Overview

Dataset statistics

Number of variables47
Number of observations197
Missing cells2740
Missing cells (%)29.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.2 KiB
Average record size in memory406.7 B

Variable types

Numeric12
Categorical15
Text6
Unsupported12
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_15_P_용기·포장지제조업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085858&dataSetDetailId=DDI_0000085918&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
본사종업원수 is highly imbalanced (65.2%)Imbalance
공장판매직종업원수 is highly imbalanced (61.5%)Imbalance
보증액 is highly imbalanced (94.2%)Imbalance
월세액 is highly imbalanced (94.2%)Imbalance
인허가취소일자 has 197 (100.0%) missing valuesMissing
폐업일자 has 72 (36.5%) missing valuesMissing
휴업시작일자 has 197 (100.0%) missing valuesMissing
휴업종료일자 has 197 (100.0%) missing valuesMissing
재개업일자 has 197 (100.0%) missing valuesMissing
소재지전화 has 13 (6.6%) missing valuesMissing
소재지면적 has 31 (15.7%) missing valuesMissing
소재지우편번호 has 2 (1.0%) missing valuesMissing
도로명전체주소 has 80 (40.6%) missing valuesMissing
도로명우편번호 has 83 (42.1%) missing valuesMissing
좌표정보(X) has 15 (7.6%) missing valuesMissing
좌표정보(Y) has 15 (7.6%) missing valuesMissing
남성종사자수 has 197 (100.0%) missing valuesMissing
여성종사자수 has 197 (100.0%) missing valuesMissing
영업장주변구분명 has 197 (100.0%) missing valuesMissing
등급구분명 has 197 (100.0%) missing valuesMissing
총종업원수 has 197 (100.0%) missing valuesMissing
공장사무직종업원수 has 32 (16.2%) missing valuesMissing
공장생산직종업원수 has 32 (16.2%) missing valuesMissing
전통업소지정번호 has 197 (100.0%) missing valuesMissing
전통업소주된음식 has 197 (100.0%) missing valuesMissing
홈페이지 has 197 (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 (75.6%) zerosZeros
공장생산직종업원수 has 138 (70.1%) zerosZeros
시설총규모 has 183 (92.9%) zerosZeros

Reproduction

Analysis started2023-12-10 18:19:36.050200
Analysis finished2023-12-10 18:19:37.080240
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:37.196631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2023-12-11T03:19:37.414606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 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%
Other values (187) 187
94.9%
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 (%)
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%
190 1
0.5%
189 1
0.5%
188 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기·포장지제조업
197 

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 197
100.0%

Length

2023-12-11T03:19:37.620856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:37.745712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기·포장지제조업 197
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
07_22_15_P
197 

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 197
100.0%

Length

2023-12-11T03:19:37.862817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:38.014613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_15_p 197
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3466446.7
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:38.133909image/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 deviation17337.098
Coefficient of variation (CV)0.0050014032
Kurtosis2.4993801
Mean3466446.7
Median Absolute Deviation (MAD)10000
Skewness-1.753856
Sum6.8289 × 108
Variance3.0057495 × 108
MonotonicityIncreasing
2023-12-11T03:19:38.310800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 82
41.6%
3480000 70
35.5%
3450000 25
 
12.7%
3430000 7
 
3.6%
3420000 6
 
3.0%
3410000 5
 
2.5%
3460000 2
 
1.0%
ValueCountFrequency (%)
3410000 5
 
2.5%
3420000 6
 
3.0%
3430000 7
 
3.6%
3450000 25
 
12.7%
3460000 2
 
1.0%
3470000 82
41.6%
3480000 70
35.5%
ValueCountFrequency (%)
3480000 70
35.5%
3470000 82
41.6%
3460000 2
 
1.0%
3450000 25
 
12.7%
3430000 7
 
3.6%
3420000 6
 
3.0%
3410000 5
 
2.5%

관리번호
Text

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:19:38.594094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4334
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

Unique197 ?
Unique (%)100.0%

Sample

1st row3410000-118-2007-00002
2nd row3410000-118-2004-00001
3rd row3410000-118-2017-00001
4th row3410000-118-2008-00001
5th row3410000-118-2007-00001
ValueCountFrequency (%)
3410000-118-2007-00002 1
 
0.5%
3470000-118-2008-00002 1
 
0.5%
3470000-118-1997-00003 1
 
0.5%
3480000-118-2002-00004 1
 
0.5%
3480000-118-2001-00006 1
 
0.5%
3480000-118-2001-00005 1
 
0.5%
3480000-118-2001-00004 1
 
0.5%
3480000-118-2001-00003 1
 
0.5%
3480000-118-1987-00001 1
 
0.5%
3480000-118-2020-00001 1
 
0.5%
Other values (187) 187
94.9%
2023-12-11T03:19:38.991220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1874
43.2%
- 591
 
13.6%
1 587
 
13.5%
8 297
 
6.9%
3 251
 
5.8%
2 245
 
5.7%
4 231
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 54
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3743
86.4%
Dash Punctuation 591
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1874
50.1%
1 587
 
15.7%
8 297
 
7.9%
3 251
 
6.7%
2 245
 
6.5%
4 231
 
6.2%
7 108
 
2.9%
9 74
 
2.0%
5 54
 
1.4%
6 22
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 591
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4334
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1874
43.2%
- 591
 
13.6%
1 587
 
13.5%
8 297
 
6.9%
3 251
 
5.8%
2 245
 
5.7%
4 231
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 54
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1874
43.2%
- 591
 
13.6%
1 587
 
13.5%
8 297
 
6.9%
3 251
 
5.8%
2 245
 
5.7%
4 231
 
5.3%
7 108
 
2.5%
9 74
 
1.7%
5 54
 
1.2%

인허가일자
Real number (ℝ)

Distinct189
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20052059
Minimum19870227
Maximum20200611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:39.223300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870227
5-th percentile19948463
Q120010917
median20050111
Q320091125
95-th percentile20170211
Maximum20200611
Range330384
Interquartile range (IQR)80208

Descriptive statistics

Standard deviation68222.371
Coefficient of variation (CV)0.0034022626
Kurtosis0.049306189
Mean20052059
Median Absolute Deviation (MAD)39806
Skewness-0.081438082
Sum3.9502556 × 109
Variance4.654292 × 109
MonotonicityNot monotonic
2023-12-11T03:19:39.494857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070503 3
 
1.5%
20021205 3
 
1.5%
20010907 2
 
1.0%
20110803 2
 
1.0%
20070807 2
 
1.0%
19870227 2
 
1.0%
19971030 1
 
0.5%
20021105 1
 
0.5%
20011005 1
 
0.5%
20010917 1
 
0.5%
Other values (179) 179
90.9%
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 (%)
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%
20170306 1
0.5%
20170224 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
125 
1
72 

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
63.5%
1 72
36.5%

Length

2023-12-11T03:19:39.680099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:39.824912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 125
63.5%
1 72
36.5%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
125 
영업/정상
72 

Length

Max length5
Median length2
Mean length3.0964467
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 125
63.5%
영업/정상 72
36.5%

Length

2023-12-11T03:19:39.984390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:40.152343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 125
63.5%
영업/정상 72
36.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
125 
1
72 

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
63.5%
1 72
36.5%

Length

2023-12-11T03:19:40.346933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:40.500761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 125
63.5%
1 72
36.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
125 
영업
72 

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
63.5%
영업 72
36.5%

Length

2023-12-11T03:19:40.674539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:40.813581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 125
63.5%
영업 72
36.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)94.4%
Missing72
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean20105295
Minimum20011030
Maximum20200519
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:40.975326image/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
2023-12-11T03:19:41.183450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120306 4
 
2.0%
20050831 2
 
1.0%
20151229 2
 
1.0%
20110524 2
 
1.0%
20061208 2
 
1.0%
20191204 1
 
0.5%
20120613 1
 
0.5%
20101026 1
 
0.5%
20090821 1
 
0.5%
20051006 1
 
0.5%
Other values (108) 108
54.8%
(Missing) 72
36.5%
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 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

소재지전화
Text

MISSING 

Distinct175
Distinct (%)95.1%
Missing13
Missing (%)6.6%
Memory size1.7 KiB
2023-12-11T03:19:41.616413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.027174
Min length7

Characters and Unicode

Total characters2029
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

Unique167 ?
Unique (%)90.8%

Sample

1st row053 5857788
2nd row053 5548531
3rd row053 256 3375
4th row053 2525022
5th row053 9640371
ValueCountFrequency (%)
053 138
36.9%
581 5
 
1.3%
615 3
 
0.8%
583 3
 
0.8%
585 3
 
0.8%
5857788 3
 
0.8%
593 3
 
0.8%
5857956 2
 
0.5%
5919494 2
 
0.5%
611 2
 
0.5%
Other values (200) 210
56.1%
2023-12-11T03:19:42.611158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 378
18.6%
0 323
15.9%
3 300
14.8%
191
9.4%
8 168
8.3%
1 162
8.0%
6 148
 
7.3%
4 103
 
5.1%
2 97
 
4.8%
9 81
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1838
90.6%
Space Separator 191
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 378
20.6%
0 323
17.6%
3 300
16.3%
8 168
9.1%
1 162
8.8%
6 148
 
8.1%
4 103
 
5.6%
2 97
 
5.3%
9 81
 
4.4%
7 78
 
4.2%
Space Separator
ValueCountFrequency (%)
191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2029
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 378
18.6%
0 323
15.9%
3 300
14.8%
191
9.4%
8 168
8.3%
1 162
8.0%
6 148
 
7.3%
4 103
 
5.1%
2 97
 
4.8%
9 81
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 378
18.6%
0 323
15.9%
3 300
14.8%
191
9.4%
8 168
8.3%
1 162
8.0%
6 148
 
7.3%
4 103
 
5.1%
2 97
 
4.8%
9 81
 
4.0%

소재지면적
Text

MISSING 

Distinct156
Distinct (%)94.0%
Missing31
Missing (%)15.7%
Memory size1.7 KiB
2023-12-11T03:19:43.129672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1626506
Min length3

Characters and Unicode

Total characters1023
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

Unique149 ?
Unique (%)89.8%

Sample

1st row52.80
2nd row130.20
3rd row16.54
4th row195.50
5th row821.40
ValueCountFrequency (%)
00 5
 
3.0%
270.00 2
 
1.2%
264.00 2
 
1.2%
334.80 2
 
1.2%
132.00 2
 
1.2%
337.50 2
 
1.2%
475.97 2
 
1.2%
4,000.00 1
 
0.6%
354.20 1
 
0.6%
1,217.37 1
 
0.6%
Other values (146) 146
88.0%
2023-12-11T03:19:43.876369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
21.1%
. 166
16.2%
2 88
8.6%
1 76
 
7.4%
3 75
 
7.3%
4 74
 
7.2%
6 68
 
6.6%
7 62
 
6.1%
5 60
 
5.9%
8 54
 
5.3%
Other values (2) 84
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 826
80.7%
Other Punctuation 197
 
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
26.2%
2 88
10.7%
1 76
 
9.2%
3 75
 
9.1%
4 74
 
9.0%
6 68
 
8.2%
7 62
 
7.5%
5 60
 
7.3%
8 54
 
6.5%
9 53
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 166
84.3%
, 31
 
15.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1023
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
21.1%
. 166
16.2%
2 88
8.6%
1 76
 
7.4%
3 75
 
7.3%
4 74
 
7.2%
6 68
 
6.6%
7 62
 
6.1%
5 60
 
5.9%
8 54
 
5.3%
Other values (2) 84
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1023
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
21.1%
. 166
16.2%
2 88
8.6%
1 76
 
7.4%
3 75
 
7.3%
4 74
 
7.2%
6 68
 
6.6%
7 62
 
6.1%
5 60
 
5.9%
8 54
 
5.3%
Other values (2) 84
 
8.2%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)38.5%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean706734.19
Minimum700191
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:44.102390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700191
5-th percentile701864
Q1704190
median704833
Q3711841
95-th percentile711858
Maximum711893
Range11702
Interquartile range (IQR)7651

Descriptive statistics

Standard deviation3880.5455
Coefficient of variation (CV)0.0054908133
Kurtosis-1.4940229
Mean706734.19
Median Absolute Deviation (MAD)1998
Skewness0.41518437
Sum1.3781317 × 108
Variance15058633
MonotonicityNot monotonic
2023-12-11T03:19:44.325852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704801 17
 
8.6%
704833 16
 
8.1%
704190 8
 
4.1%
711855 8
 
4.1%
704900 8
 
4.1%
702800 7
 
3.6%
711842 6
 
3.0%
711841 6
 
3.0%
711891 5
 
2.5%
704901 5
 
2.5%
Other values (65) 109
55.3%
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 1
 
0.5%
711891 5
2.5%
711890 1
 
0.5%
711874 1
 
0.5%
711858 4
2.0%
711856 3
 
1.5%
711855 8
4.1%
711852 5
2.5%
711851 3
 
1.5%

소재지전체주소
Text

Distinct191
Distinct (%)97.4%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2023-12-11T03:19:44.782082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length33
Mean length25.102041
Min length19

Characters and Unicode

Total characters4920
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

Unique186 ?
Unique (%)94.9%

Sample

1st row대구광역시 중구 남산동 0615-0002번지 지상3층
2nd row대구광역시 중구 달성동 0209-0015번지
3rd row대구광역시 중구 종로1가 0040-0002번지 지상8층
4th row대구광역시 중구 시장북로 0026-0001번지 지상 1층
5th row대구광역시 중구 남산동 2114-0010번지
ValueCountFrequency (%)
대구광역시 196
21.2%
달서구 82
 
8.9%
달성군 69
 
7.5%
북구 25
 
2.7%
논공읍 23
 
2.5%
옥포면 21
 
2.3%
월암동 18
 
2.0%
대천동 17
 
1.8%
지상1층 15
 
1.6%
갈산동 13
 
1.4%
Other values (293) 444
48.1%
2023-12-11T03:19:45.460152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
930
18.9%
구 332
 
6.7%
지 239
 
4.9%
1 222
 
4.5%
대 213
 
4.3%
시 199
 
4.0%
역 196
 
4.0%
광 196
 
4.0%
번 196
 
4.0%
달 153
 
3.1%
Other values (117) 2044
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2875
58.4%
Space Separator 930
 
18.9%
Decimal Number 900
 
18.3%
Dash Punctuation 144
 
2.9%
Close Punctuation 25
 
0.5%
Open 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 332
 
11.5%
지 239
 
8.3%
대 213
 
7.4%
시 199
 
6.9%
역 196
 
6.8%
광 196
 
6.8%
번 196
 
6.8%
달 153
 
5.3%
동 152
 
5.3%
서 94
 
3.3%
Other values (96) 905
31.5%
Decimal Number
ValueCountFrequency (%)
1 222
24.7%
2 109
12.1%
0 103
11.4%
3 91
10.1%
6 76
 
8.4%
4 74
 
8.2%
5 63
 
7.0%
7 62
 
6.9%
9 51
 
5.7%
8 49
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
46.7%
B 5
33.3%
C 1
 
6.7%
D 1
 
6.7%
L 1
 
6.7%
Space Separator
ValueCountFrequency (%)
930
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2875
58.4%
Common 2030
41.3%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 332
 
11.5%
지 239
 
8.3%
대 213
 
7.4%
시 199
 
6.9%
역 196
 
6.8%
광 196
 
6.8%
번 196
 
6.8%
달 153
 
5.3%
동 152
 
5.3%
서 94
 
3.3%
Other values (96) 905
31.5%
Common
ValueCountFrequency (%)
930
45.8%
1 222
 
10.9%
- 144
 
7.1%
2 109
 
5.4%
0 103
 
5.1%
3 91
 
4.5%
6 76
 
3.7%
4 74
 
3.6%
5 63
 
3.1%
7 62
 
3.1%
Other values (6) 156
 
7.7%
Latin
ValueCountFrequency (%)
A 7
46.7%
B 5
33.3%
C 1
 
6.7%
D 1
 
6.7%
L 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2875
58.4%
ASCII 2045
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
930
45.5%
1 222
 
10.9%
- 144
 
7.0%
2 109
 
5.3%
0 103
 
5.0%
3 91
 
4.4%
6 76
 
3.7%
4 74
 
3.6%
5 63
 
3.1%
7 62
 
3.0%
Other values (11) 171
 
8.4%
Hangul
ValueCountFrequency (%)
구 332
 
11.5%
지 239
 
8.3%
대 213
 
7.4%
시 199
 
6.9%
역 196
 
6.8%
광 196
 
6.8%
번 196
 
6.8%
달 153
 
5.3%
동 152
 
5.3%
서 94
 
3.3%
Other values (96) 905
31.5%

도로명전체주소
Text

MISSING 

Distinct117
Distinct (%)100.0%
Missing80
Missing (%)40.6%
Memory size1.7 KiB
2023-12-11T03:19:45.951451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length28.042735
Min length20

Characters and Unicode

Total characters3281
Distinct characters141
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

Unique117 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 중앙대로65길 28, 3층 (남산동)
2nd row대구광역시 중구 국채보상로 554-1 (종로1가, 지상8층)
3rd row대구광역시 동구 금강로 186, A동,B동,C동 1층 (금강동)
4th row대구광역시 동구 팔공로 96-8 (지저동)
5th row대구광역시 서구 서대구로 329-14 (비산동)
ValueCountFrequency (%)
대구광역시 117
 
18.0%
달서구 51
 
7.8%
달성군 48
 
7.4%
1층 27
 
4.1%
논공읍 19
 
2.9%
옥포면 13
 
2.0%
북구 11
 
1.7%
월암동 11
 
1.7%
대천동 9
 
1.4%
구지면 7
 
1.1%
Other values (241) 338
51.9%
2023-12-11T03:19:46.658877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
534
 
16.3%
구 195
 
5.9%
대 140
 
4.3%
1 132
 
4.0%
시 121
 
3.7%
광 117
 
3.6%
역 117
 
3.6%
달 110
 
3.4%
서 105
 
3.2%
로 102
 
3.1%
Other values (131) 1608
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1969
60.0%
Space Separator 534
 
16.3%
Decimal Number 495
 
15.1%
Open Punctuation 86
 
2.6%
Close Punctuation 86
 
2.6%
Other Punctuation 61
 
1.9%
Dash Punctuation 28
 
0.9%
Uppercase Letter 17
 
0.5%
Math Symbol 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 195
 
9.9%
대 140
 
7.1%
시 121
 
6.1%
광 117
 
5.9%
역 117
 
5.9%
달 110
 
5.6%
서 105
 
5.3%
로 102
 
5.2%
동 102
 
5.2%
성 94
 
4.8%
Other values (109) 766
38.9%
Decimal Number
ValueCountFrequency (%)
1 132
26.7%
2 69
13.9%
3 58
11.7%
5 50
 
10.1%
6 41
 
8.3%
8 32
 
6.5%
7 32
 
6.5%
4 32
 
6.5%
9 26
 
5.3%
0 23
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
B 2
 
11.8%
D 2
 
11.8%
E 1
 
5.9%
L 1
 
5.9%
Space Separator
ValueCountFrequency (%)
534
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Other Punctuation
ValueCountFrequency (%)
, 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1969
60.0%
Common 1295
39.5%
Latin 17
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 195
 
9.9%
대 140
 
7.1%
시 121
 
6.1%
광 117
 
5.9%
역 117
 
5.9%
달 110
 
5.6%
서 105
 
5.3%
로 102
 
5.2%
동 102
 
5.2%
성 94
 
4.8%
Other values (109) 766
38.9%
Common
ValueCountFrequency (%)
534
41.2%
1 132
 
10.2%
( 86
 
6.6%
) 86
 
6.6%
2 69
 
5.3%
, 61
 
4.7%
3 58
 
4.5%
5 50
 
3.9%
6 41
 
3.2%
8 32
 
2.5%
Other values (6) 146
 
11.3%
Latin
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
B 2
 
11.8%
D 2
 
11.8%
E 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1969
60.0%
ASCII 1312
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
534
40.7%
1 132
 
10.1%
( 86
 
6.6%
) 86
 
6.6%
2 69
 
5.3%
, 61
 
4.6%
3 58
 
4.4%
5 50
 
3.8%
6 41
 
3.1%
8 32
 
2.4%
Other values (12) 163
 
12.4%
Hangul
ValueCountFrequency (%)
구 195
 
9.9%
대 140
 
7.1%
시 121
 
6.1%
광 117
 
5.9%
역 117
 
5.9%
달 110
 
5.6%
서 105
 
5.3%
로 102
 
5.2%
동 102
 
5.2%
성 94
 
4.8%
Other values (109) 766
38.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)53.5%
Missing83
Missing (%)42.1%
Infinite0
Infinite (%)0.0%
Mean42649.939
Minimum41037
Maximum43013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:46.862158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41037
5-th percentile41506.25
Q142703.25
median42721
Q342972
95-th percentile43008
Maximum43013
Range1976
Interquartile range (IQR)268.75

Descriptive statistics

Standard deviation484.50241
Coefficient of variation (CV)0.011359979
Kurtosis2.4090578
Mean42649.939
Median Absolute Deviation (MAD)247
Skewness-1.8861253
Sum4862093
Variance234742.59
MonotonicityNot monotonic
2023-12-11T03:19:47.048081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42718 7
 
3.6%
42719 7
 
3.6%
42721 6
 
3.0%
42968 5
 
2.5%
42972 4
 
2.0%
42976 4
 
2.0%
42982 4
 
2.0%
42970 3
 
1.5%
42701 3
 
1.5%
43008 3
 
1.5%
Other values (51) 68
34.5%
(Missing) 83
42.1%
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 1
0.5%
41510 1
0.5%
41512 1
0.5%
ValueCountFrequency (%)
43013 3
1.5%
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

Distinct183
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:19:47.370677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.8375635
Min length2

Characters and Unicode

Total characters1150
Distinct characters194
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

Unique171 ?
Unique (%)86.8%

Sample

1st row동아피엔비
2nd row명성인쇄사
3rd row카유아티산
4th row오성상사
5th row대양정밀인쇄
ValueCountFrequency (%)
동아피엔비 3
 
1.5%
대호화학산업 3
 
1.5%
대성비닐공업사 2
 
1.0%
주식회사 2
 
1.0%
주)우창케미칼 2
 
1.0%
신오산업 2
 
1.0%
오성그라비아 2
 
1.0%
대붕그라비아 2
 
1.0%
주)동신에스피 2
 
1.0%
대우포장 2
 
1.0%
Other values (180) 183
89.3%
2023-12-11T03:19:47.901633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 66
 
5.7%
산 63
 
5.5%
주 49
 
4.3%
) 48
 
4.2%
( 48
 
4.2%
대 37
 
3.2%
사 37
 
3.2%
성 29
 
2.5%
스 26
 
2.3%
동 26
 
2.3%
Other values (184) 721
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1035
90.0%
Close Punctuation 48
 
4.2%
Open Punctuation 48
 
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
 
6.4%
산 63
 
6.1%
주 49
 
4.7%
대 37
 
3.6%
사 37
 
3.6%
성 29
 
2.8%
스 26
 
2.5%
동 26
 
2.5%
라 23
 
2.2%
이 22
 
2.1%
Other values (174) 657
63.5%
Uppercase Letter
ValueCountFrequency (%)
S 4
44.4%
J 1
 
11.1%
C 1
 
11.1%
E 1
 
11.1%
D 1
 
11.1%
H 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1035
90.0%
Common 106
 
9.2%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 66
 
6.4%
산 63
 
6.1%
주 49
 
4.7%
대 37
 
3.6%
사 37
 
3.6%
성 29
 
2.8%
스 26
 
2.5%
동 26
 
2.5%
라 23
 
2.2%
이 22
 
2.1%
Other values (174) 657
63.5%
Latin
ValueCountFrequency (%)
S 4
44.4%
J 1
 
11.1%
C 1
 
11.1%
E 1
 
11.1%
D 1
 
11.1%
H 1
 
11.1%
Common
ValueCountFrequency (%)
) 48
45.3%
( 48
45.3%
8
 
7.5%
& 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1035
90.0%
ASCII 115
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 66
 
6.4%
산 63
 
6.1%
주 49
 
4.7%
대 37
 
3.6%
사 37
 
3.6%
성 29
 
2.8%
스 26
 
2.5%
동 26
 
2.5%
라 23
 
2.2%
이 22
 
2.1%
Other values (174) 657
63.5%
ASCII
ValueCountFrequency (%)
) 48
41.7%
( 48
41.7%
8
 
7.0%
S 4
 
3.5%
& 2
 
1.7%
J 1
 
0.9%
C 1
 
0.9%
E 1
 
0.9%
D 1
 
0.9%
H 1
 
0.9%

최종수정시점
Real number (ℝ)

Distinct169
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0105017 × 1013
Minimum2.0010822 × 1013
Maximum2.0200619 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:48.088178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010822 × 1013
5-th percentile2.0018295 × 1013
Q12.0040621 × 1013
median2.0110315 × 1013
Q32.0160128 × 1013
95-th percentile2.0193005 × 1013
Maximum2.0200619 × 1013
Range1.8979715 × 1011
Interquartile range (IQR)1.1950719 × 1011

Descriptive statistics

Standard deviation6.5164122 × 1010
Coefficient of variation (CV)0.0032411871
Kurtosis-1.5460401
Mean2.0105017 × 1013
Median Absolute Deviation (MAD)6.0200061 × 1010
Skewness-0.068156472
Sum3.9606883 × 1015
Variance4.2463627 × 1021
MonotonicityNot monotonic
2023-12-11T03:19:48.276144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020523000000 16
 
8.1%
20010822000000 8
 
4.1%
20020903000000 2
 
1.0%
20011015000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20041018000000 2
 
1.0%
20041019000000 2
 
1.0%
20200226171124 1
 
0.5%
20200413164529 1
 
0.5%
Other values (159) 159
80.7%
ValueCountFrequency (%)
20010822000000 8
4.1%
20011015000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20020214000000 1
 
0.5%
20020420000000 1
 
0.5%
20020523000000 16
8.1%
20020615000000 1
 
0.5%
20020903000000 2
 
1.0%
20021016000000 1
 
0.5%
ValueCountFrequency (%)
20200619152212 1
0.5%
20200611112555 1
0.5%
20200519100535 1
0.5%
20200506155606 1
0.5%
20200413164529 1
0.5%
20200311144708 1
0.5%
20200226171124 1
0.5%
20200221134227 1
0.5%
20200120164451 1
0.5%
20200102102616 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
174 
U
23 

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
88.3%
U 23
 
11.7%

Length

2023-12-11T03:19:48.461051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:48.583323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 174
88.3%
u 23
 
11.7%

데이터갱신일자
Date

Distinct28
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2020-06-21 02:40:00
2023-12-11T03:19:48.699547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:19:48.822825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
197 

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 197
100.0%

Length

2023-12-11T03:19:48.996998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:49.123004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 197
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct174
Distinct (%)95.6%
Missing15
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean336022.46
Minimum325886.5
Maximum356719.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:49.252379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325886.5
5-th percentile328251.35
Q1332728.37
median335517.64
Q3337234.61
95-th percentile346444.15
Maximum356719.23
Range30832.738
Interquartile range (IQR)4506.2426

Descriptive statistics

Standard deviation5627.1065
Coefficient of variation (CV)0.016746221
Kurtosis2.1683222
Mean336022.46
Median Absolute Deviation (MAD)2579.2895
Skewness1.1833347
Sum61156088
Variance31664327
MonotonicityNot monotonic
2023-12-11T03:19:49.452918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336397.922682 3
 
1.5%
331839.79406 2
 
1.0%
333135.698427 2
 
1.0%
331841.584525 2
 
1.0%
328209.453202 2
 
1.0%
345971.954573 2
 
1.0%
335156.423755 2
 
1.0%
335790.447945 1
 
0.5%
328252.402614 1
 
0.5%
332722.497387 1
 
0.5%
Other values (164) 164
83.2%
(Missing) 15
 
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%
327960.00471 1
0.5%
328209.453202 2
1.0%
328251.2996 1
0.5%
328252.402614 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 

Distinct174
Distinct (%)95.6%
Missing15
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean258853.08
Minimum238106.71
Maximum272526.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:49.687020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238106.71
5-th percentile244847.28
Q1255641.54
median260162.7
Q3262691.94
95-th percentile268210.26
Maximum272526.51
Range34419.797
Interquartile range (IQR)7050.403

Descriptive statistics

Standard deviation6853.3104
Coefficient of variation (CV)0.026475676
Kurtosis1.2293996
Mean258853.08
Median Absolute Deviation (MAD)3572.5876
Skewness-1.0174069
Sum47111261
Variance46967864
MonotonicityNot monotonic
2023-12-11T03:19:49.906327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
260400.384173 3
 
1.5%
249314.473196 2
 
1.0%
255625.666969 2
 
1.0%
255452.921933 2
 
1.0%
251079.280489 2
 
1.0%
269410.738999 2
 
1.0%
259818.122046 2
 
1.0%
260163.154002 1
 
0.5%
238106.714053 1
 
0.5%
250114.085686 1
 
0.5%
Other values (164) 164
83.2%
(Missing) 15
 
7.6%
ValueCountFrequency (%)
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%
244680.842404 1
0.5%
ValueCountFrequency (%)
272526.511063 1
0.5%
269502.747796 1
0.5%
269411.257496 1
0.5%
269410.738999 2
1.0%
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%
268096.126656 1
0.5%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
197 

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 197
100.0%

Length

2023-12-11T03:19:50.092610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:50.220161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 197
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
125 
상수도전용
71 
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.3654822
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
63.5%
상수도전용 71
36.0%
간이상수도 1
 
0.5%

Length

2023-12-11T03:19:50.368717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:50.536337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
63.5%
상수도전용 71
36.0%
간이상수도 1
 
0.5%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
161 
<NA>
32 
1
 
2
4
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.4873096
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 161
81.7%
<NA> 32
 
16.2%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

Length

2023-12-11T03:19:50.703489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:50.895799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 161
81.7%
na 32
 
16.2%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.6%
Missing32
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean0.26666667
Minimum0
Maximum15
Zeros149
Zeros (%)75.6%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:51.057417image/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 deviation1.4530596
Coefficient of variation (CV)5.4489734
Kurtosis76.707149
Mean0.26666667
Median Absolute Deviation (MAD)0
Skewness8.3852328
Sum44
Variance2.1113821
MonotonicityNot monotonic
2023-12-11T03:19:51.208412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 149
75.6%
1 11
 
5.6%
3 2
 
1.0%
10 1
 
0.5%
2 1
 
0.5%
15 1
 
0.5%
(Missing) 32
 
16.2%
ValueCountFrequency (%)
0 149
75.6%
1 11
 
5.6%
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 11
 
5.6%
0 149
75.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
158 
<NA>
32 
1
 
5
2
 
1
6
 
1

Length

Max length4
Median length1
Mean length1.4873096
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 158
80.2%
<NA> 32
 
16.2%
1 5
 
2.5%
2 1
 
0.5%
6 1
 
0.5%

Length

2023-12-11T03:19:51.421469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:51.608792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 158
80.2%
na 32
 
16.2%
1 5
 
2.5%
2 1
 
0.5%
6 1
 
0.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.7%
Missing32
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean1.2
Minimum0
Maximum45
Zeros138
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:51.766746image/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 deviation5.2268071
Coefficient of variation (CV)4.3556726
Kurtosis59.541318
Mean1.2
Median Absolute Deviation (MAD)0
Skewness7.3924528
Sum198
Variance27.319512
MonotonicityNot monotonic
2023-12-11T03:19:51.920237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 138
70.1%
2 7
 
3.6%
4 5
 
2.5%
3 3
 
1.5%
1 2
 
1.0%
5 2
 
1.0%
9 2
 
1.0%
7 2
 
1.0%
45 2
 
1.0%
11 1
 
0.5%
(Missing) 32
 
16.2%
ValueCountFrequency (%)
0 138
70.1%
1 2
 
1.0%
2 7
 
3.6%
3 3
 
1.5%
4 5
 
2.5%
5 2
 
1.0%
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 2
 
1.0%
4 5
2.5%
3 3
1.5%
2 7
3.6%
1 2
 
1.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
147 
임대
25 
자가
25 

Length

Max length4
Median length4
Mean length3.4923858
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
74.6%
임대 25
 
12.7%
자가 25
 
12.7%

Length

2023-12-11T03:19:52.135072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:52.307369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
74.6%
임대 25
 
12.7%
자가 25
 
12.7%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
195 
30000000
 
1
0
 
1

Length

Max length8
Median length4
Mean length4.0050761
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> 195
99.0%
30000000 1
 
0.5%
0 1
 
0.5%

Length

2023-12-11T03:19:52.472147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:52.637542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 195
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>
195 
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> 195
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

Length

2023-12-11T03:19:52.831484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:19:53.389146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 195
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size329.0 B
False
197 
ValueCountFrequency (%)
False 197
100.0%
2023-12-11T03:19:53.521533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2652792
Minimum0
Maximum907.75
Zeros183
Zeros (%)92.9%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:19:53.665504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10.52
Maximum907.75
Range907.75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation65.032314
Coefficient of variation (CV)10.379795
Kurtosis191.20658
Mean6.2652792
Median Absolute Deviation (MAD)0
Skewness13.736214
Sum1234.26
Variance4229.2019
MonotonicityNot monotonic
2023-12-11T03:19:53.848585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 183
92.9%
10.0 1
 
0.5%
64.0 1
 
0.5%
3.0 1
 
0.5%
19.5 1
 
0.5%
19.6 1
 
0.5%
9.9 1
 
0.5%
3.35 1
 
0.5%
45.0 1
 
0.5%
41.0 1
 
0.5%
Other values (5) 5
 
2.5%
ValueCountFrequency (%)
0.0 183
92.9%
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 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01용기·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>
12용기·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>
23용기·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>
34용기·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>
45용기·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>
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_P34200003420000-118-2009-0000220091125<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>
78용기·포장지제조업07_22_15_P34200003420000-118-2002-0000120021220<NA>3폐업2폐업20060529<NA><NA><NA>053 981944494.40701807대구광역시 동구 불로동 1032-15번지<NA><NA>제일산업20040621000000I2018-08-31 23:59:59.0용기.포장지제조업347291.028197267487.611868용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
89용기·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>
910용기·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>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
187188용기·포장지제조업07_22_15_P34800003480000-118-2014-0000120140627<NA>3폐업2폐업20191203<NA><NA><NA>053 637 9466240.00711851대구광역시 달성군 논공읍 금포리 469-1번지대구광역시 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>
188189용기·포장지제조업07_22_15_P34800003480000-118-2012-0000120120822<NA>3폐업2폐업20120831<NA><NA><NA>585 5456<NA>711813대구광역시 달성군 다사읍 서재리 396-1번지대구광역시 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>
189190용기·포장지제조업07_22_15_P34800003480000-118-2011-0000320110803<NA>3폐업2폐업20110831<NA><NA><NA>053 6168800<NA>711844대구광역시 달성군 옥포면 반송리 504-1번지<NA><NA>코벤트기술연구소20110803113827I2018-08-31 23:59:59.0용기.포장지제조업335639.362693251187.051976용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
190191용기·포장지제조업07_22_15_P34800003480000-118-2010-0000320101028<NA>3폐업2폐업20120206<NA><NA><NA>053 583 8764472.00711821대구광역시 달성군 하빈면 하산리 133-1번지<NA><NA>(주)오투페이퍼20101104101923I2018-08-31 23:59:59.0용기.포장지제조업327642.468368267180.710022용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
191192용기·포장지제조업07_22_15_P34800003480000-118-2010-0000220101025<NA>3폐업2폐업20151229<NA><NA><NA>053 614 6943278.40711841대구광역시 달성군 옥포면 간경리 730번지<NA><NA>건영산업20130104152432I2018-08-31 23:59:59.0용기.포장지제조업332765.531939256138.240182용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
192193용기·포장지제조업07_22_15_P34800003480000-118-2010-0000120100209<NA>3폐업2폐업20120523<NA><NA><NA>053 635 4560399.78711832대구광역시 달성군 화원읍 명곡리 206-4번지<NA><NA>신오산업20100304171806I2018-08-31 23:59:59.0용기.포장지제조업334610.925422256612.715185용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
193194용기·포장지제조업07_22_15_P34800003480000-118-2009-0000320090831<NA>3폐업2폐업20120321<NA><NA><NA>053 581 0061440.40711821대구광역시 달성군 하빈면 하산리 509-3번지<NA><NA>(주)월드글라스20090914090218I2018-08-31 23:59:59.0용기.포장지제조업327262.266542266143.643429용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
194195용기·포장지제조업07_22_15_P34800003480000-118-2015-0000320150519<NA>3폐업2폐업20190308<NA><NA><NA>053 643 0101315.35711858대구광역시 달성군 논공읍 상리 660번지 C동대구광역시 달성군 논공읍 걸미1길 5, C동 1층42976영일산업20190308135701U2019-03-12 02:40:00.0용기.포장지제조업328209.453202251079.280489용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N35.35<NA><NA><NA>
195196용기·포장지제조업07_22_15_P34800003480000-118-1989-0000119891207<NA>3폐업2폐업20050119<NA><NA><NA>053 6154110<NA>711852대구광역시 달성군 논공읍 북리 213-16번지<NA><NA>(주)뉴대화20010822000000I2018-08-31 23:59:59.0용기.포장지제조업332045.070675249279.214233용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
196197용기·포장지제조업07_22_15_P34800003480000-118-2003-0000120030121<NA>3폐업2폐업20120306<NA><NA><NA>053 6410417<NA>711831대구광역시 달성군 화원읍 구라리 1645-4번지<NA><NA>명강화학20030121000000I2018-08-31 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>