%
T 1
 
1.4%
O 1
 
1.4%
R 1
 
1.4%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.020225 × 1013
Minimum2.0161021 × 1013
Maximum2.0220721 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:40.798789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0161021 × 1013
5-th percentile2.0170702 × 1013
Q12.0180808 × 1013
median2.0210324 × 1013
Q32.0220232 × 1013
95-th percentile2.0220605 × 1013
Maximum2.0220721 × 1013
Range5.9699985 × 1010
Interquartile range (IQR)3.9424227 × 1010

Descriptive statistics

Standard deviation1.808285 × 1010
Coefficient of variation (CV)0.00089509086
Kurtosis-0.82854365
Mean2.020225 × 1013
Median Absolute Deviation (MAD)9.9855503 × 109
Skewness-0.74548633
Sum8.0809002 × 1014
Variance3.2698946 × 1020
MonotonicityNot monotonic
2023-12-11T05:44:41.005278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
20220418130514 1
 
2.5%
20180627161357 1
 
2.5%
20190416164208 1
 
2.5%
20170717112210 1
 
2.5%
20220425095602 1
 
2.5%
20220303093748 1
 
2.5%
20210406173034 1
 
2.5%
20220209125907 1
 
2.5%
20161021165941 1
 
2.5%
20220311143934 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
20161021165941 1
2.5%
20170406145346 1
2.5%
20170717112210 1
2.5%
20171128175541 1
2.5%
20180504091612 1
2.5%
20180627161357 1
2.5%
20180808142631 1
2.5%
20180808143207 1
2.5%
20180808143244 1
2.5%
20180808143341 1
2.5%
ValueCountFrequency (%)
20220721151409 1
2.5%
20220630135525 1
2.5%
20220604173020 1
2.5%
20220425095602 1
2.5%
20220418130514 1
2.5%
20220311143934 1
2.5%
20220307150837 1
2.5%
20220304113715 1
2.5%
20220303093748 1
2.5%
20220302102940 1
2.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
U
29 
I
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 29
72.5%
I 11
 
27.5%

Length

2023-12-11T05:44:41.184092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:41.343737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 29
72.5%
i 11
 
27.5%

데이터갱신일자
Date

Distinct23
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2018-08-31 23:59:59
Maximum2022-07-23 02:40:00
2023-12-11T05:44:41.475960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:44:41.670139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)84.6%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean339460.15
Minimum325882.67
Maximum357185.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:41.838628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325882.67
5-th percentile326396.88
Q1335522.95
median338718.82
Q3342861.65
95-th percentile352463.17
Maximum357185.65
Range31302.985
Interquartile range (IQR)7338.7029

Descriptive statistics

Standard deviation7496.7765
Coefficient of variation (CV)0.022084408
Kurtosis0.057775561
Mean339460.15
Median Absolute Deviation (MAD)3871.6326
Skewness0.27725784
Sum13238946
Variance56201658
MonotonicityNot monotonic
2023-12-11T05:44:42.006044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
338320.441561 3
 
7.5%
345104.629075 2
 
5.0%
341996.147284 2
 
5.0%
332043.385293 2
 
5.0%
338652.490962 2
 
5.0%
337201.767098 1
 
2.5%
334230.828823 1
 
2.5%
336912.533188 1
 
2.5%
334847.191884 1
 
2.5%
332594.833622 1
 
2.5%
Other values (23) 23
57.5%
ValueCountFrequency (%)
325882.665956 1
2.5%
326365.727247 1
2.5%
326400.337854 1
2.5%
328896.087037 1
2.5%
329091.062282 1
2.5%
332043.385293 2
5.0%
332594.833622 1
2.5%
334230.828823 1
2.5%
334847.191884 1
2.5%
336198.702041 1
2.5%
ValueCountFrequency (%)
357185.650583 1
2.5%
354152.470906 1
2.5%
352275.472365 1
2.5%
352124.562037 1
2.5%
347905.252913 1
2.5%
347444.554528 1
2.5%
347138.386516 1
2.5%
345104.629075 2
5.0%
343190.441327 1
2.5%
342532.858301 1
2.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)84.6%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean263567.6
Minimum238535.28
Maximum271717.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:42.175143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238535.28
5-th percentile253874.1
Q1263268.85
median264499.83
Q3267252.98
95-th percentile270166.57
Maximum271717.98
Range33182.7
Interquartile range (IQR)3984.1233

Descriptive statistics

Standard deviation6906.922
Coefficient of variation (CV)0.026205505
Kurtosis7.6331962
Mean263567.6
Median Absolute Deviation (MAD)2709.7726
Skewness-2.5326241
Sum10279136
Variance47705571
MonotonicityNot monotonic
2023-12-11T05:44:42.362334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
264380.82356 3
 
7.5%
268810.630389 2
 
5.0%
267252.975798 2
 
5.0%
271717.976928 2
 
5.0%
263268.852472 2
 
5.0%
259837.094146 1
 
2.5%
261391.712895 1
 
2.5%
258001.352595 1
 
2.5%
263255.981834 1
 
2.5%
255569.367788 1
 
2.5%
Other values (23) 23
57.5%
ValueCountFrequency (%)
238535.276618 1
2.5%
238616.641454 1
2.5%
255569.367788 1
2.5%
256188.262446 1
2.5%
258001.352595 1
2.5%
259837.094146 1
2.5%
260628.415315 1
2.5%
261391.712895 1
2.5%
263255.981834 1
2.5%
263268.852472 2
5.0%
ValueCountFrequency (%)
271717.976928 2
5.0%
269994.191655 1
2.5%
269901.794964 1
2.5%
268810.630389 2
5.0%
268102.63152 1
2.5%
267952.488804 1
2.5%
267459.254448 1
2.5%
267252.975798 2
5.0%
267209.603161 1
2.5%
265877.410292 1
2.5%

일반창고_동수
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
29 
2
6 
0
3 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
72.5%
2 6
 
15.0%
0 3
 
7.5%
3 2
 
5.0%

Length

2023-12-11T05:44:42.521639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:42.662671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
72.5%
2 6
 
15.0%
0 3
 
7.5%
3 2
 
5.0%

일반창고_면적
Real number (ℝ)

ZEROS 

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3716.1359
Minimum0
Maximum21034.67
Zeros3
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:42.821692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11338.2075
median2943.16
Q34862.945
95-th percentile12687.893
Maximum21034.67
Range21034.67
Interquartile range (IQR)3524.7375

Descriptive statistics

Standard deviation4043.5079
Coefficient of variation (CV)1.0880947
Kurtosis9.0789351
Mean3716.1359
Median Absolute Deviation (MAD)1740.745
Skewness2.774129
Sum148645.43
Variance16349956
MonotonicityNot monotonic
2023-12-11T05:44:43.002115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.0 3
 
7.5%
3012.68 2
 
5.0%
3666.0 2
 
5.0%
4984.98 1
 
2.5%
2049.44 1
 
2.5%
3450.48 1
 
2.5%
2217.54 1
 
2.5%
3574.82 1
 
2.5%
1122.6 1
 
2.5%
4862.0 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
0.0 3
7.5%
490.0 1
 
2.5%
1014.8 1
 
2.5%
1121.46 1
 
2.5%
1122.6 1
 
2.5%
1180.8 1
 
2.5%
1183.0 1
 
2.5%
1221.83 1
 
2.5%
1377.0 1
 
2.5%
1416.5 1
 
2.5%
ValueCountFrequency (%)
21034.67 1
2.5%
14357.86 1
2.5%
12600.0 1
2.5%
6244.98 1
2.5%
5816.0 1
2.5%
5388.45 1
2.5%
5289.26 1
2.5%
5144.39 1
2.5%
4984.98 1
2.5%
4865.78 1
2.5%

냉동_냉장창고_동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
35 
1
4 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
87.5%
1 4
 
10.0%
2 1
 
2.5%

Length

2023-12-11T05:44:43.192933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:43.339116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
87.5%
1 4
 
10.0%
2 1
 
2.5%

냉동_냉장창고_면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0.0
35 
1203.0
 
2
6634.0
 
1
1872.0
 
1
1462.2
 
1

Length

Max length6
Median length3
Mean length3.375
Min length3

Unique

Unique3 ?
Unique (%)7.5%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row6634.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 35
87.5%
1203.0 2
 
5.0%
6634.0 1
 
2.5%
1872.0 1
 
2.5%
1462.2 1
 
2.5%

Length

2023-12-11T05:44:43.516345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:43.693430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 35
87.5%
1203.0 2
 
5.0%
6634.0 1
 
2.5%
1872.0 1
 
2.5%
1462.2 1
 
2.5%

보관장소_면적
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2093.965
Minimum0
Maximum17880
Zeros32
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:43.848059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17636.8
Maximum17880
Range17880
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5074.0522
Coefficient of variation (CV)2.4231791
Kurtosis5.2268084
Mean2093.965
Median Absolute Deviation (MAD)0
Skewness2.4959207
Sum83758.6
Variance25746005
MonotonicityNot monotonic
2023-12-11T05:44:44.028218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 32
80.0%
17880.0 2
 
5.0%
8405.0 1
 
2.5%
8205.0 1
 
2.5%
1122.6 1
 
2.5%
4046.0 1
 
2.5%
8596.0 1
 
2.5%
17624.0 1
 
2.5%
ValueCountFrequency (%)
0.0 32
80.0%
1122.6 1
 
2.5%
4046.0 1
 
2.5%
8205.0 1
 
2.5%
8405.0 1
 
2.5%
8596.0 1
 
2.5%
17624.0 1
 
2.5%
17880.0 2
 
5.0%
ValueCountFrequency (%)
17880.0 2
 
5.0%
17624.0 1
 
2.5%
8596.0 1
 
2.5%
8405.0 1
 
2.5%
8205.0 1
 
2.5%
4046.0 1
 
2.5%
1122.6 1
 
2.5%
0.0 32
80.0%

직원수
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)51.4%
Missing5
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean19.171429
Minimum1
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:44.373264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q315
95-th percentile70.2
Maximum177
Range176
Interquartile range (IQR)12

Descriptive statistics

Standard deviation34.022039
Coefficient of variation (CV)1.774622
Kurtosis13.737759
Mean19.171429
Median Absolute Deviation (MAD)6
Skewness3.4306272
Sum671
Variance1157.4992
MonotonicityNot monotonic
2023-12-11T05:44:44.718054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 7
17.5%
4 3
 
7.5%
5 3
 
7.5%
8 3
 
7.5%
10 3
 
7.5%
40 2
 
5.0%
2 2
 
5.0%
7 2
 
5.0%
12 1
 
2.5%
9 1
 
2.5%
Other values (8) 8
20.0%
(Missing) 5
12.5%
ValueCountFrequency (%)
1 7
17.5%
2 2
 
5.0%
4 3
7.5%
5 3
7.5%
7 2
 
5.0%
8 3
7.5%
9 1
 
2.5%
10 3
7.5%
11 1
 
2.5%
12 1
 
2.5%
ValueCountFrequency (%)
177 1
2.5%
87 1
2.5%
63 1
2.5%
60 1
2.5%
40 2
5.0%
25 1
2.5%
23 1
2.5%
18 1
2.5%
12 1
2.5%
11 1
2.5%

시설/장비현황
Text

MISSING 

Distinct31
Distinct (%)88.6%
Missing5
Missing (%)12.5%
Memory size452.0 B
2023-12-11T05:44:45.109797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length11.542857
Min length3

Characters and Unicode

Total characters404
Distinct characters91
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

Unique27 ?
Unique (%)77.1%

Sample

1st rowE/L, 컨베어
2nd row컨베어, 지게차
3rd row랙, 지게차
4th row지게차, 철재파랫트
5th row컨베이어벨트, 지게차 등
ValueCountFrequency (%)
지게차 24
27.6%
등 8
 
9.2%
랙(rack)설치 4
 
4.6%
컨베이어 3
 
3.4%
5대 3
 
3.4%
컨베어 3
 
3.4%
렉설치 2
 
2.3%
자동c/v설비 2
 
2.3%
컨베이어벨트 2
 
2.3%
1대 2
 
2.3%
Other values (33) 34
39.1%
2023-12-11T05:44:45.654868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
12.9%
, 30
 
7.4%
차 29
 
7.2%
지 26
 
6.4%
게 26
 
6.4%
트 12
 
3.0%
베 11
 
2.7%
대 10
 
2.5%
설 10
 
2.5%
어 10
 
2.5%
Other values (81) 188
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 265
65.6%
Space Separator 52
 
12.9%
Other Punctuation 35
 
8.7%
Decimal Number 15
 
3.7%
Uppercase Letter 13
 
3.2%
Lowercase Letter 12
 
3.0%
Open Punctuation 6
 
1.5%
Close Punctuation 6
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 29
 
10.9%
지 26
 
9.8%
게 26
 
9.8%
트 12
 
4.5%
베 11
 
4.2%
대 10
 
3.8%
설 10
 
3.8%
어 10
 
3.8%
컨 9
 
3.4%
치 8
 
3.0%
Other values (58) 114
43.0%
Uppercase Letter
ValueCountFrequency (%)
C 4
30.8%
V 3
23.1%
M 1
 
7.7%
E 1
 
7.7%
R 1
 
7.7%
A 1
 
7.7%
K 1
 
7.7%
L 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 4
26.7%
2 4
26.7%
5 3
20.0%
6 2
13.3%
8 1
 
6.7%
0 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
k 3
25.0%
c 3
25.0%
a 3
25.0%
r 3
25.0%
Other Punctuation
ValueCountFrequency (%)
, 30
85.7%
/ 5
 
14.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 265
65.6%
Common 114
28.2%
Latin 25
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 29
 
10.9%
지 26
 
9.8%
게 26
 
9.8%
트 12
 
4.5%
베 11
 
4.2%
대 10
 
3.8%
설 10
 
3.8%
어 10
 
3.8%
컨 9
 
3.4%
치 8
 
3.0%
Other values (58) 114
43.0%
Latin
ValueCountFrequency (%)
C 4
16.0%
k 3
12.0%
c 3
12.0%
a 3
12.0%
r 3
12.0%
V 3
12.0%
M 1
 
4.0%
E 1
 
4.0%
R 1
 
4.0%
A 1
 
4.0%
Other values (2) 2
8.0%
Common
ValueCountFrequency (%)
52
45.6%
, 30
26.3%
( 6
 
5.3%
) 6
 
5.3%
/ 5
 
4.4%
1 4
 
3.5%
2 4
 
3.5%
5 3
 
2.6%
6 2
 
1.8%
8 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 265
65.6%
ASCII 139
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
37.4%
, 30
21.6%
( 6
 
4.3%
) 6
 
4.3%
/ 5
 
3.6%
1 4
 
2.9%
2 4
 
2.9%
C 4
 
2.9%
k 3
 
2.2%
c 3
 
2.2%
Other values (13) 22
15.8%
Hangul
ValueCountFrequency (%)
차 29
 
10.9%
지 26
 
9.8%
게 26
 
9.8%
트 12
 
4.5%
베 11
 
4.2%
대 10
 
3.8%
설 10
 
3.8%
어 10
 
3.8%
컨 9
 
3.4%
치 8
 
3.0%
Other values (58) 114
43.0%

보관요율
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)63.2%
Missing21
Missing (%)52.5%
Infinite0
Infinite (%)0.0%
Mean6559.4211
Minimum0
Maximum19400
Zeros2
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-11T05:44:45.829807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12615
median5000
Q39600
95-th percentile15557
Maximum19400
Range19400
Interquartile range (IQR)6985

Descriptive statistics

Standard deviation5212.5393
Coefficient of variation (CV)0.79466454
Kurtosis0.60713738
Mean6559.4211
Median Absolute Deviation (MAD)4080
Skewness0.79403023
Sum124629
Variance27170566
MonotonicityNot monotonic
2023-12-11T05:44:45.993013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5000 4
 
10.0%
10000 3
 
7.5%
0 2
 
5.0%
9080 2
 
5.0%
209 1
 
2.5%
6000 1
 
2.5%
3030 1
 
2.5%
2200 1
 
2.5%
19400 1
 
2.5%
15130 1
 
2.5%
Other values (2) 2
 
5.0%
(Missing) 21
52.5%
ValueCountFrequency (%)
0 2
5.0%
209 1
 
2.5%
1300 1
 
2.5%
2200 1
 
2.5%
3030 1
 
2.5%
5000 4
10.0%
6000 1
 
2.5%
9080 2
5.0%
9200 1
 
2.5%
10000 3
7.5%
ValueCountFrequency (%)
19400 1
 
2.5%
15130 1
 
2.5%
10000 3
7.5%
9200 1
 
2.5%
9080 2
5.0%
6000 1
 
2.5%
5000 4
10.0%
3030 1
 
2.5%
2200 1
 
2.5%
1300 1
 
2.5%

법인여부명
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
법인
37 
개인
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 37
92.5%
개인 3
 
7.5%

Length

2023-12-11T05:44:46.182022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:46.331288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 37
92.5%
개인 3
 
7.5%

업태_보관및창고업
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
31 
<NA>
9 

Length

Max length4
Median length1
Mean length1.675
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 31
77.5%
<NA> 9
 
22.5%

Length

2023-12-11T05:44:46.518920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:46.685721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
77.5%
na 9
 
22.5%

업태_운송및택배업
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
25 
1
15 

Length

Max length4
Median length4
Mean length2.875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
62.5%
1 15
37.5%

Length

2023-12-11T05:44:46.849330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:47.011818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
62.5%
1 15
37.5%

업태_판매업
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
31 
1
9 

Length

Max length4
Median length4
Mean length3.325
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
77.5%
1 9
 
22.5%

Length

2023-12-11T05:44:47.186773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:47.373524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
77.5%
1 9
 
22.5%

업태_제조업
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
35 
1
5 

Length

Max length4
Median length4
Mean length3.625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 35
87.5%
1 5
 
12.5%

Length

2023-12-11T05:44:47.549101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:44:47.718140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
87.5%
1 5
 
12.5%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동_냉장창고_동수냉동_냉장창고_면적보관장소_면적직원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
01물류창고업체11_45_02_P3420000201334200983250000120130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-211-3855<NA>701835대구광역시 동구 용계동 854번지대구광역시 동구 금호강변로 57 (용계동)701835씨제이대한통운(주)20220418130514U2022-04-20 02:40:00.0<NA>352124.562037264490.74415924984.9800.00.010E/L, 컨베어5000법인11<NA><NA>
12물류창고업체11_45_02_P3420000201334200983250000220130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-381-3355<NA>701835대구광역시 동구 용계동 662번지 1호대구광역시 동구 화랑로 584 (용계동)701835롯데글로벌로지스(주)20210128143842U2021-01-30 02:40:00.0<NA>352275.472365264925.05816415388.4500.00.060컨베어, 지게차5000법인11<NA><NA>
23물류창고업체11_45_02_P3420000201334200983250000320130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-965-2620<NA>701170대구광역시 동구 봉무동 1566번지대구광역시 동구 팔공로45길 11 (봉무동)701170(주)코리아대동20220304113715U2022-03-06 02:40:00.0<NA>347905.252913269901.79496411909.000.00.025랙, 지게차<NA>법인11<NA>1
34물류창고업체11_45_02_P3420000201334200983250000420130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-963-8942<NA>701320대구광역시 동구 괴전동 258번지대구광역시 동구 안심로102길 9 (괴전동)701320한국농수산식품유통공사20220307150837U2022-03-09 02:40:00.0<NA>357185.650583265189.065200.026634.00.02지게차, 철재파랫트<NA>법인111<NA>
45물류창고업체11_45_02_P3420000201534201503252580020150202<NA>1영업/정상1영업중<NA><NA><NA><NA>053-351-0777<NA><NA>대구광역시 동구 율암동 1151대구광역시 동구 혁신대로 85 (율암동)41065롯데글로벌로지스(주)20220630135525U2022-07-02 02:40:00.0<NA>354152.470906265877.410292214357.8600.00.040컨베이어벨트, 지게차 등0법인1<NA><NA><NA>
56물류창고업체11_45_02_P3420000202034201803250000120200909<NA>1영업/정상1영업중<NA><NA><NA><NA>054-979-2202<NA><NA>대구광역시 동구 봉무동 1563-2대구광역시 동구 팔공로53길 114 (봉무동)41028(주)대원지에스아이20210628141041U2021-06-30 02:40:00.0<NA>347444.554528269994.19165524865.7800.00.010컨베이어벨트, 지게차 등<NA>법인1<NA><NA><NA>
67물류창고업체11_45_02_P3430000201234300533250000320130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-567-7748<NA><NA>대구광역시 서구 이현동 44번지 48호대구광역시 서구 국채보상로23길 13 (이현동)41759대동산업공사20210325092933U2021-03-27 02:40:00.0<NA>339313.968196264434.17220211377.000.00.04콤베아<NA>개인1<NA><NA><NA>
78물류창고업체11_45_02_P3430000201234300533250000420130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-571-7740<NA>703830대구광역시 서구 이현동 45번지 214호대구광역시 서구 국채보상로5길 28 (이현동)703830동진무역20210325093033U2021-03-27 02:40:00.0<NA>338512.293391264499.83054411221.8300.00.01지게차, 원단5000개인1<NA><NA><NA>
89물류창고업체11_45_02_P3430000201234300533250000620130311<NA>1영업/정상1영업중<NA><NA><NA><NA>053-556-5001<NA>703830대구광역시 서구 이현동 44번지 34호대구광역시 서구 와룡로90길 64 (이현동)703830풍국산업주식회사20210325093317U2021-03-27 02:40:00.0<NA>339497.560082264475.5429412975.2200.00.012상하차용 컨베어 6대209법인1<NA><NA><NA>
910물류창고업체11_45_02_P3430000201334300533250000920130712<NA>1영업/정상1영업중<NA><NA><NA><NA>053-559-0081<NA>703830대구광역시 서구 이현동 42번지 275호대구광역시 서구 국채보상로 51 (이현동)703830(주) 신양보세물류20210325093439U2021-03-27 02:40:00.0<NA>338718.824505264300.66884623444.02500.00.09화물승강기 2기, 지게차 5대, 랙(rack)설치 등6000법인1<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동_냉장창고_동수냉동_냉장창고_면적보관장소_면적직원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
3031물류창고업체11_45_02_P3480000202234803703250000120220302<NA>1영업/정상1영업중<NA><NA><NA><NA>053-614-0018<NA><NA>대구광역시 달성군 유가읍 금리 1134-1대구광역시 달성군 유가읍 테크노순환로1길 71, 대원제이(주) 티피산단보세창고43022대원제이(주) 티피산단보세창고20220311143934U2022-03-13 02:40:00.0<NA><NA><NA>14862.000.04046.01고정식도크80M, 지게차 2대<NA>법인1<NA><NA><NA>
3132물류창고업체11_45_02_P3480000201234803133250000120130227<NA>1영업/정상1영업중<NA><NA><NA><NA>02-3771-1954<NA>711845대구광역시 달성군 옥포면 본리리 742번지 1호 , 742번지-2호대구광역시 달성군 옥포면 비슬로453길 15711845(주)판토스20210809102232U2021-08-11 02:40:00.0<NA>332594.833622255569.367788121034.6700.00.0177지게차 16대<NA>법인111<NA>
3233물류창고업체11_45_02_P3480000201334803133250000420130227<NA>1영업/정상1영업중<NA><NA><NA><NA>053-757-9036<NA>711823대구광역시 달성군 하빈면 하산리 1105번지 1호대구광역시 달성군 하빈면 달구벌대로8길 22<NA>주식회사 투에버 (TOEVER)20210322101217U2021-03-24 02:40:00.0<NA>326400.337854264928.22081111416.500.00.011지게차 2<NA>법인1111
3334물류창고업체11_45_02_P3480000201334803133250000620140103<NA>1영업/정상1영업중<NA><NA><NA><NA>053-610-7948<NA>711891대구광역시 달성군 구지면 예현리 760번지 2호대구광역시 달성군 구지면 달성2차로 200<NA>(주)영원무역20210322101155U2021-03-24 02:40:00.0<NA>329091.062282238616.641454312600.000.00.018이동식 컨베이어9200법인1<NA>11
3435물류창고업체11_45_02_P3480000201634803133250000120160830<NA>1영업/정상1영업중<NA><NA><NA><NA>055-714-1980<NA><NA>대구광역시 달성군 하빈면 봉촌리 768번지 30호대구광역시 달성군 하빈면 하빈남로 44842905한국로지스풀(주)20210322101127U2021-03-24 02:40:00.0<NA>325882.665956263771.24527112631.0900.00.01지게차(1대)<NA>법인1<NA><NA><NA>
3536물류창고업체11_45_02_P3480000201734803133250000120170904<NA>1영업/정상1영업중<NA><NA><NA><NA>053-760-7945<NA><NA>대구광역시 달성군 가창면 용계리 452번지<NA><NA>(주)한진20220302102940U2022-03-04 02:40:00.0<NA>347138.386516256188.26244615144.3900.00.023지게차 2대, 파레트 자키 1대, 스트레치 랩 1대<NA>법인1<NA><NA><NA>
3637물류창고업체11_45_02_P3480000201834803703250000120180503<NA>1영업/정상1영업중<NA><NA><NA><NA>053-582-7396<NA><NA>대구광역시 달성군 하빈면 대평리 340번지대구광역시 달성군 하빈면 하빈로171길 28-2342901롯데글로벌로지스(주)20210322100924U2021-03-24 02:40:00.0<NA>332043.385293271717.97692813666.000.017880.05지게차 5대<NA>법인111<NA>
3738물류창고업체11_45_02_P3480000201234803133250000220130227<NA>3폐업3폐업20180504<NA><NA><NA>053 582 7397<NA>711822대구광역시 달성군 하빈면 대평리 340번지대구광역시 달성군 하빈면 하빈로171길 28-23<NA>롯데로지스틱스(주)20180504091612I2018-08-31 23:59:59.0<NA>332043.385293271717.97692813666.000.017880.05지게차 5대<NA>법인111<NA>
3839물류창고업체11_45_02_P3480000201334803133250000320130227<NA>3폐업3폐업20200407<NA><NA><NA><NA><NA>711823대구광역시 달성군 하빈면 하산리 1105번지대구광역시 달성군 하빈면 달구벌대로8길 46<NA>한양파렛트20200408085157U2020-04-10 02:40:00.0<NA>326365.727247264804.12639511717.500.08596.0<NA><NA><NA>개인<NA><NA><NA><NA>
3940물류창고업체11_45_02_P3480000201334803133250000520130227<NA>3폐업3폐업20190614<NA><NA><NA>0542306009<NA>711891대구광역시 달성군 구지면 예현리 760번지 3호대구광역시 달성군 구지면 달성2차4로 75<NA>세방(주)20190715142415U2019-07-17 02:40:00.0<NA>328896.087037238535.27661815816.000.017624.040트럭, 지게차1300법인1111