Overview

Dataset statistics

Number of variables48
Number of observations259
Missing cells3249
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory105.1 KiB
Average record size in memory415.5 B

Variable types

Numeric10
Categorical19
Text6
Unsupported11
DateTime1
Boolean1

Dataset

Description2021-02-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123102

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
남성종사자수 is highly imbalanced (96.3%)Imbalance
여성종사자수 is highly imbalanced (96.3%)Imbalance
공장사무직종업원수 is highly imbalanced (53.9%)Imbalance
공장생산직종업원수 is highly imbalanced (58.4%)Imbalance
인허가취소일자 has 259 (100.0%) missing valuesMissing
폐업일자 has 114 (44.0%) missing valuesMissing
휴업시작일자 has 259 (100.0%) missing valuesMissing
휴업종료일자 has 259 (100.0%) missing valuesMissing
재개업일자 has 259 (100.0%) missing valuesMissing
소재지전화 has 58 (22.4%) missing valuesMissing
소재지면적 has 67 (25.9%) missing valuesMissing
소재지우편번호 has 7 (2.7%) missing valuesMissing
소재지전체주소 has 3 (1.2%) missing valuesMissing
도로명전체주소 has 67 (25.9%) missing valuesMissing
도로명우편번호 has 68 (26.3%) missing valuesMissing
좌표정보(x) has 8 (3.1%) missing valuesMissing
좌표정보(y) has 8 (3.1%) missing valuesMissing
영업장주변구분명 has 259 (100.0%) missing valuesMissing
등급구분명 has 259 (100.0%) missing valuesMissing
총종업원수 has 259 (100.0%) missing valuesMissing
전통업소지정번호 has 259 (100.0%) missing valuesMissing
전통업소주된음식 has 259 (100.0%) missing valuesMissing
홈페이지 has 259 (100.0%) missing valuesMissing
Unnamed: 47 has 259 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 243 (93.8%) zerosZeros

Reproduction

Analysis started2024-04-16 15:58:32.025907
Analysis finished2024-04-16 15:58:32.923689
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130
Minimum1
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:32.997419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.9
Q165.5
median130
Q3194.5
95-th percentile246.1
Maximum259
Range258
Interquartile range (IQR)129

Descriptive statistics

Standard deviation74.911058
Coefficient of variation (CV)0.57623891
Kurtosis-1.2
Mean130
Median Absolute Deviation (MAD)65
Skewness0
Sum33670
Variance5611.6667
MonotonicityStrictly increasing
2024-04-17T00:58:33.603718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
164 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
Other values (249) 249
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
259 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 259
100.0%

Length

2024-04-17T00:58:33.750930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:33.853417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 259
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
07_22_09_P
259 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_09_P
2nd row07_22_09_P
3rd row07_22_09_P
4th row07_22_09_P
5th row07_22_09_P

Common Values

ValueCountFrequency (%)
07_22_09_P 259
100.0%

Length

2024-04-17T00:58:33.942230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:34.020086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_09_p 259
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3334131.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:34.101146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3340000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation41933.85
Coefficient of variation (CV)0.012577144
Kurtosis-0.8112197
Mean3334131.3
Median Absolute Deviation (MAD)30000
Skewness-0.3090477
Sum8.6354 × 108
Variance1.7584478 × 109
MonotonicityNot monotonic
2024-04-17T00:58:34.203424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3340000 45
17.4%
3390000 35
13.5%
3360000 29
11.2%
3290000 23
8.9%
3330000 21
8.1%
3350000 19
7.3%
3260000 18
 
6.9%
3300000 13
 
5.0%
3400000 11
 
4.2%
3320000 11
 
4.2%
Other values (5) 34
13.1%
ValueCountFrequency (%)
3250000 6
 
2.3%
3260000 18
 
6.9%
3270000 11
 
4.2%
3290000 23
8.9%
3300000 13
 
5.0%
3310000 7
 
2.7%
3320000 11
 
4.2%
3330000 21
8.1%
3340000 45
17.4%
3350000 19
7.3%
ValueCountFrequency (%)
3400000 11
 
4.2%
3390000 35
13.5%
3380000 6
 
2.3%
3370000 4
 
1.5%
3360000 29
11.2%
3350000 19
7.3%
3340000 45
17.4%
3330000 21
8.1%
3320000 11
 
4.2%
3310000 7
 
2.7%

관리번호
Text

UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-17T00:58:34.390243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5698
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

Unique259 ?
Unique (%)100.0%

Sample

1st row3400000-117-2017-00001
2nd row3400000-117-2011-00001
3rd row3400000-117-2008-00002
4th row3390000-117-2018-00001
5th row3390000-117-2015-00002
ValueCountFrequency (%)
3400000-117-2017-00001 1
 
0.4%
3270000-117-2007-00001 1
 
0.4%
3360000-117-2013-00003 1
 
0.4%
3390000-117-2007-00002 1
 
0.4%
3390000-117-2006-00002 1
 
0.4%
3390000-117-2017-00002 1
 
0.4%
3380000-117-2017-00001 1
 
0.4%
3380000-117-2011-00003 1
 
0.4%
3360000-117-2020-00001 1
 
0.4%
3360000-117-2019-00005 1
 
0.4%
Other values (249) 249
96.1%
2024-04-17T00:58:34.677681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2515
44.1%
1 794
 
13.9%
- 777
 
13.6%
3 521
 
9.1%
2 417
 
7.3%
7 318
 
5.6%
4 90
 
1.6%
9 83
 
1.5%
5 69
 
1.2%
6 69
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4921
86.4%
Dash Punctuation 777
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2515
51.1%
1 794
 
16.1%
3 521
 
10.6%
2 417
 
8.5%
7 318
 
6.5%
4 90
 
1.8%
9 83
 
1.7%
5 69
 
1.4%
6 69
 
1.4%
8 45
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 777
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5698
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2515
44.1%
1 794
 
13.9%
- 777
 
13.6%
3 521
 
9.1%
2 417
 
7.3%
7 318
 
5.6%
4 90
 
1.6%
9 83
 
1.5%
5 69
 
1.2%
6 69
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2515
44.1%
1 794
 
13.9%
- 777
 
13.6%
3 521
 
9.1%
2 417
 
7.3%
7 318
 
5.6%
4 90
 
1.6%
9 83
 
1.5%
5 69
 
1.2%
6 69
 
1.2%

인허가일자
Real number (ℝ)

Distinct214
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104314
Minimum19970528
Maximum20201023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:34.813900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970528
5-th percentile20031112
Q120061062
median20090527
Q320141208
95-th percentile20200719
Maximum20201023
Range230495
Interquartile range (IQR)80146.5

Descriptive statistics

Standard deviation51268.442
Coefficient of variation (CV)0.0025501214
Kurtosis-0.83785417
Mean20104314
Median Absolute Deviation (MAD)39417
Skewness0.3585076
Sum5.2070174 × 109
Variance2.6284531 × 109
MonotonicityNot monotonic
2024-04-17T00:58:34.960871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20071127 3
 
1.2%
20111111 3
 
1.2%
20171116 3
 
1.2%
20070427 3
 
1.2%
20110831 3
 
1.2%
20050718 3
 
1.2%
20081223 3
 
1.2%
20200818 3
 
1.2%
20140417 2
 
0.8%
20190115 2
 
0.8%
Other values (204) 231
89.2%
ValueCountFrequency (%)
19970528 1
0.4%
20000806 1
0.4%
20011108 1
0.4%
20030227 1
0.4%
20030324 1
0.4%
20030512 1
0.4%
20030823 1
0.4%
20030826 1
0.4%
20031015 1
0.4%
20031020 1
0.4%
ValueCountFrequency (%)
20201023 1
 
0.4%
20201013 1
 
0.4%
20200909 1
 
0.4%
20200908 1
 
0.4%
20200904 1
 
0.4%
20200902 1
 
0.4%
20200901 1
 
0.4%
20200827 2
0.8%
20200820 1
 
0.4%
20200818 3
1.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
145 
1
114 

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 (%)
3 145
56.0%
1 114
44.0%

Length

2024-04-17T00:58:35.077688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:35.159357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 145
56.0%
1 114
44.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
145 
영업/정상
114 

Length

Max length5
Median length2
Mean length3.3204633
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 145
56.0%
영업/정상 114
44.0%

Length

2024-04-17T00:58:35.279127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:35.371897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 145
56.0%
영업/정상 114
44.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2
145 
1
114 

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 (%)
2 145
56.0%
1 114
44.0%

Length

2024-04-17T00:58:35.475512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:35.555836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 145
56.0%
1 114
44.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
145 
영업
114 

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 145
56.0%
영업 114
44.0%

Length

2024-04-17T00:58:35.642747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:35.721848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 145
56.0%
영업 114
44.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)92.4%
Missing114
Missing (%)44.0%
Infinite0
Infinite (%)0.0%
Mean20135986
Minimum20030114
Maximum20201218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:35.845094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030114
5-th percentile20060461
Q120100601
median20140328
Q320171207
95-th percentile20201006
Maximum20201218
Range171104
Interquartile range (IQR)70606

Descriptive statistics

Standard deviation45657.169
Coefficient of variation (CV)0.0022674415
Kurtosis-0.92216694
Mean20135986
Median Absolute Deviation (MAD)39706
Skewness-0.2345347
Sum2.9197179 × 109
Variance2.0845771 × 109
MonotonicityNot monotonic
2024-04-17T00:58:36.002340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201006 7
 
2.7%
20180921 2
 
0.8%
20160426 2
 
0.8%
20140328 2
 
0.8%
20091216 2
 
0.8%
20200608 2
 
0.8%
20100622 1
 
0.4%
20180719 1
 
0.4%
20200109 1
 
0.4%
20190708 1
 
0.4%
Other values (124) 124
47.9%
(Missing) 114
44.0%
ValueCountFrequency (%)
20030114 1
0.4%
20031210 1
0.4%
20050215 1
0.4%
20050629 1
0.4%
20050805 1
0.4%
20051110 1
0.4%
20060308 1
0.4%
20060421 1
0.4%
20060623 1
0.4%
20070119 1
0.4%
ValueCountFrequency (%)
20201218 1
 
0.4%
20201216 1
 
0.4%
20201125 1
 
0.4%
20201030 1
 
0.4%
20201016 1
 
0.4%
20201006 7
2.7%
20200608 2
 
0.8%
20200603 1
 
0.4%
20200602 1
 
0.4%
20200529 1
 
0.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

소재지전화
Text

MISSING 

Distinct172
Distinct (%)85.6%
Missing58
Missing (%)22.4%
Memory size2.2 KiB
2024-04-17T00:58:36.268541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.358209
Min length7

Characters and Unicode

Total characters2283
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

Unique150 ?
Unique (%)74.6%

Sample

1st row051 714 3322
2nd row051 582 4581
3rd row051 322 2969
4th row051 325 5669
5th row051 645 6360
ValueCountFrequency (%)
051 176
35.7%
070 6
 
1.2%
242 5
 
1.0%
3006 4
 
0.8%
583 4
 
0.8%
257 4
 
0.8%
271 3
 
0.6%
294 3
 
0.6%
941 3
 
0.6%
5280454 3
 
0.6%
Other values (245) 282
57.2%
2024-04-17T00:58:36.645453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 351
15.4%
0 347
15.2%
5 332
14.5%
294
12.9%
2 180
7.9%
3 171
7.5%
4 160
7.0%
6 153
6.7%
8 107
 
4.7%
9 97
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1989
87.1%
Space Separator 294
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 351
17.6%
0 347
17.4%
5 332
16.7%
2 180
9.0%
3 171
8.6%
4 160
8.0%
6 153
7.7%
8 107
 
5.4%
9 97
 
4.9%
7 91
 
4.6%
Space Separator
ValueCountFrequency (%)
294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2283
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 351
15.4%
0 347
15.2%
5 332
14.5%
294
12.9%
2 180
7.9%
3 171
7.5%
4 160
7.0%
6 153
6.7%
8 107
 
4.7%
9 97
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2283
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 351
15.4%
0 347
15.2%
5 332
14.5%
294
12.9%
2 180
7.9%
3 171
7.5%
4 160
7.0%
6 153
6.7%
8 107
 
4.7%
9 97
 
4.2%

소재지면적
Text

MISSING 

Distinct150
Distinct (%)78.1%
Missing67
Missing (%)25.9%
Memory size2.2 KiB
2024-04-17T00:58:36.951498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0729167
Min length3

Characters and Unicode

Total characters974
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

Unique126 ?
Unique (%)65.6%

Sample

1st row150.00
2nd row33.04
3rd row35.70
4th row60.00
5th row37.50
ValueCountFrequency (%)
00 8
 
4.2%
60.00 6
 
3.1%
33.00 5
 
2.6%
30.00 4
 
2.1%
39.60 3
 
1.6%
15.00 3
 
1.6%
50.00 3
 
1.6%
11.88 2
 
1.0%
30.55 2
 
1.0%
11.93 2
 
1.0%
Other values (140) 154
80.2%
2024-04-17T00:58:37.384877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
22.8%
. 192
19.7%
1 98
10.1%
6 76
 
7.8%
5 72
 
7.4%
3 69
 
7.1%
2 57
 
5.9%
8 50
 
5.1%
4 49
 
5.0%
9 44
 
4.5%
Other values (2) 45
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 781
80.2%
Other Punctuation 193
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
28.4%
1 98
12.5%
6 76
 
9.7%
5 72
 
9.2%
3 69
 
8.8%
2 57
 
7.3%
8 50
 
6.4%
4 49
 
6.3%
9 44
 
5.6%
7 44
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 192
99.5%
, 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
22.8%
. 192
19.7%
1 98
10.1%
6 76
 
7.8%
5 72
 
7.4%
3 69
 
7.1%
2 57
 
5.9%
8 50
 
5.1%
4 49
 
5.0%
9 44
 
4.5%
Other values (2) 45
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
22.8%
. 192
19.7%
1 98
10.1%
6 76
 
7.8%
5 72
 
7.4%
3 69
 
7.1%
2 57
 
5.9%
8 50
 
5.1%
4 49
 
5.0%
9 44
 
4.5%
Other values (2) 45
 
4.6%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct137
Distinct (%)54.4%
Missing7
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean611244.52
Minimum600021
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:37.574195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600021
5-th percentile601837.55
Q1604837.5
median612808
Q3617804
95-th percentile618819
Maximum619953
Range19932
Interquartile range (IQR)12966.5

Descriptive statistics

Standard deviation6132.6097
Coefficient of variation (CV)0.010032989
Kurtosis-1.4310321
Mean611244.52
Median Absolute Deviation (MAD)5023
Skewness-0.1899575
Sum1.5403362 × 108
Variance37608902
MonotonicityNot monotonic
2024-04-17T00:58:37.722178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604804 14
 
5.4%
617831 11
 
4.2%
617804 9
 
3.5%
602030 8
 
3.1%
602833 6
 
2.3%
609845 6
 
2.3%
618817 5
 
1.9%
618899 4
 
1.5%
618819 4
 
1.5%
612828 4
 
1.5%
Other values (127) 181
69.9%
(Missing) 7
 
2.7%
ValueCountFrequency (%)
600021 1
0.4%
600804 1
0.4%
600816 2
0.8%
600817 2
0.8%
601010 1
0.4%
601803 1
0.4%
601808 1
0.4%
601812 1
0.4%
601813 1
0.4%
601837 2
0.8%
ValueCountFrequency (%)
619953 1
 
0.4%
619913 3
1.2%
619906 3
1.2%
618899 4
1.5%
618820 1
 
0.4%
618819 4
1.5%
618817 5
1.9%
618816 1
 
0.4%
618815 1
 
0.4%
618812 1
 
0.4%

소재지전체주소
Text

MISSING 

Distinct224
Distinct (%)87.5%
Missing3
Missing (%)1.2%
Memory size2.2 KiB
2024-04-17T00:58:37.983490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length24.539062
Min length17

Characters and Unicode

Total characters6282
Distinct characters199
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)79.7%

Sample

1st row부산광역시 기장군 정관읍 달산리 425
2nd row부산광역시 기장군 정관읍 용수리 449-1번지 A동
3rd row부산광역시 기장군 기장읍 청강리 27-1번지
4th row부산광역시 사상구 엄궁동 512-2번지
5th row부산광역시 사상구 감전동 168-22번지 A동 2층
ValueCountFrequency (%)
부산광역시 256
 
21.2%
사하구 45
 
3.7%
사상구 35
 
2.9%
강서구 29
 
2.4%
부산진구 22
 
1.8%
해운대구 20
 
1.7%
금정구 19
 
1.6%
서구 18
 
1.5%
감천동 16
 
1.3%
암남동 14
 
1.2%
Other values (398) 732
60.7%
2024-04-17T00:58:38.394234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
950
 
15.1%
부 302
 
4.8%
산 296
 
4.7%
동 296
 
4.7%
1 284
 
4.5%
광 262
 
4.2%
시 260
 
4.1%
구 257
 
4.1%
역 256
 
4.1%
지 234
 
3.7%
Other values (189) 2885
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3765
59.9%
Decimal Number 1316
 
20.9%
Space Separator 950
 
15.1%
Dash Punctuation 206
 
3.3%
Close Punctuation 14
 
0.2%
Open Punctuation 14
 
0.2%
Uppercase Letter 13
 
0.2%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 302
 
8.0%
산 296
 
7.9%
동 296
 
7.9%
광 262
 
7.0%
시 260
 
6.9%
구 257
 
6.8%
역 256
 
6.8%
지 234
 
6.2%
번 225
 
6.0%
사 87
 
2.3%
Other values (167) 1290
34.3%
Decimal Number
ValueCountFrequency (%)
1 284
21.6%
2 221
16.8%
3 137
10.4%
4 122
9.3%
5 107
 
8.1%
0 107
 
8.1%
6 100
 
7.6%
9 84
 
6.4%
8 80
 
6.1%
7 74
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
A 6
46.2%
K 2
 
15.4%
W 1
 
7.7%
B 1
 
7.7%
T 1
 
7.7%
P 1
 
7.7%
I 1
 
7.7%
Space Separator
ValueCountFrequency (%)
950
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3765
59.9%
Common 2504
39.9%
Latin 13
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 302
 
8.0%
산 296
 
7.9%
동 296
 
7.9%
광 262
 
7.0%
시 260
 
6.9%
구 257
 
6.8%
역 256
 
6.8%
지 234
 
6.2%
번 225
 
6.0%
사 87
 
2.3%
Other values (167) 1290
34.3%
Common
ValueCountFrequency (%)
950
37.9%
1 284
 
11.3%
2 221
 
8.8%
- 206
 
8.2%
3 137
 
5.5%
4 122
 
4.9%
5 107
 
4.3%
0 107
 
4.3%
6 100
 
4.0%
9 84
 
3.4%
Other values (5) 186
 
7.4%
Latin
ValueCountFrequency (%)
A 6
46.2%
K 2
 
15.4%
W 1
 
7.7%
B 1
 
7.7%
T 1
 
7.7%
P 1
 
7.7%
I 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3765
59.9%
ASCII 2517
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
950
37.7%
1 284
 
11.3%
2 221
 
8.8%
- 206
 
8.2%
3 137
 
5.4%
4 122
 
4.8%
5 107
 
4.3%
0 107
 
4.3%
6 100
 
4.0%
9 84
 
3.3%
Other values (12) 199
 
7.9%
Hangul
ValueCountFrequency (%)
부 302
 
8.0%
산 296
 
7.9%
동 296
 
7.9%
광 262
 
7.0%
시 260
 
6.9%
구 257
 
6.8%
역 256
 
6.8%
지 234
 
6.2%
번 225
 
6.0%
사 87
 
2.3%
Other values (167) 1290
34.3%

도로명전체주소
Text

MISSING 

Distinct174
Distinct (%)90.6%
Missing67
Missing (%)25.9%
Memory size2.2 KiB
2024-04-17T00:58:38.722907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length42
Mean length31.260417
Min length21

Characters and Unicode

Total characters6002
Distinct characters226
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

Unique161 ?
Unique (%)83.9%

Sample

1st row부산광역시 기장군 정관읍 산막길 60, A동
2nd row부산광역시 기장군 기장읍 기장대로 543-8
3rd row부산광역시 사상구 낙동대로776번길 19, 2층 (엄궁동)
4th row부산광역시 사상구 낙동대로1016번길 17, A동 2층 (감전동)
5th row부산광역시 사상구 새벽로 131, 4동 110호 (감전동, 부산산업용재유통상가)
ValueCountFrequency (%)
부산광역시 192
 
16.5%
2층 27
 
2.3%
사하구 25
 
2.2%
사상구 25
 
2.2%
1층 24
 
2.1%
원양로 19
 
1.6%
강서구 19
 
1.6%
해운대구 18
 
1.5%
부산진구 17
 
1.5%
금정구 16
 
1.4%
Other values (435) 780
67.1%
2024-04-17T00:58:39.177164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
971
 
16.2%
1 260
 
4.3%
동 254
 
4.2%
산 240
 
4.0%
부 237
 
3.9%
광 200
 
3.3%
시 200
 
3.3%
역 192
 
3.2%
로 192
 
3.2%
) 191
 
3.2%
Other values (216) 3065
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3444
57.4%
Decimal Number 992
 
16.5%
Space Separator 971
 
16.2%
Close Punctuation 191
 
3.2%
Open Punctuation 191
 
3.2%
Other Punctuation 162
 
2.7%
Dash Punctuation 34
 
0.6%
Uppercase Letter 15
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 254
 
7.4%
산 240
 
7.0%
부 237
 
6.9%
광 200
 
5.8%
시 200
 
5.8%
역 192
 
5.6%
로 192
 
5.6%
구 191
 
5.5%
층 96
 
2.8%
길 87
 
2.5%
Other values (192) 1555
45.2%
Decimal Number
ValueCountFrequency (%)
1 260
26.2%
2 150
15.1%
3 101
 
10.2%
4 87
 
8.8%
0 84
 
8.5%
6 72
 
7.3%
7 70
 
7.1%
5 64
 
6.5%
9 60
 
6.0%
8 44
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
46.7%
B 2
 
13.3%
K 2
 
13.3%
W 1
 
6.7%
P 1
 
6.7%
T 1
 
6.7%
I 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 161
99.4%
: 1
 
0.6%
Space Separator
ValueCountFrequency (%)
971
100.0%
Close Punctuation
ValueCountFrequency (%)
) 191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3444
57.4%
Common 2543
42.4%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 254
 
7.4%
산 240
 
7.0%
부 237
 
6.9%
광 200
 
5.8%
시 200
 
5.8%
역 192
 
5.6%
로 192
 
5.6%
구 191
 
5.5%
층 96
 
2.8%
길 87
 
2.5%
Other values (192) 1555
45.2%
Common
ValueCountFrequency (%)
971
38.2%
1 260
 
10.2%
) 191
 
7.5%
( 191
 
7.5%
, 161
 
6.3%
2 150
 
5.9%
3 101
 
4.0%
4 87
 
3.4%
0 84
 
3.3%
6 72
 
2.8%
Other values (7) 275
 
10.8%
Latin
ValueCountFrequency (%)
A 7
46.7%
B 2
 
13.3%
K 2
 
13.3%
W 1
 
6.7%
P 1
 
6.7%
T 1
 
6.7%
I 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3444
57.4%
ASCII 2558
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
971
38.0%
1 260
 
10.2%
) 191
 
7.5%
( 191
 
7.5%
, 161
 
6.3%
2 150
 
5.9%
3 101
 
3.9%
4 87
 
3.4%
0 84
 
3.3%
6 72
 
2.8%
Other values (14) 290
 
11.3%
Hangul
ValueCountFrequency (%)
동 254
 
7.4%
산 240
 
7.0%
부 237
 
6.9%
광 200
 
5.8%
시 200
 
5.8%
역 192
 
5.6%
로 192
 
5.6%
구 191
 
5.5%
층 96
 
2.8%
길 87
 
2.5%
Other values (192) 1555
45.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct125
Distinct (%)65.4%
Missing68
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean47729.031
Minimum46004
Maximum49478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:39.315926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46150.5
Q146751
median47565
Q348787.5
95-th percentile49452
Maximum49478
Range3474
Interquartile range (IQR)2036.5

Descriptive statistics

Standard deviation1125.2316
Coefficient of variation (CV)0.023575412
Kurtosis-1.2972418
Mean47729.031
Median Absolute Deviation (MAD)858
Skewness0.23243876
Sum9116245
Variance1266146.2
MonotonicityNot monotonic
2024-04-17T00:58:39.504826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49273 12
 
4.6%
47027 9
 
3.5%
46259 6
 
2.3%
46721 4
 
1.5%
48056 4
 
1.5%
48031 3
 
1.2%
49449 3
 
1.2%
46751 3
 
1.2%
49460 3
 
1.2%
46043 3
 
1.2%
Other values (115) 141
54.4%
(Missing) 68
26.3%
ValueCountFrequency (%)
46004 2
 
0.8%
46022 1
 
0.4%
46033 1
 
0.4%
46043 3
1.2%
46064 1
 
0.4%
46078 1
 
0.4%
46080 1
 
0.4%
46221 1
 
0.4%
46222 1
 
0.4%
46259 6
2.3%
ValueCountFrequency (%)
49478 1
 
0.4%
49463 1
 
0.4%
49462 1
 
0.4%
49460 3
1.2%
49455 2
0.8%
49453 1
 
0.4%
49452 2
0.8%
49451 2
0.8%
49449 3
1.2%
49423 1
 
0.4%

사업장명
Text

Distinct217
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-17T00:58:39.811836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.8687259
Min length2

Characters and Unicode

Total characters1779
Distinct characters221
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)72.2%

Sample

1st row(주)성원푸드스토리
2nd row동현푸드시스템
3rd row세흥물류
4th row(주)현대로지스
5th row연승물류
ValueCountFrequency (%)
주식회사 8
 
2.9%
개별화물 6
 
2.2%
개인용달 4
 
1.5%
주)한맥물류 4
 
1.5%
주)영진지엘에스 3
 
1.1%
주)중앙로지스 3
 
1.1%
주)세종물류 3
 
1.1%
용진운수(주 3
 
1.1%
대경유통 2
 
0.7%
거성통운(주 2
 
0.7%
Other values (214) 236
86.1%
2024-04-17T00:58:40.251280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 146
 
8.2%
( 135
 
7.6%
) 135
 
7.6%
물 64
 
3.6%
스 48
 
2.7%
류 48
 
2.7%
동 38
 
2.1%
수 38
 
2.1%
운 37
 
2.1%
지 35
 
2.0%
Other values (211) 1055
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1462
82.2%
Open Punctuation 135
 
7.6%
Close Punctuation 135
 
7.6%
Uppercase Letter 19
 
1.1%
Space Separator 15
 
0.8%
Decimal Number 8
 
0.4%
Other Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 146
 
10.0%
물 64
 
4.4%
스 48
 
3.3%
류 48
 
3.3%
동 38
 
2.6%
수 38
 
2.6%
운 37
 
2.5%
지 35
 
2.4%
통 33
 
2.3%
에 28
 
1.9%
Other values (191) 947
64.8%
Uppercase Letter
ValueCountFrequency (%)
S 3
15.8%
T 3
15.8%
C 3
15.8%
Y 2
10.5%
F 2
10.5%
W 1
 
5.3%
A 1
 
5.3%
G 1
 
5.3%
B 1
 
5.3%
J 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
9 4
50.0%
5 2
25.0%
2 2
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
, 2
40.0%
& 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1462
82.2%
Common 298
 
16.8%
Latin 19
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 146
 
10.0%
물 64
 
4.4%
스 48
 
3.3%
류 48
 
3.3%
동 38
 
2.6%
수 38
 
2.6%
운 37
 
2.5%
지 35
 
2.4%
통 33
 
2.3%
에 28
 
1.9%
Other values (191) 947
64.8%
Latin
ValueCountFrequency (%)
S 3
15.8%
T 3
15.8%
C 3
15.8%
Y 2
10.5%
F 2
10.5%
W 1
 
5.3%
A 1
 
5.3%
G 1
 
5.3%
B 1
 
5.3%
J 1
 
5.3%
Common
ValueCountFrequency (%)
( 135
45.3%
) 135
45.3%
15
 
5.0%
9 4
 
1.3%
. 2
 
0.7%
, 2
 
0.7%
5 2
 
0.7%
2 2
 
0.7%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1462
82.2%
ASCII 317
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 146
 
10.0%
물 64
 
4.4%
스 48
 
3.3%
류 48
 
3.3%
동 38
 
2.6%
수 38
 
2.6%
운 37
 
2.5%
지 35
 
2.4%
통 33
 
2.3%
에 28
 
1.9%
Other values (191) 947
64.8%
ASCII
ValueCountFrequency (%)
( 135
42.6%
) 135
42.6%
15
 
4.7%
9 4
 
1.3%
S 3
 
0.9%
T 3
 
0.9%
C 3
 
0.9%
. 2
 
0.6%
, 2
 
0.6%
Y 2
 
0.6%
Other values (10) 13
 
4.1%

최종수정시점
Real number (ℝ)

Distinct258
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0140031 × 1013
Minimum2.0020226 × 1013
Maximum2.0201218 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:40.394642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020226 × 1013
5-th percentile2.0050609 × 1013
Q12.0090918 × 1013
median2.0150806 × 1013
Q32.0190369 × 1013
95-th percentile2.0201013 × 1013
Maximum2.0201218 × 1013
Range1.8099216 × 1011
Interquartile range (IQR)9.9451018 × 1010

Descriptive statistics

Standard deviation5.3002103 × 1010
Coefficient of variation (CV)0.0026316793
Kurtosis-1.0538344
Mean2.0140031 × 1013
Median Absolute Deviation (MAD)4.020495 × 1010
Skewness-0.47723536
Sum5.216268 × 1015
Variance2.8092229 × 1021
MonotonicityNot monotonic
2024-04-17T00:58:40.545317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050824000000 2
 
0.8%
20201125154729 1
 
0.4%
20130412140148 1
 
0.4%
20180130133507 1
 
0.4%
20171204154927 1
 
0.4%
20200508163216 1
 
0.4%
20180111111602 1
 
0.4%
20140612125202 1
 
0.4%
20200910153221 1
 
0.4%
20190417165524 1
 
0.4%
Other values (248) 248
95.8%
ValueCountFrequency (%)
20020226000000 1
0.4%
20030324000000 1
0.4%
20030512000000 1
0.4%
20031020000000 1
0.4%
20031021000000 1
0.4%
20031027000000 1
0.4%
20031121000000 1
0.4%
20040217000000 1
0.4%
20040315000000 1
0.4%
20040709000000 1
0.4%
ValueCountFrequency (%)
20201218162009 1
0.4%
20201218155941 1
0.4%
20201218113956 1
0.4%
20201216143240 1
0.4%
20201207151314 1
0.4%
20201125154729 1
0.4%
20201122130532 1
0.4%
20201113140448 1
0.4%
20201030144538 1
0.4%
20201023134009 1
0.4%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
I
192 
U
67 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 192
74.1%
U 67
 
25.9%

Length

2024-04-17T00:58:40.669275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:40.767316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 192
74.1%
u 67
 
25.9%

데이터갱신일자
Date

Distinct64
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-20 02:40:00
2024-04-17T00:58:40.862568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:58:40.999264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
259 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 259
100.0%

Length

2024-04-17T00:58:41.118210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:41.196995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 259
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)76.1%
Missing8
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean385091.99
Minimum367454.56
Maximum403920.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:41.295881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367454.56
5-th percentile374001.78
Q1380222.85
median383539.6
Q3389910.3
95-th percentile396079.3
Maximum403920.39
Range36465.83
Interquartile range (IQR)9687.4526

Descriptive statistics

Standard deviation7005.028
Coefficient of variation (CV)0.018190532
Kurtosis0.51919974
Mean385091.99
Median Absolute Deviation (MAD)4217.9513
Skewness0.11660773
Sum96658090
Variance49070417
MonotonicityNot monotonic
2024-04-17T00:58:41.425330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
379764.389679699 9
 
3.5%
383518.040204105 6
 
2.3%
393054.070020468 5
 
1.9%
367454.564232222 5
 
1.9%
381454.594898065 4
 
1.5%
393233.931123062 3
 
1.2%
382859.036470648 3
 
1.2%
393564.154856479 3
 
1.2%
382852.793754942 3
 
1.2%
380205.138152822 3
 
1.2%
Other values (181) 207
79.9%
(Missing) 8
 
3.1%
ValueCountFrequency (%)
367454.564232222 5
1.9%
368098.86127099 1
 
0.4%
368677.63451413 1
 
0.4%
369324.667538937 1
 
0.4%
369510.064865473 2
 
0.8%
372337.596274806 1
 
0.4%
372994.73172451 1
 
0.4%
373017.818475368 1
 
0.4%
374985.749975672 1
 
0.4%
376683.252769612 1
 
0.4%
ValueCountFrequency (%)
403920.394694604 1
 
0.4%
403400.70176596 3
1.2%
403232.866658086 1
 
0.4%
401995.797588582 1
 
0.4%
401928.416182264 1
 
0.4%
400921.195390687 1
 
0.4%
398687.383627252 1
 
0.4%
398663.970066616 1
 
0.4%
398128.076450259 1
 
0.4%
397438.831338517 1
 
0.4%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)76.1%
Missing8
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean185810.63
Minimum174611.96
Maximum206599.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:41.895395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174611.96
5-th percentile175767.56
Q1179352.77
median185333.75
Q3190943.42
95-th percentile198185.16
Maximum206599.78
Range31987.822
Interquartile range (IQR)11590.647

Descriptive statistics

Standard deviation7013.7251
Coefficient of variation (CV)0.037746631
Kurtosis-0.39307089
Mean185810.63
Median Absolute Deviation (MAD)5664.4271
Skewness0.4220416
Sum46638467
Variance49192340
MonotonicityNot monotonic
2024-04-17T00:58:42.022781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185333.750017244 9
 
3.5%
175580.741380931 6
 
2.3%
194090.700712147 5
 
1.9%
179343.014764116 5
 
1.9%
177164.789486544 4
 
1.5%
192684.487637586 3
 
1.2%
177962.876339211 3
 
1.2%
189232.298979587 3
 
1.2%
177505.422460379 3
 
1.2%
176522.453427325 3
 
1.2%
Other values (181) 207
79.9%
(Missing) 8
 
3.1%
ValueCountFrequency (%)
174611.961458235 1
 
0.4%
174626.658689664 2
 
0.8%
175140.099221406 1
 
0.4%
175274.144961403 1
 
0.4%
175469.439982525 1
 
0.4%
175580.741380931 6
2.3%
175767.563913389 2
 
0.8%
175944.196657226 2
 
0.8%
176183.105551719 1
 
0.4%
176522.453427325 3
1.2%
ValueCountFrequency (%)
206599.783800745 1
 
0.4%
206240.13184752 1
 
0.4%
204872.34472323 1
 
0.4%
203653.574237789 1
 
0.4%
203648.795712099 1
 
0.4%
198866.796058539 3
1.2%
198690.393083898 1
 
0.4%
198690.232287766 1
 
0.4%
198457.294596131 1
 
0.4%
198403.97184169 1
 
0.4%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
259 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 259
100.0%

Length

2024-04-17T00:58:42.132864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:42.226396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 259
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
1

Length

Max length4
Median length4
Mean length3.988417
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 258
99.6%
0 1
 
0.4%

Length

2024-04-17T00:58:42.319130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:42.414538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
99.6%
0 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
1

Length

Max length4
Median length4
Mean length3.988417
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 258
99.6%
0 1
 
0.4%

Length

2024-04-17T00:58:42.511259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:42.601749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
99.6%
0 1
 
0.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
230 
상수도전용
29 

Length

Max length5
Median length4
Mean length4.1119691
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
88.8%
상수도전용 29
 
11.2%

Length

2024-04-17T00:58:42.696259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:42.800873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
88.8%
상수도전용 29
 
11.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

본사종업원수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
165 
<NA>
92 
96
 
1
1
 
1

Length

Max length4
Median length1
Mean length2.0694981
Min length1

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 165
63.7%
<NA> 92
35.5%
96 1
 
0.4%
1 1
 
0.4%

Length

2024-04-17T00:58:42.906677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:42.999280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 165
63.7%
na 92
35.5%
96 1
 
0.4%
1 1
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
160 
<NA>
90 
1
 
4
2
 
2
3
 
2

Length

Max length4
Median length1
Mean length2.042471
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 160
61.8%
<NA> 90
34.7%
1 4
 
1.5%
2 2
 
0.8%
3 2
 
0.8%
6 1
 
0.4%

Length

2024-04-17T00:58:43.110321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:43.216666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 160
61.8%
na 90
34.7%
1 4
 
1.5%
2 2
 
0.8%
3 2
 
0.8%
6 1
 
0.4%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
165 
<NA>
93 
2
 
1

Length

Max length4
Median length1
Mean length2.0772201
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 165
63.7%
<NA> 93
35.9%
2 1
 
0.4%

Length

2024-04-17T00:58:43.325249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:43.416637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 165
63.7%
na 93
35.9%
2 1
 
0.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
163 
<NA>
92 
3
 
1
11
 
1
4
 
1

Length

Max length4
Median length1
Mean length2.0694981
Min length1

Unique

Unique4 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 163
62.9%
<NA> 92
35.5%
3 1
 
0.4%
11 1
 
0.4%
4 1
 
0.4%
1 1
 
0.4%

Length

2024-04-17T00:58:43.515109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:43.627303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 163
62.9%
na 92
35.5%
3 1
 
0.4%
11 1
 
0.4%
4 1
 
0.4%
1 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
147 
자가
69 
임대
43 

Length

Max length4
Median length4
Mean length3.1351351
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
56.8%
자가 69
26.6%
임대 43
 
16.6%

Length

2024-04-17T00:58:43.741823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:43.870186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
56.8%
자가 69
26.6%
임대 43
 
16.6%

보증액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
219 
0
40 

Length

Max length4
Median length4
Mean length3.5366795
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
84.6%
0 40
 
15.4%

Length

2024-04-17T00:58:43.982977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:44.067532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
84.6%
0 40
 
15.4%

월세액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
219 
0
40 

Length

Max length4
Median length4
Mean length3.5366795
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
84.6%
0 40
 
15.4%

Length

2024-04-17T00:58:44.161068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:44.272808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
84.6%
0 40
 
15.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size391.0 B
False
259 
ValueCountFrequency (%)
False 259
100.0%
2024-04-17T00:58:44.359140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6617375
Minimum0
Maximum1204
Zeros243
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-17T00:58:44.434773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19.5
Maximum1204
Range1204
Interquartile range (IQR)0

Descriptive statistics

Standard deviation76.54052
Coefficient of variation (CV)9.9899691
Kurtosis233.93138
Mean7.6617375
Median Absolute Deviation (MAD)0
Skewness15.000785
Sum1984.39
Variance5858.4513
MonotonicityNot monotonic
2024-04-17T00:58:44.534595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 243
93.8%
19.0 2
 
0.8%
49.5 2
 
0.8%
150.0 1
 
0.4%
33.04 1
 
0.4%
36.55 1
 
0.4%
45.0 1
 
0.4%
43.3 1
 
0.4%
16.5 1
 
0.4%
24.0 1
 
0.4%
Other values (5) 5
 
1.9%
ValueCountFrequency (%)
0.0 243
93.8%
16.5 1
 
0.4%
19.0 2
 
0.8%
24.0 1
 
0.4%
26.4 1
 
0.4%
33.0 1
 
0.4%
33.04 1
 
0.4%
36.55 1
 
0.4%
39.6 1
 
0.4%
43.3 1
 
0.4%
ValueCountFrequency (%)
1204.0 1
0.4%
196.0 1
0.4%
150.0 1
0.4%
49.5 2
0.8%
45.0 1
0.4%
43.3 1
0.4%
39.6 1
0.4%
36.55 1
0.4%
33.04 1
0.4%
33.0 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing259
Missing (%)100.0%
Memory size2.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품운반업07_22_09_P34000003400000-117-2017-0000120170822<NA>3폐업2폐업20201125<NA><NA><NA>051 714 3322150.00<NA>부산광역시 기장군 정관읍 달산리 425<NA><NA>(주)성원푸드스토리20201125154729U2020-11-27 02:40:00.0식품운반업398663.970067203653.574238식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N150.0<NA><NA><NA><NA>
12식품운반업07_22_09_P34000003400000-117-2011-0000120110831<NA>3폐업2폐업20180921<NA><NA><NA>051 582 458133.04<NA>부산광역시 기장군 정관읍 용수리 449-1번지 A동부산광역시 기장군 정관읍 산막길 60, A동46004동현푸드시스템20180927112056U2018-09-27 23:59:59.0식품운반업397438.831339206240.131848식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N33.04<NA><NA><NA><NA>
23식품운반업07_22_09_P34000003400000-117-2008-0000220081201<NA>3폐업2폐업20180921<NA><NA><NA><NA><NA>619906부산광역시 기장군 기장읍 청강리 27-1번지부산광역시 기장군 기장읍 기장대로 543-846064세흥물류20180927113118U2018-09-27 23:59:59.0식품운반업401995.797589196084.044896식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품운반업07_22_09_P33900003390000-117-2018-0000120180330<NA>3폐업2폐업20190315<NA><NA><NA>051 322 296935.70617828부산광역시 사상구 엄궁동 512-2번지부산광역시 사상구 낙동대로776번길 19, 2층 (엄궁동)47039(주)현대로지스20190315150748U2019-03-17 02:40:00.0식품운반업379707.209193182943.722265식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
45식품운반업07_22_09_P33900003390000-117-2015-0000220151019<NA>3폐업2폐업20170424<NA><NA><NA><NA>60.00617804부산광역시 사상구 감전동 168-22번지 A동 2층부산광역시 사상구 낙동대로1016번길 17, A동 2층 (감전동)47027연승물류20170424144227I2018-08-31 23:59:59.0식품운반업379764.38968185333.750017식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
56식품운반업07_22_09_P33900003390000-117-2015-0000120150604<NA>3폐업2폐업20150619<NA><NA><NA><NA><NA>617721부산광역시 사상구 감전동 152-2번지 부산산업용재유통상가 4동 110호부산광역시 사상구 새벽로 131, 4동 110호 (감전동, 부산산업용재유통상가)46988용달20150604100012I2018-08-31 23:59:59.0식품운반업380482.767624185582.274948식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
67식품운반업07_22_09_P33900003390000-117-2014-0000120140326<NA>3폐업2폐업20150427<NA><NA><NA>051 325 566937.50617804부산광역시 사상구 감전동 168-22번지 1층부산광역시 사상구 낙동대로1016번길 17, 1층 (감전동)47027천하특수20140514204808I2018-08-31 23:59:59.0식품운반업379764.38968185333.750017식품운반업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품운반업07_22_09_P33900003390000-117-2012-0000120121123<NA>3폐업2폐업20151210<NA><NA><NA>051 645 636022.30617831부산광역시 사상구 엄궁동 651-14번지 2층부산광역시 사상구 강변대로 458 (엄궁동)47033대상베스트코 주식회사20121220111411I2018-08-31 23:59:59.0식품운반업378882.565675182515.834086식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
89식품운반업07_22_09_P33900003390000-117-2011-0000220110822<NA>3폐업2폐업20150820<NA><NA><NA>070 8169400088.20617831부산광역시 사상구 엄궁동 651-39번지부산광역시 사상구 강변대로456번길 16-8 (엄궁동)47033(주)아이온에프앤지20130115093032I2018-08-31 23:59:59.0식품운반업378870.066218182430.977571식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
910식품운반업07_22_09_P33900003390000-117-2011-0000120110314<NA>3폐업2폐업20150121<NA><NA><NA>051 316334124.00617838부산광역시 사상구 주례동 616-4번지부산광역시 사상구 주례로139번길 8 (주례동)47017농업회사법인(주)푸드아이20140415133022I2018-08-31 23:59:59.0식품운반업382304.20248184696.810796식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
249250식품운반업07_22_09_P32600003260000-117-2011-0000220111205<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 900039.20602030부산광역시 서구 암남동 735 (2층)부산광역시 서구 원양로 189 (암남동)49273(주)이스턴웰스20200729153515U2020-07-31 02:40:00.0식품운반업383161.450357176183.105552식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
250251식품운반업07_22_09_P32600003260000-117-2011-0000120110831<NA>1영업/정상1영업<NA><NA><NA><NA>051 256 596019.60602030부산광역시 서구 암남동 716번지 냉장인터불고2공장 7층부산광역시 서구 원양로 125, 7층 (암남동, 냉장인터불고2공장)49273(주)푸드엔씨20161108142159I2018-08-31 23:59:59.0식품운반업383539.60243175767.563913식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
251252식품운반업07_22_09_P32600003260000-117-2009-0000120090527<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 688633.00602833부산광역시 서구 암남동 620-29번지 원양프라자 902호부산광역시 서구 원양로 105, 9층 902호 (암남동, 원양프라자)49273(주)한맥물류20170830102943I2018-08-31 23:59:59.0식품운반업383518.040204175580.741381식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
252253식품운반업07_22_09_P32600003260000-117-2007-0000220071127<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 283336.30602030부산광역시 서구 암남동 712번지 동영빌딩 304호부산광역시 서구 원양로 310, 304호 (암남동, 동영빌딩)49273(주)해인지엘에스20150817153006I2018-08-31 23:59:59.0식품운반업382890.650587177336.22369식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
253254식품운반업07_22_09_P32600003260000-117-2007-0000420071120<NA>1영업/정상1영업<NA><NA><NA><NA>051 203 347423.80602030부산광역시 서구 암남동 753번지 동양글로벌냉장 5층부산광역시 서구 원양로 243, 5층 (암남동, 동양글로벌냉장)49273백두냉동운수(주)20190219113531U2019-02-21 02:40:00.0식품운반업382929.6612176610.19321식품운반업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
254255식품운반업07_22_09_P32600003260000-117-2005-0000120050907<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 299316.52602833부산광역시 서구 암남동 620-29번지 원양프라자 902호부산광역시 서구 원양로 105, 9층 902호 (암남동, 원양프라자)49273(주)한맥로지스틱스20200115154114U2020-01-17 02:40:00.0식품운반업383518.040204175580.741381식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
255256식품운반업07_22_09_P32600003260000-117-2004-0000120040312<NA>1영업/정상1영업<NA><NA><NA><NA>051 257333130.00602030부산광역시 서구 암남동 712번지부산광역시 서구 원양로 310, 304호 (암남동)49273(주)삼일물류20171206134428I2018-08-31 23:59:59.0식품운반업382890.650587177336.22369식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
256257식품운반업07_22_09_P32500003250000-117-2020-0000120200708<NA>1영업/정상1영업<NA><NA><NA><NA>051 463 321130.00600817부산광역시 중구 중앙동4가 81-7부산광역시 중구 충장대로9번길 35-1, 3층 (중앙동4가)48937동아통운(주)20200708095342I2020-07-10 00:23:16.0식품운반업385731.290616180730.387826식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
257258식품운반업07_22_09_P32500003250000-117-2014-0000120140210<NA>1영업/정상1영업<NA><NA><NA><NA>051 442 203885.93600817부산광역시 중구 중앙동4가 80-16번지 3층 306호부산광역시 중구 충장대로9번길 28, 3층 306호 (중앙동4가)48937합자회사 동신기업사20180806154758I2018-08-31 23:59:59.0식품운반업385730.223219180633.142129식품운반업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
258259식품운반업07_22_09_P32500003250000-117-2006-0000120060411<NA>1영업/정상1영업<NA><NA><NA><NA>051 2572471100.11600021부산광역시 중구 동광동1가 7번지 우리은행 304호부산광역시 중구 광복로97번길 11, 304호 (동광동1가, 우리은행)48952(주)에어앤씨카고20120207161656I2018-08-31 23:59:59.0식품운반업385498.102705179739.963317식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>