Overview

Dataset statistics

Number of variables47
Number of observations1004
Missing cells12180
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory398.2 KiB
Average record size in memory406.1 B

Variable types

Numeric12
Categorical17
Text6
Unsupported10
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_17_P_유통전문판매업_11월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000086708&dataSetDetailId=DDI_0000086754&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (98.9%)Imbalance
여성종사자수 is highly imbalanced (98.9%)Imbalance
본사종업원수 is highly imbalanced (59.5%)Imbalance
공장생산직종업원수 is highly imbalanced (52.6%)Imbalance
보증액 is highly imbalanced (95.5%)Imbalance
월세액 is highly imbalanced (95.5%)Imbalance
인허가취소일자 has 1004 (100.0%) missing valuesMissing
폐업일자 has 432 (43.0%) missing valuesMissing
휴업시작일자 has 1004 (100.0%) missing valuesMissing
휴업종료일자 has 1004 (100.0%) missing valuesMissing
재개업일자 has 1004 (100.0%) missing valuesMissing
소재지전화 has 355 (35.4%) missing valuesMissing
소재지면적 has 140 (13.9%) missing valuesMissing
소재지우편번호 has 17 (1.7%) missing valuesMissing
도로명전체주소 has 231 (23.0%) missing valuesMissing
도로명우편번호 has 234 (23.3%) missing valuesMissing
좌표정보(X) has 20 (2.0%) missing valuesMissing
좌표정보(Y) has 20 (2.0%) missing valuesMissing
영업장주변구분명 has 1004 (100.0%) missing valuesMissing
등급구분명 has 1004 (100.0%) missing valuesMissing
총종업원수 has 1004 (100.0%) missing valuesMissing
공장사무직종업원수 has 345 (34.4%) missing valuesMissing
공장판매직종업원수 has 345 (34.4%) missing valuesMissing
전통업소지정번호 has 1004 (100.0%) missing valuesMissing
전통업소주된음식 has 1004 (100.0%) missing valuesMissing
홈페이지 has 1004 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장사무직종업원수 has 595 (59.3%) zerosZeros
공장판매직종업원수 has 618 (61.6%) zerosZeros
시설총규모 has 934 (93.0%) zerosZeros

Reproduction

Analysis started2024-04-21 14:47:44.536563
Analysis finished2024-04-21 14:47:46.102265
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1004
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean502.5
Minimum1
Maximum1004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:47:46.235199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.15
Q1251.75
median502.5
Q3753.25
95-th percentile953.85
Maximum1004
Range1003
Interquartile range (IQR)501.5

Descriptive statistics

Standard deviation289.97414
Coefficient of variation (CV)0.57706296
Kurtosis-1.2
Mean502.5
Median Absolute Deviation (MAD)251
Skewness0
Sum504510
Variance84085
MonotonicityStrictly increasing
2024-04-21T23:47:46.488871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
676 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
667 1
 
0.1%
668 1
 
0.1%
669 1
 
0.1%
670 1
 
0.1%
Other values (994) 994
99.0%
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 (%)
1004 1
0.1%
1003 1
0.1%
1002 1
0.1%
1001 1
0.1%
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%
995 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유통전문판매업
1004 

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 1004
100.0%

Length

2024-04-21T23:47:46.710895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:46.864711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1004
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
07_22_17_P
1004 

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 1004
100.0%

Length

2024-04-21T23:47:47.029572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:47.184640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_17_p 1004
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447470.1
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:47:47.325450image/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 deviation21452.122
Coefficient of variation (CV)0.0062225693
Kurtosis-1.092543
Mean3447470.1
Median Absolute Deviation (MAD)20000
Skewness-0.25061288
Sum3.46126 × 109
Variance4.6019352 × 108
MonotonicityIncreasing
2024-04-21T23:47:47.518928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 206
20.5%
3460000 176
17.5%
3420000 150
14.9%
3470000 141
14.0%
3480000 99
9.9%
3430000 84
8.4%
3410000 81
 
8.1%
3440000 67
 
6.7%
ValueCountFrequency (%)
3410000 81
 
8.1%
3420000 150
14.9%
3430000 84
8.4%
3440000 67
 
6.7%
3450000 206
20.5%
3460000 176
17.5%
3470000 141
14.0%
3480000 99
9.9%
ValueCountFrequency (%)
3480000 99
9.9%
3470000 141
14.0%
3460000 176
17.5%
3450000 206
20.5%
3440000 67
 
6.7%
3430000 84
8.4%
3420000 150
14.9%
3410000 81
 
8.1%

관리번호
Text

UNIQUE 

Distinct1004
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-21T23:47:48.137298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22088
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

Unique1004 ?
Unique (%)100.0%

Sample

1st row3410000-113-2015-00001
2nd row3410000-113-2015-00002
3rd row3410000-113-2015-00003
4th row3410000-113-2015-00004
5th row3410000-113-2015-00005
ValueCountFrequency (%)
3410000-113-2015-00001 1
 
0.1%
3460000-113-2002-00003 1
 
0.1%
3460000-113-1997-00002 1
 
0.1%
3460000-113-2019-00010 1
 
0.1%
3460000-113-1997-00001 1
 
0.1%
3460000-113-2015-00008 1
 
0.1%
3460000-113-1999-00001 1
 
0.1%
3460000-113-1999-00003 1
 
0.1%
3460000-113-1999-00004 1
 
0.1%
3460000-113-2000-00001 1
 
0.1%
Other values (994) 994
99.0%
2024-04-21T23:47:48.968561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9310
42.1%
1 3118
 
14.1%
- 3012
 
13.6%
3 2299
 
10.4%
2 1452
 
6.6%
4 1278
 
5.8%
5 434
 
2.0%
6 363
 
1.6%
7 293
 
1.3%
9 270
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19076
86.4%
Dash Punctuation 3012
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9310
48.8%
1 3118
 
16.3%
3 2299
 
12.1%
2 1452
 
7.6%
4 1278
 
6.7%
5 434
 
2.3%
6 363
 
1.9%
7 293
 
1.5%
9 270
 
1.4%
8 259
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 3012
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22088
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9310
42.1%
1 3118
 
14.1%
- 3012
 
13.6%
3 2299
 
10.4%
2 1452
 
6.6%
4 1278
 
5.8%
5 434
 
2.0%
6 363
 
1.6%
7 293
 
1.3%
9 270
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9310
42.1%
1 3118
 
14.1%
- 3012
 
13.6%
3 2299
 
10.4%
2 1452
 
6.6%
4 1278
 
5.8%
5 434
 
2.0%
6 363
 
1.6%
7 293
 
1.3%
9 270
 
1.2%

인허가일자
Real number (ℝ)

Distinct851
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122438
Minimum19950510
Maximum20201127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:47:49.222816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950510
5-th percentile20002576
Q120080213
median20140929
Q320171050
95-th percentile20200617
Maximum20201127
Range250617
Interquartile range (IQR)90837

Descriptive statistics

Standard deviation63474.512
Coefficient of variation (CV)0.0031544146
Kurtosis-0.66173563
Mean20122438
Median Absolute Deviation (MAD)40809
Skewness-0.66922017
Sum2.0202928 × 1010
Variance4.0290136 × 109
MonotonicityNot monotonic
2024-04-21T23:47:49.484212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170320 5
 
0.5%
20180508 4
 
0.4%
20121105 4
 
0.4%
20190826 4
 
0.4%
20151109 3
 
0.3%
20200911 3
 
0.3%
20140508 3
 
0.3%
20150625 3
 
0.3%
20121204 3
 
0.3%
20130605 3
 
0.3%
Other values (841) 969
96.5%
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 (%)
20201127 2
0.2%
20201126 1
0.1%
20201118 1
0.1%
20201117 1
0.1%
20201113 2
0.2%
20201111 1
0.1%
20201106 1
0.1%
20201030 1
0.1%
20201022 1
0.1%
20201019 2
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
3
572 
1
432 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 572
57.0%
1 432
43.0%

Length

2024-04-21T23:47:49.709308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:49.870310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 572
57.0%
1 432
43.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
폐업
572 
영업/정상
432 

Length

Max length5
Median length2
Mean length3.2908367
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 572
57.0%
영업/정상 432
43.0%

Length

2024-04-21T23:47:50.052058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:50.230927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 572
57.0%
영업/정상 432
43.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2
572 
1
432 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 572
57.0%
1 432
43.0%

Length

2024-04-21T23:47:50.400086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:50.561641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 572
57.0%
1 432
43.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
폐업
572 
영업
432 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 572
57.0%
영업 432
43.0%

Length

2024-04-21T23:47:50.729159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:47:50.890400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 572
57.0%
영업 432
43.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct511
Distinct (%)89.3%
Missing432
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean20128644
Minimum20001029
Maximum20201130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:47:51.088015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001029
5-th percentile20040265
Q120080124
median20141172
Q320180410
95-th percentile20200618
Maximum20201130
Range200101
Interquartile range (IQR)100285.5

Descriptive statistics

Standard deviation55628.486
Coefficient of variation (CV)0.0027636479
Kurtosis-1.2380953
Mean20128644
Median Absolute Deviation (MAD)48943
Skewness-0.38972001
Sum1.1513585 × 1010
Variance3.0945284 × 109
MonotonicityNot monotonic
2024-04-21T23:47:51.363910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 5
 
0.5%
20070116 4
 
0.4%
20191227 3
 
0.3%
20021224 3
 
0.3%
20040830 3
 
0.3%
20161229 3
 
0.3%
20151229 3
 
0.3%
20051128 3
 
0.3%
20201028 3
 
0.3%
20201124 3
 
0.3%
Other values (501) 539
53.7%
(Missing) 432
43.0%
ValueCountFrequency (%)
20001029 1
 
0.1%
20020507 1
 
0.1%
20020722 1
 
0.1%
20020808 1
 
0.1%
20020827 1
 
0.1%
20021023 1
 
0.1%
20021205 1
 
0.1%
20021223 1
 
0.1%
20021224 3
0.3%
20021227 1
 
0.1%
ValueCountFrequency (%)
20201130 1
 
0.1%
20201125 2
0.2%
20201124 3
0.3%
20201119 1
 
0.1%
20201116 1
 
0.1%
20201113 1
 
0.1%
20201104 1
 
0.1%
20201029 1
 
0.1%
20201028 3
0.3%
20201026 2
0.2%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

소재지전화
Text

MISSING 

Distinct605
Distinct (%)93.2%
Missing355
Missing (%)35.4%
Memory size8.0 KiB
2024-04-21T23:47:52.062120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.901387
Min length7

Characters and Unicode

Total characters7075
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

Unique566 ?
Unique (%)87.2%

Sample

1st row053 2532230
2nd row053 2543717
3rd row053 2521737
4th row053 256 4077
5th row053 381 0039
ValueCountFrequency (%)
053 454
32.2%
070 35
 
2.5%
311 9
 
0.6%
313 8
 
0.6%
746 7
 
0.5%
625 7
 
0.5%
312 7
 
0.5%
9909 6
 
0.4%
755 5
 
0.4%
742 4
 
0.3%
Other values (740) 870
61.6%
2024-04-21T23:47:52.942856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1071
15.1%
0 1023
14.5%
3 946
13.4%
769
10.9%
2 528
7.5%
1 528
7.5%
7 509
7.2%
6 452
6.4%
4 444
6.3%
8 444
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6306
89.1%
Space Separator 769
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1071
17.0%
0 1023
16.2%
3 946
15.0%
2 528
8.4%
1 528
8.4%
7 509
8.1%
6 452
7.2%
4 444
7.0%
8 444
7.0%
9 361
 
5.7%
Space Separator
ValueCountFrequency (%)
769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7075
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1071
15.1%
0 1023
14.5%
3 946
13.4%
769
10.9%
2 528
7.5%
1 528
7.5%
7 509
7.2%
6 452
6.4%
4 444
6.3%
8 444
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7075
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1071
15.1%
0 1023
14.5%
3 946
13.4%
769
10.9%
2 528
7.5%
1 528
7.5%
7 509
7.2%
6 452
6.4%
4 444
6.3%
8 444
6.3%

소재지면적
Text

MISSING 

Distinct597
Distinct (%)69.1%
Missing140
Missing (%)13.9%
Memory size8.0 KiB
2024-04-21T23:47:54.361110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0196759
Min length3

Characters and Unicode

Total characters4337
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

Unique506 ?
Unique (%)58.6%

Sample

1st row.00
2nd row3.30
3rd row14.40
4th row71.00
5th row9.50
ValueCountFrequency (%)
00 38
 
4.4%
33.00 25
 
2.9%
30.00 14
 
1.6%
16.50 10
 
1.2%
3.30 10
 
1.2%
50.00 8
 
0.9%
25.00 8
 
0.9%
66.00 8
 
0.9%
10.00 7
 
0.8%
20.00 6
 
0.7%
Other values (587) 730
84.5%
2024-04-21T23:47:56.111749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 994
22.9%
. 864
19.9%
1 388
 
8.9%
2 362
 
8.3%
3 322
 
7.4%
5 292
 
6.7%
4 262
 
6.0%
6 250
 
5.8%
8 206
 
4.7%
9 199
 
4.6%
Other values (2) 198
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3470
80.0%
Other Punctuation 867
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 994
28.6%
1 388
 
11.2%
2 362
 
10.4%
3 322
 
9.3%
5 292
 
8.4%
4 262
 
7.6%
6 250
 
7.2%
8 206
 
5.9%
9 199
 
5.7%
7 195
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 864
99.7%
, 3
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4337
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 994
22.9%
. 864
19.9%
1 388
 
8.9%
2 362
 
8.3%
3 322
 
7.4%
5 292
 
6.7%
4 262
 
6.0%
6 250
 
5.8%
8 206
 
4.7%
9 199
 
4.6%
Other values (2) 198
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4337
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 994
22.9%
. 864
19.9%
1 388
 
8.9%
2 362
 
8.3%
3 322
 
7.4%
5 292
 
6.7%
4 262
 
6.0%
6 250
 
5.8%
8 206
 
4.7%
9 199
 
4.6%
Other values (2) 198
 
4.6%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct373
Distinct (%)37.8%
Missing17
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean704459.91
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:47:56.363667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700802.3
Q1702090
median703830
Q3706220
95-th percentile711833
Maximum711892
Range11882
Interquartile range (IQR)4130

Descriptive statistics

Standard deviation2982.7287
Coefficient of variation (CV)0.0042340644
Kurtosis0.68217644
Mean704459.91
Median Absolute Deviation (MAD)1982
Skewness1.0158026
Sum6.9530194 × 108
Variance8896670.2
MonotonicityNot monotonic
2024-04-21T23:47:56.620538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 19
 
1.9%
703100 13
 
1.3%
703830 12
 
1.2%
700230 10
 
1.0%
711851 9
 
0.9%
706818 9
 
0.9%
704080 9
 
0.9%
701824 9
 
0.9%
706803 8
 
0.8%
711833 8
 
0.8%
Other values (363) 881
87.7%
(Missing) 17
 
1.7%
ValueCountFrequency (%)
700010 2
 
0.2%
700040 3
 
0.3%
700070 1
 
0.1%
700092 3
 
0.3%
700111 1
 
0.1%
700150 2
 
0.2%
700170 1
 
0.1%
700180 1
 
0.1%
700230 10
1.0%
700240 1
 
0.1%
ValueCountFrequency (%)
711892 2
 
0.2%
711891 3
 
0.3%
711874 1
 
0.1%
711863 5
0.5%
711858 3
 
0.3%
711856 1
 
0.1%
711855 6
0.6%
711852 3
 
0.3%
711851 9
0.9%
711845 4
0.4%
Distinct962
Distinct (%)95.9%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-21T23:47:57.736078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length24.258225
Min length17

Characters and Unicode

Total characters24331
Distinct characters257
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique926 ?
Unique (%)92.3%

Sample

1st row대구광역시 중구 사일동 0059번지 영스퀘어
2nd row대구광역시 중구 남성로 0113번지 지상1층
3rd row대구광역시 중구 남성로 0020-0004번지
4th row대구광역시 중구 동인동3가 0282-0020번지 지상1층
5th row대구광역시 중구 남성로 0118번지 지상2층
ValueCountFrequency (%)
대구광역시 1003
22.1%
북구 206
 
4.5%
수성구 175
 
3.9%
동구 150
 
3.3%
달서구 140
 
3.1%
달성군 100
 
2.2%
서구 84
 
1.8%
중구 81
 
1.8%
남구 67
 
1.5%
1층 56
 
1.2%
Other values (1299) 2479
54.6%
2024-04-21T23:47:59.292918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4520
18.6%
1942
 
8.0%
1 1183
 
4.9%
1119
 
4.6%
1094
 
4.5%
1050
 
4.3%
1018
 
4.2%
1004
 
4.1%
1003
 
4.1%
889
 
3.7%
Other values (247) 9509
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13669
56.2%
Decimal Number 5123
 
21.1%
Space Separator 4520
 
18.6%
Dash Punctuation 833
 
3.4%
Open Punctuation 74
 
0.3%
Close Punctuation 74
 
0.3%
Uppercase Letter 22
 
0.1%
Other Punctuation 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1942
14.2%
1119
 
8.2%
1094
 
8.0%
1050
 
7.7%
1018
 
7.4%
1004
 
7.3%
1003
 
7.3%
889
 
6.5%
347
 
2.5%
262
 
1.9%
Other values (221) 3941
28.8%
Decimal Number
ValueCountFrequency (%)
1 1183
23.1%
0 667
13.0%
2 665
13.0%
3 494
9.6%
5 415
 
8.1%
4 384
 
7.5%
8 348
 
6.8%
6 347
 
6.8%
7 325
 
6.3%
9 295
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
27.3%
A 3
13.6%
T 3
13.6%
C 2
 
9.1%
D 2
 
9.1%
J 2
 
9.1%
P 2
 
9.1%
N 1
 
4.5%
F 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 13
81.2%
/ 2
 
12.5%
. 1
 
6.2%
Space Separator
ValueCountFrequency (%)
4520
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 833
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13669
56.2%
Common 10640
43.7%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1942
14.2%
1119
 
8.2%
1094
 
8.0%
1050
 
7.7%
1018
 
7.4%
1004
 
7.3%
1003
 
7.3%
889
 
6.5%
347
 
2.5%
262
 
1.9%
Other values (221) 3941
28.8%
Common
ValueCountFrequency (%)
4520
42.5%
1 1183
 
11.1%
- 833
 
7.8%
0 667
 
6.3%
2 665
 
6.2%
3 494
 
4.6%
5 415
 
3.9%
4 384
 
3.6%
8 348
 
3.3%
6 347
 
3.3%
Other values (7) 784
 
7.4%
Latin
ValueCountFrequency (%)
B 6
27.3%
A 3
13.6%
T 3
13.6%
C 2
 
9.1%
D 2
 
9.1%
J 2
 
9.1%
P 2
 
9.1%
N 1
 
4.5%
F 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13669
56.2%
ASCII 10662
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4520
42.4%
1 1183
 
11.1%
- 833
 
7.8%
0 667
 
6.3%
2 665
 
6.2%
3 494
 
4.6%
5 415
 
3.9%
4 384
 
3.6%
8 348
 
3.3%
6 347
 
3.3%
Other values (16) 806
 
7.6%
Hangul
ValueCountFrequency (%)
1942
14.2%
1119
 
8.2%
1094
 
8.0%
1050
 
7.7%
1018
 
7.4%
1004
 
7.3%
1003
 
7.3%
889
 
6.5%
347
 
2.5%
262
 
1.9%
Other values (221) 3941
28.8%

도로명전체주소
Text

MISSING 

Distinct754
Distinct (%)97.5%
Missing231
Missing (%)23.0%
Memory size8.0 KiB
2024-04-21T23:48:00.604484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length28.725744
Min length20

Characters and Unicode

Total characters22205
Distinct characters297
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

Unique737 ?
Unique (%)95.3%

Sample

1st row대구광역시 중구 동성로 25, 영스퀘어 9층 965호 (사일동)
2nd row대구광역시 중구 남성로 30 (남성로, 지상1층)
3rd row대구광역시 중구 남성로 3-1 (남성로)
4th row대구광역시 중구 국채보상로143길 74-16 (동인동3가, 지상1층)
5th row대구광역시 중구 약령길 42 (남성로, 지상2층)
ValueCountFrequency (%)
대구광역시 773
 
16.8%
1층 235
 
5.1%
북구 156
 
3.4%
수성구 137
 
3.0%
동구 114
 
2.5%
달서구 103
 
2.2%
2층 94
 
2.0%
달성군 83
 
1.8%
중구 71
 
1.5%
서구 62
 
1.3%
Other values (1234) 2766
60.2%
2024-04-21T23:48:02.211967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3821
 
17.2%
1554
 
7.0%
985
 
4.4%
983
 
4.4%
1 883
 
4.0%
793
 
3.6%
782
 
3.5%
773
 
3.5%
737
 
3.3%
( 720
 
3.2%
Other values (287) 10174
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12553
56.5%
Space Separator 3821
 
17.2%
Decimal Number 3563
 
16.0%
Open Punctuation 720
 
3.2%
Close Punctuation 720
 
3.2%
Other Punctuation 602
 
2.7%
Dash Punctuation 190
 
0.9%
Uppercase Letter 32
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1554
 
12.4%
985
 
7.8%
983
 
7.8%
793
 
6.3%
782
 
6.2%
773
 
6.2%
737
 
5.9%
522
 
4.2%
433
 
3.4%
341
 
2.7%
Other values (261) 4650
37.0%
Decimal Number
ValueCountFrequency (%)
1 883
24.8%
2 590
16.6%
3 436
12.2%
4 322
 
9.0%
5 293
 
8.2%
6 251
 
7.0%
0 246
 
6.9%
7 214
 
6.0%
8 182
 
5.1%
9 146
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 13
40.6%
A 9
28.1%
T 3
 
9.4%
J 3
 
9.4%
P 2
 
6.2%
N 1
 
3.1%
D 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 600
99.7%
/ 1
 
0.2%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3821
100.0%
Open Punctuation
ValueCountFrequency (%)
( 720
100.0%
Close Punctuation
ValueCountFrequency (%)
) 720
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12553
56.5%
Common 9618
43.3%
Latin 34
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1554
 
12.4%
985
 
7.8%
983
 
7.8%
793
 
6.3%
782
 
6.2%
773
 
6.2%
737
 
5.9%
522
 
4.2%
433
 
3.4%
341
 
2.7%
Other values (261) 4650
37.0%
Common
ValueCountFrequency (%)
3821
39.7%
1 883
 
9.2%
( 720
 
7.5%
) 720
 
7.5%
, 600
 
6.2%
2 590
 
6.1%
3 436
 
4.5%
4 322
 
3.3%
5 293
 
3.0%
6 251
 
2.6%
Other values (8) 982
 
10.2%
Latin
ValueCountFrequency (%)
B 13
38.2%
A 9
26.5%
T 3
 
8.8%
J 3
 
8.8%
P 2
 
5.9%
e 2
 
5.9%
N 1
 
2.9%
D 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12553
56.5%
ASCII 9652
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3821
39.6%
1 883
 
9.1%
( 720
 
7.5%
) 720
 
7.5%
, 600
 
6.2%
2 590
 
6.1%
3 436
 
4.5%
4 322
 
3.3%
5 293
 
3.0%
6 251
 
2.6%
Other values (16) 1016
 
10.5%
Hangul
ValueCountFrequency (%)
1554
 
12.4%
985
 
7.8%
983
 
7.8%
793
 
6.3%
782
 
6.2%
773
 
6.2%
737
 
5.9%
522
 
4.2%
433
 
3.4%
341
 
2.7%
Other values (261) 4650
37.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct481
Distinct (%)62.5%
Missing234
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean41998.019
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:02.462529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41073
Q141487
median41954
Q342489.75
95-th percentile42968
Maximum43024
Range2024
Interquartile range (IQR)1002.75

Descriptive statistics

Standard deviation594.47668
Coefficient of variation (CV)0.014154874
Kurtosis-1.1311364
Mean41998.019
Median Absolute Deviation (MAD)476.5
Skewness0.13361307
Sum32338475
Variance353402.53
MonotonicityNot monotonic
2024-04-21T23:48:02.728877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 12
 
1.2%
41490 12
 
1.2%
41934 9
 
0.9%
41750 8
 
0.8%
42922 6
 
0.6%
42974 6
 
0.6%
42162 6
 
0.6%
41472 6
 
0.6%
41256 5
 
0.5%
42970 5
 
0.5%
Other values (471) 695
69.2%
(Missing) 234
 
23.3%
ValueCountFrequency (%)
41000 2
0.2%
41001 1
0.1%
41007 1
0.1%
41008 2
0.2%
41009 2
0.2%
41015 1
0.1%
41020 2
0.2%
41026 1
0.1%
41027 1
0.1%
41028 2
0.2%
ValueCountFrequency (%)
43024 1
0.1%
43023 1
0.1%
43018 1
0.1%
43014 1
0.1%
43013 1
0.1%
43011 1
0.1%
43009 1
0.1%
43003 1
0.1%
42996 1
0.1%
42993 2
0.2%
Distinct928
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-21T23:48:03.559212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.5557769
Min length2

Characters and Unicode

Total characters6582
Distinct characters556
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique864 ?
Unique (%)86.1%

Sample

1st row디스커버리 컴퍼니
2nd row약령길
3rd row초목약업사,초목허브
4th row장보기
5th row다소목
ValueCountFrequency (%)
주식회사 46
 
4.1%
농업회사법인 7
 
0.6%
선진vfc 6
 
0.5%
5
 
0.4%
아세아그린팜 3
 
0.3%
한미네츄럴 3
 
0.3%
company 3
 
0.3%
산수원 3
 
0.3%
자연애 3
 
0.3%
주)프로페셔널 3
 
0.3%
Other values (961) 1032
92.6%
2024-04-21T23:48:04.599452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
 
5.3%
) 302
 
4.6%
( 300
 
4.6%
205
 
3.1%
170
 
2.6%
149
 
2.3%
118
 
1.8%
111
 
1.7%
111
 
1.7%
110
 
1.7%
Other values (546) 4660
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5581
84.8%
Close Punctuation 302
 
4.6%
Open Punctuation 300
 
4.6%
Uppercase Letter 128
 
1.9%
Lowercase Letter 123
 
1.9%
Space Separator 110
 
1.7%
Other Punctuation 18
 
0.3%
Decimal Number 17
 
0.3%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
346
 
6.2%
205
 
3.7%
170
 
3.0%
149
 
2.7%
118
 
2.1%
111
 
2.0%
111
 
2.0%
104
 
1.9%
92
 
1.6%
85
 
1.5%
Other values (487) 4090
73.3%
Uppercase Letter
ValueCountFrequency (%)
F 20
15.6%
C 19
14.8%
S 15
11.7%
V 7
 
5.5%
D 7
 
5.5%
B 6
 
4.7%
I 6
 
4.7%
M 6
 
4.7%
N 6
 
4.7%
T 5
 
3.9%
Other values (12) 31
24.2%
Lowercase Letter
ValueCountFrequency (%)
n 16
13.0%
a 14
11.4%
o 13
10.6%
e 13
10.6%
t 11
8.9%
i 10
8.1%
l 8
 
6.5%
y 7
 
5.7%
r 5
 
4.1%
u 4
 
3.3%
Other values (11) 22
17.9%
Decimal Number
ValueCountFrequency (%)
2 4
23.5%
9 3
17.6%
1 3
17.6%
3 2
11.8%
4 2
11.8%
7 1
 
5.9%
0 1
 
5.9%
5 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
& 11
61.1%
. 6
33.3%
, 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 302
100.0%
Open Punctuation
ValueCountFrequency (%)
( 300
100.0%
Space Separator
ValueCountFrequency (%)
110
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5583
84.8%
Common 748
 
11.4%
Latin 251
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
346
 
6.2%
205
 
3.7%
170
 
3.0%
149
 
2.7%
118
 
2.1%
111
 
2.0%
111
 
2.0%
104
 
1.9%
92
 
1.6%
85
 
1.5%
Other values (488) 4092
73.3%
Latin
ValueCountFrequency (%)
F 20
 
8.0%
C 19
 
7.6%
n 16
 
6.4%
S 15
 
6.0%
a 14
 
5.6%
o 13
 
5.2%
e 13
 
5.2%
t 11
 
4.4%
i 10
 
4.0%
l 8
 
3.2%
Other values (33) 112
44.6%
Common
ValueCountFrequency (%)
) 302
40.4%
( 300
40.1%
110
 
14.7%
& 11
 
1.5%
. 6
 
0.8%
2 4
 
0.5%
9 3
 
0.4%
1 3
 
0.4%
3 2
 
0.3%
4 2
 
0.3%
Other values (5) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5581
84.8%
ASCII 999
 
15.2%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
346
 
6.2%
205
 
3.7%
170
 
3.0%
149
 
2.7%
118
 
2.1%
111
 
2.0%
111
 
2.0%
104
 
1.9%
92
 
1.6%
85
 
1.5%
Other values (487) 4090
73.3%
ASCII
ValueCountFrequency (%)
) 302
30.2%
( 300
30.0%
110
 
11.0%
F 20
 
2.0%
C 19
 
1.9%
n 16
 
1.6%
S 15
 
1.5%
a 14
 
1.4%
o 13
 
1.3%
e 13
 
1.3%
Other values (48) 177
17.7%
None
ValueCountFrequency (%)
2
100.0%

최종수정시점
Real number (ℝ)

Distinct946
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.014206 × 1013
Minimum2.0010823 × 1013
Maximum2.020113 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:04.844543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0021013 × 1013
Q12.0100387 × 1013
median2.0170219 × 1013
Q32.019073 × 1013
95-th percentile2.0201014 × 1013
Maximum2.020113 × 1013
Range1.9030715 × 1011
Interquartile range (IQR)9.0343784 × 1010

Descriptive statistics

Standard deviation5.9344828 × 1010
Coefficient of variation (CV)0.0029463138
Kurtosis-0.67247819
Mean2.014206 × 1013
Median Absolute Deviation (MAD)3.0147486 × 1010
Skewness-0.83725415
Sum2.0222628 × 1016
Variance3.5218087 × 1021
MonotonicityNot monotonic
2024-04-21T23:48:05.107556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020530000000 12
 
1.2%
20021113000000 10
 
1.0%
20020126000000 9
 
0.9%
20020115000000 5
 
0.5%
20021019000000 5
 
0.5%
20020510000000 5
 
0.5%
20021012000000 3
 
0.3%
20060825000000 3
 
0.3%
20041011000000 3
 
0.3%
20140512105112 3
 
0.3%
Other values (936) 946
94.2%
ValueCountFrequency (%)
20010823000000 1
 
0.1%
20020115000000 5
0.5%
20020124000000 2
 
0.2%
20020125000000 2
 
0.2%
20020126000000 9
0.9%
20020326000000 1
 
0.1%
20020403000000 1
 
0.1%
20020416000000 1
 
0.1%
20020503000000 1
 
0.1%
20020507000000 1
 
0.1%
ValueCountFrequency (%)
20201130154115 1
0.1%
20201130133947 1
0.1%
20201130113318 1
0.1%
20201130111951 1
0.1%
20201130105225 1
0.1%
20201127114845 1
0.1%
20201127114825 1
0.1%
20201127110700 1
0.1%
20201126162012 1
0.1%
20201126124642 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
I
693 
U
311 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 693
69.0%
U 311
31.0%

Length

2024-04-21T23:48:05.341675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:05.502923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 693
69.0%
u 311
31.0%
Distinct285
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-02 02:40:00
2024-04-21T23:48:05.686615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:48:05.939666image/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 size8.0 KiB
유통전문판매업
1004 

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 1004
100.0%

Length

2024-04-21T23:48:06.173471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:06.328236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1004
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct908
Distinct (%)92.3%
Missing20
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean342766.47
Minimum325733.86
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:06.506716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325733.86
5-th percentile332581.83
Q1339197.06
median343083.45
Q3346522.32
95-th percentile353008.02
Maximum358046.4
Range32312.548
Interquartile range (IQR)7325.2619

Descriptive statistics

Standard deviation5640.4653
Coefficient of variation (CV)0.016455709
Kurtosis0.14910554
Mean342766.47
Median Absolute Deviation (MAD)3621.8699
Skewness-0.079929025
Sum3.372822 × 108
Variance31814849
MonotonicityNot monotonic
2024-04-21T23:48:06.750756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336590.459071 6
 
0.6%
345687.898519 3
 
0.3%
339320.839241 3
 
0.3%
329092.356185 3
 
0.3%
341215.925853 3
 
0.3%
338421.494971 3
 
0.3%
343157.682044 3
 
0.3%
346942.691097 3
 
0.3%
345206.578526 3
 
0.3%
344010.849417 3
 
0.3%
Other values (898) 951
94.7%
(Missing) 20
 
2.0%
ValueCountFrequency (%)
325733.855686 1
0.1%
326032.481595 1
0.1%
327448.497282 1
0.1%
327590.551952 1
0.1%
327894.698221 1
0.1%
328237.006988 1
0.1%
328520.607105 1
0.1%
328779.085065 1
0.1%
328874.867518 1
0.1%
328945.225812 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 

Distinct908
Distinct (%)92.3%
Missing20
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean263558.38
Minimum238306.85
Maximum277799.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:06.998281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238306.85
5-th percentile255783.09
Q1261137.14
median264082.17
Q3266069.13
95-th percentile271294.9
Maximum277799.71
Range39492.858
Interquartile range (IQR)4931.996

Descriptive statistics

Standard deviation5020.9003
Coefficient of variation (CV)0.019050429
Kurtosis4.001761
Mean263558.38
Median Absolute Deviation (MAD)2663.6378
Skewness-1.0378836
Sum2.5934145 × 108
Variance25209440
MonotonicityNot monotonic
2024-04-21T23:48:07.252608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257286.897263 6
 
0.6%
266987.666828 3
 
0.3%
265197.142652 3
 
0.3%
253359.522917 3
 
0.3%
260848.360361 3
 
0.3%
260797.727311 3
 
0.3%
261957.795169 3
 
0.3%
263989.847737 3
 
0.3%
260875.577524 3
 
0.3%
263014.492917 3
 
0.3%
Other values (898) 951
94.7%
(Missing) 20
 
2.0%
ValueCountFrequency (%)
238306.850311 1
0.1%
238531.35408 1
0.1%
239240.086699 1
0.1%
239536.919741 1
0.1%
240205.085494 1
0.1%
242273.0 1
0.1%
242311.21229 1
0.1%
243088.915629 1
0.1%
244839.424611 1
0.1%
245025.08546 1
0.1%
ValueCountFrequency (%)
277799.708684 1
0.1%
277755.206408 2
0.2%
277541.768688 1
0.1%
277428.083074 1
0.1%
275969.761183 1
0.1%
275787.590179 1
0.1%
274594.894588 1
0.1%
274508.218106 1
0.1%
274214.678839 1
0.1%
273994.885719 1
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유통전문판매업
1004 

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 1004
100.0%

Length

2024-04-21T23:48:07.489259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:07.643810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 1004
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
1003 
0
 
1

Length

Max length4
Median length4
Mean length3.997012
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1003
99.9%
0 1
 
0.1%

Length

2024-04-21T23:48:07.818070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:07.988110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1003
99.9%
0 1
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
1003 
0
 
1

Length

Max length4
Median length4
Mean length3.997012
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1003
99.9%
0 1
 
0.1%

Length

2024-04-21T23:48:08.166920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:08.351298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1003
99.9%
0 1
 
0.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
716 
상수도전용
286 
지하수전용
 
2

Length

Max length5
Median length4
Mean length4.2868526
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> 716
71.3%
상수도전용 286
 
28.5%
지하수전용 2
 
0.2%

Length

2024-04-21T23:48:08.661085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:08.998132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 716
71.3%
상수도전용 286
 
28.5%
지하수전용 2
 
0.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
0
645 
<NA>
345 
1
 
8
2
 
3
4
 
2

Length

Max length4
Median length1
Mean length2.0308765
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 645
64.2%
<NA> 345
34.4%
1 8
 
0.8%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%

Length

2024-04-21T23:48:09.365367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:09.706258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 645
64.2%
na 345
34.4%
1 8
 
0.8%
2 3
 
0.3%
4 2
 
0.2%
3 1
 
0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.9%
Missing345
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean0.14871017
Minimum0
Maximum6
Zeros595
Zeros (%)59.3%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:10.016635image/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 deviation0.53085125
Coefficient of variation (CV)3.5697038
Kurtosis33.474172
Mean0.14871017
Median Absolute Deviation (MAD)0
Skewness4.9636509
Sum98
Variance0.28180305
MonotonicityNot monotonic
2024-04-21T23:48:10.271391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 595
59.3%
1 40
 
4.0%
2 18
 
1.8%
3 4
 
0.4%
6 1
 
0.1%
4 1
 
0.1%
(Missing) 345
34.4%
ValueCountFrequency (%)
0 595
59.3%
1 40
 
4.0%
2 18
 
1.8%
3 4
 
0.4%
4 1
 
0.1%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 1
 
0.1%
3 4
 
0.4%
2 18
 
1.8%
1 40
 
4.0%
0 595
59.3%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.2%
Missing345
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean0.13657056
Minimum0
Maximum20
Zeros618
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:10.674919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.96418276
Coefficient of variation (CV)7.0599605
Kurtosis291.90543
Mean0.13657056
Median Absolute Deviation (MAD)0
Skewness15.468637
Sum90
Variance0.9296484
MonotonicityNot monotonic
2024-04-21T23:48:10.871258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 618
61.6%
1 25
 
2.5%
2 10
 
1.0%
3 2
 
0.2%
5 1
 
0.1%
20 1
 
0.1%
4 1
 
0.1%
10 1
 
0.1%
(Missing) 345
34.4%
ValueCountFrequency (%)
0 618
61.6%
1 25
 
2.5%
2 10
 
1.0%
3 2
 
0.2%
4 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%
20 1
 
0.1%
ValueCountFrequency (%)
20 1
 
0.1%
10 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 2
 
0.2%
2 10
 
1.0%
1 25
 
2.5%
0 618
61.6%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
0
635 
<NA>
346 
1
 
13
2
 
9
4
 
1

Length

Max length4
Median length1
Mean length2.0338645
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 635
63.2%
<NA> 346
34.5%
1 13
 
1.3%
2 9
 
0.9%
4 1
 
0.1%

Length

2024-04-21T23:48:11.105646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:11.294726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 635
63.2%
na 346
34.5%
1 13
 
1.3%
2 9
 
0.9%
4 1
 
0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
668 
자가
198 
임대
138 

Length

Max length4
Median length4
Mean length3.3306773
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> 668
66.5%
자가 198
 
19.7%
임대 138
 
13.7%

Length

2024-04-21T23:48:11.507530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:11.690893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 668
66.5%
자가 198
 
19.7%
임대 138
 
13.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
999 
0
 
5

Length

Max length4
Median length4
Mean length3.9850598
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 999
99.5%
0 5
 
0.5%

Length

2024-04-21T23:48:11.882853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:12.060108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 999
99.5%
0 5
 
0.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
<NA>
999 
0
 
5

Length

Max length4
Median length4
Mean length3.9850598
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 999
99.5%
0 5
 
0.5%

Length

2024-04-21T23:48:12.239942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:48:12.411281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 999
99.5%
0 5
 
0.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
False
1004 
ValueCountFrequency (%)
False 1004
100.0%
2024-04-21T23:48:12.543298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct55
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5820319
Minimum0
Maximum240
Zeros934
Zeros (%)93.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-04-21T23:48:12.727913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.925
Maximum240
Range240
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.348506
Coefficient of variation (CV)7.8054723
Kurtosis250.27731
Mean1.5820319
Median Absolute Deviation (MAD)0
Skewness14.576168
Sum1588.36
Variance152.4856
MonotonicityNot monotonic
2024-04-21T23:48:12.982556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 934
93.0%
5.0 4
 
0.4%
3.3 4
 
0.4%
10.0 3
 
0.3%
33.0 3
 
0.3%
8.0 2
 
0.2%
20.0 2
 
0.2%
6.6 2
 
0.2%
4.5 2
 
0.2%
4.0 2
 
0.2%
Other values (45) 46
 
4.6%
ValueCountFrequency (%)
0.0 934
93.0%
1.2 1
 
0.1%
2.18 1
 
0.1%
2.25 1
 
0.1%
2.55 1
 
0.1%
2.56 1
 
0.1%
2.75 1
 
0.1%
2.81 1
 
0.1%
3.0 1
 
0.1%
3.3 4
 
0.4%
ValueCountFrequency (%)
240.0 1
 
0.1%
222.12 1
 
0.1%
106.6 1
 
0.1%
101.52 1
 
0.1%
66.0 2
0.2%
51.68 1
 
0.1%
50.85 1
 
0.1%
35.0 1
 
0.1%
33.0 3
0.3%
31.32 1
 
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1004
Missing (%)100.0%
Memory size8.9 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01유통전문판매업07_22_17_P34100003410000-113-2015-0000120150213<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00700040대구광역시 중구 사일동 0059번지 영스퀘어대구광역시 중구 동성로 25, 영스퀘어 9층 965호 (사일동)41937디스커버리 컴퍼니20200615110303U2020-06-17 02:40:00.0유통전문판매업344936.761428263064.299672유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
12유통전문판매업07_22_17_P34100003410000-113-2015-0000220150422<NA>1영업/정상1영업<NA><NA><NA><NA>053 25322303.30700230대구광역시 중구 남성로 0113번지 지상1층대구광역시 중구 남성로 30 (남성로, 지상1층)41933약령길20151013085042I2018-08-31 23:59:59.0유통전문판매업343529.342134264220.392997유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23유통전문판매업07_22_17_P34100003410000-113-2015-0000320150424<NA>1영업/정상1영업<NA><NA><NA><NA>053 254371714.40700230대구광역시 중구 남성로 0020-0004번지대구광역시 중구 남성로 3-1 (남성로)41934초목약업사,초목허브20150625111246I2018-08-31 23:59:59.0유통전문판매업343330.382149264384.775463유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
34유통전문판매업07_22_17_P34100003410000-113-2015-0000420150527<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.00700845대구광역시 중구 동인동3가 0282-0020번지 지상1층대구광역시 중구 국채보상로143길 74-16 (동인동3가, 지상1층)41906장보기20160317172613I2018-08-31 23:59:59.0유통전문판매업345291.887665264734.736049유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
45유통전문판매업07_22_17_P34100003410000-113-2015-0000520150817<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.50700230대구광역시 중구 남성로 0118번지 지상2층대구광역시 중구 약령길 42 (남성로, 지상2층)41933다소목20150817164404I2018-08-31 23:59:59.0유통전문판매업343453.665498264264.14957유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
56유통전문판매업07_22_17_P34100003410000-113-2015-0000620150819<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00700240대구광역시 중구 장관동 0041-0001번지 지상1층대구광역시 중구 중앙대로77길 58 (장관동, 지상1층)41934우성약업사(우성허브)20150819123454I2018-08-31 23:59:59.0유통전문판매업343560.99747264321.514086유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
67유통전문판매업07_22_17_P34100003410000-113-2015-0000720150819<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.60700230대구광역시 중구 남성로 0058번지 지상1층대구광역시 중구 남성로 29-1 (남성로, 지상1층)41934아산약업사(아산허브)20150819123525I2018-08-31 23:59:59.0유통전문판매업343543.862553264242.822231유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78유통전문판매업07_22_17_P34100003410000-113-2017-0000620170918<NA>1영업/정상1영업<NA><NA><NA><NA>053 2521737.00700230대구광역시 중구 남성로 0051-0006 덕신빌딩대구광역시 중구 남성로 25, 덕신빌딩 지하1층 (남성로)41934대구약령시협동조합20200811172755U2020-08-13 02:40:00.0유통전문판매업343560.99747264321.514086유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
89유통전문판매업07_22_17_P34100003410000-113-2008-0000120081028<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.04700230대구광역시 중구 남성로 52-2대구광역시 중구 남성로 27-1 (남성로)41934큐엔바이오20200701170849U2020-07-03 02:40:00.0유통전문판매업343519.051121264287.551286유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0010<NA><NA><NA>N27.0<NA><NA><NA>
910유통전문판매업07_22_17_P34100003410000-113-2009-0000120090325<NA>1영업/정상1영업<NA><NA><NA><NA>053 256 407750.00700847대구광역시 중구 동인동4가 0206-0001번지 지상1층대구광역시 중구 국채보상로140길 17-11, 1층 (동인동4가)41945진가명가20120201155807I2018-08-31 23:59:59.0유통전문판매업345071.572032264292.844322유통전문판매업<NA><NA><NA><NA><NA><NA>0110임대<NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
994995유통전문판매업07_22_17_P34800003480000-113-2019-0001220191011<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>711851대구광역시 달성군 논공읍 금포리 1771-1번지 1층대구광역시 달성군 논공읍 노이길 72-1, 1층42975티오피글로벌20191011100448I2019-10-13 00:22:48.0유통전문판매업328779.085065253068.189867유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
995996유통전문판매업07_22_17_P34800003480000-113-2015-0000720150918<NA>1영업/정상1영업<NA><NA><NA><NA>032 821 4545.00711855대구광역시 달성군 논공읍 본리리 29-27번지 2층대구광역시 달성군 논공읍 논공로 626, 2층42981주식회사아라인터내셔널20191218161646I2019-12-20 00:23:35.0유통전문판매업331541.808475249475.583994유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
996997유통전문판매업07_22_17_P34800003480000-113-2020-0000320200331<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>711814대구광역시 달성군 다사읍 세천리 1572-9번지 1층대구광역시 달성군 다사읍 세천본길 45-13, 1층42922(주)이움20200331132936I2020-04-02 00:23:32.0유통전문판매업333418.909828265111.852339유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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