Overview

Dataset statistics

Number of variables47
Number of observations1219
Missing cells13740
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory483.4 KiB
Average record size in memory406.1 B

Variable types

Numeric13
Categorical17
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description22년06월_6270000_대구광역시_07_22_17_P_유통전문판매업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093750&dataSetDetailId=DDI_0000093764&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 (56.8%)Imbalance
인허가취소일자 has 1219 (100.0%) missing valuesMissing
폐업일자 has 530 (43.5%) missing valuesMissing
휴업시작일자 has 1219 (100.0%) missing valuesMissing
휴업종료일자 has 1219 (100.0%) missing valuesMissing
재개업일자 has 1219 (100.0%) missing valuesMissing
소재지전화 has 505 (41.4%) missing valuesMissing
소재지면적 has 151 (12.4%) missing valuesMissing
소재지우편번호 has 25 (2.1%) missing valuesMissing
도로명전체주소 has 230 (18.9%) missing valuesMissing
도로명우편번호 has 233 (19.1%) missing valuesMissing
좌표정보(X) has 37 (3.0%) missing valuesMissing
좌표정보(Y) has 37 (3.0%) missing valuesMissing
영업장주변구분명 has 1219 (100.0%) missing valuesMissing
등급구분명 has 1219 (100.0%) missing valuesMissing
본사종업원수 has 340 (27.9%) missing valuesMissing
공장사무직종업원수 has 340 (27.9%) missing valuesMissing
공장판매직종업원수 has 340 (27.9%) missing valuesMissing
전통업소지정번호 has 1219 (100.0%) missing valuesMissing
전통업소주된음식 has 1219 (100.0%) missing valuesMissing
홈페이지 has 1219 (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 864 (70.9%) zerosZeros
공장사무직종업원수 has 809 (66.4%) zerosZeros
공장판매직종업원수 has 838 (68.7%) zerosZeros
시설총규모 has 1130 (92.7%) zerosZeros

Reproduction

Analysis started2024-04-17 15:54:52.659630
Analysis finished2024-04-17 15:54:53.504873
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610
Minimum1
Maximum1219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:53.564620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile61.9
Q1305.5
median610
Q3914.5
95-th percentile1158.1
Maximum1219
Range1218
Interquartile range (IQR)609

Descriptive statistics

Standard deviation352.0393
Coefficient of variation (CV)0.5771136
Kurtosis-1.2
Mean610
Median Absolute Deviation (MAD)305
Skewness0
Sum743590
Variance123931.67
MonotonicityStrictly increasing
2024-04-18T00:54:53.672253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
812 1
 
0.1%
819 1
 
0.1%
818 1
 
0.1%
817 1
 
0.1%
816 1
 
0.1%
815 1
 
0.1%
814 1
 
0.1%
813 1
 
0.1%
811 1
 
0.1%
Other values (1209) 1209
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 (%)
1219 1
0.1%
1218 1
0.1%
1217 1
0.1%
1216 1
0.1%
1215 1
0.1%
1214 1
0.1%
1213 1
0.1%
1212 1
0.1%
1211 1
0.1%
1210 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
유통전문판매업
1219 

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 1219
100.0%

Length

2024-04-18T00:54:53.784644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:53.852097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1219
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
07_22_17_P
1219 

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 1219
100.0%

Length

2024-04-18T00:54:53.924867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:53.992476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 1219
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447571.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:54.057397image/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 deviation21621.7
Coefficient of variation (CV)0.0062715736
Kurtosis-1.1010268
Mean3447571.8
Median Absolute Deviation (MAD)20000
Skewness-0.27047799
Sum4.20259 × 109
Variance4.6749792 × 108
MonotonicityIncreasing
2024-04-18T00:54:54.141198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 248
20.3%
3460000 222
18.2%
3420000 188
15.4%
3470000 170
13.9%
3480000 123
10.1%
3410000 102
8.4%
3430000 89
 
7.3%
3440000 77
 
6.3%
ValueCountFrequency (%)
3410000 102
8.4%
3420000 188
15.4%
3430000 89
 
7.3%
3440000 77
 
6.3%
3450000 248
20.3%
3460000 222
18.2%
3470000 170
13.9%
3480000 123
10.1%
ValueCountFrequency (%)
3480000 123
10.1%
3470000 170
13.9%
3460000 222
18.2%
3450000 248
20.3%
3440000 77
 
6.3%
3430000 89
 
7.3%
3420000 188
15.4%
3410000 102
8.4%

관리번호
Text

UNIQUE 

Distinct1219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-04-18T00:54:54.311727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters26818
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

Unique1219 ?
Unique (%)100.0%

Sample

1st row3410000-113-2020-00007
2nd row3410000-113-2020-00010
3rd row3410000-113-2018-00003
4th row3410000-113-2018-00004
5th row3410000-113-2018-00005
ValueCountFrequency (%)
3410000-113-2020-00007 1
 
0.1%
3460000-113-2015-00022 1
 
0.1%
3460000-113-2018-00003 1
 
0.1%
3460000-113-2015-00017 1
 
0.1%
3460000-113-2014-00009 1
 
0.1%
3460000-113-2014-00008 1
 
0.1%
3460000-113-2014-00006 1
 
0.1%
3460000-113-2014-00003 1
 
0.1%
3460000-113-2015-00015 1
 
0.1%
3460000-113-2020-00013 1
 
0.1%
Other values (1209) 1209
99.2%
2024-04-18T00:54:54.569810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11187
41.7%
1 3799
 
14.2%
- 3657
 
13.6%
3 2762
 
10.3%
2 2012
 
7.5%
4 1524
 
5.7%
5 500
 
1.9%
6 436
 
1.6%
7 344
 
1.3%
8 306
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23161
86.4%
Dash Punctuation 3657
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11187
48.3%
1 3799
 
16.4%
3 2762
 
11.9%
2 2012
 
8.7%
4 1524
 
6.6%
5 500
 
2.2%
6 436
 
1.9%
7 344
 
1.5%
8 306
 
1.3%
9 291
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 3657
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26818
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11187
41.7%
1 3799
 
14.2%
- 3657
 
13.6%
3 2762
 
10.3%
2 2012
 
7.5%
4 1524
 
5.7%
5 500
 
1.9%
6 436
 
1.6%
7 344
 
1.3%
8 306
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11187
41.7%
1 3799
 
14.2%
- 3657
 
13.6%
3 2762
 
10.3%
2 2012
 
7.5%
4 1524
 
5.7%
5 500
 
1.9%
6 436
 
1.6%
7 344
 
1.3%
8 306
 
1.1%

인허가일자
Real number (ℝ)

Distinct992
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137468
Minimum19950510
Maximum20220628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:54.691918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20010614
Q120090712
median20151020
Q320190905
95-th percentile20220112
Maximum20220628
Range270118
Interquartile range (IQR)100193.5

Descriptive statistics

Standard deviation66855.668
Coefficient of variation (CV)0.003319964
Kurtosis-0.49915436
Mean20137468
Median Absolute Deviation (MAD)49506
Skewness-0.74512816
Sum2.4547573 × 1010
Variance4.4696803 × 109
MonotonicityNot monotonic
2024-04-18T00:54:54.805428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180508 5
 
0.4%
20170320 5
 
0.4%
20190613 4
 
0.3%
20121105 4
 
0.3%
20220107 4
 
0.3%
20190826 4
 
0.3%
20160712 4
 
0.3%
20121204 3
 
0.2%
20220530 3
 
0.2%
20201113 3
 
0.2%
Other values (982) 1180
96.8%
ValueCountFrequency (%)
19950510 1
0.1%
19950904 1
0.1%
19961210 1
0.1%
19961218 1
0.1%
19970201 1
0.1%
19970318 1
0.1%
19970627 1
0.1%
19971009 1
0.1%
19971015 1
0.1%
19971209 1
0.1%
ValueCountFrequency (%)
20220628 2
0.2%
20220624 2
0.2%
20220617 1
 
0.1%
20220613 1
 
0.1%
20220603 1
 
0.1%
20220531 1
 
0.1%
20220530 3
0.2%
20220526 1
 
0.1%
20220524 1
 
0.1%
20220523 1
 
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
3
689 
1
530 

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 (%)
3 689
56.5%
1 530
43.5%

Length

2024-04-18T00:54:54.907079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:54.981137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 689
56.5%
1 530
43.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
폐업
689 
영업/정상
530 

Length

Max length5
Median length2
Mean length3.3043478
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 689
56.5%
영업/정상 530
43.5%

Length

2024-04-18T00:54:55.076499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:55.173680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 689
56.5%
영업/정상 530
43.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2
689 
1
530 

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 (%)
2 689
56.5%
1 530
43.5%

Length

2024-04-18T00:54:55.253024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:55.326535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 689
56.5%
1 530
43.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
폐업
689 
영업
530 

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 689
56.5%
영업 530
43.5%

Length

2024-04-18T00:54:55.406671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:55.481780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 689
56.5%
영업 530
43.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct606
Distinct (%)88.0%
Missing530
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean20142868
Minimum20001029
Maximum20220628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:55.579731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040662
Q120090817
median20160624
Q320191203
95-th percentile20211230
Maximum20220628
Range219599
Interquartile range (IQR)100386

Descriptive statistics

Standard deviation59703.198
Coefficient of variation (CV)0.002963987
Kurtosis-1.0734878
Mean20142868
Median Absolute Deviation (MAD)40501
Skewness-0.51417736
Sum1.3878436 × 1010
Variance3.5644719 × 109
MonotonicityNot monotonic
2024-04-18T00:54:55.691936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.4%
20070116 4
 
0.3%
20191227 3
 
0.2%
20021224 3
 
0.2%
20051128 3
 
0.2%
20220103 3
 
0.2%
20201028 3
 
0.2%
20220221 3
 
0.2%
20201207 3
 
0.2%
20201124 3
 
0.2%
Other values (596) 656
53.8%
(Missing) 530
43.5%
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 (%)
20220628 1
0.1%
20220624 1
0.1%
20220607 1
0.1%
20220603 1
0.1%
20220525 1
0.1%
20220524 2
0.2%
20220516 1
0.1%
20220513 2
0.2%
20220504 1
0.1%
20220426 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

소재지전화
Text

MISSING 

Distinct657
Distinct (%)92.0%
Missing505
Missing (%)41.4%
Memory size9.7 KiB
2024-04-18T00:54:55.909266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.87535
Min length7

Characters and Unicode

Total characters7765
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

Unique606 ?
Unique (%)84.9%

Sample

1st row053 7461239
2nd row16001037
3rd row053 2540892
4th row053 7812662
5th row053 8547554
ValueCountFrequency (%)
053 486
31.7%
070 40
 
2.6%
311 9
 
0.6%
313 8
 
0.5%
625 7
 
0.5%
746 7
 
0.5%
312 7
 
0.5%
9909 6
 
0.4%
584 5
 
0.3%
755 5
 
0.3%
Other values (802) 953
62.2%
2024-04-18T00:54:56.209772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1163
15.0%
0 1139
14.7%
3 1039
13.4%
825
10.6%
1 591
7.6%
2 588
7.6%
7 560
7.2%
8 495
6.4%
6 490
6.3%
4 485
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6940
89.4%
Space Separator 825
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1163
16.8%
0 1139
16.4%
3 1039
15.0%
1 591
8.5%
2 588
8.5%
7 560
8.1%
8 495
7.1%
6 490
7.1%
4 485
7.0%
9 390
 
5.6%
Space Separator
ValueCountFrequency (%)
825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7765
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1163
15.0%
0 1139
14.7%
3 1039
13.4%
825
10.6%
1 591
7.6%
2 588
7.6%
7 560
7.2%
8 495
6.4%
6 490
6.3%
4 485
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7765
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1163
15.0%
0 1139
14.7%
3 1039
13.4%
825
10.6%
1 591
7.6%
2 588
7.6%
7 560
7.2%
8 495
6.4%
6 490
6.3%
4 485
6.2%

소재지면적
Text

MISSING 

Distinct678
Distinct (%)63.5%
Missing151
Missing (%)12.4%
Memory size9.7 KiB
2024-04-18T00:54:56.503839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9447566
Min length3

Characters and Unicode

Total characters5281
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

Unique569 ?
Unique (%)53.3%

Sample

1st row9.00
2nd row14.76
3rd row4.20
4th row80.00
5th row143.01
ValueCountFrequency (%)
00 77
 
7.2%
33.00 27
 
2.5%
3.30 18
 
1.7%
30.00 16
 
1.5%
50.00 13
 
1.2%
16.50 13
 
1.2%
25.00 12
 
1.1%
10.00 10
 
0.9%
6.60 9
 
0.8%
20.00 8
 
0.7%
Other values (668) 865
81.0%
2024-04-18T00:54:56.891545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1282
24.3%
. 1068
20.2%
1 468
 
8.9%
2 428
 
8.1%
3 401
 
7.6%
5 341
 
6.5%
6 305
 
5.8%
4 297
 
5.6%
9 233
 
4.4%
8 230
 
4.4%
Other values (2) 228
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4209
79.7%
Other Punctuation 1072
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1282
30.5%
1 468
 
11.1%
2 428
 
10.2%
3 401
 
9.5%
5 341
 
8.1%
6 305
 
7.2%
4 297
 
7.1%
9 233
 
5.5%
8 230
 
5.5%
7 224
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 1068
99.6%
, 4
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5281
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1282
24.3%
. 1068
20.2%
1 468
 
8.9%
2 428
 
8.1%
3 401
 
7.6%
5 341
 
6.5%
6 305
 
5.8%
4 297
 
5.6%
9 233
 
4.4%
8 230
 
4.4%
Other values (2) 228
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5281
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1282
24.3%
. 1068
20.2%
1 468
 
8.9%
2 428
 
8.1%
3 401
 
7.6%
5 341
 
6.5%
6 305
 
5.8%
4 297
 
5.6%
9 233
 
4.4%
8 230
 
4.4%
Other values (2) 228
 
4.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct404
Distinct (%)33.8%
Missing25
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean704444.29
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:57.016345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700802.65
Q1702061
median703830
Q3706220
95-th percentile711833
Maximum711892
Range11882
Interquartile range (IQR)4159

Descriptive statistics

Standard deviation2985.5559
Coefficient of variation (CV)0.0042381718
Kurtosis0.64753439
Mean704444.29
Median Absolute Deviation (MAD)1986
Skewness1.0002361
Sum8.4110648 × 108
Variance8913544.1
MonotonicityNot monotonic
2024-04-18T00:54:57.120355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 21
 
1.7%
701824 15
 
1.2%
706818 13
 
1.1%
703100 13
 
1.1%
703830 13
 
1.1%
704080 11
 
0.9%
711851 11
 
0.9%
711814 10
 
0.8%
700230 10
 
0.8%
706220 10
 
0.8%
Other values (394) 1067
87.5%
(Missing) 25
 
2.1%
ValueCountFrequency (%)
700010 2
 
0.2%
700040 5
0.4%
700070 1
 
0.1%
700092 3
 
0.2%
700111 1
 
0.1%
700150 3
 
0.2%
700170 1
 
0.1%
700180 1
 
0.1%
700192 1
 
0.1%
700230 10
0.8%
ValueCountFrequency (%)
711892 2
 
0.2%
711891 5
0.4%
711874 1
 
0.1%
711863 5
0.4%
711862 1
 
0.1%
711858 3
 
0.2%
711856 2
 
0.2%
711855 7
0.6%
711852 3
 
0.2%
711851 11
0.9%
Distinct1148
Distinct (%)94.3%
Missing1
Missing (%)0.1%
Memory size9.7 KiB
2024-04-18T00:54:57.402785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length22.795567
Min length16

Characters and Unicode

Total characters27765
Distinct characters288
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

Unique1087 ?
Unique (%)89.2%

Sample

1st row대구광역시 중구 남산동 0937-0011
2nd row대구광역시 중구 삼덕동3가 0264-0001
3rd row대구광역시 중구 동성로2가 0166-0001 대구백화점건물 지상 11층
4th row대구광역시 중구 대봉동 0188-0009 지상 3층
5th row대구광역시 중구 봉산동 0028-0006 지상 3층
ValueCountFrequency (%)
대구광역시 1218
 
21.8%
북구 248
 
4.4%
수성구 221
 
3.9%
동구 187
 
3.3%
달서구 170
 
3.0%
달성군 124
 
2.2%
중구 102
 
1.8%
서구 89
 
1.6%
1층 87
 
1.6%
남구 77
 
1.4%
Other values (1564) 3076
54.9%
2024-04-18T00:54:57.810005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5558
20.0%
2361
 
8.5%
1 1442
 
5.2%
1365
 
4.9%
1345
 
4.8%
1239
 
4.5%
1222
 
4.4%
1218
 
4.4%
- 1009
 
3.6%
2 834
 
3.0%
Other values (278) 10172
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14692
52.9%
Decimal Number 6298
22.7%
Space Separator 5558
 
20.0%
Dash Punctuation 1009
 
3.6%
Open Punctuation 76
 
0.3%
Close Punctuation 76
 
0.3%
Uppercase Letter 30
 
0.1%
Other Punctuation 22
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2361
16.1%
1365
 
9.3%
1345
 
9.2%
1239
 
8.4%
1222
 
8.3%
1218
 
8.3%
436
 
3.0%
319
 
2.2%
297
 
2.0%
290
 
2.0%
Other values (246) 4600
31.3%
Uppercase Letter
ValueCountFrequency (%)
B 7
23.3%
D 3
10.0%
A 3
10.0%
T 3
10.0%
J 3
10.0%
M 2
 
6.7%
P 2
 
6.7%
C 2
 
6.7%
N 1
 
3.3%
S 1
 
3.3%
Other values (3) 3
10.0%
Decimal Number
ValueCountFrequency (%)
1 1442
22.9%
2 834
13.2%
0 825
13.1%
3 616
9.8%
5 511
 
8.1%
4 479
 
7.6%
6 420
 
6.7%
8 413
 
6.6%
7 396
 
6.3%
9 362
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 19
86.4%
/ 2
 
9.1%
. 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
d 2
50.0%
s 2
50.0%
Space Separator
ValueCountFrequency (%)
5558
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1009
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14692
52.9%
Common 13039
47.0%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2361
16.1%
1365
 
9.3%
1345
 
9.2%
1239
 
8.4%
1222
 
8.3%
1218
 
8.3%
436
 
3.0%
319
 
2.2%
297
 
2.0%
290
 
2.0%
Other values (246) 4600
31.3%
Common
ValueCountFrequency (%)
5558
42.6%
1 1442
 
11.1%
- 1009
 
7.7%
2 834
 
6.4%
0 825
 
6.3%
3 616
 
4.7%
5 511
 
3.9%
4 479
 
3.7%
6 420
 
3.2%
8 413
 
3.2%
Other values (7) 932
 
7.1%
Latin
ValueCountFrequency (%)
B 7
20.6%
D 3
8.8%
A 3
8.8%
T 3
8.8%
J 3
8.8%
d 2
 
5.9%
M 2
 
5.9%
P 2
 
5.9%
C 2
 
5.9%
s 2
 
5.9%
Other values (5) 5
14.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14692
52.9%
ASCII 13073
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5558
42.5%
1 1442
 
11.0%
- 1009
 
7.7%
2 834
 
6.4%
0 825
 
6.3%
3 616
 
4.7%
5 511
 
3.9%
4 479
 
3.7%
6 420
 
3.2%
8 413
 
3.2%
Other values (22) 966
 
7.4%
Hangul
ValueCountFrequency (%)
2361
16.1%
1365
 
9.3%
1345
 
9.2%
1239
 
8.4%
1222
 
8.3%
1218
 
8.3%
436
 
3.0%
319
 
2.2%
297
 
2.0%
290
 
2.0%
Other values (246) 4600
31.3%

도로명전체주소
Text

MISSING 

Distinct957
Distinct (%)96.8%
Missing230
Missing (%)18.9%
Memory size9.7 KiB
2024-04-18T00:54:58.121114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length29.489383
Min length20

Characters and Unicode

Total characters29165
Distinct characters324
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

Unique929 ?
Unique (%)93.9%

Sample

1st row대구광역시 중구 달구벌대로 2078, 5층 (남산동)
2nd row대구광역시 중구 달구벌대로445길 44-22, 3층 (삼덕동3가)
3rd row대구광역시 중구 동성로 30, 대구백화점건물 지상 11층 (동성로2가)
4th row대구광역시 중구 동덕로 7, 지상 3층 (대봉동)
5th row대구광역시 중구 동성로1길 52, 지상 3층 (봉산동)
ValueCountFrequency (%)
대구광역시 989
 
16.4%
1층 309
 
5.1%
북구 198
 
3.3%
수성구 183
 
3.0%
동구 151
 
2.5%
달서구 133
 
2.2%
2층 132
 
2.2%
달성군 108
 
1.8%
중구 92
 
1.5%
3층 74
 
1.2%
Other values (1515) 3644
60.6%
2024-04-18T00:54:58.731266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5024
 
17.2%
2002
 
6.9%
1289
 
4.4%
1273
 
4.4%
1 1216
 
4.2%
1020
 
3.5%
1003
 
3.4%
989
 
3.4%
946
 
3.2%
( 917
 
3.1%
Other values (314) 13486
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16376
56.1%
Space Separator 5024
 
17.2%
Decimal Number 4793
 
16.4%
Open Punctuation 917
 
3.1%
Close Punctuation 917
 
3.1%
Other Punctuation 840
 
2.9%
Dash Punctuation 246
 
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 (%)
2002
 
12.2%
1289
 
7.9%
1273
 
7.8%
1020
 
6.2%
1003
 
6.1%
989
 
6.0%
946
 
5.8%
698
 
4.3%
543
 
3.3%
449
 
2.7%
Other values (281) 6164
37.6%
Uppercase Letter
ValueCountFrequency (%)
B 15
34.9%
A 11
25.6%
J 4
 
9.3%
T 3
 
7.0%
P 2
 
4.7%
M 2
 
4.7%
D 2
 
4.7%
S 1
 
2.3%
K 1
 
2.3%
N 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 1216
25.4%
2 778
16.2%
3 558
11.6%
4 426
 
8.9%
5 382
 
8.0%
0 372
 
7.8%
6 335
 
7.0%
7 278
 
5.8%
8 231
 
4.8%
9 217
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
s 2
28.6%
d 2
28.6%
c 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 838
99.8%
/ 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5024
100.0%
Open Punctuation
ValueCountFrequency (%)
( 917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 917
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 246
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16376
56.1%
Common 12739
43.7%
Latin 50
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2002
 
12.2%
1289
 
7.9%
1273
 
7.8%
1020
 
6.2%
1003
 
6.1%
989
 
6.0%
946
 
5.8%
698
 
4.3%
543
 
3.3%
449
 
2.7%
Other values (281) 6164
37.6%
Common
ValueCountFrequency (%)
5024
39.4%
1 1216
 
9.5%
( 917
 
7.2%
) 917
 
7.2%
, 838
 
6.6%
2 778
 
6.1%
3 558
 
4.4%
4 426
 
3.3%
5 382
 
3.0%
0 372
 
2.9%
Other values (8) 1311
 
10.3%
Latin
ValueCountFrequency (%)
B 15
30.0%
A 11
22.0%
J 4
 
8.0%
T 3
 
6.0%
P 2
 
4.0%
M 2
 
4.0%
e 2
 
4.0%
D 2
 
4.0%
s 2
 
4.0%
d 2
 
4.0%
Other values (5) 5
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16376
56.1%
ASCII 12789
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5024
39.3%
1 1216
 
9.5%
( 917
 
7.2%
) 917
 
7.2%
, 838
 
6.6%
2 778
 
6.1%
3 558
 
4.4%
4 426
 
3.3%
5 382
 
3.0%
0 372
 
2.9%
Other values (23) 1361
 
10.6%
Hangul
ValueCountFrequency (%)
2002
 
12.2%
1289
 
7.9%
1273
 
7.8%
1020
 
6.2%
1003
 
6.1%
989
 
6.0%
946
 
5.8%
698
 
4.3%
543
 
3.3%
449
 
2.7%
Other values (281) 6164
37.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct559
Distinct (%)56.7%
Missing233
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean42001.2
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:58.849262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41078
Q141489
median41964
Q342490
95-th percentile42969.75
Maximum43024
Range2024
Interquartile range (IQR)1001

Descriptive statistics

Standard deviation596.25048
Coefficient of variation (CV)0.014196034
Kurtosis-1.1408369
Mean42001.2
Median Absolute Deviation (MAD)483
Skewness0.12602948
Sum41413183
Variance355514.63
MonotonicityNot monotonic
2024-04-18T00:54:58.959610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41490 14
 
1.1%
41485 14
 
1.1%
41934 10
 
0.8%
42974 8
 
0.7%
41260 8
 
0.7%
41750 8
 
0.7%
41937 7
 
0.6%
42922 7
 
0.6%
42819 6
 
0.5%
41256 6
 
0.5%
Other values (549) 898
73.7%
(Missing) 233
 
19.1%
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%
Distinct1115
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-04-18T00:54:59.169669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.6316653
Min length2

Characters and Unicode

Total characters8084
Distinct characters603
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

Unique1027 ?
Unique (%)84.2%

Sample

1st row데일리케어컴퍼니
2nd row유어밸런스
3rd row토담순두부대백점
4th row주식회사 다다컴퍼니
5th row히트방앗간
ValueCountFrequency (%)
주식회사 70
 
5.1%
농업회사법인 9
 
0.7%
선진vfc 6
 
0.4%
6
 
0.4%
company 4
 
0.3%
아우노 4
 
0.3%
산수원 3
 
0.2%
자연애 3
 
0.2%
카페봄봄 3
 
0.2%
우야꼬닭강정 3
 
0.2%
Other values (1161) 1262
91.9%
2024-04-18T00:54:59.490862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
429
 
5.3%
) 351
 
4.3%
( 348
 
4.3%
263
 
3.3%
226
 
2.8%
204
 
2.5%
165
 
2.0%
154
 
1.9%
150
 
1.9%
128
 
1.6%
Other values (593) 5666
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6840
84.6%
Close Punctuation 351
 
4.3%
Open Punctuation 348
 
4.3%
Uppercase Letter 172
 
2.1%
Lowercase Letter 162
 
2.0%
Space Separator 154
 
1.9%
Decimal Number 32
 
0.4%
Other Punctuation 22
 
0.3%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
429
 
6.3%
263
 
3.8%
226
 
3.3%
204
 
3.0%
165
 
2.4%
150
 
2.2%
128
 
1.9%
121
 
1.8%
110
 
1.6%
109
 
1.6%
Other values (530) 4935
72.1%
Uppercase Letter
ValueCountFrequency (%)
F 23
13.4%
C 21
12.2%
S 19
 
11.0%
N 10
 
5.8%
D 9
 
5.2%
T 9
 
5.2%
B 9
 
5.2%
I 9
 
5.2%
V 8
 
4.7%
M 7
 
4.1%
Other values (13) 48
27.9%
Lowercase Letter
ValueCountFrequency (%)
n 20
12.3%
e 20
12.3%
a 19
11.7%
o 18
11.1%
i 12
 
7.4%
t 11
 
6.8%
l 10
 
6.2%
y 9
 
5.6%
r 7
 
4.3%
u 5
 
3.1%
Other values (12) 31
19.1%
Decimal Number
ValueCountFrequency (%)
2 7
21.9%
9 5
15.6%
1 4
12.5%
4 4
12.5%
3 3
9.4%
0 3
9.4%
5 3
9.4%
8 1
 
3.1%
6 1
 
3.1%
7 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
& 15
68.2%
. 6
 
27.3%
, 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 351
100.0%
Open Punctuation
ValueCountFrequency (%)
( 348
100.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6841
84.6%
Common 908
 
11.2%
Latin 334
 
4.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
429
 
6.3%
263
 
3.8%
226
 
3.3%
204
 
3.0%
165
 
2.4%
150
 
2.2%
128
 
1.9%
121
 
1.8%
110
 
1.6%
109
 
1.6%
Other values (530) 4936
72.2%
Latin
ValueCountFrequency (%)
F 23
 
6.9%
C 21
 
6.3%
n 20
 
6.0%
e 20
 
6.0%
a 19
 
5.7%
S 19
 
5.7%
o 18
 
5.4%
i 12
 
3.6%
t 11
 
3.3%
N 10
 
3.0%
Other values (35) 161
48.2%
Common
ValueCountFrequency (%)
) 351
38.7%
( 348
38.3%
154
17.0%
& 15
 
1.7%
2 7
 
0.8%
. 6
 
0.7%
9 5
 
0.6%
1 4
 
0.4%
4 4
 
0.4%
3 3
 
0.3%
Other values (7) 11
 
1.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6839
84.6%
ASCII 1242
 
15.4%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
429
 
6.3%
263
 
3.8%
226
 
3.3%
204
 
3.0%
165
 
2.4%
150
 
2.2%
128
 
1.9%
121
 
1.8%
110
 
1.6%
109
 
1.6%
Other values (529) 4934
72.1%
ASCII
ValueCountFrequency (%)
) 351
28.3%
( 348
28.0%
154
12.4%
F 23
 
1.9%
C 21
 
1.7%
n 20
 
1.6%
e 20
 
1.6%
a 19
 
1.5%
S 19
 
1.5%
o 18
 
1.4%
Other values (52) 249
20.0%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1161
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0158389 × 1013
Minimum2.0010823 × 1013
Maximum2.0220629 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:54:59.604200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0021113 × 1013
Q12.0120827 × 1013
median2.0190107 × 1013
Q32.0210324 × 1013
95-th percentile2.0220413 × 1013
Maximum2.0220629 × 1013
Range2.0980617 × 1011
Interquartile range (IQR)8.949754 × 1010

Descriptive statistics

Standard deviation6.2543717 × 1010
Coefficient of variation (CV)0.0031026149
Kurtosis-0.34287737
Mean2.0158389 × 1013
Median Absolute Deviation (MAD)2.1120049 × 1010
Skewness-0.98885645
Sum2.4573076 × 1016
Variance3.9117166 × 1021
MonotonicityNot monotonic
2024-04-18T00:54:59.706482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.0%
20021113000000 10
 
0.8%
20020126000000 9
 
0.7%
20021019000000 5
 
0.4%
20020510000000 5
 
0.4%
20020115000000 5
 
0.4%
20041011000000 3
 
0.2%
20021012000000 3
 
0.2%
20140512105112 3
 
0.2%
20060825000000 3
 
0.2%
Other values (1151) 1161
95.2%
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 (%)
20220629170454 1
0.1%
20220628145220 1
0.1%
20220628145122 1
0.1%
20220628111853 1
0.1%
20220627174743 1
0.1%
20220624145659 1
0.1%
20220624142233 1
0.1%
20220624141032 1
0.1%
20220624103109 1
0.1%
20220622175806 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
I
712 
U
507 

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 712
58.4%
U 507
41.6%

Length

2024-04-18T00:54:59.799367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:54:59.872818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 712
58.4%
u 507
41.6%
Distinct485
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
Minimum2018-08-31 23:59:59
Maximum2022-07-02 02:40:00
2024-04-18T00:54:59.953598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:55:00.073830image/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 size9.7 KiB
유통전문판매업
1219 

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 1219
100.0%

Length

2024-04-18T00:55:00.183220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:00.267100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1219
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1080
Distinct (%)91.4%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean342809.04
Minimum325733.86
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:00.341645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325733.86
5-th percentile332332.29
Q1339261.95
median343330.38
Q3346618.28
95-th percentile352997.57
Maximum358046.4
Range32312.548
Interquartile range (IQR)7356.3312

Descriptive statistics

Standard deviation5682.5237
Coefficient of variation (CV)0.016576353
Kurtosis0.14475204
Mean342809.04
Median Absolute Deviation (MAD)3625.8911
Skewness-0.16650831
Sum4.0520029 × 108
Variance32291076
MonotonicityNot monotonic
2024-04-18T00:55:00.444534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343981.615381 5
 
0.4%
336590.459071 5
 
0.4%
343157.682044 4
 
0.3%
346193.266936 3
 
0.2%
342826.756531 3
 
0.2%
329092.356185 3
 
0.2%
345687.898519 3
 
0.2%
339320.839241 3
 
0.2%
339048.376979 3
 
0.2%
345866.653115 3
 
0.2%
Other values (1070) 1147
94.1%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
325733.855686 1
0.1%
326032.481595 1
0.1%
327448.497282 1
0.1%
327489.324167 1
0.1%
327590.551952 1
0.1%
327723.104095 1
0.1%
327894.698221 1
0.1%
328237.006988 1
0.1%
328453.839356 1
0.1%
328501.384301 1
0.1%
ValueCountFrequency (%)
358046.403776 1
0.1%
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 

Distinct1080
Distinct (%)91.4%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean263484.59
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:00.550473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile255754.14
Q1261214.42
median264054.29
Q3265972.15
95-th percentile271268.72
Maximum277799.71
Range39492.858
Interquartile range (IQR)4757.7265

Descriptive statistics

Standard deviation5172.9288
Coefficient of variation (CV)0.019632757
Kurtosis4.6513925
Mean263484.59
Median Absolute Deviation (MAD)2568.2894
Skewness-1.2792197
Sum3.1143879 × 108
Variance26759193
MonotonicityNot monotonic
2024-04-18T00:55:00.672470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264421.75276 5
 
0.4%
257286.897263 5
 
0.4%
261957.795169 4
 
0.3%
264708.839935 3
 
0.2%
263824.293143 3
 
0.2%
253359.522917 3
 
0.2%
266987.666828 3
 
0.2%
265197.142652 3
 
0.2%
258618.826409 3
 
0.2%
261215.496084 3
 
0.2%
Other values (1070) 1147
94.1%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
238306.850311 1
0.1%
238531.35408 1
0.1%
238893.829912 1
0.1%
239240.086699 1
0.1%
239536.919741 1
0.1%
240205.085494 1
0.1%
240739.938523 1
0.1%
240811.478411 1
0.1%
242273.0 1
0.1%
242311.21229 1
0.1%
ValueCountFrequency (%)
277799.708684 1
0.1%
277755.206408 2
0.2%
277541.768688 1
0.1%
277428.083074 1
0.1%
276596.005371 1
0.1%
275969.761183 1
0.1%
275787.590179 1
0.1%
274811.331596 1
0.1%
274594.894588 1
0.1%
274508.218106 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
유통전문판매업
1219 

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 1219
100.0%

Length

2024-04-18T00:55:00.804063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:00.892123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1219
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
991 
0
228 

Length

Max length4
Median length4
Mean length3.4388843
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 991
81.3%
0 228
 
18.7%

Length

2024-04-18T00:55:00.967438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:01.041138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 991
81.3%
0 228
 
18.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
991 
0
228 

Length

Max length4
Median length4
Mean length3.4388843
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 991
81.3%
0 228
 
18.7%

Length

2024-04-18T00:55:01.125685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:01.202481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 991
81.3%
0 228
 
18.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
897 
상수도전용
320 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.2641509
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> 897
73.6%
상수도전용 320
 
26.3%
지하수전용 2
 
0.2%

Length

2024-04-18T00:55:01.290044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:01.372186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 897
73.6%
상수도전용 320
 
26.3%
지하수전용 2
 
0.2%

총종업원수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
992 
0
227 

Length

Max length4
Median length4
Mean length3.4413454
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 992
81.4%
0 227
 
18.6%

Length

2024-04-18T00:55:01.457367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:01.538174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 992
81.4%
0 227
 
18.6%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing340
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean0.034129693
Minimum0
Maximum5
Zeros864
Zeros (%)70.9%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:01.609034image/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 deviation0.31110083
Coefficient of variation (CV)9.1152542
Kurtosis147.81727
Mean0.034129693
Median Absolute Deviation (MAD)0
Skewness11.497747
Sum30
Variance0.096783723
MonotonicityNot monotonic
2024-04-18T00:55:01.690810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 864
70.9%
1 8
 
0.7%
2 3
 
0.2%
4 2
 
0.2%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 340
 
27.9%
ValueCountFrequency (%)
0 864
70.9%
1 8
 
0.7%
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
 
0.7%
0 864
70.9%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.7%
Missing340
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean0.12172924
Minimum0
Maximum6
Zeros809
Zeros (%)66.4%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:01.762530image/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 deviation0.4819935
Coefficient of variation (CV)3.9595541
Kurtosis40.041647
Mean0.12172924
Median Absolute Deviation (MAD)0
Skewness5.4533626
Sum107
Variance0.23231774
MonotonicityNot monotonic
2024-04-18T00:55:01.838427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 809
66.4%
1 44
 
3.6%
2 19
 
1.6%
3 5
 
0.4%
6 1
 
0.1%
4 1
 
0.1%
(Missing) 340
27.9%
ValueCountFrequency (%)
0 809
66.4%
1 44
 
3.6%
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 44
 
3.6%
0 809
66.4%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.9%
Missing340
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean0.10238908
Minimum0
Maximum20
Zeros838
Zeros (%)68.7%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:01.916806image/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 deviation0.83678593
Coefficient of variation (CV)8.1726092
Kurtosis388.61526
Mean0.10238908
Median Absolute Deviation (MAD)0
Skewness17.842778
Sum90
Variance0.70021069
MonotonicityNot monotonic
2024-04-18T00:55:01.998463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 838
68.7%
1 25
 
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) 340
27.9%
ValueCountFrequency (%)
0 838
68.7%
1 25
 
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 25
 
2.1%
0 838
68.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
0
855 
<NA>
341 
1
 
13
2
 
9
4
 
1

Length

Max length4
Median length1
Mean length1.8392125
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 855
70.1%
<NA> 341
 
28.0%
1 13
 
1.1%
2 9
 
0.7%
4 1
 
0.1%

Length

2024-04-18T00:55:02.107267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:02.188532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 855
70.1%
na 341
 
28.0%
1 13
 
1.1%
2 9
 
0.7%
4 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
756 
자가
303 
임대
160 

Length

Max length4
Median length4
Mean length3.240361
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> 756
62.0%
자가 303
24.9%
임대 160
 
13.1%

Length

2024-04-18T00:55:02.301790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:02.387694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 756
62.0%
자가 303
24.9%
임대 160
 
13.1%

보증액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
987 
0
232 

Length

Max length4
Median length4
Mean length3.4290402
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 987
81.0%
0 232
 
19.0%

Length

2024-04-18T00:55:02.474761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:02.550697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 987
81.0%
0 232
 
19.0%

월세액
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
987 
0
232 

Length

Max length4
Median length4
Mean length3.4290402
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 987
81.0%
0 232
 
19.0%

Length

2024-04-18T00:55:02.630649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:55:02.706778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 987
81.0%
0 232
 
19.0%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
False
1219 
ValueCountFrequency (%)
False 1219
100.0%
2024-04-18T00:55:02.778708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct69
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9548893
Minimum0
Maximum312.55
Zeros1130
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-18T00:55:02.863294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.883
Maximum312.55
Range312.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.435049
Coefficient of variation (CV)8.4071512
Kurtosis230.51065
Mean1.9548893
Median Absolute Deviation (MAD)0
Skewness14.378511
Sum2383.01
Variance270.11085
MonotonicityNot monotonic
2024-04-18T00:55:02.990410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1130
92.7%
3.3 6
 
0.5%
5.0 5
 
0.4%
4.0 3
 
0.2%
10.0 3
 
0.2%
8.0 2
 
0.2%
6.6 2
 
0.2%
4.5 2
 
0.2%
33.0 2
 
0.2%
2.0 2
 
0.2%
Other values (59) 62
 
5.1%
ValueCountFrequency (%)
0.0 1130
92.7%
1.0 1
 
0.1%
1.2 1
 
0.1%
2.0 2
 
0.2%
2.18 1
 
0.1%
2.25 1
 
0.1%
2.55 1
 
0.1%
2.56 1
 
0.1%
2.75 1
 
0.1%
2.81 1
 
0.1%
ValueCountFrequency (%)
312.55 1
0.1%
274.38 1
0.1%
240.0 1
0.1%
222.12 1
0.1%
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%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_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>
12유통전문판매업07_22_17_P34100003410000-113-2020-0001020200831<NA>3폐업2폐업20210415<NA><NA><NA><NA>14.76700413대구광역시 중구 삼덕동3가 0264-0001대구광역시 중구 달구벌대로445길 44-22, 3층 (삼덕동3가)41948유어밸런스20210415172041U2021-04-17 02:40:00.0유통전문판매업345133.885687263875.819382유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23유통전문판매업07_22_17_P34100003410000-113-2018-0000320180420<NA>3폐업2폐업20210708<NA><NA><NA><NA>4.20700716대구광역시 중구 동성로2가 0166-0001 대구백화점건물 지상 11층대구광역시 중구 동성로 30, 대구백화점건물 지상 11층 (동성로2가)41938토담순두부대백점20210709091538U2021-07-11 02:40:00.0유통전문판매업344047.979265264405.128696유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
34유통전문판매업07_22_17_P34100003410000-113-2018-0000420180508<NA>3폐업2폐업20210126<NA><NA><NA><NA>80.00700811대구광역시 중구 대봉동 0188-0009 지상 3층대구광역시 중구 동덕로 7, 지상 3층 (대봉동)41954주식회사 다다컴퍼니20210126154759U2021-01-28 02:40:00.0유통전문판매업344803.668313262942.555066유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45유통전문판매업07_22_17_P34100003410000-113-2018-0000520180626<NA>3폐업2폐업20191218<NA><NA><NA><NA>143.01700822대구광역시 중구 봉산동 0028-0006 지상 3층대구광역시 중구 동성로1길 52, 지상 3층 (봉산동)41943히트방앗간20191218170108U2019-12-20 02:40:00.0유통전문판매업344087.048465264015.597741유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
56유통전문판매업07_22_17_P34100003410000-113-2016-0000220160427<NA>3폐업2폐업20180314<NA><NA><NA><NA>5.70700230대구광역시 중구 남성로 0020-0005 지상1층대구광역시 중구 남성로 5 (남성로, 지상1층)41934대한약초20180314161314I2018-08-31 23:59:59.0유통전문판매업343338.902682264381.802951유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
67유통전문판매업07_22_17_P34100003410000-113-2016-0000320160620<NA>3폐업2폐업20170623<NA><NA><NA><NA>29.70700823대구광역시 중구 봉산동 0127-0001 메트로프라자 D212대구광역시 중구 달구벌대로 지하 2160 (봉산동, 메트로프라자 D212)41959설화20170623141221I2018-08-31 23:59:59.0유통전문판매업344083.488663263931.205868유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78유통전문판매업07_22_17_P34100003410000-113-2011-0000220110830<NA>3폐업2폐업20140613<NA><NA><NA>053 746123971.69700421대구광역시 중구 동인동1가 0204-0002 지상2층대구광역시 중구 공평로20길 51-32, 2층 (동인동1가)41911지성건강식품20120201160134I2018-08-31 23:59:59.0유통전문판매업344689.839528264805.59973유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
89유통전문판매업07_22_17_P34100003410000-113-2012-0000120120403<NA>3폐업2폐업20140305<NA><NA><NA>16001037<NA>700837대구광역시 중구 남산동 2466-0026 지상2층대구광역시 중구 남산로 39 (남산동, 지상2층)41978야미고프20131031092326I2018-08-31 23:59:59.0유통전문판매업342856.914363263364.097215유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
910유통전문판매업07_22_17_P34100003410000-113-2014-0000220140925<NA>3폐업2폐업20150122<NA><NA><NA><NA>23.56700840대구광역시 중구 달성동 0145-0007 지상3층대구광역시 중구 태평로 13 (달성동, 지상3층)41900세종라이프20140925143146I2018-08-31 23:59:59.0유통전문판매업342566.486427265380.887132유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
12091210유통전문판매업07_22_17_P34800003480000-113-2017-0000320170427<NA>1영업/정상1영업<NA><NA><NA><NA>053 555 229921.00711833대구광역시 달성군 화원읍 설화리 736-3대구광역시 달성군 화원읍 류목정길 56, 1층42957DMG푸드20210408175333U2021-04-10 02:40:00.0유통전문판매업334255.076962255771.102947유통전문판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
12101211유통전문판매업07_22_17_P34800003480000-113-2017-0000520171030<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00711833대구광역시 달성군 화원읍 설화리 739-2 . 1층대구광역시 달성군 화원읍 명천로 320, 1층42957형제베리팜20171030145014I2018-08-31 23:59:59.0유통전문판매업334280.860598255888.547077유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.0<NA><NA><NA>
12111212유통전문판매업07_22_17_P34800003480000-113-2021-0000120210112<NA>1영업/정상1영업<NA><NA><NA><NA>053267 371721.30<NA>대구광역시 달성군 유가읍 금리 1149-10 1층대구광역시 달성군 유가읍 테크노중앙대로1길 38-6, 1층43024(주)리앤힐바이오20220629170454U2022-07-02 02:40:00.0유통전문판매업331679.0242514.0유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12121213유통전문판매업07_22_17_P34800003480000-113-2020-0001720201221<NA>1영업/정상1영업<NA><NA><NA><NA><NA>150.25711814대구광역시 달성군 다사읍 세천리 1686-2 2층대구광역시 달성군 다사읍 세천로6길 8, 2층42921주식회사 지룩20211027095301U2021-10-29 02:40:00.0유통전문판매업332798.969329264572.080152유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12131214유통전문판매업07_22_17_P34800003480000-113-2022-0001120220628<NA>1영업/정상1영업<NA><NA><NA><NA>053558 2345.00<NA>대구광역시 달성군 유가읍 유곡리 1163-9 (주)도야지식품대구광역시 달성군 유가읍 테크노중앙대로 20 (주)도야지식품42993(주)도야지식품20220628145122I2022-06-30 00:22:30.0유통전문판매업332236.415742242646.872394유통전문판매업00<NA><NA>상수도전용00000자가00N0.0<NA><NA><NA>
12141215유통전문판매업07_22_17_P34800003480000-113-2022-0001020220530<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00711812대구광역시 달성군 다사읍 매곡리 1517-6 1층대구광역시 달성군 다사읍 대실역북로2길 176, 1층42910엔돌핀식품20220530163648I2022-06-04 00:22:32.0유통전문판매업332064.648972263802.189758유통전문판매업00<NA><NA>상수도전용00000자가00N0.0<NA><NA><NA>
12151216유통전문판매업07_22_17_P34800003480000-113-2022-0000820220503<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4.10711812대구광역시 달성군 다사읍 매곡리 1523 1층대구광역시 달성군 다사읍 대실역북로5길 54, 1층42911파파크롭20220512170803U2022-05-14 02:40:00.0유통전문판매업332275.245171263774.892269유통전문판매업00<NA><NA>상수도전용00000자가00N0.0<NA><NA><NA>
12161217유통전문판매업07_22_17_P34800003480000-113-2022-0000920220523<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.00711862대구광역시 달성군 가창면 주리 485-1대구광역시 달성군 가창면 주리2길 48, 1층42939라운드힐 90520220524171341I2022-05-25 00:22:31.0유통전문판매업346712.253087251342.002897유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12171218유통전문판매업07_22_17_P34800003480000-113-2019-0000120190123<NA>3폐업2폐업20220524<NA><NA><NA><NA>33.00<NA>대구광역시 달성군 옥포읍 본리리 988-2대구광역시 달성군 옥포읍 옥계길 5742970씨지에프 주식회사20220524161250U2022-05-26 02:40:00.0유통전문판매업331725.0255856.0유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12181219유통전문판매업07_22_17_P34800003480000-113-2019-0000320190418<NA>3폐업2폐업20211125<NA><NA><NA><NA>20.00<NA>대구광역시 달성군 옥포읍 교항리 1076대구광역시 달성군 옥포읍 교항3길 20, 2층42969인터푸드20211125093443U2021-11-27 02:40:00.0유통전문판매업330037.52576255756.813647유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>