Overview

Dataset statistics

Number of variables47
Number of observations1241
Missing cells13965
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory492.2 KiB
Average record size in memory406.1 B

Variable types

Numeric13
Categorical17
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description22년08월_6270000_대구광역시_07_22_17_P_유통전문판매업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094290&dataSetDetailId=DDI_0000094302&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
공장생산직직원수 is highly imbalanced (57.3%)Imbalance
인허가취소일자 has 1241 (100.0%) missing valuesMissing
폐업일자 has 543 (43.8%) missing valuesMissing
휴업시작일자 has 1241 (100.0%) missing valuesMissing
휴업종료일자 has 1241 (100.0%) missing valuesMissing
재개업일자 has 1241 (100.0%) missing valuesMissing
소재지전화 has 523 (42.1%) missing valuesMissing
소재지면적 has 153 (12.3%) missing valuesMissing
소재지우편번호 has 25 (2.0%) missing valuesMissing
도로명전체주소 has 230 (18.5%) missing valuesMissing
도로명우편번호 has 233 (18.8%) missing valuesMissing
좌표정보(X) has 37 (3.0%) missing valuesMissing
좌표정보(Y) has 37 (3.0%) missing valuesMissing
영업장주변구분명 has 1241 (100.0%) missing valuesMissing
등급구분명 has 1241 (100.0%) missing valuesMissing
본사직원수 has 338 (27.2%) missing valuesMissing
공장사무직직원수 has 338 (27.2%) missing valuesMissing
공장판매직직원수 has 338 (27.2%) missing valuesMissing
전통업소지정번호 has 1241 (100.0%) missing valuesMissing
전통업소주된음식 has 1241 (100.0%) missing valuesMissing
홈페이지 has 1241 (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
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
본사직원수 has 888 (71.6%) zerosZeros
공장사무직직원수 has 833 (67.1%) zerosZeros
공장판매직직원수 has 861 (69.4%) zerosZeros
시설총규모 has 1148 (92.5%) zerosZeros

Reproduction

Analysis started2024-04-20 15:53:15.627857
Analysis finished2024-04-20 15:53:17.255307
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1241
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean621
Minimum1
Maximum1241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:17.384305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63
Q1311
median621
Q3931
95-th percentile1179
Maximum1241
Range1240
Interquartile range (IQR)620

Descriptive statistics

Standard deviation358.39015
Coefficient of variation (CV)0.57711779
Kurtosis-1.2
Mean621
Median Absolute Deviation (MAD)310
Skewness0
Sum770661
Variance128443.5
MonotonicityStrictly increasing
2024-04-21T00:53:17.643565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
826 1
 
0.1%
833 1
 
0.1%
832 1
 
0.1%
831 1
 
0.1%
830 1
 
0.1%
829 1
 
0.1%
828 1
 
0.1%
827 1
 
0.1%
825 1
 
0.1%
Other values (1231) 1231
99.2%
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 (%)
1241 1
0.1%
1240 1
0.1%
1239 1
0.1%
1238 1
0.1%
1237 1
0.1%
1236 1
0.1%
1235 1
0.1%
1234 1
0.1%
1233 1
0.1%
1232 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
유통전문판매업
1241 

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 1241
100.0%

Length

2024-04-21T00:53:17.878081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:18.039290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1241
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
07_22_17_P
1241 

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 1241
100.0%

Length

2024-04-21T00:53:18.208845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:18.370322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 1241
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447566.5
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:18.516128image/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 deviation21557.327
Coefficient of variation (CV)0.0062529113
Kurtosis-1.0939926
Mean3447566.5
Median Absolute Deviation (MAD)20000
Skewness-0.26762225
Sum4.27843 × 109
Variance4.6471836 × 108
MonotonicityIncreasing
2024-04-21T00:53:18.710454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 254
20.5%
3460000 226
18.2%
3420000 192
15.5%
3470000 171
13.8%
3480000 125
10.1%
3410000 102
8.2%
3430000 90
 
7.3%
3440000 81
 
6.5%
ValueCountFrequency (%)
3410000 102
8.2%
3420000 192
15.5%
3430000 90
 
7.3%
3440000 81
 
6.5%
3450000 254
20.5%
3460000 226
18.2%
3470000 171
13.8%
3480000 125
10.1%
ValueCountFrequency (%)
3480000 125
10.1%
3470000 171
13.8%
3460000 226
18.2%
3450000 254
20.5%
3440000 81
 
6.5%
3430000 90
 
7.3%
3420000 192
15.5%
3410000 102
8.2%

관리번호
Text

UNIQUE 

Distinct1241
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-04-21T00:53:19.335899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters27302
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

Unique1241 ?
Unique (%)100.0%

Sample

1st row3410000-113-2020-00006
2nd row3410000-113-2020-00010
3rd row3410000-113-2018-00003
4th row3410000-113-2018-00004
5th row3410000-113-2018-00005
ValueCountFrequency (%)
3410000-113-2020-00006 1
 
0.1%
3460000-113-2004-00005 1
 
0.1%
3460000-113-2013-00007 1
 
0.1%
3460000-113-2015-00022 1
 
0.1%
3460000-113-2015-00021 1
 
0.1%
3460000-113-2012-00002 1
 
0.1%
3460000-113-2012-00001 1
 
0.1%
3460000-113-2009-00004 1
 
0.1%
3460000-113-2014-00010 1
 
0.1%
3460000-113-2015-00003 1
 
0.1%
Other values (1231) 1231
99.2%
2024-04-21T00:53:20.188810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11370
41.6%
1 3862
 
14.1%
- 3723
 
13.6%
3 2810
 
10.3%
2 2079
 
7.6%
4 1554
 
5.7%
5 509
 
1.9%
6 447
 
1.6%
7 347
 
1.3%
8 309
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23579
86.4%
Dash Punctuation 3723
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11370
48.2%
1 3862
 
16.4%
3 2810
 
11.9%
2 2079
 
8.8%
4 1554
 
6.6%
5 509
 
2.2%
6 447
 
1.9%
7 347
 
1.5%
8 309
 
1.3%
9 292
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3723
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11370
41.6%
1 3862
 
14.1%
- 3723
 
13.6%
3 2810
 
10.3%
2 2079
 
7.6%
4 1554
 
5.7%
5 509
 
1.9%
6 447
 
1.6%
7 347
 
1.3%
8 309
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11370
41.6%
1 3862
 
14.1%
- 3723
 
13.6%
3 2810
 
10.3%
2 2079
 
7.6%
4 1554
 
5.7%
5 509
 
1.9%
6 447
 
1.6%
7 347
 
1.3%
8 309
 
1.1%

인허가일자
Real number (ℝ)

Distinct1008
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20138839
Minimum19950510
Maximum20220831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:20.443272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20010628
Q120090814
median20151116
Q320191118
95-th percentile20220228
Maximum20220831
Range270321
Interquartile range (IQR)100304

Descriptive statistics

Standard deviation67081.922
Coefficient of variation (CV)0.0033309726
Kurtosis-0.47957581
Mean20138839
Median Absolute Deviation (MAD)49501
Skewness-0.75544934
Sum2.4992299 × 1010
Variance4.4999842 × 109
MonotonicityNot monotonic
2024-04-21T00:53:20.707539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170320 5
 
0.4%
20180508 5
 
0.4%
20121105 4
 
0.3%
20220107 4
 
0.3%
20160127 4
 
0.3%
20190826 4
 
0.3%
20160712 4
 
0.3%
20190613 4
 
0.3%
20121204 3
 
0.2%
20220112 3
 
0.2%
Other values (998) 1201
96.8%
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 (%)
20220831 1
0.1%
20220830 2
0.2%
20220825 1
0.1%
20220822 2
0.2%
20220816 1
0.1%
20220812 1
0.1%
20220811 1
0.1%
20220808 1
0.1%
20220803 1
0.1%
20220726 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
3
698 
1
543 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 698
56.2%
1 543
43.8%

Length

2024-04-21T00:53:20.937114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:21.104719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 698
56.2%
1 543
43.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
폐업
698 
영업/정상
543 

Length

Max length5
Median length2
Mean length3.3126511
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 698
56.2%
영업/정상 543
43.8%

Length

2024-04-21T00:53:21.292702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:21.476226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 698
56.2%
영업/정상 543
43.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2
698 
1
543 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 698
56.2%
1 543
43.8%

Length

2024-04-21T00:53:21.651117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:21.819365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 698
56.2%
1 543
43.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
폐업
698 
영업
543 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 698
56.2%
영업 543
43.8%

Length

2024-04-21T00:53:21.992113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:22.159566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 698
56.2%
영업 543
43.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct614
Distinct (%)88.0%
Missing543
Missing (%)43.8%
Infinite0
Infinite (%)0.0%
Mean20143873
Minimum20001029
Maximum20220825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:22.361261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040706
Q120090826
median20160810
Q320191215
95-th percentile20220122
Maximum20220825
Range219796
Interquartile range (IQR)100388.5

Descriptive statistics

Standard deviation59965.186
Coefficient of variation (CV)0.002976845
Kurtosis-1.0611485
Mean20143873
Median Absolute Deviation (MAD)40417.5
Skewness-0.5228992
Sum1.4060423 × 1010
Variance3.5958236 × 109
MonotonicityNot monotonic
2024-04-21T00:53:22.613054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.4%
20070116 4
 
0.3%
20220221 3
 
0.2%
20040830 3
 
0.2%
20201207 3
 
0.2%
20201028 3
 
0.2%
20151229 3
 
0.2%
20220103 3
 
0.2%
20051128 3
 
0.2%
20021224 3
 
0.2%
Other values (604) 665
53.6%
(Missing) 543
43.8%
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
0.2%
20021227 1
 
0.1%
ValueCountFrequency (%)
20220825 1
0.1%
20220823 1
0.1%
20220817 1
0.1%
20220816 1
0.1%
20220808 2
0.2%
20220726 1
0.1%
20220714 1
0.1%
20220711 1
0.1%
20220628 1
0.1%
20220624 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

소재지전화
Text

MISSING 

Distinct661
Distinct (%)92.1%
Missing523
Missing (%)42.1%
Memory size9.8 KiB
2024-04-21T00:53:23.501250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.874652
Min length7

Characters and Unicode

Total characters7808
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

Unique610 ?
Unique (%)85.0%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 489
31.7%
070 40
 
2.6%
311 9
 
0.6%
313 8
 
0.5%
625 7
 
0.5%
746 7
 
0.5%
312 7
 
0.5%
9909 6
 
0.4%
755 5
 
0.3%
584 5
 
0.3%
Other values (806) 959
62.2%
2024-04-21T00:53:24.817096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1168
15.0%
0 1142
14.6%
3 1044
13.4%
830
10.6%
1 595
7.6%
2 593
7.6%
7 566
7.2%
8 496
6.4%
6 494
6.3%
4 487
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6978
89.4%
Space Separator 830
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1168
16.7%
0 1142
16.4%
3 1044
15.0%
1 595
8.5%
2 593
8.5%
7 566
8.1%
8 496
7.1%
6 494
7.1%
4 487
7.0%
9 393
 
5.6%
Space Separator
ValueCountFrequency (%)
830
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7808
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1168
15.0%
0 1142
14.6%
3 1044
13.4%
830
10.6%
1 595
7.6%
2 593
7.6%
7 566
7.2%
8 496
6.4%
6 494
6.3%
4 487
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1168
15.0%
0 1142
14.6%
3 1044
13.4%
830
10.6%
1 595
7.6%
2 593
7.6%
7 566
7.2%
8 496
6.4%
6 494
6.3%
4 487
6.2%

소재지면적
Text

MISSING 

Distinct689
Distinct (%)63.3%
Missing153
Missing (%)12.3%
Memory size9.8 KiB
2024-04-21T00:53:26.088675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9430147
Min length3

Characters and Unicode

Total characters5378
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

Unique581 ?
Unique (%)53.4%

Sample

1st row25.90
2nd row14.76
3rd row4.20
4th row80.00
5th row143.01
ValueCountFrequency (%)
00 79
 
7.3%
33.00 29
 
2.7%
3.30 22
 
2.0%
30.00 17
 
1.6%
16.50 14
 
1.3%
50.00 12
 
1.1%
25.00 12
 
1.1%
10.00 10
 
0.9%
6.60 9
 
0.8%
60.00 8
 
0.7%
Other values (679) 876
80.5%
2024-04-21T00:53:27.597774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1307
24.3%
. 1088
20.2%
1 480
 
8.9%
2 436
 
8.1%
3 414
 
7.7%
5 343
 
6.4%
6 307
 
5.7%
4 305
 
5.7%
9 235
 
4.4%
8 234
 
4.4%
Other values (2) 229
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4286
79.7%
Other Punctuation 1092
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1307
30.5%
1 480
 
11.2%
2 436
 
10.2%
3 414
 
9.7%
5 343
 
8.0%
6 307
 
7.2%
4 305
 
7.1%
9 235
 
5.5%
8 234
 
5.5%
7 225
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 1088
99.6%
, 4
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1307
24.3%
. 1088
20.2%
1 480
 
8.9%
2 436
 
8.1%
3 414
 
7.7%
5 343
 
6.4%
6 307
 
5.7%
4 305
 
5.7%
9 235
 
4.4%
8 234
 
4.4%
Other values (2) 229
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1307
24.3%
. 1088
20.2%
1 480
 
8.9%
2 436
 
8.1%
3 414
 
7.7%
5 343
 
6.4%
6 307
 
5.7%
4 305
 
5.7%
9 235
 
4.4%
8 234
 
4.4%
Other values (2) 229
 
4.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct410
Distinct (%)33.7%
Missing25
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean704449.6
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:27.849314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700803.75
Q1702061
median703830
Q3706220
95-th percentile711833
Maximum711892
Range11882
Interquartile range (IQR)4159

Descriptive statistics

Standard deviation2984.8673
Coefficient of variation (CV)0.0042371622
Kurtosis0.6449339
Mean704449.6
Median Absolute Deviation (MAD)1986.5
Skewness0.99978037
Sum8.5661072 × 108
Variance8909432.5
MonotonicityNot monotonic
2024-04-21T00:53:28.100576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 21
 
1.7%
701824 15
 
1.2%
706818 14
 
1.1%
703830 13
 
1.0%
703100 13
 
1.0%
711814 11
 
0.9%
704080 11
 
0.9%
711851 11
 
0.9%
706220 10
 
0.8%
706803 10
 
0.8%
Other values (400) 1087
87.6%
(Missing) 25
 
2.0%
ValueCountFrequency (%)
700010 2
 
0.2%
700040 5
0.4%
700070 1
 
0.1%
700092 3
 
0.2%
700111 1
 
0.1%
700150 3
 
0.2%
700170 1
 
0.1%
700180 1
 
0.1%
700192 1
 
0.1%
700230 10
0.8%
ValueCountFrequency (%)
711892 2
 
0.2%
711891 5
0.4%
711874 1
 
0.1%
711863 6
0.5%
711862 1
 
0.1%
711858 3
 
0.2%
711856 2
 
0.2%
711855 7
0.6%
711852 3
 
0.2%
711851 11
0.9%
Distinct1169
Distinct (%)94.3%
Missing1
Missing (%)0.1%
Memory size9.8 KiB
2024-04-21T00:53:29.364882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length22.816935
Min length16

Characters and Unicode

Total characters28293
Distinct characters292
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1108 ?
Unique (%)89.4%

Sample

1st row대구광역시 중구 삼덕동2가 0017-0001
2nd row대구광역시 중구 삼덕동3가 0264-0001
3rd row대구광역시 중구 동성로2가 0166-0001 대구백화점건물 지상 11층
4th row대구광역시 중구 대봉동 0188-0009 지상 3층
5th row대구광역시 중구 봉산동 0028-0006 지상 3층
ValueCountFrequency (%)
대구광역시 1240
 
21.8%
북구 254
 
4.5%
수성구 225
 
3.9%
동구 191
 
3.4%
달서구 171
 
3.0%
달성군 126
 
2.2%
중구 102
 
1.8%
서구 90
 
1.6%
1층 88
 
1.5%
남구 81
 
1.4%
Other values (1590) 3133
55.0%
2024-04-21T00:53:30.932142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5661
20.0%
2404
 
8.5%
1 1468
 
5.2%
1392
 
4.9%
1369
 
4.8%
1262
 
4.5%
1244
 
4.4%
1240
 
4.4%
- 1029
 
3.6%
2 847
 
3.0%
Other values (282) 10377
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14970
52.9%
Decimal Number 6418
22.7%
Space Separator 5661
 
20.0%
Dash Punctuation 1029
 
3.6%
Close Punctuation 76
 
0.3%
Open Punctuation 76
 
0.3%
Uppercase Letter 30
 
0.1%
Other Punctuation 29
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2404
16.1%
1392
 
9.3%
1369
 
9.1%
1262
 
8.4%
1244
 
8.3%
1240
 
8.3%
443
 
3.0%
322
 
2.2%
300
 
2.0%
295
 
2.0%
Other values (250) 4699
31.4%
Uppercase Letter
ValueCountFrequency (%)
B 7
23.3%
T 3
10.0%
J 3
10.0%
A 3
10.0%
D 3
10.0%
M 2
 
6.7%
P 2
 
6.7%
C 2
 
6.7%
N 1
 
3.3%
F 1
 
3.3%
Other values (3) 3
10.0%
Decimal Number
ValueCountFrequency (%)
1 1468
22.9%
2 847
13.2%
0 835
13.0%
3 633
9.9%
5 518
 
8.1%
4 484
 
7.5%
8 427
 
6.7%
6 425
 
6.6%
7 413
 
6.4%
9 368
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 26
89.7%
/ 2
 
6.9%
. 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
d 2
50.0%
s 2
50.0%
Space Separator
ValueCountFrequency (%)
5661
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1029
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14970
52.9%
Common 13289
47.0%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2404
16.1%
1392
 
9.3%
1369
 
9.1%
1262
 
8.4%
1244
 
8.3%
1240
 
8.3%
443
 
3.0%
322
 
2.2%
300
 
2.0%
295
 
2.0%
Other values (250) 4699
31.4%
Common
ValueCountFrequency (%)
5661
42.6%
1 1468
 
11.0%
- 1029
 
7.7%
2 847
 
6.4%
0 835
 
6.3%
3 633
 
4.8%
5 518
 
3.9%
4 484
 
3.6%
8 427
 
3.2%
6 425
 
3.2%
Other values (7) 962
 
7.2%
Latin
ValueCountFrequency (%)
B 7
20.6%
T 3
8.8%
J 3
8.8%
A 3
8.8%
D 3
8.8%
d 2
 
5.9%
M 2
 
5.9%
P 2
 
5.9%
C 2
 
5.9%
s 2
 
5.9%
Other values (5) 5
14.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14970
52.9%
ASCII 13323
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5661
42.5%
1 1468
 
11.0%
- 1029
 
7.7%
2 847
 
6.4%
0 835
 
6.3%
3 633
 
4.8%
5 518
 
3.9%
4 484
 
3.6%
8 427
 
3.2%
6 425
 
3.2%
Other values (22) 996
 
7.5%
Hangul
ValueCountFrequency (%)
2404
16.1%
1392
 
9.3%
1369
 
9.1%
1262
 
8.4%
1244
 
8.3%
1240
 
8.3%
443
 
3.0%
322
 
2.2%
300
 
2.0%
295
 
2.0%
Other values (250) 4699
31.4%

도로명전체주소
Text

MISSING 

Distinct978
Distinct (%)96.7%
Missing230
Missing (%)18.5%
Memory size9.8 KiB
2024-04-21T00:53:32.349554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length48
Mean length29.563798
Min length20

Characters and Unicode

Total characters29889
Distinct characters326
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

Unique950 ?
Unique (%)94.0%

Sample

1st row대구광역시 중구 공평로10길 18, 1층 (삼덕동2가)
2nd row대구광역시 중구 달구벌대로445길 44-22, 3층 (삼덕동3가)
3rd row대구광역시 중구 동성로 30, 대구백화점건물 지상 11층 (동성로2가)
4th row대구광역시 중구 동덕로 7, 지상 3층 (대봉동)
5th row대구광역시 중구 동성로1길 52, 지상 3층 (봉산동)
ValueCountFrequency (%)
대구광역시 1011
 
16.4%
1층 314
 
5.1%
북구 204
 
3.3%
수성구 187
 
3.0%
동구 155
 
2.5%
2층 136
 
2.2%
달서구 134
 
2.2%
달성군 110
 
1.8%
중구 92
 
1.5%
3층 76
 
1.2%
Other values (1543) 3738
60.7%
2024-04-21T00:53:34.191049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5146
 
17.2%
2046
 
6.8%
1318
 
4.4%
1300
 
4.3%
1 1248
 
4.2%
1043
 
3.5%
1025
 
3.4%
1011
 
3.4%
969
 
3.2%
( 936
 
3.1%
Other values (316) 13847
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16753
56.1%
Space Separator 5146
 
17.2%
Decimal Number 4943
 
16.5%
Open Punctuation 936
 
3.1%
Close Punctuation 936
 
3.1%
Other Punctuation 871
 
2.9%
Dash Punctuation 252
 
0.8%
Uppercase Letter 43
 
0.1%
Lowercase Letter 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2046
 
12.2%
1318
 
7.9%
1300
 
7.8%
1043
 
6.2%
1025
 
6.1%
1011
 
6.0%
969
 
5.8%
714
 
4.3%
554
 
3.3%
457
 
2.7%
Other values (283) 6316
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 15
34.9%
A 11
25.6%
J 4
 
9.3%
T 3
 
7.0%
M 2
 
4.7%
D 2
 
4.7%
P 2
 
4.7%
N 1
 
2.3%
K 1
 
2.3%
S 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 1248
25.2%
2 803
16.2%
3 572
11.6%
4 435
 
8.8%
5 397
 
8.0%
0 393
 
8.0%
6 342
 
6.9%
7 289
 
5.8%
8 243
 
4.9%
9 221
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
s 2
28.6%
d 2
28.6%
e 2
28.6%
c 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 869
99.8%
/ 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 936
100.0%
Close Punctuation
ValueCountFrequency (%)
) 936
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16753
56.1%
Common 13086
43.8%
Latin 50
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2046
 
12.2%
1318
 
7.9%
1300
 
7.8%
1043
 
6.2%
1025
 
6.1%
1011
 
6.0%
969
 
5.8%
714
 
4.3%
554
 
3.3%
457
 
2.7%
Other values (283) 6316
37.7%
Common
ValueCountFrequency (%)
5146
39.3%
1 1248
 
9.5%
( 936
 
7.2%
) 936
 
7.2%
, 869
 
6.6%
2 803
 
6.1%
3 572
 
4.4%
4 435
 
3.3%
5 397
 
3.0%
0 393
 
3.0%
Other values (8) 1351
 
10.3%
Latin
ValueCountFrequency (%)
B 15
30.0%
A 11
22.0%
J 4
 
8.0%
T 3
 
6.0%
s 2
 
4.0%
d 2
 
4.0%
M 2
 
4.0%
D 2
 
4.0%
P 2
 
4.0%
e 2
 
4.0%
Other values (5) 5
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16753
56.1%
ASCII 13136
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5146
39.2%
1 1248
 
9.5%
( 936
 
7.1%
) 936
 
7.1%
, 869
 
6.6%
2 803
 
6.1%
3 572
 
4.4%
4 435
 
3.3%
5 397
 
3.0%
0 393
 
3.0%
Other values (23) 1401
 
10.7%
Hangul
ValueCountFrequency (%)
2046
 
12.2%
1318
 
7.9%
1300
 
7.8%
1043
 
6.2%
1025
 
6.1%
1011
 
6.0%
969
 
5.8%
714
 
4.3%
554
 
3.3%
457
 
2.7%
Other values (283) 6316
37.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct569
Distinct (%)56.4%
Missing233
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean41999.426
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:34.622320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41075.7
Q141488.75
median41964
Q342490
95-th percentile42969
Maximum43024
Range2024
Interquartile range (IQR)1001.25

Descriptive statistics

Standard deviation596.21067
Coefficient of variation (CV)0.014195686
Kurtosis-1.1412122
Mean41999.426
Median Absolute Deviation (MAD)483.5
Skewness0.12692796
Sum42335421
Variance355467.16
MonotonicityNot monotonic
2024-04-21T00:53:35.093092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 14
 
1.1%
41485 14
 
1.1%
41934 10
 
0.8%
42922 8
 
0.6%
41750 8
 
0.6%
42974 8
 
0.6%
41260 8
 
0.6%
41472 7
 
0.6%
41937 7
 
0.6%
41586 6
 
0.5%
Other values (559) 918
74.0%
(Missing) 233
 
18.8%
ValueCountFrequency (%)
41000 2
0.2%
41001 2
0.2%
41002 1
0.1%
41007 1
0.1%
41008 2
0.2%
41009 2
0.2%
41015 1
0.1%
41020 2
0.2%
41023 1
0.1%
41026 1
0.1%
ValueCountFrequency (%)
43024 3
0.2%
43023 1
 
0.1%
43019 1
 
0.1%
43018 1
 
0.1%
43017 1
 
0.1%
43014 1
 
0.1%
43013 2
0.2%
43011 1
 
0.1%
43010 1
 
0.1%
43009 1
 
0.1%
Distinct1135
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-04-21T00:53:36.139890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.6478646
Min length2

Characters and Unicode

Total characters8250
Distinct characters608
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1046 ?
Unique (%)84.3%

Sample

1st row하우스오브브이(House of V)
2nd row유어밸런스
3rd row토담순두부대백점
4th row주식회사 다다컴퍼니
5th row히트방앗간
ValueCountFrequency (%)
주식회사 75
 
5.4%
농업회사법인 9
 
0.6%
선진vfc 6
 
0.4%
6
 
0.4%
아우노 4
 
0.3%
company 4
 
0.3%
부경코프레이션 3
 
0.2%
international 3
 
0.2%
산수원 3
 
0.2%
한미네츄럴 3
 
0.2%
Other values (1181) 1284
91.7%
2024-04-21T00:53:37.555117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
5.3%
) 354
 
4.3%
( 351
 
4.3%
274
 
3.3%
236
 
2.9%
214
 
2.6%
175
 
2.1%
159
 
1.9%
155
 
1.9%
128
 
1.6%
Other values (598) 5763
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6989
84.7%
Close Punctuation 354
 
4.3%
Open Punctuation 351
 
4.3%
Uppercase Letter 172
 
2.1%
Lowercase Letter 168
 
2.0%
Space Separator 159
 
1.9%
Decimal Number 32
 
0.4%
Other Punctuation 22
 
0.3%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
441
 
6.3%
274
 
3.9%
236
 
3.4%
214
 
3.1%
175
 
2.5%
155
 
2.2%
128
 
1.8%
122
 
1.7%
114
 
1.6%
114
 
1.6%
Other values (535) 5016
71.8%
Uppercase Letter
ValueCountFrequency (%)
F 23
13.4%
C 21
12.2%
S 19
 
11.0%
N 10
 
5.8%
I 9
 
5.2%
B 9
 
5.2%
T 9
 
5.2%
D 9
 
5.2%
V 8
 
4.7%
H 7
 
4.1%
Other values (13) 48
27.9%
Lowercase Letter
ValueCountFrequency (%)
e 21
12.5%
a 20
11.9%
n 20
11.9%
o 18
10.7%
i 13
7.7%
t 11
 
6.5%
l 10
 
6.0%
r 9
 
5.4%
y 9
 
5.4%
u 5
 
3.0%
Other values (12) 32
19.0%
Decimal Number
ValueCountFrequency (%)
2 7
21.9%
9 5
15.6%
1 4
12.5%
4 4
12.5%
3 3
9.4%
0 3
9.4%
5 3
9.4%
6 1
 
3.1%
8 1
 
3.1%
7 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
& 15
68.2%
. 6
 
27.3%
, 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 354
100.0%
Open Punctuation
ValueCountFrequency (%)
( 351
100.0%
Space Separator
ValueCountFrequency (%)
159
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6990
84.7%
Common 919
 
11.1%
Latin 340
 
4.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
441
 
6.3%
274
 
3.9%
236
 
3.4%
214
 
3.1%
175
 
2.5%
155
 
2.2%
128
 
1.8%
122
 
1.7%
114
 
1.6%
114
 
1.6%
Other values (535) 5017
71.8%
Latin
ValueCountFrequency (%)
F 23
 
6.8%
e 21
 
6.2%
C 21
 
6.2%
a 20
 
5.9%
n 20
 
5.9%
S 19
 
5.6%
o 18
 
5.3%
i 13
 
3.8%
t 11
 
3.2%
l 10
 
2.9%
Other values (35) 164
48.2%
Common
ValueCountFrequency (%)
) 354
38.5%
( 351
38.2%
159
17.3%
& 15
 
1.6%
2 7
 
0.8%
. 6
 
0.7%
9 5
 
0.5%
1 4
 
0.4%
4 4
 
0.4%
3 3
 
0.3%
Other values (7) 11
 
1.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6988
84.7%
ASCII 1259
 
15.3%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
441
 
6.3%
274
 
3.9%
236
 
3.4%
214
 
3.1%
175
 
2.5%
155
 
2.2%
128
 
1.8%
122
 
1.7%
114
 
1.6%
114
 
1.6%
Other values (534) 5015
71.8%
ASCII
ValueCountFrequency (%)
) 354
28.1%
( 351
27.9%
159
12.6%
F 23
 
1.8%
e 21
 
1.7%
C 21
 
1.7%
a 20
 
1.6%
n 20
 
1.6%
S 19
 
1.5%
o 18
 
1.4%
Other values (52) 253
20.1%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1183
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0159707 × 1013
Minimum2.0010823 × 1013
Maximum2.0220831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:37.885862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0021113 × 1013
Q12.0120921 × 1013
median2.0190208 × 1013
Q32.0210507 × 1013
95-th percentile2.022053 × 1013
Maximum2.0220831 × 1013
Range2.1000816 × 1011
Interquartile range (IQR)8.9585971 × 1010

Descriptive statistics

Standard deviation6.2672526 × 1010
Coefficient of variation (CV)0.0031088014
Kurtosis-0.30545757
Mean2.0159707 × 1013
Median Absolute Deviation (MAD)2.9597972 × 1010
Skewness-1.0051953
Sum2.5018196 × 1016
Variance3.9278455 × 1021
MonotonicityNot monotonic
2024-04-21T00:53:38.190536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.0%
20021113000000 10
 
0.8%
20020126000000 9
 
0.7%
20020115000000 5
 
0.4%
20021019000000 5
 
0.4%
20020510000000 5
 
0.4%
20060825000000 3
 
0.2%
20140512105112 3
 
0.2%
20041011000000 3
 
0.2%
20021012000000 3
 
0.2%
Other values (1173) 1183
95.3%
ValueCountFrequency (%)
20010823000000 1
 
0.1%
20020115000000 5
0.4%
20020124000000 2
 
0.2%
20020125000000 2
 
0.2%
20020126000000 9
0.7%
20020326000000 1
 
0.1%
20020403000000 1
 
0.1%
20020416000000 1
 
0.1%
20020503000000 1
 
0.1%
20020507000000 1
 
0.1%
ValueCountFrequency (%)
20220831163129 1
0.1%
20220831131741 1
0.1%
20220831100021 1
0.1%
20220830153134 1
0.1%
20220830152041 1
0.1%
20220829170642 1
0.1%
20220826123400 1
0.1%
20220825132402 1
0.1%
20220825114623 1
0.1%
20220824164614 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
I
717 
U
524 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 717
57.8%
U 524
42.2%

Length

2024-04-21T00:53:38.480080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:38.694960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 717
57.8%
u 524
42.2%
Distinct506
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
Minimum2018-08-31 23:59:59
Maximum2022-09-02 02:40:00
2024-04-21T00:53:38.952981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:53:39.275884image/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 size9.8 KiB
유통전문판매업
1241 

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 1241
100.0%

Length

2024-04-21T00:53:39.573021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:39.782808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1241
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1100
Distinct (%)91.4%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean342842.96
Minimum325733.86
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:40.011546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325733.86
5-th percentile332345.25
Q1339307.44
median343340.53
Q3346619.69
95-th percentile353055.11
Maximum358046.4
Range32312.548
Interquartile range (IQR)7312.2505

Descriptive statistics

Standard deviation5699.9009
Coefficient of variation (CV)0.016625399
Kurtosis0.16291652
Mean342842.96
Median Absolute Deviation (MAD)3625.9115
Skewness-0.14530169
Sum4.1278292 × 108
Variance32488870
MonotonicityNot monotonic
2024-04-21T00:53:40.315382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343981.615381 5
 
0.4%
336590.459071 5
 
0.4%
343157.682044 4
 
0.3%
344010.849417 3
 
0.2%
345866.653115 3
 
0.2%
345206.578526 3
 
0.2%
346942.691097 3
 
0.2%
347950.194975 3
 
0.2%
346677.868181 3
 
0.2%
342826.756531 3
 
0.2%
Other values (1090) 1169
94.2%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
325733.855686 1
0.1%
326032.481595 1
0.1%
327448.497282 1
0.1%
327489.324167 1
0.1%
327590.551952 1
0.1%
327723.104095 1
0.1%
327894.698221 1
0.1%
328237.006988 1
0.1%
328453.839356 1
0.1%
328501.384301 1
0.1%
ValueCountFrequency (%)
358046.403776 1
0.1%
357908.12325 1
0.1%
357870.136201 1
0.1%
356698.367083 2
0.2%
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%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1100
Distinct (%)91.4%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean263495.91
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:40.632117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile255754.42
Q1261215.5
median264049.39
Q3265978.51
95-th percentile271294.9
Maximum277799.71
Range39492.858
Interquartile range (IQR)4763.0175

Descriptive statistics

Standard deviation5169.9251
Coefficient of variation (CV)0.019620514
Kurtosis4.6144004
Mean263495.91
Median Absolute Deviation (MAD)2562.9784
Skewness-1.273409
Sum3.1724908 × 108
Variance26728126
MonotonicityNot monotonic
2024-04-21T00:53:40.950633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264421.75276 5
 
0.4%
257286.897263 5
 
0.4%
261957.795169 4
 
0.3%
263014.492917 3
 
0.2%
261215.496084 3
 
0.2%
260875.577524 3
 
0.2%
263989.847737 3
 
0.2%
265687.62574 3
 
0.2%
264714.344433 3
 
0.2%
263824.293143 3
 
0.2%
Other values (1090) 1169
94.2%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
238306.850311 1
0.1%
238531.35408 1
0.1%
238893.829912 1
0.1%
239240.086699 1
0.1%
239536.919741 1
0.1%
240205.085494 1
0.1%
240739.938523 1
0.1%
240811.478411 1
0.1%
242273.0 1
0.1%
242311.21229 1
0.1%
ValueCountFrequency (%)
277799.708684 1
0.1%
277755.206408 2
0.2%
277541.768688 1
0.1%
277428.083074 1
0.1%
276596.005371 1
0.1%
275969.761183 1
0.1%
275787.590179 1
0.1%
274811.331596 1
0.1%
274594.894588 1
0.1%
274508.218106 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
유통전문판매업
1241 

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 1241
100.0%

Length

2024-04-21T00:53:41.587660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:41.883442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1241
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
983 
0
258 

Length

Max length4
Median length4
Mean length3.3763094
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 983
79.2%
0 258
 
20.8%

Length

2024-04-21T00:53:42.222090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:42.539781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 983
79.2%
0 258
 
20.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
983 
0
258 

Length

Max length4
Median length4
Mean length3.3763094
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 983
79.2%
0 258
 
20.8%

Length

2024-04-21T00:53:42.884699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:43.203003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 983
79.2%
0 258
 
20.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
912 
상수도전용
327 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.2651088
Min length4

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> 912
73.5%
상수도전용 327
 
26.3%
지하수전용 2
 
0.2%

Length

2024-04-21T00:53:43.532640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:43.844171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 912
73.5%
상수도전용 327
 
26.3%
지하수전용 2
 
0.2%

총직원수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
984 
0
257 

Length

Max length4
Median length4
Mean length3.3787268
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 984
79.3%
0 257
 
20.7%

Length

2024-04-21T00:53:44.203697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:44.524636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 984
79.3%
0 257
 
20.7%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing338
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean0.033222591
Minimum0
Maximum5
Zeros888
Zeros (%)71.6%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:44.810631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.30698325
Coefficient of variation (CV)9.2401959
Kurtosis151.95138
Mean0.033222591
Median Absolute Deviation (MAD)0
Skewness11.656378
Sum30
Variance0.094238716
MonotonicityNot monotonic
2024-04-21T00:53:45.145074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 888
71.6%
1 8
 
0.6%
2 3
 
0.2%
4 2
 
0.2%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 338
 
27.2%
ValueCountFrequency (%)
0 888
71.6%
1 8
 
0.6%
2 3
 
0.2%
3 1
 
0.1%
4 2
 
0.2%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.2%
3 1
 
0.1%
2 3
 
0.2%
1 8
 
0.6%
0 888
71.6%

공장사무직직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing338
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean0.11849391
Minimum0
Maximum6
Zeros833
Zeros (%)67.1%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:45.455763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4759413
Coefficient of variation (CV)4.0165888
Kurtosis41.211932
Mean0.11849391
Median Absolute Deviation (MAD)0
Skewness5.5330104
Sum107
Variance0.22652012
MonotonicityNot monotonic
2024-04-21T00:53:45.778539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 833
67.1%
1 44
 
3.5%
2 19
 
1.5%
3 5
 
0.4%
6 1
 
0.1%
4 1
 
0.1%
(Missing) 338
27.2%
ValueCountFrequency (%)
0 833
67.1%
1 44
 
3.5%
2 19
 
1.5%
3 5
 
0.4%
4 1
 
0.1%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 1
 
0.1%
3 5
 
0.4%
2 19
 
1.5%
1 44
 
3.5%
0 833
67.1%

공장판매직직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.9%
Missing338
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean0.10077519
Minimum0
Maximum20
Zeros861
Zeros (%)69.4%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:46.112275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.82627947
Coefficient of variation (CV)8.1992347
Kurtosis398.02722
Mean0.10077519
Median Absolute Deviation (MAD)0
Skewness18.045164
Sum91
Variance0.68273776
MonotonicityNot monotonic
2024-04-21T00:53:46.471602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 861
69.4%
1 26
 
2.1%
2 10
 
0.8%
3 2
 
0.2%
5 1
 
0.1%
20 1
 
0.1%
4 1
 
0.1%
10 1
 
0.1%
(Missing) 338
 
27.2%
ValueCountFrequency (%)
0 861
69.4%
1 26
 
2.1%
2 10
 
0.8%
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
 
0.8%
1 26
 
2.1%
0 861
69.4%

공장생산직직원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
0
879 
<NA>
339 
1
 
13
2
 
9
4
 
1

Length

Max length4
Median length1
Mean length1.8195004
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 879
70.8%
<NA> 339
 
27.3%
1 13
 
1.0%
2 9
 
0.7%
4 1
 
0.1%

Length

2024-04-21T00:53:46.877036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:47.205416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 879
70.8%
na 339
 
27.3%
1 13
 
1.0%
2 9
 
0.7%
4 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
765 
자가
313 
임대
163 

Length

Max length4
Median length4
Mean length3.2328767
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> 765
61.6%
자가 313
25.2%
임대 163
 
13.1%

Length

2024-04-21T00:53:47.593569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:47.929926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 765
61.6%
자가 313
25.2%
임대 163
 
13.1%

보증액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
979 
0
262 

Length

Max length4
Median length4
Mean length3.3666398
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 979
78.9%
0 262
 
21.1%

Length

2024-04-21T00:53:48.293117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:48.611720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 979
78.9%
0 262
 
21.1%

월세액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
979 
0
262 

Length

Max length4
Median length4
Mean length3.3666398
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 979
78.9%
0 262
 
21.1%

Length

2024-04-21T00:53:48.957642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:53:49.189235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 979
78.9%
0 262
 
21.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
False
1241 
ValueCountFrequency (%)
False 1241
100.0%
2024-04-21T00:53:49.331237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct72
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0758421
Minimum0
Maximum312.55
Zeros1148
Zeros (%)92.5%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-04-21T00:53:49.636168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum312.55
Range312.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.999201
Coefficient of variation (CV)8.1890629
Kurtosis205.24837
Mean2.0758421
Median Absolute Deviation (MAD)0
Skewness13.560665
Sum2576.12
Variance288.97284
MonotonicityNot monotonic
2024-04-21T00:53:50.069542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1148
92.5%
3.3 7
 
0.6%
5.0 5
 
0.4%
10.0 3
 
0.2%
4.0 3
 
0.2%
6.6 2
 
0.2%
8.0 2
 
0.2%
33.0 2
 
0.2%
2.0 2
 
0.2%
4.5 2
 
0.2%
Other values (62) 65
 
5.2%
ValueCountFrequency (%)
0.0 1148
92.5%
1.0 1
 
0.1%
1.2 1
 
0.1%
2.0 2
 
0.2%
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%
ValueCountFrequency (%)
312.55 1
0.1%
274.38 1
0.1%
240.0 1
0.1%
222.12 1
0.1%
172.72 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%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1241
Missing (%)100.0%
Memory size11.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_22_17_P34100003410000-113-2020-0000620200720<NA>3폐업2폐업20220816<NA><NA><NA><NA>25.90700412대구광역시 중구 삼덕동2가 0017-0001대구광역시 중구 공평로10길 18, 1층 (삼덕동2가)41940하우스오브브이(House of V)20220816170356U2022-08-18 02:40:00.0유통전문판매업344503.721048264249.902082유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12유통전문판매업07_22_17_P34100003410000-113-2020-0001020200831<NA>3폐업2폐업20210415<NA><NA><NA><NA>14.76700413대구광역시 중구 삼덕동3가 0264-0001대구광역시 중구 달구벌대로445길 44-22, 3층 (삼덕동3가)41948유어밸런스20210415172041U2021-04-17 02:40:00.0유통전문판매업345133.885687263875.819382유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23유통전문판매업07_22_17_P34100003410000-113-2018-0000320180420<NA>3폐업2폐업20210708<NA><NA><NA><NA>4.20700716대구광역시 중구 동성로2가 0166-0001 대구백화점건물 지상 11층대구광역시 중구 동성로 30, 대구백화점건물 지상 11층 (동성로2가)41938토담순두부대백점20210709091538U2021-07-11 02:40:00.0유통전문판매업344047.979265264405.128696유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
34유통전문판매업07_22_17_P34100003410000-113-2018-0000420180508<NA>3폐업2폐업20210126<NA><NA><NA><NA>80.00700811대구광역시 중구 대봉동 0188-0009 지상 3층대구광역시 중구 동덕로 7, 지상 3층 (대봉동)41954주식회사 다다컴퍼니20210126154759U2021-01-28 02:40:00.0유통전문판매업344803.668313262942.555066유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45유통전문판매업07_22_17_P34100003410000-113-2018-0000520180626<NA>3폐업2폐업20191218<NA><NA><NA><NA>143.01700822대구광역시 중구 봉산동 0028-0006 지상 3층대구광역시 중구 동성로1길 52, 지상 3층 (봉산동)41943히트방앗간20191218170108U2019-12-20 02:40:00.0유통전문판매업344087.048465264015.597741유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
56유통전문판매업07_22_17_P34100003410000-113-2016-0000220160427<NA>3폐업2폐업20180314<NA><NA><NA><NA>5.70700230대구광역시 중구 남성로 0020-0005 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>
67유통전문판매업07_22_17_P34100003410000-113-2016-0000320160620<NA>3폐업2폐업20170623<NA><NA><NA><NA>29.70700823대구광역시 중구 봉산동 0127-0001 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>
78유통전문판매업07_22_17_P34100003410000-113-2011-0000220110830<NA>3폐업2폐업20140613<NA><NA><NA>053 746123971.69700421대구광역시 중구 동인동1가 0204-0002 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>
89유통전문판매업07_22_17_P34100003410000-113-2012-0000120120403<NA>3폐업2폐업20140305<NA><NA><NA>16001037<NA>700837대구광역시 중구 남산동 2466-0026 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>
910유통전문판매업07_22_17_P34100003410000-113-2014-0000220140925<NA>3폐업2폐업20150122<NA><NA><NA><NA>23.56700840대구광역시 중구 달성동 0145-0007 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>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
12311232유통전문판매업07_22_17_P34800003480000-113-2017-0000320170427<NA>1영업/정상1영업<NA><NA><NA><NA>053 555 229921.00711833대구광역시 달성군 화원읍 설화리 736-3대구광역시 달성군 화원읍 류목정길 56, 1층42957DMG푸드20210408175333U2021-04-10 02:40:00.0유통전문판매업334255.076962255771.102947유통전문판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
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12331234유통전문판매업07_22_17_P34800003480000-113-2021-0000920210415<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00711814대구광역시 달성군 다사읍 세천리 1678-5대구광역시 달성군 다사읍 세천로21길 2742922태광20220831100021U2022-09-02 02:40:00.0유통전문판매업332987.039749264990.963906유통전문판매업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
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12351236유통전문판매업07_22_17_P34800003480000-113-2021-0000120210112<NA>1영업/정상1영업<NA><NA><NA><NA>053267 371721.30<NA>대구광역시 달성군 유가읍 금리 1149-10 1층대구광역시 달성군 유가읍 테크노중앙대로1길 38-6, 1층43024(주)리앤힐바이오20220629170454U2022-07-02 02:40:00.0유통전문판매업331679.0242514.0유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12361237유통전문판매업07_22_17_P34800003480000-113-2020-0001720201221<NA>1영업/정상1영업<NA><NA><NA><NA><NA>150.25711814대구광역시 달성군 다사읍 세천리 1686-2 2층대구광역시 달성군 다사읍 세천로6길 8, 2층42921주식회사 지룩20211027095301U2021-10-29 02:40:00.0유통전문판매업332798.969329264572.080152유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
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