Overview

Dataset statistics

Number of variables47
Number of observations1996
Missing cells22168
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory791.5 KiB
Average record size in memory406.1 B

Variable types

Numeric11
Categorical19
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_08_P_식품소분업_11월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000086708&dataSetDetailId=DDI_0000086757&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (99.4%)Imbalance
위생업태명 is highly imbalanced (98.9%)Imbalance
남성종사자수 is highly imbalanced (96.2%)Imbalance
여성종사자수 is highly imbalanced (96.2%)Imbalance
본사종업원수 is highly imbalanced (58.4%)Imbalance
공장사무직종업원수 is highly imbalanced (57.9%)Imbalance
보증액 is highly imbalanced (89.0%)Imbalance
월세액 is highly imbalanced (93.9%)Imbalance
홈페이지 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 1996 (100.0%) missing valuesMissing
폐업일자 has 514 (25.8%) missing valuesMissing
휴업시작일자 has 1996 (100.0%) missing valuesMissing
휴업종료일자 has 1996 (100.0%) missing valuesMissing
재개업일자 has 1996 (100.0%) missing valuesMissing
소재지전화 has 725 (36.3%) missing valuesMissing
소재지면적 has 343 (17.2%) missing valuesMissing
도로명전체주소 has 908 (45.5%) missing valuesMissing
도로명우편번호 has 919 (46.0%) missing valuesMissing
좌표정보(X) has 86 (4.3%) missing valuesMissing
좌표정보(Y) has 86 (4.3%) missing valuesMissing
영업장주변구분명 has 1996 (100.0%) missing valuesMissing
등급구분명 has 1996 (100.0%) missing valuesMissing
총종업원수 has 1996 (100.0%) missing valuesMissing
공장생산직종업원수 has 601 (30.1%) missing valuesMissing
전통업소지정번호 has 1996 (100.0%) missing valuesMissing
전통업소주된음식 has 1996 (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
공장생산직종업원수 has 1198 (60.0%) zerosZeros
시설총규모 has 1922 (96.3%) zerosZeros

Reproduction

Analysis started2024-04-17 20:46:15.687615
Analysis finished2024-04-17 20:46:16.617371
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1996
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean998.5
Minimum1
Maximum1996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:16.673483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile100.75
Q1499.75
median998.5
Q31497.25
95-th percentile1896.25
Maximum1996
Range1995
Interquartile range (IQR)997.5

Descriptive statistics

Standard deviation576.33989
Coefficient of variation (CV)0.5772057
Kurtosis-1.2
Mean998.5
Median Absolute Deviation (MAD)499
Skewness0
Sum1993006
Variance332167.67
MonotonicityStrictly increasing
2024-04-18T05:46:16.780241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1328 1
 
0.1%
1341 1
 
0.1%
1340 1
 
0.1%
1339 1
 
0.1%
1338 1
 
0.1%
1337 1
 
0.1%
1336 1
 
0.1%
1335 1
 
0.1%
1334 1
 
0.1%
Other values (1986) 1986
99.5%
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 (%)
1996 1
0.1%
1995 1
0.1%
1994 1
0.1%
1993 1
0.1%
1992 1
0.1%
1991 1
0.1%
1990 1
0.1%
1989 1
0.1%
1988 1
0.1%
1987 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
식품소분업
1996 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1996
100.0%

Length

2024-04-18T05:46:16.878997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:16.949121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1996
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
07_22_08_P
1996 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_08_P
2nd row07_22_08_P
3rd row07_22_08_P
4th row07_22_08_P
5th row07_22_08_P

Common Values

ValueCountFrequency (%)
07_22_08_P 1996
100.0%

Length

2024-04-18T05:46:17.017897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:17.092635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 1996
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447845.7
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:17.169273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21599.411
Coefficient of variation (CV)0.0062646108
Kurtosis-1.0523717
Mean3447845.7
Median Absolute Deviation (MAD)20000
Skewness-0.35665416
Sum6.8819 × 109
Variance4.6653457 × 108
MonotonicityIncreasing
2024-04-18T05:46:17.275220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 436
21.8%
3470000 390
19.5%
3460000 290
14.5%
3420000 221
11.1%
3410000 208
10.4%
3430000 178
8.9%
3480000 156
 
7.8%
3440000 117
 
5.9%
ValueCountFrequency (%)
3410000 208
10.4%
3420000 221
11.1%
3430000 178
8.9%
3440000 117
 
5.9%
3450000 436
21.8%
3460000 290
14.5%
3470000 390
19.5%
3480000 156
 
7.8%
ValueCountFrequency (%)
3480000 156
 
7.8%
3470000 390
19.5%
3460000 290
14.5%
3450000 436
21.8%
3440000 117
 
5.9%
3430000 178
8.9%
3420000 221
11.1%
3410000 208
10.4%

관리번호
Text

UNIQUE 

Distinct1996
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-04-18T05:46:17.450046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters43912
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

Unique1996 ?
Unique (%)100.0%

Sample

1st row3410000-109-2009-00006
2nd row3410000-109-2008-00004
3rd row3410000-109-2004-00002
4th row3410000-109-2001-00029
5th row3410000-109-2009-00001
ValueCountFrequency (%)
3410000-109-2009-00006 1
 
0.1%
3460000-109-2001-00021 1
 
0.1%
3460000-109-2013-00002 1
 
0.1%
3460000-109-2013-00003 1
 
0.1%
3460000-109-2013-00005 1
 
0.1%
3460000-109-2013-00006 1
 
0.1%
3460000-109-2013-00007 1
 
0.1%
3460000-109-2014-00013 1
 
0.1%
3460000-109-2010-00006 1
 
0.1%
3460000-109-2009-00005 1
 
0.1%
Other values (1986) 1986
99.5%
2024-04-18T05:46:17.700204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20561
46.8%
- 5988
 
13.6%
1 4079
 
9.3%
2 2769
 
6.3%
3 2675
 
6.1%
4 2595
 
5.9%
9 2524
 
5.7%
5 860
 
2.0%
7 711
 
1.6%
6 681
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37924
86.4%
Dash Punctuation 5988
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20561
54.2%
1 4079
 
10.8%
2 2769
 
7.3%
3 2675
 
7.1%
4 2595
 
6.8%
9 2524
 
6.7%
5 860
 
2.3%
7 711
 
1.9%
6 681
 
1.8%
8 469
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 5988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20561
46.8%
- 5988
 
13.6%
1 4079
 
9.3%
2 2769
 
6.3%
3 2675
 
6.1%
4 2595
 
5.9%
9 2524
 
5.7%
5 860
 
2.0%
7 711
 
1.6%
6 681
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20561
46.8%
- 5988
 
13.6%
1 4079
 
9.3%
2 2769
 
6.3%
3 2675
 
6.1%
4 2595
 
5.9%
9 2524
 
5.7%
5 860
 
2.0%
7 711
 
1.6%
6 681
 
1.6%

인허가일자
Real number (ℝ)

Distinct1611
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20082413
Minimum19790523
Maximum20201127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:18.100452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790523
5-th percentile19991124
Q120031105
median20080214
Q320131125
95-th percentile20190444
Maximum20201127
Range410604
Interquartile range (IQR)100020.25

Descriptive statistics

Standard deviation64257.192
Coefficient of variation (CV)0.0031996749
Kurtosis-0.16699173
Mean20082413
Median Absolute Deviation (MAD)49905.5
Skewness-0.097794232
Sum4.0084496 × 1010
Variance4.1289867 × 109
MonotonicityNot monotonic
2024-04-18T05:46:18.212477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030219 6
 
0.3%
20091015 5
 
0.3%
20021127 5
 
0.3%
20040827 5
 
0.3%
20131126 5
 
0.3%
20010910 4
 
0.2%
20110721 4
 
0.2%
20001124 4
 
0.2%
20040621 4
 
0.2%
20040712 4
 
0.2%
Other values (1601) 1950
97.7%
ValueCountFrequency (%)
19790523 1
0.1%
19791213 1
0.1%
19810727 1
0.1%
19850905 1
0.1%
19870905 1
0.1%
19890315 1
0.1%
19890318 1
0.1%
19900707 1
0.1%
19900711 1
0.1%
19900818 1
0.1%
ValueCountFrequency (%)
20201127 2
0.1%
20201125 2
0.1%
20201106 1
0.1%
20201102 1
0.1%
20201026 1
0.1%
20201023 1
0.1%
20201020 1
0.1%
20201019 1
0.1%
20201013 1
0.1%
20200925 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
3
1482 
1
514 

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 1482
74.2%
1 514
 
25.8%

Length

2024-04-18T05:46:18.310683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:18.386245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1482
74.2%
1 514
 
25.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
폐업
1482 
영업/정상
514 

Length

Max length5
Median length2
Mean length2.7725451
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 1482
74.2%
영업/정상 514
 
25.8%

Length

2024-04-18T05:46:18.469420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:18.550240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1482
74.2%
영업/정상 514
 
25.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2
1482 
1
514 

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 1482
74.2%
1 514
 
25.8%

Length

2024-04-18T05:46:18.629909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:18.702446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1482
74.2%
1 514
 
25.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
폐업
1482 
영업
514 

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 1482
74.2%
영업 514
 
25.8%

Length

2024-04-18T05:46:18.774712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:18.844397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1482
74.2%
영업 514
 
25.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct1152
Distinct (%)77.7%
Missing514
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean20102880
Minimum20000919
Maximum20201111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:18.933418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000919
5-th percentile20030524
Q120060108
median20100205
Q320150184
95-th percentile20190807
Maximum20201111
Range200192
Interquartile range (IQR)90076.25

Descriptive statistics

Standard deviation51889.968
Coefficient of variation (CV)0.0025812206
Kurtosis-1.1502948
Mean20102880
Median Absolute Deviation (MAD)48985
Skewness0.25503452
Sum2.9792468 × 1010
Variance2.6925688 × 109
MonotonicityNot monotonic
2024-04-18T05:46:19.055218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100512 8
 
0.4%
20080213 7
 
0.4%
20021224 6
 
0.3%
20050331 5
 
0.3%
20181227 5
 
0.3%
20080212 4
 
0.2%
20141230 4
 
0.2%
20050620 4
 
0.2%
20070306 4
 
0.2%
20051117 4
 
0.2%
Other values (1142) 1431
71.7%
(Missing) 514
 
25.8%
ValueCountFrequency (%)
20000919 1
0.1%
20010108 1
0.1%
20011017 1
0.1%
20020115 1
0.1%
20020128 1
0.1%
20020131 1
0.1%
20020219 1
0.1%
20020321 1
0.1%
20020403 1
0.1%
20020408 2
0.1%
ValueCountFrequency (%)
20201111 1
0.1%
20201109 1
0.1%
20201028 1
0.1%
20201021 1
0.1%
20201014 1
0.1%
20200911 1
0.1%
20200831 1
0.1%
20200826 1
0.1%
20200819 2
0.1%
20200811 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

소재지전화
Text

MISSING 

Distinct1160
Distinct (%)91.3%
Missing725
Missing (%)36.3%
Memory size15.7 KiB
2024-04-18T05:46:19.318880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.555468
Min length2

Characters and Unicode

Total characters13416
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

Unique1082 ?
Unique (%)85.1%

Sample

1st row053 257 1636
2nd row053 4261234
3rd row053 4258941
4th row053 252 0632
5th row053 254 9562
ValueCountFrequency (%)
053 880
33.2%
070 27
 
1.0%
312 13
 
0.5%
1234 10
 
0.4%
6602001 8
 
0.3%
313 8
 
0.3%
765 7
 
0.3%
031 7
 
0.3%
986 7
 
0.3%
322 6
 
0.2%
Other values (1310) 1679
63.3%
2024-04-18T05:46:19.681542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2107
15.7%
5 2053
15.3%
3 1864
13.9%
1388
10.3%
2 1041
7.8%
6 993
7.4%
7 883
6.6%
1 877
6.5%
8 799
 
6.0%
4 763
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12028
89.7%
Space Separator 1388
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2107
17.5%
5 2053
17.1%
3 1864
15.5%
2 1041
8.7%
6 993
8.3%
7 883
7.3%
1 877
7.3%
8 799
 
6.6%
4 763
 
6.3%
9 648
 
5.4%
Space Separator
ValueCountFrequency (%)
1388
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13416
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2107
15.7%
5 2053
15.3%
3 1864
13.9%
1388
10.3%
2 1041
7.8%
6 993
7.4%
7 883
6.6%
1 877
6.5%
8 799
 
6.0%
4 763
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2107
15.7%
5 2053
15.3%
3 1864
13.9%
1388
10.3%
2 1041
7.8%
6 993
7.4%
7 883
6.6%
1 877
6.5%
8 799
 
6.0%
4 763
 
5.7%

소재지면적
Text

MISSING 

Distinct862
Distinct (%)52.1%
Missing343
Missing (%)17.2%
Memory size15.7 KiB
2024-04-18T05:46:19.995592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.707804
Min length3

Characters and Unicode

Total characters7782
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

Unique672 ?
Unique (%)40.7%

Sample

1st row24.79
2nd row39.00
3rd row5.52
4th row4.00
5th row39.57
ValueCountFrequency (%)
3.30 38
 
2.3%
4.00 36
 
2.2%
6.00 34
 
2.1%
6.60 32
 
1.9%
00 31
 
1.9%
3.00 29
 
1.8%
20.00 27
 
1.6%
12.00 26
 
1.6%
33.00 24
 
1.5%
30.00 24
 
1.5%
Other values (852) 1352
81.8%
2024-04-18T05:46:20.401088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1907
24.5%
. 1653
21.2%
1 658
 
8.5%
2 615
 
7.9%
3 552
 
7.1%
6 508
 
6.5%
4 463
 
5.9%
5 457
 
5.9%
9 336
 
4.3%
7 326
 
4.2%
Other values (2) 307
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6128
78.7%
Other Punctuation 1654
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1907
31.1%
1 658
 
10.7%
2 615
 
10.0%
3 552
 
9.0%
6 508
 
8.3%
4 463
 
7.6%
5 457
 
7.5%
9 336
 
5.5%
7 326
 
5.3%
8 306
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 1653
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 7782
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1907
24.5%
. 1653
21.2%
1 658
 
8.5%
2 615
 
7.9%
3 552
 
7.1%
6 508
 
6.5%
4 463
 
5.9%
5 457
 
5.9%
9 336
 
4.3%
7 326
 
4.2%
Other values (2) 307
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1907
24.5%
. 1653
21.2%
1 658
 
8.5%
2 615
 
7.9%
3 552
 
7.1%
6 508
 
6.5%
4 463
 
5.9%
5 457
 
5.9%
9 336
 
4.3%
7 326
 
4.2%
Other values (2) 307
 
3.9%

소재지우편번호
Real number (ℝ)

Distinct450
Distinct (%)22.7%
Missing16
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean704296.95
Minimum700040
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:20.518065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700040
5-th percentile700421
Q1702746
median703832.5
Q3705813
95-th percentile711832
Maximum711892
Range11852
Interquartile range (IQR)3067

Descriptive statistics

Standard deviation2828.5646
Coefficient of variation (CV)0.0040161535
Kurtosis1.2077599
Mean704296.95
Median Absolute Deviation (MAD)1771.5
Skewness1.0838668
Sum1.394508 × 109
Variance8000778
MonotonicityNot monotonic
2024-04-18T05:46:20.623719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 60
 
3.0%
704923 56
 
2.8%
702746 31
 
1.6%
704722 29
 
1.5%
700718 27
 
1.4%
700811 26
 
1.3%
700070 24
 
1.2%
702853 23
 
1.2%
711852 22
 
1.1%
706813 22
 
1.1%
Other values (440) 1660
83.2%
ValueCountFrequency (%)
700040 1
 
0.1%
700060 1
 
0.1%
700070 24
1.2%
700082 4
 
0.2%
700092 21
1.1%
700093 1
 
0.1%
700111 3
 
0.2%
700180 12
0.6%
700191 1
 
0.1%
700192 2
 
0.1%
ValueCountFrequency (%)
711892 3
0.2%
711891 1
 
0.1%
711874 3
0.2%
711873 1
 
0.1%
711872 1
 
0.1%
711864 3
0.2%
711863 1
 
0.1%
711861 1
 
0.1%
711858 1
 
0.1%
711855 5
0.3%

소재지전체주소
Text

Distinct1685
Distinct (%)84.6%
Missing4
Missing (%)0.2%
Memory size15.7 KiB
2024-04-18T05:46:20.846254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length26.551707
Min length17

Characters and Unicode

Total characters52891
Distinct characters290
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1531 ?
Unique (%)76.9%

Sample

1st row대구광역시 중구 대신동 0115-0030번지 동산상가1층 139,140호
2nd row대구광역시 중구 대신동 0115-0241번지 지상1층
3rd row대구광역시 중구 동성로2가 0088-0025
4th row대구광역시 중구 대봉동 0214번지 대백프라자 지하1층 식품부
5th row대구광역시 중구 남산동 2104-0003번지 1층 7,8,27,28,29,30호
ValueCountFrequency (%)
대구광역시 1992
 
20.8%
북구 436
 
4.6%
달서구 389
 
4.1%
수성구 289
 
3.0%
동구 222
 
2.3%
중구 208
 
2.2%
서구 178
 
1.9%
달성군 155
 
1.6%
남구 115
 
1.2%
지상1층 94
 
1.0%
Other values (2005) 5479
57.3%
2024-04-18T05:46:21.199901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9512
18.0%
구 3917
 
7.4%
지 2528
 
4.8%
1 2475
 
4.7%
동 2322
 
4.4%
대 2313
 
4.4%
시 2043
 
3.9%
역 1994
 
3.8%
광 1994
 
3.8%
번 1930
 
3.6%
Other values (280) 21863
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30256
57.2%
Decimal Number 10874
 
20.6%
Space Separator 9512
 
18.0%
Dash Punctuation 1523
 
2.9%
Open Punctuation 255
 
0.5%
Close Punctuation 251
 
0.5%
Other Punctuation 111
 
0.2%
Uppercase Letter 102
 
0.2%
Math Symbol 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3917
 
12.9%
지 2528
 
8.4%
동 2322
 
7.7%
대 2313
 
7.6%
시 2043
 
6.8%
역 1994
 
6.6%
광 1994
 
6.6%
번 1930
 
6.4%
성 732
 
2.4%
서 653
 
2.2%
Other values (249) 9830
32.5%
Uppercase Letter
ValueCountFrequency (%)
A 54
52.9%
B 33
32.4%
C 5
 
4.9%
S 2
 
2.0%
T 2
 
2.0%
E 1
 
1.0%
L 1
 
1.0%
P 1
 
1.0%
M 1
 
1.0%
G 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 2475
22.8%
0 1751
16.1%
2 1454
13.4%
3 1059
9.7%
5 922
 
8.5%
4 726
 
6.7%
7 672
 
6.2%
6 668
 
6.1%
8 607
 
5.6%
9 540
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 100
90.1%
. 10
 
9.0%
@ 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
9512
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1523
100.0%
Open Punctuation
ValueCountFrequency (%)
( 255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 251
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30254
57.2%
Common 22530
42.6%
Latin 105
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3917
 
12.9%
지 2528
 
8.4%
동 2322
 
7.7%
대 2313
 
7.6%
시 2043
 
6.8%
역 1994
 
6.6%
광 1994
 
6.6%
번 1930
 
6.4%
성 732
 
2.4%
서 653
 
2.2%
Other values (248) 9828
32.5%
Common
ValueCountFrequency (%)
9512
42.2%
1 2475
 
11.0%
0 1751
 
7.8%
- 1523
 
6.8%
2 1454
 
6.5%
3 1059
 
4.7%
5 922
 
4.1%
4 726
 
3.2%
7 672
 
3.0%
6 668
 
3.0%
Other values (8) 1768
 
7.8%
Latin
ValueCountFrequency (%)
A 54
51.4%
B 33
31.4%
C 5
 
4.8%
e 2
 
1.9%
S 2
 
1.9%
T 2
 
1.9%
b 1
 
1.0%
E 1
 
1.0%
L 1
 
1.0%
P 1
 
1.0%
Other values (3) 3
 
2.9%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30254
57.2%
ASCII 22635
42.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9512
42.0%
1 2475
 
10.9%
0 1751
 
7.7%
- 1523
 
6.7%
2 1454
 
6.4%
3 1059
 
4.7%
5 922
 
4.1%
4 726
 
3.2%
7 672
 
3.0%
6 668
 
3.0%
Other values (21) 1873
 
8.3%
Hangul
ValueCountFrequency (%)
구 3917
 
12.9%
지 2528
 
8.4%
동 2322
 
7.7%
대 2313
 
7.6%
시 2043
 
6.8%
역 1994
 
6.6%
광 1994
 
6.6%
번 1930
 
6.4%
성 732
 
2.4%
서 653
 
2.2%
Other values (248) 9828
32.5%
CJK
ValueCountFrequency (%)
內 2
100.0%

도로명전체주소
Text

MISSING 

Distinct1053
Distinct (%)96.8%
Missing908
Missing (%)45.5%
Memory size15.7 KiB
2024-04-18T05:46:21.508101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length29.219669
Min length19

Characters and Unicode

Total characters31791
Distinct characters303
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

Unique1024 ?
Unique (%)94.1%

Sample

1st row대구광역시 중구 큰장로26길 65 (대신동, 동산상가1층 139,140호)
2nd row대구광역시 중구 큰장로26길 32 (대신동, 지상1층)
3rd row대구광역시 중구 국채보상로 586 (동성로2가)
4th row대구광역시 중구 명덕로 333 (대봉동, 대백프라자 지하1층 식품부 )
5th row대구광역시 중구 명덕로 221 (남산동, 1층 7,8,27,28,29,30호)
ValueCountFrequency (%)
대구광역시 1088
 
17.1%
1층 304
 
4.8%
북구 232
 
3.7%
달서구 221
 
3.5%
동구 152
 
2.4%
수성구 147
 
2.3%
달성군 92
 
1.4%
서구 89
 
1.4%
남구 82
 
1.3%
중구 73
 
1.1%
Other values (1531) 3875
61.0%
2024-04-18T05:46:21.921494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5269
 
16.6%
구 2216
 
7.0%
동 1422
 
4.5%
대 1403
 
4.4%
1 1401
 
4.4%
시 1135
 
3.6%
역 1094
 
3.4%
광 1090
 
3.4%
) 1075
 
3.4%
( 1075
 
3.4%
Other values (293) 14611
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18324
57.6%
Space Separator 5269
 
16.6%
Decimal Number 4928
 
15.5%
Close Punctuation 1075
 
3.4%
Open Punctuation 1075
 
3.4%
Other Punctuation 809
 
2.5%
Dash Punctuation 208
 
0.7%
Uppercase Letter 97
 
0.3%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2216
 
12.1%
동 1422
 
7.8%
대 1403
 
7.7%
시 1135
 
6.2%
역 1094
 
6.0%
광 1090
 
5.9%
로 1048
 
5.7%
길 610
 
3.3%
층 584
 
3.2%
성 451
 
2.5%
Other values (265) 7271
39.7%
Uppercase Letter
ValueCountFrequency (%)
A 47
48.5%
B 34
35.1%
C 4
 
4.1%
T 3
 
3.1%
E 3
 
3.1%
R 1
 
1.0%
W 1
 
1.0%
O 1
 
1.0%
S 1
 
1.0%
M 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 1401
28.4%
2 732
14.9%
3 554
 
11.2%
4 400
 
8.1%
5 354
 
7.2%
0 344
 
7.0%
6 320
 
6.5%
7 304
 
6.2%
8 277
 
5.6%
9 242
 
4.9%
Space Separator
ValueCountFrequency (%)
5269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1075
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1075
100.0%
Other Punctuation
ValueCountFrequency (%)
, 809
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 208
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18324
57.6%
Common 13368
42.0%
Latin 99
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2216
 
12.1%
동 1422
 
7.8%
대 1403
 
7.7%
시 1135
 
6.2%
역 1094
 
6.0%
광 1090
 
5.9%
로 1048
 
5.7%
길 610
 
3.3%
층 584
 
3.2%
성 451
 
2.5%
Other values (265) 7271
39.7%
Common
ValueCountFrequency (%)
5269
39.4%
1 1401
 
10.5%
) 1075
 
8.0%
( 1075
 
8.0%
, 809
 
6.1%
2 732
 
5.5%
3 554
 
4.1%
4 400
 
3.0%
5 354
 
2.6%
0 344
 
2.6%
Other values (6) 1355
 
10.1%
Latin
ValueCountFrequency (%)
A 47
47.5%
B 34
34.3%
C 4
 
4.0%
T 3
 
3.0%
E 3
 
3.0%
e 2
 
2.0%
R 1
 
1.0%
W 1
 
1.0%
O 1
 
1.0%
S 1
 
1.0%
Other values (2) 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18324
57.6%
ASCII 13467
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5269
39.1%
1 1401
 
10.4%
) 1075
 
8.0%
( 1075
 
8.0%
, 809
 
6.0%
2 732
 
5.4%
3 554
 
4.1%
4 400
 
3.0%
5 354
 
2.6%
0 344
 
2.6%
Other values (18) 1454
 
10.8%
Hangul
ValueCountFrequency (%)
구 2216
 
12.1%
동 1422
 
7.8%
대 1403
 
7.7%
시 1135
 
6.2%
역 1094
 
6.0%
광 1090
 
5.9%
로 1048
 
5.7%
길 610
 
3.3%
층 584
 
3.2%
성 451
 
2.5%
Other values (265) 7271
39.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct590
Distinct (%)54.8%
Missing919
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean42029.684
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:22.033787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41088
Q141488
median41962
Q342637
95-th percentile42945
Maximum43024
Range2024
Interquartile range (IQR)1149

Descriptive statistics

Standard deviation605.03914
Coefficient of variation (CV)0.01439552
Kurtosis-1.3016633
Mean42029.684
Median Absolute Deviation (MAD)505
Skewness0.016762478
Sum45265970
Variance366072.36
MonotonicityNot monotonic
2024-04-18T05:46:22.146796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41488 27
 
1.4%
42637 24
 
1.2%
41485 20
 
1.0%
41490 15
 
0.8%
41557 12
 
0.6%
41936 8
 
0.4%
41927 7
 
0.4%
41582 7
 
0.4%
42945 7
 
0.4%
42979 6
 
0.3%
Other values (580) 944
47.3%
(Missing) 919
46.0%
ValueCountFrequency (%)
41000 3
0.2%
41001 1
 
0.1%
41002 3
0.2%
41007 1
 
0.1%
41009 3
0.2%
41020 2
0.1%
41026 4
0.2%
41028 1
 
0.1%
41035 1
 
0.1%
41036 1
 
0.1%
ValueCountFrequency (%)
43024 1
 
0.1%
43023 2
0.1%
43013 1
 
0.1%
43011 3
0.2%
43005 1
 
0.1%
43004 1
 
0.1%
43003 2
0.1%
42993 1
 
0.1%
42989 1
 
0.1%
42986 2
0.1%

사업장명
Text

Distinct1565
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-04-18T05:46:22.366609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length5.9739479
Min length2

Characters and Unicode

Total characters11924
Distinct characters565
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1357 ?
Unique (%)68.0%

Sample

1st row대성수입
2nd row성화상회
3rd row교보핫트랙스(주) 대구점
4th row다정식품
5th row한일통상
ValueCountFrequency (%)
주식회사 26
 
1.2%
대백마트 20
 
0.9%
개미농특산 14
 
0.7%
궁전방식품 11
 
0.5%
일해식품(주 9
 
0.4%
서문떡방 9
 
0.4%
조은식품 9
 
0.4%
우리농수산 8
 
0.4%
주)바다누리 8
 
0.4%
현식품 7
 
0.3%
Other values (1624) 2027
94.4%
2024-04-18T05:46:22.686484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 471
 
4.0%
) 406
 
3.4%
( 402
 
3.4%
품 392
 
3.3%
주 387
 
3.2%
마 359
 
3.0%
트 358
 
3.0%
대 217
 
1.8%
산 212
 
1.8%
이 205
 
1.7%
Other values (555) 8515
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10750
90.2%
Close Punctuation 406
 
3.4%
Open Punctuation 402
 
3.4%
Space Separator 152
 
1.3%
Uppercase Letter 108
 
0.9%
Lowercase Letter 54
 
0.5%
Decimal Number 34
 
0.3%
Other Punctuation 11
 
0.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 471
 
4.4%
품 392
 
3.6%
주 387
 
3.6%
마 359
 
3.3%
트 358
 
3.3%
대 217
 
2.0%
산 212
 
2.0%
이 205
 
1.9%
점 200
 
1.9%
스 171
 
1.6%
Other values (501) 7778
72.4%
Uppercase Letter
ValueCountFrequency (%)
O 13
12.0%
D 13
12.0%
S 13
12.0%
K 11
10.2%
F 10
9.3%
G 7
 
6.5%
C 6
 
5.6%
M 5
 
4.6%
B 5
 
4.6%
N 4
 
3.7%
Other values (11) 21
19.4%
Lowercase Letter
ValueCountFrequency (%)
o 10
18.5%
e 8
14.8%
n 5
9.3%
y 5
9.3%
d 4
 
7.4%
w 3
 
5.6%
s 3
 
5.6%
l 3
 
5.6%
t 3
 
5.6%
a 3
 
5.6%
Other values (6) 7
13.0%
Decimal Number
ValueCountFrequency (%)
1 7
20.6%
0 5
14.7%
2 5
14.7%
9 4
11.8%
4 4
11.8%
7 3
8.8%
3 3
8.8%
8 1
 
2.9%
6 1
 
2.9%
5 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
& 5
45.5%
. 5
45.5%
, 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 406
100.0%
Open Punctuation
ValueCountFrequency (%)
( 402
100.0%
Space Separator
ValueCountFrequency (%)
152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10750
90.2%
Common 1012
 
8.5%
Latin 162
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 471
 
4.4%
품 392
 
3.6%
주 387
 
3.6%
마 359
 
3.3%
트 358
 
3.3%
대 217
 
2.0%
산 212
 
2.0%
이 205
 
1.9%
점 200
 
1.9%
스 171
 
1.6%
Other values (501) 7778
72.4%
Latin
ValueCountFrequency (%)
O 13
 
8.0%
D 13
 
8.0%
S 13
 
8.0%
K 11
 
6.8%
o 10
 
6.2%
F 10
 
6.2%
e 8
 
4.9%
G 7
 
4.3%
C 6
 
3.7%
M 5
 
3.1%
Other values (27) 66
40.7%
Common
ValueCountFrequency (%)
) 406
40.1%
( 402
39.7%
152
 
15.0%
- 7
 
0.7%
1 7
 
0.7%
0 5
 
0.5%
& 5
 
0.5%
. 5
 
0.5%
2 5
 
0.5%
9 4
 
0.4%
Other values (7) 14
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10749
90.1%
ASCII 1174
 
9.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 471
 
4.4%
품 392
 
3.6%
주 387
 
3.6%
마 359
 
3.3%
트 358
 
3.3%
대 217
 
2.0%
산 212
 
2.0%
이 205
 
1.9%
점 200
 
1.9%
스 171
 
1.6%
Other values (500) 7777
72.4%
ASCII
ValueCountFrequency (%)
) 406
34.6%
( 402
34.2%
152
 
12.9%
O 13
 
1.1%
D 13
 
1.1%
S 13
 
1.1%
K 11
 
0.9%
o 10
 
0.9%
F 10
 
0.9%
e 8
 
0.7%
Other values (44) 136
 
11.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct1678
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0108624 × 1013
Minimum2.0010823 × 1013
Maximum2.020113 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:22.795777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0020725 × 1013
Q12.0050384 × 1013
median2.0110365 × 1013
Q32.017051 × 1013
95-th percentile2.0200313 × 1013
Maximum2.020113 × 1013
Range1.9030714 × 1011
Interquartile range (IQR)1.201266 × 1011

Descriptive statistics

Standard deviation6.103596 × 1010
Coefficient of variation (CV)0.0030353127
Kurtosis-1.4294287
Mean2.0108624 × 1013
Median Absolute Deviation (MAD)6.0042656 × 1010
Skewness0.042138433
Sum4.0136813 × 1016
Variance3.7253885 × 1021
MonotonicityNot monotonic
2024-04-18T05:46:22.906555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041011000000 34
 
1.7%
20020124000000 29
 
1.5%
20020725000000 13
 
0.7%
20050322000000 11
 
0.6%
20020527000000 10
 
0.5%
20021121000000 10
 
0.5%
20030612000000 10
 
0.5%
20020528000000 10
 
0.5%
20021012000000 10
 
0.5%
20010823000000 9
 
0.5%
Other values (1668) 1850
92.7%
ValueCountFrequency (%)
20010823000000 9
 
0.5%
20020124000000 29
1.5%
20020125000000 2
 
0.1%
20020207000000 1
 
0.1%
20020226000000 1
 
0.1%
20020228000000 1
 
0.1%
20020307000000 1
 
0.1%
20020320000000 1
 
0.1%
20020403000000 1
 
0.1%
20020413000000 2
 
0.1%
ValueCountFrequency (%)
20201130135156 1
0.1%
20201130132137 1
0.1%
20201127113208 1
0.1%
20201127105326 1
0.1%
20201127091930 1
0.1%
20201127090857 1
0.1%
20201126114625 1
0.1%
20201125165741 1
0.1%
20201118144135 1
0.1%
20201117180314 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
I
1696 
U
300 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1696
85.0%
U 300
 
15.0%

Length

2024-04-18T05:46:23.001907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:23.073552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1696
85.0%
u 300
 
15.0%

데이터갱신일자
Date

Distinct272
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-02 02:40:00
2024-04-18T05:46:23.152269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:46:23.255143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
식품소분업
1995 
<NA>
 
1

Length

Max length5
Median length5
Mean length4.999499
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1995
99.9%
<NA> 1
 
0.1%

Length

2024-04-18T05:46:23.355854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:23.429620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1995
99.9%
na 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1271
Distinct (%)66.5%
Missing86
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean342467.04
Minimum326848.48
Maximum358098.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:23.506742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326848.48
5-th percentile334091.65
Q1339047.79
median341944.56
Q3345663.6
95-th percentile353218.4
Maximum358098.35
Range31249.864
Interquartile range (IQR)6615.8065

Descriptive statistics

Standard deviation5304.732
Coefficient of variation (CV)0.015489759
Kurtosis0.29711243
Mean342467.04
Median Absolute Deviation (MAD)3087.6751
Skewness0.18011782
Sum6.5411206 × 108
Variance28140181
MonotonicityNot monotonic
2024-04-18T05:46:23.609883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
345032.238221 51
 
2.6%
339047.793379 46
 
2.3%
339243.983122 30
 
1.5%
338123.173581 29
 
1.5%
348194.499421 29
 
1.5%
337916.079938 25
 
1.3%
343705.561002 22
 
1.1%
345663.599839 19
 
1.0%
344066.98467 16
 
0.8%
340320.72271 16
 
0.8%
Other values (1261) 1627
81.5%
(Missing) 86
 
4.3%
ValueCountFrequency (%)
326848.481791 1
0.1%
327437.783351 1
0.1%
327489.324167 1
0.1%
327531.565421 1
0.1%
327605.063942 1
0.1%
327637.398011 1
0.1%
328311.018298 1
0.1%
328332.000154 1
0.1%
328493.333555 1
0.1%
328797.873691 1
0.1%
ValueCountFrequency (%)
358098.345472 1
 
0.1%
356370.489825 1
 
0.1%
356351.617491 1
 
0.1%
356347.076958 1
 
0.1%
356327.570046 1
 
0.1%
356325.339359 1
 
0.1%
356222.826617 1
 
0.1%
356082.08851 1
 
0.1%
355939.362329 7
0.4%
355875.122869 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1271
Distinct (%)66.5%
Missing86
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean263339.82
Minimum238813.23
Maximum277755.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:23.709506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238813.23
5-th percentile256766.25
Q1261138.27
median263506.5
Q3265598.64
95-th percentile270765.5
Maximum277755.21
Range38941.98
Interquartile range (IQR)4460.3779

Descriptive statistics

Standard deviation4535.5947
Coefficient of variation (CV)0.017223353
Kurtosis4.1674243
Mean263339.82
Median Absolute Deviation (MAD)2188.5892
Skewness-0.92044936
Sum5.0297906 × 108
Variance20571619
MonotonicityNot monotonic
2024-04-18T05:46:23.811536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262949.871621 51
 
2.6%
258741.90218 46
 
2.3%
268026.454531 30
 
1.5%
262253.34421 29
 
1.5%
259144.519321 29
 
1.5%
262111.061698 25
 
1.3%
264056.630949 22
 
1.1%
263506.50013 19
 
1.0%
264414.299416 16
 
0.8%
272735.67566 16
 
0.8%
Other values (1261) 1627
81.5%
(Missing) 86
 
4.3%
ValueCountFrequency (%)
238813.226712 1
0.1%
238824.505921 1
0.1%
238893.362765 1
0.1%
238893.829912 1
0.1%
239536.919741 1
0.1%
242349.0 1
0.1%
243088.915629 2
0.1%
244299.117529 1
0.1%
244666.651946 1
0.1%
244744.379191 1
0.1%
ValueCountFrequency (%)
277755.206408 1
0.1%
277673.246368 1
0.1%
277008.50814 1
0.1%
276811.276708 1
0.1%
275582.004218 1
0.1%
274822.293106 1
0.1%
274594.894588 1
0.1%
274508.218106 2
0.1%
274053.957157 1
0.1%
274035.207096 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
식품소분업
1994 
<NA>
 
2

Length

Max length5
Median length5
Mean length4.998998
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 1994
99.9%
<NA> 2
 
0.1%

Length

2024-04-18T05:46:23.911398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:23.984381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 1994
99.9%
na 2
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1988 
0
 
8

Length

Max length4
Median length4
Mean length3.987976
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> 1988
99.6%
0 8
 
0.4%

Length

2024-04-18T05:46:24.062591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:24.139071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1988
99.6%
0 8
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1988 
0
 
8

Length

Max length4
Median length4
Mean length3.987976
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> 1988
99.6%
0 8
 
0.4%

Length

2024-04-18T05:46:24.220795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:24.296992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1988
99.6%
0 8
 
0.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1311 
상수도전용
684 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.3431864
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1311
65.7%
상수도전용 684
34.3%
지하수전용 1
 
0.1%

Length

2024-04-18T05:46:24.376669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:24.456748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1311
65.7%
상수도전용 684
34.3%
지하수전용 1
 
0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
0
1339 
<NA>
602 
1
 
45
2
 
6
3
 
3

Length

Max length4
Median length1
Mean length1.9048096
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1339
67.1%
<NA> 602
30.2%
1 45
 
2.3%
2 6
 
0.3%
3 3
 
0.2%
6 1
 
0.1%

Length

2024-04-18T05:46:24.544900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:24.633687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1339
67.1%
na 602
30.2%
1 45
 
2.3%
2 6
 
0.3%
3 3
 
0.2%
6 1
 
0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
0
1370 
<NA>
602 
1
 
22
13
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.9053106
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1370
68.6%
<NA> 602
30.2%
1 22
 
1.1%
13 1
 
0.1%
2 1
 
0.1%

Length

2024-04-18T05:46:24.754586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:25.246028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1370
68.6%
na 602
30.2%
1 22
 
1.1%
13 1
 
0.1%
2 1
 
0.1%

공장판매직종업원수
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
0
1233 
<NA>
603 
1
140 
2
 
15
3
 
4

Length

Max length4
Median length1
Mean length1.9063126
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 1233
61.8%
<NA> 603
30.2%
1 140
 
7.0%
2 15
 
0.8%
3 4
 
0.2%
4 1
 
0.1%

Length

2024-04-18T05:46:25.334586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:25.421004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1233
61.8%
na 603
30.2%
1 140
 
7.0%
2 15
 
0.8%
3 4
 
0.2%
4 1
 
0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing601
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean0.2
Minimum0
Maximum5
Zeros1198
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:25.507836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55487923
Coefficient of variation (CV)2.7743962
Kurtosis12.712608
Mean0.2
Median Absolute Deviation (MAD)0
Skewness3.2980573
Sum279
Variance0.30789096
MonotonicityNot monotonic
2024-04-18T05:46:25.606394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1198
60.0%
1 132
 
6.6%
2 51
 
2.6%
3 12
 
0.6%
5 1
 
0.1%
4 1
 
0.1%
(Missing) 601
30.1%
ValueCountFrequency (%)
0 1198
60.0%
1 132
 
6.6%
2 51
 
2.6%
3 12
 
0.6%
4 1
 
0.1%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 1
 
0.1%
3 12
 
0.6%
2 51
 
2.6%
1 132
 
6.6%
0 1198
60.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1330 
임대
402 
자가
264 

Length

Max length4
Median length4
Mean length3.3326653
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1330
66.6%
임대 402
 
20.1%
자가 264
 
13.2%

Length

2024-04-18T05:46:25.705434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:25.793628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1330
66.6%
임대 402
 
20.1%
자가 264
 
13.2%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1967 
0
 
29

Length

Max length4
Median length4
Mean length3.9564128
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> 1967
98.5%
0 29
 
1.5%

Length

2024-04-18T05:46:25.875683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:25.951196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1967
98.5%
0 29
 
1.5%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1965 
0
 
29
1200000
 
1
1000000
 
1

Length

Max length7
Median length4
Mean length3.9594188
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1965
98.4%
0 29
 
1.5%
1200000 1
 
0.1%
1000000 1
 
0.1%

Length

2024-04-18T05:46:26.044945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:26.147626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1965
98.4%
0 29
 
1.5%
1200000 1
 
0.1%
1000000 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing1
Missing (%)0.1%
Memory size4.0 KiB
False
1995 
(Missing)
 
1
ValueCountFrequency (%)
False 1995
99.9%
(Missing) 1
 
0.1%
2024-04-18T05:46:26.223801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct65
Distinct (%)3.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.74105263
Minimum0
Maximum122.56
Zeros1922
Zeros (%)96.3%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-18T05:46:26.304403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum122.56
Range122.56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.9922488
Coefficient of variation (CV)8.0861312
Kurtosis187.46847
Mean0.74105263
Median Absolute Deviation (MAD)0
Skewness12.477547
Sum1478.4
Variance35.907045
MonotonicityNot monotonic
2024-04-18T05:46:26.415882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1922
96.3%
10.0 3
 
0.2%
3.3 3
 
0.2%
6.0 3
 
0.2%
70.0 2
 
0.1%
9.9 2
 
0.1%
3.0 2
 
0.1%
9.2 1
 
0.1%
28.0 1
 
0.1%
4.8 1
 
0.1%
Other values (55) 55
 
2.8%
ValueCountFrequency (%)
0.0 1922
96.3%
2.0 1
 
0.1%
2.02 1
 
0.1%
2.18 1
 
0.1%
2.53 1
 
0.1%
2.56 1
 
0.1%
2.7 1
 
0.1%
3.0 2
 
0.1%
3.3 3
 
0.2%
3.4 1
 
0.1%
ValueCountFrequency (%)
122.56 1
0.1%
104.92 1
0.1%
76.57 1
0.1%
72.46 1
0.1%
70.0 2
0.1%
66.0 1
0.1%
56.16 1
0.1%
53.22 1
0.1%
35.5 1
0.1%
34.7 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1996
Missing (%)100.0%
Memory size17.7 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
<NA>
1995 
53
 
1

Length

Max length4
Median length4
Mean length3.998998
Min length2

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> 1995
99.9%
53 1
 
0.1%

Length

2024-04-18T05:46:26.518104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:46:26.608536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1995
99.9%
53 1
 
0.1%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품소분업07_22_08_P34100003410000-109-2009-0000620090806<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.79700320대구광역시 중구 대신동 0115-0030번지 동산상가1층 139,140호대구광역시 중구 큰장로26길 65 (대신동, 동산상가1층 139,140호)41926대성수입20120723131146I2018-08-31 23:59:59.0식품소분업342780.445665264345.364396식품소분업<NA><NA><NA><NA><NA><NA>0020<NA><NA><NA>N0.0<NA><NA><NA>
12식품소분업07_22_08_P34100003410000-109-2008-0000420080212<NA>1영업/정상1영업<NA><NA><NA><NA>053 257 163639.00700320대구광역시 중구 대신동 0115-0241번지 지상1층대구광역시 중구 큰장로26길 32 (대신동, 지상1층)41927성화상회20150320105411I2018-08-31 23:59:59.0식품소분업342622.493267264277.582553식품소분업<NA><NA><NA><NA>상수도전용<NA>0011임대<NA><NA>N0.0<NA><NA><NA>
23식품소분업07_22_08_P34100003410000-109-2004-0000220040206<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.52700092대구광역시 중구 동성로2가 0088-0025대구광역시 중구 국채보상로 586 (동성로2가)41937교보핫트랙스(주) 대구점20200928161650U2020-09-30 02:40:00.0식품소분업343959.823762264529.39356식품소분업<NA><NA><NA><NA>상수도전용<NA>0011임대<NA><NA>N0.0<NA><NA><NA>
34식품소분업07_22_08_P34100003410000-109-2001-0002920011208<NA>1영업/정상1영업<NA><NA><NA><NA>053 42612344.00700718대구광역시 중구 대봉동 0214번지 대백프라자 지하1층 식품부대구광역시 중구 명덕로 333 (대봉동, 대백프라자 지하1층 식품부 )41953다정식품20180515104309I2018-08-31 23:59:59.0식품소분업345032.238221262949.871621식품소분업<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
45식품소분업07_22_08_P34100003410000-109-2009-0000120090130<NA>1영업/정상1영업<NA><NA><NA><NA>053 425894139.57700826대구광역시 중구 남산동 2104-0003번지 1층 7,8,27,28,29,30호대구광역시 중구 명덕로 221 (남산동, 1층 7,8,27,28,29,30호)41962한일통상20140919084757I2018-08-31 23:59:59.0식품소분업343943.116942263037.972531식품소분업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
56식품소분업07_22_08_P34100003410000-109-2008-0000320080212<NA>1영업/정상1영업<NA><NA><NA><NA>053 252 063210.00700320대구광역시 중구 대신동 0115-0045번지대구광역시 중구 큰장로26길 9, 1층 (대신동)41926경북 농산20180514165407I2018-08-31 23:59:59.0식품소분업342505.9177264299.730347식품소분업<NA><NA><NA><NA>상수도전용<NA>0011임대<NA><NA>N0.0<NA><NA><NA>
67식품소분업07_22_08_P34100003410000-109-2008-0000220080130<NA>1영업/정상1영업<NA><NA><NA><NA>053 254 95626.60700816대구광역시 중구 대신동 0265-0004번지대구광역시 중구 큰장로26안길 1, 1층 (대신동)41927부흥상회20130506153639I2018-08-31 23:59:59.0식품소분업342587.95073264267.659616식품소분업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
78식품소분업07_22_08_P34100003410000-109-2007-0000620070910<NA>1영업/정상1영업<NA><NA><NA><NA>053 426 12343.60700718대구광역시 중구 대봉동 0214번지 대백프라자 지하1층대구광역시 중구 명덕로 333 (대봉동, 대백프라자 지하1층)41953티모네20180309145055I2018-08-31 23:59:59.0식품소분업345032.238221262949.871621식품소분업<NA><NA><NA><NA><NA><NA>0010임대<NA><NA>N0.0<NA><NA><NA>
89식품소분업07_22_08_P34100003410000-109-2007-0000520070906<NA>1영업/정상1영업<NA><NA><NA><NA>053 252 56016.51700808대구광역시 중구 남산동 2971-0011번지대구광역시 중구 달구벌대로 1936, 1층 (남산동)41974롯데쇼핑(주)롯데슈퍼 남산점20170421163044I2018-08-31 23:59:59.0식품소분업342303.123488263634.294525식품소분업<NA><NA><NA><NA>상수도전용<NA>0002임대<NA><NA>N0.0<NA><NA><NA>
910식품소분업07_22_08_P34100003410000-109-2005-0002120051206<NA>1영업/정상1영업<NA><NA><NA><NA>053 32507988.25700070대구광역시 중구 덕산동 0053-0003번지 외1필지 (지하1층)대구광역시 중구 달구벌대로 2085 (덕산동, 외1필지(지하1층))41936(주)해찬20120723110925I2018-08-31 23:59:59.0식품소분업343705.561002264056.630949식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
19861987식품소분업07_22_08_P34800003480000-109-2003-0000220030701<NA>3폐업2폐업20090630<NA><NA><NA>053 60720007.36711833대구광역시 달성군 화원읍 설화리 555번지 외21필지<NA><NA>미담푸드20070720110435I2018-08-31 23:59:59.0식품소분업334363.502587256515.655111식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
19871988식품소분업07_22_08_P34800003480000-109-2003-0000120030618<NA>3폐업2폐업20111213<NA><NA><NA>053 607200022.00711833대구광역시 달성군 화원읍 설화리 555번지 외21필지<NA><NA>유가농협20071101153328I2018-08-31 23:59:59.0식품소분업334363.502587256515.655111식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
19881989식품소분업07_22_08_P34800003480000-109-2002-0000520021202<NA>3폐업2폐업20030221<NA><NA><NA>053 6395607<NA>711832대구광역시 달성군 화원읍 명곡리 166번지 외 1필지<NA><NA>(주)독도20021202000000I2018-08-31 23:59:59.0식품소분업335151.250265256572.997486식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
19891990식품소분업07_22_08_P34800003480000-109-2006-0000320060406<NA>3폐업2폐업20060608<NA><NA><NA><NA>13.05711834대구광역시 달성군 화원읍 천내리 240번지<NA><NA>해도지 수산20060406000000I2018-08-31 23:59:59.0식품소분업335177.980312257114.729223식품소분업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
19901991식품소분업07_22_08_P34800003480000-109-2002-0000320021015<NA>3폐업2폐업20130902<NA><NA><NA>053 6150266<NA>711852대구광역시 달성군 논공읍 북리 833-75번지대구광역시 달성군 논공읍 논공중앙로 12842985(주)킴스유통20070601000000I2018-08-31 23:59:59.0식품소분업330992.612575248466.723517식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
19911992식품소분업07_22_08_P34800003480000-109-2002-0000120020320<NA>3폐업2폐업20071221<NA><NA><NA>053 6119933<NA>711872대구광역시 달성군 현풍면 부리 398번지<NA><NA>무궁화산업20020320000000I2018-08-31 23:59:59.0식품소분업330643.311222245146.78569식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
19921993식품소분업07_22_08_P34800003480000-109-2001-0000520010529<NA>3폐업2폐업20061228<NA><NA><NA>053 615684013.72711873대구광역시 달성군 현풍면 중리 424-2번지<NA><NA>D 할인마트20030703000000I2018-08-31 23:59:59.0식품소분업330794.801926244299.117529식품소분업<NA><NA><NA><NA><NA><NA>0001<NA><NA><NA>N0.0<NA><NA><NA>
19931994식품소분업07_22_08_P34800003480000-109-2001-0000420010516<NA>3폐업2폐업20070611<NA><NA><NA>053 58770565.75711812대구광역시 달성군 다사읍 매곡리 719-3번지<NA><NA>007마트(한서점)20020207000000I2018-08-31 23:59:59.0식품소분업331781.789518263289.821736식품소분업<NA><NA><NA><NA><NA><NA>0001<NA><NA><NA>N0.0<NA><NA><NA>
19941995식품소분업07_22_08_P34800003480000-109-2001-0000320010313<NA>3폐업2폐업20100405<NA><NA><NA>053 61683632.88711852대구광역시 달성군 논공읍 북리 824-7번지<NA><NA>D-마트20061220000000I2018-08-31 23:59:59.0식품소분업330649.777461248630.522012식품소분업<NA><NA><NA><NA><NA><NA>0002<NA><NA><NA>N0.0<NA><NA><NA>
19951996식품소분업07_22_08_P34800003480000-109-2001-0000220010307<NA>3폐업2폐업20061228<NA><NA><NA><NA>8.14711834대구광역시 달성군 화원읍 천내리 187-2번지<NA><NA>주왕식품20010823000000I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업<NA><NA><NA><NA><NA><NA>0001<NA><NA><NA>N0.0<NA><NA><NA>