Overview

Dataset statistics

Number of variables47
Number of observations200
Missing cells2786
Missing cells (%)29.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.4 KiB
Average record size in memory406.7 B

Variable types

Numeric12
Categorical16
Text6
Unsupported12
Boolean1

Dataset

Description6270000_대구광역시_07_22_15_P_용기·포장지제조업_1월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000088168&dataSetDetailId=DDI_0000088228&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
데이터갱신일자 is highly imbalanced (72.8%)Imbalance
본사종업원수 is highly imbalanced (64.5%)Imbalance
공장판매직종업원수 is highly imbalanced (60.9%)Imbalance
보증액 is highly imbalanced (94.3%)Imbalance
월세액 is highly imbalanced (94.3%)Imbalance
인허가취소일자 has 200 (100.0%) missing valuesMissing
폐업일자 has 75 (37.5%) missing valuesMissing
휴업시작일자 has 200 (100.0%) missing valuesMissing
휴업종료일자 has 200 (100.0%) missing valuesMissing
재개업일자 has 200 (100.0%) missing valuesMissing
소재지전화 has 14 (7.0%) missing valuesMissing
소재지면적 has 32 (16.0%) missing valuesMissing
소재지우편번호 has 3 (1.5%) missing valuesMissing
도로명전체주소 has 80 (40.0%) missing valuesMissing
도로명우편번호 has 83 (41.5%) missing valuesMissing
좌표정보(X) has 15 (7.5%) missing valuesMissing
좌표정보(Y) has 15 (7.5%) missing valuesMissing
남성종사자수 has 200 (100.0%) missing valuesMissing
여성종사자수 has 200 (100.0%) missing valuesMissing
영업장주변구분명 has 200 (100.0%) missing valuesMissing
등급구분명 has 200 (100.0%) missing valuesMissing
총종업원수 has 200 (100.0%) missing valuesMissing
공장사무직종업원수 has 34 (17.0%) missing valuesMissing
공장생산직종업원수 has 34 (17.0%) missing valuesMissing
전통업소지정번호 has 200 (100.0%) missing valuesMissing
전통업소주된음식 has 200 (100.0%) missing valuesMissing
홈페이지 has 200 (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
남성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 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 149 (74.5%) zerosZeros
공장생산직종업원수 has 138 (69.0%) zerosZeros
시설총규모 has 186 (93.0%) zerosZeros

Reproduction

Analysis started2023-12-10 19:16:14.067264
Analysis finished2023-12-10 19:16:14.873443
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.5
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:14.982891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.95
Q150.75
median100.5
Q3150.25
95-th percentile190.05
Maximum200
Range199
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation57.879185
Coefficient of variation (CV)0.57591228
Kurtosis-1.2
Mean100.5
Median Absolute Deviation (MAD)50
Skewness0
Sum20100
Variance3350
MonotonicityStrictly increasing
2023-12-11T04:16:15.192858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
139 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기·포장지제조업
200 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용기·포장지제조업
2nd row용기·포장지제조업
3rd row용기·포장지제조업
4th row용기·포장지제조업
5th row용기·포장지제조업

Common Values

ValueCountFrequency (%)
용기·포장지제조업 200
100.0%

Length

2023-12-11T04:16:15.366447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:15.494331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기·포장지제조업 200
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
07_22_15_P
200 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_15_P
2nd row07_22_15_P
3rd row07_22_15_P
4th row07_22_15_P
5th row07_22_15_P

Common Values

ValueCountFrequency (%)
07_22_15_P 200
100.0%

Length

2023-12-11T04:16:15.629344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:15.755342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_15_p 200
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3466500
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:15.869940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13470000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation17298.735
Coefficient of variation (CV)0.0049902596
Kurtosis2.4926051
Mean3466500
Median Absolute Deviation (MAD)10000
Skewness-1.747483
Sum6.933 × 108
Variance2.9924623 × 108
MonotonicityIncreasing
2023-12-11T04:16:16.040158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 82
41.0%
3480000 72
36.0%
3450000 26
 
13.0%
3430000 7
 
3.5%
3420000 6
 
3.0%
3410000 5
 
2.5%
3460000 2
 
1.0%
ValueCountFrequency (%)
3410000 5
 
2.5%
3420000 6
 
3.0%
3430000 7
 
3.5%
3450000 26
 
13.0%
3460000 2
 
1.0%
3470000 82
41.0%
3480000 72
36.0%
ValueCountFrequency (%)
3480000 72
36.0%
3470000 82
41.0%
3460000 2
 
1.0%
3450000 26
 
13.0%
3430000 7
 
3.5%
3420000 6
 
3.0%
3410000 5
 
2.5%

관리번호
Text

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T04:16:16.302587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4400
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

Unique200 ?
Unique (%)100.0%

Sample

1st row3410000-118-2017-00001
2nd row3410000-118-2008-00001
3rd row3410000-118-2007-00001
4th row3410000-118-2007-00002
5th row3410000-118-2004-00001
ValueCountFrequency (%)
3410000-118-2017-00001 1
 
0.5%
3480000-118-2001-00002 1
 
0.5%
3480000-118-2005-00004 1
 
0.5%
3470000-118-2019-00001 1
 
0.5%
3480000-118-2002-00002 1
 
0.5%
3480000-118-2002-00001 1
 
0.5%
3480000-118-1988-00001 1
 
0.5%
3480000-118-2002-00003 1
 
0.5%
3480000-118-1988-00002 1
 
0.5%
3480000-118-2020-00002 1
 
0.5%
Other values (190) 190
95.0%
2023-12-11T04:16:16.762299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1903
43.2%
- 600
 
13.6%
1 595
 
13.5%
8 302
 
6.9%
3 257
 
5.8%
2 250
 
5.7%
4 234
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3800
86.4%
Dash Punctuation 600
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1903
50.1%
1 595
 
15.7%
8 302
 
7.9%
3 257
 
6.8%
2 250
 
6.6%
4 234
 
6.2%
7 108
 
2.8%
9 74
 
1.9%
5 55
 
1.4%
6 22
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1903
43.2%
- 600
 
13.6%
1 595
 
13.5%
8 302
 
6.9%
3 257
 
5.8%
2 250
 
5.7%
4 234
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1903
43.2%
- 600
 
13.6%
1 595
 
13.5%
8 302
 
6.9%
3 257
 
5.8%
2 250
 
5.7%
4 234
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

인허가일자
Real number (ℝ)

Distinct192
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20053944
Minimum19870227
Maximum20201116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:17.103758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870227
5-th percentile19949917
Q120010983
median20050216
Q320100517
95-th percentile20170816
Maximum20201116
Range330889
Interquartile range (IQR)89534.25

Descriptive statistics

Standard deviation69534.582
Coefficient of variation (CV)0.0034673768
Kurtosis0.0062225924
Mean20053944
Median Absolute Deviation (MAD)39952.5
Skewness-0.050633152
Sum4.0107889 × 109
Variance4.8350582 × 109
MonotonicityNot monotonic
2023-12-11T04:16:17.338368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021205 3
 
1.5%
20070503 3
 
1.5%
20010907 2
 
1.0%
20070807 2
 
1.0%
19870227 2
 
1.0%
20110803 2
 
1.0%
20170306 1
 
0.5%
20020130 1
 
0.5%
19880208 1
 
0.5%
20020919 1
 
0.5%
Other values (182) 182
91.0%
ValueCountFrequency (%)
19870227 2
1.0%
19880208 1
0.5%
19880805 1
0.5%
19891207 1
0.5%
19900228 1
0.5%
19900416 1
0.5%
19930907 1
0.5%
19940124 1
0.5%
19940713 1
0.5%
19950401 1
0.5%
ValueCountFrequency (%)
20201116 1
0.5%
20200924 1
0.5%
20200611 1
0.5%
20200506 1
0.5%
20200401 1
0.5%
20190412 1
0.5%
20190226 1
0.5%
20181031 1
0.5%
20180720 1
0.5%
20180514 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
125 
1
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 125
62.5%
1 75
37.5%

Length

2023-12-11T04:16:17.529214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:17.646726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 125
62.5%
1 75
37.5%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
125 
영업/정상
75 

Length

Max length5
Median length2
Mean length3.125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 125
62.5%
영업/정상 75
37.5%

Length

2023-12-11T04:16:17.811334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:17.978039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 125
62.5%
영업/정상 75
37.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
125 
1
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 125
62.5%
1 75
37.5%

Length

2023-12-11T04:16:18.135471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:18.281103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 125
62.5%
1 75
37.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
125 
영업
75 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 125
62.5%
영업 75
37.5%

Length

2023-12-11T04:16:18.416382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:18.570719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 125
62.5%
영업 75
37.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)94.4%
Missing75
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean20105295
Minimum20011030
Maximum20200519
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:18.801759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011030
5-th percentile20030689
Q120060529
median20101207
Q320151229
95-th percentile20190481
Maximum20200519
Range189489
Interquartile range (IQR)90700

Descriptive statistics

Standard deviation52324.486
Coefficient of variation (CV)0.0026025227
Kurtosis-1.1999056
Mean20105295
Median Absolute Deviation (MAD)50022
Skewness0.17434371
Sum2.5131618 × 109
Variance2.7378518 × 109
MonotonicityNot monotonic
2023-12-11T04:16:19.021423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120306 4
 
2.0%
20050831 2
 
1.0%
20110524 2
 
1.0%
20061208 2
 
1.0%
20151229 2
 
1.0%
20180130 1
 
0.5%
20130107 1
 
0.5%
20110120 1
 
0.5%
20040216 1
 
0.5%
20020721 1
 
0.5%
Other values (108) 108
54.0%
(Missing) 75
37.5%
ValueCountFrequency (%)
20011030 1
0.5%
20020109 1
0.5%
20020721 1
0.5%
20021105 1
0.5%
20021203 1
0.5%
20030317 1
0.5%
20030605 1
0.5%
20031025 1
0.5%
20040113 1
0.5%
20040203 1
0.5%
ValueCountFrequency (%)
20200519 1
0.5%
20200207 1
0.5%
20191230 1
0.5%
20191227 1
0.5%
20191204 1
0.5%
20191203 1
0.5%
20190524 1
0.5%
20190308 1
0.5%
20190124 1
0.5%
20181226 1
0.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

소재지전화
Text

MISSING 

Distinct177
Distinct (%)95.2%
Missing14
Missing (%)7.0%
Memory size1.7 KiB
2023-12-11T04:16:19.438504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.037634
Min length7

Characters and Unicode

Total characters2053
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

Unique169 ?
Unique (%)90.9%

Sample

1st row053 256 3375
2nd row053 2525022
3rd row053 5857788
4th row053 5548531
5th row053 9640371
ValueCountFrequency (%)
053 139
36.6%
581 5
 
1.3%
583 3
 
0.8%
593 3
 
0.8%
5857788 3
 
0.8%
585 3
 
0.8%
615 3
 
0.8%
05305855400 2
 
0.5%
6168800 2
 
0.5%
611 2
 
0.5%
Other values (204) 215
56.6%
2023-12-11T04:16:20.069734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 381
18.6%
0 325
15.8%
3 304
14.8%
195
9.5%
8 169
8.2%
1 166
8.1%
6 149
 
7.3%
4 105
 
5.1%
2 99
 
4.8%
9 81
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1858
90.5%
Space Separator 195
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 381
20.5%
0 325
17.5%
3 304
16.4%
8 169
9.1%
1 166
8.9%
6 149
 
8.0%
4 105
 
5.7%
2 99
 
5.3%
9 81
 
4.4%
7 79
 
4.3%
Space Separator
ValueCountFrequency (%)
195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2053
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 381
18.6%
0 325
15.8%
3 304
14.8%
195
9.5%
8 169
8.2%
1 166
8.1%
6 149
 
7.3%
4 105
 
5.1%
2 99
 
4.8%
9 81
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 381
18.6%
0 325
15.8%
3 304
14.8%
195
9.5%
8 169
8.2%
1 166
8.1%
6 149
 
7.3%
4 105
 
5.1%
2 99
 
4.8%
9 81
 
3.9%

소재지면적
Text

MISSING 

Distinct158
Distinct (%)94.0%
Missing32
Missing (%)16.0%
Memory size1.7 KiB
2023-12-11T04:16:20.630452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1845238
Min length3

Characters and Unicode

Total characters1039
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

Unique151 ?
Unique (%)89.9%

Sample

1st row16.54
2nd row195.50
3rd row52.80
4th row130.20
5th row821.40
ValueCountFrequency (%)
00 5
 
3.0%
337.50 2
 
1.2%
334.80 2
 
1.2%
264.00 2
 
1.2%
270.00 2
 
1.2%
132.00 2
 
1.2%
475.97 2
 
1.2%
16.54 1
 
0.6%
1.00 1
 
0.6%
16,233.43 1
 
0.6%
Other values (148) 148
88.1%
2023-12-11T04:16:21.394884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 218
21.0%
. 168
16.2%
2 90
8.7%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 838
80.7%
Other Punctuation 201
 
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218
26.0%
2 90
10.7%
1 78
 
9.3%
4 76
 
9.1%
3 75
 
8.9%
6 72
 
8.6%
7 62
 
7.4%
5 60
 
7.2%
8 54
 
6.4%
9 53
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 168
83.6%
, 33
 
16.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1039
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 218
21.0%
. 168
16.2%
2 90
8.7%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 218
21.0%
. 168
16.2%
2 90
8.7%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)38.1%
Missing3
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean706740.4
Minimum700191
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:21.947831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700191
5-th percentile701866
Q1704190
median704833
Q3711841
95-th percentile711861.2
Maximum711893
Range11702
Interquartile range (IQR)7651

Descriptive statistics

Standard deviation3888.3972
Coefficient of variation (CV)0.0055018748
Kurtosis-1.5031354
Mean706740.4
Median Absolute Deviation (MAD)2016
Skewness0.41027029
Sum1.3922786 × 108
Variance15119633
MonotonicityNot monotonic
2023-12-11T04:16:22.191742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704801 17
 
8.5%
704833 16
 
8.0%
704190 8
 
4.0%
711855 8
 
4.0%
702800 8
 
4.0%
704900 8
 
4.0%
711841 6
 
3.0%
711842 6
 
3.0%
704901 5
 
2.5%
704830 5
 
2.5%
Other values (65) 110
55.0%
ValueCountFrequency (%)
700191 1
0.5%
700290 1
0.5%
700804 1
0.5%
700832 1
0.5%
700841 1
0.5%
701260 1
0.5%
701330 1
0.5%
701807 1
0.5%
701848 1
0.5%
701850 1
0.5%
ValueCountFrequency (%)
711893 1
 
0.5%
711892 2
 
1.0%
711891 5
2.5%
711890 1
 
0.5%
711874 1
 
0.5%
711858 4
2.0%
711856 3
 
1.5%
711855 8
4.0%
711852 5
2.5%
711851 3
 
1.5%

소재지전체주소
Text

Distinct195
Distinct (%)98.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2023-12-11T04:16:22.672956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length25.080402
Min length19

Characters and Unicode

Total characters4991
Distinct characters127
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)96.0%

Sample

1st row대구광역시 중구 종로1가 0040-0002번지 지상8층
2nd row대구광역시 중구 시장북로 0026-0001번지 지상 1층
3rd row대구광역시 중구 남산동 2114-0010번지
4th row대구광역시 중구 남산동 0615-0002번지 지상3층
5th row대구광역시 중구 달성동 0209-0015번지
ValueCountFrequency (%)
대구광역시 199
21.2%
달서구 82
 
8.7%
달성군 71
 
7.6%
북구 26
 
2.8%
논공읍 23
 
2.4%
옥포면 21
 
2.2%
월암동 18
 
1.9%
대천동 17
 
1.8%
지상1층 15
 
1.6%
본리리 14
 
1.5%
Other values (298) 454
48.3%
2023-12-11T04:16:23.475628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
947
19.0%
구 337
 
6.8%
지 239
 
4.8%
1 227
 
4.5%
대 216
 
4.3%
시 202
 
4.0%
광 199
 
4.0%
역 199
 
4.0%
번 195
 
3.9%
달 155
 
3.1%
Other values (117) 2075
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2914
58.4%
Space Separator 947
 
19.0%
Decimal Number 914
 
18.3%
Dash Punctuation 145
 
2.9%
Open Punctuation 25
 
0.5%
Close Punctuation 25
 
0.5%
Uppercase Letter 15
 
0.3%
Other Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 337
 
11.6%
지 239
 
8.2%
대 216
 
7.4%
시 202
 
6.9%
광 199
 
6.8%
역 199
 
6.8%
번 195
 
6.7%
달 155
 
5.3%
동 154
 
5.3%
서 94
 
3.2%
Other values (96) 924
31.7%
Decimal Number
ValueCountFrequency (%)
1 227
24.8%
2 109
11.9%
0 103
11.3%
3 92
10.1%
6 76
 
8.3%
4 75
 
8.2%
5 64
 
7.0%
7 62
 
6.8%
8 53
 
5.8%
9 53
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 7
46.7%
B 5
33.3%
C 1
 
6.7%
L 1
 
6.7%
D 1
 
6.7%
Space Separator
ValueCountFrequency (%)
947
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2914
58.4%
Common 2062
41.3%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 337
 
11.6%
지 239
 
8.2%
대 216
 
7.4%
시 202
 
6.9%
광 199
 
6.8%
역 199
 
6.8%
번 195
 
6.7%
달 155
 
5.3%
동 154
 
5.3%
서 94
 
3.2%
Other values (96) 924
31.7%
Common
ValueCountFrequency (%)
947
45.9%
1 227
 
11.0%
- 145
 
7.0%
2 109
 
5.3%
0 103
 
5.0%
3 92
 
4.5%
6 76
 
3.7%
4 75
 
3.6%
5 64
 
3.1%
7 62
 
3.0%
Other values (6) 162
 
7.9%
Latin
ValueCountFrequency (%)
A 7
46.7%
B 5
33.3%
C 1
 
6.7%
L 1
 
6.7%
D 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2914
58.4%
ASCII 2077
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
947
45.6%
1 227
 
10.9%
- 145
 
7.0%
2 109
 
5.2%
0 103
 
5.0%
3 92
 
4.4%
6 76
 
3.7%
4 75
 
3.6%
5 64
 
3.1%
7 62
 
3.0%
Other values (11) 177
 
8.5%
Hangul
ValueCountFrequency (%)
구 337
 
11.6%
지 239
 
8.2%
대 216
 
7.4%
시 202
 
6.9%
광 199
 
6.8%
역 199
 
6.8%
번 195
 
6.7%
달 155
 
5.3%
동 154
 
5.3%
서 94
 
3.2%
Other values (96) 924
31.7%

도로명전체주소
Text

MISSING 

Distinct120
Distinct (%)100.0%
Missing80
Missing (%)40.0%
Memory size1.7 KiB
2023-12-11T04:16:24.060978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length28.008333
Min length20

Characters and Unicode

Total characters3361
Distinct characters142
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 국채보상로 554-1 (종로1가, 지상8층)
2nd row대구광역시 중구 중앙대로65길 28, 3층 (남산동)
3rd row대구광역시 동구 팔공로 96-8 (지저동)
4th row대구광역시 동구 금강로 186, A동,B동,C동 1층 (금강동)
5th row대구광역시 서구 평리로33길 20, 1층 (중리동)
ValueCountFrequency (%)
대구광역시 120
 
17.9%
달서구 51
 
7.6%
달성군 50
 
7.5%
1층 29
 
4.3%
논공읍 19
 
2.8%
옥포면 13
 
1.9%
북구 12
 
1.8%
월암동 11
 
1.6%
대천동 9
 
1.3%
구지면 8
 
1.2%
Other values (246) 347
51.9%
2023-12-11T04:16:24.821777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
549
 
16.3%
구 200
 
6.0%
대 143
 
4.3%
1 136
 
4.0%
시 124
 
3.7%
역 120
 
3.6%
광 120
 
3.6%
달 113
 
3.4%
서 105
 
3.1%
로 104
 
3.1%
Other values (132) 1647
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2016
60.0%
Space Separator 549
 
16.3%
Decimal Number 508
 
15.1%
Open Punctuation 87
 
2.6%
Close Punctuation 87
 
2.6%
Other Punctuation 63
 
1.9%
Dash Punctuation 29
 
0.9%
Uppercase Letter 17
 
0.5%
Math Symbol 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 200
 
9.9%
대 143
 
7.1%
시 124
 
6.2%
역 120
 
6.0%
광 120
 
6.0%
달 113
 
5.6%
서 105
 
5.2%
로 104
 
5.2%
동 104
 
5.2%
성 97
 
4.8%
Other values (110) 786
39.0%
Decimal Number
ValueCountFrequency (%)
1 136
26.8%
2 72
14.2%
3 59
11.6%
5 50
 
9.8%
6 42
 
8.3%
7 35
 
6.9%
4 32
 
6.3%
8 32
 
6.3%
9 26
 
5.1%
0 24
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
D 2
 
11.8%
B 2
 
11.8%
E 1
 
5.9%
L 1
 
5.9%
Space Separator
ValueCountFrequency (%)
549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Other Punctuation
ValueCountFrequency (%)
, 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2016
60.0%
Common 1328
39.5%
Latin 17
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 200
 
9.9%
대 143
 
7.1%
시 124
 
6.2%
역 120
 
6.0%
광 120
 
6.0%
달 113
 
5.6%
서 105
 
5.2%
로 104
 
5.2%
동 104
 
5.2%
성 97
 
4.8%
Other values (110) 786
39.0%
Common
ValueCountFrequency (%)
549
41.3%
1 136
 
10.2%
( 87
 
6.6%
) 87
 
6.6%
2 72
 
5.4%
, 63
 
4.7%
3 59
 
4.4%
5 50
 
3.8%
6 42
 
3.2%
7 35
 
2.6%
Other values (6) 148
 
11.1%
Latin
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
D 2
 
11.8%
B 2
 
11.8%
E 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2016
60.0%
ASCII 1345
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
549
40.8%
1 136
 
10.1%
( 87
 
6.5%
) 87
 
6.5%
2 72
 
5.4%
, 63
 
4.7%
3 59
 
4.4%
5 50
 
3.7%
6 42
 
3.1%
7 35
 
2.6%
Other values (12) 165
 
12.3%
Hangul
ValueCountFrequency (%)
구 200
 
9.9%
대 143
 
7.1%
시 124
 
6.2%
역 120
 
6.0%
광 120
 
6.0%
달 113
 
5.6%
서 105
 
5.2%
로 104
 
5.2%
동 104
 
5.2%
성 97
 
4.8%
Other values (110) 786
39.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)52.1%
Missing83
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean42646.026
Minimum41037
Maximum43013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:25.168207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41037
5-th percentile41507
Q142703
median42721
Q342972
95-th percentile43008
Maximum43013
Range1976
Interquartile range (IQR)269

Descriptive statistics

Standard deviation491.83081
Coefficient of variation (CV)0.011532864
Kurtosis2.1569673
Mean42646.026
Median Absolute Deviation (MAD)247
Skewness-1.8348898
Sum4989585
Variance241897.54
MonotonicityNot monotonic
2023-12-11T04:16:25.434650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42719 7
 
3.5%
42718 7
 
3.5%
42721 6
 
3.0%
42968 5
 
2.5%
43013 4
 
2.0%
42970 4
 
2.0%
42976 4
 
2.0%
42972 4
 
2.0%
42982 4
 
2.0%
42701 3
 
1.5%
Other values (51) 69
34.5%
(Missing) 83
41.5%
ValueCountFrequency (%)
41037 1
0.5%
41095 1
0.5%
41433 1
0.5%
41495 1
0.5%
41499 1
0.5%
41503 1
0.5%
41508 1
0.5%
41509 2
1.0%
41510 1
0.5%
41512 1
0.5%
ValueCountFrequency (%)
43013 4
2.0%
43011 1
 
0.5%
43008 3
1.5%
42993 1
 
0.5%
42985 1
 
0.5%
42983 3
1.5%
42982 4
2.0%
42981 2
1.0%
42977 3
1.5%
42976 4
2.0%

사업장명
Text

Distinct185
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T04:16:25.847018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.835
Min length2

Characters and Unicode

Total characters1167
Distinct characters195
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)86.0%

Sample

1st row카유아티산
2nd row오성상사
3rd row대양정밀인쇄
4th row동아피엔비
5th row명성인쇄사
ValueCountFrequency (%)
대호화학산업 3
 
1.4%
동아피엔비 3
 
1.4%
대붕그라비아 2
 
1.0%
대우포장 2
 
1.0%
동화기업사 2
 
1.0%
한일산업사 2
 
1.0%
주)동신에스피 2
 
1.0%
주식회사 2
 
1.0%
신오산업 2
 
1.0%
대성비닐공업사 2
 
1.0%
Other values (182) 186
89.4%
2023-12-11T04:16:26.540500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 66
 
5.7%
산 63
 
5.4%
주 50
 
4.3%
( 49
 
4.2%
) 49
 
4.2%
대 38
 
3.3%
사 37
 
3.2%
성 30
 
2.6%
스 27
 
2.3%
동 26
 
2.2%
Other values (185) 732
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1050
90.0%
Open Punctuation 49
 
4.2%
Close Punctuation 49
 
4.2%
Uppercase Letter 9
 
0.8%
Space Separator 8
 
0.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 66
 
6.3%
산 63
 
6.0%
주 50
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.9%
스 27
 
2.6%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 666
63.4%
Uppercase Letter
ValueCountFrequency (%)
S 4
44.4%
C 1
 
11.1%
E 1
 
11.1%
J 1
 
11.1%
D 1
 
11.1%
H 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1050
90.0%
Common 108
 
9.3%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 66
 
6.3%
산 63
 
6.0%
주 50
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.9%
스 27
 
2.6%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 666
63.4%
Latin
ValueCountFrequency (%)
S 4
44.4%
C 1
 
11.1%
E 1
 
11.1%
J 1
 
11.1%
D 1
 
11.1%
H 1
 
11.1%
Common
ValueCountFrequency (%)
( 49
45.4%
) 49
45.4%
8
 
7.4%
& 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1050
90.0%
ASCII 117
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 66
 
6.3%
산 63
 
6.0%
주 50
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.9%
스 27
 
2.6%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 666
63.4%
ASCII
ValueCountFrequency (%)
( 49
41.9%
) 49
41.9%
8
 
6.8%
S 4
 
3.4%
& 2
 
1.7%
C 1
 
0.9%
E 1
 
0.9%
J 1
 
0.9%
D 1
 
0.9%
H 1
 
0.9%

최종수정시점
Real number (ℝ)

Distinct172
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0106461 × 1013
Minimum2.0010822 × 1013
Maximum2.0201215 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:26.791170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010822 × 1013
5-th percentile2.001966 × 1013
Q12.0040626 × 1013
median2.0110414 × 1013
Q32.0160246 × 1013
95-th percentile2.0200221 × 1013
Maximum2.0201215 × 1013
Range1.9039315 × 1011
Interquartile range (IQR)1.196194 × 1011

Descriptive statistics

Standard deviation6.5725812 × 1010
Coefficient of variation (CV)0.0032688902
Kurtosis-1.5425008
Mean2.0106461 × 1013
Median Absolute Deviation (MAD)6.0303557 × 1010
Skewness-0.084174926
Sum4.0212921 × 1015
Variance4.3198823 × 1021
MonotonicityNot monotonic
2023-12-11T04:16:27.110402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020523000000 16
 
8.0%
20010822000000 8
 
4.0%
20020903000000 2
 
1.0%
20020115000000 2
 
1.0%
20011015000000 2
 
1.0%
20041018000000 2
 
1.0%
20041019000000 2
 
1.0%
20020124000000 2
 
1.0%
20171219152418 1
 
0.5%
20200102102616 1
 
0.5%
Other values (162) 162
81.0%
ValueCountFrequency (%)
20010822000000 8
4.0%
20011015000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20020214000000 1
 
0.5%
20020420000000 1
 
0.5%
20020523000000 16
8.0%
20020615000000 1
 
0.5%
20020903000000 2
 
1.0%
20021016000000 1
 
0.5%
ValueCountFrequency (%)
20201215145501 1
0.5%
20201127153200 1
0.5%
20201116160203 1
0.5%
20200924120545 1
0.5%
20200619152212 1
0.5%
20200519100535 1
0.5%
20200506155606 1
0.5%
20200413164529 1
0.5%
20200311144708 1
0.5%
20200226171124 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
176 
U
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 176
88.0%
U 24
 
12.0%

Length

2023-12-11T04:16:27.505985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:27.764127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 176
88.0%
u 24
 
12.0%

데이터갱신일자
Categorical

IMBALANCE 

Distinct31
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2018-08-31 23:59:59.0
170 
2020-09-26 00:23:11.0
 
1
2019-01-08 02:40:00.0
 
1
2018-12-28 02:40:00.0
 
1
2018-12-13 02:40:00.0
 
1
Other values (26)
26 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique30 ?
Unique (%)15.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 170
85.0%
2020-09-26 00:23:11.0 1
 
0.5%
2019-01-08 02:40:00.0 1
 
0.5%
2018-12-28 02:40:00.0 1
 
0.5%
2018-12-13 02:40:00.0 1
 
0.5%
2019-01-26 02:40:00.0 1
 
0.5%
2018-12-01 02:40:00.0 1
 
0.5%
2019-12-06 02:40:00.0 1
 
0.5%
2020-05-21 02:40:00.0 1
 
0.5%
2018-11-15 02:36:02.0 1
 
0.5%
Other values (21) 21
 
10.5%

Length

2023-12-11T04:16:27.957679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 170
42.5%
23:59:59.0 170
42.5%
02:40:00.0 23
 
5.8%
00:23:08.0 2
 
0.5%
2020-01-22 1
 
0.2%
2019-05-26 1
 
0.2%
00:23:40.0 1
 
0.2%
2020-04-15 1
 
0.2%
2019-02-28 1
 
0.2%
02:21:34.0 1
 
0.2%
Other values (29) 29
 
7.2%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
200 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용기.포장지제조업
2nd row용기.포장지제조업
3rd row용기.포장지제조업
4th row용기.포장지제조업
5th row용기.포장지제조업

Common Values

ValueCountFrequency (%)
용기.포장지제조업 200
100.0%

Length

2023-12-11T04:16:28.186807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:28.346756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 200
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct177
Distinct (%)95.7%
Missing15
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean336011.03
Minimum325886.5
Maximum356719.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:28.527382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325886.5
5-th percentile328221.11
Q1332714.67
median335513.79
Q3337237.14
95-th percentile346401.99
Maximum356719.23
Range30832.738
Interquartile range (IQR)4522.4756

Descriptive statistics

Standard deviation5667.7408
Coefficient of variation (CV)0.016867723
Kurtosis2.0217257
Mean336011.03
Median Absolute Deviation (MAD)2676.1213
Skewness1.1584793
Sum62162040
Variance32123286
MonotonicityNot monotonic
2023-12-11T04:16:28.759875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336397.922682 3
 
1.5%
345971.954573 2
 
1.0%
331839.79406 2
 
1.0%
331841.584525 2
 
1.0%
335156.423755 2
 
1.0%
328209.453202 2
 
1.0%
333135.698427 2
 
1.0%
331206.199479 1
 
0.5%
332714.667572 1
 
0.5%
328908.419991 1
 
0.5%
Other values (167) 167
83.5%
(Missing) 15
 
7.5%
ValueCountFrequency (%)
325886.496212 1
0.5%
326023.452178 1
0.5%
327262.266542 1
0.5%
327419.359621 1
0.5%
327642.468368 1
0.5%
327654.764936 1
0.5%
327960.00471 1
0.5%
328209.453202 2
1.0%
328213.561416 1
0.5%
328251.2996 1
0.5%
ValueCountFrequency (%)
356719.234223 1
0.5%
355704.044616 1
0.5%
354790.108191 1
0.5%
353966.914738 1
0.5%
352544.091201 1
0.5%
350089.181179 1
0.5%
348103.326642 1
0.5%
347291.028197 1
0.5%
346477.440716 1
0.5%
346458.200769 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct177
Distinct (%)95.7%
Missing15
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean258780.8
Minimum237999.44
Maximum272526.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:29.000786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237999.44
5-th percentile242955.6
Q1255625.67
median260162.24
Q3262850.25
95-th percentile268638.1
Maximum272526.51
Range34527.074
Interquartile range (IQR)7224.5873

Descriptive statistics

Standard deviation7015.2155
Coefficient of variation (CV)0.027108717
Kurtosis1.2061572
Mean258780.8
Median Absolute Deviation (MAD)3627.9707
Skewness-1.027889
Sum47874448
Variance49213249
MonotonicityNot monotonic
2023-12-11T04:16:29.241467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
260400.384173 3
 
1.5%
269410.738999 2
 
1.0%
249314.473196 2
 
1.0%
255452.921933 2
 
1.0%
259818.122046 2
 
1.0%
251079.280489 2
 
1.0%
255625.666969 2
 
1.0%
249493.752629 1
 
0.5%
250011.626107 1
 
0.5%
252864.877295 1
 
0.5%
Other values (167) 167
83.5%
(Missing) 15
 
7.5%
ValueCountFrequency (%)
237999.437164 1
0.5%
238106.714053 1
0.5%
238349.842802 1
0.5%
239004.505882 1
0.5%
239341.509277 1
0.5%
239494.339675 1
0.5%
239584.975982 1
0.5%
239622.025833 1
0.5%
240780.386054 1
0.5%
242524.285797 1
0.5%
ValueCountFrequency (%)
272526.511063 1
0.5%
269502.747796 1
0.5%
269411.257496 1
0.5%
269410.738999 2
1.0%
269382.179664 1
0.5%
269187.036736 1
0.5%
269153.36154 1
0.5%
269078.525441 1
0.5%
268743.555815 1
0.5%
268216.27041 1
0.5%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
200 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용기.포장지제조업
2nd row용기.포장지제조업
3rd row용기.포장지제조업
4th row용기.포장지제조업
5th row용기.포장지제조업

Common Values

ValueCountFrequency (%)
용기.포장지제조업 200
100.0%

Length

2023-12-11T04:16:29.490143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:29.671745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 200
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
127 
상수도전용
72 
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.365
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 127
63.5%
상수도전용 72
36.0%
간이상수도 1
 
0.5%

Length

2023-12-11T04:16:29.872302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:30.078231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
63.5%
상수도전용 72
36.0%
간이상수도 1
 
0.5%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
162 
<NA>
34 
1
 
2
4
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.51
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 162
81.0%
<NA> 34
 
17.0%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

Length

2023-12-11T04:16:30.284343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:30.567807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 162
81.0%
na 34
 
17.0%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.6%
Missing34
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean0.27108434
Minimum0
Maximum15
Zeros149
Zeros (%)74.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:30.737560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4497674
Coefficient of variation (CV)5.3480308
Kurtosis76.824598
Mean0.27108434
Median Absolute Deviation (MAD)0
Skewness8.3822412
Sum45
Variance2.1018255
MonotonicityNot monotonic
2023-12-11T04:16:31.028003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 149
74.5%
1 12
 
6.0%
3 2
 
1.0%
10 1
 
0.5%
2 1
 
0.5%
15 1
 
0.5%
(Missing) 34
 
17.0%
ValueCountFrequency (%)
0 149
74.5%
1 12
 
6.0%
2 1
 
0.5%
3 2
 
1.0%
10 1
 
0.5%
15 1
 
0.5%
ValueCountFrequency (%)
15 1
 
0.5%
10 1
 
0.5%
3 2
 
1.0%
2 1
 
0.5%
1 12
 
6.0%
0 149
74.5%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
159 
<NA>
34 
1
 
5
2
 
1
6
 
1

Length

Max length4
Median length1
Mean length1.51
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row0
2nd row<NA>
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 159
79.5%
<NA> 34
 
17.0%
1 5
 
2.5%
2 1
 
0.5%
6 1
 
0.5%

Length

2023-12-11T04:16:31.288560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:31.491445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 159
79.5%
na 34
 
17.0%
1 5
 
2.5%
2 1
 
0.5%
6 1
 
0.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.6%
Missing34
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean1.2228916
Minimum0
Maximum45
Zeros138
Zeros (%)69.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:31.679203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.2192842
Coefficient of variation (CV)4.2679861
Kurtosis59.377111
Mean1.2228916
Median Absolute Deviation (MAD)0
Skewness7.3679715
Sum203
Variance27.240927
MonotonicityNot monotonic
2023-12-11T04:16:31.845260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 138
69.0%
2 7
 
3.5%
4 5
 
2.5%
3 3
 
1.5%
5 3
 
1.5%
1 2
 
1.0%
9 2
 
1.0%
7 2
 
1.0%
45 2
 
1.0%
11 1
 
0.5%
(Missing) 34
 
17.0%
ValueCountFrequency (%)
0 138
69.0%
1 2
 
1.0%
2 7
 
3.5%
3 3
 
1.5%
4 5
 
2.5%
5 3
 
1.5%
7 2
 
1.0%
9 2
 
1.0%
10 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
45 2
 
1.0%
11 1
 
0.5%
10 1
 
0.5%
9 2
 
1.0%
7 2
 
1.0%
5 3
1.5%
4 5
2.5%
3 3
1.5%
2 7
3.5%
1 2
 
1.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
148 
자가
27 
임대
25 

Length

Max length4
Median length4
Mean length3.48
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 148
74.0%
자가 27
 
13.5%
임대 25
 
12.5%

Length

2023-12-11T04:16:32.074862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:32.292628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
74.0%
자가 27
 
13.5%
임대 25
 
12.5%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
30000000
 
1
0
 
1

Length

Max length8
Median length4
Mean length4.005
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
99.0%
30000000 1
 
0.5%
0 1
 
0.5%

Length

2023-12-11T04:16:32.487608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:32.656362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
99.0%
30000000 1
 
0.5%
0 1
 
0.5%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
1200000
 
1
0
 
1

Length

Max length7
Median length4
Mean length4
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

Length

2023-12-11T04:16:32.815478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:16:32.979315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size332.0 B
False
200 
ValueCountFrequency (%)
False 200
100.0%
2023-12-11T04:16:33.129804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1713
Minimum0
Maximum907.75
Zeros186
Zeros (%)93.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T04:16:33.279221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10.13
Maximum907.75
Range907.75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64.544775
Coefficient of variation (CV)10.458862
Kurtosis194.11662
Mean6.1713
Median Absolute Deviation (MAD)0
Skewness13.840304
Sum1234.26
Variance4166.028
MonotonicityNot monotonic
2023-12-11T04:16:33.455286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 186
93.0%
64.0 1
 
0.5%
10.0 1
 
0.5%
9.9 1
 
0.5%
3.35 1
 
0.5%
45.0 1
 
0.5%
41.0 1
 
0.5%
3.0 1
 
0.5%
19.5 1
 
0.5%
19.6 1
 
0.5%
Other values (5) 5
 
2.5%
ValueCountFrequency (%)
0.0 186
93.0%
3.0 1
 
0.5%
3.35 1
 
0.5%
9.9 1
 
0.5%
10.0 1
 
0.5%
12.6 1
 
0.5%
16.51 1
 
0.5%
19.5 1
 
0.5%
19.6 1
 
0.5%
35.35 1
 
0.5%
ValueCountFrequency (%)
907.75 1
0.5%
64.0 1
0.5%
46.7 1
0.5%
45.0 1
0.5%
41.0 1
0.5%
35.35 1
0.5%
19.6 1
0.5%
19.5 1
0.5%
16.51 1
0.5%
12.6 1
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01용기·포장지제조업07_22_15_P34100003410000-118-2017-0000120170306<NA>3폐업2폐업20171219<NA><NA><NA><NA>16.54700191대구광역시 중구 종로1가 0040-0002번지 지상8층대구광역시 중구 국채보상로 554-1 (종로1가, 지상8층)41935카유아티산20171219152418I2018-08-31 23:59:59.0용기.포장지제조업343655.153991264524.42689용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
12용기·포장지제조업07_22_15_P34100003410000-118-2008-0000120081022<NA>3폐업2폐업20101207<NA><NA><NA>053 256 3375<NA>700290대구광역시 중구 시장북로 0026-0001번지 지상 1층<NA><NA>오성상사20081022110517I2018-08-31 23:59:59.0용기.포장지제조업342897.130045264638.387292용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
23용기·포장지제조업07_22_15_P34100003410000-118-2007-0000120071126<NA>3폐업2폐업20090306<NA><NA><NA>053 2525022195.50700804대구광역시 중구 남산동 2114-0010번지<NA><NA>대양정밀인쇄20071130111756I2018-08-31 23:59:59.0용기.포장지제조업343403.777962263258.821601용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0011임대<NA><NA>N0.0<NA><NA><NA>
34용기·포장지제조업07_22_15_P34100003410000-118-2007-0000220070503<NA>3폐업2폐업20160112<NA><NA><NA>053 585778852.80700832대구광역시 중구 남산동 0615-0002번지 지상3층대구광역시 중구 중앙대로65길 28, 3층 (남산동)41967동아피엔비20140120165840I2018-08-31 23:59:59.0용기.포장지제조업343661.921792263633.443803용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45용기·포장지제조업07_22_15_P34100003410000-118-2004-0000120040922<NA>3폐업2폐업20060619<NA><NA><NA>053 5548531130.20700841대구광역시 중구 달성동 0209-0015번지<NA><NA>명성인쇄사20040922000000I2018-08-31 23:59:59.0용기.포장지제조업342602.22917265112.336673용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0002<NA><NA><NA>N0.0<NA><NA><NA>
56용기·포장지제조업07_22_15_P34200003420000-118-2001-0000120010809<NA>3폐업2폐업20021105<NA><NA><NA>053 9640371821.40701848대구광역시 동구 동호동 98-10번지<NA><NA>세진산업포장20020903000000I2018-08-31 23:59:59.0용기.포장지제조업354790.108191264731.243907용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
67용기·포장지제조업07_22_15_P34200003420000-118-1996-0000119960304<NA>3폐업2폐업20040402<NA><NA><NA>053 9554029450.59701870대구광역시 동구 신서동 626-6번지<NA><NA>유진화성20020903000000I2018-08-31 23:59:59.0용기.포장지제조업355704.044616264594.008033용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
78용기·포장지제조업07_22_15_P34200003420000-118-2009-0000120091112<NA>3폐업2폐업20171226<NA><NA><NA>053 981 4735525.68701850대구광역시 동구 지저동 203-6번지대구광역시 동구 팔공로 96-8 (지저동)41037현대아이존20171226101318I2018-08-31 23:59:59.0용기.포장지제조업348103.326642268743.555815용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0003자가<NA><NA>N64.0<NA><NA><NA>
89용기·포장지제조업07_22_15_P34200003420000-118-2004-0000120040402<NA>3폐업2폐업20051128<NA><NA><NA>053 9642513194.50701260대구광역시 동구 율암동 363-9번지<NA><NA>세광프라스틱20040628000000I2018-08-31 23:59:59.0용기.포장지제조업353966.914738265491.811987용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
910용기·포장지제조업07_22_15_P34200003420000-118-2009-0000220091125<NA>1영업/정상1영업<NA><NA><NA><NA>053 963 6305876.46701330대구광역시 동구 금강동 1144번지대구광역시 동구 금강로 186, A동,B동,C동 1층 (금강동)41095대영프라젠20180208154721I2018-08-31 23:59:59.0용기.포장지제조업356719.234223263628.328553용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0105자가<NA><NA>N10.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
190191용기·포장지제조업07_22_15_P34800003480000-118-2011-0000120110330<NA>1영업/정상1영업<NA><NA><NA><NA>053 585 2373.00711841대구광역시 달성군 옥포면 간경리 724번지대구광역시 달성군 옥포면 비슬로457길 89-5, A동 1층42972대흥산업사20160711145019I2018-08-31 23:59:59.0용기.포장지제조업332745.987327256212.928958용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
191192용기·포장지제조업07_22_15_P34800003480000-118-2009-0000420091015<NA>1영업/정상1영업<NA><NA><NA><NA>053 611 88353,956.83711890대구광역시 달성군 구지면 848-4번지 가,라동대구광역시 달성군 구지면 달성2차동1로 57, 가,라동43013케이아이비20160128192806I2018-08-31 23:59:59.0용기.포장지제조업328251.2996238349.842802용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
192193용기·포장지제조업07_22_15_P34800003480000-118-2009-0000220090626<NA>1영업/정상1영업<NA><NA><NA><NA>053 615 050690.00711852대구광역시 달성군 논공읍 남리 717-4번지대구광역시 달성군 논공읍 논공로 24242985달성군장애인재활자립작업장20160128192825I2018-08-31 23:59:59.0용기.포장지제조업331461.531843248009.66281용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
193194용기·포장지제조업07_22_15_P34800003480000-118-2009-0000120090515<NA>1영업/정상1영업<NA><NA><NA><NA>053 615 21218,708.00711852대구광역시 달성군 논공읍 북리 580번지 외3필지대구광역시 달성군 논공읍 논공로53길 70 (외3필지)42981대원기계공업(주)20160128192848I2018-08-31 23:59:59.0용기.포장지제조업331206.199479249493.752629용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
194195용기·포장지제조업07_22_15_P34800003480000-118-2008-0000520080707<NA>1영업/정상1영업<NA><NA><NA><NA>053 6415433695.60711891대구광역시 달성군 구지면 예현리 757-4번지대구광역시 달성군 구지면 달성2차동1로 18743013대붕그라비아20160128192910I2018-08-31 23:59:59.0용기.포장지제조업328977.69611239004.505882용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
195196용기·포장지제조업07_22_15_P34800003480000-118-2015-0000420150703<NA>1영업/정상1영업<NA><NA><NA><NA>053 615 4490640.20711858대구광역시 달성군 논공읍 상리 694번지대구광역시 달성군 논공읍 비슬로262길 75-8, 1층42976동인산업20160128192501I2018-08-31 23:59:59.0용기.포장지제조업327960.00471250906.857956용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N46.7<NA><NA><NA>
196197용기·포장지제조업07_22_15_P34800003480000-118-1996-0000119961118<NA>1영업/정상1영업<NA><NA><NA><NA>053 6155858336.00711843대구광역시 달성군 옥포면 신당리 1168번지대구광역시 달성군 옥포면 신당4길 842969(주)성도팩20160128192156I2018-08-31 23:59:59.0용기.포장지제조업330161.023075256039.513677용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0013자가<NA><NA>N0.0<NA><NA><NA>
197198용기·포장지제조업07_22_15_P34800003480000-118-1995-0000219950506<NA>1영업/정상1영업<NA><NA><NA><NA>053 6165244694.32711842대구광역시 달성군 옥포면 강림리 173-4번지대구광역시 달성군 옥포면 시저로 92-742968동진산업20160128192139I2018-08-31 23:59:59.0용기.포장지제조업329008.163117254973.175151용기.포장지제조업<NA><NA><NA><NA><NA><NA>0304<NA><NA><NA>N0.0<NA><NA><NA>
198199용기·포장지제조업07_22_15_P34800003480000-118-1995-0000119950401<NA>1영업/정상1영업<NA><NA><NA><NA>053 6160057484.00711856대구광역시 달성군 논공읍 노이리 1303번지대구광역시 달성군 논공읍 노이길 12-642975상협산업주식회사20160128192121I2018-08-31 23:59:59.0용기.포장지제조업328908.419991252864.877295용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
199200용기·포장지제조업07_22_15_P34800003480000-118-2003-0000220030304<NA>1영업/정상1영업<NA><NA><NA><NA>053 6158083<NA>711855대구광역시 달성군 논공읍 본리리 29-116번지대구광역시 달성군 논공읍 논공로71길 2242982비닐월드(주)20200619152212U2020-06-21 02:40:00.0용기.포장지제조업332714.667572250011.626107용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>