Overview

Dataset statistics

Number of variables47
Number of observations1270
Missing cells14232
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory503.7 KiB
Average record size in memory406.1 B

Variable types

Numeric13
Categorical17
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description22년11월_6270000_대구광역시_07_22_17_P_유통전문판매업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000097155&dataSetDetailId=DDI_0000097187&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 (58.1%)Imbalance
인허가취소일자 has 1270 (100.0%) missing valuesMissing
폐업일자 has 557 (43.9%) missing valuesMissing
휴업시작일자 has 1270 (100.0%) missing valuesMissing
휴업종료일자 has 1270 (100.0%) missing valuesMissing
재개업일자 has 1270 (100.0%) missing valuesMissing
소재지전화 has 544 (42.8%) missing valuesMissing
소재지면적 has 153 (12.0%) missing valuesMissing
소재지우편번호 has 26 (2.0%) missing valuesMissing
도로명전체주소 has 230 (18.1%) missing valuesMissing
도로명우편번호 has 233 (18.3%) missing valuesMissing
좌표정보(X) has 34 (2.7%) missing valuesMissing
좌표정보(Y) has 34 (2.7%) missing valuesMissing
영업장주변구분명 has 1270 (100.0%) missing valuesMissing
등급구분명 has 1270 (100.0%) missing valuesMissing
본사직원수 has 330 (26.0%) missing valuesMissing
공장사무직직원수 has 330 (26.0%) missing valuesMissing
공장판매직직원수 has 330 (26.0%) missing valuesMissing
전통업소지정번호 has 1270 (100.0%) missing valuesMissing
전통업소주된음식 has 1270 (100.0%) missing valuesMissing
홈페이지 has 1270 (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 925 (72.8%) zerosZeros
공장사무직직원수 has 870 (68.5%) zerosZeros
공장판매직직원수 has 897 (70.6%) zerosZeros
시설총규모 has 1173 (92.4%) zerosZeros

Reproduction

Analysis started2024-04-18 08:01:45.832396
Analysis finished2024-04-18 08:01:46.932908
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1270
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean635.5
Minimum1
Maximum1270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:46.997800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile64.45
Q1318.25
median635.5
Q3952.75
95-th percentile1206.55
Maximum1270
Range1269
Interquartile range (IQR)634.5

Descriptive statistics

Standard deviation366.76173
Coefficient of variation (CV)0.5771231
Kurtosis-1.2
Mean635.5
Median Absolute Deviation (MAD)317.5
Skewness0
Sum807085
Variance134514.17
MonotonicityStrictly increasing
2024-04-18T17:01:47.137989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
846 1
 
0.1%
853 1
 
0.1%
852 1
 
0.1%
851 1
 
0.1%
850 1
 
0.1%
849 1
 
0.1%
848 1
 
0.1%
847 1
 
0.1%
845 1
 
0.1%
Other values (1260) 1260
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 (%)
1270 1
0.1%
1269 1
0.1%
1268 1
0.1%
1267 1
0.1%
1266 1
0.1%
1265 1
0.1%
1264 1
0.1%
1263 1
0.1%
1262 1
0.1%
1261 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
유통전문판매업
1270 

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 1270
100.0%

Length

2024-04-18T17:01:47.262712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:47.352413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1270
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
07_22_17_P
1270 

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 1270
100.0%

Length

2024-04-18T17:01:47.448620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:47.548079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 1270
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447551.2
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:47.635819image/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 deviation21647.731
Coefficient of variation (CV)0.0062791616
Kurtosis-1.1014638
Mean3447551.2
Median Absolute Deviation (MAD)20000
Skewness-0.26355344
Sum4.37839 × 109
Variance4.6862425 × 108
MonotonicityIncreasing
2024-04-18T17:01:47.750723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 261
20.6%
3460000 228
18.0%
3420000 198
15.6%
3470000 174
13.7%
3480000 131
10.3%
3410000 106
8.3%
3430000 90
 
7.1%
3440000 82
 
6.5%
ValueCountFrequency (%)
3410000 106
8.3%
3420000 198
15.6%
3430000 90
 
7.1%
3440000 82
 
6.5%
3450000 261
20.6%
3460000 228
18.0%
3470000 174
13.7%
3480000 131
10.3%
ValueCountFrequency (%)
3480000 131
10.3%
3470000 174
13.7%
3460000 228
18.0%
3450000 261
20.6%
3440000 82
 
6.5%
3430000 90
 
7.1%
3420000 198
15.6%
3410000 106
8.3%

관리번호
Text

UNIQUE 

Distinct1270
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
2024-04-18T17:01:47.935646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters27940
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

Unique1270 ?
Unique (%)100.0%

Sample

1st row3410000-113-2021-00009
2nd row3410000-113-2020-00007
3rd row3410000-113-2020-00006
4th row3410000-113-2020-00009
5th row3410000-113-2020-00010
ValueCountFrequency (%)
3410000-113-2021-00009 1
 
0.1%
3460000-113-2013-00009 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%
3460000-113-2006-00004 1
 
0.1%
3460000-113-2004-00005 1
 
0.1%
3460000-113-2014-00003 1
 
0.1%
3460000-113-2012-00011 1
 
0.1%
Other values (1260) 1260
99.2%
2024-04-18T17:01:48.265488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11608
41.5%
1 3949
 
14.1%
- 3810
 
13.6%
3 2871
 
10.3%
2 2179
 
7.8%
4 1586
 
5.7%
5 517
 
1.9%
6 450
 
1.6%
7 353
 
1.3%
8 321
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24130
86.4%
Dash Punctuation 3810
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11608
48.1%
1 3949
 
16.4%
3 2871
 
11.9%
2 2179
 
9.0%
4 1586
 
6.6%
5 517
 
2.1%
6 450
 
1.9%
7 353
 
1.5%
8 321
 
1.3%
9 296
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3810
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11608
41.5%
1 3949
 
14.1%
- 3810
 
13.6%
3 2871
 
10.3%
2 2179
 
7.8%
4 1586
 
5.7%
5 517
 
1.9%
6 450
 
1.6%
7 353
 
1.3%
8 321
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11608
41.5%
1 3949
 
14.1%
- 3810
 
13.6%
3 2871
 
10.3%
2 2179
 
7.8%
4 1586
 
5.7%
5 517
 
1.9%
6 450
 
1.6%
7 353
 
1.3%
8 321
 
1.1%

인허가일자
Real number (ℝ)

Distinct1028
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20140692
Minimum19950510
Maximum20221129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:48.412279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20010710
Q120090917
median20160213
Q320200305
95-th percentile20220504
Maximum20221129
Range270619
Interquartile range (IQR)109388

Descriptive statistics

Standard deviation67413.412
Coefficient of variation (CV)0.0033471249
Kurtosis-0.4564827
Mean20140692
Median Absolute Deviation (MAD)40807.5
Skewness-0.76972884
Sum2.5578679 × 1010
Variance4.5445681 × 109
MonotonicityNot monotonic
2024-04-18T17:01:48.576090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180508 5
 
0.4%
20170320 5
 
0.4%
20190826 4
 
0.3%
20160712 4
 
0.3%
20190613 4
 
0.3%
20121105 4
 
0.3%
20160127 4
 
0.3%
20220107 4
 
0.3%
20150819 3
 
0.2%
20220530 3
 
0.2%
Other values (1018) 1230
96.9%
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 (%)
20221129 1
 
0.1%
20221128 1
 
0.1%
20221124 1
 
0.1%
20221123 1
 
0.1%
20221121 2
0.2%
20221118 1
 
0.1%
20221111 1
 
0.1%
20221108 1
 
0.1%
20221104 3
0.2%
20221101 3
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
3
713 
1
557 

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 (%)
3 713
56.1%
1 557
43.9%

Length

2024-04-18T17:01:48.704383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:49.151887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 713
56.1%
1 557
43.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
폐업
713 
영업/정상
557 

Length

Max length5
Median length2
Mean length3.315748
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 713
56.1%
영업/정상 557
43.9%

Length

2024-04-18T17:01:49.282999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:49.391069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 713
56.1%
영업/정상 557
43.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
2
713 
1
557 

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 (%)
2 713
56.1%
1 557
43.9%

Length

2024-04-18T17:01:49.483740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:49.569734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 713
56.1%
1 557
43.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
폐업
713 
영업
557 

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 713
56.1%
영업 557
43.9%

Length

2024-04-18T17:01:49.669289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:49.759673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 713
56.1%
영업 557
43.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct629
Distinct (%)88.2%
Missing557
Missing (%)43.9%
Infinite0
Infinite (%)0.0%
Mean20145497
Minimum20001029
Maximum20221129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:49.890748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040722
Q120091116
median20161103
Q320200218
95-th percentile20220423
Maximum20221129
Range220100
Interquartile range (IQR)109102

Descriptive statistics

Standard deviation60357.146
Coefficient of variation (CV)0.0029960615
Kurtosis-1.0406921
Mean20145497
Median Absolute Deviation (MAD)40787
Skewness-0.53870955
Sum1.4363739 × 1010
Variance3.6429851 × 109
MonotonicityNot monotonic
2024-04-18T17:01:50.030344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.4%
20070116 4
 
0.3%
20220103 3
 
0.2%
20021224 3
 
0.2%
20201124 3
 
0.2%
20191111 3
 
0.2%
20201229 3
 
0.2%
20161229 3
 
0.2%
20040830 3
 
0.2%
20191227 3
 
0.2%
Other values (619) 680
53.5%
(Missing) 557
43.9%
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 (%)
20221129 1
0.1%
20221125 1
0.1%
20221124 1
0.1%
20221123 1
0.1%
20221122 1
0.1%
20221121 1
0.1%
20221117 1
0.1%
20221115 1
0.1%
20221111 1
0.1%
20221107 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

소재지전화
Text

MISSING 

Distinct667
Distinct (%)91.9%
Missing544
Missing (%)42.8%
Memory size10.1 KiB
2024-04-18T17:01:50.307081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.880165
Min length7

Characters and Unicode

Total characters7899
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

Unique614 ?
Unique (%)84.6%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 494
31.7%
070 40
 
2.6%
311 9
 
0.6%
313 8
 
0.5%
312 7
 
0.4%
625 7
 
0.4%
746 7
 
0.4%
9909 6
 
0.4%
719 5
 
0.3%
755 5
 
0.3%
Other values (814) 971
62.3%
2024-04-18T17:01:50.677935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1183
15.0%
0 1157
14.6%
3 1059
13.4%
839
10.6%
2 600
7.6%
1 600
7.6%
7 573
7.3%
8 498
6.3%
6 497
6.3%
4 493
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7060
89.4%
Space Separator 839
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1183
16.8%
0 1157
16.4%
3 1059
15.0%
2 600
8.5%
1 600
8.5%
7 573
8.1%
8 498
7.1%
6 497
7.0%
4 493
7.0%
9 400
 
5.7%
Space Separator
ValueCountFrequency (%)
839
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7899
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1183
15.0%
0 1157
14.6%
3 1059
13.4%
839
10.6%
2 600
7.6%
1 600
7.6%
7 573
7.3%
8 498
6.3%
6 497
6.3%
4 493
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1183
15.0%
0 1157
14.6%
3 1059
13.4%
839
10.6%
2 600
7.6%
1 600
7.6%
7 573
7.3%
8 498
6.3%
6 497
6.3%
4 493
6.2%

소재지면적
Text

MISSING 

Distinct702
Distinct (%)62.8%
Missing153
Missing (%)12.0%
Memory size10.1 KiB
2024-04-18T17:01:51.020368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9265891
Min length3

Characters and Unicode

Total characters5503
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

Unique591 ?
Unique (%)52.9%

Sample

1st row.00
2nd row9.00
3rd row25.90
4th row12.00
5th row14.76
ValueCountFrequency (%)
00 86
 
7.7%
33.00 29
 
2.6%
3.30 23
 
2.1%
30.00 17
 
1.5%
16.50 14
 
1.3%
50.00 12
 
1.1%
25.00 12
 
1.1%
6.60 11
 
1.0%
10.00 11
 
1.0%
20.00 8
 
0.7%
Other values (692) 894
80.0%
2024-04-18T17:01:51.494835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1341
24.4%
. 1117
20.3%
1 488
 
8.9%
2 446
 
8.1%
3 418
 
7.6%
5 351
 
6.4%
6 317
 
5.8%
4 312
 
5.7%
9 240
 
4.4%
8 238
 
4.3%
Other values (2) 235
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4382
79.6%
Other Punctuation 1121
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1341
30.6%
1 488
 
11.1%
2 446
 
10.2%
3 418
 
9.5%
5 351
 
8.0%
6 317
 
7.2%
4 312
 
7.1%
9 240
 
5.5%
8 238
 
5.4%
7 231
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 1117
99.6%
, 4
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5503
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1341
24.4%
. 1117
20.3%
1 488
 
8.9%
2 446
 
8.1%
3 418
 
7.6%
5 351
 
6.4%
6 317
 
5.8%
4 312
 
5.7%
9 240
 
4.4%
8 238
 
4.3%
Other values (2) 235
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5503
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1341
24.4%
. 1117
20.3%
1 488
 
8.9%
2 446
 
8.1%
3 418
 
7.6%
5 351
 
6.4%
6 317
 
5.8%
4 312
 
5.7%
9 240
 
4.4%
8 238
 
4.3%
Other values (2) 235
 
4.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct415
Distinct (%)33.4%
Missing26
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean704450.36
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:51.660472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700804
Q1702055.75
median703830
Q3706220
95-th percentile711833
Maximum711893
Range11883
Interquartile range (IQR)4164.25

Descriptive statistics

Standard deviation3006.2016
Coefficient of variation (CV)0.0042674428
Kurtosis0.62312976
Mean704450.36
Median Absolute Deviation (MAD)1987
Skewness1.0057185
Sum8.7633625 × 108
Variance9037248.2
MonotonicityNot monotonic
2024-04-18T17:01:51.796257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 22
 
1.7%
701824 15
 
1.2%
706818 14
 
1.1%
703100 13
 
1.0%
703830 13
 
1.0%
706803 11
 
0.9%
704080 11
 
0.9%
711851 11
 
0.9%
711814 11
 
0.9%
706220 10
 
0.8%
Other values (405) 1113
87.6%
(Missing) 26
 
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%
700191 2
 
0.2%
700192 1
 
0.1%
ValueCountFrequency (%)
711893 1
 
0.1%
711892 2
 
0.2%
711891 6
0.5%
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 4
0.3%
Distinct1195
Distinct (%)94.2%
Missing1
Missing (%)0.1%
Memory size10.1 KiB
2024-04-18T17:01:52.133714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length22.875493
Min length16

Characters and Unicode

Total characters29029
Distinct characters295
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

Unique1133 ?
Unique (%)89.3%

Sample

1st row대구광역시 중구 종로2가 0039-0001 3층 302호
2nd row대구광역시 중구 남산동 0937-0011
3rd row대구광역시 중구 삼덕동2가 0017-0001
4th row대구광역시 중구 동문동 0038-0006 패션쥬얼리 전문타운
5th row대구광역시 중구 삼덕동3가 0264-0001
ValueCountFrequency (%)
대구광역시 1269
 
21.7%
북구 261
 
4.5%
수성구 227
 
3.9%
동구 197
 
3.4%
달서구 174
 
3.0%
달성군 132
 
2.3%
중구 106
 
1.8%
서구 90
 
1.5%
1층 87
 
1.5%
남구 82
 
1.4%
Other values (1627) 3226
55.1%
2024-04-18T17:01:52.663167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5808
20.0%
2462
 
8.5%
1 1508
 
5.2%
1426
 
4.9%
1402
 
4.8%
1294
 
4.5%
1273
 
4.4%
1269
 
4.4%
- 1047
 
3.6%
2 871
 
3.0%
Other values (285) 10669
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15379
53.0%
Decimal Number 6577
22.7%
Space Separator 5808
 
20.0%
Dash Punctuation 1047
 
3.6%
Open Punctuation 76
 
0.3%
Close Punctuation 76
 
0.3%
Other Punctuation 32
 
0.1%
Uppercase Letter 30
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2462
16.0%
1426
 
9.3%
1402
 
9.1%
1294
 
8.4%
1273
 
8.3%
1269
 
8.3%
455
 
3.0%
331
 
2.2%
305
 
2.0%
301
 
2.0%
Other values (253) 4861
31.6%
Uppercase Letter
ValueCountFrequency (%)
B 7
23.3%
A 3
10.0%
T 3
10.0%
D 3
10.0%
J 3
10.0%
P 2
 
6.7%
M 2
 
6.7%
C 2
 
6.7%
N 1
 
3.3%
K 1
 
3.3%
Other values (3) 3
10.0%
Decimal Number
ValueCountFrequency (%)
1 1508
22.9%
2 871
13.2%
0 857
13.0%
3 648
9.9%
5 526
 
8.0%
4 489
 
7.4%
8 437
 
6.6%
6 437
 
6.6%
7 428
 
6.5%
9 376
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 29
90.6%
/ 2
 
6.2%
. 1
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
d 2
50.0%
Space Separator
ValueCountFrequency (%)
5808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1047
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15379
53.0%
Common 13616
46.9%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2462
16.0%
1426
 
9.3%
1402
 
9.1%
1294
 
8.4%
1273
 
8.3%
1269
 
8.3%
455
 
3.0%
331
 
2.2%
305
 
2.0%
301
 
2.0%
Other values (253) 4861
31.6%
Common
ValueCountFrequency (%)
5808
42.7%
1 1508
 
11.1%
- 1047
 
7.7%
2 871
 
6.4%
0 857
 
6.3%
3 648
 
4.8%
5 526
 
3.9%
4 489
 
3.6%
8 437
 
3.2%
6 437
 
3.2%
Other values (7) 988
 
7.3%
Latin
ValueCountFrequency (%)
B 7
20.6%
A 3
8.8%
T 3
8.8%
D 3
8.8%
J 3
8.8%
P 2
 
5.9%
M 2
 
5.9%
C 2
 
5.9%
s 2
 
5.9%
d 2
 
5.9%
Other values (5) 5
14.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15379
53.0%
ASCII 13650
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5808
42.5%
1 1508
 
11.0%
- 1047
 
7.7%
2 871
 
6.4%
0 857
 
6.3%
3 648
 
4.7%
5 526
 
3.9%
4 489
 
3.6%
8 437
 
3.2%
6 437
 
3.2%
Other values (22) 1022
 
7.5%
Hangul
ValueCountFrequency (%)
2462
16.0%
1426
 
9.3%
1402
 
9.1%
1294
 
8.4%
1273
 
8.3%
1269
 
8.3%
455
 
3.0%
331
 
2.2%
305
 
2.0%
301
 
2.0%
Other values (253) 4861
31.6%

도로명전체주소
Text

MISSING 

Distinct1006
Distinct (%)96.7%
Missing230
Missing (%)18.1%
Memory size10.1 KiB
2024-04-18T17:01:53.002049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length29.683654
Min length20

Characters and Unicode

Total characters30871
Distinct characters328
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

Unique978 ?
Unique (%)94.0%

Sample

1st row대구광역시 중구 중앙대로77길 45, 3층 302호 (종로2가)
2nd row대구광역시 중구 달구벌대로 2078, 5층 (남산동)
3rd row대구광역시 중구 공평로10길 18, 1층 (삼덕동2가)
4th row대구광역시 중구 경상감영길 176, 패션쥬얼리 전문타운 2층 (동문동)
5th row대구광역시 중구 달구벌대로445길 44-22, 3층 (삼덕동3가)
ValueCountFrequency (%)
대구광역시 1040
 
16.4%
1층 318
 
5.0%
북구 211
 
3.3%
수성구 189
 
3.0%
동구 161
 
2.5%
2층 146
 
2.3%
달서구 137
 
2.2%
달성군 116
 
1.8%
중구 96
 
1.5%
3층 78
 
1.2%
Other values (1582) 3866
60.8%
2024-04-18T17:01:53.476562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5318
 
17.2%
2106
 
6.8%
1364
 
4.4%
1336
 
4.3%
1 1303
 
4.2%
1075
 
3.5%
1054
 
3.4%
1040
 
3.4%
1000
 
3.2%
( 961
 
3.1%
Other values (318) 14314
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17286
56.0%
Space Separator 5318
 
17.2%
Decimal Number 5130
 
16.6%
Open Punctuation 961
 
3.1%
Close Punctuation 961
 
3.1%
Other Punctuation 903
 
2.9%
Dash Punctuation 260
 
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 (%)
2106
 
12.2%
1364
 
7.9%
1336
 
7.7%
1075
 
6.2%
1054
 
6.1%
1040
 
6.0%
1000
 
5.8%
733
 
4.2%
568
 
3.3%
470
 
2.7%
Other values (285) 6540
37.8%
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 1303
25.4%
2 840
16.4%
3 586
11.4%
4 447
 
8.7%
0 421
 
8.2%
5 411
 
8.0%
6 349
 
6.8%
7 299
 
5.8%
8 250
 
4.9%
9 224
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
d 2
28.6%
s 2
28.6%
c 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 901
99.8%
/ 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 961
100.0%
Close Punctuation
ValueCountFrequency (%)
) 961
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 260
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17286
56.0%
Common 13535
43.8%
Latin 50
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2106
 
12.2%
1364
 
7.9%
1336
 
7.7%
1075
 
6.2%
1054
 
6.1%
1040
 
6.0%
1000
 
5.8%
733
 
4.2%
568
 
3.3%
470
 
2.7%
Other values (285) 6540
37.8%
Common
ValueCountFrequency (%)
5318
39.3%
1 1303
 
9.6%
( 961
 
7.1%
) 961
 
7.1%
, 901
 
6.7%
2 840
 
6.2%
3 586
 
4.3%
4 447
 
3.3%
0 421
 
3.1%
5 411
 
3.0%
Other values (8) 1386
 
10.2%
Latin
ValueCountFrequency (%)
B 15
30.0%
A 11
22.0%
J 4
 
8.0%
T 3
 
6.0%
M 2
 
4.0%
D 2
 
4.0%
e 2
 
4.0%
P 2
 
4.0%
d 2
 
4.0%
s 2
 
4.0%
Other values (5) 5
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17286
56.0%
ASCII 13585
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5318
39.1%
1 1303
 
9.6%
( 961
 
7.1%
) 961
 
7.1%
, 901
 
6.6%
2 840
 
6.2%
3 586
 
4.3%
4 447
 
3.3%
0 421
 
3.1%
5 411
 
3.0%
Other values (23) 1436
 
10.6%
Hangul
ValueCountFrequency (%)
2106
 
12.2%
1364
 
7.9%
1336
 
7.7%
1075
 
6.2%
1054
 
6.1%
1040
 
6.0%
1000
 
5.8%
733
 
4.2%
568
 
3.3%
470
 
2.7%
Other values (285) 6540
37.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct580
Distinct (%)55.9%
Missing233
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean41999.18
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:53.612718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41080.2
Q141487
median41962
Q342490
95-th percentile42970
Maximum43024
Range2024
Interquartile range (IQR)1003

Descriptive statistics

Standard deviation598.5619
Coefficient of variation (CV)0.014251752
Kurtosis-1.1486041
Mean41999.18
Median Absolute Deviation (MAD)484
Skewness0.13543143
Sum43553150
Variance358276.35
MonotonicityNot monotonic
2024-04-18T17:01:53.753466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 15
 
1.2%
41490 14
 
1.1%
41934 10
 
0.8%
41260 8
 
0.6%
42922 8
 
0.6%
42974 8
 
0.6%
41750 8
 
0.6%
41937 7
 
0.6%
41472 7
 
0.6%
42819 6
 
0.5%
Other values (570) 946
74.5%
(Missing) 233
 
18.3%
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%
Distinct1162
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
2024-04-18T17:01:53.993598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.6464567
Min length2

Characters and Unicode

Total characters8441
Distinct characters612
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

Unique1071 ?
Unique (%)84.3%

Sample

1st row뷰티(View Tea)
2nd row데일리케어컴퍼니
3rd row하우스오브브이(House of V)
4th row리브유
5th row유어밸런스
ValueCountFrequency (%)
주식회사 79
 
5.5%
농업회사법인 9
 
0.6%
선진vfc 6
 
0.4%
6
 
0.4%
company 4
 
0.3%
아우노 4
 
0.3%
주)프로페셔널 3
 
0.2%
자연애 3
 
0.2%
아세아그린팜 3
 
0.2%
하나그린통상 3
 
0.2%
Other values (1208) 1315
91.6%
2024-04-18T17:01:54.368084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
450
 
5.3%
) 361
 
4.3%
( 359
 
4.3%
283
 
3.4%
242
 
2.9%
220
 
2.6%
180
 
2.1%
165
 
2.0%
161
 
1.9%
133
 
1.6%
Other values (602) 5887
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7146
84.7%
Close Punctuation 361
 
4.3%
Open Punctuation 359
 
4.3%
Uppercase Letter 187
 
2.2%
Lowercase Letter 168
 
2.0%
Space Separator 165
 
2.0%
Decimal Number 29
 
0.3%
Other Punctuation 23
 
0.3%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
450
 
6.3%
283
 
4.0%
242
 
3.4%
220
 
3.1%
180
 
2.5%
161
 
2.3%
133
 
1.9%
123
 
1.7%
120
 
1.7%
116
 
1.6%
Other values (539) 5118
71.6%
Uppercase Letter
ValueCountFrequency (%)
F 25
13.4%
C 21
11.2%
S 21
11.2%
N 12
 
6.4%
D 11
 
5.9%
T 10
 
5.3%
B 10
 
5.3%
I 9
 
4.8%
V 8
 
4.3%
O 8
 
4.3%
Other values (13) 52
27.8%
Lowercase Letter
ValueCountFrequency (%)
e 21
12.5%
n 20
11.9%
a 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
24.1%
1 4
13.8%
4 4
13.8%
9 4
13.8%
3 3
10.3%
5 2
 
6.9%
0 2
 
6.9%
8 1
 
3.4%
6 1
 
3.4%
7 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 16
69.6%
. 6
 
26.1%
, 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 361
100.0%
Open Punctuation
ValueCountFrequency (%)
( 359
100.0%
Space Separator
ValueCountFrequency (%)
165
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7147
84.7%
Common 938
 
11.1%
Latin 355
 
4.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
450
 
6.3%
283
 
4.0%
242
 
3.4%
220
 
3.1%
180
 
2.5%
161
 
2.3%
133
 
1.9%
123
 
1.7%
120
 
1.7%
116
 
1.6%
Other values (539) 5119
71.6%
Latin
ValueCountFrequency (%)
F 25
 
7.0%
e 21
 
5.9%
C 21
 
5.9%
S 21
 
5.9%
n 20
 
5.6%
a 20
 
5.6%
o 18
 
5.1%
i 13
 
3.7%
N 12
 
3.4%
D 11
 
3.1%
Other values (35) 173
48.7%
Common
ValueCountFrequency (%)
) 361
38.5%
( 359
38.3%
165
17.6%
& 16
 
1.7%
2 7
 
0.7%
. 6
 
0.6%
1 4
 
0.4%
4 4
 
0.4%
9 4
 
0.4%
3 3
 
0.3%
Other values (7) 9
 
1.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7145
84.6%
ASCII 1293
 
15.3%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
450
 
6.3%
283
 
4.0%
242
 
3.4%
220
 
3.1%
180
 
2.5%
161
 
2.3%
133
 
1.9%
123
 
1.7%
120
 
1.7%
116
 
1.6%
Other values (538) 5117
71.6%
ASCII
ValueCountFrequency (%)
) 361
27.9%
( 359
27.8%
165
12.8%
F 25
 
1.9%
e 21
 
1.6%
C 21
 
1.6%
S 21
 
1.6%
n 20
 
1.5%
a 20
 
1.5%
o 18
 
1.4%
Other values (52) 262
20.3%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1212
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.016148 × 1013
Minimum2.0010823 × 1013
Maximum2.0221129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:54.504365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0021113 × 1013
Q12.0121226 × 1013
median2.0190328 × 1013
Q32.0210709 × 1013
95-th percentile2.0220872 × 1013
Maximum2.0221129 × 1013
Range2.1030617 × 1011
Interquartile range (IQR)8.9482721 × 1010

Descriptive statistics

Standard deviation6.2892963 × 1010
Coefficient of variation (CV)0.0031194616
Kurtosis-0.26031503
Mean2.016148 × 1013
Median Absolute Deviation (MAD)2.9887974 × 1010
Skewness-1.0247398
Sum2.560508 × 1016
Variance3.9555248 × 1021
MonotonicityNot monotonic
2024-04-18T17:01:54.626483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
0.9%
20021113000000 10
 
0.8%
20020126000000 9
 
0.7%
20021019000000 5
 
0.4%
20020510000000 5
 
0.4%
20020115000000 5
 
0.4%
20140512105112 3
 
0.2%
20060825000000 3
 
0.2%
20021012000000 3
 
0.2%
20041011000000 3
 
0.2%
Other values (1202) 1212
95.4%
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 (%)
20221129171227 1
0.1%
20221129170152 1
0.1%
20221129153152 1
0.1%
20221128114232 1
0.1%
20221125143505 1
0.1%
20221124160539 1
0.1%
20221124113231 1
0.1%
20221123152030 1
0.1%
20221123112222 1
0.1%
20221123102903 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
I
719 
U
551 

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 719
56.6%
U 551
43.4%

Length

2024-04-18T17:01:54.741922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:54.833506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 719
56.6%
u 551
43.4%
Distinct527
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
Minimum2018-08-31 23:59:59
Maximum2022-12-01 02:40:00
2024-04-18T17:01:54.937943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T17:01:55.077570image/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 size10.1 KiB
유통전문판매업
1270 

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 1270
100.0%

Length

2024-04-18T17:01:55.208323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:55.295253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1270
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1122
Distinct (%)90.8%
Missing34
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean342888.89
Minimum323859.83
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:55.387358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323859.83
5-th percentile332364.98
Q1339307.1
median343426.5
Q3346634.85
95-th percentile353078.97
Maximum358046.4
Range34186.574
Interquartile range (IQR)7327.7523

Descriptive statistics

Standard deviation5697.7787
Coefficient of variation (CV)0.016616982
Kurtosis0.17581651
Mean342888.89
Median Absolute Deviation (MAD)3602.2176
Skewness-0.13808145
Sum4.2381067 × 108
Variance32464682
MonotonicityNot monotonic
2024-04-18T17:01:55.514421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
347950.194974987 5
 
0.4%
343981.615381126 5
 
0.4%
336590.459070581 5
 
0.4%
343157.682044362 4
 
0.3%
342826.75653139 3
 
0.2%
334476.772367791 3
 
0.2%
346677.868181036 3
 
0.2%
344010.84941716 3
 
0.2%
339320.83924135 3
 
0.2%
341215.925853297 3
 
0.2%
Other values (1112) 1199
94.4%
(Missing) 34
 
2.7%
ValueCountFrequency (%)
323859.830021514 1
0.1%
325733.855685744 1
0.1%
326032.481594907 1
0.1%
327448.497282442 1
0.1%
327489.324166674 1
0.1%
327590.551952401 1
0.1%
327723.743609075 1
0.1%
327894.698221242 1
0.1%
328237.006988233 1
0.1%
328453.839355586 1
0.1%
ValueCountFrequency (%)
358046.403776034 1
0.1%
357908.123249657 1
0.1%
357870.136201308 1
0.1%
356698.367083593 2
0.2%
356588.107240614 1
0.1%
356477.570167987 1
0.1%
356353.915440362 1
0.1%
356331.11092277 1
0.1%
356325.33935912 1
0.1%
356032.203863692 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1122
Distinct (%)90.8%
Missing34
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean263480.13
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:55.641546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile255819.89
Q1261220.37
median264094.8
Q3266007.09
95-th percentile271300.13
Maximum277799.71
Range39492.858
Interquartile range (IQR)4786.7182

Descriptive statistics

Standard deviation5302.02
Coefficient of variation (CV)0.020123036
Kurtosis4.7700626
Mean263480.13
Median Absolute Deviation (MAD)2604.2841
Skewness-1.3860886
Sum3.2566144 × 108
Variance28111416
MonotonicityNot monotonic
2024-04-18T17:01:55.781086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
265687.625739554 5
 
0.4%
264421.752760284 5
 
0.4%
257286.897263086 5
 
0.4%
261957.795169076 4
 
0.3%
263824.293143197 3
 
0.2%
260459.894286451 3
 
0.2%
264714.344433082 3
 
0.2%
263014.492917054 3
 
0.2%
265197.142651548 3
 
0.2%
260848.360360923 3
 
0.2%
Other values (1112) 1199
94.4%
(Missing) 34
 
2.7%
ValueCountFrequency (%)
238306.8503106 1
0.1%
238531.354079775 1
0.1%
238893.829911915 1
0.1%
239193.193196123 1
0.1%
239536.919741222 1
0.1%
240205.085493659 1
0.1%
240739.938522968 1
0.1%
240813.150041343 1
0.1%
241221.080539637 2
0.2%
242257.668367543 1
0.1%
ValueCountFrequency (%)
277799.708684077 1
0.1%
277755.206407657 2
0.2%
277541.768687529 1
0.1%
277428.083074127 1
0.1%
276596.005371307 1
0.1%
275969.761183465 1
0.1%
275787.590179158 1
0.1%
274811.331596085 1
0.1%
274594.894588392 1
0.1%
274508.218106082 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
유통전문판매업
1270 

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 1270
100.0%

Length

2024-04-18T17:01:55.907120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:55.991707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1270
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
967 
0
303 

Length

Max length4
Median length4
Mean length3.284252
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 967
76.1%
0 303
 
23.9%

Length

2024-04-18T17:01:56.095534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:56.213159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 967
76.1%
0 303
 
23.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
967 
0
303 

Length

Max length4
Median length4
Mean length3.284252
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 967
76.1%
0 303
 
23.9%

Length

2024-04-18T17:01:56.354426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:56.476010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 967
76.1%
0 303
 
23.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
933 
상수도전용
335 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.2653543
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> 933
73.5%
상수도전용 335
 
26.4%
지하수전용 2
 
0.2%

Length

2024-04-18T17:01:56.601592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:56.700192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 933
73.5%
상수도전용 335
 
26.4%
지하수전용 2
 
0.2%

총직원수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
968 
0
302 

Length

Max length4
Median length4
Mean length3.2866142
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 968
76.2%
0 302
 
23.8%

Length

2024-04-18T17:01:56.807606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:56.901716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 968
76.2%
0 302
 
23.8%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing330
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean0.031914894
Minimum0
Maximum5
Zeros925
Zeros (%)72.8%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:56.985065image/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 deviation0.30094376
Coefficient of variation (CV)9.4295713
Kurtosis158.3248
Mean0.031914894
Median Absolute Deviation (MAD)0
Skewness11.896791
Sum30
Variance0.090567149
MonotonicityNot monotonic
2024-04-18T17:01:57.085771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 925
72.8%
1 8
 
0.6%
2 3
 
0.2%
4 2
 
0.2%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 330
 
26.0%
ValueCountFrequency (%)
0 925
72.8%
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%
0 925
72.8%

공장사무직직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing330
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean0.11382979
Minimum0
Maximum6
Zeros870
Zeros (%)68.5%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:57.187781image/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 deviation0.4670395
Coefficient of variation (CV)4.1029638
Kurtosis43.016603
Mean0.11382979
Median Absolute Deviation (MAD)0
Skewness5.6536197
Sum107
Variance0.21812589
MonotonicityNot monotonic
2024-04-18T17:01:57.290297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 870
68.5%
1 44
 
3.5%
2 19
 
1.5%
3 5
 
0.4%
6 1
 
0.1%
4 1
 
0.1%
(Missing) 330
 
26.0%
ValueCountFrequency (%)
0 870
68.5%
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%
0 870
68.5%

공장판매직직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.9%
Missing330
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean0.09787234
Minimum0
Maximum20
Zeros897
Zeros (%)70.6%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:57.392097image/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 deviation0.81060315
Coefficient of variation (CV)8.2822496
Kurtosis413.05812
Mean0.09787234
Median Absolute Deviation (MAD)0
Skewness18.369917
Sum92
Variance0.65707747
MonotonicityNot monotonic
2024-04-18T17:01:57.912321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 897
70.6%
1 27
 
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) 330
 
26.0%
ValueCountFrequency (%)
0 897
70.6%
1 27
 
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 27
 
2.1%
0 897
70.6%

공장생산직직원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
0
916 
<NA>
331 
1
 
13
2
 
9
4
 
1

Length

Max length4
Median length1
Mean length1.7818898
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 916
72.1%
<NA> 331
 
26.1%
1 13
 
1.0%
2 9
 
0.7%
4 1
 
0.1%

Length

2024-04-18T17:01:58.036772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:58.157307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 916
72.1%
na 331
 
26.1%
1 13
 
1.0%
2 9
 
0.7%
4 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
774 
자가
328 
임대
168 

Length

Max length4
Median length4
Mean length3.2188976
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 774
60.9%
자가 328
25.8%
임대 168
 
13.2%

Length

2024-04-18T17:01:58.276774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:58.387881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 774
60.9%
자가 328
25.8%
임대 168
 
13.2%

보증액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
963 
0
307 

Length

Max length4
Median length4
Mean length3.2748031
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 963
75.8%
0 307
 
24.2%

Length

2024-04-18T17:01:58.555874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:58.695796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 963
75.8%
0 307
 
24.2%

월세액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.1 KiB
<NA>
963 
0
307 

Length

Max length4
Median length4
Mean length3.2748031
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 963
75.8%
0 307
 
24.2%

Length

2024-04-18T17:01:58.799941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:01:58.897408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 963
75.8%
0 307
 
24.2%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
False
1270 
ValueCountFrequency (%)
False 1270
100.0%
2024-04-18T17:01:58.979411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct74
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1087165
Minimum0
Maximum312.55
Zeros1173
Zeros (%)92.4%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2024-04-18T17:01:59.131984image/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 deviation17.022105
Coefficient of variation (CV)8.0722587
Kurtosis201.07358
Mean2.1087165
Median Absolute Deviation (MAD)0
Skewness13.381376
Sum2678.07
Variance289.75207
MonotonicityNot monotonic
2024-04-18T17:01:59.322846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1173
92.4%
3.3 7
 
0.6%
5.0 5
 
0.4%
10.0 3
 
0.2%
6.6 3
 
0.2%
4.0 3
 
0.2%
33.0 2
 
0.2%
2.0 2
 
0.2%
66.0 2
 
0.2%
20.0 2
 
0.2%
Other values (64) 68
 
5.4%
ValueCountFrequency (%)
0.0 1173
92.4%
1.0 2
 
0.2%
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%
2.6 1
 
0.1%
2.75 1
 
0.1%
ValueCountFrequency (%)
312.55 1
0.1%
274.38 1
0.1%
240.0 1
0.1%
222.12 1
0.1%
179.55 1
0.1%
106.6 1
0.1%
101.52 1
0.1%
84.92 1
0.1%
66.0 2
0.2%
51.68 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1270
Missing (%)100.0%
Memory size11.3 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_22_17_P34100003410000-113-2021-0000920211129<NA>3폐업2폐업20220726<NA><NA><NA><NA>.00700192대구광역시 중구 종로2가 0039-0001 3층 302호대구광역시 중구 중앙대로77길 45, 3층 302호 (종로2가)41934뷰티(View Tea)20220726175625U2022-07-28 02:40:00.0유통전문판매업343618.460958264278.482979유통전문판매업00<NA><NA><NA>00000자가00N0.0<NA><NA><NA>
12유통전문판매업07_22_17_P34100003410000-113-2020-0000720200807<NA>3폐업2폐업20220110<NA><NA><NA><NA>9.00700832대구광역시 중구 남산동 0937-0011대구광역시 중구 달구벌대로 2078, 5층 (남산동)41966데일리케어컴퍼니20220110100018U2022-01-12 02:40:00.0유통전문판매업343617.423503263991.522262유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
23유통전문판매업07_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>
34유통전문판매업07_22_17_P34100003410000-113-2020-0000920200827<NA>3폐업2폐업20220930<NA><NA><NA><NA>12.00700180대구광역시 중구 동문동 0038-0006 패션쥬얼리 전문타운대구광역시 중구 경상감영길 176, 패션쥬얼리 전문타운 2층 (동문동)41913리브유20220930143739U2022-10-02 02:40:00.0유통전문판매업344123.607113264682.567328유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
45유통전문판매업07_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>
56유통전문판매업07_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>
67유통전문판매업07_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>
78유통전문판매업07_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>
89유통전문판매업07_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>
910유통전문판매업07_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>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
12601261유통전문판매업07_22_17_P34800003480000-113-2014-0000120140213<NA>1영업/정상1영업<NA><NA><NA><NA>1899491554.12711863대구광역시 달성군 가창면 삼산리 711대구광역시 달성군 가창면 가창로57길 2342940(주)종초원20160104164748I2018-08-31 23:59:59.0유통전문판매업349873.999232249984.471618유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N2.75<NA><NA><NA>
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