Overview

Dataset statistics

Number of variables47
Number of observations883
Missing cells10401
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory350.2 KiB
Average record size in memory406.1 B

Variable types

Numeric11
Categorical18
Text6
Unsupported10
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_17_P_유통전문판매업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000068198&dataSetDetailId=DDI_0000068244&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 883 (100.0%) missing valuesMissing
폐업일자 has 376 (42.6%) missing valuesMissing
휴업시작일자 has 883 (100.0%) missing valuesMissing
휴업종료일자 has 883 (100.0%) missing valuesMissing
재개업일자 has 883 (100.0%) missing valuesMissing
소재지전화 has 275 (31.1%) missing valuesMissing
소재지면적 has 116 (13.1%) missing valuesMissing
소재지우편번호 has 10 (1.1%) missing valuesMissing
도로명전체주소 has 231 (26.2%) missing valuesMissing
도로명우편번호 has 234 (26.5%) missing valuesMissing
좌표정보(X) has 17 (1.9%) missing valuesMissing
좌표정보(Y) has 17 (1.9%) missing valuesMissing
영업장주변구분명 has 883 (100.0%) missing valuesMissing
등급구분명 has 883 (100.0%) missing valuesMissing
총종업원수 has 883 (100.0%) missing valuesMissing
공장판매직종업원수 has 294 (33.3%) missing valuesMissing
전통업소지정번호 has 883 (100.0%) missing valuesMissing
전통업소주된음식 has 883 (100.0%) missing valuesMissing
홈페이지 has 883 (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 548 (62.1%) zerosZeros
시설총규모 has 820 (92.9%) zerosZeros

Reproduction

Analysis started2023-12-10 19:37:30.325965
Analysis finished2023-12-10 19:37:31.609787
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct883
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442
Minimum1
Maximum883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:31.696460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.1
Q1221.5
median442
Q3662.5
95-th percentile838.9
Maximum883
Range882
Interquartile range (IQR)441

Descriptive statistics

Standard deviation255.04444
Coefficient of variation (CV)0.57702362
Kurtosis-1.2
Mean442
Median Absolute Deviation (MAD)221
Skewness0
Sum390286
Variance65047.667
MonotonicityStrictly increasing
2023-12-11T04:37:31.853047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
595 1
 
0.1%
584 1
 
0.1%
585 1
 
0.1%
586 1
 
0.1%
587 1
 
0.1%
588 1
 
0.1%
589 1
 
0.1%
590 1
 
0.1%
591 1
 
0.1%
Other values (873) 873
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 (%)
883 1
0.1%
882 1
0.1%
881 1
0.1%
880 1
0.1%
879 1
0.1%
878 1
0.1%
877 1
0.1%
876 1
0.1%
875 1
0.1%
874 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
유통전문판매업
883 

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 883
100.0%

Length

2023-12-11T04:37:32.015944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:32.146512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 883
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
07_22_17_P
883 

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 883
100.0%

Length

2023-12-11T04:37:32.299329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:32.426663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 883
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447372.6
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:32.522818image/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 deviation21014.637
Coefficient of variation (CV)0.0060958416
Kurtosis-1.0524042
Mean3447372.6
Median Absolute Deviation (MAD)20000
Skewness-0.25515951
Sum3.04403 × 109
Variance4.4161498 × 108
MonotonicityIncreasing
2023-12-11T04:37:32.691374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 192
21.7%
3460000 154
17.4%
3420000 131
14.8%
3470000 125
14.2%
3480000 78
8.8%
3430000 76
 
8.6%
3410000 66
 
7.5%
3440000 61
 
6.9%
ValueCountFrequency (%)
3410000 66
 
7.5%
3420000 131
14.8%
3430000 76
 
8.6%
3440000 61
 
6.9%
3450000 192
21.7%
3460000 154
17.4%
3470000 125
14.2%
3480000 78
8.8%
ValueCountFrequency (%)
3480000 78
8.8%
3470000 125
14.2%
3460000 154
17.4%
3450000 192
21.7%
3440000 61
 
6.9%
3430000 76
 
8.6%
3420000 131
14.8%
3410000 66
 
7.5%

관리번호
Text

UNIQUE 

Distinct883
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2023-12-11T04:37:32.915715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters19426
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

Unique883 ?
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%
3460000-113-2012-00011 1
 
0.1%
3460000-113-2015-00022 1
 
0.1%
3460000-113-2017-00011 1
 
0.1%
3460000-113-2003-00004 1
 
0.1%
3460000-113-2019-00006 1
 
0.1%
3460000-113-2019-00009 1
 
0.1%
3460000-113-2019-00008 1
 
0.1%
3460000-113-2019-00007 1
 
0.1%
3460000-113-2019-00005 1
 
0.1%
Other values (873) 873
98.9%
2023-12-11T04:37:33.255650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8169
42.1%
1 2769
 
14.3%
- 2649
 
13.6%
3 2034
 
10.5%
2 1210
 
6.2%
4 1136
 
5.8%
5 407
 
2.1%
6 326
 
1.7%
7 258
 
1.3%
9 237
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16777
86.4%
Dash Punctuation 2649
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8169
48.7%
1 2769
 
16.5%
3 2034
 
12.1%
2 1210
 
7.2%
4 1136
 
6.8%
5 407
 
2.4%
6 326
 
1.9%
7 258
 
1.5%
9 237
 
1.4%
8 231
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2649
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19426
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8169
42.1%
1 2769
 
14.3%
- 2649
 
13.6%
3 2034
 
10.5%
2 1210
 
6.2%
4 1136
 
5.8%
5 407
 
2.1%
6 326
 
1.7%
7 258
 
1.3%
9 237
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8169
42.1%
1 2769
 
14.3%
- 2649
 
13.6%
3 2034
 
10.5%
2 1210
 
6.2%
4 1136
 
5.8%
5 407
 
2.1%
6 326
 
1.7%
7 258
 
1.3%
9 237
 
1.2%

인허가일자
Real number (ℝ)

Distinct758
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20112626
Minimum19950510
Maximum20190930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:33.410618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20000801
Q120061115
median20130718
Q320160828
95-th percentile20190396
Maximum20190930
Range240420
Interquartile range (IQR)99712.5

Descriptive statistics

Standard deviation60899.899
Coefficient of variation (CV)0.0030279436
Kurtosis-0.76487814
Mean20112626
Median Absolute Deviation (MAD)40117
Skewness-0.61284319
Sum1.7759449 × 1010
Variance3.7087977 × 109
MonotonicityNot monotonic
2023-12-11T04:37:33.566842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121105 4
 
0.5%
20180508 4
 
0.5%
20190613 3
 
0.3%
20121016 3
 
0.3%
20150625 3
 
0.3%
20130610 3
 
0.3%
20150819 3
 
0.3%
20170809 3
 
0.3%
20140508 3
 
0.3%
19990223 3
 
0.3%
Other values (748) 851
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 (%)
20190930 1
0.1%
20190926 1
0.1%
20190905 2
0.2%
20190902 2
0.2%
20190827 1
0.1%
20190826 2
0.2%
20190823 1
0.1%
20190822 1
0.1%
20190820 1
0.1%
20190819 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
3
507 
1
376 

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 (%)
3 507
57.4%
1 376
42.6%

Length

2023-12-11T04:37:33.704987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:33.797163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 507
57.4%
1 376
42.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
폐업
507 
영업/정상
376 

Length

Max length5
Median length2
Mean length3.2774632
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 507
57.4%
영업/정상 376
42.6%

Length

2023-12-11T04:37:33.900333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:34.050069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 507
57.4%
영업/정상 376
42.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2
507 
1
376 

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 (%)
2 507
57.4%
1 376
42.6%

Length

2023-12-11T04:37:34.164571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:34.257174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 507
57.4%
1 376
42.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
폐업
507 
영업
376 

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 507
57.4%
영업 376
42.6%

Length

2023-12-11T04:37:34.374426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:34.488747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 507
57.4%
영업 376
42.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct460
Distinct (%)90.7%
Missing376
Missing (%)42.6%
Infinite0
Infinite (%)0.0%
Mean20119850
Minimum20001029
Maximum20190906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:34.634751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040127
Q120070210
median20130924
Q320170202
95-th percentile20190312
Maximum20190906
Range189877
Interquartile range (IQR)99993

Descriptive statistics

Standard deviation52984.335
Coefficient of variation (CV)0.0026334359
Kurtosis-1.3130414
Mean20119850
Median Absolute Deviation (MAD)49282
Skewness-0.28834356
Sum1.0200764 × 1010
Variance2.8073398 × 109
MonotonicityNot monotonic
2023-12-11T04:37:34.792622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.6%
20070116 4
 
0.5%
20151229 3
 
0.3%
20051128 3
 
0.3%
20040830 3
 
0.3%
20161229 3
 
0.3%
20021224 3
 
0.3%
20190904 2
 
0.2%
20190320 2
 
0.2%
20180307 2
 
0.2%
Other values (450) 477
54.0%
(Missing) 376
42.6%
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 (%)
20190906 1
0.1%
20190904 2
0.2%
20190820 1
0.1%
20190814 1
0.1%
20190813 1
0.1%
20190731 1
0.1%
20190704 1
0.1%
20190701 1
0.1%
20190620 1
0.1%
20190619 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

소재지전화
Text

MISSING 

Distinct573
Distinct (%)94.2%
Missing275
Missing (%)31.1%
Memory size7.0 KiB
2023-12-11T04:37:35.176238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.883224
Min length7

Characters and Unicode

Total characters6617
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

Unique540 ?
Unique (%)88.8%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 428
32.3%
070 31
 
2.3%
311 9
 
0.7%
313 8
 
0.6%
746 6
 
0.5%
755 6
 
0.5%
625 4
 
0.3%
584 4
 
0.3%
312 4
 
0.3%
742 4
 
0.3%
Other values (703) 820
61.9%
2023-12-11T04:37:35.684968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1009
15.2%
0 945
14.3%
3 892
13.5%
722
10.9%
1 502
7.6%
2 488
7.4%
7 476
7.2%
6 425
6.4%
8 417
6.3%
4 410
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5895
89.1%
Space Separator 722
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1009
17.1%
0 945
16.0%
3 892
15.1%
1 502
8.5%
2 488
8.3%
7 476
8.1%
6 425
7.2%
8 417
7.1%
4 410
7.0%
9 331
 
5.6%
Space Separator
ValueCountFrequency (%)
722
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6617
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1009
15.2%
0 945
14.3%
3 892
13.5%
722
10.9%
1 502
7.6%
2 488
7.4%
7 476
7.2%
6 425
6.4%
8 417
6.3%
4 410
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1009
15.2%
0 945
14.3%
3 892
13.5%
722
10.9%
1 502
7.6%
2 488
7.4%
7 476
7.2%
6 425
6.4%
8 417
6.3%
4 410
6.2%

소재지면적
Text

MISSING 

Distinct555
Distinct (%)72.4%
Missing116
Missing (%)13.1%
Memory size7.0 KiB
2023-12-11T04:37:36.024607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0756193
Min length3

Characters and Unicode

Total characters3893
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

Unique472 ?
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%
99.00 6
 
0.8%
20.00 6
 
0.8%
Other values (545) 656
85.5%
2023-12-11T04:37:36.497353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 858
22.0%
. 767
19.7%
1 353
9.1%
2 330
 
8.5%
3 296
 
7.6%
5 271
 
7.0%
4 240
 
6.2%
6 228
 
5.9%
9 185
 
4.8%
8 183
 
4.7%
Other values (2) 182
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3123
80.2%
Other Punctuation 770
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 858
27.5%
1 353
11.3%
2 330
 
10.6%
3 296
 
9.5%
5 271
 
8.7%
4 240
 
7.7%
6 228
 
7.3%
9 185
 
5.9%
8 183
 
5.9%
7 179
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 767
99.6%
, 3
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3893
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 858
22.0%
. 767
19.7%
1 353
9.1%
2 330
 
8.5%
3 296
 
7.6%
5 271
 
7.0%
4 240
 
6.2%
6 228
 
5.9%
9 185
 
4.8%
8 183
 
4.7%
Other values (2) 182
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3893
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 858
22.0%
. 767
19.7%
1 353
9.1%
2 330
 
8.5%
3 296
 
7.6%
5 271
 
7.0%
4 240
 
6.2%
6 228
 
5.9%
9 185
 
4.8%
8 183
 
4.7%
Other values (2) 182
 
4.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct354
Distinct (%)40.5%
Missing10
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean704431.55
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:36.649715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700809
Q1702230
median703830
Q3706140
95-th percentile711832.4
Maximum711892
Range11882
Interquartile range (IQR)3910

Descriptive statistics

Standard deviation2905.4787
Coefficient of variation (CV)0.0041245721
Kurtosis0.84196187
Mean704431.55
Median Absolute Deviation (MAD)1977
Skewness1.0500983
Sum6.1496874 × 108
Variance8441806.6
MonotonicityNot monotonic
2023-12-11T04:37:36.823649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 18
 
2.0%
703830 10
 
1.1%
703100 10
 
1.1%
700230 9
 
1.0%
706818 9
 
1.0%
706803 8
 
0.9%
706220 8
 
0.9%
702866 7
 
0.8%
702903 7
 
0.8%
706838 7
 
0.8%
Other values (344) 780
88.3%
(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
0.5%
711852 3
0.3%
711851 5
0.6%
711845 5
0.6%
Distinct845
Distinct (%)95.8%
Missing1
Missing (%)0.1%
Memory size7.0 KiB
2023-12-11T04:37:37.142891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length24.441043
Min length18

Characters and Unicode

Total characters21557
Distinct characters242
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

Unique812 ?
Unique (%)92.1%

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 882
22.2%
북구 192
 
4.8%
수성구 153
 
3.9%
동구 131
 
3.3%
달서구 125
 
3.2%
달성군 78
 
2.0%
서구 76
 
1.9%
중구 66
 
1.7%
남구 61
 
1.5%
대명동 47
 
1.2%
Other values (1141) 2157
54.4%
2023-12-11T04:37:37.605965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3952
18.3%
1719
 
8.0%
1040
 
4.8%
1 1032
 
4.8%
985
 
4.6%
965
 
4.5%
894
 
4.1%
884
 
4.1%
882
 
4.1%
882
 
4.1%
Other values (232) 8322
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12177
56.5%
Decimal Number 4506
 
20.9%
Space Separator 3952
 
18.3%
Dash Punctuation 739
 
3.4%
Open Punctuation 73
 
0.3%
Close Punctuation 73
 
0.3%
Uppercase Letter 22
 
0.1%
Other Punctuation 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1719
14.1%
1040
 
8.5%
985
 
8.1%
965
 
7.9%
894
 
7.3%
884
 
7.3%
882
 
7.2%
882
 
7.2%
296
 
2.4%
229
 
1.9%
Other values (206) 3401
27.9%
Decimal Number
ValueCountFrequency (%)
1 1032
22.9%
2 585
13.0%
0 580
12.9%
3 442
9.8%
5 356
 
7.9%
4 351
 
7.8%
6 315
 
7.0%
8 303
 
6.7%
7 281
 
6.2%
9 261
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
27.3%
A 3
13.6%
T 3
13.6%
C 2
 
9.1%
D 2
 
9.1%
J 2
 
9.1%
P 2
 
9.1%
N 1
 
4.5%
F 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 12
80.0%
/ 2
 
13.3%
. 1
 
6.7%
Space Separator
ValueCountFrequency (%)
3952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 739
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12177
56.5%
Common 9358
43.4%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1719
14.1%
1040
 
8.5%
985
 
8.1%
965
 
7.9%
894
 
7.3%
884
 
7.3%
882
 
7.2%
882
 
7.2%
296
 
2.4%
229
 
1.9%
Other values (206) 3401
27.9%
Common
ValueCountFrequency (%)
3952
42.2%
1 1032
 
11.0%
- 739
 
7.9%
2 585
 
6.3%
0 580
 
6.2%
3 442
 
4.7%
5 356
 
3.8%
4 351
 
3.8%
6 315
 
3.4%
8 303
 
3.2%
Other values (7) 703
 
7.5%
Latin
ValueCountFrequency (%)
B 6
27.3%
A 3
13.6%
T 3
13.6%
C 2
 
9.1%
D 2
 
9.1%
J 2
 
9.1%
P 2
 
9.1%
N 1
 
4.5%
F 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12177
56.5%
ASCII 9380
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3952
42.1%
1 1032
 
11.0%
- 739
 
7.9%
2 585
 
6.2%
0 580
 
6.2%
3 442
 
4.7%
5 356
 
3.8%
4 351
 
3.7%
6 315
 
3.4%
8 303
 
3.2%
Other values (16) 725
 
7.7%
Hangul
ValueCountFrequency (%)
1719
14.1%
1040
 
8.5%
985
 
8.1%
965
 
7.9%
894
 
7.3%
884
 
7.3%
882
 
7.2%
882
 
7.2%
296
 
2.4%
229
 
1.9%
Other values (206) 3401
27.9%

도로명전체주소
Text

MISSING 

Distinct638
Distinct (%)97.9%
Missing231
Missing (%)26.2%
Memory size7.0 KiB
2023-12-11T04:37:38.035129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length28.45092
Min length20

Characters and Unicode

Total characters18550
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

Unique626 ?
Unique (%)96.0%

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 652
 
17.1%
1층 173
 
4.5%
북구 142
 
3.7%
수성구 115
 
3.0%
동구 95
 
2.5%
달서구 88
 
2.3%
2층 72
 
1.9%
달성군 61
 
1.6%
중구 56
 
1.5%
서구 54
 
1.4%
Other values (1067) 2314
60.5%
2023-12-11T04:37:38.933233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3170
 
17.1%
1326
 
7.1%
834
 
4.5%
826
 
4.5%
1 726
 
3.9%
669
 
3.6%
658
 
3.5%
652
 
3.5%
623
 
3.4%
) 621
 
3.3%
Other values (272) 8445
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10537
56.8%
Space Separator 3170
 
17.1%
Decimal Number 2941
 
15.9%
Close Punctuation 621
 
3.3%
Open Punctuation 621
 
3.3%
Other Punctuation 476
 
2.6%
Dash Punctuation 149
 
0.8%
Uppercase Letter 31
 
0.2%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1326
 
12.6%
834
 
7.9%
826
 
7.8%
669
 
6.3%
658
 
6.2%
652
 
6.2%
623
 
5.9%
405
 
3.8%
371
 
3.5%
280
 
2.7%
Other values (245) 3893
36.9%
Decimal Number
ValueCountFrequency (%)
1 726
24.7%
2 469
15.9%
3 367
12.5%
4 278
 
9.5%
5 237
 
8.1%
6 218
 
7.4%
0 196
 
6.7%
7 181
 
6.2%
8 148
 
5.0%
9 121
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 12
38.7%
A 8
25.8%
T 3
 
9.7%
J 3
 
9.7%
P 2
 
6.5%
D 1
 
3.2%
C 1
 
3.2%
N 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 474
99.6%
. 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 621
100.0%
Open Punctuation
ValueCountFrequency (%)
( 621
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10537
56.8%
Common 7980
43.0%
Latin 33
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1326
 
12.6%
834
 
7.9%
826
 
7.8%
669
 
6.3%
658
 
6.2%
652
 
6.2%
623
 
5.9%
405
 
3.8%
371
 
3.5%
280
 
2.7%
Other values (245) 3893
36.9%
Common
ValueCountFrequency (%)
3170
39.7%
1 726
 
9.1%
) 621
 
7.8%
( 621
 
7.8%
, 474
 
5.9%
2 469
 
5.9%
3 367
 
4.6%
4 278
 
3.5%
5 237
 
3.0%
6 218
 
2.7%
Other values (8) 799
 
10.0%
Latin
ValueCountFrequency (%)
B 12
36.4%
A 8
24.2%
T 3
 
9.1%
J 3
 
9.1%
P 2
 
6.1%
e 2
 
6.1%
D 1
 
3.0%
C 1
 
3.0%
N 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10537
56.8%
ASCII 8013
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3170
39.6%
1 726
 
9.1%
) 621
 
7.7%
( 621
 
7.7%
, 474
 
5.9%
2 469
 
5.9%
3 367
 
4.6%
4 278
 
3.5%
5 237
 
3.0%
6 218
 
2.7%
Other values (17) 832
 
10.4%
Hangul
ValueCountFrequency (%)
1326
 
12.6%
834
 
7.9%
826
 
7.8%
669
 
6.3%
658
 
6.2%
652
 
6.2%
623
 
5.9%
405
 
3.8%
371
 
3.5%
280
 
2.7%
Other values (245) 3893
36.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct428
Distinct (%)65.9%
Missing234
Missing (%)26.5%
Infinite0
Infinite (%)0.0%
Mean41980.547
Minimum41000
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:39.135813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41082.6
Q141485
median41947
Q342483
95-th percentile42953.6
Maximum43023
Range2023
Interquartile range (IQR)998

Descriptive statistics

Standard deviation584.56037
Coefficient of variation (CV)0.013924553
Kurtosis-1.1136232
Mean41980.547
Median Absolute Deviation (MAD)470
Skewness0.17107271
Sum27245375
Variance341710.82
MonotonicityNot monotonic
2023-12-11T04:37:39.351576image/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%
42819 5
 
0.6%
41750 5
 
0.6%
42020 5
 
0.6%
41477 5
 
0.6%
42922 5
 
0.6%
Other values (418) 581
65.8%
(Missing) 234
26.5%
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 1
 
0.1%
Distinct821
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2023-12-11T04:37:39.698436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.4869762
Min length2

Characters and Unicode

Total characters5728
Distinct characters526
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

Unique766 ?
Unique (%)86.7%

Sample

1st row샤프한사람들
2nd row로드다이닝(주)
3rd row대한약초
4th row설화
5th row지성건강식품
ValueCountFrequency (%)
주식회사 35
 
3.6%
농업회사법인 7
 
0.7%
5
 
0.5%
선진vfc 3
 
0.3%
산수원 3
 
0.3%
company 3
 
0.3%
아세아그린팜 3
 
0.3%
자연애 3
 
0.3%
international 3
 
0.3%
천상무역(cs 3
 
0.3%
Other values (852) 910
93.0%
2023-12-11T04:37:40.188261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
 
5.3%
) 267
 
4.7%
( 265
 
4.6%
184
 
3.2%
140
 
2.4%
127
 
2.2%
115
 
2.0%
95
 
1.7%
93
 
1.6%
93
 
1.6%
Other values (516) 4045
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4900
85.5%
Close Punctuation 267
 
4.7%
Open Punctuation 265
 
4.6%
Space Separator 95
 
1.7%
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 (%)
304
 
6.2%
184
 
3.8%
140
 
2.9%
127
 
2.6%
115
 
2.3%
93
 
1.9%
93
 
1.9%
90
 
1.8%
80
 
1.6%
76
 
1.6%
Other values (463) 3598
73.4%
Uppercase Letter
ValueCountFrequency (%)
C 16
18.2%
S 14
15.9%
F 13
14.8%
M 5
 
5.7%
N 4
 
4.5%
I 4
 
4.5%
B 4
 
4.5%
V 3
 
3.4%
T 3
 
3.4%
E 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%
e 6
7.4%
l 6
7.4%
y 4
 
4.9%
m 3
 
3.7%
p 3
 
3.7%
Other values (7) 9
11.1%
Decimal Number
ValueCountFrequency (%)
2 3
23.1%
9 3
23.1%
3 2
15.4%
1 2
15.4%
7 1
 
7.7%
4 1
 
7.7%
5 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
& 9
56.2%
. 6
37.5%
, 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 267
100.0%
Open Punctuation
ValueCountFrequency (%)
( 265
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 4902
85.6%
Common 657
 
11.5%
Latin 169
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
304
 
6.2%
184
 
3.8%
140
 
2.9%
127
 
2.6%
115
 
2.3%
93
 
1.9%
93
 
1.9%
90
 
1.8%
80
 
1.6%
76
 
1.6%
Other values (464) 3600
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%
e 6
 
3.6%
l 6
 
3.6%
Other values (28) 64
37.9%
Common
ValueCountFrequency (%)
) 267
40.6%
( 265
40.3%
95
 
14.5%
& 9
 
1.4%
. 6
 
0.9%
2 3
 
0.5%
9 3
 
0.5%
3 2
 
0.3%
1 2
 
0.3%
- 1
 
0.2%
Other values (4) 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4900
85.5%
ASCII 826
 
14.4%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
304
 
6.2%
184
 
3.8%
140
 
2.9%
127
 
2.6%
115
 
2.3%
93
 
1.9%
93
 
1.9%
90
 
1.8%
80
 
1.6%
76
 
1.6%
Other values (463) 3598
73.4%
ASCII
ValueCountFrequency (%)
) 267
32.3%
( 265
32.1%
95
 
11.5%
C 16
 
1.9%
S 14
 
1.7%
n 13
 
1.6%
F 13
 
1.6%
a 11
 
1.3%
t 9
 
1.1%
i 9
 
1.1%
Other values (42) 114
13.8%
None
ValueCountFrequency (%)
2
100.0%

최종수정시점
Real number (ℝ)

Distinct825
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131231 × 1013
Minimum2.0010823 × 1013
Maximum2.019093 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:40.343341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0020628 × 1013
Q12.0090316 × 1013
median2.0150728 × 1013
Q32.0180526 × 1013
95-th percentile2.0190705 × 1013
Maximum2.019093 × 1013
Range1.8010714 × 1011
Interquartile range (IQR)9.0210502 × 1010

Descriptive statistics

Standard deviation5.6799859 × 1010
Coefficient of variation (CV)0.0028214796
Kurtosis-0.85583722
Mean2.0131231 × 1013
Median Absolute Deviation (MAD)3.0500018 × 1010
Skewness-0.73483539
Sum1.7775877 × 1016
Variance3.2262239 × 1021
MonotonicityNot monotonic
2023-12-11T04:37:40.503118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.4%
20021113000000 10
 
1.1%
20020126000000 9
 
1.0%
20021019000000 5
 
0.6%
20020510000000 5
 
0.6%
20020115000000 5
 
0.6%
20021012000000 3
 
0.3%
20060825000000 3
 
0.3%
20140512105112 3
 
0.3%
20041011000000 3
 
0.3%
Other values (815) 825
93.4%
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 (%)
20190930140507 1
0.1%
20190930093231 1
0.1%
20190926170600 1
0.1%
20190923133546 1
0.1%
20190923110924 1
0.1%
20190920092033 1
0.1%
20190917133353 1
0.1%
20190917112815 1
0.1%
20190916141425 1
0.1%
20190916094928 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
I
720 
U
163 

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 720
81.5%
U 163
 
18.5%

Length

2023-12-11T04:37:40.637544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:40.756725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 720
81.5%
u 163
 
18.5%
Distinct135
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2018-08-31 23:59:59
Maximum2019-10-02 02:40:00
2023-12-11T04:37:40.868191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:37:41.007637image/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 size7.0 KiB
유통전문판매업
883 

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 883
100.0%

Length

2023-12-11T04:37:41.182039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:41.301927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 883
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct804
Distinct (%)92.8%
Missing17
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean342786.88
Minimum326032.48
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:41.444287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326032.48
5-th percentile332775.4
Q1339227.25
median342890.81
Q3346503.8
95-th percentile352954.39
Maximum358046.4
Range32013.922
Interquartile range (IQR)7276.5466

Descriptive statistics

Standard deviation5488.5818
Coefficient of variation (CV)0.016011645
Kurtosis0.16762195
Mean342786.88
Median Absolute Deviation (MAD)3640.5046
Skewness-0.023142843
Sum2.9685344 × 108
Variance30124531
MonotonicityNot monotonic
2023-12-11T04:37:41.598747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336590.459071 6
 
0.7%
339320.839241 3
 
0.3%
338421.494971 3
 
0.3%
345687.898519 3
 
0.3%
343157.682044 3
 
0.3%
341215.925853 3
 
0.3%
344010.849417 3
 
0.3%
345206.578526 3
 
0.3%
346942.691097 3
 
0.3%
346193.266936 2
 
0.2%
Other values (794) 834
94.5%
(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%
328874.867518 1
0.1%
328945.225812 1
0.1%
328968.535954 1
0.1%
329092.356185 1
0.1%
ValueCountFrequency (%)
358046.403776 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%
355737.427712 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct804
Distinct (%)92.8%
Missing17
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean263697.22
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:41.807460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile256390.14
Q1261203.43
median264123.72
Q3266249.17
95-th percentile271366.76
Maximum277799.71
Range39492.858
Interquartile range (IQR)5045.7371

Descriptive statistics

Standard deviation4980.3509
Coefficient of variation (CV)0.018886626
Kurtosis4.3917142
Mean263697.22
Median Absolute Deviation (MAD)2709.541
Skewness-1.0315501
Sum2.283618 × 108
Variance24803895
MonotonicityNot monotonic
2023-12-11T04:37:42.007828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257286.897263 6
 
0.7%
265197.142652 3
 
0.3%
260797.727311 3
 
0.3%
266987.666828 3
 
0.3%
261957.795169 3
 
0.3%
260848.360361 3
 
0.3%
263014.492917 3
 
0.3%
260875.577524 3
 
0.3%
263989.847737 3
 
0.3%
264708.839935 2
 
0.2%
Other values (794) 834
94.5%
(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 size7.0 KiB
유통전문판매업
883 

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 883
100.0%

Length

2023-12-11T04:37:42.159910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:42.280117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 883
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
882 
0
 
1

Length

Max length4
Median length4
Mean length3.9966025
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> 882
99.9%
0 1
 
0.1%

Length

2023-12-11T04:37:42.404594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:42.525193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 882
99.9%
0 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
882 
0
 
1

Length

Max length4
Median length4
Mean length3.9966025
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> 882
99.9%
0 1
 
0.1%

Length

2023-12-11T04:37:42.642649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:42.752974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 882
99.9%
0 1
 
0.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
613 
상수도전용
268 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.3057758
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> 613
69.4%
상수도전용 268
30.4%
지하수전용 2
 
0.2%

Length

2023-12-11T04:37:42.916887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:43.049500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 613
69.4%
상수도전용 268
30.4%
지하수전용 2
 
0.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
579 
<NA>
294 
1
 
4
2
 
3
4
 
2

Length

Max length4
Median length1
Mean length1.9988675
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 (%)
0 579
65.6%
<NA> 294
33.3%
1 4
 
0.5%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%

Length

2023-12-11T04:37:43.188148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:43.316449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 579
65.6%
na 294
33.3%
1 4
 
0.5%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%
Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
536 
<NA>
294 
1
 
33
2
 
18
3
 
2

Length

Max length4
Median length1
Mean length1.9988675
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 (%)
0 536
60.7%
<NA> 294
33.3%
1 33
 
3.7%
2 18
 
2.0%
3 2
 
0.2%

Length

2023-12-11T04:37:43.494693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:43.670654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 536
60.7%
na 294
33.3%
1 33
 
3.7%
2 18
 
2.0%
3 2
 
0.2%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.4%
Missing294
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean0.15280136
Minimum0
Maximum20
Zeros548
Zeros (%)62.1%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:43.859774image/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 deviation1.0187426
Coefficient of variation (CV)6.6671045
Kurtosis261.13977
Mean0.15280136
Median Absolute Deviation (MAD)0
Skewness14.632878
Sum90
Variance1.0378365
MonotonicityNot monotonic
2023-12-11T04:37:44.044148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 548
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) 294
33.3%
ValueCountFrequency (%)
0 548
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%
0 548
62.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
0
569 
<NA>
295 
1
 
11
2
 
7
4
 
1

Length

Max length4
Median length1
Mean length2.002265
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 (%)
0 569
64.4%
<NA> 295
33.4%
1 11
 
1.2%
2 7
 
0.8%
4 1
 
0.1%

Length

2023-12-11T04:37:44.246675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:44.432705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 569
64.4%
na 295
33.4%
1 11
 
1.2%
2 7
 
0.8%
4 1
 
0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
585 
자가
170 
임대
128 

Length

Max length4
Median length4
Mean length3.3250283
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> 585
66.3%
자가 170
 
19.3%
임대 128
 
14.5%

Length

2023-12-11T04:37:44.628979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:44.778427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 585
66.3%
자가 170
 
19.3%
임대 128
 
14.5%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
878 
0
 
5

Length

Max length4
Median length4
Mean length3.9830125
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> 878
99.4%
0 5
 
0.6%

Length

2023-12-11T04:37:44.944909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:45.088873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 878
99.4%
0 5
 
0.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
878 
0
 
5

Length

Max length4
Median length4
Mean length3.9830125
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> 878
99.4%
0 5
 
0.6%

Length

2023-12-11T04:37:45.231677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:37:45.372800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 878
99.4%
0 5
 
0.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1015.0 B
False
883 
ValueCountFrequency (%)
False 883
100.0%
2023-12-11T04:37:45.494774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct49
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7055832
Minimum0
Maximum240
Zeros820
Zeros (%)92.9%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-11T04:37:45.654276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation13.098203
Coefficient of variation (CV)7.6796035
Kurtosis224.15654
Mean1.7055832
Median Absolute Deviation (MAD)0
Skewness13.849042
Sum1506.03
Variance171.56292
MonotonicityNot monotonic
2023-12-11T04:37:45.848414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 820
92.9%
3.3 4
 
0.5%
5.0 4
 
0.5%
33.0 3
 
0.3%
10.0 3
 
0.3%
8.0 2
 
0.2%
20.0 2
 
0.2%
6.6 2
 
0.2%
4.5 2
 
0.2%
66.0 2
 
0.2%
Other values (39) 39
 
4.4%
ValueCountFrequency (%)
0.0 820
92.9%
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
 
0.5%
ValueCountFrequency (%)
240.0 1
 
0.1%
222.12 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%
27.0 1
 
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing883
Missing (%)100.0%
Memory size7.9 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
873874유통전문판매업07_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>
874875유통전문판매업07_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>
875876유통전문판매업07_22_17_P34800003480000-113-2018-0000220180607<NA>1영업/정상1영업<NA><NA><NA><NA>053 582 310023.00711821대구광역시 달성군 하빈면 현내리 479번지 1층대구광역시 달성군 하빈면 하빈로90길 6, 1층42902물댄동산 아로니아20180607160202I2018-08-31 23:59:59.0유통전문판매업330537.039615267925.888183유통전문판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
876877유통전문판매업07_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>
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