Overview

Dataset statistics

Number of variables47
Number of observations1168
Missing cells13210
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory463.2 KiB
Average record size in memory406.1 B

Variable types

Numeric13
Categorical17
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description22년02월_6270000_대구광역시_07_22_17_P_유통전문판매업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000092438&dataSetDetailId=DDI_0000092484&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
공장생산직종업원수 is highly imbalanced (55.7%)Imbalance
인허가취소일자 has 1168 (100.0%) missing valuesMissing
폐업일자 has 497 (42.6%) missing valuesMissing
휴업시작일자 has 1168 (100.0%) missing valuesMissing
휴업종료일자 has 1168 (100.0%) missing valuesMissing
재개업일자 has 1168 (100.0%) missing valuesMissing
소재지전화 has 468 (40.1%) missing valuesMissing
소재지면적 has 145 (12.4%) missing valuesMissing
소재지우편번호 has 23 (2.0%) missing valuesMissing
도로명전체주소 has 231 (19.8%) missing valuesMissing
도로명우편번호 has 234 (20.0%) missing valuesMissing
좌표정보(X) has 32 (2.7%) missing valuesMissing
좌표정보(Y) has 32 (2.7%) missing valuesMissing
영업장주변구분명 has 1168 (100.0%) missing valuesMissing
등급구분명 has 1168 (100.0%) missing valuesMissing
본사종업원수 has 345 (29.5%) missing valuesMissing
공장사무직종업원수 has 345 (29.5%) missing valuesMissing
공장판매직종업원수 has 345 (29.5%) missing valuesMissing
전통업소지정번호 has 1168 (100.0%) missing valuesMissing
전통업소주된음식 has 1168 (100.0%) missing valuesMissing
홈페이지 has 1168 (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
본사종업원수 has 808 (69.2%) zerosZeros
공장사무직종업원수 has 754 (64.6%) zerosZeros
공장판매직종업원수 has 782 (67.0%) zerosZeros
시설총규모 has 1084 (92.8%) zerosZeros

Reproduction

Analysis started2024-04-17 17:41:33.044670
Analysis finished2024-04-17 17:41:33.908379
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1168
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean584.5
Minimum1
Maximum1168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:33.960473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile59.35
Q1292.75
median584.5
Q3876.25
95-th percentile1109.65
Maximum1168
Range1167
Interquartile range (IQR)583.5

Descriptive statistics

Standard deviation337.31686
Coefficient of variation (CV)0.57710327
Kurtosis-1.2
Mean584.5
Median Absolute Deviation (MAD)292
Skewness0
Sum682696
Variance113782.67
MonotonicityStrictly increasing
2024-04-18T02:41:34.064396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
769 1
 
0.1%
785 1
 
0.1%
784 1
 
0.1%
783 1
 
0.1%
782 1
 
0.1%
781 1
 
0.1%
780 1
 
0.1%
779 1
 
0.1%
778 1
 
0.1%
Other values (1158) 1158
99.1%
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 (%)
1168 1
0.1%
1167 1
0.1%
1166 1
0.1%
1165 1
0.1%
1164 1
0.1%
1163 1
0.1%
1162 1
0.1%
1161 1
0.1%
1160 1
0.1%
1159 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
유통전문판매업
1168 

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 1168
100.0%

Length

2024-04-18T02:41:34.163475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:34.231884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1168
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
07_22_17_P
1168 

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 1168
100.0%

Length

2024-04-18T02:41:34.301954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:34.371811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 1168
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447628.4
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:34.438821image/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 deviation21597.128
Coefficient of variation (CV)0.0062643433
Kurtosis-1.0950679
Mean3447628.4
Median Absolute Deviation (MAD)20000
Skewness-0.27664433
Sum4.02683 × 109
Variance4.6643594 × 108
MonotonicityIncreasing
2024-04-18T02:41:34.538705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 240
20.5%
3460000 212
18.2%
3420000 177
15.2%
3470000 165
14.1%
3480000 117
10.0%
3410000 98
8.4%
3430000 88
 
7.5%
3440000 71
 
6.1%
ValueCountFrequency (%)
3410000 98
8.4%
3420000 177
15.2%
3430000 88
 
7.5%
3440000 71
 
6.1%
3450000 240
20.5%
3460000 212
18.2%
3470000 165
14.1%
3480000 117
10.0%
ValueCountFrequency (%)
3480000 117
10.0%
3470000 165
14.1%
3460000 212
18.2%
3450000 240
20.5%
3440000 71
 
6.1%
3430000 88
 
7.5%
3420000 177
15.2%
3410000 98
8.4%

관리번호
Text

UNIQUE 

Distinct1168
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2024-04-18T02:41:34.693293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters25696
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

Unique1168 ?
Unique (%)100.0%

Sample

1st row3410000-113-2018-00005
2nd row3410000-113-2016-00002
3rd row3410000-113-2016-00003
4th row3410000-113-2011-00002
5th row3410000-113-2012-00001
ValueCountFrequency (%)
3410000-113-2018-00005 1
 
0.1%
3460000-113-2013-00007 1
 
0.1%
3460000-113-2015-00009 1
 
0.1%
3460000-113-2017-00005 1
 
0.1%
3460000-113-1999-00002 1
 
0.1%
3460000-113-2015-00007 1
 
0.1%
3460000-113-2018-00009 1
 
0.1%
3460000-113-2018-00007 1
 
0.1%
3460000-113-2021-00001 1
 
0.1%
3460000-113-2018-00006 1
 
0.1%
Other values (1158) 1158
99.1%
2024-04-18T02:41:34.949329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10738
41.8%
1 3666
 
14.3%
- 3504
 
13.6%
3 2655
 
10.3%
2 1857
 
7.2%
4 1464
 
5.7%
5 486
 
1.9%
6 418
 
1.6%
7 331
 
1.3%
8 294
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22192
86.4%
Dash Punctuation 3504
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10738
48.4%
1 3666
 
16.5%
3 2655
 
12.0%
2 1857
 
8.4%
4 1464
 
6.6%
5 486
 
2.2%
6 418
 
1.9%
7 331
 
1.5%
8 294
 
1.3%
9 283
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 3504
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25696
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10738
41.8%
1 3666
 
14.3%
- 3504
 
13.6%
3 2655
 
10.3%
2 1857
 
7.2%
4 1464
 
5.7%
5 486
 
1.9%
6 418
 
1.6%
7 331
 
1.3%
8 294
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10738
41.8%
1 3666
 
14.3%
- 3504
 
13.6%
3 2655
 
10.3%
2 1857
 
7.2%
4 1464
 
5.7%
5 486
 
1.9%
6 418
 
1.6%
7 331
 
1.3%
8 294
 
1.1%

인허가일자
Real number (ℝ)

Distinct962
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20134116
Minimum19950510
Maximum20220228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:35.066199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20010446
Q120090413
median20150814
Q320190503
95-th percentile20210909
Maximum20220228
Range269718
Interquartile range (IQR)100090.5

Descriptive statistics

Standard deviation66206.46
Coefficient of variation (CV)0.0032882725
Kurtosis-0.54299298
Mean20134116
Median Absolute Deviation (MAD)49491
Skewness-0.72490054
Sum2.3516647 × 1010
Variance4.3832953 × 109
MonotonicityNot monotonic
2024-04-18T02:41:35.186871image/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%
20190826 4
 
0.3%
20220107 4
 
0.3%
20160712 4
 
0.3%
20151109 3
 
0.3%
20080826 3
 
0.3%
20200617 3
 
0.3%
20161227 3
 
0.3%
Other values (952) 1130
96.7%
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 (%)
20220228 2
0.2%
20220224 1
 
0.1%
20220223 1
 
0.1%
20220214 2
0.2%
20220209 1
 
0.1%
20220127 3
0.3%
20220121 2
0.2%
20220120 2
0.2%
20220119 2
0.2%
20220112 2
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
3
671 
1
497 

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 (%)
3 671
57.4%
1 497
42.6%

Length

2024-04-18T02:41:35.293251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:35.366162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 671
57.4%
1 497
42.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
폐업
671 
영업/정상
497 

Length

Max length5
Median length2
Mean length3.2765411
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 671
57.4%
영업/정상 497
42.6%

Length

2024-04-18T02:41:35.444949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:35.518081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 671
57.4%
영업/정상 497
42.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2
671 
1
497 

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 (%)
2 671
57.4%
1 497
42.6%

Length

2024-04-18T02:41:35.589442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:35.659897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 671
57.4%
1 497
42.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
폐업
671 
영업
497 

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 671
57.4%
영업 497
42.6%

Length

2024-04-18T02:41:35.733199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:35.803131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 671
57.4%
영업 497
42.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct590
Distinct (%)87.9%
Missing497
Missing (%)42.6%
Infinite0
Infinite (%)0.0%
Mean20140786
Minimum20001029
Maximum20220228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:35.886955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040624
Q120090416
median20160307
Q320190817
95-th percentile20211110
Maximum20220228
Range219199
Interquartile range (IQR)100401.5

Descriptive statistics

Standard deviation59110.149
Coefficient of variation (CV)0.0029348482
Kurtosis-1.0989824
Mean20140786
Median Absolute Deviation (MAD)40721
Skewness-0.49906683
Sum1.3514467 × 1010
Variance3.4940097 × 109
MonotonicityNot monotonic
2024-04-18T02:41:35.991320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.4%
20070116 4
 
0.3%
20161229 3
 
0.3%
20201124 3
 
0.3%
20220221 3
 
0.3%
20040830 3
 
0.3%
20051128 3
 
0.3%
20191111 3
 
0.3%
20201229 3
 
0.3%
20191227 3
 
0.3%
Other values (580) 638
54.6%
(Missing) 497
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 (%)
20220228 1
 
0.1%
20220225 1
 
0.1%
20220221 3
0.3%
20220211 1
 
0.1%
20220128 1
 
0.1%
20220125 1
 
0.1%
20220121 2
0.2%
20220119 1
 
0.1%
20220110 1
 
0.1%
20220103 3
0.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

소재지전화
Text

MISSING 

Distinct647
Distinct (%)92.4%
Missing468
Missing (%)40.1%
Memory size9.3 KiB
2024-04-18T02:41:36.194650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.877143
Min length7

Characters and Unicode

Total characters7614
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

Unique600 ?
Unique (%)85.7%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 479
31.8%
070 38
 
2.5%
311 9
 
0.6%
313 8
 
0.5%
625 7
 
0.5%
312 7
 
0.5%
746 7
 
0.5%
9909 6
 
0.4%
755 5
 
0.3%
584 5
 
0.3%
Other values (789) 935
62.1%
2024-04-18T02:41:36.503419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1140
15.0%
0 1116
14.7%
3 1016
13.3%
812
10.7%
2 577
7.6%
1 577
7.6%
7 546
7.2%
8 488
6.4%
6 481
6.3%
4 479
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6802
89.3%
Space Separator 812
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1140
16.8%
0 1116
16.4%
3 1016
14.9%
2 577
8.5%
1 577
8.5%
7 546
8.0%
8 488
7.2%
6 481
7.1%
4 479
7.0%
9 382
 
5.6%
Space Separator
ValueCountFrequency (%)
812
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7614
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1140
15.0%
0 1116
14.7%
3 1016
13.3%
812
10.7%
2 577
7.6%
1 577
7.6%
7 546
7.2%
8 488
6.4%
6 481
6.3%
4 479
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1140
15.0%
0 1116
14.7%
3 1016
13.3%
812
10.7%
2 577
7.6%
1 577
7.6%
7 546
7.2%
8 488
6.4%
6 481
6.3%
4 479
6.3%

소재지면적
Text

MISSING 

Distinct653
Distinct (%)63.8%
Missing145
Missing (%)12.4%
Memory size9.3 KiB
2024-04-18T02:41:36.797879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9462366
Min length3

Characters and Unicode

Total characters5060
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

Unique547 ?
Unique (%)53.5%

Sample

1st row143.01
2nd row5.70
3rd row29.70
4th row71.69
5th row23.56
ValueCountFrequency (%)
00 76
 
7.4%
33.00 26
 
2.5%
3.30 16
 
1.6%
30.00 15
 
1.5%
50.00 12
 
1.2%
16.50 12
 
1.2%
10.00 10
 
1.0%
25.00 10
 
1.0%
20.00 9
 
0.9%
6.60 9
 
0.9%
Other values (643) 828
80.9%
2024-04-18T02:41:37.217648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1225
24.2%
. 1023
20.2%
1 448
 
8.9%
2 411
 
8.1%
3 383
 
7.6%
5 326
 
6.4%
6 287
 
5.7%
4 287
 
5.7%
9 226
 
4.5%
8 225
 
4.4%
Other values (2) 219
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4033
79.7%
Other Punctuation 1027
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1225
30.4%
1 448
 
11.1%
2 411
 
10.2%
3 383
 
9.5%
5 326
 
8.1%
6 287
 
7.1%
4 287
 
7.1%
9 226
 
5.6%
8 225
 
5.6%
7 215
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 1023
99.6%
, 4
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5060
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1225
24.2%
. 1023
20.2%
1 448
 
8.9%
2 411
 
8.1%
3 383
 
7.6%
5 326
 
6.4%
6 287
 
5.7%
4 287
 
5.7%
9 226
 
4.5%
8 225
 
4.4%
Other values (2) 219
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1225
24.2%
. 1023
20.2%
1 448
 
8.9%
2 411
 
8.1%
3 383
 
7.6%
5 326
 
6.4%
6 287
 
5.7%
4 287
 
5.7%
9 226
 
4.5%
8 225
 
4.4%
Other values (2) 219
 
4.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct394
Distinct (%)34.4%
Missing23
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean704443.59
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:37.352675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700802.2
Q1702061
median703830
Q3706220
95-th percentile711833
Maximum711892
Range11882
Interquartile range (IQR)4159

Descriptive statistics

Standard deviation2985.558
Coefficient of variation (CV)0.0042381789
Kurtosis0.6538912
Mean704443.59
Median Absolute Deviation (MAD)1985
Skewness1.0031637
Sum8.0658791 × 108
Variance8913556.4
MonotonicityNot monotonic
2024-04-18T02:41:37.473393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 20
 
1.7%
701824 14
 
1.2%
706818 13
 
1.1%
703100 13
 
1.1%
703830 13
 
1.1%
704080 10
 
0.9%
700230 10
 
0.9%
711814 10
 
0.9%
711851 10
 
0.9%
706838 9
 
0.8%
Other values (384) 1023
87.6%
(Missing) 23
 
2.0%
ValueCountFrequency (%)
700010 2
 
0.2%
700040 5
0.4%
700070 1
 
0.1%
700092 3
 
0.3%
700111 1
 
0.1%
700150 3
 
0.3%
700170 1
 
0.1%
700180 1
 
0.1%
700192 1
 
0.1%
700230 10
0.9%
ValueCountFrequency (%)
711892 2
 
0.2%
711891 5
0.4%
711874 1
 
0.1%
711863 5
0.4%
711858 3
 
0.3%
711856 2
 
0.2%
711855 7
0.6%
711852 3
 
0.3%
711851 10
0.9%
711845 4
 
0.3%
Distinct771
Distinct (%)66.1%
Missing1
Missing (%)0.1%
Memory size9.3 KiB
2024-04-18T02:41:37.721335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length24.055698
Min length16

Characters and Unicode

Total characters28073
Distinct characters268
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

Unique577 ?
Unique (%)49.4%

Sample

1st row대구광역시 중구 봉산동 ****-****번지 지상 *층
2nd row대구광역시 중구 남성로 ****-****번지 지상*층
3rd row대구광역시 중구 봉산동 ****-****번지 메트로프라자 D***
4th row대구광역시 중구 동인동*가 ****-****번지 지상*층
5th row대구광역시 중구 남산동 ****-****번지 지상*층
ValueCountFrequency (%)
대구광역시 1167
21.8%
번지 782
14.6%
398
 
7.4%
북구 240
 
4.5%
수성구 211
 
3.9%
180
 
3.4%
동구 176
 
3.3%
달서구 165
 
3.1%
달성군 118
 
2.2%
중구 98
 
1.8%
Other values (352) 1814
33.9%
2024-04-18T02:41:38.298941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 6029
21.5%
5310
18.9%
2264
 
8.1%
1306
 
4.7%
1279
 
4.6%
1183
 
4.2%
1171
 
4.2%
1167
 
4.2%
- 973
 
3.5%
962
 
3.4%
Other values (258) 6429
22.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15560
55.4%
Other Punctuation 6048
 
21.5%
Space Separator 5310
 
18.9%
Dash Punctuation 973
 
3.5%
Open Punctuation 75
 
0.3%
Close Punctuation 75
 
0.3%
Uppercase Letter 28
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2264
14.6%
1306
 
8.4%
1279
 
8.2%
1183
 
7.6%
1171
 
7.5%
1167
 
7.5%
962
 
6.2%
783
 
5.0%
414
 
2.7%
307
 
2.0%
Other values (237) 4724
30.4%
Uppercase Letter
ValueCountFrequency (%)
B 7
25.0%
T 3
10.7%
A 3
10.7%
J 3
10.7%
D 3
10.7%
P 2
 
7.1%
M 2
 
7.1%
C 2
 
7.1%
N 1
 
3.6%
F 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
* 6029
99.7%
, 16
 
0.3%
/ 2
 
< 0.1%
. 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
d 2
50.0%
s 2
50.0%
Space Separator
ValueCountFrequency (%)
5310
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 973
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15560
55.4%
Common 12481
44.5%
Latin 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2264
14.6%
1306
 
8.4%
1279
 
8.2%
1183
 
7.6%
1171
 
7.5%
1167
 
7.5%
962
 
6.2%
783
 
5.0%
414
 
2.7%
307
 
2.0%
Other values (237) 4724
30.4%
Latin
ValueCountFrequency (%)
B 7
21.9%
T 3
9.4%
A 3
9.4%
J 3
9.4%
D 3
9.4%
P 2
 
6.2%
M 2
 
6.2%
C 2
 
6.2%
d 2
 
6.2%
s 2
 
6.2%
Other values (3) 3
9.4%
Common
ValueCountFrequency (%)
* 6029
48.3%
5310
42.5%
- 973
 
7.8%
( 75
 
0.6%
) 75
 
0.6%
, 16
 
0.1%
/ 2
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15560
55.4%
ASCII 12513
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 6029
48.2%
5310
42.4%
- 973
 
7.8%
( 75
 
0.6%
) 75
 
0.6%
, 16
 
0.1%
B 7
 
0.1%
T 3
 
< 0.1%
A 3
 
< 0.1%
J 3
 
< 0.1%
Other values (11) 19
 
0.2%
Hangul
ValueCountFrequency (%)
2264
14.6%
1306
 
8.4%
1279
 
8.2%
1183
 
7.6%
1171
 
7.5%
1167
 
7.5%
962
 
6.2%
783
 
5.0%
414
 
2.7%
307
 
2.0%
Other values (237) 4724
30.4%

도로명전체주소
Text

MISSING 

Distinct827
Distinct (%)88.3%
Missing231
Missing (%)19.8%
Memory size9.3 KiB
2024-04-18T02:41:38.561742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length29.299893
Min length20

Characters and Unicode

Total characters27454
Distinct characters306
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

Unique737 ?
Unique (%)78.7%

Sample

1st row대구광역시 중구 동성로*길 **, 지상 *층 (봉산동)
2nd row대구광역시 중구 남성로 * (남성로, 지상*층)
3rd row대구광역시 중구 달구벌대로 지하 **** (봉산동, 메트로프라자 D***)
4th row대구광역시 중구 공평로**길 **-**, *층 (동인동*가)
5th row대구광역시 중구 남산로 ** (남산동, 지상*층)
ValueCountFrequency (%)
939
16.6%
대구광역시 937
16.5%
580
 
10.2%
북구 190
 
3.4%
수성구 173
 
3.1%
동구 140
 
2.5%
달서구 128
 
2.3%
115
 
2.0%
달성군 101
 
1.8%
중구 88
 
1.6%
Other values (702) 2276
40.2%
2024-04-18T02:41:38.938734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4730
17.2%
* 4491
16.4%
1899
 
6.9%
1203
 
4.4%
1203
 
4.4%
960
 
3.5%
949
 
3.5%
937
 
3.4%
897
 
3.3%
) 870
 
3.2%
Other values (296) 9315
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15424
56.2%
Other Punctuation 5272
 
19.2%
Space Separator 4730
 
17.2%
Close Punctuation 870
 
3.2%
Open Punctuation 870
 
3.2%
Dash Punctuation 239
 
0.9%
Uppercase Letter 40
 
0.1%
Lowercase Letter 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1899
 
12.3%
1203
 
7.8%
1203
 
7.8%
960
 
6.2%
949
 
6.2%
937
 
6.1%
897
 
5.8%
664
 
4.3%
519
 
3.4%
422
 
2.7%
Other values (274) 5771
37.4%
Uppercase Letter
ValueCountFrequency (%)
B 14
35.0%
A 11
27.5%
J 4
 
10.0%
T 3
 
7.5%
M 2
 
5.0%
D 2
 
5.0%
P 2
 
5.0%
N 1
 
2.5%
H 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
* 4491
85.2%
, 779
 
14.8%
/ 1
 
< 0.1%
. 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
d 2
28.6%
e 2
28.6%
s 2
28.6%
c 1
14.3%
Space Separator
ValueCountFrequency (%)
4730
100.0%
Close Punctuation
ValueCountFrequency (%)
) 870
100.0%
Open Punctuation
ValueCountFrequency (%)
( 870
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 239
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15424
56.2%
Common 11983
43.6%
Latin 47
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1899
 
12.3%
1203
 
7.8%
1203
 
7.8%
960
 
6.2%
949
 
6.2%
937
 
6.1%
897
 
5.8%
664
 
4.3%
519
 
3.4%
422
 
2.7%
Other values (274) 5771
37.4%
Latin
ValueCountFrequency (%)
B 14
29.8%
A 11
23.4%
J 4
 
8.5%
T 3
 
6.4%
d 2
 
4.3%
e 2
 
4.3%
M 2
 
4.3%
s 2
 
4.3%
D 2
 
4.3%
P 2
 
4.3%
Other values (3) 3
 
6.4%
Common
ValueCountFrequency (%)
4730
39.5%
* 4491
37.5%
) 870
 
7.3%
( 870
 
7.3%
, 779
 
6.5%
- 239
 
2.0%
~ 2
 
< 0.1%
/ 1
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15424
56.2%
ASCII 12030
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4730
39.3%
* 4491
37.3%
) 870
 
7.2%
( 870
 
7.2%
, 779
 
6.5%
- 239
 
2.0%
B 14
 
0.1%
A 11
 
0.1%
J 4
 
< 0.1%
T 3
 
< 0.1%
Other values (12) 19
 
0.2%
Hangul
ValueCountFrequency (%)
1899
 
12.3%
1203
 
7.8%
1203
 
7.8%
960
 
6.2%
949
 
6.2%
937
 
6.1%
897
 
5.8%
664
 
4.3%
519
 
3.4%
422
 
2.7%
Other values (274) 5771
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct537
Distinct (%)57.5%
Missing234
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean41999.863
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:39.051495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41076.3
Q141489.25
median41962
Q342490
95-th percentile42969
Maximum43024
Range2024
Interquartile range (IQR)1000.75

Descriptive statistics

Standard deviation594.54234
Coefficient of variation (CV)0.014155816
Kurtosis-1.1303572
Mean41999.863
Median Absolute Deviation (MAD)480
Skewness0.13414464
Sum39227872
Variance353480.59
MonotonicityNot monotonic
2024-04-18T02:41:39.179258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 13
 
1.1%
41485 13
 
1.1%
41934 10
 
0.9%
41750 8
 
0.7%
41937 7
 
0.6%
42974 7
 
0.6%
42922 7
 
0.6%
41260 7
 
0.6%
41472 6
 
0.5%
42162 6
 
0.5%
Other values (527) 850
72.8%
(Missing) 234
 
20.0%
ValueCountFrequency (%)
41000 2
0.2%
41001 1
0.1%
41002 1
0.1%
41007 1
0.1%
41008 2
0.2%
41009 2
0.2%
41015 1
0.1%
41020 2
0.2%
41026 1
0.1%
41027 1
0.1%
ValueCountFrequency (%)
43024 2
0.2%
43023 1
0.1%
43018 1
0.1%
43017 1
0.1%
43014 1
0.1%
43013 1
0.1%
43011 1
0.1%
43010 1
0.1%
43009 1
0.1%
43008 2
0.2%
Distinct1071
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2024-04-18T02:41:39.397393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.6164384
Min length2

Characters and Unicode

Total characters7728
Distinct characters593
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

Unique989 ?
Unique (%)84.7%

Sample

1st row히트방앗간
2nd row대한약초
3rd row설화
4th row지성건강식품
5th row야미고프
ValueCountFrequency (%)
주식회사 63
 
4.8%
농업회사법인 8
 
0.6%
선진vfc 6
 
0.5%
5
 
0.4%
아우노 4
 
0.3%
company 4
 
0.3%
산수원 3
 
0.2%
부경코프레이션 3
 
0.2%
하나그린통상 3
 
0.2%
한미네츄럴 3
 
0.2%
Other values (1116) 1210
92.2%
2024-04-18T02:41:39.712419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
408
 
5.3%
) 338
 
4.4%
( 335
 
4.3%
249
 
3.2%
215
 
2.8%
192
 
2.5%
153
 
2.0%
144
 
1.9%
142
 
1.8%
125
 
1.6%
Other values (583) 5427
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6541
84.6%
Close Punctuation 338
 
4.4%
Open Punctuation 335
 
4.3%
Uppercase Letter 166
 
2.1%
Lowercase Letter 150
 
1.9%
Space Separator 144
 
1.9%
Decimal Number 29
 
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 (%)
408
 
6.2%
249
 
3.8%
215
 
3.3%
192
 
2.9%
153
 
2.3%
142
 
2.2%
125
 
1.9%
118
 
1.8%
107
 
1.6%
103
 
1.6%
Other values (520) 4729
72.3%
Uppercase Letter
ValueCountFrequency (%)
F 23
13.9%
C 20
12.0%
S 19
11.4%
B 9
 
5.4%
N 9
 
5.4%
T 9
 
5.4%
D 8
 
4.8%
I 8
 
4.8%
V 8
 
4.8%
H 7
 
4.2%
Other values (13) 46
27.7%
Lowercase Letter
ValueCountFrequency (%)
e 19
12.7%
a 18
12.0%
n 18
12.0%
o 14
9.3%
i 12
8.0%
t 11
 
7.3%
y 9
 
6.0%
l 8
 
5.3%
r 7
 
4.7%
u 5
 
3.3%
Other values (12) 29
19.3%
Decimal Number
ValueCountFrequency (%)
2 7
24.1%
9 4
13.8%
4 4
13.8%
1 4
13.8%
3 3
10.3%
0 2
 
6.9%
5 2
 
6.9%
6 1
 
3.4%
8 1
 
3.4%
7 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 15
68.2%
. 6
 
27.3%
, 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 335
100.0%
Space Separator
ValueCountFrequency (%)
144
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6542
84.7%
Common 869
 
11.2%
Latin 316
 
4.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
408
 
6.2%
249
 
3.8%
215
 
3.3%
192
 
2.9%
153
 
2.3%
142
 
2.2%
125
 
1.9%
118
 
1.8%
107
 
1.6%
103
 
1.6%
Other values (520) 4730
72.3%
Latin
ValueCountFrequency (%)
F 23
 
7.3%
C 20
 
6.3%
S 19
 
6.0%
e 19
 
6.0%
a 18
 
5.7%
n 18
 
5.7%
o 14
 
4.4%
i 12
 
3.8%
t 11
 
3.5%
B 9
 
2.8%
Other values (35) 153
48.4%
Common
ValueCountFrequency (%)
) 338
38.9%
( 335
38.6%
144
16.6%
& 15
 
1.7%
2 7
 
0.8%
. 6
 
0.7%
9 4
 
0.5%
4 4
 
0.5%
1 4
 
0.5%
3 3
 
0.3%
Other values (7) 9
 
1.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6540
84.6%
ASCII 1185
 
15.3%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
408
 
6.2%
249
 
3.8%
215
 
3.3%
192
 
2.9%
153
 
2.3%
142
 
2.2%
125
 
1.9%
118
 
1.8%
107
 
1.6%
103
 
1.6%
Other values (519) 4728
72.3%
ASCII
ValueCountFrequency (%)
) 338
28.5%
( 335
28.3%
144
12.2%
F 23
 
1.9%
C 20
 
1.7%
S 19
 
1.6%
e 19
 
1.6%
a 18
 
1.5%
n 18
 
1.5%
& 15
 
1.3%
Other values (52) 236
19.9%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1110
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0155118 × 1013
Minimum2.0010823 × 1013
Maximum2.0220228 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:39.822666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0021058 × 1013
Q12.0120184 × 1013
median2.0180916 × 1013
Q32.0201218 × 1013
95-th percentile2.0211229 × 1013
Maximum2.0220228 × 1013
Range2.0940515 × 1011
Interquartile range (IQR)8.1033945 × 1010

Descriptive statistics

Standard deviation6.2106188 × 1010
Coefficient of variation (CV)0.0030814102
Kurtosis-0.42489508
Mean2.0155118 × 1013
Median Absolute Deviation (MAD)2.9896491 × 1010
Skewness-0.95383657
Sum2.3541178 × 1016
Variance3.8571785 × 1021
MonotonicityNot monotonic
2024-04-18T02:41:39.919884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.0%
20021113000000 10
 
0.9%
20020126000000 9
 
0.8%
20020115000000 5
 
0.4%
20021019000000 5
 
0.4%
20020510000000 5
 
0.4%
20140512105112 3
 
0.3%
20021012000000 3
 
0.3%
20041011000000 3
 
0.3%
20060825000000 3
 
0.3%
Other values (1100) 1110
95.0%
ValueCountFrequency (%)
20010823000000 1
 
0.1%
20020115000000 5
0.4%
20020124000000 2
 
0.2%
20020125000000 2
 
0.2%
20020126000000 9
0.8%
20020326000000 1
 
0.1%
20020403000000 1
 
0.1%
20020416000000 1
 
0.1%
20020503000000 1
 
0.1%
20020507000000 1
 
0.1%
ValueCountFrequency (%)
20220228151944 1
0.1%
20220228121320 1
0.1%
20220228113146 1
0.1%
20220225111924 1
0.1%
20220224151140 1
0.1%
20220224150642 1
0.1%
20220223103145 1
0.1%
20220223102949 1
0.1%
20220222093130 1
0.1%
20220221160128 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
I
706 
U
462 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 706
60.4%
U 462
39.6%

Length

2024-04-18T02:41:40.011176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:40.081916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 706
60.4%
u 462
39.6%
Distinct447
Distinct (%)38.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
Minimum2018-08-31 23:59:59
Maximum2022-03-02 02:40:00
2024-04-18T02:41:40.162383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:41:40.264704image/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 size9.3 KiB
유통전문판매업
1168 

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 1168
100.0%

Length

2024-04-18T02:41:40.357709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:40.424478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1168
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1036
Distinct (%)91.2%
Missing32
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean342784.9
Minimum325733.86
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:40.495585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325733.86
5-th percentile332364.98
Q1339218.65
median343278.1
Q3346589.53
95-th percentile352973.2
Maximum358046.4
Range32312.548
Interquartile range (IQR)7370.8807

Descriptive statistics

Standard deviation5669.8588
Coefficient of variation (CV)0.016540573
Kurtosis0.15335769
Mean342784.9
Median Absolute Deviation (MAD)3650.1958
Skewness-0.15479381
Sum3.8940365 × 108
Variance32147299
MonotonicityNot monotonic
2024-04-18T02:41:40.593130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336590.459071 5
 
0.4%
343981.615381 5
 
0.4%
343157.682044 4
 
0.3%
346193.266936 3
 
0.3%
344010.849417 3
 
0.3%
345866.653115 3
 
0.3%
334476.772368 3
 
0.3%
346942.691097 3
 
0.3%
329092.356185 3
 
0.3%
345687.898519 3
 
0.3%
Other values (1026) 1101
94.3%
(Missing) 32
 
2.7%
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%
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%
355875.122869 1
0.1%
355811.748371 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1036
Distinct (%)91.2%
Missing32
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean263500.83
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:40.693948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile255767.53
Q1261210.06
median264071.25
Q3266007.09
95-th percentile271149.46
Maximum277799.71
Range39492.858
Interquartile range (IQR)4797.0241

Descriptive statistics

Standard deviation5129.867
Coefficient of variation (CV)0.019468124
Kurtosis4.7354937
Mean263500.83
Median Absolute Deviation (MAD)2584.8417
Skewness-1.2917344
Sum2.9933694 × 108
Variance26315535
MonotonicityNot monotonic
2024-04-18T02:41:40.798141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257286.897263 5
 
0.4%
264421.75276 5
 
0.4%
261957.795169 4
 
0.3%
264708.839935 3
 
0.3%
263014.492917 3
 
0.3%
261215.496084 3
 
0.3%
260459.894286 3
 
0.3%
263989.847737 3
 
0.3%
253359.522917 3
 
0.3%
266987.666828 3
 
0.3%
Other values (1026) 1101
94.3%
(Missing) 32
 
2.7%
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%
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%
274192.358868 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
유통전문판매업
1168 

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 1168
100.0%

Length

2024-04-18T02:41:40.897002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:40.963710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1168
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
1008 
0
160 

Length

Max length4
Median length4
Mean length3.5890411
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> 1008
86.3%
0 160
 
13.7%

Length

2024-04-18T02:41:41.038755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:41.110361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1008
86.3%
0 160
 
13.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
1008 
0
160 

Length

Max length4
Median length4
Mean length3.5890411
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> 1008
86.3%
0 160
 
13.7%

Length

2024-04-18T02:41:41.187037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:41.260609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1008
86.3%
0 160
 
13.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
860 
상수도전용
306 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.2636986
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 860
73.6%
상수도전용 306
 
26.2%
지하수전용 2
 
0.2%

Length

2024-04-18T02:41:41.335776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:41.409889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 860
73.6%
상수도전용 306
 
26.2%
지하수전용 2
 
0.2%

총종업원수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
1009 
0
159 

Length

Max length4
Median length4
Mean length3.5916096
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> 1009
86.4%
0 159
 
13.6%

Length

2024-04-18T02:41:41.488940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:41.571963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1009
86.4%
0 159
 
13.6%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing345
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean0.036452005
Minimum0
Maximum5
Zeros808
Zeros (%)69.2%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:41.639488image/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 deviation0.32139151
Coefficient of variation (CV)8.8168406
Kurtosis138.17102
Mean0.036452005
Median Absolute Deviation (MAD)0
Skewness11.118811
Sum30
Variance0.10329251
MonotonicityNot monotonic
2024-04-18T02:41:41.713242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 808
69.2%
1 8
 
0.7%
2 3
 
0.3%
4 2
 
0.2%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 345
29.5%
ValueCountFrequency (%)
0 808
69.2%
1 8
 
0.7%
2 3
 
0.3%
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
 
0.3%
1 8
 
0.7%
0 808
69.2%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing345
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean0.12879708
Minimum0
Maximum6
Zeros754
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:41.786175image/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 deviation0.49615003
Coefficient of variation (CV)3.8521837
Kurtosis37.648517
Mean0.12879708
Median Absolute Deviation (MAD)0
Skewness5.2925843
Sum106
Variance0.24616485
MonotonicityNot monotonic
2024-04-18T02:41:41.861129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 754
64.6%
1 43
 
3.7%
2 19
 
1.6%
3 5
 
0.4%
6 1
 
0.1%
4 1
 
0.1%
(Missing) 345
29.5%
ValueCountFrequency (%)
0 754
64.6%
1 43
 
3.7%
2 19
 
1.6%
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
 
1.6%
1 43
 
3.7%
0 754
64.6%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.0%
Missing345
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean0.10935601
Minimum0
Maximum20
Zeros782
Zeros (%)67.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:41.941936image/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 deviation0.86437885
Coefficient of variation (CV)7.9042644
Kurtosis363.99639
Mean0.10935601
Median Absolute Deviation (MAD)0
Skewness17.269389
Sum90
Variance0.7471508
MonotonicityNot monotonic
2024-04-18T02:41:42.022443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 782
67.0%
1 25
 
2.1%
2 10
 
0.9%
3 2
 
0.2%
5 1
 
0.1%
20 1
 
0.1%
4 1
 
0.1%
10 1
 
0.1%
(Missing) 345
29.5%
ValueCountFrequency (%)
0 782
67.0%
1 25
 
2.1%
2 10
 
0.9%
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
 
0.9%
1 25
 
2.1%
0 782
67.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
0
799 
<NA>
346 
1
 
13
2
 
9
4
 
1

Length

Max length4
Median length1
Mean length1.8886986
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 799
68.4%
<NA> 346
29.6%
1 13
 
1.1%
2 9
 
0.8%
4 1
 
0.1%

Length

2024-04-18T02:41:42.121813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:42.200069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 799
68.4%
na 346
29.6%
1 13
 
1.1%
2 9
 
0.8%
4 1
 
0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
734 
자가
285 
임대
149 

Length

Max length4
Median length4
Mean length3.2568493
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> 734
62.8%
자가 285
 
24.4%
임대 149
 
12.8%

Length

2024-04-18T02:41:42.301778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:42.385005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 734
62.8%
자가 285
 
24.4%
임대 149
 
12.8%

보증액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
1004 
0
164 

Length

Max length4
Median length4
Mean length3.5787671
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> 1004
86.0%
0 164
 
14.0%

Length

2024-04-18T02:41:42.463708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:42.536746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1004
86.0%
0 164
 
14.0%

월세액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
<NA>
1004 
0
164 

Length

Max length4
Median length4
Mean length3.5787671
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> 1004
86.0%
0 164
 
14.0%

Length

2024-04-18T02:41:42.611913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:42.692805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1004
86.0%
0 164
 
14.0%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
False
1168 
ValueCountFrequency (%)
False 1168
100.0%
2024-04-18T02:41:42.753277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7361815
Minimum0
Maximum274.38
Zeros1084
Zeros (%)92.8%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-18T02:41:42.830408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.9545
Maximum274.38
Range274.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.075251
Coefficient of variation (CV)8.107016
Kurtosis246.81166
Mean1.7361815
Median Absolute Deviation (MAD)0
Skewness14.70509
Sum2027.86
Variance198.1127
MonotonicityNot monotonic
2024-04-18T02:41:42.928394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1084
92.8%
5.0 5
 
0.4%
3.3 4
 
0.3%
4.0 3
 
0.3%
10.0 3
 
0.3%
33.0 2
 
0.2%
66.0 2
 
0.2%
2.0 2
 
0.2%
6.6 2
 
0.2%
4.5 2
 
0.2%
Other values (57) 59
 
5.1%
ValueCountFrequency (%)
0.0 1084
92.8%
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%
3.0 1
 
0.1%
ValueCountFrequency (%)
274.38 1
0.1%
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%
40.76 1
0.1%
35.0 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1168
Missing (%)100.0%
Memory size10.4 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_22_17_P34100003410000-113-2018-0000520180626<NA>3폐업2폐업20191218<NA><NA><NA><NA>143.01700822대구광역시 중구 봉산동 ****-****번지 지상 *층대구광역시 중구 동성로*길 **, 지상 *층 (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>
12유통전문판매업07_22_17_P34100003410000-113-2016-0000220160427<NA>3폐업2폐업20180314<NA><NA><NA><NA>5.70700230대구광역시 중구 남성로 ****-****번지 지상*층대구광역시 중구 남성로 * (남성로, 지상*층)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>
23유통전문판매업07_22_17_P34100003410000-113-2016-0000320160620<NA>3폐업2폐업20170623<NA><NA><NA><NA>29.70700823대구광역시 중구 봉산동 ****-****번지 메트로프라자 D***대구광역시 중구 달구벌대로 지하 **** (봉산동, 메트로프라자 D***)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>
34유통전문판매업07_22_17_P34100003410000-113-2011-0000220110830<NA>3폐업2폐업20140613<NA><NA><NA>053 746123971.69700421대구광역시 중구 동인동*가 ****-****번지 지상*층대구광역시 중구 공평로**길 **-**, *층 (동인동*가)41911지성건강식품20120201160134I2018-08-31 23:59:59.0유통전문판매업344689.839528264805.59973유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45유통전문판매업07_22_17_P34100003410000-113-2012-0000120120403<NA>3폐업2폐업20140305<NA><NA><NA>16001037<NA>700837대구광역시 중구 남산동 ****-****번지 지상*층대구광역시 중구 남산로 ** (남산동, 지상*층)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>
56유통전문판매업07_22_17_P34100003410000-113-2014-0000220140925<NA>3폐업2폐업20150122<NA><NA><NA><NA>23.56700840대구광역시 중구 달성동 ****-****번지 지상*층대구광역시 중구 태평로 ** (달성동, 지상*층)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>
67유통전문판매업07_22_17_P34100003410000-113-2014-0000420141114<NA>3폐업2폐업20160429<NA><NA><NA>053 2540892120.00700413대구광역시 중구 삼덕동*가 ****번지 지상*층대구광역시 중구 동덕로**길 *** (삼덕동*가, 지상*층)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>
78유통전문판매업07_22_17_P34100003410000-113-2015-0000820150910<NA>3폐업2폐업20180308<NA><NA><NA>053 781266211.54700413대구광역시 중구 삼덕동*가 ****-****번지 지상*층대구광역시 중구 달구벌대로***길 ** (삼덕동*가, 지상*층)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>
89유통전문판매업07_22_17_P34100003410000-113-2016-0000420160628<NA>3폐업2폐업20220119<NA><NA><NA><NA><NA>700230대구광역시 중구 남성로 **** 지상*층대구광역시 중구 달구벌대로***길 ** (남성로, 지상*층)41934영진식품20220119140634U2022-01-21 02:40:00.0유통전문판매업343562.397354264232.568585유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
910유통전문판매업07_22_17_P34100003410000-113-2016-0000520161011<NA>3폐업2폐업20180712<NA><NA><NA><NA>178.70700320대구광역시 중구 대신동 ****-****번지 *층 ***호대구광역시 중구 국채보상로 *** (대신동, *층 ***호)41926웰빙코리아20180712100455I2018-08-31 23:59:59.0유통전문판매업342714.834681264487.841783유통전문판매업<NA><NA><NA><NA><NA><NA>0010<NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
11581159유통전문판매업07_22_17_P34800003480000-113-2017-0000520171030<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00711833대구광역시 달성군 화원읍 설화리 ***-*번지 . *층대구광역시 달성군 화원읍 명천로 ***, *층42957형제베리팜20171030145014I2018-08-31 23:59:59.0유통전문판매업334280.860598255888.547077유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.0<NA><NA><NA>
11591160유통전문판매업07_22_17_P34800003480000-113-2021-0000120210112<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.30<NA>대구광역시 달성군 유가읍 금리 ****-** *층대구광역시 달성군 유가읍 테크노중앙대로*길 **-*, *층43024리앤힐 바이오20211008111540U2021-10-10 02:40:00.0유통전문판매업331679.0242514.0유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11601161유통전문판매업07_22_17_P34800003480000-113-2020-0001720201221<NA>1영업/정상1영업<NA><NA><NA><NA><NA>150.25711814대구광역시 달성군 다사읍 세천리 ****-* *층대구광역시 달성군 다사읍 세천로*길 *, *층42921주식회사 지룩20211027095301U2021-10-29 02:40:00.0유통전문판매업332798.969329264572.080152유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11611162유통전문판매업07_22_17_P34800003480000-113-2019-0000320190418<NA>3폐업2폐업20211125<NA><NA><NA><NA>20.00<NA>대구광역시 달성군 옥포읍 교항리 ****대구광역시 달성군 옥포읍 교항*길 **, *층42969인터푸드20211125093443U2021-11-27 02:40:00.0유통전문판매업330037.52576255756.813647유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11621163유통전문판매업07_22_17_P34800003480000-113-2019-0001220191011<NA>3폐업2폐업20211203<NA><NA><NA><NA>100.00711851대구광역시 달성군 논공읍 금포리 ****-* *층대구광역시 달성군 논공읍 노이길 **-*, *층42975티오피글로벌20211203153303U2021-12-05 02:40:00.0유통전문판매업328779.085065253068.189867유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11631164유통전문판매업07_22_17_P34800003480000-113-2015-0000720150918<NA>3폐업2폐업20210512<NA><NA><NA>032 821 4545.00711855대구광역시 달성군 논공읍 본리리 **-** *층대구광역시 달성군 논공읍 논공로 ***, *층42981주식회사아라인터내셔널20210512101403U2021-05-14 02:40:00.0유통전문판매업331541.808475249475.583994유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
11641165유통전문판매업07_22_17_P34800003480000-113-2020-0000120200108<NA>3폐업2폐업20210722<NA><NA><NA>070 8820200527.00711855대구광역시 달성군 논공읍 본리리 **-***대구광역시 달성군 논공읍 논공로 ***42982(주)산하바이오20210722141543U2021-07-24 02:40:00.0유통전문판매업332327.523657250014.011622유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11651166유통전문판매업07_22_17_P34800003480000-113-2020-0000220200129<NA>3폐업2폐업20200923<NA><NA><NA><NA>31.10<NA>대구광역시 달성군 현풍읍 중리 ***-* *층대구광역시 달성군 현풍읍 테크노중앙대로*길 **-**, *층43014원교푸드20200923135001U2020-09-25 02:40:00.0유통전문판매업331670.0245131.0유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
11661167유통전문판매업07_22_17_P34800003480000-113-2020-0000620200526<NA>3폐업2폐업20211123<NA><NA><NA><NA>12.00711838대구광역시 달성군 화원읍 본리리 ** 외*필지 *층대구광역시 달성군 화원읍 비슬로***길 **-**, *층42964고고락푸드컴퍼니20211123091340U2021-11-25 02:40:00.0유통전문판매업336144.089753257162.22972유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
11671168유통전문판매업07_22_17_P34800003480000-113-2020-0000520200504<NA>3폐업2폐업20210708<NA><NA><NA><NA>65.00711839대구광역시 달성군 화원읍 성산리 ** *층대구광역시 달성군 화원읍 사문진로 ***-**, *층42943투맨푸드20210708104902U2021-07-10 02:40:00.0유통전문판매업334561.11348257547.642664유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>