Overview

Dataset statistics

Number of variables47
Number of observations202
Missing cells2816
Missing cells (%)29.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory80.2 KiB
Average record size in memory406.7 B

Variable types

Numeric12
Categorical16
Text6
Unsupported12
Boolean1

Dataset

Description6270000_대구광역시_07_22_15_P_용기·포장지제조업_3월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000088932&dataSetDetailId=DDI_0000088962&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신일자 is highly imbalanced (71.8%)Imbalance
본사종업원수 is highly imbalanced (63.8%)Imbalance
공장판매직종업원수 is highly imbalanced (60.2%)Imbalance
보증액 is highly imbalanced (94.3%)Imbalance
월세액 is highly imbalanced (94.3%)Imbalance
인허가취소일자 has 202 (100.0%) missing valuesMissing
폐업일자 has 75 (37.1%) missing valuesMissing
휴업시작일자 has 202 (100.0%) missing valuesMissing
휴업종료일자 has 202 (100.0%) missing valuesMissing
재개업일자 has 202 (100.0%) missing valuesMissing
소재지전화 has 15 (7.4%) missing valuesMissing
소재지면적 has 33 (16.3%) missing valuesMissing
소재지우편번호 has 3 (1.5%) missing valuesMissing
도로명전체주소 has 80 (39.6%) missing valuesMissing
도로명우편번호 has 83 (41.1%) missing valuesMissing
좌표정보(X) has 15 (7.4%) missing valuesMissing
좌표정보(Y) has 15 (7.4%) missing valuesMissing
남성종사자수 has 202 (100.0%) missing valuesMissing
여성종사자수 has 202 (100.0%) missing valuesMissing
영업장주변구분명 has 202 (100.0%) missing valuesMissing
등급구분명 has 202 (100.0%) missing valuesMissing
총종업원수 has 202 (100.0%) missing valuesMissing
공장사무직종업원수 has 36 (17.8%) missing valuesMissing
공장생산직종업원수 has 36 (17.8%) missing valuesMissing
전통업소지정번호 has 202 (100.0%) missing valuesMissing
전통업소주된음식 has 202 (100.0%) missing valuesMissing
홈페이지 has 202 (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 (73.8%) zerosZeros
공장생산직종업원수 has 138 (68.3%) zerosZeros
시설총규모 has 188 (93.1%) zerosZeros

Reproduction

Analysis started2024-04-17 23:03:48.675472
Analysis finished2024-04-17 23:03:49.206614
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct202
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.5
Minimum1
Maximum202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:49.853723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.05
Q151.25
median101.5
Q3151.75
95-th percentile191.95
Maximum202
Range201
Interquartile range (IQR)100.5

Descriptive statistics

Standard deviation58.456537
Coefficient of variation (CV)0.57592647
Kurtosis-1.2
Mean101.5
Median Absolute Deviation (MAD)50.5
Skewness0
Sum20503
Variance3417.1667
MonotonicityStrictly increasing
2024-04-18T08:03:49.998137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
140 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
Other values (192) 192
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기·포장지제조업
202 

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 202
100.0%

Length

2024-04-18T08:03:50.151271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:50.243302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기·포장지제조업 202
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
07_22_15_P
202 

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 202
100.0%

Length

2024-04-18T08:03:50.331525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:50.434490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_15_p 202
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3466584.2
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:50.515982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420500
Q13470000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation17240.336
Coefficient of variation (CV)0.0049732923
Kurtosis2.5478058
Mean3466584.2
Median Absolute Deviation (MAD)10000
Skewness-1.7598974
Sum7.0025 × 108
Variance2.972292 × 108
MonotonicityIncreasing
2024-04-18T08:03:50.628431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3470000 83
41.1%
3480000 73
36.1%
3450000 26
 
12.9%
3430000 7
 
3.5%
3420000 6
 
3.0%
3410000 5
 
2.5%
3460000 2
 
1.0%
ValueCountFrequency (%)
3410000 5
 
2.5%
3420000 6
 
3.0%
3430000 7
 
3.5%
3450000 26
 
12.9%
3460000 2
 
1.0%
3470000 83
41.1%
3480000 73
36.1%
ValueCountFrequency (%)
3480000 73
36.1%
3470000 83
41.1%
3460000 2
 
1.0%
3450000 26
 
12.9%
3430000 7
 
3.5%
3420000 6
 
3.0%
3410000 5
 
2.5%

관리번호
Text

UNIQUE 

Distinct202
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T08:03:50.818159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4444
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

Unique202 ?
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%
3480000-118-2001-00002 1
 
0.5%
3470000-118-2001-00001 1
 
0.5%
3480000-118-1996-00001 1
 
0.5%
3470000-118-2006-00004 1
 
0.5%
3480000-118-1997-00001 1
 
0.5%
3480000-118-1998-00001 1
 
0.5%
3480000-118-1999-00001 1
 
0.5%
3480000-118-2000-00001 1
 
0.5%
3480000-118-2000-00002 1
 
0.5%
Other values (192) 192
95.0%
2024-04-18T08:03:51.147410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1921
43.2%
- 606
 
13.6%
1 603
 
13.6%
8 305
 
6.9%
3 259
 
5.8%
2 254
 
5.7%
4 236
 
5.3%
7 109
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3838
86.4%
Dash Punctuation 606
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1921
50.1%
1 603
 
15.7%
8 305
 
7.9%
3 259
 
6.7%
2 254
 
6.6%
4 236
 
6.1%
7 109
 
2.8%
9 74
 
1.9%
5 55
 
1.4%
6 22
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 606
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1921
43.2%
- 606
 
13.6%
1 603
 
13.6%
8 305
 
6.9%
3 259
 
5.8%
2 254
 
5.7%
4 236
 
5.3%
7 109
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1921
43.2%
- 606
 
13.6%
1 603
 
13.6%
8 305
 
6.9%
3 259
 
5.8%
2 254
 
5.7%
4 236
 
5.3%
7 109
 
2.5%
9 74
 
1.7%
5 55
 
1.2%

인허가일자
Real number (ℝ)

Distinct194
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20055493
Minimum19870227
Maximum20210317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:51.295014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870227
5-th percentile19950406
Q120011005
median20050362
Q320100655
95-th percentile20180710
Maximum20210317
Range340090
Interquartile range (IQR)89650

Descriptive statistics

Standard deviation70907.253
Coefficient of variation (CV)0.0035355528
Kurtosis-0.011772105
Mean20055493
Median Absolute Deviation (MAD)40147
Skewness-0.0056567178
Sum4.0512095 × 109
Variance5.0278386 × 109
MonotonicityNot monotonic
2024-04-18T08:03:51.429778image/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%
20070807 2
 
1.0%
20110803 2
 
1.0%
19870227 2
 
1.0%
19880208 1
 
0.5%
20020919 1
 
0.5%
19971210 1
 
0.5%
19981202 1
 
0.5%
Other values (184) 184
91.1%
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 (%)
20210317 1
0.5%
20210312 1
0.5%
20201116 1
0.5%
20200924 1
0.5%
20200611 1
0.5%
20200506 1
0.5%
20200401 1
0.5%
20190412 1
0.5%
20190226 1
0.5%
20181031 1
0.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
127 
1
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 127
62.9%
1 75
37.1%

Length

2024-04-18T08:03:51.549659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:51.646486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 127
62.9%
1 75
37.1%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
127 
영업/정상
75 

Length

Max length5
Median length2
Mean length3.1138614
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 127
62.9%
영업/정상 75
37.1%

Length

2024-04-18T08:03:51.746044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:51.846429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 127
62.9%
영업/정상 75
37.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
127 
1
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 127
62.9%
1 75
37.1%

Length

2024-04-18T08:03:51.937018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:52.042064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 127
62.9%
1 75
37.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
127 
영업
75 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 127
62.9%
영업 75
37.1%

Length

2024-04-18T08:03:52.138638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:52.234838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 127
62.9%
영업 75
37.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)94.5%
Missing75
Missing (%)37.1%
Infinite0
Infinite (%)0.0%
Mean20106948
Minimum20011030
Maximum20210325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:52.345823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011030
5-th percentile20030731
Q120060572
median20110120
Q320160114
95-th percentile20191204
Maximum20210325
Range199295
Interquartile range (IQR)99541

Descriptive statistics

Standard deviation53540.408
Coefficient of variation (CV)0.0026627815
Kurtosis-1.17551
Mean20106948
Median Absolute Deviation (MAD)49618
Skewness0.18753518
Sum2.5535824 × 109
Variance2.8665753 × 109
MonotonicityNot monotonic
2024-04-18T08:03:52.499929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120306 4
 
2.0%
20151229 2
 
1.0%
20050831 2
 
1.0%
20061208 2
 
1.0%
20110524 2
 
1.0%
20160428 1
 
0.5%
20131023 1
 
0.5%
20050727 1
 
0.5%
20170206 1
 
0.5%
20021203 1
 
0.5%
Other values (110) 110
54.5%
(Missing) 75
37.1%
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 (%)
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%
20190524 1
0.5%
20190308 1
0.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

소재지전화
Text

MISSING 

Distinct178
Distinct (%)95.2%
Missing15
Missing (%)7.4%
Memory size1.7 KiB
2024-04-18T08:03:52.818182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.037433
Min length7

Characters and Unicode

Total characters2064
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

Unique170 ?
Unique (%)90.9%

Sample

1st row053 5857788
2nd row053 2525022
3rd row053 256 3375
4th row053 5548531
5th row053 9642513
ValueCountFrequency (%)
053 140
36.6%
581 5
 
1.3%
5857788 3
 
0.8%
585 3
 
0.8%
583 3
 
0.8%
593 3
 
0.8%
615 3
 
0.8%
05305855400 2
 
0.5%
637 2
 
0.5%
611 2
 
0.5%
Other values (205) 216
56.5%
2024-04-18T08:03:53.249582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 382
18.5%
0 327
15.8%
3 305
14.8%
196
9.5%
8 170
8.2%
1 167
8.1%
6 151
 
7.3%
4 106
 
5.1%
2 100
 
4.8%
9 81
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1868
90.5%
Space Separator 196
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 382
20.4%
0 327
17.5%
3 305
16.3%
8 170
9.1%
1 167
8.9%
6 151
 
8.1%
4 106
 
5.7%
2 100
 
5.4%
9 81
 
4.3%
7 79
 
4.2%
Space Separator
ValueCountFrequency (%)
196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2064
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 382
18.5%
0 327
15.8%
3 305
14.8%
196
9.5%
8 170
8.2%
1 167
8.1%
6 151
 
7.3%
4 106
 
5.1%
2 100
 
4.8%
9 81
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 382
18.5%
0 327
15.8%
3 305
14.8%
196
9.5%
8 170
8.2%
1 167
8.1%
6 151
 
7.3%
4 106
 
5.1%
2 100
 
4.8%
9 81
 
3.9%

소재지면적
Text

MISSING 

Distinct158
Distinct (%)93.5%
Missing33
Missing (%)16.3%
Memory size1.7 KiB
2024-04-18T08:03:53.553430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1656805
Min length3

Characters and Unicode

Total characters1042
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)89.3%

Sample

1st row52.80
2nd row195.50
3rd row16.54
4th row130.20
5th row194.50
ValueCountFrequency (%)
00 6
 
3.6%
132.00 2
 
1.2%
334.80 2
 
1.2%
264.00 2
 
1.2%
337.50 2
 
1.2%
475.97 2
 
1.2%
270.00 2
 
1.2%
244.80 1
 
0.6%
574.80 1
 
0.6%
226.90 1
 
0.6%
Other values (148) 148
87.6%
2024-04-18T08:03:54.015129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 220
21.1%
. 169
16.2%
2 90
8.6%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 840
80.6%
Other Punctuation 202
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 220
26.2%
2 90
10.7%
1 78
 
9.3%
4 76
 
9.0%
3 75
 
8.9%
6 72
 
8.6%
7 62
 
7.4%
5 60
 
7.1%
8 54
 
6.4%
9 53
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 169
83.7%
, 33
 
16.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1042
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 220
21.1%
. 169
16.2%
2 90
8.6%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 220
21.1%
. 169
16.2%
2 90
8.6%
1 78
 
7.5%
4 76
 
7.3%
3 75
 
7.2%
6 72
 
6.9%
7 62
 
6.0%
5 60
 
5.8%
8 54
 
5.2%
Other values (2) 86
 
8.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)37.7%
Missing3
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean706756.37
Minimum700191
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:54.149840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700191
5-th percentile701868
Q1704190
median704833
Q3711841
95-th percentile711859.6
Maximum711893
Range11702
Interquartile range (IQR)7651

Descriptive statistics

Standard deviation3888.1771
Coefficient of variation (CV)0.0055014391
Kurtosis-1.5093199
Mean706756.37
Median Absolute Deviation (MAD)2016
Skewness0.40470509
Sum1.4064452 × 108
Variance15117921
MonotonicityNot monotonic
2024-04-18T08:03:54.280010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704801 18
 
8.9%
704833 16
 
7.9%
702800 8
 
4.0%
704190 8
 
4.0%
704900 8
 
4.0%
711855 8
 
4.0%
711841 6
 
3.0%
711842 6
 
3.0%
704901 5
 
2.5%
704830 5
 
2.5%
Other values (65) 111
55.0%
ValueCountFrequency (%)
700191 1
0.5%
700290 1
0.5%
700804 1
0.5%
700832 1
0.5%
700841 1
0.5%
701260 1
0.5%
701330 1
0.5%
701807 1
0.5%
701848 1
0.5%
701850 1
0.5%
ValueCountFrequency (%)
711893 1
 
0.5%
711892 2
 
1.0%
711891 5
2.5%
711890 1
 
0.5%
711874 1
 
0.5%
711858 5
2.5%
711856 3
 
1.5%
711855 8
4.0%
711852 5
2.5%
711851 3
 
1.5%

소재지전체주소
Text

Distinct197
Distinct (%)98.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2024-04-18T08:03:54.568306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length33
Mean length25.049751
Min length19

Characters and Unicode

Total characters5035
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

Unique193 ?
Unique (%)96.0%

Sample

1st row대구광역시 중구 남산동 0615-0002번지 지상3층
2nd row대구광역시 중구 남산동 2114-0010번지
3rd row대구광역시 중구 시장북로 0026-0001번지 지상 1층
4th row대구광역시 중구 종로1가 0040-0002번지 지상8층
5th row대구광역시 중구 달성동 0209-0015번지
ValueCountFrequency (%)
대구광역시 201
21.2%
달서구 83
 
8.7%
달성군 72
 
7.6%
북구 26
 
2.7%
논공읍 24
 
2.5%
옥포면 21
 
2.2%
대천동 18
 
1.9%
월암동 18
 
1.9%
지상1층 15
 
1.6%
본리리 14
 
1.5%
Other values (300) 458
48.2%
2024-04-18T08:03:55.008496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
957
19.0%
구 340
 
6.8%
지 238
 
4.7%
1 228
 
4.5%
대 219
 
4.3%
시 204
 
4.1%
광 201
 
4.0%
역 201
 
4.0%
번 194
 
3.9%
달 157
 
3.1%
Other values (117) 2096
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2937
58.3%
Space Separator 957
 
19.0%
Decimal Number 923
 
18.3%
Dash Punctuation 147
 
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 340
 
11.6%
지 238
 
8.1%
대 219
 
7.5%
시 204
 
6.9%
광 201
 
6.8%
역 201
 
6.8%
번 194
 
6.6%
달 157
 
5.3%
동 155
 
5.3%
서 95
 
3.2%
Other values (96) 933
31.8%
Decimal Number
ValueCountFrequency (%)
1 228
24.7%
2 110
11.9%
0 104
11.3%
3 93
10.1%
6 77
 
8.3%
4 75
 
8.1%
5 65
 
7.0%
7 64
 
6.9%
9 54
 
5.9%
8 53
 
5.7%
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 (%)
957
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
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 2937
58.3%
Common 2083
41.4%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 340
 
11.6%
지 238
 
8.1%
대 219
 
7.5%
시 204
 
6.9%
광 201
 
6.8%
역 201
 
6.8%
번 194
 
6.6%
달 157
 
5.3%
동 155
 
5.3%
서 95
 
3.2%
Other values (96) 933
31.8%
Common
ValueCountFrequency (%)
957
45.9%
1 228
 
10.9%
- 147
 
7.1%
2 110
 
5.3%
0 104
 
5.0%
3 93
 
4.5%
6 77
 
3.7%
4 75
 
3.6%
5 65
 
3.1%
7 64
 
3.1%
Other values (6) 163
 
7.8%
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 2937
58.3%
ASCII 2098
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
957
45.6%
1 228
 
10.9%
- 147
 
7.0%
2 110
 
5.2%
0 104
 
5.0%
3 93
 
4.4%
6 77
 
3.7%
4 75
 
3.6%
5 65
 
3.1%
7 64
 
3.1%
Other values (11) 178
 
8.5%
Hangul
ValueCountFrequency (%)
구 340
 
11.6%
지 238
 
8.1%
대 219
 
7.5%
시 204
 
6.9%
광 201
 
6.8%
역 201
 
6.8%
번 194
 
6.6%
달 157
 
5.3%
동 155
 
5.3%
서 95
 
3.2%
Other values (96) 933
31.8%

도로명전체주소
Text

MISSING 

Distinct122
Distinct (%)100.0%
Missing80
Missing (%)39.6%
Memory size1.7 KiB
2024-04-18T08:03:55.336724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length28.02459
Min length20

Characters and Unicode

Total characters3419
Distinct characters142
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
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 122
 
17.9%
달서구 52
 
7.6%
달성군 51
 
7.5%
1층 31
 
4.6%
논공읍 20
 
2.9%
옥포면 13
 
1.9%
북구 12
 
1.8%
월암동 11
 
1.6%
대천동 10
 
1.5%
구지면 8
 
1.2%
Other values (247) 351
51.5%
2024-04-18T08:03:55.758728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
559
 
16.3%
구 203
 
5.9%
대 146
 
4.3%
1 138
 
4.0%
시 126
 
3.7%
광 122
 
3.6%
역 122
 
3.6%
달 115
 
3.4%
서 107
 
3.1%
로 106
 
3.1%
Other values (132) 1675
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2048
59.9%
Space Separator 559
 
16.3%
Decimal Number 519
 
15.2%
Open Punctuation 88
 
2.6%
Close Punctuation 88
 
2.6%
Other Punctuation 65
 
1.9%
Dash Punctuation 30
 
0.9%
Uppercase Letter 17
 
0.5%
Math Symbol 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 203
 
9.9%
대 146
 
7.1%
시 126
 
6.2%
광 122
 
6.0%
역 122
 
6.0%
달 115
 
5.6%
서 107
 
5.2%
로 106
 
5.2%
동 105
 
5.1%
성 99
 
4.8%
Other values (110) 797
38.9%
Decimal Number
ValueCountFrequency (%)
1 138
26.6%
2 74
14.3%
3 60
11.6%
5 52
 
10.0%
6 43
 
8.3%
7 36
 
6.9%
4 33
 
6.4%
8 32
 
6.2%
9 27
 
5.2%
0 24
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
D 2
 
11.8%
B 2
 
11.8%
L 1
 
5.9%
E 1
 
5.9%
Space Separator
ValueCountFrequency (%)
559
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2048
59.9%
Common 1354
39.6%
Latin 17
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 203
 
9.9%
대 146
 
7.1%
시 126
 
6.2%
광 122
 
6.0%
역 122
 
6.0%
달 115
 
5.6%
서 107
 
5.2%
로 106
 
5.2%
동 105
 
5.1%
성 99
 
4.8%
Other values (110) 797
38.9%
Common
ValueCountFrequency (%)
559
41.3%
1 138
 
10.2%
( 88
 
6.5%
) 88
 
6.5%
2 74
 
5.5%
, 65
 
4.8%
3 60
 
4.4%
5 52
 
3.8%
6 43
 
3.2%
7 36
 
2.7%
Other values (6) 151
 
11.2%
Latin
ValueCountFrequency (%)
A 8
47.1%
C 3
 
17.6%
D 2
 
11.8%
B 2
 
11.8%
L 1
 
5.9%
E 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2048
59.9%
ASCII 1371
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
559
40.8%
1 138
 
10.1%
( 88
 
6.4%
) 88
 
6.4%
2 74
 
5.4%
, 65
 
4.7%
3 60
 
4.4%
5 52
 
3.8%
6 43
 
3.1%
7 36
 
2.6%
Other values (12) 168
 
12.3%
Hangul
ValueCountFrequency (%)
구 203
 
9.9%
대 146
 
7.1%
시 126
 
6.2%
광 122
 
6.0%
역 122
 
6.0%
달 115
 
5.6%
서 107
 
5.2%
로 106
 
5.2%
동 105
 
5.1%
성 99
 
4.8%
Other values (110) 797
38.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)51.3%
Missing83
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean42649.412
Minimum41037
Maximum43013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:55.898597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41037
5-th percentile41507.5
Q142703.5
median42721
Q342973
95-th percentile43008
Maximum43013
Range1976
Interquartile range (IQR)269.5

Descriptive statistics

Standard deviation488.62449
Coefficient of variation (CV)0.01145677
Kurtosis2.2562191
Mean42649.412
Median Absolute Deviation (MAD)247
Skewness-1.8574572
Sum5075280
Variance238753.89
MonotonicityNot monotonic
2024-04-18T08:03:56.043955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42719 8
 
4.0%
42718 7
 
3.5%
42721 6
 
3.0%
42968 5
 
2.5%
42976 5
 
2.5%
42970 4
 
2.0%
42982 4
 
2.0%
43013 4
 
2.0%
42972 4
 
2.0%
42983 3
 
1.5%
Other values (51) 69
34.2%
(Missing) 83
41.1%
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 2
1.0%
41510 1
0.5%
41512 1
0.5%
ValueCountFrequency (%)
43013 4
2.0%
43011 1
 
0.5%
43008 3
1.5%
42993 1
 
0.5%
42985 1
 
0.5%
42983 3
1.5%
42982 4
2.0%
42981 2
 
1.0%
42977 3
1.5%
42976 5
2.5%

사업장명
Text

Distinct187
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T08:03:56.258644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.8415842
Min length2

Characters and Unicode

Total characters1180
Distinct characters195
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)86.1%

Sample

1st row동아피엔비
2nd row대양정밀인쇄
3rd row오성상사
4th row카유아티산
5th row명성인쇄사
ValueCountFrequency (%)
동아피엔비 3
 
1.4%
대호화학산업 3
 
1.4%
신오산업 2
 
1.0%
대붕그라비아 2
 
1.0%
주식회사 2
 
1.0%
주)동신에스피 2
 
1.0%
대우포장 2
 
1.0%
대성비닐공업사 2
 
1.0%
오성그라비아 2
 
1.0%
경북인쇄포장 2
 
1.0%
Other values (184) 188
89.5%
2024-04-18T08:03:56.599377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 66
 
5.6%
산 63
 
5.3%
주 51
 
4.3%
) 50
 
4.2%
( 50
 
4.2%
대 38
 
3.2%
사 37
 
3.1%
성 30
 
2.5%
스 29
 
2.5%
동 26
 
2.2%
Other values (185) 740
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1061
89.9%
Close Punctuation 50
 
4.2%
Open Punctuation 50
 
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
 
6.2%
산 63
 
5.9%
주 51
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.8%
스 29
 
2.7%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 674
63.5%
Uppercase Letter
ValueCountFrequency (%)
S 4
44.4%
D 1
 
11.1%
E 1
 
11.1%
C 1
 
11.1%
H 1
 
11.1%
J 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1061
89.9%
Common 110
 
9.3%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 66
 
6.2%
산 63
 
5.9%
주 51
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.8%
스 29
 
2.7%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 674
63.5%
Latin
ValueCountFrequency (%)
S 4
44.4%
D 1
 
11.1%
E 1
 
11.1%
C 1
 
11.1%
H 1
 
11.1%
J 1
 
11.1%
Common
ValueCountFrequency (%)
) 50
45.5%
( 50
45.5%
8
 
7.3%
& 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1061
89.9%
ASCII 119
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 66
 
6.2%
산 63
 
5.9%
주 51
 
4.8%
대 38
 
3.6%
사 37
 
3.5%
성 30
 
2.8%
스 29
 
2.7%
동 26
 
2.5%
라 24
 
2.3%
비 23
 
2.2%
Other values (175) 674
63.5%
ASCII
ValueCountFrequency (%)
) 50
42.0%
( 50
42.0%
8
 
6.7%
S 4
 
3.4%
& 2
 
1.7%
D 1
 
0.8%
E 1
 
0.8%
C 1
 
0.8%
H 1
 
0.8%
J 1
 
0.8%

최종수정시점
Real number (ℝ)

Distinct174
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0107539 × 1013
Minimum2.0010822 × 1013
Maximum2.0210326 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:56.726139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010822 × 1013
5-th percentile2.0020115 × 1013
Q12.0040702 × 1013
median2.011042 × 1013
Q32.0160314 × 1013
95-th percentile2.0200408 × 1013
Maximum2.0210326 × 1013
Range1.995041 × 1011
Interquartile range (IQR)1.1961239 × 1011

Descriptive statistics

Standard deviation6.6279647 × 1010
Coefficient of variation (CV)0.0032962586
Kurtosis-1.5302596
Mean2.0107539 × 1013
Median Absolute Deviation (MAD)6.0552576 × 1010
Skewness-0.086786362
Sum4.0617229 × 1015
Variance4.3929917 × 1021
MonotonicityNot monotonic
2024-04-18T08:03:56.860511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020523000000 16
 
7.9%
20010822000000 8
 
4.0%
20041019000000 2
 
1.0%
20011015000000 2
 
1.0%
20041018000000 2
 
1.0%
20020903000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20200619152212 1
 
0.5%
20191125153256 1
 
0.5%
Other values (164) 164
81.2%
ValueCountFrequency (%)
20010822000000 8
4.0%
20011015000000 2
 
1.0%
20020115000000 2
 
1.0%
20020124000000 2
 
1.0%
20020214000000 1
 
0.5%
20020420000000 1
 
0.5%
20020523000000 16
7.9%
20020615000000 1
 
0.5%
20020903000000 2
 
1.0%
20021016000000 1
 
0.5%
ValueCountFrequency (%)
20210326095221 1
0.5%
20210318113410 1
0.5%
20210226130211 1
0.5%
20201215145501 1
0.5%
20201127153200 1
0.5%
20201116160203 1
0.5%
20200924120545 1
0.5%
20200619152212 1
0.5%
20200519100535 1
0.5%
20200506155606 1
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
177 
U
25 

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 177
87.6%
U 25
 
12.4%

Length

2024-04-18T08:03:56.992149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:57.094905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 177
87.6%
u 25
 
12.4%

데이터갱신일자
Categorical

IMBALANCE 

Distinct33
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2018-08-31 23:59:59.0
170 
2020-09-26 00:23:11.0
 
1
2019-01-08 02:40:00.0
 
1
2019-04-14 02:20:20.0
 
1
2019-05-03 02:40:00.0
 
1
Other values (28)
28 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique32 ?
Unique (%)15.8%

Sample

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

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 170
84.2%
2020-09-26 00:23:11.0 1
 
0.5%
2019-01-08 02:40:00.0 1
 
0.5%
2019-04-14 02:20:20.0 1
 
0.5%
2019-05-03 02:40:00.0 1
 
0.5%
2020-12-17 02:40:00.0 1
 
0.5%
2020-03-13 02:40:00.0 1
 
0.5%
2019-12-29 02:40:00.0 1
 
0.5%
2021-03-19 00:22:59.0 1
 
0.5%
2018-11-15 02:36:02.0 1
 
0.5%
Other values (23) 23
 
11.4%

Length

2024-04-18T08:03:57.197728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 170
42.1%
23:59:59.0 170
42.1%
02:40:00.0 24
 
5.9%
00:23:08.0 2
 
0.5%
2020-02-23 1
 
0.2%
2020-02-28 1
 
0.2%
2019-02-28 1
 
0.2%
02:21:34.0 1
 
0.2%
2020-04-15 1
 
0.2%
2020-05-08 1
 
0.2%
Other values (32) 32
 
7.9%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
202 

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 202
100.0%

Length

2024-04-18T08:03:57.302194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:57.384706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 202
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct179
Distinct (%)95.7%
Missing15
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean335965.61
Minimum325886.5
Maximum356719.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:57.484185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325886.5
5-th percentile328210.69
Q1332712.27
median335513.79
Q3337232.08
95-th percentile346373.88
Maximum356719.23
Range30832.738
Interquartile range (IQR)4519.8126

Descriptive statistics

Standard deviation5668.6346
Coefficient of variation (CV)0.016872663
Kurtosis2.0238993
Mean335965.61
Median Absolute Deviation (MAD)2676.1213
Skewness1.1535026
Sum62825569
Variance32133418
MonotonicityNot monotonic
2024-04-18T08:03:57.602973image/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%
331841.584525 2
 
1.0%
335156.423755 2
 
1.0%
328209.453202 2
 
1.0%
333135.698427 2
 
1.0%
345971.954573 2
 
1.0%
327862.554647 1
 
0.5%
329008.163117 1
 
0.5%
335521.491963 1
 
0.5%
Other values (169) 169
83.7%
(Missing) 15
 
7.4%
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%
328213.561416 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 

Distinct179
Distinct (%)95.7%
Missing15
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean258741.66
Minimum237999.44
Maximum272526.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:57.726597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237999.44
5-th percentile243171.25
Q1255625.67
median260044.13
Q3262533.63
95-th percentile268585.37
Maximum272526.51
Range34527.074
Interquartile range (IQR)6907.9653

Descriptive statistics

Standard deviation7001.9615
Coefficient of variation (CV)0.027061593
Kurtosis1.1774415
Mean258741.66
Median Absolute Deviation (MAD)3693.6845
Skewness-1.0135954
Sum48384690
Variance49027464
MonotonicityNot monotonic
2024-04-18T08:03:57.850893image/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%
255452.921933 2
 
1.0%
259818.122046 2
 
1.0%
251079.280489 2
 
1.0%
255625.666969 2
 
1.0%
269410.738999 2
 
1.0%
250798.385007 1
 
0.5%
254973.175151 1
 
0.5%
251251.800532 1
 
0.5%
Other values (169) 169
83.7%
(Missing) 15
 
7.4%
ValueCountFrequency (%)
237999.437164 1
0.5%
238106.714053 1
0.5%
238349.842802 1
0.5%
239004.505882 1
0.5%
239341.509277 1
0.5%
239494.339675 1
0.5%
239584.975982 1
0.5%
239622.025833 1
0.5%
240780.386054 1
0.5%
242524.285797 1
0.5%
ValueCountFrequency (%)
272526.511063 1
0.5%
269502.747796 1
0.5%
269411.257496 1
0.5%
269410.738999 2
1.0%
269382.179664 1
0.5%
269187.036736 1
0.5%
269153.36154 1
0.5%
269078.525441 1
0.5%
268743.555815 1
0.5%
268216.27041 1
0.5%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
용기.포장지제조업
202 

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 202
100.0%

Length

2024-04-18T08:03:57.994585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:58.080184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 202
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

급수시설구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
129 
상수도전용
72 
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.3613861
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
63.9%
상수도전용 72
35.6%
간이상수도 1
 
0.5%

Length

2024-04-18T08:03:58.173694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:58.272927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
63.9%
상수도전용 72
35.6%
간이상수도 1
 
0.5%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
162 
<NA>
36 
1
 
2
4
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.5346535
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 162
80.2%
<NA> 36
 
17.8%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

Length

2024-04-18T08:03:58.397981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:58.500333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 162
80.2%
na 36
 
17.8%
1 2
 
1.0%
4 1
 
0.5%
3 1
 
0.5%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.6%
Missing36
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean0.27108434
Minimum0
Maximum15
Zeros149
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:58.603741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.4497674
Coefficient of variation (CV)5.3480308
Kurtosis76.824598
Mean0.27108434
Median Absolute Deviation (MAD)0
Skewness8.3822412
Sum45
Variance2.1018255
MonotonicityNot monotonic
2024-04-18T08:03:58.699093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 149
73.8%
1 12
 
5.9%
3 2
 
1.0%
10 1
 
0.5%
2 1
 
0.5%
15 1
 
0.5%
(Missing) 36
 
17.8%
ValueCountFrequency (%)
0 149
73.8%
1 12
 
5.9%
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
 
5.9%
0 149
73.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
159 
<NA>
36 
1
 
5
6
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.5346535
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 159
78.7%
<NA> 36
 
17.8%
1 5
 
2.5%
6 1
 
0.5%
2 1
 
0.5%

Length

2024-04-18T08:03:58.818155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:58.938393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 159
78.7%
na 36
 
17.8%
1 5
 
2.5%
6 1
 
0.5%
2 1
 
0.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)6.6%
Missing36
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean1.2228916
Minimum0
Maximum45
Zeros138
Zeros (%)68.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:03:59.049026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation5.2192842
Coefficient of variation (CV)4.2679861
Kurtosis59.377111
Mean1.2228916
Median Absolute Deviation (MAD)0
Skewness7.3679715
Sum203
Variance27.240927
MonotonicityNot monotonic
2024-04-18T08:03:59.168412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 138
68.3%
2 7
 
3.5%
4 5
 
2.5%
3 3
 
1.5%
5 3
 
1.5%
1 2
 
1.0%
9 2
 
1.0%
7 2
 
1.0%
45 2
 
1.0%
11 1
 
0.5%
(Missing) 36
 
17.8%
ValueCountFrequency (%)
0 138
68.3%
1 2
 
1.0%
2 7
 
3.5%
3 3
 
1.5%
4 5
 
2.5%
5 3
 
1.5%
7 2
 
1.0%
9 2
 
1.0%
10 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
45 2
 
1.0%
11 1
 
0.5%
10 1
 
0.5%
9 2
 
1.0%
7 2
 
1.0%
5 3
1.5%
4 5
2.5%
3 3
1.5%
2 7
3.5%
1 2
 
1.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
149 
자가
28 
임대
25 

Length

Max length4
Median length4
Mean length3.4752475
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> 149
73.8%
자가 28
 
13.9%
임대 25
 
12.4%

Length

2024-04-18T08:03:59.305514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:59.413613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
73.8%
자가 28
 
13.9%
임대 25
 
12.4%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
200 
30000000
 
1
0
 
1

Length

Max length8
Median length4
Mean length4.0049505
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> 200
99.0%
30000000 1
 
0.5%
0 1
 
0.5%

Length

2024-04-18T08:03:59.533032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:59.637545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
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>
200 
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> 200
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

Length

2024-04-18T08:03:59.734886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:03:59.834692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
99.0%
1200000 1
 
0.5%
0 1
 
0.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size334.0 B
False
202 
ValueCountFrequency (%)
False 202
100.0%
2024-04-18T08:03:59.915132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.110198
Minimum0
Maximum907.75
Zeros188
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T08:04:00.005955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.995
Maximum907.75
Range907.75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64.225775
Coefficient of variation (CV)10.511243
Kurtosis196.05665
Mean6.110198
Median Absolute Deviation (MAD)0
Skewness13.909264
Sum1234.26
Variance4124.9502
MonotonicityNot monotonic
2024-04-18T08:04:00.112131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 188
93.1%
64.0 1
 
0.5%
10.0 1
 
0.5%
19.6 1
 
0.5%
19.5 1
 
0.5%
3.0 1
 
0.5%
41.0 1
 
0.5%
45.0 1
 
0.5%
3.35 1
 
0.5%
9.9 1
 
0.5%
Other values (5) 5
 
2.5%
ValueCountFrequency (%)
0.0 188
93.1%
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 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
Missing (%)100.0%
Memory size1.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing202
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_P34100003410000-118-2007-0000120071126<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>
23용기·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>
34용기·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>
45용기·포장지제조업07_22_15_P34100003410000-118-2004-0000120040922<NA>3폐업2폐업20060619<NA><NA><NA>053 5548531130.20700841대구광역시 중구 달성동 0209-0015번지<NA><NA>명성인쇄사20040922000000I2018-08-31 23:59:59.0용기.포장지제조업342602.22917265112.336673용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0002<NA><NA><NA>N0.0<NA><NA><NA>
56용기·포장지제조업07_22_15_P34200003420000-118-2004-0000120040402<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>
67용기·포장지제조업07_22_15_P34200003420000-118-2009-0000120091112<NA>3폐업2폐업20171226<NA><NA><NA>053 981 4735525.68701850대구광역시 동구 지저동 203-6번지대구광역시 동구 팔공로 96-8 (지저동)41037현대아이존20171226101318I2018-08-31 23:59:59.0용기.포장지제조업348103.326642268743.555815용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0003자가<NA><NA>N64.0<NA><NA><NA>
78용기·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>
89용기·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>
910용기·포장지제조업07_22_15_P34200003420000-118-2009-0000220091125<NA>1영업/정상1영업<NA><NA><NA><NA>053 963 6305876.46701330대구광역시 동구 금강동 1144번지대구광역시 동구 금강로 186, A동,B동,C동 1층 (금강동)41095대영프라젠20180208154721I2018-08-31 23:59:59.0용기.포장지제조업356719.234223263628.328553용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0105자가<NA><NA>N10.0<NA><NA><NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
192193용기·포장지제조업07_22_15_P34800003480000-118-2003-0000320030422<NA>3폐업2폐업20161128<NA><NA><NA>053 6170965723.93711858대구광역시 달성군 논공읍 상리 799-20번지 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>
193194용기·포장지제조업07_22_15_P34800003480000-118-2003-0000420031017<NA>3폐업2폐업20151229<NA><NA><NA>053 6169716200.00711844대구광역시 달성군 옥포면 김흥리 1157-1번지대구광역시 달성군 옥포면 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>
194195용기·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>
195196용기·포장지제조업07_22_15_P34800003480000-118-2005-0000120050114<NA>3폐업2폐업20131230<NA><NA><NA>053 6150860475.97711841대구광역시 달성군 옥포면 간경리 640번지 외 1필지대구광역시 달성군 옥포면 비슬로 2309-6 (외 1필지)42972한도피엠씨20050114000000I2018-08-31 23:59:59.0용기.포장지제조업333135.698427255625.666969용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
196197용기·포장지제조업07_22_15_P34800003480000-118-2005-0000320050825<NA>3폐업2폐업20070116<NA><NA><NA>053 633009082.17711836대구광역시 달성군 화원읍 천내리 450-4번지<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>
197198용기·포장지제조업07_22_15_P34800003480000-118-2005-0000420051205<NA>3폐업2폐업20200207<NA><NA><NA>053 637 9466<NA>711836대구광역시 달성군 화원읍 천내리 540-1번지대구광역시 달성군 화원읍 명천로21길 26-442961진산20200221134227U2020-02-23 02:40:00.0용기.포장지제조업335977.991625256719.624531용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
198199용기·포장지제조업07_22_15_P34800003480000-118-2006-0000120060418<NA>3폐업2폐업20150303<NA><NA><NA>053 58468411,950.00711823대구광역시 달성군 하빈면 봉촌리 1044번지 외 1필지대구광역시 달성군 하빈면 하빈남로 438-16 (외 1필지)42905한국프라스틱(주)20060418000000I2018-08-31 23:59:59.0용기.포장지제조업325886.496212263537.964136용기.포장지제조업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
199200용기·포장지제조업07_22_15_P34800003480000-118-2007-0000120071010<NA>3폐업2폐업20191227<NA><NA><NA>053 6159828744.00711891대구광역시 달성군 구지면 고봉리 228-3번지대구광역시 달성군 구지면 국가산단동로42길 3243008(주)코멕스라텍스20200102102616U2020-01-04 02:40:00.0용기.포장지제조업329901.539717239341.509277용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
200201용기·포장지제조업07_22_15_P34800003480000-118-2008-0000120080115<NA>3폐업2폐업20080121<NA><NA><NA>053 5851950<NA>711814대구광역시 달성군 다사읍 세천리 155-1번지 외 1필지<NA><NA>보권산업사20080115145433I2018-08-31 23:59:59.0용기.포장지제조업333207.053297265172.715553용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
201202용기·포장지제조업07_22_15_P34800003480000-118-2008-0000220080321<NA>3폐업2폐업20120306<NA><NA><NA>053 2848005337.50711814대구광역시 달성군 다사읍 세천리 221번지 외 1필지<NA><NA>매직세이브글로벌20080408100714I2018-08-31 23:59:59.0용기.포장지제조업333132.706239265390.957692용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>