Overview

Dataset statistics

Number of variables47
Number of observations210
Missing cells2291
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory83.4 KiB
Average record size in memory406.6 B

Variable types

Numeric12
Categorical18
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description22년06월_6270000_대구광역시_07_22_15_P_용기·포장지제조업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093750&dataSetDetailId=DDI_0000093778&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (74.5%)Imbalance
여성종사자수 is highly imbalanced (74.5%)Imbalance
총종업원수 is highly imbalanced (74.5%)Imbalance
본사종업원수 is highly imbalanced (65.1%)Imbalance
공장판매직종업원수 is highly imbalanced (61.7%)Imbalance
보증액 is highly imbalanced (79.8%)Imbalance
월세액 is highly imbalanced (79.8%)Imbalance
인허가취소일자 has 210 (100.0%) missing valuesMissing
폐업일자 has 81 (38.6%) missing valuesMissing
휴업시작일자 has 210 (100.0%) missing valuesMissing
휴업종료일자 has 210 (100.0%) missing valuesMissing
재개업일자 has 210 (100.0%) missing valuesMissing
소재지전화 has 17 (8.1%) missing valuesMissing
소재지면적 has 33 (15.7%) missing valuesMissing
소재지우편번호 has 4 (1.9%) missing valuesMissing
도로명전체주소 has 80 (38.1%) missing valuesMissing
도로명우편번호 has 83 (39.5%) missing valuesMissing
좌표정보(X) has 16 (7.6%) missing valuesMissing
좌표정보(Y) has 16 (7.6%) missing valuesMissing
영업장주변구분명 has 210 (100.0%) missing valuesMissing
등급구분명 has 210 (100.0%) missing valuesMissing
공장사무직종업원수 has 35 (16.7%) missing valuesMissing
공장생산직종업원수 has 35 (16.7%) missing valuesMissing
전통업소지정번호 has 210 (100.0%) missing valuesMissing
전통업소주된음식 has 210 (100.0%) missing valuesMissing
홈페이지 has 210 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장사무직종업원수 has 158 (75.2%) zerosZeros
공장생산직종업원수 has 147 (70.0%) zerosZeros
시설총규모 has 191 (91.0%) zerosZeros

Reproduction

Analysis started2024-04-20 18:26:10.472324
Analysis finished2024-04-20 18:26:11.565387
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.5
Minimum1
Maximum210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:11.761071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.45
Q153.25
median105.5
Q3157.75
95-th percentile199.55
Maximum210
Range209
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation60.765944
Coefficient of variation (CV)0.57598052
Kurtosis-1.2
Mean105.5
Median Absolute Deviation (MAD)52.5
Skewness0
Sum22155
Variance3692.5
MonotonicityStrictly increasing
2024-04-21T03:26:12.130819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
159 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
Other values (200) 200
95.2%
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 (%)
210 1
0.5%
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
용기·포장지제조업
210 

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 210
100.0%

Length

2024-04-21T03:26:12.398933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:12.565790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기·포장지제조업 210
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
07_22_15_P
210 

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 210
100.0%

Length

2024-04-21T03:26:12.732360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:12.896228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_15_p 210
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3466619
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:13.047314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3424500
Q13470000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation17237.37
Coefficient of variation (CV)0.0049723864
Kurtosis2.4587337
Mean3466619
Median Absolute Deviation (MAD)10000
Skewness-1.7401921
Sum7.2799 × 108
Variance2.9712691 × 108
MonotonicityIncreasing
2024-04-21T03:26:13.240714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 85
40.5%
3480000 77
36.7%
3450000 27
 
12.9%
3430000 8
 
3.8%
3420000 6
 
2.9%
3410000 5
 
2.4%
3460000 2
 
1.0%
ValueCountFrequency (%)
3410000 5
 
2.4%
3420000 6
 
2.9%
3430000 8
 
3.8%
3450000 27
 
12.9%
3460000 2
 
1.0%
3470000 85
40.5%
3480000 77
36.7%
ValueCountFrequency (%)
3480000 77
36.7%
3470000 85
40.5%
3460000 2
 
1.0%
3450000 27
 
12.9%
3430000 8
 
3.8%
3420000 6
 
2.9%
3410000 5
 
2.4%

관리번호
Text

UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-21T03:26:13.960232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4620
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

Unique210 ?
Unique (%)100.0%

Sample

1st row3410000-118-2007-00002
2nd row3410000-118-2007-00001
3rd row3410000-118-2008-00001
4th row3410000-118-2017-00001
5th row3410000-118-2004-00001
ValueCountFrequency (%)
3410000-118-2007-00002 1
 
0.5%
3480000-118-2002-00001 1
 
0.5%
3470000-118-2006-00004 1
 
0.5%
3480000-118-2001-00001 1
 
0.5%
3480000-118-2006-00001 1
 
0.5%
3480000-118-2007-00001 1
 
0.5%
3480000-118-2008-00001 1
 
0.5%
3480000-118-2008-00002 1
 
0.5%
3480000-118-1997-00001 1
 
0.5%
3480000-118-1998-00001 1
 
0.5%
Other values (200) 200
95.2%
2024-04-21T03:26:14.772786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1993
43.1%
- 630
 
13.6%
1 628
 
13.6%
8 317
 
6.9%
2 275
 
6.0%
3 270
 
5.8%
4 244
 
5.3%
7 111
 
2.4%
9 74
 
1.6%
5 56
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3990
86.4%
Dash Punctuation 630
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1993
49.9%
1 628
 
15.7%
8 317
 
7.9%
2 275
 
6.9%
3 270
 
6.8%
4 244
 
6.1%
7 111
 
2.8%
9 74
 
1.9%
5 56
 
1.4%
6 22
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 630
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4620
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1993
43.1%
- 630
 
13.6%
1 628
 
13.6%
8 317
 
6.9%
2 275
 
6.0%
3 270
 
5.8%
4 244
 
5.3%
7 111
 
2.4%
9 74
 
1.6%
5 56
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1993
43.1%
- 630
 
13.6%
1 628
 
13.6%
8 317
 
6.9%
2 275
 
6.0%
3 270
 
5.8%
4 244
 
5.3%
7 111
 
2.4%
9 74
 
1.6%
5 56
 
1.2%

인허가일자
Real number (ℝ)

Distinct202
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20061496
Minimum19870227
Maximum20220307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:15.035647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870227
5-th percentile19950448
Q120011101
median20051168
Q320110803
95-th percentile20201030
Maximum20220307
Range350080
Interquartile range (IQR)99701.75

Descriptive statistics

Standard deviation75832.105
Coefficient of variation (CV)0.0037799825
Kurtosis-0.14990808
Mean20061496
Median Absolute Deviation (MAD)40796
Skewness0.10285616
Sum4.2129142 × 109
Variance5.7505082 × 109
MonotonicityNot monotonic
2024-04-21T03:26:15.494406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070503 3
 
1.4%
20021205 3
 
1.4%
20010907 2
 
1.0%
20110803 2
 
1.0%
20070807 2
 
1.0%
19870227 2
 
1.0%
20200401 1
 
0.5%
20020919 1
 
0.5%
20071010 1
 
0.5%
20080115 1
 
0.5%
Other values (192) 192
91.4%
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 (%)
20220307 1
0.5%
20220128 1
0.5%
20211130 1
0.5%
20210909 1
0.5%
20210812 1
0.5%
20210621 1
0.5%
20210407 1
0.5%
20210402 1
0.5%
20210317 1
0.5%
20210312 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
129 
1
81 

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 (%)
3 129
61.4%
1 81
38.6%

Length

2024-04-21T03:26:15.906362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:16.221856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 129
61.4%
1 81
38.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
129 
영업/정상
81 

Length

Max length5
Median length2
Mean length3.1571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 129
61.4%
영업/정상 81
38.6%

Length

2024-04-21T03:26:16.602042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:16.939752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 129
61.4%
영업/정상 81
38.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2
129 
1
81 

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 (%)
2 129
61.4%
1 81
38.6%

Length

2024-04-21T03:26:17.117321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:17.356855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 129
61.4%
1 81
38.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
129 
영업
81 

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 129
61.4%
영업 81
38.6%

Length

2024-04-21T03:26:17.707295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:18.240257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 129
61.4%
영업 81
38.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct122
Distinct (%)94.6%
Missing81
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean20108707
Minimum20011030
Maximum20220426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:18.588083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011030
5-th percentile20030773
Q120060616
median20110414
Q320160226
95-th percentile20191229
Maximum20220426
Range209396
Interquartile range (IQR)99610

Descriptive statistics

Standard deviation54952.976
Coefficient of variation (CV)0.0027327951
Kurtosis-1.1269335
Mean20108707
Median Absolute Deviation (MAD)49812
Skewness0.21281685
Sum2.5940232 × 109
Variance3.0198296 × 109
MonotonicityNot monotonic
2024-04-21T03:26:19.011611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120306 4
 
1.9%
20050831 2
 
1.0%
20061208 2
 
1.0%
20151229 2
 
1.0%
20110524 2
 
1.0%
20120613 1
 
0.5%
20170321 1
 
0.5%
20191227 1
 
0.5%
20150303 1
 
0.5%
20170206 1
 
0.5%
Other values (112) 112
53.3%
(Missing) 81
38.6%
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 (%)
20220426 1
0.5%
20220401 1
0.5%
20210325 1
0.5%
20210226 1
0.5%
20200519 1
0.5%
20200207 1
0.5%
20191230 1
0.5%
20191227 1
0.5%
20191204 1
0.5%
20191203 1
0.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

소재지전화
Text

MISSING 

Distinct184
Distinct (%)95.3%
Missing17
Missing (%)8.1%
Memory size1.8 KiB
2024-04-21T03:26:20.062751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.031088
Min length7

Characters and Unicode

Total characters2129
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

Unique176 ?
Unique (%)91.2%

Sample

1st row053 5857788
2nd row053 2525022
3rd row053 256 3375
4th row053 5548531
5th row053 9642513
ValueCountFrequency (%)
053 145
36.9%
581 5
 
1.3%
5857788 3
 
0.8%
593 3
 
0.8%
583 3
 
0.8%
585 3
 
0.8%
615 3
 
0.8%
522 2
 
0.5%
592 2
 
0.5%
525 2
 
0.5%
Other values (210) 222
56.5%
2024-04-21T03:26:21.509327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 400
18.8%
0 335
15.7%
3 319
15.0%
201
9.4%
8 176
8.3%
1 170
8.0%
6 158
 
7.4%
4 106
 
5.0%
2 102
 
4.8%
9 82
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1928
90.6%
Space Separator 201
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 400
20.7%
0 335
17.4%
3 319
16.5%
8 176
9.1%
1 170
8.8%
6 158
 
8.2%
4 106
 
5.5%
2 102
 
5.3%
9 82
 
4.3%
7 80
 
4.1%
Space Separator
ValueCountFrequency (%)
201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2129
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 400
18.8%
0 335
15.7%
3 319
15.0%
201
9.4%
8 176
8.3%
1 170
8.0%
6 158
 
7.4%
4 106
 
5.0%
2 102
 
4.8%
9 82
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 400
18.8%
0 335
15.7%
3 319
15.0%
201
9.4%
8 176
8.3%
1 170
8.0%
6 158
 
7.4%
4 106
 
5.0%
2 102
 
4.8%
9 82
 
3.9%

소재지면적
Text

MISSING 

Distinct163
Distinct (%)92.1%
Missing33
Missing (%)15.7%
Memory size1.8 KiB
2024-04-21T03:26:22.696368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1129944
Min length3

Characters and Unicode

Total characters1082
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

Unique156 ?
Unique (%)88.1%

Sample

1st row52.80
2nd row195.50
3rd row16.54
4th row130.20
5th row194.50
ValueCountFrequency (%)
00 9
 
5.1%
132.00 2
 
1.1%
475.97 2
 
1.1%
334.80 2
 
1.1%
270.00 2
 
1.1%
264.00 2
 
1.1%
337.50 2
 
1.1%
244.80 1
 
0.6%
8,435.56 1
 
0.6%
52.80 1
 
0.6%
Other values (153) 153
86.4%
2024-04-21T03:26:24.302857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 230
21.3%
. 177
16.4%
2 92
 
8.5%
1 85
 
7.9%
4 78
 
7.2%
3 76
 
7.0%
6 74
 
6.8%
7 66
 
6.1%
5 62
 
5.7%
8 55
 
5.1%
Other values (2) 87
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 872
80.6%
Other Punctuation 210
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 230
26.4%
2 92
 
10.6%
1 85
 
9.7%
4 78
 
8.9%
3 76
 
8.7%
6 74
 
8.5%
7 66
 
7.6%
5 62
 
7.1%
8 55
 
6.3%
9 54
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 177
84.3%
, 33
 
15.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1082
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 230
21.3%
. 177
16.4%
2 92
 
8.5%
1 85
 
7.9%
4 78
 
7.2%
3 76
 
7.0%
6 74
 
6.8%
7 66
 
6.1%
5 62
 
5.7%
8 55
 
5.1%
Other values (2) 87
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1082
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 230
21.3%
. 177
16.4%
2 92
 
8.5%
1 85
 
7.9%
4 78
 
7.2%
3 76
 
7.0%
6 74
 
6.8%
7 66
 
6.1%
5 62
 
5.7%
8 55
 
5.1%
Other values (2) 87
 
8.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)36.4%
Missing4
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean706773.34
Minimum700191
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:24.715219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700191
5-th percentile701920.75
Q1704190
median704833
Q3711841.75
95-th percentile711886
Maximum711893
Range11702
Interquartile range (IQR)7651.75

Descriptive statistics

Standard deviation3894.2253
Coefficient of variation (CV)0.0055098644
Kurtosis-1.5242982
Mean706773.34
Median Absolute Deviation (MAD)2016.5
Skewness0.39955125
Sum1.4559531 × 108
Variance15164991
MonotonicityNot monotonic
2024-04-21T03:26:25.155707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704801 18
 
8.6%
704833 15
 
7.1%
704190 9
 
4.3%
704900 9
 
4.3%
711855 8
 
3.8%
702800 8
 
3.8%
711891 7
 
3.3%
711842 6
 
2.9%
711841 6
 
2.9%
711858 6
 
2.9%
Other values (65) 114
54.3%
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 7
3.3%
711890 1
 
0.5%
711874 1
 
0.5%
711858 6
2.9%
711856 4
1.9%
711855 8
3.8%
711852 4
1.9%
711851 3
 
1.4%

소재지전체주소
Text

Distinct205
Distinct (%)98.1%
Missing1
Missing (%)0.5%
Memory size1.8 KiB
2024-04-21T03:26:26.560575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length23.215311
Min length17

Characters and Unicode

Total characters4852
Distinct characters132
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

Unique201 ?
Unique (%)96.2%

Sample

1st row대구광역시 중구 남산동 0615-0002 지상3층
2nd row대구광역시 중구 남산동 2114-0010
3rd row대구광역시 중구 시장북로 0026-0001 지상 1층
4th row대구광역시 중구 종로1가 0040-0002 지상8층
5th row대구광역시 중구 달성동 0209-0015
ValueCountFrequency (%)
대구광역시 209
21.2%
달서구 85
 
8.6%
달성군 76
 
7.7%
북구 27
 
2.7%
논공읍 25
 
2.5%
옥포읍 24
 
2.4%
대천동 18
 
1.8%
월암동 17
 
1.7%
지상1층 15
 
1.5%
갈산동 14
 
1.4%
Other values (307) 476
48.3%
2024-04-21T03:26:28.386436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
998
20.6%
구 354
 
7.3%
1 237
 
4.9%
대 227
 
4.7%
시 212
 
4.4%
광 209
 
4.3%
역 209
 
4.3%
달 164
 
3.4%
동 160
 
3.3%
- 156
 
3.2%
Other values (122) 1926
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2664
54.9%
Space Separator 998
 
20.6%
Decimal Number 963
 
19.8%
Dash Punctuation 156
 
3.2%
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 354
13.3%
대 227
 
8.5%
시 212
 
8.0%
광 209
 
7.8%
역 209
 
7.8%
달 164
 
6.2%
동 160
 
6.0%
서 98
 
3.7%
리 94
 
3.5%
성 92
 
3.5%
Other values (101) 845
31.7%
Decimal Number
ValueCountFrequency (%)
1 237
24.6%
2 114
11.8%
0 108
11.2%
3 98
10.2%
6 80
 
8.3%
4 76
 
7.9%
5 72
 
7.5%
7 66
 
6.9%
9 58
 
6.0%
8 54
 
5.6%
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 (%)
998
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
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 2664
54.9%
Common 2173
44.8%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 354
13.3%
대 227
 
8.5%
시 212
 
8.0%
광 209
 
7.8%
역 209
 
7.8%
달 164
 
6.2%
동 160
 
6.0%
서 98
 
3.7%
리 94
 
3.5%
성 92
 
3.5%
Other values (101) 845
31.7%
Common
ValueCountFrequency (%)
998
45.9%
1 237
 
10.9%
- 156
 
7.2%
2 114
 
5.2%
0 108
 
5.0%
3 98
 
4.5%
6 80
 
3.7%
4 76
 
3.5%
5 72
 
3.3%
7 66
 
3.0%
Other values (6) 168
 
7.7%
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 2664
54.9%
ASCII 2188
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
998
45.6%
1 237
 
10.8%
- 156
 
7.1%
2 114
 
5.2%
0 108
 
4.9%
3 98
 
4.5%
6 80
 
3.7%
4 76
 
3.5%
5 72
 
3.3%
7 66
 
3.0%
Other values (11) 183
 
8.4%
Hangul
ValueCountFrequency (%)
구 354
13.3%
대 227
 
8.5%
시 212
 
8.0%
광 209
 
7.8%
역 209
 
7.8%
달 164
 
6.2%
동 160
 
6.0%
서 98
 
3.7%
리 94
 
3.5%
성 92
 
3.5%
Other values (101) 845
31.7%

도로명전체주소
Text

MISSING 

Distinct130
Distinct (%)100.0%
Missing80
Missing (%)38.1%
Memory size1.8 KiB
2024-04-21T03:26:29.600100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length28.330769
Min length20

Characters and Unicode

Total characters3683
Distinct characters151
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

Unique130 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 중앙대로65길 28, 3층 (남산동)
2nd row대구광역시 중구 국채보상로 554-1 (종로1가, 지상8층)
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 130
 
17.7%
달성군 55
 
7.5%
달서구 54
 
7.3%
1층 40
 
5.4%
논공읍 21
 
2.9%
옥포읍 16
 
2.2%
북구 13
 
1.8%
대천동 10
 
1.4%
월암동 10
 
1.4%
구지면 10
 
1.4%
Other values (265) 376
51.2%
2024-04-21T03:26:31.332318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
605
 
16.4%
구 217
 
5.9%
1 154
 
4.2%
대 154
 
4.2%
시 135
 
3.7%
광 130
 
3.5%
역 130
 
3.5%
달 125
 
3.4%
동 113
 
3.1%
서 112
 
3.0%
Other values (141) 1808
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2203
59.8%
Space Separator 605
 
16.4%
Decimal Number 560
 
15.2%
Close Punctuation 93
 
2.5%
Open Punctuation 93
 
2.5%
Other Punctuation 74
 
2.0%
Dash Punctuation 33
 
0.9%
Uppercase Letter 16
 
0.4%
Math Symbol 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 217
 
9.9%
대 154
 
7.0%
시 135
 
6.1%
광 130
 
5.9%
역 130
 
5.9%
달 125
 
5.7%
동 113
 
5.1%
서 112
 
5.1%
로 112
 
5.1%
성 107
 
4.9%
Other values (119) 868
39.4%
Decimal Number
ValueCountFrequency (%)
1 154
27.5%
2 79
14.1%
3 63
11.2%
5 58
 
10.4%
6 44
 
7.9%
7 41
 
7.3%
8 33
 
5.9%
4 33
 
5.9%
9 30
 
5.4%
0 25
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 8
50.0%
C 3
 
18.8%
B 2
 
12.5%
L 1
 
6.2%
E 1
 
6.2%
D 1
 
6.2%
Space Separator
ValueCountFrequency (%)
605
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2203
59.8%
Common 1464
39.8%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 217
 
9.9%
대 154
 
7.0%
시 135
 
6.1%
광 130
 
5.9%
역 130
 
5.9%
달 125
 
5.7%
동 113
 
5.1%
서 112
 
5.1%
로 112
 
5.1%
성 107
 
4.9%
Other values (119) 868
39.4%
Common
ValueCountFrequency (%)
605
41.3%
1 154
 
10.5%
) 93
 
6.4%
( 93
 
6.4%
2 79
 
5.4%
, 74
 
5.1%
3 63
 
4.3%
5 58
 
4.0%
6 44
 
3.0%
7 41
 
2.8%
Other values (6) 160
 
10.9%
Latin
ValueCountFrequency (%)
A 8
50.0%
C 3
 
18.8%
B 2
 
12.5%
L 1
 
6.2%
E 1
 
6.2%
D 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2203
59.8%
ASCII 1480
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
605
40.9%
1 154
 
10.4%
) 93
 
6.3%
( 93
 
6.3%
2 79
 
5.3%
, 74
 
5.0%
3 63
 
4.3%
5 58
 
3.9%
6 44
 
3.0%
7 41
 
2.8%
Other values (12) 176
 
11.9%
Hangul
ValueCountFrequency (%)
구 217
 
9.9%
대 154
 
7.0%
시 135
 
6.1%
광 130
 
5.9%
역 130
 
5.9%
달 125
 
5.7%
동 113
 
5.1%
서 112
 
5.1%
로 112
 
5.1%
성 107
 
4.9%
Other values (119) 868
39.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)48.8%
Missing83
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean42644.756
Minimum41037
Maximum43013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:31.760953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41037
5-th percentile41504.5
Q142703
median42721
Q342974.5
95-th percentile43010.1
Maximum43013
Range1976
Interquartile range (IQR)271.5

Descriptive statistics

Standard deviation494.13833
Coefficient of variation (CV)0.011587318
Kurtosis1.9601382
Mean42644.756
Median Absolute Deviation (MAD)247
Skewness-1.7905414
Sum5415884
Variance244172.69
MonotonicityNot monotonic
2024-04-21T03:26:32.168437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42719 8
 
3.8%
42718 8
 
3.8%
42976 6
 
2.9%
43013 6
 
2.9%
42968 6
 
2.9%
42721 4
 
1.9%
42982 4
 
1.9%
42970 4
 
1.9%
42972 4
 
1.9%
42724 3
 
1.4%
Other values (52) 74
35.2%
(Missing) 83
39.5%
ValueCountFrequency (%)
41037 1
0.5%
41095 1
0.5%
41433 1
0.5%
41495 1
0.5%
41498 1
0.5%
41499 1
0.5%
41503 1
0.5%
41508 1
0.5%
41509 2
1.0%
41510 1
0.5%
ValueCountFrequency (%)
43013 6
2.9%
43011 1
 
0.5%
43008 3
1.4%
42993 1
 
0.5%
42983 3
1.4%
42982 4
1.9%
42981 2
 
1.0%
42977 3
1.4%
42976 6
2.9%
42975 3
1.4%

사업장명
Text

Distinct195
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-21T03:26:33.218767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.847619
Min length2

Characters and Unicode

Total characters1228
Distinct characters200
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

Unique182 ?
Unique (%)86.7%

Sample

1st row동아피엔비
2nd row대양정밀인쇄
3rd row오성상사
4th row카유아티산
5th row명성인쇄사
ValueCountFrequency (%)
동아피엔비 3
 
1.4%
주식회사 3
 
1.4%
대호화학산업 3
 
1.4%
한일산업사 2
 
0.9%
주)코레쉬텍 2
 
0.9%
오성그라비아 2
 
0.9%
대우포장 2
 
0.9%
주)동신에스피 2
 
0.9%
신오산업 2
 
0.9%
경북인쇄포장 2
 
0.9%
Other values (192) 196
89.5%
2024-04-21T03:26:34.677312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 69
 
5.6%
산 64
 
5.2%
주 54
 
4.4%
( 52
 
4.2%
) 52
 
4.2%
사 40
 
3.3%
대 39
 
3.2%
성 30
 
2.4%
스 29
 
2.4%
동 27
 
2.2%
Other values (190) 772
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1104
89.9%
Open Punctuation 52
 
4.2%
Close Punctuation 52
 
4.2%
Space Separator 9
 
0.7%
Uppercase Letter 9
 
0.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 69
 
6.2%
산 64
 
5.8%
주 54
 
4.9%
사 40
 
3.6%
대 39
 
3.5%
성 30
 
2.7%
스 29
 
2.6%
동 27
 
2.4%
라 24
 
2.2%
아 23
 
2.1%
Other values (180) 705
63.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
44.4%
H 1
 
11.1%
D 1
 
11.1%
J 1
 
11.1%
C 1
 
11.1%
E 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1104
89.9%
Common 115
 
9.4%
Latin 9
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 69
 
6.2%
산 64
 
5.8%
주 54
 
4.9%
사 40
 
3.6%
대 39
 
3.5%
성 30
 
2.7%
스 29
 
2.6%
동 27
 
2.4%
라 24
 
2.2%
아 23
 
2.1%
Other values (180) 705
63.9%
Latin
ValueCountFrequency (%)
S 4
44.4%
H 1
 
11.1%
D 1
 
11.1%
J 1
 
11.1%
C 1
 
11.1%
E 1
 
11.1%
Common
ValueCountFrequency (%)
( 52
45.2%
) 52
45.2%
9
 
7.8%
& 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1104
89.9%
ASCII 124
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 69
 
6.2%
산 64
 
5.8%
주 54
 
4.9%
사 40
 
3.6%
대 39
 
3.5%
성 30
 
2.7%
스 29
 
2.6%
동 27
 
2.4%
라 24
 
2.2%
아 23
 
2.1%
Other values (180) 705
63.9%
ASCII
ValueCountFrequency (%)
( 52
41.9%
) 52
41.9%
9
 
7.3%
S 4
 
3.2%
& 2
 
1.6%
H 1
 
0.8%
D 1
 
0.8%
J 1
 
0.8%
C 1
 
0.8%
E 1
 
0.8%

최종수정시점
Real number (ℝ)

Distinct182
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0113134 × 1013
Minimum2.0010822 × 1013
Maximum2.022052 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:35.090314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010822 × 1013
5-th percentile2.0020115 × 1013
Q12.0041013 × 1013
median2.0120267 × 1013
Q32.0171224 × 1013
95-th percentile2.0210681 × 1013
Maximum2.022052 × 1013
Range2.0969817 × 1011
Interquartile range (IQR)1.3021161 × 1011

Descriptive statistics

Standard deviation6.9746026 × 1010
Coefficient of variation (CV)0.0034676856
Kurtosis-1.5030994
Mean2.0113134 × 1013
Median Absolute Deviation (MAD)6.9303667 × 1010
Skewness-0.089783495
Sum4.2237582 × 1015
Variance4.8645081 × 1021
MonotonicityNot monotonic
2024-04-21T03:26:35.511939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020523000000 16
 
7.6%
20010822000000 8
 
3.8%
20041019000000 2
 
1.0%
20011015000000 2
 
1.0%
20020903000000 2
 
1.0%
20020115000000 2
 
1.0%
20041018000000 2
 
1.0%
20020124000000 2
 
1.0%
20160128192334 1
 
0.5%
20190226151848 1
 
0.5%
Other values (172) 172
81.9%
ValueCountFrequency (%)
20010822000000 8
3.8%
20011015000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20020214000000 1
 
0.5%
20020420000000 1
 
0.5%
20020523000000 16
7.6%
20020615000000 1
 
0.5%
20020903000000 2
 
1.0%
20021016000000 1
 
0.5%
ValueCountFrequency (%)
20220520165757 1
0.5%
20220426170721 1
0.5%
20220401113935 1
0.5%
20220307134454 1
0.5%
20220207174258 1
0.5%
20211227151614 1
0.5%
20211227104327 1
0.5%
20211130130815 1
0.5%
20210909103208 1
0.5%
20210824180631 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
I
174 
U
36 

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 174
82.9%
U 36
 
17.1%

Length

2024-04-21T03:26:35.902997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:36.213940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 174
82.9%
u 36
 
17.1%

데이터갱신일자
Date

Distinct45
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-08-31 23:59:59
Maximum2022-05-22 02:40:00
2024-04-21T03:26:36.543054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:26:36.874534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
용기.포장지제조업
210 

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 210
100.0%

Length

2024-04-21T03:26:37.091360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:37.253866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 210
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct188
Distinct (%)96.9%
Missing16
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean335861.98
Minimum325886.5
Maximum356719.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:37.440370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325886.5
5-th percentile328210.27
Q1332575.81
median335501.87
Q3337234.61
95-th percentile346275.5
Maximum356719.23
Range30832.738
Interquartile range (IQR)4658.8028

Descriptive statistics

Standard deviation5661.9068
Coefficient of variation (CV)0.016857838
Kurtosis1.9968586
Mean335861.98
Median Absolute Deviation (MAD)2723.6776
Skewness1.1337085
Sum65157223
Variance32057189
MonotonicityNot monotonic
2024-04-21T03:26:37.897291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
331841.584525 2
 
1.0%
345971.954573 2
 
1.0%
328209.453202 2
 
1.0%
333135.698427 2
 
1.0%
335156.423755 2
 
1.0%
331839.79406 2
 
1.0%
326023.452178 1
 
0.5%
328210.715551 1
 
0.5%
328973.17482 1
 
0.5%
333132.706239 1
 
0.5%
Other values (178) 178
84.8%
(Missing) 16
 
7.6%
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%
327862.554647 1
0.5%
327960.00471 1
0.5%
328209.453202 2
1.0%
328210.715551 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 

Distinct188
Distinct (%)96.9%
Missing16
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean258631.22
Minimum237999.44
Maximum272637.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:38.145806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237999.44
5-th percentile240374.96
Q1255615.25
median260051.15
Q3262691.94
95-th percentile268400.82
Maximum272637.94
Range34638.5
Interquartile range (IQR)7076.6956

Descriptive statistics

Standard deviation7200.1073
Coefficient of variation (CV)0.027839282
Kurtosis1.1758604
Mean258631.22
Median Absolute Deviation (MAD)3821.9038
Skewness-1.0588461
Sum50174456
Variance51841546
MonotonicityNot monotonic
2024-04-21T03:26:38.390527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
255452.921933 2
 
1.0%
269410.738999 2
 
1.0%
251079.280489 2
 
1.0%
255625.666969 2
 
1.0%
259818.122046 2
 
1.0%
249314.473196 2
 
1.0%
240780.386054 1
 
0.5%
251104.705085 1
 
0.5%
255004.386047 1
 
0.5%
265390.957692 1
 
0.5%
Other values (178) 178
84.8%
(Missing) 16
 
7.6%
ValueCountFrequency (%)
237999.437164 1
0.5%
238106.714053 1
0.5%
238349.842802 1
0.5%
238351.723424 1
0.5%
238819.915072 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%
ValueCountFrequency (%)
272637.936804 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 size1.8 KiB
용기.포장지제조업
210 

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 210
100.0%

Length

2024-04-21T03:26:38.612695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:38.775602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 210
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
201 
0
 
9

Length

Max length4
Median length4
Mean length3.8714286
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> 201
95.7%
0 9
 
4.3%

Length

2024-04-21T03:26:38.957935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:39.136010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
95.7%
0 9
 
4.3%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
201 
0
 
9

Length

Max length4
Median length4
Mean length3.8714286
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> 201
95.7%
0 9
 
4.3%

Length

2024-04-21T03:26:39.321759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:39.498667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
95.7%
0 9
 
4.3%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
136 
상수도전용
73 
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.352381
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 136
64.8%
상수도전용 73
34.8%
간이상수도 1
 
0.5%

Length

2024-04-21T03:26:39.685044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:39.873497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
64.8%
상수도전용 73
34.8%
간이상수도 1
 
0.5%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
201 
0
 
9

Length

Max length4
Median length4
Mean length3.8714286
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> 201
95.7%
0 9
 
4.3%

Length

2024-04-21T03:26:40.067039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:40.249490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
95.7%
0 9
 
4.3%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
0
171 
<NA>
35 
1
 
2
4
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.5
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 171
81.4%
<NA> 35
 
16.7%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

Length

2024-04-21T03:26:40.476928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:40.830805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 171
81.4%
na 35
 
16.7%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.4%
Missing35
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean0.25714286
Minimum0
Maximum15
Zeros158
Zeros (%)75.2%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:41.142552image/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 deviation1.413052
Coefficient of variation (CV)5.4952022
Kurtosis81.070014
Mean0.25714286
Median Absolute Deviation (MAD)0
Skewness8.6086997
Sum45
Variance1.9967159
MonotonicityNot monotonic
2024-04-21T03:26:41.493807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 158
75.2%
1 12
 
5.7%
3 2
 
1.0%
10 1
 
0.5%
2 1
 
0.5%
15 1
 
0.5%
(Missing) 35
 
16.7%
ValueCountFrequency (%)
0 158
75.2%
1 12
 
5.7%
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
 
5.7%
0 158
75.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
0
168 
<NA>
35 
1
 
5
6
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.5
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 168
80.0%
<NA> 35
 
16.7%
1 5
 
2.4%
6 1
 
0.5%
2 1
 
0.5%

Length

2024-04-21T03:26:41.913295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:42.265576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 168
80.0%
na 35
 
16.7%
1 5
 
2.4%
6 1
 
0.5%
2 1
 
0.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.3%
Missing35
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean1.16
Minimum0
Maximum45
Zeros147
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:42.594340image/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 deviation5.0897237
Coefficient of variation (CV)4.3876928
Kurtosis62.671856
Mean1.16
Median Absolute Deviation (MAD)0
Skewness7.5661776
Sum203
Variance25.905287
MonotonicityNot monotonic
2024-04-21T03:26:42.939953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 147
70.0%
2 7
 
3.3%
4 5
 
2.4%
3 3
 
1.4%
5 3
 
1.4%
1 2
 
1.0%
9 2
 
1.0%
7 2
 
1.0%
45 2
 
1.0%
11 1
 
0.5%
(Missing) 35
 
16.7%
ValueCountFrequency (%)
0 147
70.0%
1 2
 
1.0%
2 7
 
3.3%
3 3
 
1.4%
4 5
 
2.4%
5 3
 
1.4%
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
1.4%
4 5
2.4%
3 3
1.4%
2 7
3.3%
1 2
 
1.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
153 
자가
32 
임대
25 

Length

Max length4
Median length4
Mean length3.4571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
72.9%
자가 32
 
15.2%
임대 25
 
11.9%

Length

2024-04-21T03:26:43.359231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:43.717779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
72.9%
자가 32
 
15.2%
임대 25
 
11.9%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
199 
0
 
10
30000000
 
1

Length

Max length8
Median length4
Mean length3.8761905
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
94.8%
0 10
 
4.8%
30000000 1
 
0.5%

Length

2024-04-21T03:26:44.096313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:44.434855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 199
94.8%
0 10
 
4.8%
30000000 1
 
0.5%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
199 
0
 
10
1200000
 
1

Length

Max length7
Median length4
Mean length3.8714286
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
94.8%
0 10
 
4.8%
1200000 1
 
0.5%

Length

2024-04-21T03:26:44.794637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:26:45.125679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 199
94.8%
0 10
 
4.8%
1200000 1
 
0.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size338.0 B
False
210 
ValueCountFrequency (%)
False 210
100.0%
2024-04-21T03:26:45.417733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1436667
Minimum0
Maximum907.75
Zeros191
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T03:26:45.719128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19.555
Maximum907.75
Range907.75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation70.082914
Coefficient of variation (CV)7.66464
Kurtosis135.20658
Mean9.1436667
Median Absolute Deviation (MAD)0
Skewness11.146462
Sum1920.17
Variance4911.6148
MonotonicityNot monotonic
2024-04-21T03:26:46.064544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 191
91.0%
3.0 1
 
0.5%
35.35 1
 
0.5%
12.6 1
 
0.5%
16.51 1
 
0.5%
46.7 1
 
0.5%
24.13 1
 
0.5%
401.01 1
 
0.5%
907.75 1
 
0.5%
9.9 1
 
0.5%
Other values (10) 10
 
4.8%
ValueCountFrequency (%)
0.0 191
91.0%
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%
17.5 1
 
0.5%
19.5 1
 
0.5%
19.6 1
 
0.5%
ValueCountFrequency (%)
907.75 1
0.5%
401.01 1
0.5%
211.47 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%
31.8 1
0.5%
24.13 1
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing210
Missing (%)100.0%
Memory size2.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01용기·포장지제조업07_22_15_P34100003410000-118-2007-0000220070503<NA>3폐업2폐업20160112<NA><NA><NA>053 585778852.80700832대구광역시 중구 남산동 0615-0002 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>
12용기·포장지제조업07_22_15_P34100003410000-118-2007-0000120071126<NA>3폐업2폐업20090306<NA><NA><NA>053 2525022195.50700804대구광역시 중구 남산동 2114-0010<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>
23용기·포장지제조업07_22_15_P34100003410000-118-2008-0000120081022<NA>3폐업2폐업20101207<NA><NA><NA>053 256 3375<NA>700290대구광역시 중구 시장북로 0026-0001 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>
34용기·포장지제조업07_22_15_P34100003410000-118-2017-0000120170306<NA>3폐업2폐업20171219<NA><NA><NA><NA>16.54700191대구광역시 중구 종로1가 0040-0002 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>
45용기·포장지제조업07_22_15_P34100003410000-118-2004-0000120040922<NA>3폐업2폐업20060619<NA><NA><NA>053 5548531130.20700841대구광역시 중구 달성동 0209-0015<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_P34200003420000-118-2004-0000120040402<NA>3폐업2폐업20051128<NA><NA><NA>053 9642513194.50701260대구광역시 동구 율암동 363-9<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>
67용기·포장지제조업07_22_15_P34200003420000-118-2009-0000120091112<NA>3폐업2폐업20171226<NA><NA><NA>053 981 4735525.68701850대구광역시 동구 지저동 203-6대구광역시 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>
78용기·포장지제조업07_22_15_P34200003420000-118-1996-0000119960304<NA>3폐업2폐업20040402<NA><NA><NA>053 9554029450.59701870대구광역시 동구 신서동 626-6<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>
89용기·포장지제조업07_22_15_P34200003420000-118-2001-0000120010809<NA>3폐업2폐업20021105<NA><NA><NA>053 9640371821.40701848대구광역시 동구 동호동 98-10<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>
910용기·포장지제조업07_22_15_P34200003420000-118-2009-0000220091125<NA>1영업/정상1영업<NA><NA><NA><NA>053 963 6305876.46701330대구광역시 동구 금강동 1144대구광역시 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>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
200201용기·포장지제조업07_22_15_P34800003480000-118-2012-0000120120822<NA>3폐업2폐업20120831<NA><NA><NA>585 5456<NA>711813대구광역시 달성군 다사읍 서재리 396-1대구광역시 달성군 다사읍 서재로14길 1642927신평비닐산업사20120822111339I2018-08-31 23:59:59.0용기.포장지제조업335261.341201264322.319515용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
201202용기·포장지제조업07_22_15_P34800003480000-118-2014-0000120140627<NA>3폐업2폐업20191203<NA><NA><NA>053 637 9466240.00711851대구광역시 달성군 논공읍 금포리 469-1대구광역시 달성군 논공읍 농공공단1길 66-8, 1층42968주식회사 누리산업20191203135159U2019-12-05 02:40:00.0용기.포장지제조업328725.704925254722.735305용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
202203용기·포장지제조업07_22_15_P34800003480000-118-2014-0000220141106<NA>3폐업2폐업20190524<NA><NA><NA>070 41116449149.75711851대구광역시 달성군 논공읍 금포리 1370-1대구광역시 달성군 논공읍 달성군청로6길 1642974(주)크린코리아20190524175611U2019-05-26 02:40:00.0용기.포장지제조업328972.589147253698.137636용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
203204용기·포장지제조업07_22_15_P34800003480000-118-2002-0000520021118<NA>3폐업2폐업20100118<NA><NA><NA>053 6168800495.00711842대구광역시 달성군 옥포읍 반송리 504-1<NA><NA>코벤트 기술연구소20090309154643I2018-08-31 23:59:59.0용기.포장지제조업<NA><NA>용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
204205용기·포장지제조업07_22_15_P34800003480000-118-2003-0000320030422<NA>3폐업2폐업20161128<NA><NA><NA>053 6170965723.93711858대구광역시 달성군 논공읍 상리 799-20 1~2층대구광역시 달성군 논공읍 비슬로262길 35-16 (1~2층)42976동원산업20160128192424I2018-08-31 23:59:59.0용기.포장지제조업327654.764936250726.806252용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
205206용기·포장지제조업07_22_15_P34800003480000-118-2003-0000420031017<NA>3폐업2폐업20151229<NA><NA><NA>053 6169716200.00711844대구광역시 달성군 옥포읍 김흥리 1157-1대구광역시 달성군 옥포읍 원전1길 2542977수림산업사20031017000000I2018-08-31 23:59:59.0용기.포장지제조업335393.858976250758.695027용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
206207용기·포장지제조업07_22_15_P34800003480000-118-2004-0000120040702<NA>3폐업2폐업20210226<NA><NA><NA>043 214 271467.23711855대구광역시 달성군 논공읍 본리리 29-6대구광역시 달성군 논공읍 논공중앙로 35042983(주)에이치 팩토리 대구지점20210226130211U2021-02-28 02:40:00.0용기.포장지제조업332837.665548249837.479543용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
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208209용기·포장지제조업07_22_15_P34800003480000-118-2005-0000320050825<NA>3폐업2폐업20070116<NA><NA><NA>053 633009082.17711836대구광역시 달성군 화원읍 천내리 450-4<NA><NA>대명산업20050825000000I2018-08-31 23:59:59.0용기.포장지제조업335642.525911256872.960873용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
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