Overview

Dataset statistics

Number of variables41
Number of observations56
Missing cells476
Missing cells (%)20.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.4 KiB
Average record size in memory354.4 B

Variable types

Numeric9
Categorical15
DateTime4
Unsupported6
Text7

Dataset

Description24년03월_6270000_대구광역시_11_45_02_P_물류창고업체
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000106686&dataSetDetailId=DDI_0000106724&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
냉동_냉장창고_동수 is highly imbalanced (68.5%)Imbalance
냉동_냉장창고_면적 is highly imbalanced (73.9%)Imbalance
법인여부명 is highly imbalanced (50.9%)Imbalance
업태_제조업 is highly imbalanced (62.9%)Imbalance
인허가취소일자 has 56 (100.0%) missing valuesMissing
폐업일자 has 35 (62.5%) missing valuesMissing
휴업시작일자 has 56 (100.0%) missing valuesMissing
휴업종료일자 has 56 (100.0%) missing valuesMissing
재개업일자 has 56 (100.0%) missing valuesMissing
소재지전화 has 3 (5.4%) missing valuesMissing
소재지면적 has 56 (100.0%) missing valuesMissing
소재지우편번호 has 28 (50.0%) missing valuesMissing
소재지전체주소 has 2 (3.6%) missing valuesMissing
도로명전체주소 has 1 (1.8%) missing valuesMissing
도로명우편번호 has 6 (10.7%) missing valuesMissing
업태구분명 has 56 (100.0%) missing valuesMissing
좌표정보(X) has 2 (3.6%) missing valuesMissing
좌표정보(Y) has 2 (3.6%) missing valuesMissing
직원수 has 12 (21.4%) missing valuesMissing
시설/장비현황 has 13 (23.2%) missing valuesMissing
보관요율 has 36 (64.3%) 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 (5.4%) zerosZeros
보관장소_면적 has 49 (87.5%) zerosZeros
보관요율 has 2 (3.6%) zerosZeros

Reproduction

Analysis started2024-04-29 12:45:56.917842
Analysis finished2024-04-29 12:45:57.581733
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:45:57.651465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.75
Q114.75
median28.5
Q342.25
95-th percentile53.25
Maximum56
Range55
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.309506
Coefficient of variation (CV)0.57226338
Kurtosis-1.2
Mean28.5
Median Absolute Deviation (MAD)14
Skewness0
Sum1596
Variance266
MonotonicityStrictly increasing
2024-04-29T21:45:57.785218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
30 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
물류창고업체
56 

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 56
100.0%

Length

2024-04-29T21:45:57.909837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:57.996661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물류창고업체 56
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
11_45_02_P
56 

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 56
100.0%

Length

2024-04-29T21:45:58.086953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:58.173537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_45_02_p 56
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3662267.9
Minimum3420000
Maximum5141000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:45:58.245041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3420000
Q13430000
median3450000
Q33480000
95-th percentile5141000
Maximum5141000
Range1721000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation564398.94
Coefficient of variation (CV)0.15411187
Kurtosis3.5387772
Mean3662267.9
Median Absolute Deviation (MAD)25000
Skewness2.3235508
Sum2.05087 × 108
Variance3.1854616 × 1011
MonotonicityIncreasing
2024-04-29T21:45:58.342432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3430000 14
25.0%
3480000 14
25.0%
3450000 8
14.3%
3420000 7
12.5%
5141000 7
12.5%
3470000 6
10.7%
ValueCountFrequency (%)
3420000 7
12.5%
3430000 14
25.0%
3450000 8
14.3%
3470000 6
10.7%
3480000 14
25.0%
5141000 7
12.5%
ValueCountFrequency (%)
5141000 7
12.5%
3480000 14
25.0%
3470000 6
10.7%
3450000 8
14.3%
3430000 14
25.0%
3420000 7
12.5%

관리번호
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0162234 × 1018
Minimum2.012343 × 1018
Maximum2.023348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:45:58.468555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.012343 × 1018
5-th percentile2.012343 × 1018
Q12.013342 × 1018
median2.013348 × 1018
Q32.020514 × 1018
95-th percentile2.023348 × 1018
Maximum2.023348 × 1018
Range1.1005033 × 1016
Interquartile range (IQR)7.1719987 × 1015

Descriptive statistics

Standard deviation4.2431026 × 1015
Coefficient of variation (CV)0.0021044804
Kurtosis-1.238846
Mean2.0162234 × 1018
Median Absolute Deviation (MAD)1.005026 × 1015
Skewness0.72698706
Sum2.2280444 × 1018
Variance1.800392 × 1031
MonotonicityNot monotonic
2024-04-29T21:45:58.603032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2015342015032525800 1
 
1.8%
2013347008632500001 1
 
1.8%
2013347008632500004 1
 
1.8%
2015347008632500001 1
 
1.8%
2022347018432500001 1
 
1.8%
2013347008632500003 1
 
1.8%
2018348037032500001 1
 
1.8%
2023348038232500002 1
 
1.8%
2022348037032500001 1
 
1.8%
2023348038232500001 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
2012343005332500001 1
1.8%
2012343005332500002 1
1.8%
2012343005332500003 1
1.8%
2012343005332500004 1
1.8%
2012343005332500005 1
1.8%
2012343005332500006 1
1.8%
2012343005332500007 1
1.8%
2012343005332500008 1
1.8%
2012348031332500001 1
1.8%
2012348031332500002 1
1.8%
ValueCountFrequency (%)
2023348038232500004 1
1.8%
2023348038232500003 1
1.8%
2023348038232500002 1
1.8%
2023348038232500001 1
1.8%
2023343010032500003 1
1.8%
2023343010032500002 1
1.8%
2023343010032500001 1
1.8%
2023342018032500001 1
1.8%
2022348037032500001 1
1.8%
2022347018432500001 1
1.8%

인허가일자
Date

Distinct30
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2012-08-03 00:00:00
Maximum2023-09-26 00:00:00
2024-04-29T21:45:58.718451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:45:58.825454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
32 
3
24 

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 32
57.1%
3 24
42.9%

Length

2024-04-29T21:45:58.945625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:59.037203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 32
57.1%
3 24
42.9%

영업상태명
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
영업/정상
32 
폐업
24 

Length

Max length5
Median length5
Mean length3.7142857
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 32
57.1%
폐업 24
42.9%

Length

2024-04-29T21:45:59.137355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:59.226056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 32
57.1%
폐업 24
42.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
32 
3
24 

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 32
57.1%
3 24
42.9%

Length

2024-04-29T21:45:59.312298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:59.397723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 32
57.1%
3 24
42.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
영업중
32 
폐업
24 

Length

Max length3
Median length3
Mean length2.5714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 32
57.1%
폐업 24
42.9%

Length

2024-04-29T21:45:59.487567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:45:59.581986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 32
57.1%
폐업 24
42.9%

폐업일자
Date

MISSING 

Distinct18
Distinct (%)85.7%
Missing35
Missing (%)62.5%
Memory size580.0 B
Minimum2016-01-20 00:00:00
Maximum2023-12-27 00:00:00
2024-04-29T21:45:59.684000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:45:59.788949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

소재지전화
Text

MISSING 

Distinct48
Distinct (%)90.6%
Missing3
Missing (%)5.4%
Memory size580.0 B
2024-04-29T21:45:59.971537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.90566
Min length10

Characters and Unicode

Total characters631
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

Unique45 ?
Unique (%)84.9%

Sample

1st row053-351-0777
2nd row053-963-8942
3rd row053-965-2620
4th row053-381-3355
5th row053-211-3855
ValueCountFrequency (%)
053 11
 
15.1%
054-383-8420 3
 
4.1%
02-1544-9898 3
 
4.1%
5620365 2
 
2.7%
053-582-7396 1
 
1.4%
383 1
 
1.4%
4851 1
 
1.4%
054 1
 
1.4%
380 1
 
1.4%
0620 1
 
1.4%
Other values (48) 48
65.8%
2024-04-29T21:46:00.476187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 108
17.1%
5 94
14.9%
3 77
12.2%
- 76
12.0%
8 43
 
6.8%
4 42
 
6.7%
1 36
 
5.7%
7 35
 
5.5%
2 34
 
5.4%
9 34
 
5.4%
Other values (2) 52
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 532
84.3%
Dash Punctuation 76
 
12.0%
Space Separator 23
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108
20.3%
5 94
17.7%
3 77
14.5%
8 43
 
8.1%
4 42
 
7.9%
1 36
 
6.8%
7 35
 
6.6%
2 34
 
6.4%
9 34
 
6.4%
6 29
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 631
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108
17.1%
5 94
14.9%
3 77
12.2%
- 76
12.0%
8 43
 
6.8%
4 42
 
6.7%
1 36
 
5.7%
7 35
 
5.5%
2 34
 
5.4%
9 34
 
5.4%
Other values (2) 52
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108
17.1%
5 94
14.9%
3 77
12.2%
- 76
12.0%
8 43
 
6.8%
4 42
 
6.7%
1 36
 
5.7%
7 35
 
5.5%
2 34
 
5.4%
9 34
 
5.4%
Other values (2) 52
8.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

소재지우편번호
Text

MISSING 

Distinct17
Distinct (%)60.7%
Missing28
Missing (%)50.0%
Memory size580.0 B
2024-04-29T21:46:00.629495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters196
Distinct characters10
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

Unique11 ?
Unique (%)39.3%

Sample

1st row701-320
2nd row701-170
3rd row701-835
4th row703-833
5th row703-830
ValueCountFrequency (%)
703-830 7
25.0%
702-814 2
 
7.1%
702-872 2
 
7.1%
711-823 2
 
7.1%
703-833 2
 
7.1%
711-891 2
 
7.1%
701-320 1
 
3.6%
701-835 1
 
3.6%
702-845 1
 
3.6%
704-190 1
 
3.6%
Other values (7) 7
25.0%
2024-04-29T21:46:00.883512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
17.3%
7 31
15.8%
- 28
14.3%
3 27
13.8%
8 23
11.7%
1 21
10.7%
2 14
7.1%
4 9
 
4.6%
9 6
 
3.1%
5 3
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
85.7%
Dash Punctuation 28
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
20.2%
7 31
18.5%
3 27
16.1%
8 23
13.7%
1 21
12.5%
2 14
8.3%
4 9
 
5.4%
9 6
 
3.6%
5 3
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 196
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
17.3%
7 31
15.8%
- 28
14.3%
3 27
13.8%
8 23
11.7%
1 21
10.7%
2 14
7.1%
4 9
 
4.6%
9 6
 
3.1%
5 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
17.3%
7 31
15.8%
- 28
14.3%
3 27
13.8%
8 23
11.7%
1 21
10.7%
2 14
7.1%
4 9
 
4.6%
9 6
 
3.1%
5 3
 
1.5%

소재지전체주소
Text

MISSING 

Distinct45
Distinct (%)83.3%
Missing2
Missing (%)3.6%
Memory size580.0 B
2024-04-29T21:46:01.114952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length26
Mean length21.425926
Min length17

Characters and Unicode

Total characters1157
Distinct characters78
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

Unique38 ?
Unique (%)70.4%

Sample

1st row대구광역시 동구 봉무동 1547
2nd row대구광역시 동구 괴전동 258번지
3rd row대구광역시 동구 봉무동 1566번지
4th row대구광역시 동구 율암동 1151
5th row대구광역시 동구 용계동 854번지
ValueCountFrequency (%)
대구광역시 54
21.2%
달성군 14
 
5.5%
서구 14
 
5.5%
이현동 9
 
3.5%
북구 8
 
3.1%
동구 7
 
2.7%
달서구 6
 
2.4%
하빈면 5
 
2.0%
군위군 5
 
2.0%
45번지 4
 
1.6%
Other values (86) 129
50.6%
2024-04-29T21:46:01.512825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
17.5%
구 92
 
8.0%
대 56
 
4.8%
1 55
 
4.8%
광 54
 
4.7%
역 54
 
4.7%
시 54
 
4.7%
동 41
 
3.5%
지 36
 
3.1%
4 35
 
3.0%
Other values (68) 478
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
62.4%
Decimal Number 219
 
18.9%
Space Separator 202
 
17.5%
Dash Punctuation 13
 
1.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 92
 
12.7%
대 56
 
7.8%
광 54
 
7.5%
역 54
 
7.5%
시 54
 
7.5%
동 41
 
5.7%
지 36
 
5.0%
번 33
 
4.6%
리 24
 
3.3%
군 24
 
3.3%
Other values (55) 254
35.2%
Decimal Number
ValueCountFrequency (%)
1 55
25.1%
4 35
16.0%
6 23
10.5%
5 21
 
9.6%
0 19
 
8.7%
3 17
 
7.8%
2 16
 
7.3%
8 14
 
6.4%
7 11
 
5.0%
9 8
 
3.7%
Space Separator
ValueCountFrequency (%)
202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
62.4%
Common 435
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 92
 
12.7%
대 56
 
7.8%
광 54
 
7.5%
역 54
 
7.5%
시 54
 
7.5%
동 41
 
5.7%
지 36
 
5.0%
번 33
 
4.6%
리 24
 
3.3%
군 24
 
3.3%
Other values (55) 254
35.2%
Common
ValueCountFrequency (%)
202
46.4%
1 55
 
12.6%
4 35
 
8.0%
6 23
 
5.3%
5 21
 
4.8%
0 19
 
4.4%
3 17
 
3.9%
2 16
 
3.7%
8 14
 
3.2%
- 13
 
3.0%
Other values (3) 20
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
62.4%
ASCII 435
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
46.4%
1 55
 
12.6%
4 35
 
8.0%
6 23
 
5.3%
5 21
 
4.8%
0 19
 
4.4%
3 17
 
3.9%
2 16
 
3.7%
8 14
 
3.2%
- 13
 
3.0%
Other values (3) 20
 
4.6%
Hangul
ValueCountFrequency (%)
구 92
 
12.7%
대 56
 
7.8%
광 54
 
7.5%
역 54
 
7.5%
시 54
 
7.5%
동 41
 
5.7%
지 36
 
5.0%
번 33
 
4.6%
리 24
 
3.3%
군 24
 
3.3%
Other values (55) 254
35.2%

도로명전체주소
Text

MISSING 

Distinct44
Distinct (%)80.0%
Missing1
Missing (%)1.8%
Memory size580.0 B
2024-04-29T21:46:01.769504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length33
Mean length25.436364
Min length21

Characters and Unicode

Total characters1399
Distinct characters119
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

Unique36 ?
Unique (%)65.5%

Sample

1st row대구광역시 동구 팔공로53길 96 (봉무동)
2nd row대구광역시 동구 안심로102길 9 (괴전동)
3rd row대구광역시 동구 팔공로45길 11 (봉무동)
4th row대구광역시 동구 혁신대로 85 (율암동)
5th row대구광역시 동구 금호강변로 57 (용계동)
ValueCountFrequency (%)
대구광역시 55
 
19.2%
서구 14
 
4.9%
달성군 13
 
4.5%
이현동 10
 
3.5%
북구 8
 
2.8%
동구 7
 
2.4%
군위군 7
 
2.4%
효령면 6
 
2.1%
달서구 6
 
2.1%
하빈면 5
 
1.7%
Other values (99) 155
54.2%
2024-04-29T21:46:02.127686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
16.5%
구 95
 
6.8%
대 66
 
4.7%
시 56
 
4.0%
광 55
 
3.9%
역 55
 
3.9%
로 54
 
3.9%
동 47
 
3.4%
1 43
 
3.1%
( 40
 
2.9%
Other values (109) 657
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 889
63.5%
Space Separator 231
 
16.5%
Decimal Number 191
 
13.7%
Open Punctuation 40
 
2.9%
Close Punctuation 39
 
2.8%
Other Punctuation 6
 
0.4%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 95
 
10.7%
대 66
 
7.4%
시 56
 
6.3%
광 55
 
6.2%
역 55
 
6.2%
로 54
 
6.1%
동 47
 
5.3%
길 27
 
3.0%
군 27
 
3.0%
달 24
 
2.7%
Other values (94) 383
43.1%
Decimal Number
ValueCountFrequency (%)
1 43
22.5%
2 30
15.7%
5 30
15.7%
8 16
 
8.4%
3 15
 
7.9%
7 14
 
7.3%
4 14
 
7.3%
0 11
 
5.8%
6 11
 
5.8%
9 7
 
3.7%
Space Separator
ValueCountFrequency (%)
231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 889
63.5%
Common 510
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 95
 
10.7%
대 66
 
7.4%
시 56
 
6.3%
광 55
 
6.2%
역 55
 
6.2%
로 54
 
6.1%
동 47
 
5.3%
길 27
 
3.0%
군 27
 
3.0%
달 24
 
2.7%
Other values (94) 383
43.1%
Common
ValueCountFrequency (%)
231
45.3%
1 43
 
8.4%
( 40
 
7.8%
) 39
 
7.6%
2 30
 
5.9%
5 30
 
5.9%
8 16
 
3.1%
3 15
 
2.9%
7 14
 
2.7%
4 14
 
2.7%
Other values (5) 38
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 889
63.5%
ASCII 510
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
45.3%
1 43
 
8.4%
( 40
 
7.8%
) 39
 
7.6%
2 30
 
5.9%
5 30
 
5.9%
8 16
 
3.1%
3 15
 
2.9%
7 14
 
2.7%
4 14
 
2.7%
Other values (5) 38
 
7.5%
Hangul
ValueCountFrequency (%)
구 95
 
10.7%
대 66
 
7.4%
시 56
 
6.3%
광 55
 
6.2%
역 55
 
6.2%
로 54
 
6.1%
동 47
 
5.3%
길 27
 
3.0%
군 27
 
3.0%
달 24
 
2.7%
Other values (94) 383
43.1%

도로명우편번호
Text

MISSING 

Distinct32
Distinct (%)64.0%
Missing6
Missing (%)10.7%
Memory size580.0 B
2024-04-29T21:46:02.304128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.92
Min length5

Characters and Unicode

Total characters296
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

Unique24 ?
Unique (%)48.0%

Sample

1st row41024
2nd row701-320
3rd row701-170
4th row41065
5th row701-835
ValueCountFrequency (%)
703-830 7
 
14.0%
39037 6
 
12.0%
43022 3
 
6.0%
702-872 2
 
4.0%
41065 2
 
4.0%
703-833 2
 
4.0%
41756 2
 
4.0%
702-814 2
 
4.0%
42943 1
 
2.0%
42603 1
 
2.0%
Other values (22) 22
44.0%
2024-04-29T21:46:02.605687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54
18.2%
3 44
14.9%
7 38
12.8%
4 33
11.1%
- 23
7.8%
2 23
7.8%
1 22
7.4%
8 21
 
7.1%
5 17
 
5.7%
9 16
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 273
92.2%
Dash Punctuation 23
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54
19.8%
3 44
16.1%
7 38
13.9%
4 33
12.1%
2 23
8.4%
1 22
8.1%
8 21
 
7.7%
5 17
 
6.2%
9 16
 
5.9%
6 5
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54
18.2%
3 44
14.9%
7 38
12.8%
4 33
11.1%
- 23
7.8%
2 23
7.8%
1 22
7.4%
8 21
 
7.1%
5 17
 
5.7%
9 16
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54
18.2%
3 44
14.9%
7 38
12.8%
4 33
11.1%
- 23
7.8%
2 23
7.8%
1 22
7.4%
8 21
 
7.1%
5 17
 
5.7%
9 16
 
5.4%

사업장명
Text

Distinct39
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-29T21:46:02.861969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.5
Min length4

Characters and Unicode

Total characters532
Distinct characters99
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

Unique29 ?
Unique (%)51.8%

Sample

1st row롯데글로벌로지스(주)
2nd row한국농수산식품유통공사
3rd row(주)코리아대동
4th row롯데글로벌로지스(주)
5th row씨제이대한통운(주)
ValueCountFrequency (%)
주)한진 5
 
6.7%
유한회사 4
 
5.3%
롯데글로벌로지스(주 4
 
5.3%
쿠팡로지스틱스서비스 3
 
4.0%
씨제이대한통운(주 3
 
4.0%
쿠팡 3
 
4.0%
주)농협물류 2
 
2.7%
주식회사 2
 
2.7%
서비스 2
 
2.7%
대상주식회사 2
 
2.7%
Other values (39) 45
60.0%
2024-04-29T21:46:03.204264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 41
 
7.7%
( 39
 
7.3%
) 39
 
7.3%
스 37
 
7.0%
로 23
 
4.3%
지 21
 
3.9%
19
 
3.6%
한 16
 
3.0%
사 16
 
3.0%
유 11
 
2.1%
Other values (89) 270
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 429
80.6%
Open Punctuation 39
 
7.3%
Close Punctuation 39
 
7.3%
Space Separator 19
 
3.6%
Uppercase Letter 6
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 41
 
9.6%
스 37
 
8.6%
로 23
 
5.4%
지 21
 
4.9%
한 16
 
3.7%
사 16
 
3.7%
유 11
 
2.6%
대 11
 
2.6%
서 10
 
2.3%
비 10
 
2.3%
Other values (81) 233
54.3%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
T 1
16.7%
O 1
16.7%
V 1
16.7%
R 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 429
80.6%
Common 97
 
18.2%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 41
 
9.6%
스 37
 
8.6%
로 23
 
5.4%
지 21
 
4.9%
한 16
 
3.7%
사 16
 
3.7%
유 11
 
2.6%
대 11
 
2.6%
서 10
 
2.3%
비 10
 
2.3%
Other values (81) 233
54.3%
Latin
ValueCountFrequency (%)
E 2
33.3%
T 1
16.7%
O 1
16.7%
V 1
16.7%
R 1
16.7%
Common
ValueCountFrequency (%)
( 39
40.2%
) 39
40.2%
19
19.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 429
80.6%
ASCII 103
 
19.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 41
 
9.6%
스 37
 
8.6%
로 23
 
5.4%
지 21
 
4.9%
한 16
 
3.7%
사 16
 
3.7%
유 11
 
2.6%
대 11
 
2.6%
서 10
 
2.3%
비 10
 
2.3%
Other values (81) 233
54.3%
ASCII
ValueCountFrequency (%)
( 39
37.9%
) 39
37.9%
19
18.4%
E 2
 
1.9%
T 1
 
1.0%
O 1
 
1.0%
V 1
 
1.0%
R 1
 
1.0%

최종수정시점
Date

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2016-10-21 16:59:41
Maximum2024-02-23 14:42:14
2024-04-29T21:46:03.347877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:46:03.468131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
U
39 
I
17 

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 39
69.6%
I 17
30.4%

Length

2024-04-29T21:46:03.579502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:03.666768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 39
69.6%
i 17
30.4%

데이터갱신일자
Date

Distinct34
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2018-08-31 23:59:59
Maximum2024-02-25 02:40:00
2024-04-29T21:46:03.759214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:46:03.876350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)74.1%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean338898.3
Minimum325882.67
Maximum354177.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:03.986668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325882.67
5-th percentile328022.57
Q1334653.64
median338686.43
Q3342032.93
95-th percentile350939.15
Maximum354177.19
Range28294.528
Interquartile range (IQR)7379.2911

Descriptive statistics

Standard deviation6768.6335
Coefficient of variation (CV)0.019972462
Kurtosis-0.085270627
Mean338898.3
Median Absolute Deviation (MAD)3682.8755
Skewness0.16625896
Sum18300508
Variance45814399
MonotonicityNot monotonic
2024-04-29T21:46:04.112161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
341575.713235792 5
 
8.9%
338320.441560511 4
 
7.1%
330886.481536152 3
 
5.4%
341996.147284023 2
 
3.6%
354177.193716317 2
 
3.6%
332043.385293457 2
 
3.6%
338652.490961776 2
 
3.6%
345104.629074562 2
 
3.6%
337201.767098434 1
 
1.8%
334589.117012608 1
 
1.8%
Other values (30) 30
53.6%
(Missing) 2
 
3.6%
ValueCountFrequency (%)
325882.665956232 1
 
1.8%
326365.727247401 1
 
1.8%
326400.337853716 1
 
1.8%
328896.087037075 1
 
1.8%
329091.062281604 1
 
1.8%
329420.447132376 1
 
1.8%
330886.481536152 3
5.4%
332043.385293457 2
3.6%
332594.833622458 1
 
1.8%
334230.828822873 1
 
1.8%
ValueCountFrequency (%)
354177.193716317 2
3.6%
352124.562037238 1
1.8%
350300.849245576 1
1.8%
347905.252912818 1
1.8%
347444.554528153 1
1.8%
347437.684055623 1
1.8%
347138.386516576 1
1.8%
345104.629074562 2
3.6%
343190.441326918 1
1.8%
342535.202371455 1
1.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)74.1%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean265740
Minimum238535.28
Maximum299931.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:04.223727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238535.28
5-th percentile242148.43
Q1261857.78
median264483.14
Q3268633.71
95-th percentile292024.59
Maximum299931.09
Range61395.813
Interquartile range (IQR)6775.9301

Descriptive statistics

Standard deviation13420.237
Coefficient of variation (CV)0.050501381
Kurtosis1.0330093
Mean265740
Median Absolute Deviation (MAD)3737.2671
Skewness0.42475198
Sum14349960
Variance1.8010276 × 108
MonotonicityNot monotonic
2024-04-29T21:46:04.356761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
292024.590733752 5
 
8.9%
264380.823560052 4
 
7.1%
243325.452076391 3
 
5.4%
267252.975798268 2
 
3.6%
265815.732944538 2
 
3.6%
271717.976927625 2
 
3.6%
263268.852472308 2
 
3.6%
268810.630389218 2
 
3.6%
259837.094145711 1
 
1.8%
257337.093046226 1
 
1.8%
Other values (30) 30
53.6%
(Missing) 2
 
3.6%
ValueCountFrequency (%)
238535.276618296 1
 
1.8%
238616.641453511 1
 
1.8%
239962.519021308 1
 
1.8%
243325.452076391 3
5.4%
255569.367788461 1
 
1.8%
256188.262445828 1
 
1.8%
257337.093046226 1
 
1.8%
258001.35259542 1
 
1.8%
259837.094145711 1
 
1.8%
260171.530169697 1
 
1.8%
ValueCountFrequency (%)
299931.089420336 1
 
1.8%
292024.590733752 5
8.9%
290695.803214273 1
 
1.8%
271717.976927625 2
 
3.6%
270160.859465186 1
 
1.8%
269994.191654881 1
 
1.8%
269901.794963631 1
 
1.8%
268810.630389218 2
 
3.6%
268102.949572544 1
 
1.8%
267952.488803975 1
 
1.8%

일반창고_동수
Categorical

Distinct5
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
43 
2
6 
0
 
3
3
 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 43
76.8%
2 6
 
10.7%
0 3
 
5.4%
3 3
 
5.4%
4 1
 
1.8%

Length

2024-04-29T21:46:04.477883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:04.576956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 43
76.8%
2 6
 
10.7%
0 3
 
5.4%
3 3
 
5.4%
4 1
 
1.8%

일반창고_면적
Real number (ℝ)

ZEROS 

Distinct49
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9613.8997
Minimum0
Maximum329867.95
Zeros3
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:04.689622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile367.5
Q11861.125
median2943.16
Q34895.58
95-th percentile11825.835
Maximum329867.95
Range329867.95
Interquartile range (IQR)3034.455

Descriptive statistics

Standard deviation43719.812
Coefficient of variation (CV)4.5475627
Kurtosis55.214304
Mean9613.8997
Median Absolute Deviation (MAD)1546.41
Skewness7.4072925
Sum538378.39
Variance1.911422 × 109
MonotonicityNot monotonic
2024-04-29T21:46:04.837549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 3
 
5.4%
9175.69 3
 
5.4%
2450.0 2
 
3.6%
3012.68 2
 
3.6%
3666.0 2
 
3.6%
21034.67 1
 
1.8%
3450.48 1
 
1.8%
2217.54 1
 
1.8%
3574.82 1
 
1.8%
5101.25 1
 
1.8%
Other values (39) 39
69.6%
ValueCountFrequency (%)
0.0 3
5.4%
490.0 1
 
1.8%
1014.8 1
 
1.8%
1121.46 1
 
1.8%
1122.6 1
 
1.8%
1180.8 1
 
1.8%
1183.0 1
 
1.8%
1208.0 1
 
1.8%
1221.83 1
 
1.8%
1377.0 1
 
1.8%
ValueCountFrequency (%)
329867.95 1
 
1.8%
21034.67 1
 
1.8%
12600.0 1
 
1.8%
11567.78 1
 
1.8%
9175.69 3
5.4%
6244.98 1
 
1.8%
6154.0 1
 
1.8%
5816.0 1
 
1.8%
5289.26 1
 
1.8%
5144.39 1
 
1.8%

냉동_냉장창고_동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
0
51 
1
 
4
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 51
91.1%
1 4
 
7.1%
2 1
 
1.8%

Length

2024-04-29T21:46:04.966589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:05.046890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 51
91.1%
1 4
 
7.1%
2 1
 
1.8%

냉동_냉장창고_면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
0.0
51 
1203.0
 
2
6634.0
 
1
1872.0
 
1
1462.2
 
1

Length

Max length6
Median length3
Mean length3.2678571
Min length3

Unique

Unique3 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 51
91.1%
1203.0 2
 
3.6%
6634.0 1
 
1.8%
1872.0 1
 
1.8%
1462.2 1
 
1.8%

Length

2024-04-29T21:46:05.141988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:05.233923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 51
91.1%
1203.0 2
 
3.6%
6634.0 1
 
1.8%
1872.0 1
 
1.8%
1462.2 1
 
1.8%

보관장소_면적
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1423.4393
Minimum0
Maximum17880
Zeros49
Zeros (%)87.5%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:05.318256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10853
Maximum17880
Range17880
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4368.5771
Coefficient of variation (CV)3.0690295
Kurtosis9.2398469
Mean1423.4393
Median Absolute Deviation (MAD)0
Skewness3.1764478
Sum79712.6
Variance19084466
MonotonicityNot monotonic
2024-04-29T21:46:05.410160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 49
87.5%
17880.0 2
 
3.6%
8405.0 1
 
1.8%
8205.0 1
 
1.8%
1122.6 1
 
1.8%
8596.0 1
 
1.8%
17624.0 1
 
1.8%
ValueCountFrequency (%)
0.0 49
87.5%
1122.6 1
 
1.8%
8205.0 1
 
1.8%
8405.0 1
 
1.8%
8596.0 1
 
1.8%
17624.0 1
 
1.8%
17880.0 2
 
3.6%
ValueCountFrequency (%)
17880.0 2
 
3.6%
17624.0 1
 
1.8%
8596.0 1
 
1.8%
8405.0 1
 
1.8%
8205.0 1
 
1.8%
1122.6 1
 
1.8%
0.0 49
87.5%

직원수
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)47.7%
Missing12
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean32.045455
Minimum1
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:05.525548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8.5
Q332.5
95-th percentile125.25
Maximum400
Range399
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation67.026185
Coefficient of variation (CV)2.0915973
Kurtosis21.817864
Mean32.045455
Median Absolute Deviation (MAD)7
Skewness4.3309202
Sum1410
Variance4492.5095
MonotonicityNot monotonic
2024-04-29T21:46:05.654335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 7
12.5%
5 4
 
7.1%
8 4
 
7.1%
10 3
 
5.4%
50 3
 
5.4%
13 3
 
5.4%
2 3
 
5.4%
40 2
 
3.6%
7 2
 
3.6%
4 2
 
3.6%
Other values (11) 11
19.6%
(Missing) 12
21.4%
ValueCountFrequency (%)
1 7
12.5%
2 3
5.4%
4 2
 
3.6%
5 4
7.1%
7 2
 
3.6%
8 4
7.1%
9 1
 
1.8%
10 3
5.4%
13 3
5.4%
18 1
 
1.8%
ValueCountFrequency (%)
400 1
 
1.8%
177 1
 
1.8%
132 1
 
1.8%
87 1
 
1.8%
63 1
 
1.8%
60 1
 
1.8%
50 3
5.4%
40 2
3.6%
30 1
 
1.8%
25 1
 
1.8%

시설/장비현황
Text

MISSING 

Distinct38
Distinct (%)88.4%
Missing13
Missing (%)23.2%
Memory size580.0 B
2024-04-29T21:46:05.838820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length17
Mean length12
Min length3

Characters and Unicode

Total characters516
Distinct characters113
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

Unique33 ?
Unique (%)76.7%

Sample

1st row컨베이어벨트, 지게차 등
2nd row지게차, 철재파랫트
3rd row랙, 지게차
4th row컨베어, 지게차
5th rowE/L, 컨베어
ValueCountFrequency (%)
지게차 28
24.6%
등 11
 
9.6%
2대 5
 
4.4%
컨베이어 4
 
3.5%
랙(rack)설치 4
 
3.5%
5대 3
 
2.6%
자동c/v설비 2
 
1.8%
컨베어 2
 
1.8%
랙 2
 
1.8%
1대 2
 
1.8%
Other values (48) 51
44.7%
2024-04-29T21:46:06.187234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
 
13.8%
, 41
 
7.9%
차 33
 
6.4%
게 31
 
6.0%
지 31
 
6.0%
대 16
 
3.1%
트 12
 
2.3%
설 11
 
2.1%
등 11
 
2.1%
베 10
 
1.9%
Other values (103) 249
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
65.3%
Space Separator 71
 
13.8%
Other Punctuation 46
 
8.9%
Decimal Number 22
 
4.3%
Uppercase Letter 16
 
3.1%
Lowercase Letter 12
 
2.3%
Close Punctuation 6
 
1.2%
Open Punctuation 6
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 33
 
9.8%
게 31
 
9.2%
지 31
 
9.2%
대 16
 
4.7%
트 12
 
3.6%
설 11
 
3.3%
등 11
 
3.3%
베 10
 
3.0%
이 10
 
3.0%
어 10
 
3.0%
Other values (77) 162
48.1%
Uppercase Letter
ValueCountFrequency (%)
C 4
25.0%
V 3
18.8%
A 2
12.5%
M 1
 
6.2%
K 1
 
6.2%
R 1
 
6.2%
E 1
 
6.2%
L 1
 
6.2%
P 1
 
6.2%
D 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 7
31.8%
1 4
18.2%
5 3
13.6%
0 3
13.6%
6 2
 
9.1%
8 2
 
9.1%
4 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
k 3
25.0%
c 3
25.0%
a 3
25.0%
r 3
25.0%
Other Punctuation
ValueCountFrequency (%)
, 41
89.1%
/ 5
 
10.9%
Space Separator
ValueCountFrequency (%)
71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
65.3%
Common 151
29.3%
Latin 28
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 33
 
9.8%
게 31
 
9.2%
지 31
 
9.2%
대 16
 
4.7%
트 12
 
3.6%
설 11
 
3.3%
등 11
 
3.3%
베 10
 
3.0%
이 10
 
3.0%
어 10
 
3.0%
Other values (77) 162
48.1%
Latin
ValueCountFrequency (%)
C 4
14.3%
k 3
10.7%
V 3
10.7%
c 3
10.7%
a 3
10.7%
r 3
10.7%
A 2
7.1%
M 1
 
3.6%
K 1
 
3.6%
R 1
 
3.6%
Other values (4) 4
14.3%
Common
ValueCountFrequency (%)
71
47.0%
, 41
27.2%
2 7
 
4.6%
) 6
 
4.0%
( 6
 
4.0%
/ 5
 
3.3%
1 4
 
2.6%
5 3
 
2.0%
0 3
 
2.0%
6 2
 
1.3%
Other values (2) 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
65.3%
ASCII 179
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
39.7%
, 41
22.9%
2 7
 
3.9%
) 6
 
3.4%
( 6
 
3.4%
/ 5
 
2.8%
1 4
 
2.2%
C 4
 
2.2%
5 3
 
1.7%
k 3
 
1.7%
Other values (16) 29
16.2%
Hangul
ValueCountFrequency (%)
차 33
 
9.8%
게 31
 
9.2%
지 31
 
9.2%
대 16
 
4.7%
트 12
 
3.6%
설 11
 
3.3%
등 11
 
3.3%
베 10
 
3.0%
이 10
 
3.0%
어 10
 
3.0%
Other values (77) 162
48.1%

보관요율
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)65.0%
Missing36
Missing (%)64.3%
Infinite0
Infinite (%)0.0%
Mean5257.95
Minimum0
Maximum15130
Zeros2
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-29T21:46:06.293076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1997.5
median5000
Q39110
95-th percentile10256.5
Maximum15130
Range15130
Interquartile range (IQR)8112.5

Descriptive statistics

Standard deviation4455.9196
Coefficient of variation (CV)0.8474633
Kurtosis-0.64706233
Mean5257.95
Median Absolute Deviation (MAD)4140
Skewness0.42183395
Sum105159
Variance19855220
MonotonicityNot monotonic
2024-04-29T21:46:06.394890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5000 4
 
7.1%
10000 3
 
5.4%
0 2
 
3.6%
9080 2
 
3.6%
20 1
 
1.8%
2200 1
 
1.8%
3030 1
 
1.8%
6000 1
 
1.8%
15130 1
 
1.8%
29 1
 
1.8%
Other values (3) 3
 
5.4%
(Missing) 36
64.3%
ValueCountFrequency (%)
0 2
3.6%
20 1
 
1.8%
29 1
 
1.8%
90 1
 
1.8%
1300 1
 
1.8%
2200 1
 
1.8%
3030 1
 
1.8%
5000 4
7.1%
6000 1
 
1.8%
9080 2
3.6%
ValueCountFrequency (%)
15130 1
 
1.8%
10000 3
5.4%
9200 1
 
1.8%
9080 2
3.6%
6000 1
 
1.8%
5000 4
7.1%
3030 1
 
1.8%
2200 1
 
1.8%
1300 1
 
1.8%
90 1
 
1.8%

법인여부명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
법인
50 
개인
6 

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 50
89.3%
개인 6
 
10.7%

Length

2024-04-29T21:46:06.508841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:06.589751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 50
89.3%
개인 6
 
10.7%

업태_보관및창고업
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
40 
<NA>
16 

Length

Max length4
Median length1
Mean length1.8571429
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 40
71.4%
<NA> 16
 
28.6%

Length

2024-04-29T21:46:06.683310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:06.765672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
71.4%
na 16
 
28.6%

업태_운송및택배업
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
37 
1
19 

Length

Max length4
Median length4
Mean length2.9821429
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 37
66.1%
1 19
33.9%

Length

2024-04-29T21:46:07.085088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:07.178941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
66.1%
1 19
33.9%

업태_판매업
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
48 
1
8 

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 48
85.7%
1 8
 
14.3%

Length

2024-04-29T21:46:07.284536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:07.375576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 48
85.7%
1 8
 
14.3%

업태_제조업
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
52 
1
 
4

Length

Max length4
Median length4
Mean length3.7857143
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> 52
92.9%
1 4
 
7.1%

Length

2024-04-29T21:46:07.478818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:46:07.574819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
92.9%
1 4
 
7.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동_냉장창고_동수냉동_냉장창고_면적보관장소_면적직원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
01물류창고업체11_45_02_P342000020153420150325258002015-02-02<NA>1영업/정상1영업중<NA><NA><NA><NA>053-351-0777<NA><NA>대구광역시 동구 봉무동 1547대구광역시 동구 팔공로53길 96 (봉무동)41024롯데글로벌로지스(주)2022-12-13 16:41:13U2022-12-15 02:40:00<NA>347437.684056270160.85946514380.000.00.040컨베이어벨트, 지게차 등0법인1<NA><NA><NA>
12물류창고업체11_45_02_P342000020133420098325000042013-03-11<NA>1영업/정상1영업중<NA><NA><NA><NA>053-963-8942<NA>701-320대구광역시 동구 괴전동 258번지대구광역시 동구 안심로102길 9 (괴전동)701-320한국농수산식품유통공사2022-03-07 15:08:37U2022-03-09 02:40:00<NA><NA><NA>00.026634.00.02지게차, 철재파랫트<NA>법인111<NA>
23물류창고업체11_45_02_P342000020133420098325000032013-03-11<NA>1영업/정상1영업중<NA><NA><NA><NA>053-965-2620<NA>701-170대구광역시 동구 봉무동 1566번지대구광역시 동구 팔공로45길 11 (봉무동)701-170(주)코리아대동2022-03-04 11:37:15U2022-03-06 02:40:00<NA>347905.252913269901.79496411909.000.00.025랙, 지게차<NA>법인11<NA>1
34물류창고업체11_45_02_P342000020133420098325000022013-03-11<NA>1영업/정상1영업중<NA><NA><NA><NA>053-381-3355<NA><NA>대구광역시 동구 율암동 1151대구광역시 동구 혁신대로 85 (율암동)41065롯데글로벌로지스(주)2023-03-28 17:47:23U2023-03-30 02:40:00<NA>354177.193716265815.732945211567.7800.00.060컨베어, 지게차5000법인11<NA><NA>
45물류창고업체11_45_02_P342000020133420098325000012013-03-11<NA>1영업/정상1영업중<NA><NA><NA><NA>053-211-3855<NA>701-835대구광역시 동구 용계동 854번지대구광역시 동구 금호강변로 57 (용계동)701-835씨제이대한통운(주)2022-04-18 13:05:14U2022-04-20 02:40:00<NA>352124.562037264490.74415924984.9800.00.010E/L, 컨베어5000법인11<NA><NA>
56물류창고업체11_45_02_P342000020233420180325000012023-02-21<NA>1영업/정상1영업중<NA><NA><NA><NA>070-4789-2000<NA><NA>대구광역시 동구 율암동 1151대구광역시 동구 혁신대로 85 (율암동)41065아이씨로지스2023-03-17 14:14:59U2023-03-19 02:40:00<NA>354177.193716265815.73294512790.0800.00.05조립식 앵글 20대, 지게차 2대, 이동식 보관함 80대 등20개인1<NA><NA><NA>
67물류창고업체11_45_02_P342000020203420180325000012020-09-09<NA>1영업/정상1영업중<NA><NA><NA><NA>054-979-2202<NA><NA>대구광역시 동구 봉무동 1563-2대구광역시 동구 팔공로53길 114 (봉무동)41028(주)대원지에스아이2021-06-28 14:10:41U2021-06-30 02:40:00<NA>347444.554528269994.19165524865.7800.00.010컨베이어벨트, 지게차 등<NA>법인1<NA><NA><NA>
78물류창고업체11_45_02_P343000020133430053325000012013-03-11<NA>3폐업3폐업2020-01-14<NA><NA><NA>053 5620365<NA>703-833대구광역시 서구 중리동 1166번지대구광역시 서구 평리로21길 8 (중리동)703-833대상주식회사2020-01-14 13:26:28U2020-01-16 02:40:00<NA>338652.490962263268.85247213012.6800.00.04랙(rack)설치, 지게차 등10000법인1<NA><NA><NA>
89물류창고업체11_45_02_P343000020123430053325000082013-03-11<NA>3폐업3폐업2018-06-29<NA><NA><NA>053 5670238<NA>703-830대구광역시 서구 이현동 48번지 109호대구광역시 서구 와룡로90길 61 (이현동)703-830한국농수산식품유통공사2018-08-08 14:32:07I2018-08-31 23:59:59<NA><NA><NA>25289.2600.00.02지게차, 컨베이어, 목재파렛트, 차량계근장<NA>법인1<NA><NA><NA>
910물류창고업체11_45_02_P343000020123430053325000072013-03-11<NA>3폐업3폐업2018-06-29<NA><NA><NA>053 593 5524<NA>703-830대구광역시 서구 이현동 45번지 6호대구광역시 서구 국채보상로 5 (이현동)703-830(주)한진2018-08-08 14:32:44I2018-08-31 23:59:59<NA>338320.441561264380.8235611183.000.00.01물류기기(자동C/V)2200법인1<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)일반창고_동수일반창고_면적냉동_냉장창고_동수냉동_냉장창고_면적보관장소_면적직원수시설/장비현황보관요율법인여부명업태_보관및창고업업태_운송및택배업업태_판매업업태_제조업
4647물류창고업체11_45_02_P348000020133480313325000042013-02-27<NA>3폐업3폐업2022-10-05<NA><NA><NA>053-757-9036<NA>711-823대구광역시 달성군 하빈면 하산리 1105번지 1호대구광역시 달성군 하빈면 달구벌대로8길 22<NA>주식회사 투에버 (TOEVER)2022-10-05 17:57:02U2022-10-07 02:40:00<NA>326400.337854264928.22081111416.500.00.0<NA><NA><NA>법인<NA><NA><NA><NA>
4748물류창고업체11_45_02_P348000020133480313325000052013-02-27<NA>3폐업3폐업2019-06-14<NA><NA><NA>0542306009<NA>711-891대구광역시 달성군 구지면 예현리 760번지 3호대구광역시 달성군 구지면 달성2차4로 75<NA>세방(주)2019-07-15 14:24:15U2019-07-17 02:40:00<NA>328896.087037238535.27661815816.000.017624.040트럭, 지게차1300법인1111
4849물류창고업체11_45_02_P348000020163480313325000012016-08-30<NA>3폐업3폐업2023-12-27<NA><NA><NA>055-714-1980<NA><NA>대구광역시 달성군 하빈면 봉촌리 768번지 30호대구광역시 달성군 하빈면 하빈남로 44842905한국로지스풀(주)2023-12-27 15:26:02U2023-12-29 02:40:00<NA>325882.665956263771.24527112631.0900.00.01지게차(1대)<NA>법인1<NA><NA><NA>
4950물류창고업체11_45_02_P514100020215140107325000022021-11-01<NA>3폐업3폐업2021-11-01<NA><NA><NA>054-383-8420<NA><NA>대구광역시 군위군 효령면 고곡리 438 농산물물류센타대구광역시 군위군 효령면 경북대로 2185, 농산물물류센타39037(주)농협하나로유통 경북지사2021-11-01 15:23:54I2023-07-01 16:42:10<NA>341575.713236292024.59073419175.6900.00.0<NA><NA><NA>법인<NA><NA><NA><NA>
5051물류창고업체11_45_02_P514100020125140085325000022012-08-03<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 군위군 효령면 고곡리 120번지대구광역시 군위군 효령면 하평길 11539037세계로 물류2021-03-17 13:26:01I2023-07-01 16:42:10<NA>342212.942915290695.80321412294.7600.00.01지게차 2대, 정렬기 2대90개인11<NA><NA>
5152물류창고업체11_45_02_P514100020135140066325000022013-06-05<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 군위군 우보면 이화리 697-1대구광역시 군위군 우보면 동부로 152139045우보대창창고2022-12-19 13:00:00I2023-07-01 16:42:10<NA>350300.849246299931.0894242038.1500.00.02농산물 집하창고<NA>개인1<NA><NA><NA>
5253물류창고업체11_45_02_P514100020215140107325000012021-11-01<NA>1영업/정상1영업중<NA><NA><NA><NA>054-383-8420<NA><NA>대구광역시 군위군 효령면 고곡리 438 농산물물류센타대구광역시 군위군 효령면 경북대로 2185, 농산물물류센타39037농협경제지주 주식회사 마트사업경북지사2023-08-25 14:12:34U2023-08-27 02:40:00<NA>341575.713236292024.59073419175.6900.00.013<NA><NA>법인1<NA><NA><NA>
5354물류창고업체11_45_02_P514100020135140066325000012013-03-25<NA>3폐업3폐업<NA><NA><NA><NA>054 380 0620<NA><NA><NA>대구광역시 군위군 효령면 경북대로 2185 (농산물물류센타)39037(주)농협물류2020-08-05 13:50:07I2023-07-01 16:42:10<NA>341575.713236292024.59073412450.000.00.013일반창고<NA>법인1<NA><NA><NA>
5455물류창고업체11_45_02_P514100020205140085325000012020-11-05<NA>3폐업3폐업<NA><NA><NA><NA>054-383-8420<NA><NA>대구광역시 군위군 효령면 고곡리 438 농산물물류센타대구광역시 군위군 효령면 경북대로 2185, 농산물물류센타39037(주)농협하나로유통 경북지사2020-11-10 16:47:46I2023-07-01 16:42:10<NA>341575.713236292024.59073419175.6900.00.013창고시설<NA>법인1<NA><NA><NA>
5556물류창고업체11_45_02_P514100020205140085325000022017-02-06<NA>3폐업3폐업2020-11-05<NA><NA><NA>054-380-0620<NA><NA><NA>대구광역시 군위군 효령면 경북대로 2185 (농산물물류센타)39037(주)농협물류2022-03-14 11:55:22I2023-07-01 16:42:10<NA>341575.713236292024.59073412450.000.00.0<NA><NA><NA>법인<NA><NA><NA><NA>