Overview

Dataset statistics

Number of variables47
Number of observations894
Missing cells10526
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory354.6 KiB
Average record size in memory406.1 B

Variable types

Numeric11
Categorical18
Text6
Unsupported10
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_17_P_유통전문판매업_11월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000078048&dataSetDetailId=DDI_0000078094&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (98.7%)Imbalance
여성종사자수 is highly imbalanced (98.7%)Imbalance
본사종업원수 is highly imbalanced (60.5%)Imbalance
공장생산직종업원수 is highly imbalanced (53.4%)Imbalance
보증액 is highly imbalanced (95.0%)Imbalance
월세액 is highly imbalanced (95.0%)Imbalance
인허가취소일자 has 894 (100.0%) missing valuesMissing
폐업일자 has 378 (42.3%) missing valuesMissing
휴업시작일자 has 894 (100.0%) missing valuesMissing
휴업종료일자 has 894 (100.0%) missing valuesMissing
재개업일자 has 894 (100.0%) missing valuesMissing
소재지전화 has 281 (31.4%) missing valuesMissing
소재지면적 has 119 (13.3%) missing valuesMissing
소재지우편번호 has 10 (1.1%) missing valuesMissing
도로명전체주소 has 231 (25.8%) missing valuesMissing
도로명우편번호 has 234 (26.2%) missing valuesMissing
좌표정보(X) has 17 (1.9%) missing valuesMissing
좌표정보(Y) has 17 (1.9%) missing valuesMissing
영업장주변구분명 has 894 (100.0%) missing valuesMissing
등급구분명 has 894 (100.0%) missing valuesMissing
총종업원수 has 894 (100.0%) missing valuesMissing
공장판매직종업원수 has 298 (33.3%) missing valuesMissing
전통업소지정번호 has 894 (100.0%) missing valuesMissing
전통업소주된음식 has 894 (100.0%) missing valuesMissing
홈페이지 has 894 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장판매직종업원수 has 555 (62.1%) zerosZeros
시설총규모 has 827 (92.5%) zerosZeros

Reproduction

Analysis started2023-12-10 18:43:50.577539
Analysis finished2023-12-10 18:43:52.259584
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct894
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447.5
Minimum1
Maximum894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:43:52.409424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.65
Q1224.25
median447.5
Q3670.75
95-th percentile849.35
Maximum894
Range893
Interquartile range (IQR)446.5

Descriptive statistics

Standard deviation258.21987
Coefficient of variation (CV)0.57702764
Kurtosis-1.2
Mean447.5
Median Absolute Deviation (MAD)223.5
Skewness0
Sum400065
Variance66677.5
MonotonicityStrictly increasing
2023-12-11T03:43:52.962284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
602 1
 
0.1%
591 1
 
0.1%
592 1
 
0.1%
593 1
 
0.1%
594 1
 
0.1%
595 1
 
0.1%
596 1
 
0.1%
597 1
 
0.1%
598 1
 
0.1%
Other values (884) 884
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
894 1
0.1%
893 1
0.1%
892 1
0.1%
891 1
0.1%
890 1
0.1%
889 1
0.1%
888 1
0.1%
887 1
0.1%
886 1
0.1%
885 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
유통전문판매업
894 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 894
100.0%

Length

2023-12-11T03:43:53.175052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:53.318122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 894
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
07_22_17_P
894 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_17_P
2nd row07_22_17_P
3rd row07_22_17_P
4th row07_22_17_P
5th row07_22_17_P

Common Values

ValueCountFrequency (%)
07_22_17_P 894
100.0%

Length

2023-12-11T03:43:53.460932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:53.621186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 894
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447438.5
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:43:53.778449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33460000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation21011.225
Coefficient of variation (CV)0.0060947353
Kurtosis-1.0505358
Mean3447438.5
Median Absolute Deviation (MAD)20000
Skewness-0.25608054
Sum3.08201 × 109
Variance4.4147157 × 108
MonotonicityIncreasing
2023-12-11T03:43:53.966180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 193
21.6%
3460000 157
17.6%
3420000 133
14.9%
3470000 126
14.1%
3480000 80
8.9%
3430000 76
 
8.5%
3410000 66
 
7.4%
3440000 63
 
7.0%
ValueCountFrequency (%)
3410000 66
 
7.4%
3420000 133
14.9%
3430000 76
 
8.5%
3440000 63
 
7.0%
3450000 193
21.6%
3460000 157
17.6%
3470000 126
14.1%
3480000 80
8.9%
ValueCountFrequency (%)
3480000 80
8.9%
3470000 126
14.1%
3460000 157
17.6%
3450000 193
21.6%
3440000 63
 
7.0%
3430000 76
 
8.5%
3420000 133
14.9%
3410000 66
 
7.4%

관리번호
Text

UNIQUE 

Distinct894
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-11T03:43:54.315887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters19668
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

Unique894 ?
Unique (%)100.0%

Sample

1st row3410000-113-2019-00002
2nd row3410000-113-2018-00006
3rd row3410000-113-2016-00002
4th row3410000-113-2016-00003
5th row3410000-113-2011-00002
ValueCountFrequency (%)
3410000-113-2019-00002 1
 
0.1%
3460000-113-2019-00007 1
 
0.1%
3460000-113-2016-00010 1
 
0.1%
3460000-113-2017-00009 1
 
0.1%
3460000-113-2017-00010 1
 
0.1%
3460000-113-2017-00011 1
 
0.1%
3460000-113-2003-00004 1
 
0.1%
3460000-113-2019-00010 1
 
0.1%
3460000-113-2019-00012 1
 
0.1%
3460000-113-2019-00011 1
 
0.1%
Other values (884) 884
98.9%
2023-12-11T03:43:54.947090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8262
42.0%
1 2811
 
14.3%
- 2682
 
13.6%
3 2058
 
10.5%
2 1225
 
6.2%
4 1151
 
5.9%
5 408
 
2.1%
6 330
 
1.7%
7 260
 
1.3%
9 248
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16986
86.4%
Dash Punctuation 2682
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8262
48.6%
1 2811
 
16.5%
3 2058
 
12.1%
2 1225
 
7.2%
4 1151
 
6.8%
5 408
 
2.4%
6 330
 
1.9%
7 260
 
1.5%
9 248
 
1.5%
8 233
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19668
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8262
42.0%
1 2811
 
14.3%
- 2682
 
13.6%
3 2058
 
10.5%
2 1225
 
6.2%
4 1151
 
5.9%
5 408
 
2.1%
6 330
 
1.7%
7 260
 
1.3%
9 248
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8262
42.0%
1 2811
 
14.3%
- 2682
 
13.6%
3 2058
 
10.5%
2 1225
 
6.2%
4 1151
 
5.9%
5 408
 
2.1%
6 330
 
1.7%
7 260
 
1.3%
9 248
 
1.3%

인허가일자
Real number (ℝ)

Distinct768
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20113591
Minimum19950510
Maximum20191119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:43:55.400695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20000804
Q120061212
median20130970
Q320161010
95-th percentile20190425
Maximum20191119
Range240609
Interquartile range (IQR)99797

Descriptive statistics

Standard deviation61138.621
Coefficient of variation (CV)0.0030396671
Kurtosis-0.75567642
Mean20113591
Median Absolute Deviation (MAD)40255
Skewness-0.61961933
Sum1.798155 × 1010
Variance3.737931 × 109
MonotonicityNot monotonic
2023-12-11T03:43:55.688879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121105 4
 
0.4%
20180508 4
 
0.4%
20160127 3
 
0.3%
20190613 3
 
0.3%
20150819 3
 
0.3%
20130610 3
 
0.3%
20080826 3
 
0.3%
20121016 3
 
0.3%
19990223 3
 
0.3%
20140508 3
 
0.3%
Other values (758) 862
96.4%
ValueCountFrequency (%)
19950510 1
0.1%
19950904 1
0.1%
19961210 1
0.1%
19961218 1
0.1%
19970201 1
0.1%
19970318 1
0.1%
19970627 1
0.1%
19971009 1
0.1%
19971015 1
0.1%
19971209 1
0.1%
ValueCountFrequency (%)
20191119 1
0.1%
20191118 1
0.1%
20191107 1
0.1%
20191031 1
0.1%
20191029 1
0.1%
20191025 1
0.1%
20191022 1
0.1%
20191016 1
0.1%
20191011 2
0.2%
20191010 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3
516 
1
378 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 516
57.7%
1 378
42.3%

Length

2023-12-11T03:43:55.916242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:56.085918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 516
57.7%
1 378
42.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
516 
영업/정상
378 

Length

Max length5
Median length2
Mean length3.2684564
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 516
57.7%
영업/정상 378
42.3%

Length

2023-12-11T03:43:56.280969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:56.463376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 516
57.7%
영업/정상 378
42.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2
516 
1
378 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 516
57.7%
1 378
42.3%

Length

2023-12-11T03:43:56.614202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:56.791246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 516
57.7%
1 378
42.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
폐업
516 
영업
378 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 516
57.7%
영업 378
42.3%

Length

2023-12-11T03:43:56.995654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:43:57.276083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 516
57.7%
영업 378
42.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct466
Distinct (%)90.3%
Missing378
Missing (%)42.3%
Infinite0
Infinite (%)0.0%
Mean20121093
Minimum20001029
Maximum20191128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:43:57.579832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040128
Q120070286
median20131211
Q320170330
95-th percentile20190404
Maximum20191128
Range190099
Interquartile range (IQR)100043.5

Descriptive statistics

Standard deviation53342.679
Coefficient of variation (CV)0.0026510826
Kurtosis-1.3057082
Mean20121093
Median Absolute Deviation (MAD)49056
Skewness-0.30598524
Sum1.0382484 × 1010
Variance2.8454414 × 109
MonotonicityNot monotonic
2023-12-11T03:43:57.883802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.6%
20070116 4
 
0.4%
20191111 3
 
0.3%
20161229 3
 
0.3%
20151229 3
 
0.3%
20021224 3
 
0.3%
20051128 3
 
0.3%
20040830 3
 
0.3%
20161116 2
 
0.2%
20190117 2
 
0.2%
Other values (456) 485
54.3%
(Missing) 378
42.3%
ValueCountFrequency (%)
20001029 1
 
0.1%
20020507 1
 
0.1%
20020722 1
 
0.1%
20020808 1
 
0.1%
20020827 1
 
0.1%
20021023 1
 
0.1%
20021205 1
 
0.1%
20021223 1
 
0.1%
20021224 3
0.3%
20021227 1
 
0.1%
ValueCountFrequency (%)
20191128 2
0.2%
20191121 1
 
0.1%
20191119 1
 
0.1%
20191111 3
0.3%
20191024 1
 
0.1%
20191021 1
 
0.1%
20190906 1
 
0.1%
20190904 2
0.2%
20190820 1
 
0.1%
20190814 1
 
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

소재지전화
Text

MISSING 

Distinct577
Distinct (%)94.1%
Missing281
Missing (%)31.4%
Memory size7.1 KiB
2023-12-11T03:43:58.395915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.892333
Min length7

Characters and Unicode

Total characters6677
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

Unique543 ?
Unique (%)88.6%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 432
32.3%
070 32
 
2.4%
311 9
 
0.7%
313 8
 
0.6%
755 6
 
0.4%
746 6
 
0.4%
625 4
 
0.3%
742 4
 
0.3%
584 4
 
0.3%
15442750 4
 
0.3%
Other values (709) 829
62.0%
2023-12-11T03:43:59.150872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1018
15.2%
0 953
14.3%
3 897
13.4%
731
10.9%
1 503
7.5%
2 496
7.4%
7 482
7.2%
6 429
6.4%
8 421
6.3%
4 414
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5946
89.1%
Space Separator 731
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1018
17.1%
0 953
16.0%
3 897
15.1%
1 503
8.5%
2 496
8.3%
7 482
8.1%
6 429
7.2%
8 421
7.1%
4 414
7.0%
9 333
 
5.6%
Space Separator
ValueCountFrequency (%)
731
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1018
15.2%
0 953
14.3%
3 897
13.4%
731
10.9%
1 503
7.5%
2 496
7.4%
7 482
7.2%
6 429
6.4%
8 421
6.3%
4 414
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1018
15.2%
0 953
14.3%
3 897
13.4%
731
10.9%
1 503
7.5%
2 496
7.4%
7 482
7.2%
6 429
6.4%
8 421
6.3%
4 414
6.2%

소재지면적
Text

MISSING 

Distinct560
Distinct (%)72.3%
Missing119
Missing (%)13.3%
Memory size7.1 KiB
2023-12-11T03:43:59.808467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0774194
Min length3

Characters and Unicode

Total characters3935
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)61.5%

Sample

1st row.00
2nd row182.00
3rd row5.70
4th row29.70
5th row71.69
ValueCountFrequency (%)
33.00 24
 
3.1%
00 20
 
2.6%
30.00 13
 
1.7%
3.30 9
 
1.2%
66.00 9
 
1.2%
16.50 9
 
1.2%
25.00 8
 
1.0%
50.00 7
 
0.9%
16.00 6
 
0.8%
10.00 6
 
0.8%
Other values (550) 664
85.7%
2023-12-11T03:44:00.626932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 866
22.0%
. 775
19.7%
1 364
9.3%
2 333
 
8.5%
3 298
 
7.6%
5 273
 
6.9%
4 242
 
6.1%
6 232
 
5.9%
9 186
 
4.7%
8 184
 
4.7%
Other values (2) 182
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3157
80.2%
Other Punctuation 778
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 866
27.4%
1 364
11.5%
2 333
 
10.5%
3 298
 
9.4%
5 273
 
8.6%
4 242
 
7.7%
6 232
 
7.3%
9 186
 
5.9%
8 184
 
5.8%
7 179
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 775
99.6%
, 3
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3935
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 866
22.0%
. 775
19.7%
1 364
9.3%
2 333
 
8.5%
3 298
 
7.6%
5 273
 
6.9%
4 242
 
6.1%
6 232
 
5.9%
9 186
 
4.7%
8 184
 
4.7%
Other values (2) 182
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3935
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 866
22.0%
. 775
19.7%
1 364
9.3%
2 333
 
8.5%
3 298
 
7.6%
5 273
 
6.9%
4 242
 
6.1%
6 232
 
5.9%
9 186
 
4.7%
8 184
 
4.7%
Other values (2) 182
 
4.6%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct356
Distinct (%)40.3%
Missing10
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean704451.8
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:00.854347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700809
Q1702252.5
median703830
Q3706170
95-th percentile711832.85
Maximum711892
Range11882
Interquartile range (IQR)3917.5

Descriptive statistics

Standard deviation2916.501
Coefficient of variation (CV)0.0041401002
Kurtosis0.80587356
Mean704451.8
Median Absolute Deviation (MAD)1977.5
Skewness1.0412968
Sum6.2273539 × 108
Variance8505978.3
MonotonicityNot monotonic
2023-12-11T03:44:01.079719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 18
 
2.0%
703100 10
 
1.1%
703830 10
 
1.1%
706818 9
 
1.0%
700230 9
 
1.0%
706803 8
 
0.9%
706220 8
 
0.9%
701824 7
 
0.8%
706809 7
 
0.8%
711814 7
 
0.8%
Other values (346) 791
88.5%
(Missing) 10
 
1.1%
ValueCountFrequency (%)
700010 2
 
0.2%
700070 1
 
0.1%
700092 2
 
0.2%
700111 1
 
0.1%
700150 2
 
0.2%
700230 9
1.0%
700240 2
 
0.2%
700251 1
 
0.1%
700300 2
 
0.2%
700320 1
 
0.1%
ValueCountFrequency (%)
711892 1
 
0.1%
711891 3
0.3%
711874 1
 
0.1%
711863 3
0.3%
711858 3
0.3%
711856 1
 
0.1%
711855 4
0.4%
711852 3
0.3%
711851 6
0.7%
711845 5
0.6%

소재지전체주소
Text

Distinct855
Distinct (%)95.7%
Missing1
Missing (%)0.1%
Memory size7.1 KiB
2023-12-11T03:44:01.588403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length24.454647
Min length18

Characters and Unicode

Total characters21838
Distinct characters244
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

Unique822 ?
Unique (%)92.0%

Sample

1st row대구광역시 중구 삼덕동1가 0027-0003번지 지상1층
2nd row대구광역시 중구 대봉동 0043-0021번지 지상 3층
3rd row대구광역시 중구 남성로 0020-0005번지 지상1층
4th row대구광역시 중구 봉산동 0127-0001번지 메트로프라자 D212
5th row대구광역시 중구 동인동1가 0204-0002번지 지상2층
ValueCountFrequency (%)
대구광역시 893
22.2%
북구 193
 
4.8%
수성구 156
 
3.9%
동구 133
 
3.3%
달서구 126
 
3.1%
달성군 80
 
2.0%
서구 76
 
1.9%
중구 66
 
1.6%
남구 63
 
1.6%
대명동 49
 
1.2%
Other values (1157) 2187
54.4%
2023-12-11T03:44:02.323320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4005
18.3%
구 1739
 
8.0%
지 1054
 
4.8%
1 1047
 
4.8%
대 998
 
4.6%
동 979
 
4.5%
시 905
 
4.1%
번 895
 
4.1%
광 893
 
4.1%
역 893
 
4.1%
Other values (234) 8430
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12342
56.5%
Decimal Number 4561
 
20.9%
Space Separator 4005
 
18.3%
Dash Punctuation 747
 
3.4%
Close Punctuation 73
 
0.3%
Open Punctuation 73
 
0.3%
Uppercase Letter 22
 
0.1%
Other Punctuation 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1739
14.1%
지 1054
 
8.5%
대 998
 
8.1%
동 979
 
7.9%
시 905
 
7.3%
번 895
 
7.3%
광 893
 
7.2%
역 893
 
7.2%
성 301
 
2.4%
서 230
 
1.9%
Other values (208) 3455
28.0%
Decimal Number
ValueCountFrequency (%)
1 1047
23.0%
2 598
13.1%
0 583
12.8%
3 444
9.7%
5 358
 
7.8%
4 351
 
7.7%
6 317
 
7.0%
8 311
 
6.8%
7 287
 
6.3%
9 265
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
27.3%
T 3
13.6%
A 3
13.6%
C 2
 
9.1%
J 2
 
9.1%
D 2
 
9.1%
P 2
 
9.1%
F 1
 
4.5%
N 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 12
80.0%
/ 2
 
13.3%
. 1
 
6.7%
Space Separator
ValueCountFrequency (%)
4005
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 747
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12342
56.5%
Common 9474
43.4%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1739
14.1%
지 1054
 
8.5%
대 998
 
8.1%
동 979
 
7.9%
시 905
 
7.3%
번 895
 
7.3%
광 893
 
7.2%
역 893
 
7.2%
성 301
 
2.4%
서 230
 
1.9%
Other values (208) 3455
28.0%
Common
ValueCountFrequency (%)
4005
42.3%
1 1047
 
11.1%
- 747
 
7.9%
2 598
 
6.3%
0 583
 
6.2%
3 444
 
4.7%
5 358
 
3.8%
4 351
 
3.7%
6 317
 
3.3%
8 311
 
3.3%
Other values (7) 713
 
7.5%
Latin
ValueCountFrequency (%)
B 6
27.3%
T 3
13.6%
A 3
13.6%
C 2
 
9.1%
J 2
 
9.1%
D 2
 
9.1%
P 2
 
9.1%
F 1
 
4.5%
N 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12342
56.5%
ASCII 9496
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4005
42.2%
1 1047
 
11.0%
- 747
 
7.9%
2 598
 
6.3%
0 583
 
6.1%
3 444
 
4.7%
5 358
 
3.8%
4 351
 
3.7%
6 317
 
3.3%
8 311
 
3.3%
Other values (16) 735
 
7.7%
Hangul
ValueCountFrequency (%)
구 1739
14.1%
지 1054
 
8.5%
대 998
 
8.1%
동 979
 
7.9%
시 905
 
7.3%
번 895
 
7.3%
광 893
 
7.2%
역 893
 
7.2%
성 301
 
2.4%
서 230
 
1.9%
Other values (208) 3455
28.0%

도로명전체주소
Text

MISSING 

Distinct648
Distinct (%)97.7%
Missing231
Missing (%)25.8%
Memory size7.1 KiB
2023-12-11T03:44:02.929487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length28.496229
Min length20

Characters and Unicode

Total characters18893
Distinct characters282
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique635 ?
Unique (%)95.8%

Sample

1st row대구광역시 중구 동성로4길 43, 지상1층 (삼덕동1가)
2nd row대구광역시 중구 동덕로 49, 지상 3층 (대봉동)
3rd row대구광역시 중구 남성로 5 (남성로, 지상1층)
4th row대구광역시 중구 달구벌대로 지하 2160 (봉산동, 메트로프라자 D212)
5th row대구광역시 중구 공평로20길 51-32, 2층 (동인동1가)
ValueCountFrequency (%)
대구광역시 663
 
17.0%
1층 180
 
4.6%
북구 143
 
3.7%
수성구 118
 
3.0%
동구 97
 
2.5%
달서구 89
 
2.3%
2층 75
 
1.9%
달성군 63
 
1.6%
중구 56
 
1.4%
서구 54
 
1.4%
Other values (1086) 2356
60.5%
2023-12-11T03:44:03.813447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3231
 
17.1%
구 1346
 
7.1%
대 850
 
4.5%
동 843
 
4.5%
1 742
 
3.9%
시 680
 
3.6%
역 670
 
3.5%
광 663
 
3.5%
로 633
 
3.4%
) 631
 
3.3%
Other values (272) 8604
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10727
56.8%
Space Separator 3231
 
17.1%
Decimal Number 2997
 
15.9%
Close Punctuation 631
 
3.3%
Open Punctuation 631
 
3.3%
Other Punctuation 487
 
2.6%
Dash Punctuation 153
 
0.8%
Uppercase Letter 32
 
0.2%
Lowercase Letter 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1346
 
12.5%
대 850
 
7.9%
동 843
 
7.9%
시 680
 
6.3%
역 670
 
6.2%
광 663
 
6.2%
로 633
 
5.9%
층 416
 
3.9%
길 376
 
3.5%
성 286
 
2.7%
Other values (245) 3964
37.0%
Decimal Number
ValueCountFrequency (%)
1 742
24.8%
2 482
16.1%
3 371
12.4%
4 283
 
9.4%
5 238
 
7.9%
6 224
 
7.5%
0 200
 
6.7%
7 184
 
6.1%
8 150
 
5.0%
9 123
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 12
37.5%
A 9
28.1%
T 3
 
9.4%
J 3
 
9.4%
P 2
 
6.2%
D 1
 
3.1%
C 1
 
3.1%
N 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 485
99.6%
. 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3231
100.0%
Close Punctuation
ValueCountFrequency (%)
) 631
100.0%
Open Punctuation
ValueCountFrequency (%)
( 631
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10727
56.8%
Common 8132
43.0%
Latin 34
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1346
 
12.5%
대 850
 
7.9%
동 843
 
7.9%
시 680
 
6.3%
역 670
 
6.2%
광 663
 
6.2%
로 633
 
5.9%
층 416
 
3.9%
길 376
 
3.5%
성 286
 
2.7%
Other values (245) 3964
37.0%
Common
ValueCountFrequency (%)
3231
39.7%
1 742
 
9.1%
) 631
 
7.8%
( 631
 
7.8%
, 485
 
6.0%
2 482
 
5.9%
3 371
 
4.6%
4 283
 
3.5%
5 238
 
2.9%
6 224
 
2.8%
Other values (8) 814
 
10.0%
Latin
ValueCountFrequency (%)
B 12
35.3%
A 9
26.5%
T 3
 
8.8%
J 3
 
8.8%
P 2
 
5.9%
e 2
 
5.9%
D 1
 
2.9%
C 1
 
2.9%
N 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10727
56.8%
ASCII 8166
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3231
39.6%
1 742
 
9.1%
) 631
 
7.7%
( 631
 
7.7%
, 485
 
5.9%
2 482
 
5.9%
3 371
 
4.5%
4 283
 
3.5%
5 238
 
2.9%
6 224
 
2.7%
Other values (17) 848
 
10.4%
Hangul
ValueCountFrequency (%)
구 1346
 
12.5%
대 850
 
7.9%
동 843
 
7.9%
시 680
 
6.3%
역 670
 
6.2%
광 663
 
6.2%
로 633
 
5.9%
층 416
 
3.9%
길 376
 
3.5%
성 286
 
2.7%
Other values (245) 3964
37.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct435
Distinct (%)65.9%
Missing234
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean41983.691
Minimum41000
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:04.067431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41080.95
Q141485
median41948
Q342483
95-th percentile42954.1
Maximum43023
Range2023
Interquartile range (IQR)998

Descriptive statistics

Standard deviation585.91974
Coefficient of variation (CV)0.013955889
Kurtosis-1.1216774
Mean41983.691
Median Absolute Deviation (MAD)471
Skewness0.160647
Sum27709236
Variance343301.95
MonotonicityNot monotonic
2023-12-11T03:44:04.319032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 11
 
1.2%
41490 11
 
1.2%
41934 9
 
1.0%
41472 6
 
0.7%
42162 6
 
0.7%
42922 5
 
0.6%
41477 5
 
0.6%
42020 5
 
0.6%
42819 5
 
0.6%
41750 5
 
0.6%
Other values (425) 592
66.2%
(Missing) 234
 
26.2%
ValueCountFrequency (%)
41000 2
0.2%
41001 1
0.1%
41007 1
0.1%
41008 2
0.2%
41009 2
0.2%
41015 1
0.1%
41020 2
0.2%
41027 1
0.1%
41028 1
0.1%
41029 1
0.1%
ValueCountFrequency (%)
43023 1
 
0.1%
43013 1
 
0.1%
43009 1
 
0.1%
43003 1
 
0.1%
42993 2
0.2%
42992 1
 
0.1%
42983 3
0.3%
42982 2
0.2%
42976 2
0.2%
42975 2
0.2%

사업장명
Text

Distinct832
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-11T03:44:04.795491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.4888143
Min length2

Characters and Unicode

Total characters5801
Distinct characters528
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique777 ?
Unique (%)86.9%

Sample

1st row샤프한사람들
2nd row로드다이닝(주)
3rd row대한약초
4th row설화
5th row지성건강식품
ValueCountFrequency (%)
주식회사 35
 
3.5%
농업회사법인 7
 
0.7%
주 5
 
0.5%
international 3
 
0.3%
하나그린통상 3
 
0.3%
company 3
 
0.3%
선진vfc 3
 
0.3%
천상무역(cs 3
 
0.3%
산수원 3
 
0.3%
아세아그린팜 3
 
0.3%
Other values (863) 921
93.1%
2023-12-11T03:44:05.507060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 311
 
5.4%
) 272
 
4.7%
( 270
 
4.7%
식 185
 
3.2%
이 141
 
2.4%
사 131
 
2.3%
품 115
 
2.0%
회 95
 
1.6%
95
 
1.6%
스 94
 
1.6%
Other values (518) 4092
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4963
85.6%
Close Punctuation 272
 
4.7%
Open Punctuation 270
 
4.7%
Space Separator 95
 
1.6%
Uppercase Letter 88
 
1.5%
Lowercase Letter 81
 
1.4%
Other Punctuation 16
 
0.3%
Decimal Number 13
 
0.2%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 311
 
6.3%
식 185
 
3.7%
이 141
 
2.8%
사 131
 
2.6%
품 115
 
2.3%
회 95
 
1.9%
스 94
 
1.9%
드 91
 
1.8%
푸 81
 
1.6%
리 75
 
1.5%
Other values (465) 3644
73.4%
Uppercase Letter
ValueCountFrequency (%)
C 16
18.2%
S 14
15.9%
F 13
14.8%
M 5
 
5.7%
B 4
 
4.5%
I 4
 
4.5%
N 4
 
4.5%
K 3
 
3.4%
E 3
 
3.4%
Y 3
 
3.4%
Other values (11) 19
21.6%
Lowercase Letter
ValueCountFrequency (%)
n 13
16.0%
a 11
13.6%
t 9
11.1%
i 9
11.1%
o 8
9.9%
l 6
7.4%
e 6
7.4%
y 4
 
4.9%
m 3
 
3.7%
p 3
 
3.7%
Other values (7) 9
11.1%
Decimal Number
ValueCountFrequency (%)
9 3
23.1%
2 3
23.1%
3 2
15.4%
1 2
15.4%
5 1
 
7.7%
7 1
 
7.7%
4 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
& 9
56.2%
. 6
37.5%
, 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 270
100.0%
Space Separator
ValueCountFrequency (%)
95
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4965
85.6%
Common 667
 
11.5%
Latin 169
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 311
 
6.3%
식 185
 
3.7%
이 141
 
2.8%
사 131
 
2.6%
품 115
 
2.3%
회 95
 
1.9%
스 94
 
1.9%
드 91
 
1.8%
푸 81
 
1.6%
리 75
 
1.5%
Other values (466) 3646
73.4%
Latin
ValueCountFrequency (%)
C 16
 
9.5%
S 14
 
8.3%
n 13
 
7.7%
F 13
 
7.7%
a 11
 
6.5%
t 9
 
5.3%
i 9
 
5.3%
o 8
 
4.7%
l 6
 
3.6%
e 6
 
3.6%
Other values (28) 64
37.9%
Common
ValueCountFrequency (%)
) 272
40.8%
( 270
40.5%
95
 
14.2%
& 9
 
1.3%
. 6
 
0.9%
9 3
 
0.4%
2 3
 
0.4%
3 2
 
0.3%
1 2
 
0.3%
5 1
 
0.1%
Other values (4) 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4963
85.6%
ASCII 836
 
14.4%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 311
 
6.3%
식 185
 
3.7%
이 141
 
2.8%
사 131
 
2.6%
품 115
 
2.3%
회 95
 
1.9%
스 94
 
1.9%
드 91
 
1.8%
푸 81
 
1.6%
리 75
 
1.5%
Other values (465) 3644
73.4%
ASCII
ValueCountFrequency (%)
) 272
32.5%
( 270
32.3%
95
 
11.4%
C 16
 
1.9%
S 14
 
1.7%
n 13
 
1.6%
F 13
 
1.6%
a 11
 
1.3%
& 9
 
1.1%
t 9
 
1.1%
Other values (42) 114
13.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정시점
Real number (ℝ)

Distinct836
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0132255 × 1013
Minimum2.0010823 × 1013
Maximum2.0191128 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:05.763018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.002068 × 1013
Q12.0090537 × 1013
median2.0150823 × 1013
Q32.0180711 × 1013
95-th percentile2.0190827 × 1013
Maximum2.0191128 × 1013
Range1.8030517 × 1011
Interquartile range (IQR)9.0174052 × 1010

Descriptive statistics

Standard deviation5.7071602 × 1010
Coefficient of variation (CV)0.002834834
Kurtosis-0.84228066
Mean2.0132255 × 1013
Median Absolute Deviation (MAD)3.9305474 × 1010
Skewness-0.74390803
Sum1.7998236 × 1016
Variance3.2571677 × 1021
MonotonicityNot monotonic
2023-12-11T03:44:06.044416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.3%
20021113000000 10
 
1.1%
20020126000000 9
 
1.0%
20020510000000 5
 
0.6%
20021019000000 5
 
0.6%
20020115000000 5
 
0.6%
20021012000000 3
 
0.3%
20140512105112 3
 
0.3%
20041011000000 3
 
0.3%
20060825000000 3
 
0.3%
Other values (826) 836
93.5%
ValueCountFrequency (%)
20010823000000 1
 
0.1%
20020115000000 5
0.6%
20020124000000 2
 
0.2%
20020125000000 2
 
0.2%
20020126000000 9
1.0%
20020326000000 1
 
0.1%
20020403000000 1
 
0.1%
20020416000000 1
 
0.1%
20020503000000 1
 
0.1%
20020507000000 1
 
0.1%
ValueCountFrequency (%)
20191128171240 1
0.1%
20191128133344 1
0.1%
20191128133016 1
0.1%
20191122161944 1
0.1%
20191121181704 1
0.1%
20191121172011 1
0.1%
20191119163049 1
0.1%
20191119160957 1
0.1%
20191118170424 1
0.1%
20191111160515 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
I
712 
U
182 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 712
79.6%
U 182
 
20.4%

Length

2023-12-11T03:44:06.327002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:06.510786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 712
79.6%
u 182
 
20.4%

데이터갱신일자
Date

Distinct157
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
Minimum2018-08-31 23:59:59
Maximum2019-11-30 02:40:00
2023-12-11T03:44:06.707083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:44:06.967933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
유통전문판매업
894 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 894
100.0%

Length

2023-12-11T03:44:07.200917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:07.356196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 894
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct814
Distinct (%)92.8%
Missing17
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean342790.29
Minimum326032.48
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:07.506649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326032.48
5-th percentile332715.77
Q1339232.74
median342896.43
Q3346490.43
95-th percentile352971.46
Maximum358046.4
Range32013.922
Interquartile range (IQR)7257.6983

Descriptive statistics

Standard deviation5512.8406
Coefficient of variation (CV)0.016082254
Kurtosis0.18310746
Mean342790.29
Median Absolute Deviation (MAD)3628.4744
Skewness-0.031160962
Sum3.0062708 × 108
Variance30391411
MonotonicityNot monotonic
2023-12-11T03:44:07.671685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336590.459071 6
 
0.7%
346942.691097 3
 
0.3%
339320.839241 3
 
0.3%
344010.849417 3
 
0.3%
341215.925853 3
 
0.3%
345206.578526 3
 
0.3%
345687.898519 3
 
0.3%
346193.266936 3
 
0.3%
338421.494971 3
 
0.3%
343157.682044 3
 
0.3%
Other values (804) 844
94.4%
(Missing) 17
 
1.9%
ValueCountFrequency (%)
326032.481595 1
0.1%
327448.497282 1
0.1%
327590.551952 1
0.1%
327894.698221 1
0.1%
328237.006988 1
0.1%
328520.607105 1
0.1%
328779.085065 1
0.1%
328874.867518 1
0.1%
328945.225812 1
0.1%
328968.535954 1
0.1%
ValueCountFrequency (%)
358046.403776 1
0.1%
356698.367083 1
0.1%
356588.107241 1
0.1%
356353.91544 1
0.1%
356331.110923 1
0.1%
356325.339359 1
0.1%
356032.203864 1
0.1%
355905.566888 1
0.1%
355875.122869 1
0.1%
355775.887964 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct814
Distinct (%)92.8%
Missing17
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean263672.75
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:08.259331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile256336.91
Q1261197.87
median264101.19
Q3266220.73
95-th percentile271329.03
Maximum277799.71
Range39492.858
Interquartile range (IQR)5022.8556

Descriptive statistics

Standard deviation4976.3879
Coefficient of variation (CV)0.018873349
Kurtosis4.3319159
Mean263672.75
Median Absolute Deviation (MAD)2700.8087
Skewness-1.0179194
Sum2.31241 × 108
Variance24764436
MonotonicityNot monotonic
2023-12-11T03:44:08.489154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257286.897263 6
 
0.7%
263989.847737 3
 
0.3%
265197.142652 3
 
0.3%
263014.492917 3
 
0.3%
260848.360361 3
 
0.3%
260875.577524 3
 
0.3%
266987.666828 3
 
0.3%
264708.839935 3
 
0.3%
260797.727311 3
 
0.3%
261957.795169 3
 
0.3%
Other values (804) 844
94.4%
(Missing) 17
 
1.9%
ValueCountFrequency (%)
238306.850311 1
0.1%
238531.35408 1
0.1%
239240.086699 1
0.1%
239536.919741 1
0.1%
240205.085494 1
0.1%
242273.0 1
0.1%
242311.21229 1
0.1%
243088.915629 1
0.1%
244839.424611 1
0.1%
248757.200867 1
0.1%
ValueCountFrequency (%)
277799.708684 1
0.1%
277755.206408 2
0.2%
277541.768688 1
0.1%
277428.083074 1
0.1%
275969.761183 1
0.1%
275787.590179 1
0.1%
274594.894588 1
0.1%
274508.218106 1
0.1%
274214.678839 1
0.1%
273994.885719 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
유통전문판매업
894 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 894
100.0%

Length

2023-12-11T03:44:08.692343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:08.839871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 894
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
893 
0
 
1

Length

Max length4
Median length4
Mean length3.9966443
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 893
99.9%
0 1
 
0.1%

Length

2023-12-11T03:44:08.983685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:09.154765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 893
99.9%
0 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
893 
0
 
1

Length

Max length4
Median length4
Mean length3.9966443
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 893
99.9%
0 1
 
0.1%

Length

2023-12-11T03:44:09.321487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:09.462015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 893
99.9%
0 1
 
0.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
622 
상수도전용
270 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.3042506
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 622
69.6%
상수도전용 270
30.2%
지하수전용 2
 
0.2%

Length

2023-12-11T03:44:09.630239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:09.809451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 622
69.6%
상수도전용 270
30.2%
지하수전용 2
 
0.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
586 
<NA>
298 
1
 
4
2
 
3
4
 
2

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 586
65.5%
<NA> 298
33.3%
1 4
 
0.4%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%

Length

2023-12-11T03:44:10.024611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:10.222781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 586
65.5%
na 298
33.3%
1 4
 
0.4%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%

공장사무직종업원수
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
543 
<NA>
298 
1
 
33
2
 
18
3
 
2

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 543
60.7%
<NA> 298
33.3%
1 33
 
3.7%
2 18
 
2.0%
3 2
 
0.2%

Length

2023-12-11T03:44:10.406128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:10.576911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 543
60.7%
na 298
33.3%
1 33
 
3.7%
2 18
 
2.0%
3 2
 
0.2%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.3%
Missing298
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean0.15100671
Minimum0
Maximum20
Zeros555
Zeros (%)62.1%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:10.729638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0128663
Coefficient of variation (CV)6.7074257
Kurtosis264.21615
Mean0.15100671
Median Absolute Deviation (MAD)0
Skewness14.718583
Sum90
Variance1.0258981
MonotonicityNot monotonic
2023-12-11T03:44:10.951232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 555
62.1%
1 25
 
2.8%
2 10
 
1.1%
3 2
 
0.2%
5 1
 
0.1%
20 1
 
0.1%
4 1
 
0.1%
10 1
 
0.1%
(Missing) 298
33.3%
ValueCountFrequency (%)
0 555
62.1%
1 25
 
2.8%
2 10
 
1.1%
3 2
 
0.2%
4 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%
20 1
 
0.1%
ValueCountFrequency (%)
20 1
 
0.1%
10 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 2
 
0.2%
2 10
 
1.1%
1 25
 
2.8%
0 555
62.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
576 
<NA>
299 
1
 
11
2
 
7
4
 
1

Length

Max length4
Median length1
Mean length2.0033557
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 576
64.4%
<NA> 299
33.4%
1 11
 
1.2%
2 7
 
0.8%
4 1
 
0.1%

Length

2023-12-11T03:44:11.151547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:11.320295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 576
64.4%
na 299
33.4%
1 11
 
1.2%
2 7
 
0.8%
4 1
 
0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
592 
자가
173 
임대
129 

Length

Max length4
Median length4
Mean length3.3243848
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 592
66.2%
자가 173
 
19.4%
임대 129
 
14.4%

Length

2023-12-11T03:44:11.510003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:11.681035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 592
66.2%
자가 173
 
19.4%
임대 129
 
14.4%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
889 
0
 
5

Length

Max length4
Median length4
Mean length3.9832215
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 889
99.4%
0 5
 
0.6%

Length

2023-12-11T03:44:11.887661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:12.067803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 889
99.4%
0 5
 
0.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
889 
0
 
5

Length

Max length4
Median length4
Mean length3.9832215
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 889
99.4%
0 5
 
0.6%

Length

2023-12-11T03:44:12.232988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:44:12.394825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 889
99.4%
0 5
 
0.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
False
894 
ValueCountFrequency (%)
False 894
100.0%
2023-12-11T03:44:12.523558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct53
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8966779
Minimum0
Maximum240
Zeros827
Zeros (%)92.5%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-11T03:44:12.710278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.592
Maximum240
Range240
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.766066
Coefficient of variation (CV)7.2579884
Kurtosis188.99191
Mean1.8966779
Median Absolute Deviation (MAD)0
Skewness12.685865
Sum1695.63
Variance189.50457
MonotonicityNot monotonic
2023-12-11T03:44:12.941730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 827
92.5%
3.3 4
 
0.4%
5.0 4
 
0.4%
33.0 3
 
0.3%
10.0 3
 
0.3%
8.0 2
 
0.2%
66.0 2
 
0.2%
20.0 2
 
0.2%
6.6 2
 
0.2%
4.5 2
 
0.2%
Other values (43) 43
 
4.8%
ValueCountFrequency (%)
0.0 827
92.5%
1.2 1
 
0.1%
2.18 1
 
0.1%
2.25 1
 
0.1%
2.55 1
 
0.1%
2.56 1
 
0.1%
2.75 1
 
0.1%
2.81 1
 
0.1%
3.0 1
 
0.1%
3.3 4
 
0.4%
ValueCountFrequency (%)
240.0 1
 
0.1%
222.12 1
 
0.1%
131.12 1
 
0.1%
106.6 1
 
0.1%
101.52 1
 
0.1%
66.0 2
0.2%
51.68 1
 
0.1%
50.85 1
 
0.1%
35.0 1
 
0.1%
33.0 3
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing894
Missing (%)100.0%
Memory size8.0 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_22_17_P34100003410000-113-2019-0000220190531<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00700411대구광역시 중구 삼덕동1가 0027-0003번지 지상1층대구광역시 중구 동성로4길 43, 지상1층 (삼덕동1가)41942샤프한사람들20190617173608U2019-06-19 02:40:00.0유통전문판매업344081.22449264310.134087유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
12유통전문판매업07_22_17_P34100003410000-113-2018-0000620180906<NA>1영업/정상1영업<NA><NA><NA><NA><NA>182.00700809대구광역시 중구 대봉동 0043-0021번지 지상 3층대구광역시 중구 동덕로 49, 지상 3층 (대봉동)41954로드다이닝(주)20180906114903U2018-09-06 23:59:59.0유통전문판매업344835.110573263330.79696유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23유통전문판매업07_22_17_P34100003410000-113-2016-0000220160427<NA>3폐업2폐업20180314<NA><NA><NA><NA>5.70700230대구광역시 중구 남성로 0020-0005번지 지상1층대구광역시 중구 남성로 5 (남성로, 지상1층)41934대한약초20180314161314I2018-08-31 23:59:59.0유통전문판매업343338.902682264381.802951유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
34유통전문판매업07_22_17_P34100003410000-113-2016-0000320160620<NA>3폐업2폐업20170623<NA><NA><NA><NA>29.70700823대구광역시 중구 봉산동 0127-0001번지 메트로프라자 D212대구광역시 중구 달구벌대로 지하 2160 (봉산동, 메트로프라자 D212)41959설화20170623141221I2018-08-31 23:59:59.0유통전문판매업344083.488663263931.205868유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
45유통전문판매업07_22_17_P34100003410000-113-2011-0000220110830<NA>3폐업2폐업20140613<NA><NA><NA>053 746123971.69700421대구광역시 중구 동인동1가 0204-0002번지 지상2층대구광역시 중구 공평로20길 51-32, 2층 (동인동1가)41911지성건강식품20120201160134I2018-08-31 23:59:59.0유통전문판매업344689.839528264805.59973유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
56유통전문판매업07_22_17_P34100003410000-113-2012-0000120120403<NA>3폐업2폐업20140305<NA><NA><NA>16001037<NA>700837대구광역시 중구 남산동 2466-0026번지 지상2층대구광역시 중구 남산로 39 (남산동, 지상2층)41978야미고프20131031092326I2018-08-31 23:59:59.0유통전문판매업342856.914363263364.097215유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
67유통전문판매업07_22_17_P34100003410000-113-2014-0000220140925<NA>3폐업2폐업20150122<NA><NA><NA><NA>23.56700840대구광역시 중구 달성동 0145-0007번지 지상3층대구광역시 중구 태평로 13 (달성동, 지상3층)41900세종라이프20140925143146I2018-08-31 23:59:59.0유통전문판매업342566.486427265380.887132유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78유통전문판매업07_22_17_P34100003410000-113-2014-0000420141114<NA>3폐업2폐업20160429<NA><NA><NA>053 2540892120.00700413대구광역시 중구 삼덕동3가 0231번지 지상2층대구광역시 중구 동덕로26길 104 (삼덕동3가, 지상2층)41948(주)커피명가20141114163307I2018-08-31 23:59:59.0유통전문판매업345250.899602263888.385046유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N20.0<NA><NA><NA>
89유통전문판매업07_22_17_P34100003410000-113-2015-0000820150910<NA>3폐업2폐업20180308<NA><NA><NA>053 781266211.54700413대구광역시 중구 삼덕동3가 0265-0003번지 지상2층대구광역시 중구 달구벌대로447길 42 (삼덕동3가, 지상2층)41948라임덴탈20180308171641I2018-08-31 23:59:59.0유통전문판매업345164.494458263868.961281유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
910유통전문판매업07_22_17_P34100003410000-113-2016-0000520161011<NA>3폐업2폐업20180712<NA><NA><NA><NA>178.70700320대구광역시 중구 대신동 0115-0005번지 5층 502호대구광역시 중구 국채보상로 458 (대신동, 5층 502호)41926웰빙코리아20180712100455I2018-08-31 23:59:59.0유통전문판매업342714.834681264487.841783유통전문판매업<NA><NA><NA><NA><NA><NA>0010<NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
884885유통전문판매업07_22_17_P34800003480000-113-2011-0000420110331<NA>1영업/정상1영업<NA><NA><NA><NA>053 324 9824461.30711814대구광역시 달성군 다사읍 세천리 1662-10번지대구광역시 달성군 다사읍 세천로1길 119, 2층42921에인에이(주)20191121172011U2019-11-23 02:40:00.0유통전문판매업332163.069053265348.507187유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
885886유통전문판매업07_22_17_P34800003480000-113-2012-0000220121105<NA>1영업/정상1영업<NA><NA><NA><NA>053 248 1860107.20711814대구광역시 달성군 다사읍 세천리 1561-2번지대구광역시 달성군 다사읍 세천북로8길 18-2, 1층42922평산네이처20150625160955I2018-08-31 23:59:59.0유통전문판매업333532.782282265310.700363유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N4.0<NA><NA><NA>
886887유통전문판매업07_22_17_P34800003480000-113-2013-0000120130718<NA>1영업/정상1영업<NA><NA><NA><NA>053 592 155074.19711811대구광역시 달성군 다사읍 달천리 295-1번지 1층대구광역시 달성군 다사읍 다사로101길 24, 1층42907꼬메르유통20130724170926I2018-08-31 23:59:59.0유통전문판매업333818.317281266384.063983유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
887888유통전문판매업07_22_17_P34800003480000-113-2013-0000320131021<NA>1영업/정상1영업<NA><NA><NA><NA>053 523 443352.69711851대구광역시 달성군 논공읍 금포리 623-10번지대구광역시 달성군 논공읍 비슬로371길 98, 1층42968부강식품20131028111608I2018-08-31 23:59:59.0유통전문판매업328237.006988254551.275809유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
888889유통전문판매업07_22_17_P34800003480000-113-2013-0000420131022<NA>1영업/정상1영업<NA><NA><NA><NA>053 630 38406.00711892대구광역시 달성군 구지면 내리 847-15번지<NA><NA>리치코리아 유한회사20131115181410I2018-08-31 23:59:59.0유통전문판매업328520.607105238531.35408유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
889890유통전문판매업07_22_17_P34800003480000-113-2018-0000120180111<NA>1영업/정상1영업<NA><NA><NA><NA>053 611 282130.00<NA>대구광역시 달성군 유가읍 유곡리 1163-4번지대구광역시 달성군 유가읍 테크노중앙대로2길 16, 1층42993유가찹쌀영농조합20180111152724I2018-08-31 23:59:59.0유통전문판매업332223.0242273.0유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
890891유통전문판매업07_22_17_P34800003480000-113-2013-0000620131118<NA>1영업/정상1영업<NA><NA><NA><NA>053 631 122216.08711835대구광역시 달성군 화원읍 천내리 264번지대구광역시 달성군 화원읍 비슬로511길 24-6, 1층42947선푸드 주식회사 육가공공장20190710155219U2019-07-12 02:40:00.0유통전문판매업335191.673553256980.574511유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
891892유통전문판매업07_22_17_P34800003480000-113-2014-0000120140213<NA>1영업/정상1영업<NA><NA><NA><NA>1899491554.12711863대구광역시 달성군 가창면 삼산리 711번지대구광역시 달성군 가창면 가창로57길 2342940(주)종초원20160104164748I2018-08-31 23:59:59.0유통전문판매업349873.999232249984.471618유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N2.75<NA><NA><NA>
892893유통전문판매업07_22_17_P34800003480000-113-2014-0000620140513<NA>1영업/정상1영업<NA><NA><NA><NA>07088635858173.50711851대구광역시 달성군 논공읍 금포리 1627-2번지대구광역시 달성군 논공읍 금강로4길 30, 1층42974주식회사 비오엠20151229155730I2018-08-31 23:59:59.0유통전문판매업328968.535954253208.672334유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
893894유통전문판매업07_22_17_P34800003480000-113-2015-0000420151020<NA>1영업/정상1영업<NA><NA><NA><NA>1544586815.70711812대구광역시 달성군 다사읍 매곡리 1532-4번지대구광역시 달성군 다사읍 대실역북로2길 101-12, 1층42911농업회사법인 맑을청웰빙 주식회사20151020140253I2018-08-31 23:59:59.0유통전문판매업332585.830281263552.843937유통전문판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>